WorldWideScience

Sample records for spatially-explicit individual-based model

  1. Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

    Science.gov (United States)

    Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

    2017-12-01

    In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results

  2. CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

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    Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

    2016-01-01

    1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

  3. Modeling Behavior by Coastal River Otter (Lontra Canadensis in Response to Prey Availability in Prince William Sound, Alaska: A Spatially-Explicit Individual-Based Approach.

    Directory of Open Access Journals (Sweden)

    Shannon E Albeke

    Full Text Available Effects of climate change on animal behavior and cascading ecosystem responses are rarely evaluated. In coastal Alaska, social river otters (Lontra Canadensis, largely males, cooperatively forage on schooling fish and use latrine sites to communicate group associations and dominance. Conversely, solitary otters, mainly females, feed on intertidal-demersal fish and display mutual avoidance via scent marking. This behavioral variability creates "hotspots" of nutrient deposition and affects plant productivity and diversity on the terrestrial landscape. Because the abundance of schooling pelagic fish is predicted to decline with climate change, we developed a spatially-explicit individual-based model (IBM of otter behavior and tested six scenarios based on potential shifts to distribution patterns of schooling fish. Emergent patterns from the IBM closely mimicked observed otter behavior and landscape use in the absence of explicit rules of intraspecific attraction or repulsion. Model results were most sensitive to rules regarding spatial memory and activity state following an encounter with a fish school. With declining availability of schooling fish, the number of social groups and the time simulated otters spent in the company of conspecifics declined. Concurrently, model results suggested an elevation of defecation rate, a 25% increase in nitrogen transport to the terrestrial landscape, and significant changes to the spatial distribution of "hotspots" with declines in schooling fish availability. However, reductions in availability of schooling fish could lead to declines in otter density over time.

  4. Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

    Science.gov (United States)

    2011-01-01

    Background Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. Methods We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. Results The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. Conclusions We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficial. PMID:21554680

  5. Spatially explicit modelling of cholera epidemics

    Science.gov (United States)

    Finger, F.; Bertuzzo, E.; Mari, L.; Knox, A. C.; Gatto, M.; Rinaldo, A.

    2013-12-01

    Epidemiological models can provide crucial understanding about the dynamics of infectious diseases. Possible applications range from real-time forecasting and allocation of health care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. We apply a spatially explicit model to the cholera epidemic that struck Haiti in October 2010 and is still ongoing. The dynamics of susceptibles as well as symptomatic and asymptomatic infectives are modelled at the scale of local human communities. Dissemination of Vibrio cholerae through hydrological transport and human mobility along the road network is explicitly taken into account, as well as the effect of rainfall as a driver of increasing disease incidence. The model is calibrated using a dataset of reported cholera cases. We further model the long term impact of several types of interventions on the disease dynamics by varying parameters appropriately. Key epidemiological mechanisms and parameters which affect the efficiency of treatments such as antibiotics are identified. Our results lead to conclusions about the influence of different intervention strategies on the overall epidemiological dynamics.

  6. Spatially explicit modeling in ecology: A review

    Science.gov (United States)

    DeAngelis, Donald L.; Yurek, Simeon

    2017-01-01

    The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

  7. Integrating remote sensing and spatially explicit epidemiological modeling

    Science.gov (United States)

    Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea

    2015-04-01

    Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.

  8. CDPOP: A spatially explicit cost distance population genetics program

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    Erin L. Landguth; S. A. Cushman

    2010-01-01

    Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

  9. A spatially explicit scenario-driven model of adaptive capacity to global change in Europe

    NARCIS (Netherlands)

    Acosta, L.; Klein, R.J.T.; Reidsma, P.; Metzger, M.J.; Rounsevell, M.D.A.; Leemans, R.

    2013-01-01

    Traditional impact models combine exposure in the form of scenarios and sensitivity in the form of parameters, providing potential impacts of global change as model outputs. However, adaptive capacity is rarely addressed in these models. This paper presents the first spatially explicit

  10. DEFINING RECOVERY GOALS AND STRATEGIES FOR ENDANGERED SPECIES USING SPATIALLY-EXPLICIT POPULATION MODELS

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    We used a spatially explicit population model of wolves (Canis lupus) to propose a framework for defining rangewide recovery priorities and finer-scale strategies for regional reintroductions. The model predicts that Yellowstone and central Idaho, where wolves have recently been ...

  11. Scaling-up spatially-explicit ecological models using graphics processors

    NARCIS (Netherlands)

    Koppel, Johan van de; Gupta, Rohit; Vuik, Cornelis

    2011-01-01

    How the properties of ecosystems relate to spatial scale is a prominent topic in current ecosystem research. Despite this, spatially explicit models typically include only a limited range of spatial scales, mostly because of computing limitations. Here, we describe the use of graphics processors to

  12. Spatially explicit models, generalized reproduction numbers and the prediction of patterns of waterborne disease

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    Rinaldo, A.; Gatto, M.; Mari, L.; Casagrandi, R.; Righetto, L.; Bertuzzo, E.; Rodriguez-Iturbe, I.

    2012-12-01

    Metacommunity and individual-based theoretical models are studied in the context of the spreading of infections of water-borne diseases along the ecological corridors defined by river basins and networks of human mobility. The overarching claim is that mathematical models can indeed provide predictive insight into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. To support the claim, we examine the ex-post reliability of published predictions of the 2010-2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. For each modeled epidemic trajectory, it is assessed how well predictions reproduced the observed spatial and temporal features of the outbreak to date. The impact of different approaches is considered to the modeling of the spatial spread of V. cholera, the mechanics of cholera transmission and in accounting for the dynamics of susceptible and infected individuals within different local human communities. A generalized model for Haitian epidemic cholera and the related uncertainty is thus constructed and applied to the year-long dataset of reported cases now available. Specific emphasis will be dedicated to models of human mobility, a fundamental infection mechanism. Lessons learned and open issues are discussed and placed in perspective, supporting the conclusion that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control. Although explicit spatial modeling is made routinely possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is

  13. A spatially explicit model for an Allee effect: why wolves recolonize so slowly in Greater Yellowstone.

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    Hurford, Amy; Hebblewhite, Mark; Lewis, Mark A

    2006-11-01

    A reduced probability of finding mates at low densities is a frequently hypothesized mechanism for a component Allee effect. At low densities dispersers are less likely to find mates and establish new breeding units. However, many mathematical models for an Allee effect do not make a distinction between breeding group establishment and subsequent population growth. Our objective is to derive a spatially explicit mathematical model, where dispersers have a reduced probability of finding mates at low densities, and parameterize the model for wolf recolonization in the Greater Yellowstone Ecosystem (GYE). In this model, only the probability of establishing new breeding units is influenced by the reduced probability of finding mates at low densities. We analytically and numerically solve the model to determine the effect of a decreased probability in finding mates at low densities on population spread rate and density. Our results suggest that a reduced probability of finding mates at low densities may slow recolonization rate.

  14. Spatially-Explicit Bayesian Information Entropy Metrics for Calibrating Landscape Transformation Models

    Directory of Open Access Journals (Sweden)

    Kostas Alexandridis

    2013-06-01

    Full Text Available Assessing spatial model performance often presents challenges related to the choice and suitability of traditional statistical methods in capturing the true validity and dynamics of the predicted outcomes. The stochastic nature of many of our contemporary spatial models of land use change necessitate the testing and development of new and innovative methodologies in statistical spatial assessment. In many cases, spatial model performance depends critically on the spatially-explicit prior distributions, characteristics, availability and prevalence of the variables and factors under study. This study explores the statistical spatial characteristics of statistical model assessment of modeling land use change dynamics in a seven-county study area in South-Eastern Wisconsin during the historical period of 1963–1990. The artificial neural network-based Land Transformation Model (LTM predictions are used to compare simulated with historical land use transformations in urban/suburban landscapes. We introduce a range of Bayesian information entropy statistical spatial metrics for assessing the model performance across multiple simulation testing runs. Bayesian entropic estimates of model performance are compared against information-theoretic stochastic entropy estimates and theoretically-derived accuracy assessments. We argue for the critical role of informational uncertainty across different scales of spatial resolution in informing spatial landscape model assessment. Our analysis reveals how incorporation of spatial and landscape information asymmetry estimates can improve our stochastic assessments of spatial model predictions. Finally our study shows how spatially-explicit entropic classification accuracy estimates can work closely with dynamic modeling methodologies in improving our scientific understanding of landscape change as a complex adaptive system and process.

  15. A Risk Assessment Example for Soil Invertebrates Using Spatially Explicit Agent-Based Models

    DEFF Research Database (Denmark)

    Reed, Melissa; Alvarez, Tania; Chelinho, Sonia

    2016-01-01

    Current risk assessment methods for measuring the toxicity of plant protection products (PPPs) on soil invertebrates use standardized laboratory conditions to determine acute effects on mortality and sublethal effects on reproduction. If an unacceptable risk is identified at the lower tier...... population models for ubiquitous soil invertebrates (collembolans and earthworms) as refinement options in current risk assessment. Both are spatially explicit agent-based models (ABMs), incorporating individual and landscape variability. The models were used to provide refined risk assessments for different...... application scenarios of a hypothetical pesticide applied to potato crops (full-field spray onto the soil surface [termed “overall”], in-furrow, and soil-incorporated pesticide applications). In the refined risk assessment, the population models suggest that soil invertebrate populations would likely recover...

  16. Predicting continental-scale patterns of bird species richness with spatially explicit models

    DEFF Research Database (Denmark)

    Rahbek, Carsten; Gotelli, Nicholas J; Colwell, Robert K

    2007-01-01

    the extraordinary diversity of avian species in the montane tropics, the most species-rich region on Earth. Our findings imply that correlative climatic models substantially underestimate the importance of historical factors and small-scale niche-driven assembly processes in shaping contemporary species-richness......The causes of global variation in species richness have been debated for nearly two centuries with no clear resolution in sight. Competing hypotheses have typically been evaluated with correlative models that do not explicitly incorporate the mechanisms responsible for biotic diversity gradients....... Here, we employ a fundamentally different approach that uses spatially explicit Monte Carlo models of the placement of cohesive geographical ranges in an environmentally heterogeneous landscape. These models predict species richness of endemic South American birds (2248 species) measured...

  17. [Application of spatially explicit landscape model in soil loss study in Huzhong area].

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    Xu, Chonggang; Hu, Yuanman; Chang, Yu; Li, Xiuzhen; Bu, Renchang; He, Hongshi; Leng, Wenfang

    2004-10-01

    Universal Soil Loss Equation (USLE) has been widely used to estimate the average annual soil loss. In most of the previous work on soil loss evaluation on forestland, cover management factor was calculated from the static forest landscape. The advent of spatially explicit forest landscape model in the last decade, which explicitly simulates the forest succession dynamics under natural and anthropogenic disturbances (fire, wind, harvest and so on) on heterogeneous landscape, makes it possible to take into consideration the change of forest cover, and to dynamically simulate the soil loss in different year (e.g. 10 years and 20 years after current year). In this study, we linked a spatially explicit landscape model (LANDIS) with USLE to simulate the soil loss dynamics under two scenarios: fire and no harvest, fire and harvest. We also simulated the soil loss with no fire and no harvest as a control. The results showed that soil loss varied periodically with simulation year, and the amplitude of change was the lowest under the control scenario and the highest under the fire and no harvest scenario. The effect of harvest on soil loss could not be easily identified on the map; however, the cumulative effect of harvest on soil loss was larger than that of fire. Decreasing the harvest area and the percent of bare soil increased by harvest could significantly reduce soil loss, but had no significant effects on the dynamic of soil loss. Although harvest increased the annual soil loss, it tended to decrease the variability of soil loss between different simulation years.

  18. Individual based model of slug population and spatial dynamics

    NARCIS (Netherlands)

    Choi, Y.H.; Bohan, D.A.; Potting, R.P.J.; Semenov, M.A.; Glen, D.M.

    2006-01-01

    The slug, Deroceras reticulatum, is one of the most important pests of agricultural and horticultural crops in UK and Europe. In this paper, a spatially explicit individual based model (IbM) is developed to study the dynamics of a population of D. reticulatum. The IbM establishes a virtual field

  19. Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

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    Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

    2005-01-01

    Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

  20. Cholera in the Lake Kivu region (DRC): Integrating remote sensing and spatially explicit epidemiological modeling

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    Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

    2014-07-01

    Mathematical models of cholera dynamics can not only help in identifying environmental drivers and processes that influence disease transmission, but may also represent valuable tools for the prediction of the epidemiological patterns in time and space as well as for the allocation of health care resources. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. They have been ravaging the shore of Lake Kivu in the east of the country repeatedly during the last decades. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of the lake. Remotely sensed data sets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multiyear data set of reported cholera cases. The best fourteen models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via proper cross validation. Among these, the one accounting for seasonality, El Niño Southern Oscillation, precipitation and human mobility outperforms the others in cross validation. Some drivers (such as human mobility and rainfall) are retained only by a few models, possibly indicating that the mechanisms through which they influence cholera dynamics in the area will have to be investigated further.

  1. A stage-structured, spatially explicit migration model for Myotis bats: mortality location affects system dynamics

    Science.gov (United States)

    Erickson, Richard A.; Thogmartin, Wayne E.; Russell, Robin E.; Diffendorfer, James E.; Szymanski, Jennifer A.

    2014-01-01

    Bats are ecologically and economically important species because they consume insects, transport nutrients, and pollinate flowers.  Many species of bats, including those in the Myotis genus, are facing population decline and increased extinction risk.  Despite these conservation concerns, few models exist for providing insight into the population dynamics of bats in a spatially explicit context.  We developed a model for bats by considering the stage-structured colonial life history of Myotis bats with their annual migration behavior.  This model provided insight into network dynamics.  We specifically focused on two Myotis species living in the eastern United States: the Indiana bat (M. sodalis), which is a Federally listed endangered species, and the little brown bat (M. lucifugus), which is under consideration for listing as an endangered species.  We found that multiple equilibria exist for the local, migratory subpopulations even though the total population was constant.  These equilibria suggest the location and magnitude of stressors such as White-nose Syndrome, meteorological phenomena, or impacts of wind turbines on survival influence system dynamics and risk of population extirpation in difficult to predict ways.

  2. SPATIALLY EXPLICIT MICRO-LEVEL MODELLING OF LAND USE CHANGE AT THE RURAL-URBAN INTERFACE. (R828012)

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    This paper describes micro-economic models of land use change applicable to the rural–urban interface in the US. Use of a spatially explicit micro-level modelling approach permits the analysis of regional patterns of land use as the aggregate outcomes of many, disparate...

  3. A spatially explicit model for the future progression of the current Haiti cholera epidemic

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    Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2011-12-01

    As a major cholera epidemic progresses in Haiti, and the figures of the infection, up to July 2011, climb to 385,000 cases and 5,800 deaths, the development of general models to track and predict the evolution of the outbreak, so as to guide the allocation of medical supplies and staff, is gaining notable urgency. We propose here a spatially explicit epidemic model that accounts for the dynamics of susceptible and infected individuals as well as the redistribution of textit{Vibrio cholera}, the causative agent of the disease, among different human communities. In particular, we model two spreading pathways: the advection of pathogens through hydrologic connections and the dissemination due to human mobility described by means of a gravity-like model. To this end the country has been divided into hydrologic units based on drainage directions derived from a digital terrain model. Moreover the population of each unit has been estimated from census data downscaled to 1 km x 1 km resolution via remotely sensed geomorphological information (LandScan texttrademark project). The model directly account for the role of rainfall patterns in driving the seasonality of cholera outbreaks. The two main outbreaks in fact occurred during the rainy seasons (October and May) when extensive floodings severely worsened the sanitation conditions and, in turn, raised the risk of infection. The model capability to reproduce the spatiotemporal features of the epidemic up to date grants robustness to the foreseen future development. In this context, the duration of acquired immunity, a hotly debated topic in the scientific community, emerges as a controlling factor for progression of the epidemic in the near future. The framework presented here can straightforwardly be used to evaluate the effectiveness of alternative intervention strategies like mass vaccinations, clean water supply and educational campaigns, thus emerging as an essential component of the control of future cholera

  4. Spatially Explicit Estimation of Optimal Light Use Efficiency for Improved Satellite Data Driven Ecosystem Productivity Modeling

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    Madani, N.; Kimball, J. S.; Running, S. W.

    2014-12-01

    Remote sensing based light use efficiency (LUE) models, including the MODIS (MODerate resolution Imaging Spectroradiometer) MOD17 algorithm are commonly used for regional estimation and monitoring of vegetation gross primary production (GPP) and photosynthetic carbon (CO2) uptake. A common model assumption is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed biome maximum light use efficiency parameter defines the maximum photosynthetic carbon conversion rate under prevailing climate conditions and is a large source of model uncertainty. Here, we used tower (FLUXNET) eddy covariance measurement based carbon flux data for estimating optimal LUE (LUEopt) over a North American domain. LUEopt was first estimated using tower observed daily carbon fluxes, meteorology and satellite (MODIS) observed fraction of photosynthetically active radiation (FPAR). LUEopt was then spatially interpolated over the domain using empirical models derived from independent geospatial data including global plant traits, surface soil moisture, terrain aspect, land cover type and percent tree cover. The derived LUEopt maps were then used as primary inputs to the MOD17 LUE algorithm for regional GPP estimation; these results were evaluated against tower observations and alternate MOD17 GPP estimates determined using Biome-specific LUEopt constants. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from a sparse North American tower network. Leaf nitrogen content and soil moisture are two important factors explaining LUEopt spatial variability. GPP estimated from spatially explicit LUEopt inputs shows significantly improved model accuracy against independent tower observations (R2 = 0.76; Mean RMSE plant trait information can explain spatial heterogeneity in LUEopt, leading to improved GPP estimates from satellite based LUE models.

  5. Biomass supply from alternative cellulosic crops and crop residues: A spatially explicit bioeconomic modeling approach

    International Nuclear Information System (INIS)

    Egbendewe-Mondzozo, Aklesso; Swinton, Scott M.; Izaurralde, César R.; Manowitz, David H.; Zhang, Xuesong

    2011-01-01

    This paper introduces a spatially-explicit bioeconomic model for the study of potential cellulosic biomass supply. For biomass crops to begin to replace current crops, farmers must earn more from them than from current crops. Using weather, topographic and soil data, the terrestrial ecosystem model, EPIC, dynamically simulates multiple cropping systems that vary by crop rotation, tillage, fertilization and residue removal rate. EPIC generates predicted crop yield and environmental outcomes over multiple watersheds. These EPIC results are used to parameterize a regional profit-maximization mathematical programming model that identifies profitable cropping system choices. The bioeconomic model is calibrated to 2007–09 crop production in a 9-county region of southwest Michigan. A simulation of biomass supply in response to rising biomass prices shows that cellulosic residues from corn stover and wheat straw begin to be supplied at minimum delivered biomass:corn grain price ratios of 0.15 and 0.18, respectively. At the mean corn price of $162.6/Mg ($4.13 per bushel) at commercial moisture content during 2007–2009, these ratios correspond to stover and straw prices of $24 and $29 per dry Mg. Perennial bioenergy crops begin to be supplied at price levels 2–3 times higher. Average biomass transport costs to the biorefinery plant range from $6 to $20/Mg compared to conventional crop production practices in the area, biomass supply from annual crop residues increased greenhouse gas emissions and reduced water quality through increased nutrient loss. By contrast, perennial cellulosic biomass crop production reduced greenhouse gas emissions and improved water quality. -- Highlights: ► A new bioeconomic model predicts biomass supply and its environmental impacts. ► The model captures the opportunity cost of switching to new cellulosic crops. ► Biomass from crop residues is supplied at lower biomass price than cellulosic crops. ► Biomass from cellulosic crops has

  6. A new approach to spatially explicit modelling of forest dynamics: spacing, ageing and neighbourhood competition of mangrove trees

    NARCIS (Netherlands)

    Berger, U.; Hildenbrandt, H.

    2000-01-01

    This paper presents a new approach to spatially explicit modelling that enables the influence of neighbourhood effects on the dynamics of forests and plant communities to be analysed. We refer to this approach as 'field of neighbourhood' (FON). It combines the 'neighbourhood philosophy' of

  7. Development and Validation of Spatially Explicit Habitat Models for Cavity-nesting Birds in Fishlake National Forest, Utah

    Science.gov (United States)

    Randall A., Jr. Schultz; Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino

    2005-01-01

    The ability of USDA Forest Service Forest Inventory and Analysis (FIA) generated spatial products to increase the predictive accuracy of spatially explicit, macroscale habitat models was examined for nest-site selection by cavity-nesting birds in Fishlake National Forest, Utah. One FIA-derived variable (percent basal area of aspen trees) was significant in the habitat...

  8. Human Mobility Patterns and Cholera Epidemics: a Spatially Explicit Modeling Approach

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    Mari, L.; Bertuzzo, E.; Righetto, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2010-12-01

    Cholera is an acute enteric disease caused by the ingestion of water or food contaminated by the bacterium Vibrio cholerae. Although most infected individuals do not develop severe symptoms, their stool may contain huge quantities of V.~cholerae cells. Therefore, while traveling or commuting, asymptomatic carriers can be responsible for the long-range dissemination of the disease. As a consequence, human mobility is an alternative and efficient driver for the spread of cholera, whose primary propagation pathway is hydrological transport through river networks. We present a multi-layer network model that accounts for the interplay between epidemiological dynamics, hydrological transport and long-distance dissemination of V.~cholerae due to human movement. In particular, building on top of state-of-the-art spatially explicit models for cholera spread through surface waters, we describe human movement and its effects on the propagation of the disease by means of a gravity-model approach borrowed from transportation theory. Gravity-like contact processes have been widely used in epidemiology, because they can satisfactorily depict human movement when data on actual mobility patterns are not available. We test our model against epidemiological data recorded during the cholera outbreak occurred in the KwaZulu-Natal province of South Africa during years 2000--2001. We show that human mobility does actually play an important role in the formation of the spatiotemporal patterns of cholera epidemics. In particular, long-range human movement may determine inter-catchment dissemination of V.~cholerae cells, thus in turn explaining the emergence of epidemic patterns that cannot be produced by hydrological transport alone. We also show that particular attention has to be devoted to study how heterogeneously distributed drinking water supplies and sanitation conditions may affect cholera transmission.

  9. Spatially Explicit Modelling of the Belgian Major Endurance Event 'The 100 km Dodentocht'.

    Directory of Open Access Journals (Sweden)

    Steffie Van Nieuland

    Full Text Available 'The 100 km Dodentocht', which takes place annually and has its start in Bornem, Belgium, is a long distance march where participants have to cover a 100 km trail in at most 24 hours. The approximately 11 000 marchers per edition are tracked by making use of passive radio-frequency-identification (RFID. These tracking data were analyzed to build a spatially explicit marching model that gives insights into the dynamics of the event and allows to evaluate the effect of changes in the starting procedure of the event. For building the model, the empirical distribution functions (edf of the marching speeds at every section of the trail in between two consecutive checkpoints and of the checkpoints where marchers retire, are determined, taking into account age, gender, and marching speeds at previous sections. These distribution functions are then used to sample the consecutive speeds and retirement, and as such to simulate the times when individual marchers pass by the consecutive checkpoints. We concluded that the data-driven model simulates the event reliably. Furthermore, we tested three scenarios to reduce the crowdiness along the first part of the trail and in this way were able to conclude that either the start should be moved to a location outside the town center where the streets are at least 25% wider, or that the marchers should start in two groups at two different locations, and that these groups should ideally merge at about 20 km after the start. The crowdiness at the start might also be reduced by installing a bottleneck at the start in order to limit the number of marchers that can pass per unit of time. Consequently, the operating hours of the consecutive checkpoints would be longer. The developed framework can likewise be used to analyze and improve the operation of other endurance events if sufficient tracking data are available.

  10. Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea.

    Directory of Open Access Journals (Sweden)

    Patricia Puerta

    Full Text Available Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla and sea surface temperature (SST, and trophic (prey density conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents

  11. Spatially explicit modeling of conflict zones between wildlife and snow sports: prioritizing areas for winter refuges.

    Science.gov (United States)

    Braunisch, Veronika; Patthey, Patrick; Arlettaz, Raphaël

    2011-04-01

    Outdoor winter recreation exerts an increasing pressure upon mountain ecosystems, with unpredictable, free-ranging activities (e.g., ski mountaineering, snowboarding, and snowshoeing) representing a major source of stress for wildlife. Mitigating anthropogenic disturbance requires the spatially explicit prediction of the interference between the activities of humans and wildlife. We applied spatial modeling to localize conflict zones between wintering Black Grouse (Tetrao tetrix), a declining species of Alpine timberline ecosystems, and two free-ranging winter sports (off-piste skiing [including snow-boarding] and snowshoeing). Track data (snow-sports and birds' traces) obtained from aerial photographs taken over a 585-km transect running along the timberline, implemented within a maximum entropy model, were used to predict the occurrence of snow sports and Black Grouse as a function of landscape characteristics. By modeling Black Grouse presence in the theoretical absence of free-ranging activities and ski infrastructure, we first estimated the amount of habitat reduction caused by these two factors. The models were then extrapolated to the altitudinal range occupied by Black Grouse, while the spatial extent and intensity of potential conflict were assessed by calculating the probability of human-wildlife co-occurrence. The two snow-sports showed different distribution patterns. Skiers' occurrence was mainly determined by ski-lift presence and a smooth terrain, while snowshoers' occurrence was linked to hiking or skiing routes and moderate slopes. Wintering Black Grouse avoided ski lifts and areas frequented by free-ranging snow sports. According to the models, Black Grouse have faced a substantial reduction of suitable wintering habitat along the timberline transect: 12% due to ski infrastructure and another 16% when adding free-ranging activities. Extrapolating the models over the whole study area results in an overall habitat loss due to ski infrastructure of

  12. Hydroclimatology of Dual Peak Cholera Incidence in Bengal Region: Inferences from a Spatial Explicit Model

    Science.gov (United States)

    Bertuzzo, E.; Mari, L.; Righetto, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2010-12-01

    The seasonality of cholera and its relation with environmental drivers are receiving increasing interest and research efforts, yet they remain unsatisfactorily understood. A striking example is the observed annual cycle of cholera incidence in the Bengal region which exhibits two peaks despite the main environmental drivers that have been linked to the disease (air and sea surface temperature, zooplankton density, river discharge) follow a synchronous single-peak annual pattern. A first outbreak, mainly affecting the coastal regions, occurs in spring and it is followed, after a period of low incidence during summer, by a second, usually larger, peak in autumn also involving regions situated farther inland. A hydroclimatological explanation for this unique seasonal cycle has been recently proposed: the low river spring flows favor the intrusion of brackish water (the natural environment of the causative agent of the disease) which, in turn, triggers the first outbreak. The summer rising river discharges have a temporary dilution effect and prompt the repulsion of contaminated water which lowers the disease incidence. However, the monsoon flooding, together with the induced crowding of the population and the failure of the sanitation systems, can possibly facilitate the spatial transmission of the disease and promote the autumn outbreak. We test this hypothesis using a mechanistic, spatially explicit model of cholera epidemic. The framework directly accounts for the role of the river network in transporting and redistributing cholera bacteria among human communities as well as for the annual fluctuation of the river flow. The model is forced with the actual environmental drivers of the region, namely river flow and temperature. Our results show that these two drivers, both having a single peak in the summer, can generate a double peak cholera incidence pattern. Besides temporal patterns, the model is also able to qualitatively reproduce spatial patterns characterized

  13. Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

    Directory of Open Access Journals (Sweden)

    Rachel R. Sleeter

    2015-06-01

    Full Text Available Spatially-explicit state-and-transition simulation models of land use and land cover (LULC increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS, a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age, spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest. Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

  14. Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

    Science.gov (United States)

    Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

    2015-01-01

    Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

  15. INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...

    Science.gov (United States)

    Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

  16. Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - FishRand Spatially-Explicit Bioaccumulation Model Demonstration

    Science.gov (United States)

    2015-08-01

    Unaccounted dynamic habitats and resultant changes in wildlife usage;  Simplified foraging strategies (lacking important considerations such as...and water exposures, fish foraging strategies, and PCB uptake. Figure 2 additionally shows the comparison of standard deviations across the...area (1, 2, and 5) at the Tyndall AFB site. ....................................... 22  Figure 5. Comparison of model predictions to site data for

  17. An unified framework to integrate biotic, abiotic processes and human activities in spatially explicit models of agricultural landscapes

    Directory of Open Access Journals (Sweden)

    Fabrice eVinatier

    2016-02-01

    Full Text Available Recent concern over possible ways to sustain ecosystem services has triggered important research worldwide on ecosystem processes at the landscape scale. Understanding this complexity of landscape functioning calls for coupled and spatially-explicit modelling approaches. However, disciplinary boundaries have limited the number of multi-process studies at the landscape scale, and current progress in coupling processes at this scale often reveals strong imbalance between biotic and abiotic processes, depending on the core discipline of the modellers. We propose a spatially-explicit, unified conceptual framework that allows researchers from different fields to develop a shared view of agricultural landscapes. In particular,we distinguish landscape elements that are mobile in space and represent biotic or abiotic objects (for example water, fauna or flora populations, and elements that are immobile and represent fixed landscape elements with a given geometry (for example ditch section or plot. The shared representation of these elements allows setting common objects and spatio-temporal process boundaries that may otherwise differ between disciplines. We present guidelines and an assessment of the applicability of this framework to a virtual landscape system with realistic properties. This framework allows the complex system to be represented with a limited set of concepts but leaves the possibility to include current modelling strategies specific to biotic or abiotic disciplines. Future operational challenges include model design, space and time discretization, and the availability of both landscape modelling platforms and data.

  18. Evaluating the effect of corridors and landscape heterogeneity on dispersal probability: a comparison of three spatially explicit modelling approaches

    DEFF Research Database (Denmark)

    Jepsen, J. U.; Baveco, J. M.; Topping, C. J.

    2004-01-01

    preferences of the modeller, rather than by a critical evaluation of model performance. We present a comparison of three common spatial simulation approaches (patch-based incidence-function model (IFM), individual-based movement model (IBMM), individual-based population model including detailed behaviour...

  19. A spatially explicit model of functional connectivity for the endangered Przewalski's gazelle (Procapra przewalskii in a patchy landscape.

    Directory of Open Access Journals (Sweden)

    Chunlin Li

    Full Text Available Habitat fragmentation, associated with human population expansion, impedes dispersal, reduces gene flow and aggravates inbreeding in species on the brink of extinction. Both scientific and conservation communities increasingly realize that maintaining and restoring landscape connectivity is of vital importance in biodiversity conservation. Prior to any conservation initiatives, it is helpful to present conservation practitioners with a spatially explicit model of functional connectivity for the target species or landscape.Using Przewalski's gazelle (Procapra przewalskii as a model of endangered ungulate species in highly fragmented landscape, we present a model providing spatially explicit information to inform the long-term preservation of well-connected metapopulations. We employed a Geographic Information System (GIS and expert-literature method to create a habitat suitability map, to identify potential habitats and to delineate a functional connectivity network (least-cost movement corridors and paths for the gazelle. Results indicated that there were limited suitable habitats for the gazelle, mainly found to the north and northwest of the Qinghai Lake where four of five potential habitat patches were identified. Fifteen pairs of least-cost corridors and paths were mapped connecting eleven extant populations and two neighboring potential patches. The least-cost paths ranged from 0.2 km to 26.8 km in length (averaging 12.4 km and were all longer than corresponding Euclidean distances.The model outputs were validated and supported by the latest findings in landscape genetics of the species, and may provide impetus for connectivity conservation programs. Dispersal barriers were examined and appropriate mitigation strategies were suggested. This study provides conservation practitioners with thorough and visualized information to reserve the landscape connectivity for Przewalski's gazelle. In a general sense, we proposed a heuristic framework

  20. An individual-based simulation model for mottled sculpin (Cottus bairdi) in a southern Appalachian stream

    Science.gov (United States)

    Brenda Rashleigh; Gary D. Grossman

    2005-01-01

    We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was based on consumption bioenergetics of benthic macroinvertebrate prey;...

  1. Analyzing key constraints to biogas production from crop residues and manure in the EU—A spatially explicit model

    Science.gov (United States)

    Persson, U. Martin

    2017-01-01

    This paper presents a spatially explicit method for making regional estimates of the potential for biogas production from crop residues and manure, accounting for key technical, biochemical, environmental and economic constraints. Methods for making such estimates are important as biofuels from agricultural residues are receiving increasing policy support from the EU and major biogas producers, such as Germany and Italy, in response to concerns over unintended negative environmental and social impacts of conventional biofuels. This analysis comprises a spatially explicit estimate of crop residue and manure production for the EU at 250 m resolution, and a biogas production model accounting for local constraints such as the sustainable removal of residues, transportation of substrates, and the substrates’ biochemical suitability for anaerobic digestion. In our base scenario, the EU biogas production potential from crop residues and manure is about 0.7 EJ/year, nearly double the current EU production of biogas from agricultural substrates, most of which does not come from residues or manure. An extensive sensitivity analysis of the model shows that the potential could easily be 50% higher or lower, depending on the stringency of economic, technical and biochemical constraints. We find that the potential is particularly sensitive to constraints on the substrate mixtures’ carbon-to-nitrogen ratio and dry matter concentration. Hence, the potential to produce biogas from crop residues and manure in the EU depends to large extent on the possibility to overcome the challenges associated with these substrates, either by complementing them with suitable co-substrates (e.g. household waste and energy crops), or through further development of biogas technology (e.g. pretreatment of substrates and recirculation of effluent). PMID:28141827

  2. Analyzing key constraints to biogas production from crop residues and manure in the EU-A spatially explicit model.

    Science.gov (United States)

    Einarsson, Rasmus; Persson, U Martin

    2017-01-01

    This paper presents a spatially explicit method for making regional estimates of the potential for biogas production from crop residues and manure, accounting for key technical, biochemical, environmental and economic constraints. Methods for making such estimates are important as biofuels from agricultural residues are receiving increasing policy support from the EU and major biogas producers, such as Germany and Italy, in response to concerns over unintended negative environmental and social impacts of conventional biofuels. This analysis comprises a spatially explicit estimate of crop residue and manure production for the EU at 250 m resolution, and a biogas production model accounting for local constraints such as the sustainable removal of residues, transportation of substrates, and the substrates' biochemical suitability for anaerobic digestion. In our base scenario, the EU biogas production potential from crop residues and manure is about 0.7 EJ/year, nearly double the current EU production of biogas from agricultural substrates, most of which does not come from residues or manure. An extensive sensitivity analysis of the model shows that the potential could easily be 50% higher or lower, depending on the stringency of economic, technical and biochemical constraints. We find that the potential is particularly sensitive to constraints on the substrate mixtures' carbon-to-nitrogen ratio and dry matter concentration. Hence, the potential to produce biogas from crop residues and manure in the EU depends to large extent on the possibility to overcome the challenges associated with these substrates, either by complementing them with suitable co-substrates (e.g. household waste and energy crops), or through further development of biogas technology (e.g. pretreatment of substrates and recirculation of effluent).

  3. Analyzing key constraints to biogas production from crop residues and manure in the EU-A spatially explicit model.

    Directory of Open Access Journals (Sweden)

    Rasmus Einarsson

    Full Text Available This paper presents a spatially explicit method for making regional estimates of the potential for biogas production from crop residues and manure, accounting for key technical, biochemical, environmental and economic constraints. Methods for making such estimates are important as biofuels from agricultural residues are receiving increasing policy support from the EU and major biogas producers, such as Germany and Italy, in response to concerns over unintended negative environmental and social impacts of conventional biofuels. This analysis comprises a spatially explicit estimate of crop residue and manure production for the EU at 250 m resolution, and a biogas production model accounting for local constraints such as the sustainable removal of residues, transportation of substrates, and the substrates' biochemical suitability for anaerobic digestion. In our base scenario, the EU biogas production potential from crop residues and manure is about 0.7 EJ/year, nearly double the current EU production of biogas from agricultural substrates, most of which does not come from residues or manure. An extensive sensitivity analysis of the model shows that the potential could easily be 50% higher or lower, depending on the stringency of economic, technical and biochemical constraints. We find that the potential is particularly sensitive to constraints on the substrate mixtures' carbon-to-nitrogen ratio and dry matter concentration. Hence, the potential to produce biogas from crop residues and manure in the EU depends to large extent on the possibility to overcome the challenges associated with these substrates, either by complementing them with suitable co-substrates (e.g. household waste and energy crops, or through further development of biogas technology (e.g. pretreatment of substrates and recirculation of effluent.

  4. Analysis of Sensitivity and Uncertainty in an Individual-Based Model of a Threatened Wildlife Species

    Science.gov (United States)

    We present a multi-faceted sensitivity analysis of a spatially explicit, individual-based model (IBM) (HexSim) of a threatened species, the Northern Spotted Owl (Strix occidentalis caurina) on a national forest in Washington, USA. Few sensitivity analyses have been conducted on ...

  5. Spatially explicit modeling of particulate nutrient flux in Large global rivers

    Science.gov (United States)

    Cohen, S.; Kettner, A.; Mayorga, E.; Harrison, J. A.

    2017-12-01

    Water, sediment, nutrient and carbon fluxes along river networks have undergone considerable alterations in response to anthropogenic and climatic changes, with significant consequences to infrastructure, agriculture, water security, ecology and geomorphology worldwide. However, in a global setting, these changes in fluvial fluxes and their spatial and temporal characteristics are poorly constrained, due to the limited availability of continuous and long-term observations. We present results from a new global-scale particulate modeling framework (WBMsedNEWS) that combines the Global NEWS watershed nutrient export model with the spatially distributed WBMsed water and sediment model. We compare the model predictions against multiple observational datasets. The results indicate that the model is able to accurately predict particulate nutrient (Nitrogen, Phosphorus and Organic Carbon) fluxes on an annual time scale. Analysis of intra-basin nutrient dynamics and fluxes to global oceans is presented.

  6. An open and extensible framework for spatially explicit land use change modelling: the lulcc R package

    Science.gov (United States)

    Moulds, S.; Buytaert, W.; Mijic, A.

    2015-10-01

    We present the lulcc software package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of alternative models; and (3) additional software is required because existing applications frequently perform only the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a data set included with the package. It is envisaged that lulcc will enable future model development and comparison within an open environment.

  7. Using Satellite Remote Sensing Data in a Spatially Explicit Price Model

    Science.gov (United States)

    Brown, Molly E.; Pinzon, Jorge E.; Prince, Stephen D.

    2007-01-01

    Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the World. In this paper we integrate several indicators that are available to enhance the information for preparation for and responses to food security emergencies. The assessment uses a price model based on the relationship between the suitability of the growing season and market prices for coarse grain. The model is then used to create spatially continuous maps of millet prices. The model is applied to the dry central and northern areas of West Africa, using satellite-derived vegetation indices for the entire region. By coupling the model with vegetation data estimated for one to four months into the future, maps are created of a leading indicator of potential price movements. It is anticipated that these maps can be used to enable early warning of famine and for planning appropriate responses.

  8. Spatially explicit Schistosoma infection risk in eastern Africa using Bayesian geostatistical modelling

    DEFF Research Database (Denmark)

    Schur, Nadine; Hürlimann, Eveline; Stensgaard, Anna-Sofie

    2013-01-01

    are currently infected with either S. mansoni, or S. haematobium, or both species concurrently. Country-specific population-adjusted prevalence estimates range between 12.9% (Uganda) and 34.5% (Mozambique) for S. mansoni and between 11.9% (Djibouti) and 40.9% (Mozambique) for S. haematobium. Our models revealed...

  9. Spatially explicit modeling of blackbird abundance in the Prairie Pothole Region

    Science.gov (United States)

    Forcey, Greg M.; Thogmartin, Wayne E.; Linz, George M.; McKann, Patrick C.; Crimmins, Shawn M.

    2015-01-01

    Knowledge of factors influencing animal abundance is important to wildlife biologists developing management plans. This is especially true for economically important species such as blackbirds (Icteridae), which cause more than $100 million in crop damages annually in the United States. Using data from the North American Breeding Bird Survey, the National Land Cover Dataset, and the National Climatic Data Center, we modeled effects of regional environmental variables on relative abundance of 3 blackbird species (red-winged blackbird,Agelaius phoeniceus; yellow-headed blackbird, Xanthocephalus xanthocephalus; common grackle, Quiscalus quiscula) in the Prairie Pothole Region of the central United States. We evaluated landscape covariates at 3 logarithmically related spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and modeled weather variables at the 100,000-ha scale. We constructed models a priori using information from published habitat associations. We fit models with WinBUGS using Markov chain Monte Carlo techniques. Both landscape and weather variables contributed strongly to predicting blackbird relative abundance (95% credibility interval did not overlap 0). Variables with the strongest associations with blackbird relative abundance were the percentage of wetland area and precipitation amount from the year before bird surveys were conducted. The influence of spatial scale appeared small—models with the same variables expressed at different scales were often in the best model subset. This large-scale study elucidated regional effects of weather and landscape variables, suggesting that management strategies aimed at reducing damages caused by these species should consider the broader landscape, including weather effects, because such factors may outweigh the influence of localized conditions or site-specific management actions. The regional species distributional models we developed for blackbirds provide a tool for understanding these broader

  10. Spatially explicit models for inference about density in unmarked or partially marked populations

    Science.gov (United States)

    Chandler, Richard B.; Royle, J. Andrew

    2013-01-01

    Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating

  11. HABSEED: a Simple Spatially Explicit Meta-Populations Model Using Remote Sensing Derived Habitat Quality Data

    Science.gov (United States)

    Heumann, B. W.; Guichard, F.; Seaquist, J. W.

    2005-05-01

    The HABSEED model uses remote sensing derived NPP as a surrogate for habitat quality as the driving mechanism for population growth and local seed dispersal. The model has been applied to the Sahel region of Africa. Results show that the functional response of plants to habitat quality alters population distribution. Plants more tolerant of medium quality habitat have greater distributions to the North while plants requiring only the best habitat are limited to the South. For all functional response types, increased seed production results in diminishing returns. Functional response types have been related to life history tradeoffs and r-K strategies based on the results. Results are compared to remote sensing derived vegetation land cover.

  12. The “Destabilizing” Effect of Cannibalism in a Spatially Explicit Three-Species Age Structured Predator-Prey Model

    Directory of Open Access Journals (Sweden)

    Aladeen Al Basheer

    2017-01-01

    Full Text Available Cannibalism, the act of killing and consumption of conspecifics, is generally considered to be a stabilising process in ODE models of predator-prey systems. On the other hand, Sun et al. were the first to show that cannibalism can cause Turing instability, in the classical Rosenzweig-McArthur two-species PDE model, which is an impossibility without cannibalism. Magnússon’s classic work is the first to show that cannibalism in a structured three-species predator-prey ODE model can actually be destabilising. In the current manuscript we consider the PDE form of the three-species model proposed in Magnússon’s classic work. We prove that, in the absence of cannibalism, Turing instability is an impossibility in this model, for any range of parameters. However, the inclusion of cannibalism can cause Turing instability. Thus, to the best of our knowledge, we report the first cannibalism induced Turing instability result, in spatially explicit three-species age structured predator-prey systems. We also show that, in the classical ODE model proposed by Magnússon, cannibalism can act as a life boat mechanism, for the prey.

  13. Spatially explicit modeling of lesser prairie-chicken lek density in Texas

    Science.gov (United States)

    Timmer, Jennifer M.; Butler, M.J.; Ballard, Warren; Boal, Clint W.; Whitlaw, Heather A.

    2014-01-01

    As with many other grassland birds, lesser prairie-chickens (Tympanuchus pallidicinctus) have experienced population declines in the Southern Great Plains. Currently they are proposed for federal protection under the Endangered Species Act. In addition to a history of land-uses that have resulted in habitat loss, lesser prairie-chickens now face a new potential disturbance from energy development. We estimated lek density in the occupied lesser prairie-chicken range of Texas, USA, and modeled anthropogenic and vegetative landscape features associated with lek density. We used an aerial line-transect survey method to count lesser prairie-chicken leks in spring 2010 and 2011 and surveyed 208 randomly selected 51.84-km(2) blocks. We divided each survey block into 12.96-km(2) quadrats and summarized landscape variables within each quadrat. We then used hierarchical distance-sampling models to examine the relationship between lek density and anthropogenic and vegetative landscape features and predict how lek density may change in response to changes on the landscape, such as an increase in energy development. Our best models indicated lek density was related to percent grassland, region (i.e., the northeast or southwest region of the Texas Panhandle), total percentage of grassland and shrubland, paved road density, and active oil and gas well density. Predicted lek density peaked at 0.39leks/12.96km(2) (SE=0.09) and 2.05leks/12.96km(2) (SE=0.56) in the northeast and southwest region of the Texas Panhandle, respectively, which corresponds to approximately 88% and 44% grassland in the northeast and southwest region. Lek density increased with an increase in total percentage of grassland and shrubland and was greatest in areas with lower densities of paved roads and lower densities of active oil and gas wells. We used the 2 most competitive models to predict lek abundance and estimated 236 leks (CV=0.138, 95% CI=177-306leks) for our sampling area. Our results suggest that

  14. Spatially-explicit LCIA model for marine eutrophication as a tool for sustainability assessment

    DEFF Research Database (Denmark)

    Cosme, Nuno Miguel Dias; Hauschild, Michael Zwicky

    2014-01-01

    The increasing emissions from human activities are overrunning the ecosystems’ natural capacity to absorb them. Nutrient emissions, mostly nitrogen- and phosphorus-forms (N, P) from e.g. agricultural runoff and combustion processes, may lead to social-economic impacts and environmental quality......-enrichment to impacts on marine ecosystems. Emitted nitrogen reaches marine coastal waters where it promotes the growth of phytoplankton biomass in the surface photic zone from where it eventually sinks to bottom waters. This downward flux of organic matter is respired there by bacteria resulting in the consumption...... of dissolved oxygen. An excessive depletion of oxygen affects the exposed organisms and loss of species diversity may be expected. A model framework was built to estimate the potential impacts arising from N-emissions (see figure). It combines the fate of N in rivers and coastal waters, the exposure...

  15. Modeling spatially explicit fire impact on gross primary production in interior Alaska using satellite images coupled with eddy covariance

    Science.gov (United States)

    Huang, Shengli; Liu, Heping; Dahal, Devendra; Jin, Suming; Welp, Lisa R.; Liu, Jinxun; Liu, Shuguang

    2013-01-01

    In interior Alaska, wildfires change gross primary production (GPP) after the initial disturbance. The impact of fires on GPP is spatially heterogeneous, which is difficult to evaluate by limited point-based comparisons or is insufficient to assess by satellite vegetation index. The direct prefire and postfire comparison is widely used, but the recovery identification may become biased due to interannual climate variability. The objective of this study is to propose a method to quantify the spatially explicit GPP change caused by fires and succession. We collected three Landsat images acquired on 13 July 2004, 5 August 2004, and 6 September 2004 to examine the GPP recovery of burned area from 1987 to 2004. A prefire Landsat image acquired in 1986 was used to reconstruct satellite images assuming that the fires of 1987–2004 had not occurred. We used a light-use efficiency model to estimate the GPP. This model was driven by maximum light-use efficiency (Emax) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). We applied this model to two scenarios (i.e., an actual postfire scenario and an assuming-no-fire scenario), where the changes in Emax and FPAR were taken into account. The changes in Emax were represented by the change in land cover of evergreen needleleaf forest, deciduous broadleaf forest, and shrub/grass mixed, whose Emax was determined from three fire chronosequence flux towers as 1.1556, 1.3336, and 0.5098 gC/MJ PAR. The changes in FPAR were inferred from NDVI change between the actual postfire NDVI and the reconstructed NDVI. After GPP quantification for July, August, and September 2004, we calculated the difference between the two scenarios in absolute and percent GPP changes. Our results showed rapid recovery of GPP post-fire with a 24% recovery immediately after burning and 43% one year later. For the fire scars with an age range of 2–17 years, the recovery rate ranged from 54% to 95%. In addition to the averaging

  16. Modeling the fate of nitrogen on the catchment scale using a spatially explicit hydro-biogeochemical simulation system

    Science.gov (United States)

    Klatt, S.; Butterbach-Bahl, K.; Kiese, R.; Haas, E.; Kraus, D.; Molina-Herrera, S. W.; Kraft, P.

    2015-12-01

    The continuous growth of the human population demands an equally growing supply for fresh water and food. As a result, available land for efficient agriculture is constantly diminishing which forces farmers to cultivate inferior croplands and intensify agricultural practices, e.g., increase the use of synthetic fertilizers. This intensification of marginal areas in particular will cause a dangerous rise in nitrate discharge into open waters or even drinking water resources. In order to reduce the amount of nitrate lost by surface runoff or lateral subsurface transport, bufferstrips have proved to be a valuable means. Current laws, however, promote rather static designs (i.e., width and usage) even though a multitude of factors, e.g., soil type, slope, vegetation and the nearby agricultural management, determines its effectiveness. We propose a spatially explicit modeling approach enabling to assess the effects of those factors on nitrate discharge from arable lands using the fully distributed hydrology model CMF coupled to the complex biogeochemical model LandscapeDNDC. Such a modeling scheme allows to observe the displacement of dissolved nutrients in both vertical and horizontal directions and serves to estimate both their uptake by the vegetated bufferstrip and loss to the environment. First results indicate a significant reduction of nitrate loss in the presence of a bufferstrip (2.5 m). We show effects induced by various buffer strip widths and plant cover on the nitrate retention.

  17. Reducing fertilizer-nitrogen losses from rowcrop landscapes: Insights and implications from a spatially explicit watershed model

    Science.gov (United States)

    McLellan, Eileen; Schilling, Keith; Robertson, Dale M.

    2015-01-01

    We present conceptual and quantitative models that predict changes in fertilizer-derived nitrogen delivery from rowcrop landscapes caused by agricultural conservation efforts implemented to reduce nutrient inputs and transport and increase nutrient retention in the landscape. To evaluate the relative importance of changes in the sources, transport, and sinks of fertilizer-derived nitrogen across a region, we use the spatially explicit SPAtially Referenced Regression On Watershed attributes watershed model to map the distribution, at the small watershed scale within the Upper Mississippi-Ohio River Basin (UMORB), of: (1) fertilizer inputs; (2) nutrient attenuation during delivery of those inputs to the UMORB outlet; and (3) nitrogen export from the UMORB outlet. Comparing these spatial distributions suggests that the amount of fertilizer input and degree of nutrient attenuation are both important in determining the extent of nitrogen export. From a management perspective, this means that agricultural conservation efforts to reduce nitrogen export would benefit by: (1) expanding their focus to include activities that restore and enhance nutrient processing in these highly altered landscapes; and (2) targeting specific types of best management practices to watersheds where they will be most valuable. Doing so successfully may result in a shift in current approaches to conservation planning, outreach, and funding.

  18. A High-Resolution Spatially Explicit Monte-Carlo Simulation Approach to Commercial and Residential Electricity and Water Demand Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Morton, April M [ORNL; McManamay, Ryan A [ORNL; Nagle, Nicholas N [ORNL; Piburn, Jesse O [ORNL; Stewart, Robert N [ORNL; Surendran Nair, Sujithkumar [ORNL

    2016-01-01

    Abstract As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for high resolution spatially explicit estimates for energy and water demand has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy and water consumption, many are provided at a course spatial resolution or rely on techniques which depend on detailed region-specific data sources that are not publicly available for many parts of the U.S. Furthermore, many existing methods do not account for errors in input data sources and may therefore not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more flexible Monte-Carlo simulation approach to high-resolution residential and commercial electricity and water consumption modeling that relies primarily on publicly available data sources. The method s flexible data requirement and statistical framework ensure that the model is both applicable to a wide range of regions and reflective of uncertainties in model results. Key words: Energy Modeling, Water Modeling, Monte-Carlo Simulation, Uncertainty Quantification Acknowledgment This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

  19. Exploring the Dynamic Mechanisms of Farmland Abandonment Based on a Spatially Explicit Economic Model for Environmental Sustainability: A Case Study in Jiangxi Province, China

    Directory of Open Access Journals (Sweden)

    Hualin Xie

    2014-03-01

    Full Text Available Farmland abandonment has important impacts on biodiversity and ecosystem recovery, as well as food security and rural sustainable development. Due to rapid urbanization and industrialization, farmland abandonment has become an increasingly important problem in many countries, particularly in China. To promote sustainable land-use management and environmental sustainability, it is important to understand the socioeconomic causes and spatial patterns of farmland abandonment. In this study, we explored the dynamic mechanisms of farmland abandonment in Jiangxi province of China using a spatially explicit economical model. The results show that the variables associated with the agricultural products yield are significantly correlated with farmland abandonment. The increasing opportunity cost of farming labor is the main factor in farmland abandonment in conjunction with a rural labor shortage due to rural-to-urban population migration and regional industrialization. Farmlands are more likely to be abandoned in areas located far from the villages and towns due to higher transportation costs. Additionally, farmers with more land but lower net income are more likely to abandon poor-quality farmland. Our results support the hypothesis that farmland abandonment takes place in locations in which the costs of cultivation are high and the potential crop yield is low. In addition, our study also demonstrates that a spatially explicit economic model is necessary to distinguish between the main driving forces of farmland abandonment. Policy implications are also provided for potential future policy decisions.

  20. Exploring spatial change and gravity center movement for ecosystem services value using a spatially explicit ecosystem services value index and gravity model.

    Science.gov (United States)

    He, Yingbin; Chen, Youqi; Tang, Huajun; Yao, Yanmin; Yang, Peng; Chen, Zhongxin

    2011-04-01

    Spatially explicit ecosystem services valuation and change is a newly developing area of research in the field of ecology. Using the Beijing region as a study area, the authors have developed a spatially explicit ecosystem services value index and implemented this to quantify and spatially differentiate ecosystem services value at 1-km grid resolution. A gravity model was developed to trace spatial change in the total ecosystem services value of the Beijing study area from a holistic point of view. Study results show that the total value of ecosystem services for the study area decreased by 19.75% during the period 1996-2006 (3,226.2739 US$×10(6) in 1996, 2,589.0321 US$×10(6) in 2006). However, 27.63% of the total area of the Beijing study area increased in ecosystem services value. Spatial differences in ecosystem services values for both 1996 and 2006 are very clear. The center of gravity of total ecosystem services value for the study area moved 32.28 km northwestward over the 10 years due to intensive human intervention taking place in southeast Beijing. The authors suggest that policy-makers should pay greater attention to ecological protection under conditions of rapid socio-economic development and increase the area of green belt in the southeastern part of Beijing.

  1. Spatially explicit models of full-season productivity and implications for landscape management of Golden-winged Warblers in the western Great Lakes Region: Chapter 9

    Science.gov (United States)

    Peterson, Sean M.; Streby, Henry M.; Andersen, David E.

    2016-01-01

    The relationship between landscape structure and composition and full-season productivity (FSP) is poorly understood for most birds. For species of high conservation concern, insight into how productivity is related to landscape structure and composition can be used to develop more effective conservation strategies that increase recruitment. We monitored nest productivity and fledgling survival of Golden-winged Warblers (Vermivora chrysoptera), a species of high conservation concern, in managed forest landscapes at two sites in northern Minnesota, and one site in southeastern Manitoba, Canada from 2010 to 2012. We used logistic exposure models to identify the influence of landscape structure and composition on nest productivity and fledgling survival. We used the models to predict spatially explicit, FSP across our study sites to identify areas of low relative productivity that could be targeted for management. We then used our models of spatially explicit, FSP to simulate the impact of potential management actions on our study sites with the goal of increasing total population productivity. Unlike previous studies that suggested wetland cover types provide higher quality breeding habitat for Golden-winged Warblers, our models predicted 14% greater productivity in upland cover types. Simulated succession of a 9-ha grassland patch to a shrubby upland suitable for nesting increased the total number of fledglings produced by that patch and adjacent upland shrublands by 30%, despite decreasing individual productivity by 13%. Further simulated succession of the same patch described above into deciduous forest reduced the total number of fledglings produced to independence on a landscape by 18% because of a decrease in the area available for nesting. Simulated reduction in the cumulative length of shrubby edge within a 50-m radius of any location in our landscapes from 0.6 to 0.3 km increased FSP by 5%. Our models demonstrated that the effects of any single management

  2. Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management

    Science.gov (United States)

    Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Overton, Cory T.; Sanchez-Chopitea, Erika; Kroger, Travis; Mauch, Kimberly; Niell, Lara; Howe, Kristy; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

    2014-01-01

    Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) populations are declining throughout the sagebrush (Artemisia spp.) ecosystem, including millions of acres of potential habitat across the West. Habitat maps derived from empirical data are needed given impending listing decisions that will affect both sage-grouse population dynamics and human land-use restrictions. This report presents the process for developing spatially explicit maps describing relative habitat suitability for sage-grouse in Nevada and northeastern California. Maps depicting habitat suitability indices (HSI) values were generated based on model-averaged resource selection functions informed by more than 31,000 independent telemetry locations from more than 1,500 radio-marked sage-grouse across 12 project areas in Nevada and northeastern California collected during a 15-year period (1998–2013). Modeled habitat covariates included land cover composition, water resources, habitat configuration, elevation, and topography, each at multiple spatial scales that were relevant to empirically observed sage-grouse movement patterns. We then present an example of how the HSI can be delineated into categories. Specifically, we demonstrate that the deviation from the mean can be used to classify habitat suitability into three categories of habitat quality (high, moderate, and low) and one non-habitat category. The classification resulted in an agreement of 93–97 percent for habitat versus non-habitat across a suite of independent validation datasets. Lastly, we provide an example of how space use models can be integrated with habitat models to help inform conservation planning. In this example, we combined probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek (traditional breeding ground) using count data to calculate a composite space use index (SUI). The SUI was then classified into two categories of use

  3. SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

    Science.gov (United States)

    Pauli, Benjamin P; McCann, Nicholas P; Zollner, Patrick A; Cummings, Robert; Gilbert, Jonathan H; Gustafson, Eric J

    2013-01-01

    Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of

  4. Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

    Science.gov (United States)

    Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

    2015-01-01

    Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.

  5. A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America

    Science.gov (United States)

    Govind, Ajit; Chen, Jing Ming; Margolis, Hank; Ju, Weimin; Sonnentag, Oliver; Giasson, Marc-André

    2009-04-01

    SummaryA spatially explicit, process-based hydro-ecological model, BEPS-TerrainLab V2.0, was developed to improve the representation of ecophysiological, hydro-ecological and biogeochemical processes of boreal ecosystems in a tightly coupled manner. Several processes unique to boreal ecosystems were implemented including the sub-surface lateral water fluxes, stratification of vegetation into distinct layers for explicit ecophysiological representation, inclusion of novel spatial upscaling strategies and biogeochemical processes. To account for preferential water fluxes common in humid boreal ecosystems, a novel scheme was introduced based on laboratory analyses. Leaf-scale ecophysiological processes were upscaled to canopy-scale by explicitly considering leaf physiological conditions as affected by light and water stress. The modified model was tested with 2 years of continuous measurements taken at the Eastern Old Black Spruce Site of the Fluxnet-Canada Research Network located in a humid boreal watershed in eastern Canada. Comparison of the simulated and measured ET, water-table depth (WTD), volumetric soil water content (VSWC) and gross primary productivity (GPP) revealed that BEPS-TerrainLab V2.0 simulates hydro-ecological processes with reasonable accuracy. The model was able to explain 83% of the ET, 92% of the GPP variability and 72% of the WTD dynamics. The model suggests that in humid ecosystems such as eastern North American boreal watersheds, topographically driven sub-surface baseflow is the main mechanism of soil water partitioning which significantly affects the local-scale hydrological conditions.

  6. Integrated and spatially explicit modelling of the economic value of complex environmental change and its indirect effects

    OpenAIRE

    Bateman, Ian; Binner, Amy; Coombes, Emma; Day, Brett; Ferrini, Silvia; Fezzi, Carlo; Hutchins, Michael; Posen, Paulette

    2012-01-01

    Arguably the greatest challenge to contemporary research is to capture the inter-relatedness and complexity of the real world environment within models so at to better inform decision makers of the accurate and complete consequences of differing options. The paper presents an integrated model of the consequence of climate change upon land use and the secondary and subsequent effects arising subsequently. The model predicts the shift in land use which climate change is likely to induce and the...

  7. Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects.

    OpenAIRE

    Bateman, Ian; Agarwala, M.; Binner, A.; Coombes, E.; Day, B.; Ferrini, Silvia; Fezzi, C.; Hutchins, M.; Lovett, A.; Posen, P.

    2016-01-01

    We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact...

  8. LANDIS 4.0 users guide. LANDIS: a spatially explicit model of forest landscape disturbance, management, and succession

    Science.gov (United States)

    Hong S. He; Wei Li; Brian R. Sturtevant; Jian Yang; Bo Z. Shang; Eric J. Gustafson; David J. Mladenoff

    2005-01-01

    LANDIS 4.0 is new-generation software that simulates forest landscape change over large spatial and temporal scales. It is used to explore how disturbances, succession, and management interact to determine forest composition and pattern. Also describes software architecture, model assumptions and provides detailed instructions on the use of the model.

  9. Spatially explicit habitat models for 28 fishes from the Upper Mississippi River System (AHAG 2.0)

    Science.gov (United States)

    Ickes, Brian S.; Sauer, J.S.; Richards, N.; Bowler, M.; Schlifer, B.

    2014-01-01

    Environmental management actions in the Upper Mississippi River System (UMRS) typically require pre-project assessments of predicted benefits under a range of project scenarios. The U.S. Army Corps of Engineers (USACE) now requires certified and peer-reviewed models to conduct these assessments. Previously, habitat benefits were estimated for fish communities in the UMRS using the Aquatic Habitat Appraisal Guide (AHAG v.1.0; AHAG from hereon). This spreadsheet-based model used a habitat suitability index (HSI) approach that drew heavily upon Habitat Evaluation Procedures (HEP; U.S. Fish and Wildlife Service, 1980) by the U.S. Fish and Wildlife Service (USFWS). The HSI approach requires developing species response curves for different environmental variables that seek to broadly represent habitat. The AHAG model uses species-specific response curves assembled from literature values, data from other ecosystems, or best professional judgment. A recent scientific review of the AHAG indicated that the model’s effectiveness is reduced by its dated approach to large river ecosystems, uncertainty regarding its data inputs and rationale for habitat-species response relationships, and lack of field validation (Abt Associates Inc., 2011). The reviewers made two major recommendations: (1) incorporate empirical data from the UMRS into defining the empirical response curves, and (2) conduct post-project biological evaluations to test pre-project benefits estimated by AHAG. Our objective was to address the first recommendation and generate updated response curves for AHAG using data from the Upper Mississippi River Restoration-Environmental Management Program (UMRR-EMP) Long Term Resource Monitoring Program (LTRMP) element. Fish community data have been collected by LTRMP (Gutreuter and others, 1995; Ratcliff and others, in press) for 20 years from 6 study reaches representing 1,930 kilometers of river and >140 species of fish. We modeled a subset of these data (28 different

  10. An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

    Science.gov (United States)

    Moulds, S.; Buytaert, W.; Mijic, A.

    2015-04-01

    Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.

  11. Skeeter Buster: a stochastic, spatially explicit modeling tool for studying Aedes aegypti population replacement and population suppression strategies.

    Directory of Open Access Journals (Sweden)

    Krisztian Magori

    2009-09-01

    Full Text Available Dengue is the most important mosquito-borne viral disease affecting humans. The only prevention measure currently available is the control of its vectors, primarily Aedes aegypti. Recent advances in genetic engineering have opened the possibility for a new range of control strategies based on genetically modified mosquitoes. Assessing the potential efficacy of genetic (and conventional strategies requires the availability of modeling tools that accurately describe the dynamics and genetics of Ae. aegypti populations.We describe in this paper a new modeling tool of Ae. aegypti population dynamics and genetics named Skeeter Buster. This model operates at the scale of individual water-filled containers for immature stages and individual properties (houses for adults. The biology of cohorts of mosquitoes is modeled based on the algorithms used in the non-spatial Container Inhabiting Mosquitoes Simulation Model (CIMSiM. Additional features incorporated into Skeeter Buster include stochasticity, spatial structure and detailed population genetics. We observe that the stochastic modeling of individual containers in Skeeter Buster is associated with a strongly reduced temporal variation in stage-specific population densities. We show that heterogeneity in container composition of individual properties has a major impact on spatial heterogeneity in population density between properties. We detail how adult dispersal reduces this spatial heterogeneity. Finally, we present the predicted genetic structure of the population by calculating F(ST values and isolation by distance patterns, and examine the effects of adult dispersal and container movement between properties.We demonstrate that the incorporated stochasticity and level of spatial detail have major impacts on the simulated population dynamics, which could potentially impact predictions in terms of control measures. The capacity to describe population genetics confers the ability to model the outcome

  12. The role of spatially explicit models in land-use change research: a case study for cropping patterns in China

    NARCIS (Netherlands)

    Verburg, P.H.; Veldkamp, A.

    2001-01-01

    Single research methodologies do not suffice for a complete analysis of land-use change. Instead, a sequence of methodologies is needed that link up and integrate disciplinary components over a range of spatial and temporal scales. In this paper, a modelling methodology is presented aiming at the

  13. Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects.

    Science.gov (United States)

    Bateman, Ian; Agarwala, Matthew; Binner, Amy; Coombes, Emma; Day, Brett; Ferrini, Silvia; Fezzi, Carlo; Hutchins, Michael; Lovett, Andrew; Posen, Paulette

    2016-10-01

    We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact of changes in such pollution on riverine ecosystems showing that these will be spatially heterogeneous. Moreover, we consider further knock-on effects upon the recreational benefits derived from water environments, which we assess using revealed preference methods. This analysis permits a multi-layered examination of the economic consequences of climate change, assessing the sequence of impacts from climate change through farm gross margins, land use, water quality and recreation, both at the individual and catchment scale. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Exploring the persistence of stream-dwelling trout populations under alternative real-world turbidity regimes with an individual-based model

    Science.gov (United States)

    Bret C. Harvey; Steven F. Railsback

    2009-01-01

    We explored the effects of elevated turbidity on stream-resident populations of coastal cutthroat trout Oncorhynchus clarkii clarkii using a spatially explicit individual-based model. Turbidity regimes were contrasted by means of 15-year simulations in a third-order stream in northwestern California. The alternative regimes were based on multiple-year, continuous...

  15. A spatially explicit whole-system model of the lignocellulosic bioethanol supply chain: an assessment of decentralised processing potential

    Directory of Open Access Journals (Sweden)

    Shah Nilay

    2008-07-01

    Full Text Available Abstract Background Lignocellulosic bioethanol technologies exhibit significant capacity for performance improvement across the supply chain through the development of high-yielding energy crops, integrated pretreatment, hydrolysis and fermentation technologies and the application of dedicated ethanol pipelines. The impact of such developments on cost-optimal plant location, scale and process composition within multiple plant infrastructures is poorly understood. A combined production and logistics model has been developed to investigate cost-optimal system configurations for a range of technological, system scale, biomass supply and ethanol demand distribution scenarios specific to European agricultural land and population densities. Results Ethanol production costs for current technologies decrease significantly from $0.71 to $0.58 per litre with increasing economies of scale, up to a maximum single-plant capacity of 550 × 106 l year-1. The development of high-yielding energy crops and consolidated bio-processing realises significant cost reductions, with production costs ranging from $0.33 to $0.36 per litre. Increased feedstock yields result in systems of eight fully integrated plants operating within a 500 × 500 km2 region, each producing between 1.24 and 2.38 × 109 l year-1 of pure ethanol. A limited potential for distributed processing and centralised purification systems is identified, requiring developments in modular, ambient pretreatment and fermentation technologies and the pipeline transport of pure ethanol. Conclusion The conceptual and mathematical modelling framework developed provides a valuable tool for the assessment and optimisation of the lignocellulosic bioethanol supply chain. In particular, it can provide insight into the optimal configuration of multiple plant systems. This information is invaluable in ensuring (near-cost-optimal strategic development within the sector at the regional and national scale. The framework

  16. Large scale spatially explicit modeling of blue and green water dynamics in a temperate mid-latitude basin

    Science.gov (United States)

    Du, Liuying; Rajib, Adnan; Merwade, Venkatesh

    2018-07-01

    Looking only at climate change impacts provides partial information about a changing hydrologic regime. Understanding the spatio-temporal nature of change in hydrologic processes, and the explicit contributions from both climate and land use drivers, holds more practical value for water resources management and policy intervention. This study presents a comprehensive assessment on the spatio-temporal trend of Blue Water (BW) and Green Water (GW) in a 490,000 km2 temperate mid-latitude basin (Ohio River Basin) over the past 80 years (1935-2014), and from thereon, quantifies the combined as well as relative contributions of climate and land use changes. The Soil and Water Assessment Tool (SWAT) is adopted to simulate hydrologic fluxes. Mann-Kendall and Theil-Sen statistical tests are performed on the modeled outputs to detect respectively the trend and magnitude of changes at three different spatial scales - the entire basin, regional level, and sub-basin level. Despite the overall volumetric increase of both BW and GW in the entire basin, changes in their annual average values during the period of simulation reveal a distinctive spatial pattern. GW has increased significantly in the upper and lower parts of the basin, which can be related to the prominent land use change in those areas. BW has increased significantly only in the lower part, likely being associated with the notable precipitation change there. Furthermore, the simulation under a time-varying climate but constant land use scenario identifies climate change in the Ohio River Basin to be influential on BW, while the impact is relatively nominal on GW; whereas, land use change increases GW remarkably, but is counterproductive on BW. The approach to quantify combined/relative effects of climate and land use change as shown in this study can be replicated to understand BW-GW dynamics in similar large basins around the globe.

  17. Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

    Science.gov (United States)

    Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

    2017-09-01

    Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates

  18. Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs.

    Science.gov (United States)

    Teshager, Awoke Dagnew; Gassman, Philip W; Secchi, Silvia; Schoof, Justin T; Misgna, Girmaye

    2016-04-01

    Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner.

  19. Hydrologic Drivers of Soil Organic Carbon Erosion and Burial: Insights from a Spatially-explicit Model of a Degraded Landscape at the Calhoun Critical Zone Observatory

    Science.gov (United States)

    Dialynas, Y. G.; Bras, R. L.; Richter, D. D., Jr.

    2017-12-01

    Soil erosion and burial of organic material may constitute a substantial sink of atmospheric CO2. Attempts to quantify impacts of soil erosion on the soil-atmosphere C exchange are limited by difficulties in accounting for the fate of eroded soil organic carbon (SOC), a key factor in estimating of the net effect of erosion on the C cycle. Processes that transport SOC are still inadequately represented in terrestrial carbon (C) cycle models. This study investigates hydrologic controls on SOC redistribution across the landscape focusing on dynamic feedbacks between watershed hydrology, soil erosional processes, and SOC burial. We use tRIBS-ECO (Triangulated Irregular Network-based Real-time Integrated Basin Simulator-Erosion and Carbon Oxidation), a spatially-explicit model of SOC dynamics coupled with a physically-based hydro-geomorphic model. tRIBS-ECO systematically accounts for the fate of eroded SOC across the watershed: Rainsplash erosion and sheet erosion redistribute SOC from upland sites to depositional environments, altering depth-dependent soil biogeochemical properties in diverse soil profiles. Eroded organic material is transferred with sediment and can be partially oxidized upon transport, or preserved from decomposition by burial. The model was applied in the Calhoun Critical Zone Observatory (CZO), a site that is recovering from some of the most serious agricultural erosion in North America. Soil biogeochemical characteristics at multiple soil horizons were used to initialize the model and test performance. Remotely sensed soil moisture data (NASA SMAP) were used for model calibration. Results show significant rates of hydrologically-induced burial of SOC at the Calhoun CZO. We find that organic material at upland eroding soil profiles is largely mobilized by rainsplash erosion. Sheet erosion mainly drives C transport in lower elevation clayey soils. While SOC erosion and deposition rates declined with recent reforestation at the study site, the

  20. Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

    Directory of Open Access Journals (Sweden)

    Justin V. Remais

    2013-07-01

    Full Text Available Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF 3.2.1 baseline/current (2001–2004 and projected (Representative Concentration Pathway (RCP 4.5 and RCP 8.5; 2057–2059 climate data. Ten dynamic population features (DPFs were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate.

  1. Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

    Science.gov (United States)

    Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

    2013-09-01

    Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

  2. SMART: a spatially explicit bio-economic model for assessing and managing demersal fisheries, with an application to italian trawlers in the strait of sicily.

    Directory of Open Access Journals (Sweden)

    Tommaso Russo

    Full Text Available Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries, a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1 spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2 an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3 a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in

  3. SMART: a spatially explicit bio-economic model for assessing and managing demersal fisheries, with an application to italian trawlers in the strait of sicily.

    Science.gov (United States)

    Russo, Tommaso; Parisi, Antonio; Garofalo, Germana; Gristina, Michele; Cataudella, Stefano; Fiorentino, Fabio

    2014-01-01

    Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries), a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1) spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2) an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3) a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in the Strait of

  4. Minimizing Erosion and Agro-Pollutants Transport from Furrow Irrigated Fields to the Nearby Water Body Using Spatially-Explicit Agent Based Model and Decision Optimization Platform

    Science.gov (United States)

    Ghoveisi, H.; Al Dughaishi, U.; Kiker, G.

    2017-12-01

    Maintaining water quality in agricultural watersheds is a worldwide challenge, especially where furrow irrigation is being practiced. The Yakima River Basin watershed in south central Washington State, (USA) is an example of these impacted areas with elevated load of sediments and other agricultural products due to runoff from furrow-irrigated fields. Within the Yakima basin, the Granger Drain watershed (area of 75 km2) is particularly challenged in this regard with more than 400 flood-irrigated individual parcels (area of 21 km2) growing a variety of crops from maize to grapes. Alternatives for improving water quality from furrow-irrigated parcels include vegetated filter strip (VFS) implementation, furrow water application efficiency, polyacrylamide (PAM) application and irrigation scheduling. These alternatives were simulated separately and in combinations to explore potential Best Management Practices (BMPs) for runoff-related-pollution reduction in a spatially explicit, agent based modeling system (QnD:GrangerDrain). Two regulatory scenarios were tested to BMP adoption within individual parcels. A blanket-style regulatory scenario simulated a total of 60 BMP combinations implemented in all 409 furrow-irrigated parcels. A second regulatory scenario simulated the BMPs in 119 furrow-irrigated parcels designated as "hotspots" based on a standard 12 Mg ha-1 seasonal sediment load. The simulated cumulative runoff and sediment loading from all BMP alternatives were ranked using Multiple Criteria Decision Analysis (MCDA), specifically the Stochastic Multi-Attribute Acceptability Analysis (SMAA) method. Several BMP combinations proved successful in reducing loads below a 25 NTU (91 mg L-1) regulatory sediment concentration. The QnD:GrangerDrain simulations and subsequent MCDA ranking revealed that the BMP combinations of 5 m-VFS and high furrow water efficiency were highly ranked alternatives for both the blanket and hotspot scenarios.

  5. Producing Distribution Maps for a Spatially-Explicit Ecosystem Model Using Large Monitoring and Environmental Databases and a Combination of Interpolation and Extrapolation

    Directory of Open Access Journals (Sweden)

    Arnaud Grüss

    2018-01-01

    Full Text Available To be able to simulate spatial patterns of predator-prey interactions, many spatially-explicit ecosystem modeling platforms, including Atlantis, need to be provided with distribution maps defining the annual or seasonal spatial distributions of functional groups and life stages. We developed a methodology combining extrapolation and interpolation of the predictions made by statistical habitat models to produce distribution maps for the fish and invertebrates represented in the Atlantis model of the Gulf of Mexico (GOM Large Marine Ecosystem (LME (“Atlantis-GOM”. This methodology consists of: (1 compiling a large monitoring database, gathering all the fisheries-independent and fisheries-dependent data collected in the northern (U.S. GOM since 2000; (2 compiling a large environmental database, storing all the environmental parameters known to influence the spatial distribution patterns of fish and invertebrates of the GOM; (3 fitting binomial generalized additive models (GAMs to the large monitoring and environmental databases, and geostatistical binomial generalized linear mixed models (GLMMs to the large monitoring database; and (4 employing GAM predictions to infer spatial distributions in the southern GOM, and GLMM predictions to infer spatial distributions in the U.S. GOM. Thus, our methodology allows for reasonable extrapolation in the southern GOM based on a large amount of monitoring and environmental data, and for interpolation in the U.S. GOM accurately reflecting the probability of encountering fish and invertebrates in that region. We used an iterative cross-validation procedure to validate GAMs. When a GAM did not pass the validation test, we employed a GAM for a related functional group/life stage to generate distribution maps for the southern GOM. In addition, no geostatistical GLMMs were fit for the functional groups and life stages whose depth, longitudinal and latitudinal ranges within the U.S. GOM are not entirely covered by

  6. Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris population in central India

    Directory of Open Access Journals (Sweden)

    Mriganka Shekhar Sarkar

    2017-11-01

    and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Discussion Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve.

  7. Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India.

    Science.gov (United States)

    Sarkar, Mriganka Shekhar; Krishnamurthy, Ramesh; Johnson, Jeyaraj A; Sen, Subharanjan; Saha, Goutam Kumar

    2017-01-01

    of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve.

  8. Caribou, individual-based modeling and mega-industry in central West Greenland

    DEFF Research Database (Denmark)

    Raundrup, Katrine; Nymand, Josephine; Nabe-Nielsen, Jacob

    in West Greenland. In a newly started PhD-project the focus will be the implementation of spatially explicit individual based modeling (IBM). The project relies on existing knowledge on caribou behavior and feeding ecology along with data on variations in the vegetation. By relating vegetation, snow......Spatial distribution of caribou (Rangifer tarandus groenlandicus) in West Greenland is a result of both short and long term changes in the Arctic landscape. To understand present distribution 40 satellite collars were deployed on 40 female caribou in the Akia-Maniitsoq herd, central West Greenland...... in an area. Further, enhanced or lowered hunting pressure, and changed weather conditions can be studied using IBM. Thus, both short and long term changes in the landscape will be studied and provide insights in how the specific spatial changes impact caribou in West Greenland....

  9. Spatially explicit shallow landslide susceptibility mapping over large areas

    Science.gov (United States)

    Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

    2011-01-01

    Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

  10. Evaluating spatially explicit burn probabilities for strategic fire management planning

    Science.gov (United States)

    C. Miller; M.-A. Parisien; A. A. Ager; M. A. Finney

    2008-01-01

    Spatially explicit information on the probability of burning is necessary for virtually all strategic fire and fuels management planning activities, including conducting wildland fire risk assessments, optimizing fuel treatments, and prevention planning. Predictive models providing a reliable estimate of the annual likelihood of fire at each point on the landscape have...

  11. Are individual based models a suitable approach to estimate population vulnerability? - a case study

    Directory of Open Access Journals (Sweden)

    Eva Maria Griebeler

    2011-04-01

    Full Text Available European populations of the Large Blue Butterfly Maculinea arion have experienced severe declines in the last decades, especially in the northern part of the species range. This endangered lycaenid butterfly needs two resources for development: flower buds of specific plants (Thymus spp., Origanum vulgare, on which young caterpillars briefly feed, and red ants of the genus Myrmica, whose nests support caterpillars during a prolonged final instar. I present an analytically solvable deterministic model to estimate the vulnerability of populations of M. arion. Results obtained from the sensitivity analysis of this mathematical model (MM are contrasted to the respective results that had been derived from a spatially explicit individual based model (IBM for this butterfly. I demonstrate that details in landscape configuration which are neglected by the MM but are easily taken into consideration by the IBM result in a different degree of intraspecific competition of caterpillars on flower buds and within host ant nests. The resulting differences in mortalities of caterpillars lead to erroneous estimates of the extinction risk of a butterfly population living in habitat with low food plant coverage and low abundance in host ant nests. This observation favors the use of an individual based modeling approach over the deterministic approach at least for the management of this threatened butterfly.

  12. DISPLACE: a dynamic, individual-based model for spatial fishing planning and effort displacement: Integrating underlying fish population models

    DEFF Research Database (Denmark)

    Bastardie, Francois; Nielsen, J. Rasmus; Miethe, Tanja

    or to the alteration of individual fishing patterns. We demonstrate that integrating the spatial activity of vessels and local fish stock abundance dynamics allow for interactions and more realistic predictions of fishermen behaviour, revenues and stock abundance......We previously developed a spatially explicit, individual-based model (IBM) evaluating the bio-economic efficiency of fishing vessel movements between regions according to the catching and targeting of different species based on the most recent high resolution spatial fishery data. The main purpose...... was to test the effects of alternative fishing effort allocation scenarios related to fuel consumption, energy efficiency (value per litre of fuel), sustainable fish stock harvesting, and profitability of the fisheries. The assumption here was constant underlying resource availability. Now, an advanced...

  13. An individual-based growth and competition model for coastal redwood forest restoration

    Science.gov (United States)

    van Mantgem, Phillip J.; Das, Adrian J.

    2014-01-01

    Thinning treatments to accelerate coastal redwood forest stand development are in wide application, but managers have yet to identify prescriptions that might best promote Sequoia sempervirens (Lamb. ex D. Don) Endl. (redwood) growth. The creation of successful thinning prescriptions would be aided by identifying the underlying mechanisms governing how individual tree growth responds to competitive environments in coastal redwood forests. We created a spatially explicit individual-based model of tree competition and growth parameterized using surveys of upland redwood forests at Redwood National Park, California. We modeled competition for overstory trees (stems ≥ 20 cm stem diameter at breast height, 1.37 m (dbh)) as growth reductions arising from sizes, distances, and species identity of competitor trees. Our model explained up to half of the variation in individual tree growth, suggesting that neighborhood crowding is an important determinant of growth in this forest type. We used our model to simulate the effects of novel thinning prescriptions (e.g., 40% stand basal area removal) for redwood forest restoration, concluding that these treatments could lead to substantial growth releases, particularly for S. sempervirens. The results of this study, along with continued improvements to our model, will help to determine spacing and species composition that best encourage growth.

  14. Simulating individual-based models of epidemics in hierarchical networks

    NARCIS (Netherlands)

    Quax, R.; Bader, D.A.; Sloot, P.M.A.

    2009-01-01

    Current mathematical modeling methods for the spreading of infectious diseases are too simplified and do not scale well. We present the Simulator of Epidemic Evolution in Complex Networks (SEECN), an efficient simulator of detailed individual-based models by parameterizing separate dynamics

  15. Individual-based modeling of ecological and evolutionary processes

    NARCIS (Netherlands)

    DeAngelis, D.L.; Mooij, W.M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential and difference equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis

  16. Individual-based modelling and control of bovine brucellosis

    Science.gov (United States)

    Nepomuceno, Erivelton G.; Barbosa, Alípio M.; Silva, Marcos X.; Perc, Matjaž

    2018-05-01

    We present a theoretical approach to control bovine brucellosis. We have used individual-based modelling, which is a network-type alternative to compartmental models. Our model thus considers heterogeneous populations, and spatial aspects such as migration among herds and control actions described as pulse interventions are also easily implemented. We show that individual-based modelling reproduces the mean field behaviour of an equivalent compartmental model. Details of this process, as well as flowcharts, are provided to facilitate the reproduction of the presented results. We further investigate three numerical examples using real parameters of herds in the São Paulo state of Brazil, in scenarios which explore eradication, continuous and pulsed vaccination and meta-population effects. The obtained results are in good agreement with the expected behaviour of this disease, which ultimately showcases the effectiveness of our theory.

  17. Linking land use change to recreational fishery valuation with a spatially explicit behavior model: A case study from Tampa Bay, FL USA

    Science.gov (United States)

    Drawing a link between habitat change and production and delivery of ecosystem services is a priority in coastal estuarine ecosystems. This link is needed to fully understand how human communities can influence ecosystem sustainability. Mechanistic modeling tools are highly fun...

  18. A spatially-explicit count data regression for modeling the density of forest cockchafer (Melolontha hippocastani larvae in the Hessian Ried (Germany

    Directory of Open Access Journals (Sweden)

    Matthias Schmidt

    2014-10-01

    Full Text Available Background In this paper, a regression model for predicting the spatial distribution of forest cockchafer larvae in the Hessian Ried region (Germany is presented. The forest cockchafer, a native biotic pest, is a major cause of damage in forests in this region particularly during the regeneration phase. The model developed in this study is based on a systematic sample inventory of forest cockchafer larvae by excavation across the Hessian Ried. These forest cockchafer larvae data were characterized by excess zeros and overdispersion. Methods Using specific generalized additive regression models, different discrete distributions, including the Poisson, negative binomial and zero-inflated Poisson distributions, were compared. The methodology employed allowed the simultaneous estimation of non-linear model effects of causal covariates and, to account for spatial autocorrelation, of a 2-dimensional spatial trend function. In the validation of the models, both the Akaike information criterion (AIC and more detailed graphical procedures based on randomized quantile residuals were used. Results The negative binomial distribution was superior to the Poisson and the zero-inflated Poisson distributions, providing a near perfect fit to the data, which was proven in an extensive validation process. The causal predictors found to affect the density of larvae significantly were distance to water table and percentage of pure clay layer in the soil to a depth of 1 m. Model predictions showed that larva density increased with an increase in distance to the water table up to almost 4 m, after which it remained constant, and with a reduction in the percentage of pure clay layer. However this latter correlation was weak and requires further investigation. The 2-dimensional trend function indicated a strong spatial effect, and thus explained by far the highest proportion of variation in larva density. Conclusions As such the model can be used to support forest

  19. Modelling Deep Water Habitats to Develop a Spatially Explicit, Fine Scale Understanding of the Distribution of the Western Rock Lobster, Panulirus cygnus

    Science.gov (United States)

    Hovey, Renae K.; Van Niel, Kimberly P.; Bellchambers, Lynda M.; Pember, Matthew B.

    2012-01-01

    Background The western rock lobster, Panulirus cygnus, is endemic to Western Australia and supports substantial commercial and recreational fisheries. Due to and its wide distribution and the commercial and recreational importance of the species a key component of managing western rock lobster is understanding the ecological processes and interactions that may influence lobster abundance and distribution. Using terrain analyses and distribution models of substrate and benthic biota, we assess the physical drivers that influence the distribution of lobsters at a key fishery site. Methods and Findings Using data collected from hydroacoustic and towed video surveys, 20 variables (including geophysical, substrate and biota variables) were developed to predict the distributions of substrate type (three classes of reef, rhodoliths and sand) and dominant biota (kelp, sessile invertebrates and macroalgae) within a 40 km2 area about 30 km off the west Australian coast. Lobster presence/absence data were collected within this area using georeferenced pots. These datasets were used to develop a classification tree model for predicting the distribution of the western rock lobster. Interestingly, kelp and reef were not selected as predictors. Instead, the model selected geophysical and geomorphic scalar variables, which emphasise a mix of terrain within limited distances. The model of lobster presence had an adjusted D2 of 64 and an 80% correct classification. Conclusions Species distribution models indicate that juxtaposition in fine scale terrain is most important to the western rock lobster. While key features like kelp and reef may be important to lobster distribution at a broad scale, it is the fine scale features in terrain that are likely to define its ecological niche. Determining the most appropriate landscape configuration and scale will be essential to refining niche habitats and will aid in selecting appropriate sites for protecting critical lobster habitats. PMID

  20. Modelling deep water habitats to develop a spatially explicit, fine scale understanding of the distribution of the western rock lobster, Panulirus cygnus.

    Directory of Open Access Journals (Sweden)

    Renae K Hovey

    Full Text Available BACKGROUND: The western rock lobster, Panulirus cygnus, is endemic to Western Australia and supports substantial commercial and recreational fisheries. Due to and its wide distribution and the commercial and recreational importance of the species a key component of managing western rock lobster is understanding the ecological processes and interactions that may influence lobster abundance and distribution. Using terrain analyses and distribution models of substrate and benthic biota, we assess the physical drivers that influence the distribution of lobsters at a key fishery site. METHODS AND FINDINGS: Using data collected from hydroacoustic and towed video surveys, 20 variables (including geophysical, substrate and biota variables were developed to predict the distributions of substrate type (three classes of reef, rhodoliths and sand and dominant biota (kelp, sessile invertebrates and macroalgae within a 40 km(2 area about 30 km off the west Australian coast. Lobster presence/absence data were collected within this area using georeferenced pots. These datasets were used to develop a classification tree model for predicting the distribution of the western rock lobster. Interestingly, kelp and reef were not selected as predictors. Instead, the model selected geophysical and geomorphic scalar variables, which emphasise a mix of terrain within limited distances. The model of lobster presence had an adjusted D(2 of 64 and an 80% correct classification. CONCLUSIONS: Species distribution models indicate that juxtaposition in fine scale terrain is most important to the western rock lobster. While key features like kelp and reef may be important to lobster distribution at a broad scale, it is the fine scale features in terrain that are likely to define its ecological niche. Determining the most appropriate landscape configuration and scale will be essential to refining niche habitats and will aid in selecting appropriate sites for protecting critical

  1. Modelling deep water habitats to develop a spatially explicit, fine scale understanding of the distribution of the western rock lobster, Panulirus cygnus.

    Science.gov (United States)

    Hovey, Renae K; Van Niel, Kimberly P; Bellchambers, Lynda M; Pember, Matthew B

    2012-01-01

    The western rock lobster, Panulirus cygnus, is endemic to Western Australia and supports substantial commercial and recreational fisheries. Due to and its wide distribution and the commercial and recreational importance of the species a key component of managing western rock lobster is understanding the ecological processes and interactions that may influence lobster abundance and distribution. Using terrain analyses and distribution models of substrate and benthic biota, we assess the physical drivers that influence the distribution of lobsters at a key fishery site. Using data collected from hydroacoustic and towed video surveys, 20 variables (including geophysical, substrate and biota variables) were developed to predict the distributions of substrate type (three classes of reef, rhodoliths and sand) and dominant biota (kelp, sessile invertebrates and macroalgae) within a 40 km(2) area about 30 km off the west Australian coast. Lobster presence/absence data were collected within this area using georeferenced pots. These datasets were used to develop a classification tree model for predicting the distribution of the western rock lobster. Interestingly, kelp and reef were not selected as predictors. Instead, the model selected geophysical and geomorphic scalar variables, which emphasise a mix of terrain within limited distances. The model of lobster presence had an adjusted D(2) of 64 and an 80% correct classification. Species distribution models indicate that juxtaposition in fine scale terrain is most important to the western rock lobster. While key features like kelp and reef may be important to lobster distribution at a broad scale, it is the fine scale features in terrain that are likely to define its ecological niche. Determining the most appropriate landscape configuration and scale will be essential to refining niche habitats and will aid in selecting appropriate sites for protecting critical lobster habitats.

  2. Eco-SpaCE: An object-oriented, spatially explicit model to assess the risk of multiple environmental stressors on terrestrial vertebrate populations

    International Nuclear Information System (INIS)

    Loos, Mark; Ragas, Ad M.J.; Plasmeijer, Rinus; Schipper, Aafke M.; Hendriks, A. Jan

    2010-01-01

    Wildlife organisms are exposed to a combination of chemical, biological and physical stressors. Information about the relative impact of each stressor can support management decisions, e.g., by the allocation of resources to counteract those stressors that cause most harm. The present paper introduces Eco-SpaCE; a novel receptor-oriented cumulative exposure model for wildlife species that includes relevant ecological processes such as spatial habitat variation, food web relations, predation, and life history. A case study is presented in which the predicted mortality due to cadmium contamination is compared with the predicted mortality due to flooding, starvation, and predation for three small mammal species (Wood mouse, Common vole, and European mole) and a predator (Little owl) living in a lowland floodplain along the river Rhine in The Netherlands. Results indicated that cadmium is the principal stressor for European mole and Little owl populations. Wood mouse and Common vole population densities were mainly influenced by flooding and food availability. Their estimated population sizes were consistent with numbers reported in literature. Predictions for cadmium accumulation and flooding stress were in agreement with field data. The large uncertainty around cadmium toxicity for wildlife leads to the conclusion that more species-specific ecotoxicological data is required for more realistic risk assessments. The predictions for starvation were subject to the limited quantitative information on biomass obtainable as food for vertebrates. It is concluded that the modelling approach employed in Eco-SpaCE, combining ecology with ecotoxicology, provides a viable option to explore the relative contribution of contamination to the overall stress in an ecosystem. This can help environmental managers to prioritize management options, and to reduce local risks.

  3. Individual-based modeling of ecological and evolutionary processes

    Science.gov (United States)

    DeAngelis, Donald L.; Mooij, Wolf M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

  4. Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

    Directory of Open Access Journals (Sweden)

    Johannes P M Heinonen

    Full Text Available Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

  5. Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

    Science.gov (United States)

    Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

    2014-01-01

    Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

  6. Spatially explicit shallow landslide susceptibility mapping over large areas

    Science.gov (United States)

    Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

    2011-01-01

    Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

  7. An Individual-based Probabilistic Model for Fish Stock Simulation

    Directory of Open Access Journals (Sweden)

    Federico Buti

    2010-08-01

    Full Text Available We define an individual-based probabilistic model of a sole (Solea solea behaviour. The individual model is given in terms of an Extended Probabilistic Discrete Timed Automaton (EPDTA, a new formalism that is introduced in the paper and that is shown to be interpretable as a Markov decision process. A given EPDTA model can be probabilistically model-checked by giving a suitable translation into syntax accepted by existing model-checkers. In order to simulate the dynamics of a given population of soles in different environmental scenarios, an agent-based simulation environment is defined in which each agent implements the behaviour of the given EPDTA model. By varying the probabilities and the characteristic functions embedded in the EPDTA model it is possible to represent different scenarios and to tune the model itself by comparing the results of the simulations with real data about the sole stock in the North Adriatic sea, available from the recent project SoleMon. The simulator is presented and made available for its adaptation to other species.

  8. INDIVIDUAL-BASED MODELS: POWERFUL OR POWER STRUGGLE?

    Science.gov (United States)

    Willem, L; Stijven, S; Hens, N; Vladislavleva, E; Broeckhove, J; Beutels, P

    2015-01-01

    Individual-based models (IBMs) offer endless possibilities to explore various research questions but come with high model complexity and computational burden. Large-scale IBMs have become feasible but the novel hardware architectures require adapted software. The increased model complexity also requires systematic exploration to gain thorough system understanding. We elaborate on the development of IBMs for vaccine-preventable infectious diseases and model exploration with active learning. Investment in IBM simulator code can lead to significant runtime reductions. We found large performance differences due to data locality. Sorting the population once, reduced simulation time by a factor two. Storing person attributes separately instead of using person objects also seemed more efficient. Next, we improved model performance up to 70% by structuring potential contacts based on health status before processing disease transmission. The active learning approach we present is based on iterative surrogate modelling and model-guided experimentation. Symbolic regression is used for nonlinear response surface modelling with automatic feature selection. We illustrate our approach using an IBM for influenza vaccination. After optimizing the parameter spade, we observed an inverse relationship between vaccination coverage and the clinical attack rate reinforced by herd immunity. These insights can be used to focus and optimise research activities, and to reduce both dimensionality and decision uncertainty.

  9. Individual based and mean-field modeling of direct aggregation

    KAUST Repository

    Burger, Martin

    2013-10-01

    We introduce two models of biological aggregation, based on randomly moving particles with individual stochasticity depending on the perceived average population density in their neighborhood. In the firstorder model the location of each individual is subject to a density-dependent random walk, while in the second-order model the density-dependent random walk acts on the velocity variable, together with a density-dependent damping term. The main novelty of our models is that we do not assume any explicit aggregative force acting on the individuals; instead, aggregation is obtained exclusively by reducing the individual stochasticity in response to higher perceived density. We formally derive the corresponding mean-field limits, leading to nonlocal degenerate diffusions. Then, we carry out the mathematical analysis of the first-order model, in particular, we prove the existence of weak solutions and show that it allows for measure-valued steady states. We also perform linear stability analysis and identify conditions for pattern formation. Moreover, we discuss the role of the nonlocality for well-posedness of the first-order model. Finally, we present results of numerical simulations for both the first- and second-order model on the individual-based and continuum levels of description. 2012 Elsevier B.V. All rights reserved.

  10. Individual based and mean-field modeling of direct aggregation

    KAUST Repository

    Burger, Martin; Haskovec, Jan; Wolfram, Marie-Therese

    2013-01-01

    We introduce two models of biological aggregation, based on randomly moving particles with individual stochasticity depending on the perceived average population density in their neighborhood. In the firstorder model the location of each individual is subject to a density-dependent random walk, while in the second-order model the density-dependent random walk acts on the velocity variable, together with a density-dependent damping term. The main novelty of our models is that we do not assume any explicit aggregative force acting on the individuals; instead, aggregation is obtained exclusively by reducing the individual stochasticity in response to higher perceived density. We formally derive the corresponding mean-field limits, leading to nonlocal degenerate diffusions. Then, we carry out the mathematical analysis of the first-order model, in particular, we prove the existence of weak solutions and show that it allows for measure-valued steady states. We also perform linear stability analysis and identify conditions for pattern formation. Moreover, we discuss the role of the nonlocality for well-posedness of the first-order model. Finally, we present results of numerical simulations for both the first- and second-order model on the individual-based and continuum levels of description. 2012 Elsevier B.V. All rights reserved.

  11. Spatially explicit spectral analysis of point clouds and geospatial data

    Science.gov (United States)

    Buscombe, Daniel D.

    2015-01-01

    The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is

  12. Spatially explicit spectral analysis of point clouds and geospatial data

    Science.gov (United States)

    Buscombe, Daniel

    2016-01-01

    The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described

  13. Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies.

    Science.gov (United States)

    Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J Andrew

    2010-11-01

    We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture-recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

  14. Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management

    Science.gov (United States)

    Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Sanchez-Chopitea, Erika; Mauch, Kimberly; Niell, Lara; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

    2016-05-20

    Successful adaptive management hinges largely upon integrating new and improved sources of information as they become available. As a timely example of this tenet, we updated a management decision support tool that was previously developed for greater sage-grouse (Centrocercus urophasianus, hereinafter referred to as “sage-grouse”) populations in Nevada and California. Specifically, recently developed spatially explicit habitat maps derived from empirical data played a key role in the conservation of this species facing listing under the Endangered Species Act. This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California (Coates and others, 2014, 2016). These updates include: (1) adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998; (2) integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models; (3) modifying the spatial extent of the analyses to match newly available vegetation layers; (4) explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering); (5) accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones; (6) integrating the three seasonal maps into a composite map of annual relative habitat suitability; (7) deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage

  15. Spatially explicit and stochastic simulation of forest landscape fire disturbance and succession

    Science.gov (United States)

    Hong S. He; David J. Mladenoff

    1999-01-01

    Understanding disturbance and recovery of forest landscapes is a challenge because of complex interactions over a range of temporal and spatial scales. Landscape simulation models offer an approach to studying such systems at broad scales. Fire can be simulated spatially using mechanistic or stochastic approaches. We describe the fire module in a spatially explicit,...

  16. An example of population-level risk assessments for small mammals using individual-based population models.

    Science.gov (United States)

    Schmitt, Walter; Auteri, Domenica; Bastiansen, Finn; Ebeling, Markus; Liu, Chun; Luttik, Robert; Mastitsky, Sergey; Nacci, Diane; Topping, Chris; Wang, Magnus

    2016-01-01

    This article presents a case study demonstrating the application of 3 individual-based, spatially explicit population models (IBMs, also known as agent-based models) in ecological risk assessments to predict long-term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long-term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios. © 2015 SETAC.

  17. Evaluating impacts of fire management strategies on native and invasive plants using an individual-based model

    Science.gov (United States)

    Gangur, Alexander N.; Fill, Jennifer M.; Northfield, Tobin D.; van de Wiel, Marco

    2017-04-01

    The capacity for species to coexist and potentially exclude one another can broadly be attributed to drivers that influence fitness differences (such as competitive ability) and niche differences (such as environmental change). These drivers, and thus the determinants of coexistence they influence, can interact and fluctuate both spatially and temporally. Understanding the spatiotemporal variation in niche and fitness differences in systems prone to fluctuating drivers, such as fire, can help to inform the management of invasive species. In the Cape floristic region of South Africa, invasive Pinus pinaster seedlings are strong competitors in the post-burn environment of the fire-driven Fynbos vegetation. In this, system native Protea spp. are especially vulnerable to unseasonal burns, but seasonal prescribed (Summer) burns are thought to present a high safety risk. Together, these issues have limited the appeal of prescribed burn management as an alternative to costly manual eradication of P. pinaster. Using a spatially-explicit field-of-neighbourhood individual-based model, we represent the drivers of spatiotemporal variation in niche differences (driven by fire regimes) and fitness differences (driven by competitive ability). In doing so, we evaluate optimal fire management strategies to a) control invasive P. pinaster in the Cape floristic region of South Africa, while b) minimizing deleterious effects of management on native Protea spp. The scarcity of appropriate data for model calibration has been problematic for models in invasion biology, but we use recent advances in Approximate Bayesian Computing techniques to overcome this limitation. We present early conclusions on the viability of prescribed burn management to control P. pinaster in South Africa.

  18. Spatially explicit animal response to composition of habitat

    Science.gov (United States)

    Benjamin P. Pauli; Nicholas P. McCann; Patrick A. Zollner; Robert Cummings; Jonathan H. Gilbert; Eric J. Gustafson

    2013-01-01

    Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-...

  19. Individual-based model for radiation risk assessment

    Science.gov (United States)

    Smirnova, O.

    A mathematical model is developed which enables one to predict the life span probability for mammals exposed to radiation. It relates statistical biometric functions with statistical and dynamic characteristics of an organism's critical system. To calculate the dynamics of the latter, the respective mathematical model is used too. This approach is applied to describe the effects of low level chronic irradiation on mice when the hematopoietic system (namely, thrombocytopoiesis) is the critical one. For identification of the joint model, experimental data on hematopoiesis in nonirradiated and irradiated mice, as well as on mortality dynamics of those in the absence of radiation are utilized. The life span probability and life span shortening predicted by the model agree with corresponding experimental data. Modeling results show the significance of ac- counting the variability of the individual radiosensitivity of critical system cells when estimating the radiation risk. These findings are corroborated by clinical data on persons involved in the elimination of the Chernobyl catastrophe after- effects. All this makes it feasible to use the model for radiation risk assessments for cosmonauts and astronauts on long-term missions such as a voyage to Mars or a lunar colony. In this case the model coefficients have to be determined by making use of the available data for humans. Scenarios for the dynamics of dose accumulation during space flights should also be taken into account.

  20. Individual-based modeling of fish: Linking to physical models and water quality.

    Energy Technology Data Exchange (ETDEWEB)

    Rose, K.A.

    1997-08-01

    The individual-based modeling approach for the simulating fish population and community dynamics is gaining popularity. Individual-based modeling has been used in many other fields, such as forest succession and astronomy. The popularity of the individual-based approach is partly a result of the lack of success of the more aggregate modeling approaches traditionally used for simulating fish population and community dynamics. Also, recent recognition that it is often the atypical individual that survives has fostered interest in the individual-based approach. Two general types of individual-based models are distribution and configuration. Distribution models follow the probability distributions of individual characteristics, such as length and age. Configuration models explicitly simulate each individual; the sum over individuals being the population. DeAngelis et al (1992) showed that, when distribution and configuration models were formulated from the same common pool of information, both approaches generated similar predictions. The distribution approach was more compact and general, while the configuration approach was more flexible. Simple biological changes, such as making growth rate dependent on previous days growth rates, were easy to implement in the configuration version but prevented simple analytical solution of the distribution version.

  1. Markovian Building Blocks for Individual-Based Modelling

    DEFF Research Database (Denmark)

    Nilsson, Lars Anders Fredrik

    2007-01-01

    previous exposure to Markov chains in continuous time (see e.g. Grimmett and Stirzaker, 2001)). Markovian arrival processes are very general point processes that are relatively easy to analyse. They have, so far, been largely unknown to the ecological modelling community. The article C deals...

  2. Assessment on the rates and potentials of soil organic carbon sequestration in agricultural lands in Japan using a process-based model and spatially explicit land-use change inventories - Part 2: Future potentials

    Science.gov (United States)

    Yagasaki, Y.; Shirato, Y.

    2014-08-01

    Future potentials of the sequestration of soil organic carbon (SOC) in agricultural lands in Japan were estimated using a simulation system we recently developed to simulate SOC stock change at country-scale under varying land-use change, climate, soil, and agricultural practices, in a spatially explicit manner. Simulation was run from 1970 to 2006 with historical inventories, and subsequently to 2020 with future scenarios of agricultural activity comprised of various agricultural policy targets advocated by the Japanese government. Furthermore, the simulation was run subsequently until 2100 while forcing no temporal changes in land-use and agricultural activity to investigate duration and course of SOC stock change at country scale. A scenario with an increased rate of organic carbon input to agricultural fields by intensified crop rotation in combination with the suppression of conversion of agricultural lands to other land-use types was found to have a greater reduction of CO2 emission by enhanced soil carbon sequestration, but only under a circumstance in which the converted agricultural lands will become settlements that were considered to have a relatively lower rate of organic carbon input. The size of relative reduction of CO2 emission in this scenario was comparable to that in another contrasting scenario (business-as-usual scenario of agricultural activity) in which a relatively lower rate of organic matter input to agricultural fields was assumed in combination with an increased rate of conversion of the agricultural fields to unmanaged grasslands through abandonment. Our simulation experiment clearly demonstrated that net-net-based accounting on SOC stock change, defined as the differences between the emissions and removals during the commitment period and the emissions and removals during a previous period (base year or base period of Kyoto Protocol), can be largely influenced by variations in future climate. Whereas baseline-based accounting, defined

  3. Calculation of Individual Tree Water Use in a Bornean Tropical Rain Forest Using Individual-Based Dynamic Vegetation Model SEIB-DGVM

    Science.gov (United States)

    Nakai, T.; Kumagai, T.; Saito, T.; Matsumoto, K.; Kume, T.; Nakagawa, M.; Sato, H.

    2015-12-01

    Bornean tropical rain forests are among the moistest biomes of the world with abundant rainfall throughout the year, and considered to be vulnerable to a change in the rainfall regime; e.g., high tree mortality was reported in such forests induced by a severe drought associated with the ENSO event in 1997-1998. In order to assess the effect (risk) of future climate change on eco-hydrology in such tropical rain forests, it is important to understand the water use of trees individually, because the vulnerability or mortality of trees against climate change can depend on the size of trees. Therefore, we refined the Spatially Explicit Individual-Based Dynamic Global Vegetation Model (SEIB-DGVM) so that the transpiration and its control by stomata are calculated for each individual tree. By using this model, we simulated the transpiration of each tree and its DBH-size dependency, and successfully reproduced the measured data of sap flow of trees and eddy covariance flux data obtained in a Bornean lowland tropical rain forest in Lambir Hills National Park, Sarawak, Malaysia.

  4. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    Science.gov (United States)

    2011-01-01

    The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular

  5. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    Directory of Open Access Journals (Sweden)

    Hongoh Valerie

    2011-12-01

    Full Text Available Abstract The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector

  6. Analyzing Variability in Landscape Nutrient Loading Using Spatially-Explicit Maps in the Great Lakes Basin

    Science.gov (United States)

    Hamlin, Q. F.; Kendall, A. D.; Martin, S. L.; Whitenack, H. D.; Roush, J. A.; Hannah, B. A.; Hyndman, D. W.

    2017-12-01

    Excessive loading of nitrogen and phosphorous to the landscape has caused biologically and economically damaging eutrophication and harmful algal blooms in the Great Lakes Basin (GLB) and across the world. We mapped source-specific loads of nitrogen and phosphorous to the landscape using broadly available data across the GLB. SENSMap (Spatially Explicit Nutrient Source Map) is a 30m resolution snapshot of nutrient loads ca. 2010. We use these maps to study variable nutrient loading and provide this information to watershed managers through NOAA's GLB Tipping Points Planner. SENSMap individually maps nutrient point sources and six non-point sources: 1) atmospheric deposition, 2) septic tanks, 3) non-agricultural chemical fertilizer, 4) agricultural chemical fertilizer, 5) manure, and 6) nitrogen fixation from legumes. To model source-specific loads at high resolution, SENSMap synthesizes a wide range of remotely sensed, surveyed, and tabular data. Using these spatially explicit nutrient loading maps, we can better calibrate local land use-based water quality models and provide insight to watershed managers on how to focus nutrient reduction strategies. Here we examine differences in dominant nutrient sources across the GLB, and how those sources vary by land use. SENSMap's high resolution, source-specific approach offers a different lens to understand nutrient loading than traditional semi-distributed or land use based models.

  7. The role of spatial information in the preservation of the shrimp nursery function of mangroves: A spatially explicit bio-economic model for the assessment of land use trade-offs

    NARCIS (Netherlands)

    Zavalloni, M.; Groeneveld, R.A.; Zwieten, van P.A.M.

    2014-01-01

    Conversion to aquaculture affects the provision of important ecosystem services provided by mangrove ecosystems, and this effect depends strongly on the location of the conversion. We introduce in a bioeconomic mathematical programming model relevant spatial elements that affect the provision of the

  8. Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry

    Directory of Open Access Journals (Sweden)

    Míriam R. García

    2018-01-01

    Full Text Available A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modeling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behavior of bacteria inside populations. In this work, we overcome this problem by estimating the individual behavior of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modeling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modeling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modeling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that P. acidilactici divide into two successive parallel planes.

  9. The role of spatial information in the preservation of the shrimp nursery function of mangroves: a spatially explicit bio-economic model for the assessment of land use trade-offs.

    Science.gov (United States)

    Zavalloni, Matteo; Groeneveld, Rolf A; van Zwieten, Paul A M

    2014-10-01

    Conversion to aquaculture affects the provision of important ecosystem services provided by mangrove ecosystems, and this effect depends strongly on the location of the conversion. We introduce in a bio-economic mathematical programming model relevant spatial elements that affect the provision of the nursery habitat service of mangroves: (1) direct or indirect connection of mangroves to watercourses; (2) the spatial allocation of aquaculture ponds; and (3) the presence of non-linear relations between mangrove extent and juvenile recruitment to wild shrimp populations. By tracing out the production possibilities frontier of wild and cultivated shrimp, the model assesses the role of spatial information in the trade-off between aquaculture and the nursery habitat function using spatial elements relevant to our model of a mangrove area in Ca Mau Province, Viet Nam. Results show that where mangrove forests have to coexist with shrimp aquaculture ponds, the inclusion of specific spatial information on ecosystem functions in considerations of land allocation can achieve aquaculture benefits while largely preserving the economic benefits generated by the nursery habitat function. However, if spatial criteria are ignored, ill-advised land allocation decisions can easily lead to a collapse of the mangrove's nursery function. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Structure and sensitivity analysis of individual-based predator–prey models

    International Nuclear Information System (INIS)

    Imron, Muhammad Ali; Gergs, Andre; Berger, Uta

    2012-01-01

    The expensive computational cost of sensitivity analyses has hampered the use of these techniques for analysing individual-based models in ecology. A relatively cheap computational cost, referred to as the Morris method, was chosen to assess the relative effects of all parameters on the model’s outputs and to gain insights into predator–prey systems. Structure and results of the sensitivity analysis of the Sumatran tiger model – the Panthera Population Persistence (PPP) and the Notonecta foraging model (NFM) – were compared. Both models are based on a general predation cycle and designed to understand the mechanisms behind the predator–prey interaction being considered. However, the models differ significantly in their complexity and the details of the processes involved. In the sensitivity analysis, parameters that directly contribute to the number of prey items killed were found to be most influential. These were the growth rate of prey and the hunting radius of tigers in the PPP model as well as attack rate parameters and encounter distance of backswimmers in the NFM model. Analysis of distances in both of the models revealed further similarities in the sensitivity of the two individual-based models. The findings highlight the applicability and importance of sensitivity analyses in general, and screening design methods in particular, during early development of ecological individual-based models. Comparison of model structures and sensitivity analyses provides a first step for the derivation of general rules in the design of predator–prey models for both practical conservation and conceptual understanding. - Highlights: ► Structure of predation processes is similar in tiger and backswimmer model. ► The two individual-based models (IBM) differ in space formulations. ► In both models foraging distance is among the sensitive parameters. ► Morris method is applicable for the sensitivity analysis even of complex IBMs.

  11. Analysis of habitat-selection rules using an individual-based model

    Science.gov (United States)

    Steven F. Railsback; Bret C. Harvey

    2002-01-01

    Abstract - Despite their promise for simulating natural complexity,individual-based models (IBMs) are rarely used for ecological research or resource management. Few IBMs have been shown to reproduce realistic patterns of behavior by individual organisms.To test our IBM of stream salmonids and draw conclusions about foraging theory,we analyzed the IBM ’s ability to...

  12. Contrast of degraded and restored stream habitat using an individual-based salmon model

    Science.gov (United States)

    S. F. Railsback; M. Gard; Bret Harvey; Jason White; J.K.H. Zimmerman

    2013-01-01

    Stream habitat restoration projects are popular, but can be expensive and difficult to evaluate. We describe inSALMO, an individual-based model designed to predict habitat effects on freshwater life stages (spawning through juvenile out-migration) of salmon. We applied inSALMO to Clear Creek, California, simulating the production of total and large (>5 cm FL)...

  13. Spatially explicit modelling of extreme weather and climate events ...

    African Journals Online (AJOL)

    The reality of climate change continues to influence the intensity and frequency of extreme weather events such as heat waves, droughts, floods, and landslides. The impacts of the cumulative interplay of these extreme weather and climate events variation continue to perturb governments causing a scramble into formation ...

  14. Integrating Biodiversity into Biosphere-Atmosphere Interactions Using Individual-Based Models (IBM)

    Science.gov (United States)

    Wang, B.; Shugart, H. H., Jr.; Lerdau, M.

    2017-12-01

    A key component regulating complex, nonlinear, and dynamic biosphere-atmosphere interactions is the inherent diversity of biological systems. The model frameworks currently widely used, i.e., Plant Functional Type models) do not even begin to capture the metabolic and taxonomic diversity found in many terrestrial systems. We propose that a transition from PFT-based to individual-based modeling approaches (hereafter referred to as IBM) is essential for integrating biodiversity into research on biosphere-atmosphere interactions. The proposal emerges from our studying the interactions of forests with atmospheric processes in the context of climate change using an individual-based forest volatile organic compounds model, UVAFME-VOC. This individual-based model can explicitly simulate VOC emissions based on an explicit modelling of forest dynamics by computing the growth, death, and regeneration of each individual tree of different species and their competition for light, moisture, and nutrient, from which system-level VOC emissions are simulated by explicitly computing and summing up each individual's emissions. We found that elevated O3 significantly altered the forest dynamics by favoring species that are O3-resistant, which, meanwhile, are producers of isoprene. Such compositional changes, on the one hand, resulted in unsuppressed forest productivity and carbon stock because of the compensation by O3-resistant species. On the other hand, with more isoprene produced arising from increased producers, a possible positive feedback loop between tropospheric O3 and forest thereby emerged. We also found that climate warming will not always stimulate isoprene emissions because warming simultaneously reduces isoprene emissions by causing a decline in the abundance of isoprene-emitting species. These results suggest that species diversity is of great significance and that individual-based modelling strategies should be applied in studying biosphere-atmosphere interactions.

  15. An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis

    Directory of Open Access Journals (Sweden)

    Corrie H. Allen

    2016-05-01

    Full Text Available Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from

  16. Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus Using Unstructured Sampling Data.

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    Femke Broekhuis

    Full Text Available Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

  17. Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

    Science.gov (United States)

    Broekhuis, Femke; Gopalaswamy, Arjun M

    2016-01-01

    Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

  18. Spatially explicit population estimates for black bears based on cluster sampling

    Science.gov (United States)

    Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

    2017-01-01

    We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

  19. Spatially Explicit Assessment of Agricultural Water Equilibrium in the Korean Peninsula

    Directory of Open Access Journals (Sweden)

    Chul-Hee Lim

    2018-01-01

    Full Text Available In agriculture, balancing water use and retention is an issue dealt with in most regions and for many crops. In this study, we suggest agricultural water equilibrium (AWE as a new concept that can facilitate a spatially explicit management of agricultural water. This concept is based on the principle of supply and demand of agricultural water, where the virtual water content of crops (VWC can be defined as the demand, and cropland water budget (CWB as the supply. For assessing the AWE of the Korean Peninsula, we quantified the CWB based on the hydrological cycle and the VWC of rice, a key crop in the Peninsula. Five factors, namely crop yield, growing season evapotranspiration, annual evapotranspiration, runoff, and annual precipitation, were used to assess the AWE, of which the first four were estimated using the spatially explicit large-scale crop model, Geographical Information System (GIS-based Environmental Policy Integrated Climate (GEPIC. The CWB and VWC were calculated for a period of three decades, and the AWE was computed by deducting the VWC from the CWB. Our results show a latitudinal difference across the Korean Peninsula. On analyzing the AWE of the major river basins, we found most basins in North Korea showed very low values inferring unsustainable overconsumption of water. The latitudinal difference in AWE is a reflectance of the latitudinal changes in the VWC and CWB. This can be explained by decoupling the demand and supply of agricultural water. Although the AWE values presented in this study were not absolute, the values were sufficient to explain the latitudinal change, and the demand and supply of agricultural water, and establish the usefulness of the indicator.

  20. Assessment on the rates and potentials of soil organic carbon sequestration in agricultural lands in Japan using a process-based model and spatially explicit land-use change inventories - Part 1: Historical trend and validation based on nation-wide soil monitoring

    Science.gov (United States)

    Yagasaki, Y.; Shirato, Y.

    2014-08-01

    In order to estimate a country-scale soil organic carbon (SOC) stock change in agricultural lands in Japan, while taking into account the effect of land-use changes, climate, different agricultural activities and the nature of soils, a spatially explicit model simulation system was developed using Rothamsted Carbon Model (RothC) with an integration of spatial and temporal inventories. Simulation was run from 1970 to 2008 with historical inventories. Simulated SOC stock was compared with observations in a nation-wide stationary monitoring program conducted during 1979-1998. Historical land-use change, characterized by a large decline in the area of paddy fields as well as a small but continuous decline in the area of orchards, occurred along with a relatively large increase in upland crop fields, unmanaged grasslands, and settlements (i.e. conversion of agricultural fields due to urbanization or abandoning). Results of the simulation on SOC stock change under varying land-use change indicated that land-use conversion from agricultural fields to settlements or other lands, as well as that from paddy fields to croplands have likely been an increasing source of CO2 emission, due to the reduction of organic carbon input to soils and the enhancement of SOC decomposition through transition of soil environment from anaerobic to aerobic conditions. The area-weighted mean concentrations of the simulated SOC stocks calculated for major soil groups under paddy fields and upland crop fields were comparable to those observed in the monitoring. Whereas in orchards, the simulated SOC stocks were underestimated. As the results of simulation indicated that SOC stock change under managed grasslands and settlements has been likely a major sink and source of CO2 emission at country-scale, respectively, validation of SOC stock change under these land-use types, which could not have been accomplished due to limited availability or a lack of measurement, remains a forthcoming challenge.

  1. Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

    Science.gov (United States)

    Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

    2016-02-07

    Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Sensitivity analysis of an individual-based model for simulation of influenza epidemics.

    Directory of Open Access Journals (Sweden)

    Elaine O Nsoesie

    Full Text Available Individual-based epidemiology models are increasingly used in the study of influenza epidemics. Several studies on influenza dynamics and evaluation of intervention measures have used the same incubation and infectious period distribution parameters based on the natural history of influenza. A sensitivity analysis evaluating the influence of slight changes to these parameters (in addition to the transmissibility would be useful for future studies and real-time modeling during an influenza pandemic.In this study, we examined individual and joint effects of parameters and ranked parameters based on their influence on the dynamics of simulated epidemics. We also compared the sensitivity of the model across synthetic social networks for Montgomery County in Virginia and New York City (and surrounding metropolitan regions with demographic and rural-urban differences. In addition, we studied the effects of changing the mean infectious period on age-specific epidemics. The research was performed from a public health standpoint using three relevant measures: time to peak, peak infected proportion and total attack rate. We also used statistical methods in the design and analysis of the experiments. The results showed that: (i minute changes in the transmissibility and mean infectious period significantly influenced the attack rate; (ii the mean of the incubation period distribution appeared to be sufficient for determining its effects on the dynamics of epidemics; (iii the infectious period distribution had the strongest influence on the structure of the epidemic curves; (iv the sensitivity of the individual-based model was consistent across social networks investigated in this study and (v age-specific epidemics were sensitive to changes in the mean infectious period irrespective of the susceptibility of the other age groups. These findings suggest that small changes in some of the disease model parameters can significantly influence the uncertainty

  3. USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

    Science.gov (United States)

    Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...

  4. An individual-based probabilistic model for simulating fisheries population dynamics

    Directory of Open Access Journals (Sweden)

    Jie Cao

    2016-12-01

    Full Text Available The purpose of stock assessment is to support managers to provide intelligent decisions regarding removal from fish populations. Errors in assessment models may have devastating impacts on the population fitness and negative impacts on the economy of the resource users. Thus, accuracte estimations of population size, growth rates are critical for success. Evaluating and testing the behavior and performance of stock assessment models and assessing the consequences of model mis-specification and the impact of management strategies requires an operating model that accurately describe the dynamics of the target species, and can resolve spatial and seasonal changes. In addition, the most thorough evaluations of assessment models use an operating model that takes a different form than the assessment model. This paper presents an individual-based probabilistic model used to simulate the complex dynamics of populations and their associated fisheries. Various components of population dynamics are expressed as random Bernoulli trials in the model and detailed life and fishery histories of each individual are tracked over their life span. The simulation model is designed to be flexible so it can be used for different species and fisheries. It can simulate mixing among multiple stocks and link stock-recruit relationships to environmental factors. Furthermore, the model allows for flexibility in sub-models (e.g., growth and recruitment and model assumptions (e.g., age- or size-dependent selectivity. This model enables the user to conduct various simulation studies, including testing the performance of assessment models under different assumptions, assessing the impacts of model mis-specification and evaluating management strategies.

  5. An individual-based model of skipjack tuna (Katsuwonus pelamis) movement in the tropical Pacific ocean

    Science.gov (United States)

    Scutt Phillips, Joe; Sen Gupta, Alex; Senina, Inna; van Sebille, Erik; Lange, Michael; Lehodey, Patrick; Hampton, John; Nicol, Simon

    2018-05-01

    The distribution of marine species is often modeled using Eulerian approaches, in which changes to population density or abundance are calculated at fixed locations in space. Conversely, Lagrangian, or individual-based, models simulate the movement of individual particles moving in continuous space, with broader-scale patterns such as distribution being an emergent property of many, potentially adaptive, individuals. These models offer advantages in examining dynamics across spatiotemporal scales and making comparisons with observations from individual-scale data. Here, we introduce and describe such a model, the Individual-based Kinesis, Advection and Movement of Ocean ANimAls model (Ikamoana), which we use to replicate the movement processes of an existing Eulerian model for marine predators (the Spatial Ecosystem and Population Dynamics Model, SEAPODYM). Ikamoana simulates the movement of either individual or groups of animals by physical ocean currents, habitat-dependent stochastic movements (kinesis), and taxis movements representing active searching behaviours. Applying our model to Pacific skipjack tuna (Katsuwonus pelamis), we show that it accurately replicates the evolution of density distribution simulated by SEAPODYM with low time-mean error and a spatial correlation of density that exceeds 0.96 at all times. We demonstrate how the Lagrangian approach permits easy tracking of individuals' trajectories for examining connectivity between different regions, and show how the model can provide independent estimates of transfer rates between commonly used assessment regions. In particular, we find that retention rates in most assessment regions are considerably smaller (up to a factor of 2) than those estimated by this population of skipjack's primary assessment model. Moreover, these rates are sensitive to ocean state (e.g. El Nino vs La Nina) and so assuming fixed transfer rates between regions may lead to spurious stock estimates. A novel feature of the

  6. A standard protocol for describing individual-based and agent-based models

    Science.gov (United States)

    Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

    2006-01-01

    Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

  7. An individual-based model of transmission of resistant bacteria in a veterinary teaching hospital.

    Directory of Open Access Journals (Sweden)

    Neeraj Suthar

    Full Text Available Veterinary nosocomial infections caused by antibiotic resistant bacteria cause increased morbidity, higher cost and length of treatment and increased zoonotic risk because of the difficulty in treating them. In this study, an individual-based model was developed to investigate the effects of movements of canine patients among ten areas (transmission points within a veterinary teaching hospital, and the effects of these movements on transmission of antibiotic susceptible and resistant pathogens. The model simulates contamination of transmission points, healthcare workers, and patients as well as the effects of decontamination of transmission points, disinfection of healthcare workers, and antibiotic treatments of canine patients. The model was parameterized using data obtained from hospital records, information obtained by interviews with hospital staff, and the published literature. The model suggested that transmission resulting from contact with healthcare workers was common, and that certain transmission points (housing wards, diagnostics room, and the intensive care unit presented higher risk for transmission than others (lobby and surgery. Sensitivity analyses using a range of parameter values demonstrated that the risk of acquisition of colonization by resistant pathogens decreased with shorter patient hospital stays (P<0.0001, more frequent decontamination of transmission points and disinfection of healthcare workers (P<0.0001 and better compliance of healthcare workers with hygiene practices (P<0.0001. More frequent decontamination of heavily trafficked transmission points was especially effective at reducing transmission of the model pathogen.

  8. Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge.

    Science.gov (United States)

    Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M

    2007-09-15

    Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.

  9. Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

    Science.gov (United States)

    Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

    2018-03-01

    GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

  10. Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

    Science.gov (United States)

    Jin, Z.; Azzari, G.; Lobell, D. B.

    2016-12-01

    Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

  11. A spatially explicit risk assessment approach: Cetaceans and marine traffic in the Pelagos Sanctuary (Mediterranean Sea.

    Directory of Open Access Journals (Sweden)

    Maria Grazia Pennino

    Full Text Available Spatially explicit risk assessment is an essential component of Marine Spatial Planning (MSP, which provides a comprehensive framework for managing multiple uses of the marine environment, minimizing environmental impacts and conflicts among users. In this study, we assessed the risk of the exposure to high intensity vessel traffic areas for the three most abundant cetacean species (Stenella coeruleoalba, Tursiops truncatus and Balaenoptera physalus in the southern area of the Pelagos Sanctuary, which is the only pelagic Marine Protected Area (MPA for marine mammals in the Mediterranean Sea. In particular, we modeled the occurrence of the three cetacean species as a function of habitat variables in June by using hierarchical Bayesian spatial-temporal models. Similarly, we modelled the marine traffic intensity in order to find high risk areas and estimated the potential conflict due to the overlap with the cetacean home ranges. Results identified two main hot-spots of high intensity marine traffic in the area, which partially overlap with the area of presence of the studied species. Our findings emphasize the need for nationally relevant and transboundary planning and management measures for these marine species.

  12. Patterns in the spatial distribution of Peruvian anchovy ( Engraulis ringens) revealed by spatially explicit fishing data

    Science.gov (United States)

    Bertrand, Sophie; Díaz, Erich; Lengaigne, Matthieu

    2008-10-01

    Peruvian anchovy ( Engraulis ringens) stock abundance is tightly driven by the high and unpredictable variability of the Humboldt Current Ecosystem. Management of the fishery therefore cannot rely on mid- or long-term management policy alone but needs to be adaptive at relatively short time scales. Regular acoustic surveys are performed on the stock at intervals of 2 to 4 times a year, but there is a need for more time continuous monitoring indicators to ensure that management can respond at suitable time scales. Existing literature suggests that spatially explicit data on the location of fishing activities could be used as a proxy for target stock distribution. Spatially explicit commercial fishing data could therefore guide adaptive management decisions at shorter time scales than is possible through scientific stock surveys. In this study we therefore aim to (1) estimate the position of fishing operations for the entire fleet of Peruvian anchovy purse-seiners using the Peruvian satellite vessel monitoring system (VMS), and (2) quantify the extent to which the distribution of purse-seine sets describes anchovy distribution. To estimate fishing set positions from vessel tracks derived from VMS data we developed a methodology based on artificial neural networks (ANN) trained on a sample of fishing trips with known fishing set positions (exact fishing positions are known for approximately 1.5% of the fleet from an at-sea observer program). The ANN correctly identified 83% of the real fishing sets and largely outperformed comparative linear models. This network is then used to forecast fishing operations for those trips where no observers were onboard. To quantify the extent to which fishing set distribution was correlated to stock distribution we compared three metrics describing features of the distributions (the mean distance to the coast, the total area of distribution, and a clustering index) for concomitant acoustic survey observations and fishing set positions

  13. An individual-based model for population viability analysis of humpback chub in Grand Canyon

    Science.gov (United States)

    Pine, William Pine; Healy, Brian; Smith, Emily Omana; Trammell, Melissa; Speas, Dave; Valdez, Rich; Yard, Mike; Walters, Carl; Ahrens, Rob; Vanhaverbeke, Randy; Stone, Dennis; Wilson, Wade

    2013-01-01

    We developed an individual-based population viability analysis model (females only) for evaluating risk to populations from catastrophic events or conservation and research actions. This model tracks attributes (size, weight, viability, etc.) for individual fish through time and then compiles this information to assess the extinction risk of the population across large numbers of simulation trials. Using a case history for the Little Colorado River population of Humpback Chub Gila cypha in Grand Canyon, Arizona, we assessed extinction risk and resiliency to a catastrophic event for this population and then assessed a series of conservation actions related to removing specific numbers of Humpback Chub at different sizes for conservation purposes, such as translocating individuals to establish other spawning populations or hatchery refuge development. Our results suggested that the Little Colorado River population is generally resilient to a single catastrophic event and also to removals of larvae and juveniles for conservation purposes, including translocations to establish new populations. Our results also suggested that translocation success is dependent on similar survival rates in receiving and donor streams and low emigration rates from recipient streams. In addition, translocating either large numbers of larvae or small numbers of large juveniles has generally an equal likelihood of successful population establishment at similar extinction risk levels to the Little Colorado River donor population. Our model created a transparent platform to consider extinction risk to populations from catastrophe or conservation actions and should prove useful to managers assessing these risks for endangered species such as Humpback Chub.

  14. Modular and Spatially Explicit: A Novel Approach to System Dynamics

    Science.gov (United States)

    The Open Modeling Environment (OME) is an open-source System Dynamics (SD) simulation engine which has been created as a joint project between Oregon State University and the US Environmental Protection Agency. It is designed around a modular implementation, and provides a standa...

  15. Uniting statistical and individual-based approaches for animal movement modelling.

    Science.gov (United States)

    Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

    2014-01-01

    The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

  16. Spatially Explicit Assessment of Ecosystem Resilience: An Approach to Adapt to Climate Changes

    Directory of Open Access Journals (Sweden)

    Haiming Yan

    2014-01-01

    Full Text Available The ecosystem resilience plays a key role in maintaining a steady flow of ecosystem services and enables quick and flexible responses to climate changes, and maintaining or restoring the ecosystem resilience of forests is a necessary societal adaptation to climate change; however, there is a great lack of spatially explicit ecosystem resilience assessments. Drawing on principles of the ecosystem resilience highlighted in the literature, we built on the theory of dissipative structures to develop a conceptual model of the ecosystem resilience of forests. A hierarchical indicator system was designed with the influencing factors of the forest ecosystem resilience, including the stand conditions and the ecological memory, which were further disaggregated into specific indicators. Furthermore, indicator weights were determined with the analytic hierarchy process (AHP and the coefficient of variation method. Based on the remote sensing data and forest inventory data and so forth, the resilience index of forests was calculated. The result suggests that there is significant spatial heterogeneity of the ecosystem resilience of forests, indicating it is feasible to generate large-scale ecosystem resilience maps with this assessment model, and the results can provide a scientific basis for the conservation of forests, which is of great significance to the climate change mitigation.

  17. Spatially Explicit Analysis of Water Footprints in the UK

    Directory of Open Access Journals (Sweden)

    John Barrett

    2010-12-01

    Full Text Available The Water Footprint, as an indicator of water consumption has become increasingly popular for analyzing environmental issues associated with the use of water resources in the global supply chain of consumer goods. This is particularly relevant for countries like the UK, which increasingly rely on products produced elsewhere in the world and thus impose pressures on foreign water resources. Existing studies calculating water footprints are mostly based on process analysis, and results are mainly available at the national level. The current paper assesses the domestic and foreign water requirements for UK final consumption by applying an environmentally extended multi-regional input-output model in combination with geo-demographic consumer segmentation data. This approach allows us to calculate water footprints (both direct and indirect for different products as well as different geographies within the UK. We distinguished between production and consumption footprints where the former is the total water consumed from the UK domestic water resources by the production activities in the UK and the latter is the total water consumed from both domestic and global water resources to satisfy the UK domestic final consumption. The results show that the production water footprint is 439 m3/cap/year, 85% of which is for the final consumption in the UK itself. The average consumption water footprint of the UK is more than three times bigger than the UK production water footprint in 2006. About half of the UK consumption water footprints were associated with imports from Non-OECD countries (many of which are water-scarce, while around 19% were from EU-OECD countries, and only 3% from Non-EU-OECD countries. We find that the water footprint differs considerably across sub-national geographies in the UK, and the differences are as big as 273 m3/cap/year for the internal water footprint and 802 m3/cap/year for the external water footprint. Our results suggest

  18. sGD: software for estimating spatially explicit indices of genetic diversity.

    Science.gov (United States)

    Shirk, A J; Cushman, S A

    2011-09-01

    Anthropogenic landscape changes have greatly reduced the population size, range and migration rates of many terrestrial species. The small local effective population size of remnant populations favours loss of genetic diversity leading to reduced fitness and adaptive potential, and thus ultimately greater extinction risk. Accurately quantifying genetic diversity is therefore crucial to assessing the viability of small populations. Diversity indices are typically calculated from the multilocus genotypes of all individuals sampled within discretely defined habitat patches or larger regional extents. Importantly, discrete population approaches do not capture the clinal nature of populations genetically isolated by distance or landscape resistance. Here, we introduce spatial Genetic Diversity (sGD), a new spatially explicit tool to estimate genetic diversity based on grouping individuals into potentially overlapping genetic neighbourhoods that match the population structure, whether discrete or clinal. We compared the estimates and patterns of genetic diversity using patch or regional sampling and sGD on both simulated and empirical populations. When the population did not meet the assumptions of an island model, we found that patch and regional sampling generally overestimated local heterozygosity, inbreeding and allelic diversity. Moreover, sGD revealed fine-scale spatial heterogeneity in genetic diversity that was not evident with patch or regional sampling. These advantages should provide a more robust means to evaluate the potential for genetic factors to influence the viability of clinal populations and guide appropriate conservation plans. © 2011 Blackwell Publishing Ltd.

  19. Behavioral response to contamination risk information in a spatially explicit groundwater environment: Experimental evidence

    Science.gov (United States)

    Li, Jingyuan; Michael, Holly A.; Duke, Joshua M.; Messer, Kent D.; Suter, Jordan F.

    2014-08-01

    This paper assesses the effectiveness of aquifer monitoring information in achieving more sustainable use of a groundwater resource in the absence of management policy. Groundwater user behavior in the face of an irreversible contamination threat is studied by applying methods of experimental economics to scenarios that combine a physics-based, spatially explicit, numerical groundwater model with different representations of information about an aquifer and its risk of contamination. The results suggest that the threat of catastrophic contamination affects pumping decisions: pumping is significantly reduced in experiments where contamination is possible compared to those where pumping cost is the only factor discouraging groundwater use. The level of information about the state of the aquifer also affects extraction behavior. Pumping rates differ when information that synthesizes data on aquifer conditions (a "risk gauge") is provided, despite invariant underlying economic incentives, and this result does not depend on whether the risk information is location-specific or from a whole aquifer perspective. Interestingly, users increase pumping when the risk gauge signals good aquifer status compared to a no-gauge treatment. When the gauge suggests impending contamination, however, pumping declines significantly, resulting in a lower probability of contamination. The study suggests that providing relatively simple aquifer condition guidance derived from monitoring data can lead to more sustainable use of groundwater resources.

  20. Spatially explicit simulation of peatland hydrology and carbon dioxide exchange

    International Nuclear Information System (INIS)

    Sonnentag, O.

    2008-01-01

    A recent version of the Boreal Ecosystem Productivity Simulator (BEPS) was extended and modified to include northern peatlands. This thesis evaluated the BEPS-TerrainLab using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was revised to represent the multi-layer canopy and processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. A quick and reliable method was also developed to determine shrub LAI with the LAI-2000 plant canopy analyzer. A large number of LAI data was collected at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple end member spectral unmixing to allow for separate tree and shrub LAI mapping in ombrotrophic peatlands. The methodology was also adapted for use in minerotrophic peatlands and their surrounding landscapes. These LAI maps within the BEPS-TerrainLab represented the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandhill fen. The study examined the influence of mesoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. The results suggested that a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology should be included in future peatland ecosystem modelling efforts in order to allow for a more realistic simulation of the soil water balance in peatlands and to reduce uncertainties in carbon dioxide and methane annual fluxes from wetlands

  1. Spatially explicit simulation of peatland hydrology and carbon dioxide exchange

    Energy Technology Data Exchange (ETDEWEB)

    Sonnentag, O.

    2008-08-01

    A recent version of the Boreal Ecosystem Productivity Simulator (BEPS) was extended and modified to include northern peatlands. This thesis evaluated the BEPS-TerrainLab using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was revised to represent the multi-layer canopy and processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. A quick and reliable method was also developed to determine shrub LAI with the LAI-2000 plant canopy analyzer. A large number of LAI data was collected at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple end member spectral unmixing to allow for separate tree and shrub LAI mapping in ombrotrophic peatlands. The methodology was also adapted for use in minerotrophic peatlands and their surrounding landscapes. These LAI maps within the BEPS-TerrainLab represented the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandhill fen. The study examined the influence of mesoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. The results suggested that a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology should be included in future peatland ecosystem modelling efforts in order to allow for a more realistic simulation of the soil water balance in peatlands and to reduce uncertainties in carbon dioxide and methane annual fluxes from wetlands.

  2. Maintenance of polygenic sex determination in a fluctuating environment: an individual-based model.

    Science.gov (United States)

    Bateman, A W; Anholt, B R

    2017-05-01

    R. A. Fisher predicted that individuals should invest equally in offspring of both sexes, and that the proportion of males and females produced (the primary sex ratio) should evolve towards 1:1 when unconstrained. For many species, sex determination is dependent on sex chromosomes, creating a strong tendency for balanced sex ratios, but in other cases, multiple autosomal genes interact to determine sex. In such cases, the maintenance of multiple sex-determining alleles at multiple loci and the consequent among-family variability in sex ratios presents a puzzle, as theory predicts that such systems should be unstable. Theory also predicts that environmental influences on sex can complicate outcomes of genetic sex determination, and that population structure may play a role. Tigriopus californicus, a copepod that lives in splash-pool metapopulations and exhibits polygenic and environment-dependent sex determination, presents a test case for relevant theory. We use this species as a model for parameterizing an individual-based simulation to investigate conditions that could maintain polygenic sex determination. We find that metapopulation structure can delay the degradation of polygenic sex determination and that periods of alternating frequency-dependent selection, imposed by seasonal fluctuations in environmental conditions, can maintain polygenic sex determination indefinitely. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

  3. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    KAUST Repository

    Matsumoto, Tomotaka

    2015-11-24

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic

  4. Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

    Science.gov (United States)

    Ginovart, Marta

    2014-01-01

    The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study…

  5. A spatially explicit estimate of the prewhaling abundance of the endangered North Atlantic right whale.

    Science.gov (United States)

    Monsarrat, Sophie; Pennino, M Grazia; Smith, Tim D; Reeves, Randall R; Meynard, Christine N; Kaplan, David M; Rodrigues, Ana S L

    2016-08-01

    The North Atlantic right whale (NARW) (Eubalaena glacialis) is one of the world's most threatened whales. It came close to extinction after nearly a millennium of exploitation and currently persists as a population of only approximately 500 individuals. Setting appropriate conservation targets for this species requires an understanding of its historical population size, as a baseline for measuring levels of depletion and progress toward recovery. This is made difficult by the scarcity of records over this species' long whaling history. We sought to estimate the preexploitation population size of the North Atlantic right whale and understand how this species was distributed across its range. We used a spatially explicit data set on historical catches of North Pacific right whales (NPRWs) (Eubalaena japonica) to model the relationship between right whale relative density and the environment during the summer feeding season. Assuming the 2 right whale species select similar environments, we projected this model to the North Atlantic to predict how the relative abundance of NARWs varied across their range. We calibrated these relative abundances with estimates of the NPRW total prewhaling population size to obtain high and low estimates for the overall NARW population size prior to exploitation. The model predicted 9,075-21,328 right whales in the North Atlantic. The current NARW population is thus <6% of the historical North Atlantic carrying capacity and has enormous potential for recovery. According to the model, in June-September NARWs concentrated in 2 main feeding areas: east of the Grand Banks of Newfoundland and in the Norwegian Sea. These 2 areas may become important in the future as feeding grounds and may already be used more regularly by this endangered species than is thought. © 2015 Society for Conservation Biology.

  6. A spatially explicit and quantitative vulnerability assessment of ecosystem service change in Europe

    NARCIS (Netherlands)

    Metzger, M.J.; Schröter, D.; Leemans, R.; Cramer, W.

    2008-01-01

    Environmental change alters ecosystem functioning and may put the provision of services to human at risk. This paper presents a spatially explicit and quantitative assessment of the corresponding vulnerability for Europe, using a new framework designed to answer multidisciplinary policy relevant

  7. The assessment of mangrove biomass and carbon in West Africa: a spatially explicit analytical framework

    Science.gov (United States)

    Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Carl C. Trettin

    2015-01-01

    Mangrove forests are highly productive and have large carbon sinks while also providing numerous goods and ecosystem services. However, effective management and conservation of the mangrove forests are often dependent on spatially explicit assessments of the resource. Given the remote and highly dispersed nature of mangroves, estimation of biomass and carbon...

  8. Spatially explicit analysis of field inventories for national forest carbon monitoring

    Directory of Open Access Journals (Sweden)

    David C. Marvin

    2016-06-01

    Full Text Available Abstract Background Tropical forests provide a crucial carbon sink for a sizable portion of annual global CO2 emissions. Policies that incentivize tropical forest conservation by monetizing forest carbon ultimately depend on accurate estimates of national carbon stocks, which are often based on field inventory sampling. As an exercise to understand the limitations of field inventory sampling, we tested whether two common field-plot sampling approaches could accurately estimate carbon stocks across approximately 76 million ha of Perúvian forests. A 1-ha resolution LiDAR-based map of carbon stocks was used as a model of the country’s carbon geography. Results Both field inventory sampling approaches worked well in estimating total national carbon stocks, almost always falling within 10 % of the model national total. However, the sampling approaches were unable to produce accurate spatially-explicit estimates of the carbon geography of Perú, with estimates falling within 10 % of the model carbon geography across no more than 44 % of the country. We did not find any associations between carbon stock errors from the field plot estimates and six different environmental variables. Conclusions Field inventory plot sampling does not provide accurate carbon geography for a tropical country with wide ranging environmental gradients such as Perú. The lack of association between estimated carbon errors and environmental variables suggests field inventory sampling results from other nations would not differ from those reported here. Tropical forest nations should understand the risks associated with primarily field-based sampling approaches, and consider alternatives leading to more effective forest conservation and climate change mitigation.

  9. Integral assessment of floodplains as a basis for spatially-explicit flood loss forecasts

    Science.gov (United States)

    Zischg, Andreas Paul; Mosimann, Markus; Weingartner, Rolf

    2016-04-01

    A key aspect of disaster prevention is flood discharge forecasting which is used for early warning and therefore as a decision support for intervention forces. Hereby, the phase between the issued forecast and the time when the expected flood occurs is crucial for an optimal planning of the intervention. Typically, river discharge forecasts cover the regional level only, i.e. larger catchments. However, it is important to note that these forecasts are not useable directly for specific target groups on local level because these forecasts say nothing about the consequences of the predicted flood in terms of affected areas, number of exposed residents and houses. For this, on one hand simulations of the flooding processes and on the other hand data of vulnerable objects are needed. Furthermore, flood modelling in a high spatial and temporal resolution is required for robust flood loss estimation. This is a resource-intensive task from a computing time point of view. Therefore, in real-time applications flood modelling in 2D is not suited. Thus, forecasting flood losses in the short-term (6h-24h in advance) requires a different approach. Here, we propose a method to downscale the river discharge forecast to a spatially-explicit flood loss forecast. The principal procedure is to generate as many flood scenarios as needed in advance to represent the flooded areas for all possible flood hydrographs, e.g. very high peak discharges of short duration vs. high peak discharges with high volumes. For this, synthetic flood hydrographs were derived from the hydrologic time series. Then, the flooded areas of each scenario were modelled with a 2D flood simulation model. All scenarios were intersected with the dataset of vulnerable objects, in our case residential, agricultural and industrial buildings with information about the number of residents, the object-specific vulnerability, and the monetary value of the objects. This dataset was prepared by a data-mining approach. For each

  10. Low Tree-Growth Elasticity of Forest Biomass Indicated by an Individual-Based Model

    Directory of Open Access Journals (Sweden)

    Robbie A. Hember

    2018-01-01

    Full Text Available Environmental conditions and silviculture fundamentally alter the metabolism of individual trees and, therefore, need to be studied at that scale. However, changes in forest biomass density (Mg C ha−1 may be decoupled from changes in growth (kg C year−1 when the latter also accelerates the life cycle of trees and strains access to light, nutrients, and water. In this study, we refer to an individual-based model of forest biomass dynamics to constrain the magnitude of system feedbacks associated with ontogeny and competition and estimate the scaling relationship between changes in tree growth and forest biomass density. The model was driven by fitted equations of annual aboveground biomass growth (Gag, probability of recruitment (Pr, and probability of mortality (Pm parameterized against field observations of black spruce (Picea mariana (Mill. BSP, interior Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn. Franco, and western hemlock (Tsuga heterophylla (Raf. Sarg.. A hypothetical positive step-change in mean tree growth was imposed half way through the simulations and landscape-scale responses were then evaluated by comparing pre- and post-stimulus periods. Imposing a 100% increase in tree growth above calibrated predictions (i.e., contemporary rates only translated into 36% to 41% increases in forest biomass density. This corresponded with a tree-growth elasticity of forest biomass (εG,SB ranging from 0.33 to 0.55. The inelastic nature of stand biomass density was attributed to the dependence of mortality on intensity of competition and tree size, which decreased stand density by 353 to 495 trees ha−1, and decreased biomass residence time by 10 to 23 years. Values of εG,SB depended on the magnitude of the stimulus. For example, a retrospective scenario in which tree growth increased from 50% below contemporary rates up to contemporary rates indicated values of εG,SB ranging from 0.66 to 0.75. We conclude that: (1 effects of

  11. A Spatially Explicit Method to Assess the Economic Suitability of a Forest Road Network for Timber Harvest in Steep Terrain

    Directory of Open Access Journals (Sweden)

    Leo Gallus Bont

    2018-03-01

    Full Text Available Despite relatively high road density in the forests of Switzerland, a large percentage of that road network does not fulfill best practice requirements. Before upgrading or rebuilding the road network, harvesting planners must first determine which areas have insufficient access. Traditional assessment methods tend to only report specific values such as road density. However, those values do not identify the exact parcels or areas that are inaccessible. Here, we present a model that assesses the economic suitability of each timbered parcel for wood-harvesting operations, including tree-felling and processing, and off- and on-road transport (hauling, based on the existing road network. The entire wood supply chain from forest (standing trees to a virtual pile at the border of the planning unit was captured. This method was particularly designed for steep terrain and was tested in the Canton of Grisons in Switzerland. Compared with classical approaches, such as the road density concept, which only deliver average values, this new method enables planners to assess the development of a road network in a spatially explicit manner and to easily identify the reason and the location of shortcomings in the road network. Moreover, while other related spatially explicit approaches focus only on harvesting operations, the assessment method proposed here also includes limitations (road standards of the road network.

  12. Global Research on Artificial Intelligence from 1990–2014: Spatially-Explicit Bibliometric Analysis

    Directory of Open Access Journals (Sweden)

    Jiqiang Niu

    2016-05-01

    Full Text Available In this article, we conducted the evaluation of artificial intelligence research from 1990–2014 by using bibliometric analysis. We introduced spatial analysis and social network analysis as geographic information retrieval methods for spatially-explicit bibliometric analysis. This study is based on the analysis of data obtained from database of the Science Citation Index Expanded (SCI-Expanded and Conference Proceedings Citation Index-Science (CPCI-S. Our results revealed scientific outputs, subject categories and main journals, author productivity and geographic distribution, international productivity and collaboration, and hot issues and research trends. The growth of article outputs in artificial intelligence research has exploded since the 1990s, along with increasing collaboration, reference, and citations. Computer science and engineering were the most frequently-used subject categories in artificial intelligence studies. The top twenty productive authors are distributed in countries with a high investment of research and development. The United States has the highest number of top research institutions in artificial intelligence, producing most single-country and collaborative articles. Although there is more and more collaboration among institutions, cooperation, especially international ones, are not highly prevalent in artificial intelligence research as expected. The keyword analysis revealed interesting research preferences, confirmed that methods, models, and application are in the central position of artificial intelligence. Further, we found interesting related keywords with high co-occurrence frequencies, which have helped identify new models and application areas in recent years. Bibliometric analysis results from our study will greatly facilitate the understanding of the progress and trends in artificial intelligence, in particular, for those researchers interested in domain-specific AI-driven problem-solving. This will be

  13. Creating a spatially-explicit index: a method for assessing the global wildfire-water risk

    Science.gov (United States)

    Robinne, François-Nicolas; Parisien, Marc-André; Flannigan, Mike; Miller, Carol; Bladon, Kevin D.

    2017-04-01

    The wildfire-water risk (WWR) has been defined as the potential for wildfires to adversely affect water resources that are important for downstream ecosystems and human water needs for adequate water quantity and quality, therefore compromising the security of their water supply. While tools and methods are numerous for watershed-scale risk analysis, the development of a toolbox for the large-scale evaluation of the wildfire risk to water security has only started recently. In order to provide managers and policy-makers with an adequate tool, we implemented a method for the spatial analysis of the global WWR based on the Driving forces-Pressures-States-Impacts-Responses (DPSIR) framework. This framework relies on the cause-and-effect relationships existing between the five categories of the DPSIR chain. As this approach heavily relies on data, we gathered an extensive set of spatial indicators relevant to fire-induced hydrological hazards and water consumption patterns by human and natural communities. When appropriate, we applied a hydrological routing function to our indicators in order to simulate downstream accumulation of potentially harmful material. Each indicator was then assigned a DPSIR category. We collapsed the information in each category using a principal component analysis in order to extract the most relevant pixel-based information provided by each spatial indicator. Finally, we compiled our five categories using an additive indexation process to produce a spatially-explicit index of the WWR. A thorough sensitivity analysis has been performed in order to understand the relationship between the final risk values and the spatial pattern of each category used during the indexation. For comparison purposes, we aggregated index scores by global hydrological regions, or hydrobelts, to get a sense of regional DPSIR specificities. This rather simple method does not necessitate the use of complex physical models and provides a scalable and efficient tool

  14. Spatially explicit assessment of ecosystem services in China's Loess Plateau: Patterns, interactions, drivers, and implications

    Science.gov (United States)

    Jiang, Chong; Zhang, Haiyan; Zhang, Zhidong

    2018-02-01

    Human demands for natural resources have significantly changed the natural landscape and induced ecological degradation and associated ecosystem services. An understanding of the patterns, interactions, and drivers of ecosystem services is essential for the ecosystem management and guiding targeted land use policy-making. The Losses Plateau (LP) provides ecosystem services including the carbon sequestration and soil retention, and exerts tremendous impacts on the midstream and downstream of the Yellow River. Three dominant ecosystem services between 2000 and 2012 within the LP were presented based on multiple source datasets and biophysical models. In addition, paired ecosystem services interactions were quantified using the correlation analysis and constraint line approach. The main conclusions are as follows. It was observed that the warming and wetting climate and ecological program jointly promoted the vegetation growth and carbon sequestration. The increasing precipitation throughout 2000-2012 was related to the soil retention and hydrological regulation fluctuations. The vegetation restoration played a positive role in the soil retention enhancement, thus substantially reduced water and sediment yields. The relationships between ecosystem services were not only correlations (tradeoffs or synergies), but rather constraint effects. The constraint effects between the three paired ecosystem services could be classified as the negative convex (carbon sequestration vs. hydrological regulation) and hump-shaped (soil retention vs. carbon sequestration and soil retention vs. hydrological regulation), and the coefficients of determination for the entire LP were 0.78, 0.84, and 0.65, respectively. In the LP, the rainfall (water availability) was the key constraint factor that affected the relationships between the paired ecosystem services. The spatially explicit mapping of ecosystem services and interaction analyses utilizing constraint line approach enriched the

  15. Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

    Science.gov (United States)

    Gillan, Jeffrey K.; Karl, Jason W.; Barger, Nichole N.; Elaksher, Ahmed; Duniway, Michael C.

    2016-01-01

    Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to

  16. Is outdoor vector control needed for malaria elimination? An individual-based modelling study.

    Science.gov (United States)

    Zhu, Lin; Müller, Günter C; Marshall, John M; Arheart, Kristopher L; Qualls, Whitney A; Hlaing, WayWay M; Schlein, Yosef; Traore, Sekou F; Doumbia, Seydou; Beier, John C

    2017-07-03

    Residual malaria transmission has been reported in many areas even with adequate indoor vector control coverage, such as long-lasting insecticidal nets (LLINs). The increased insecticide resistance in Anopheles mosquitoes has resulted in reduced efficacy of the widely used indoor tools and has been linked with an increase in outdoor malaria transmission. There are considerations of incorporating outdoor interventions into integrated vector management (IVM) to achieve malaria elimination; however, more information on the combination of tools for effective control is needed to determine their utilization. A spatial individual-based model was modified to simulate the environment and malaria transmission activities in a hypothetical, isolated African village setting. LLINs and outdoor attractive toxic sugar bait (ATSB) stations were used as examples of indoor and outdoor interventions, respectively. Different interventions and lengths of efficacy periods were tested. Simulations continued for 420 days, and each simulation scenario was repeated 50 times. Mosquito populations, entomologic inoculation rates (EIRs), probabilities of local mosquito extinction, and proportion of time when the annual EIR was reduced below one were compared between different intervention types and efficacy periods. In the village setting with clustered houses, the combinational intervention of 50% LLINs plus outdoor ATSBs significantly reduced mosquito population and EIR in short term, increased the probability of local mosquito extinction, and increased the time when annual EIR is less than one per person compared to 50% LLINs alone; outdoor ATSBs alone significantly reduced mosquito population in short term, increased the probability of mosquito extinction, and increased the time when annual EIR is less than one compared to 50% LLINs alone, but there was no significant difference in EIR in short term between 50% LLINs and outdoor ATSBs. In the village setting with dispersed houses, the

  17. Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

    Science.gov (United States)

    Ginovart, Marta

    2014-08-01

    The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study of a predator-prey system for a mathematics classroom in the first year of an undergraduate program in biosystems engineering have been designed and implemented. These activities were designed to put two modelling approaches side by side, an individual-based model and a set of ordinary differential equations. In order to organize and display this, a system with wolves and sheep in a confined domain was considered and studied. With the teaching material elaborated and a computer to perform the numerical resolutions involved and the corresponding individual-based simulations, the students answered questions and completed exercises to achieve the learning goals set. Students' responses regarding the modelling of biological systems and these two distinct methodologies applied to the study of a predator-prey system were collected via questionnaires, open-ended queries and face-to-face dialogues. Taking into account the positive responses of the students when they were doing these activities, it was clear that using a discrete individual-based model to deal with a predator-prey system jointly with a set of ordinary differential equations enriches the understanding of the modelling process, adds new insights and opens novel perspectives of what can be done with computational models versus other models. The complementary views given by the two modelling approaches were very well assessed by students.

  18. An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model

    OpenAIRE

    Gras , Robin; Devaurs , Didier; Wozniak , Adrianna; Aspinall , Adam

    2009-01-01

    International audience; This paper presents an individual-based predator-prey model with, for the first time, each agent behavior being modeled by a Fuzzy Cognitive Map (FCM), allowing the evolution of the agent behavior through the epochs of the simulation. The FCM enables the agent to evaluate its environment (e.g., distance to predator/prey, distance to potential breeding partner, distance to food, energy level), its internal state (e.g., fear, hunger, curiosity) with memory and choosing s...

  19. Remote Sensing of Vegetation Nitrogen Content for Spatially Explicit Carbon and Water Cycle Estimation

    Science.gov (United States)

    Zhang, Y. L.; Miller, J. R.; Chen, J. M.

    2009-05-01

    Foliage nitrogen concentration is a determinant of photosynthetic capacity of leaves, thereby an important input to ecological models for estimating terrestrial carbon and water budgets. Recently, spectrally continuous airborne hyperspectral remote sensing imagery has proven to be useful for retrieving an important related parameter, total chlorophyll content at both leaf and canopy scales. Thus remote sensing of vegetation biochemical parameters has promising potential for improving the prediction of global carbon and water balance patterns. In this research, we explored the feasibility of estimating leaf nitrogen content using hyperspectral remote sensing data for spatially explicit estimation of carbon and water budgets. Multi-year measurements of leaf biochemical contents of seven major boreal forest species were carried out in northeastern Ontario, Canada. The variation of leaf chlorophyll and nitrogen content in response to various growth conditions, and the relationship between them,were investigated. Despite differences in plant type (deciduous and evergreen), leaf age, stand growth conditions and developmental stages, leaf nitrogen content was strongly correlated with leaf chlorophyll content on a mass basis during the active growing season (r2=0.78). With this general correlation, leaf nitrogen content was estimated from leaf chlorophyll content at an accuracy of RMSE=2.2 mg/g, equivalent to 20.5% of the average measured leaf nitrogen content. Based on this correlation and a hyperspectral remote sensing algorithm for leaf chlorophyll content retrieval, the spatial variation of leaf nitrogen content was inferred from the airborne hyperspectral remote sensing imagery acquired by Compact Airborne Spectrographic Imager (CASI). A process-based ecological model Boreal Ecosystem Productivity Simulator (BEPS) was used for estimating terrestrial carbon and water budgets. In contrast to the scenario with leaf nitrogen content assigned as a constant value without

  20. A Spatially Explicit Approach for Sensitivity and Uncertainty Analysis of GIS-Multicriteria Landslide Susceptibility Mapping. GI_Forum 2013 – Creating the GISociety|

    OpenAIRE

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2016-01-01

    GIS multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping for the prediction of future hazards, decision making, as well as hazard mitigation plans. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are prone to multiple types of uncertainty. In this paper, the spatiality explicitly method is employed to assess the uncertainty associated with two methods of GIS-MCDA namely, Analytical Hierarchi...

  1. A Spatially Explicit Dual-Isotope Approach to Map Regions of Plant-Plant Interaction after Exotic Plant Invasion.

    Directory of Open Access Journals (Sweden)

    Christine Hellmann

    Full Text Available Understanding interactions between native and invasive plant species in field settings and quantifying the impact of invaders in heterogeneous native ecosystems requires resolving the spatial scale on which these processes take place. Therefore, functional tracers are needed that enable resolving the alterations induced by exotic plant invasion in contrast to natural variation in a spatially explicit way. 15N isoscapes, i.e., spatially referenced representations of stable nitrogen isotopic signatures, have recently provided such a tracer. However, different processes, e.g. water, nitrogen or carbon cycles, may be affected at different spatial scales. Thus multi-isotope studies, by using different functional tracers, can potentially return a more integrated picture of invader impact. This is particularly true when isoscapes are submitted to statistical methods suitable to find homogeneous subgroups in multivariate data such as cluster analysis. Here, we used model-based clustering of spatially explicit foliar δ15N and δ13C isoscapes together with N concentration of a native indicator species, Corema album, to map regions of influence in a Portuguese dune ecosystem invaded by the N2-fixing Acacia longifolia. Cluster analysis identified regions with pronounced alterations in N budget and water use efficiency in the native species, with a more than twofold increase in foliar N, and δ13C and δ15N enrichment of up to 2‰ and 8‰ closer to the invader, respectively. Furthermore, clusters of multiple functional tracers indicated a spatial shift from facilitation through N addition in the proximity of the invader to competition for resources other than N in close contact. Finding homogeneous subgroups in multi-isotope data by means of model-based cluster analysis provided an effective tool for detecting spatial structure in processes affecting plant physiology and performance. The proposed method can give an objective measure of the spatial extent

  2. SPATIALLY-EXPLICIT BAT IMPACT SCREENING TOOL FOR WIND TURBINE SITING

    Energy Technology Data Exchange (ETDEWEB)

    Versar, Inc.; Exponent, Inc.

    2013-10-28

    As the U.S. seeks to increase energy production from renewable energy sources, development of wind power resources continues to grow. One of the most important ecological issues restricting wind energy development, especially the siting of wind turbines, is the potential adverse effect on bats. High levels of bat fatality have been recorded at a number of wind energy facilities, especially in the eastern United States. The U.S. Department of Energy contracted with Versar, Inc., and Exponent to develop a spatially-explicit site screening tool to evaluate the mortality of bats resulting from interactions (collisions or barotrauma) with wind turbines. The resulting Bat Vulnerability Assessment Tool (BVAT) presented in this report integrates spatial information about turbine locations, bat habitat features, and bat behavior as it relates to possible interactions with turbines. A model demonstration was conducted that focuses on two bat species, the eastern red bat (Lasiurus borealis) and the Indiana bat (Myotis sodalis). The eastern red bat is a relatively common tree-roosting species that ranges broadly during migration in the Eastern U.S., whereas the Indiana bat is regional species that migrates between a summer range and cave hibernacula. Moreover, Indiana bats are listed as endangered, and so the impacts to this species are of particular interest. The model demonstration used conditions at the Mountaineer Wind Energy Center (MWEC), which consists of 44 wind turbines arranged in a linear array near Thomas, West Virginia (Tucker County), to illustrate model functions and not to represent actual or potential impacts of the facility. The turbines at MWEC are erected on the ridge of Backbone Mountain with a nacelle height of 70 meters and a collision area of 72 meters (blade height) or 4,071 meters square. The habitat surrounding the turbines is an Appalachian mixed mesophytic forest. Model sensitivity runs showed that bat mortality in the model was most sensitive to

  3. InSTREAM: the individual-based stream trout research and environmental assessment model

    Science.gov (United States)

    Steven F. Railsback; Bret C. Harvey; Stephen K. Jackson; Roland H. Lamberson

    2009-01-01

    This report documents Version 4.2 of InSTREAM, including its formulation, software, and application to research and management problems. InSTREAM is a simulation model designed to understand how stream and river salmonid populations respond to habitat alteration, including altered flow, temperature, and turbidity regimes and changes in channel morphology. The model...

  4. An individual-based model of Zebrafish population dynamics accounting for energy dynamics

    DEFF Research Database (Denmark)

    Beaudouin, Remy; Goussen, Benoit; Piccini, Benjamin

    2015-01-01

    Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model...

  5. An individual-based model for biofilm formation at liquid surfaces.

    Science.gov (United States)

    Ardré, Maxime; Henry, Hervé; Douarche, Carine; Plapp, Mathis

    2015-12-10

    The bacterium Bacillus subtilis frequently forms biofilms at the interface between the culture medium and the air. We present a mathematical model that couples a description of bacteria as individual discrete objects to the standard advection-diffusion equations for the environment. The model takes into account two different bacterial phenotypes. In the motile state, bacteria swim and perform a run-and-tumble motion that is biased toward regions of high oxygen concentration (aerotaxis). In the matrix-producer state they excrete extracellular polymers, which allows them to connect to other bacteria and to form a biofilm. Bacteria are also advected by the fluid, and can trigger bioconvection. Numerical simulations of the model reproduce all the stages of biofilm formation observed in laboratory experiments. Finally, we study the influence of various model parameters on the dynamics and morphology of biofilms.

  6. Equilibrium and non-equilibrium concepts in forest genetic modelling: population- and individually-based approaches

    OpenAIRE

    Kramer, Koen; van der Werf, D. C.

    2010-01-01

    The environment is changing and so are forests, in their functioning, in species composition, and in the species’ genetic composition. Many empirical and process-based models exist to support forest management. However, most of these models do not consider the impact of environmental changes and forest management on genetic diversity nor on the rate of adaptation of critical plant processes. How genetic diversity and rates of adaptation depend on management actions is a crucial next step in m...

  7. A generic framework for individual-based modelling and physical-biological interaction

    DEFF Research Database (Denmark)

    Christensen, Asbjørn; Mariani, Patrizio; Payne, Mark R.

    2018-01-01

    The increased availability of high-resolution ocean data globally has enabled more detailed analyses of physical-biological interactions and their consequences to the ecosystem. We present IBMlib, which is a versatile, portable and computationally effective framework for conducting Lagrangian...... scales. The open-source framework features a minimal robust interface to facilitate the coupling between individual-level biological models and oceanographic models, and we provide application examples including forward/backward simulations, habitat connectivity calculations, assessing ocean conditions...

  8. Modelling the effects of diving ducks on zebra mussels Dreissena polymorpha in lakes

    NARCIS (Netherlands)

    Nes, van E.H.; Noordhuis, R.; Lammens, E.H.R.R.; Portielje, R.; Reeze, B.; Peeters, E.T.H.M.

    2008-01-01

    An individual-based model describing the growth of zebra mussels (Dreissena polymorpha) is presented. The model is spatially explicit and predicts length¿frequency distributions of zebra mussels. The parameters and model inputs with the strongest effect on the model outcomes were identified using a

  9. [Construction of individual-based ecological model for Scomber japonicas at its early growth stages in East China Sea].

    Science.gov (United States)

    Li, Yue-Song; Chen, Xin-Jun; Yang, Hong

    2012-06-01

    By adopting FVCOM-simulated 3-D physical field and based on the biological processes of chub mackerel (Scomber japonicas) in its early life history from the individual-based biological model, the individual-based ecological model for S. japonicas at its early growth stages in the East China Sea was constructed through coupling the physical field in March-July with the biological model by the method of Lagrange particle tracking. The model constructed could well simulate the transport process and abundance distribution of S. japonicas eggs and larvae. The Taiwan Warm Current, Kuroshio, and Tsushima Strait Warm Current directly affected the transport process and distribution of the eggs and larvae, and indirectly affected the growth and survive of the eggs and larvae through the transport to the nursery grounds with different water temperature and foods. The spawning grounds in southern East China Sea made more contributions to the recruitment to the fishing grounds in northeast East China Sea, but less to the Yangtze estuary and Zhoushan Island. The northwestern and southwestern parts of spawning grounds had strong connectivity with the nursery grounds of Cheju and Tsushima Straits, whereas the northeastern and southeastern parts of the spawning ground had strong connectivity with the nursery grounds of Kyushu and Pacific Ocean.

  10. Applying and Individual-Based Model to Simultaneously Evaluate Net Ecosystem Production and Tree Diameter Increment

    Science.gov (United States)

    Fang, F. J.

    2017-12-01

    Reconciling observations at fundamentally different scales is central in understanding the global carbon cycle. This study investigates a model-based melding of forest inventory data, remote-sensing data and micrometeorological-station data ("flux towers" estimating forest heat, CO2 and H2O fluxes). The individual tree-based model FORCCHN was used to evaluate the tree DBH increment and forest carbon fluxes. These are the first simultaneous simulations of the forest carbon budgets from flux towers and individual-tree growth estimates of forest carbon budgets using the continuous forest inventory data — under circumstances in which both predictions can be tested. Along with the global implications of such findings, this also improves the capacity for forest sustainable management and the comprehensive understanding of forest ecosystems. In forest ecology, diameter at breast height (DBH) of a tree significantly determines an individual tree's cross-sectional sapwood area, its biomass and carbon storage. Evaluation the annual DBH increment (ΔDBH) of an individual tree is central to understanding tree growth and forest ecology. Ecosystem Carbon flux is a consequence of key ecosystem processes in the forest-ecosystem carbon cycle, Gross and Net Primary Production (GPP and NPP, respectively) and Net Ecosystem Respiration (NEP). All of these closely relate with tree DBH changes and tree death. Despite advances in evaluating forest carbon fluxes with flux towers and forest inventories for individual tree ΔDBH, few current ecological models can simultaneously quantify and predict the tree ΔDBH and forest carbon flux.

  11. Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management.

    Science.gov (United States)

    Coates, Peter S; Casazza, Michael L; Ricca, Mark A; Brussee, Brianne E; Blomberg, Erik J; Gustafson, K Benjamin; Overton, Cory T; Davis, Dawn M; Niell, Lara E; Espinosa, Shawn P; Gardner, Scott C; Delehanty, David J

    2016-02-01

    Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management.Greater sage-grouse Centrocercus urophasianus , hereafter 'sage-grouse' populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize the use of available information.Herein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by >35 500 independent telemetry locations from >1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes.We also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of the following: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. Synthesis and application s. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance and space use derived from multiple data sources yields a composite map that can guide effective allocation of management

  12. Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management

    Science.gov (United States)

    Coates, Peter S.; Casazza, Michael L.; Ricca, Mark A.; Brussee, Brianne E.; Blomberg, Erik J.; Gustafson, K. Benjamin; Overton, Cory T.; Davis, Dawn M.; Niell, Lara E.; Espinosa, Shawn P.; Gardner, Scott C.; Delehanty, David J.

    2016-01-01

    Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management. Greater sage-grouse Centrocercus urophasianus, hereafter “sage-grouse” populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize use of available information. Herein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution, and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by > 35 500 independent telemetry locations from > 1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes. We also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. Synthesis and applications. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance, and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across

  13. Sandeel ( Ammodytes marinus ) larval transport patterns in the North Sea from an individual-based hydrodynamic egg and larval model

    DEFF Research Database (Denmark)

    Christensen, Asbjørn; Jensen, Henrik; Mosegaard, Henrik

    2008-01-01

    We have calculated a time series of larval transport indices for the central and southern North Sea covering 1970-2004, using a combined three-dimensional hydrodynamic and individual-based modelling framework for studying sandeel (Ammodytes marinus) eggs, larval transport, and growth. The egg phase...... is modelled by a stochastic, nonlinear degree-day model describing the extended hatch period. The larval growth model is parameterized by individually back-tracking the local physical environment of larval survivors from their catch location and catch time. Using a detailed map of sandeel habitats...... analyzed, and we introduce novel a scheme to quantify direct and indirect connectivity on equal footings in terms of an interbank transit time scale....

  14. Global spatially explicit CO2 emission metrics at 0.25° horizontal resolution for forest bioenergy

    Science.gov (United States)

    Cherubini, F.

    2015-12-01

    Bioenergy is the most important renewable energy option in studies designed to align with future RCP projections, reaching approximately 250 EJ/yr in RCP2.6, 145 EJ/yr in RCP4.5 and 180 EJ/yr in RCP8.5 by the end of the 21st century. However, many questions enveloping the direct carbon cycle and climate response to bioenergy remain partially unexplored. Bioenergy systems are largely assessed under the default climate neutrality assumption and the time lag between CO2 emissions from biomass combustion and CO2 uptake by vegetation is usually ignored. Emission metrics of CO2 from forest bioenergy are only available on a case-specific basis and their quantification requires processing of a wide spectrum of modelled or observed local climate and forest conditions. On the other hand, emission metrics are widely used to aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.), but a spatially explicit analysis of emission metrics with global forest coverage is today lacking. Examples of emission metrics include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Here, we couple a global forest model, a heterotrophic respiration model, and a global climate model to produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy. We show their applications to global emissions in 2015 and until 2100 under the different RCP scenarios. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2-1 (mean ± standard deviation), 0.05 ± 0.05 kgCO2-eq. kgCO2-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1 for GWP, GTP and aSET, respectively. We also present results aggregated at a grid, national and continental level. The metrics are found to correlate with the site-specific turnover times and local climate variables like annual mean temperature and precipitation. Simplified

  15. Mapping of soil organic carbon stocks for spatially explicit assessments of climate change mitigation potential

    International Nuclear Information System (INIS)

    Vågen, Tor-Gunnar; Winowiecki, Leigh A

    2013-01-01

    Current methods for assessing soil organic carbon (SOC) stocks are generally not well suited for understanding variations in SOC stocks in landscapes. This is due to the tedious and time-consuming nature of the sampling methods most commonly used to collect bulk density cores, which limits repeatability across large areas, particularly where information is needed on the spatial dynamics of SOC stocks at scales relevant to management and for spatially explicit targeting of climate change mitigation options. In the current study, approaches were explored for (i) field-based estimates of SOC stocks and (ii) mapping of SOC stocks at moderate to high resolution on the basis of data from four widely contrasting ecosystems in East Africa. Estimated SOC stocks for 0–30 cm depth varied both within and between sites, with site averages ranging from 2 to 8 kg m −2 . The differences in SOC stocks were determined in part by rainfall, but more importantly by sand content. Results also indicate that managing soil erosion is a key strategy for reducing SOC loss and hence in mitigation of climate change in these landscapes. Further, maps were developed on the basis of satellite image reflectance data with multiple R-squared values of 0.65 for the independent validation data set, showing variations in SOC stocks across these landscapes. These maps allow for spatially explicit targeting of potential climate change mitigation efforts through soil carbon sequestration, which is one option for climate change mitigation and adaptation. Further, the maps can be used to monitor the impacts of such mitigation efforts over time. (letter)

  16. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

  17. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  18. HexSim: a modeling environment for ecology and conservation.

    Science.gov (United States)

    HexSim is a powerful and flexible new spatially-explicit, individual based modeling environment intended for use in ecology, conservation, genetics, epidemiology, toxicology, and other disciplines. We describe HexSim, illustrate past applications that contributed to our >10 year ...

  19. Gap models and their individual-based relatives in the assessment of the consequences of global change

    Science.gov (United States)

    Shugart, Herman H.; Wang, Bin; Fischer, Rico; Ma, Jianyong; Fang, Jing; Yan, Xiaodong; Huth, Andreas; Armstrong, Amanda H.

    2018-03-01

    Individual-based models (IBMs) of complex systems emerged in the 1960s and early 1970s, across diverse disciplines from astronomy to zoology. Ecological IBMs arose with seemingly independent origins out of the tradition of understanding the ecosystems dynamics of ecosystems from a ‘bottom-up’ accounting of the interactions of the parts. Individual trees are principal among the parts of forests. Because these models are computationally demanding, they have prospered as the power of digital computers has increased exponentially over the decades following the 1970s. This review will focus on a class of forest IBMs called gap models. Gap models simulate the changes in forests by simulating the birth, growth and death of each individual tree on a small plot of land. The summation of these plots comprise a forest (or set of sample plots on a forested landscape or region). Other, more aggregated forest IBMs have been used in global applications including cohort-based models, ecosystem demography models, etc. Gap models have been used to provide the parameters for these bulk models. Currently, gap models have grown from local-scale to continental-scale and even global-scale applications to assess the potential consequences of climate change on natural forests. Modifications to the models have enabled simulation of disturbances including fire, insect outbreak and harvest. Our objective in this review is to provide the reader with an overview of the history, motivation and applications, including theoretical applications, of these models. In a time of concern over global changes, gap models are essential tools to understand forest responses to climate change, modified disturbance regimes and other change agents. Development of forest surveys to provide the starting points for simulations and better estimates of the behavior of the diversity of tree species in response to the environment are continuing needs for improvement for these and other IBMs.

  20. Spatially explicit measures of production of young alewives in Lake Michigan: Linkage between essential fish habitat and recruitment

    Science.gov (United States)

    Hook, Tomas O.; Rutherford, Edward S.; Brines, Shannon J.; Mason, Doran M.; Schwab, David J.; McCormick, Michael; Desorcie, Timothy J.

    2003-01-01

    The identification and protection of essential habitats for early life stages of fishes are necessary to sustain fish stocks. Essential fish habitat for early life stages may be defined as areas where fish densities, growth, survival, or production rates are relatively high. To identify critical habitats for young-of-year (YOY) alewives (Alosa pseud oharengus) in Lake Michigan, we integrated bioenergetics models with GIS (Geographic Information Systems) to generate spatially explicit estimates of potential population production (an index of habitat quality). These estimates were based upon YOY alewife bioenergetic growth rate potential and their salmonine predators’ consumptive demand. We compared estimates of potential population production to YOY alewife yield (an index of habitat importance). Our analysis suggested that during 1994–1995, YOY alewife habitat quality and yield varied widely throughout Lake Michigan. Spatial patterns of alewife yield were not significantly correlated to habitat quality. Various mechanisms (e.g., predator migrations, lake circulation patterns, alternative strategies) may preclude YOY alewives from concentrating in areas of high habitat quality in Lake Michigan.

  1. A generic individual-based model to simulate morphogenesis, C-N acquisition and population dynamics in contrasting forage legumes.

    Science.gov (United States)

    Louarn, Gaëtan; Faverjon, Lucas

    2018-04-18

    Individual-based models (IBMs) are promising tools to disentangle plant interactions in multi-species grasslands and foster innovative species mixtures. This study describes an IBM dealing with the morphogenesis, growth and C-N acquisition of forage legumes that integrates plastic responses from functional-structural plant models. A generic model was developed to account for herbaceous legume species with contrasting above- and below-ground morphogenetic syndromes and to integrate the responses of plants to light, water and N. Through coupling with a radiative transfer model and a three-dimensional virtual soil, the model allows dynamic resolution of competition for multiple resources at individual plant level within a plant community. The behaviour of the model was assessed on a range of monospecific stands grown along gradients of light, water and N availability. The model proved able to capture the diversity of morphologies encountered among the forage legumes. The main density-dependent features known about even-age plant populations were correctly anticipated. The model predicted (1) the 'reciprocal yield' law relating average plant mass to density, (2) a self-thinning pattern close to that measured for herbaceous species and (3) consistent changes in the size structure of plant populations with time and pedo-climatic conditions. In addition, plastic changes in the partitioning of dry matter, the N acquisition mode and in the architecture of shoots and roots emerged from the integration of plant responses to their local environment. This resulted in taller plants and thinner roots when competition was dominated by light, and shorter plants with relatively more developed root systems when competition was dominated by soil resources. A population dynamic model considering growth and morphogenesis responses to multiple resources heterogeneously distributed in the environment was presented. It should allow scaling plant-plant interactions from individual to

  2. Toward Understanding Dynamics in Shifting Biomes: An Individual Based Modeling Approach to Characterizing Drought and Mortality in Central Western Canada

    Science.gov (United States)

    Armstrong, A. H.; Foster, A.; Rogers, B. M.; Hogg, T.; Michaelian, M.; Shuman, J. K.; Shugart, H. H., Jr.; Goetz, S. J.

    2017-12-01

    The Arctic-Boreal zone is known be warming at an accelerated rate relative to other biomes. Persistent warming has already affected the high northern latitudes, altering vegetation productivity, carbon sequestration, and many other ecosystem processes and services. The central-western Canadian boreal forests and aspen parkland are experiencing a decade long drought, and rainfall has been identified as a key factor controlling the location of the boundary between forest and prairie in this region. Shifting biome with related greening and browning trends are readily measureable with remote sensing, but the dynamics that create and result from them are not well understood. In this study, we use the University of Virginia Forest Model Enhanced (UVAFME), an individual-based forest model, to simulate the changes that are occurring across the southern boreal and parkland forests of west-central Canada. We present a parameterization of UVAFME for western central Canadian forests, validated with CIPHA data (Climate Change Impacts on the Productivity and Health of Aspen), and improved mortality. In order to gain a fine-scale understanding of how climate change and specifically drought will continue to affect the forests of this region, we simulated forest conditions following CMIP5 climate scenarios. UVAFME predictions were compared with statistical models and satellite observations of productivity across the landscape. Changes in forest cover, forest type, aboveground biomass, and mortality and recruitment dynamics are presented, highlighting the high vulnerability of this region to vegetation transitions associated with future droughts.

  3. Is pertussis actually reemerging? Insights from an individual-based model A coqueluche realmente está reermegindo? Reflexões a partir de um modelo baseado no indivíduo

    Directory of Open Access Journals (Sweden)

    Cláudia Torres Codeço

    2001-06-01

    Full Text Available In this paper, we introduce a spatially explicit, individual-based model developed to simulate the dynamics of pertussis in a small population. With this simulation approach, complex epidemic systems can be built using information on parasite population structure (strain diversity, virulence diversity, etc., human population structure (individual risk, age structure, interaction matrices, immune response, etc., as well as mechanisms of evolution and learning. We parameterized our model to describe pertussis in an age-structured community. Pertussis or whooping cough is an acute infection of the respiratory tract caused by Bordetella pertussis. Despite wide-scale vaccination in many countries, this disease is reemerging throughout the world in both adults and children. Emergence has been explained by many factors: wane of vaccine and natural immunity, increase of asymptomatic carriers, and/or natural selection of non-vaccine strains. Here, we model these hypotheses and analyze their potential impact on the observed increase of pertussis notification.Neste trabalho, nós apresentamos um modelo de indivíduos, cuja representação espacial é explícita, para simular a dinâmica da coqueluche numa pequena população. Utilizando esta abordagem de simulação, podemos construir modelos complexos utilizando informações sobre a estrutura populacional dos parasitas (diversidade fenotípica, de virulência, etc sobre a estrutura populacional humana (risco individual, estrutura etária, matrizes de interação, resposta imunológica, etc assim como processos evolutivos e de aprendizagem. Nós parametrizamos este modelo para representar a dinâmica da coqueluche numa população com estrutura etária. Coqueluche é uma infecção aguda do trato respiratório, causada por Bordetella pertussis. Apesar da vacinação em larga escala em vários países, esta infecção está reemergindo por todo o mundo, atacando adultos e crianças. Reemergência tem sido

  4. [A spatially explicit analysis of traffic accidents involving pedestrians and cyclists in Berlin].

    Science.gov (United States)

    Lakes, Tobia

    2017-12-01

    In many German cities and counties, sustainable mobility concepts that strengthen pedestrian and cyclist traffic are promoted. From the perspectives of urban development, traffic planning and public healthcare, a spatially differentiated analysis of traffic accident data is decisive. 1) The identification of spatial and temporal patterns of the distribution of accidents involving cyclists and pedestrians, 2) the identification of hotspots and exploration of possible underlying causes and 3) the critical discussion of benefits and challenges of the results and the derivation of conclusions. Spatio-temporal distributions of data from accident statistics in Berlin involving pedestrians and cyclists from 2011 to 2015 were analysed with geographic information systems (GIS). While the total number of accidents remains relatively stable for pedestrian and cyclist accidents, the spatial distribution analysis shows, however, that there are significant spatial clusters (hotspots) of traffic accidents with a strong concentration in the inner city area. In a critical discussion, the benefits of geographic concepts are identified, such as spatially explicit health data (in this case traffic accident data), the importance of the integration of other data sources for the evaluation of the health impact of areas (traffic accident statistics of the police), and the possibilities and limitations of spatial-temporal data analysis (spatial point-density analyses) for the derivation of decision-supported recommendations and for the evaluation of policy measures of health prevention and of health-relevant urban development.

  5. Quantifying multiple telecouplings using an integrated suite of spatially-explicit tools

    Science.gov (United States)

    Tonini, F.; Liu, J.

    2016-12-01

    Telecoupling is an interdisciplinary research umbrella concept that enables natural and social scientists to understand and generate information for managing how humans and nature can sustainably coexist worldwide. To systematically study telecoupling, it is essential to build a comprehensive set of spatially-explicit tools for describing and quantifying multiple reciprocal socioeconomic and environmental interactions between a focal area and other areas. Here we introduce the Telecoupling Toolbox, a new free and open-source set of tools developed to map and identify the five major interrelated components of the telecoupling framework: systems, flows, agents, causes, and effects. The modular design of the toolbox allows the integration of existing tools and software (e.g. InVEST) to assess synergies and tradeoffs associated with policies and other local to global interventions. We show applications of the toolbox using a number of representative studies that address a variety of scientific and management issues related to telecouplings throughout the world. The results suggest that the toolbox can thoroughly map and quantify multiple telecouplings under various contexts while providing users with an easy-to-use interface. It provides a powerful platform to address globally important issues, such as land use and land cover change, species invasion, migration, flows of ecosystem services, and international trade of goods and products.

  6. Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem

    Science.gov (United States)

    Govind, Ajit; Chen, Jing Ming; Ju, Weimin

    2009-06-01

    Ecosystem models that simulate biogeochemical processes usually ignore hydrological controls that govern them. It is quite possible that topographically driven water fluxes significantly influence the spatial distribution of C sources and sinks because of their large contribution to the local water balance. To investigate this, we simulated biogeochemical processes along with the associated feedback mechanisms in a boreal ecosystem using a spatially explicit hydroecological model, boreal ecosystem productivity simulator (BEPS)-TerrainLab V2.0, that has a tight coupling of ecophysiological, hydrological, and biogeochemical processes. First, the simulated dynamics of snowpack, soil temperature, net ecosystem productivity (NEP), and total ecosystem respiration (TER) were validated with high-frequency measurements for 2 years. The model was able to explain 80% of the variability in NEP and 84% of the variability in TER. Further, we investigated the influence of topographically driven subsurface base flow on soil C and N cycling and on the spatiotemporal patterns of C sources and sinks using three hydrological modeling scenarios that differed in hydrological conceptualizations. In general, the scenarios that had nonexplicit hydrological representation overestimated NEP, as opposed to the scenario that had an explicit (realistic) representation. The key processes controlling the NEP differences were attributed to the combined effects of variations in photosynthesis (due to changes in stomatal conductance and nitrogen (N) availability), heterotrophic respiration, and autotrophic respiration, all of which occur simultaneously affecting NEP. Feedback relationships were also found to exacerbate the differences. We identified six types of NEP differences (biases), of which the most commonly found was due to an underestimation of the existing C sources, highlighting the vulnerability of regional-scale ecosystem models that ignore hydrological processes.

  7. Tundra shrubification and tree-line advance amplify arctic climate warming: results from an individual-based dynamic vegetation model

    Science.gov (United States)

    Zhang, Wenxin; Miller, Paul A.; Smith, Benjamin; Wania, Rita; Koenigk, Torben; Döscher, Ralf

    2013-09-01

    One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model-downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961-1990) agreed well with a composite map of actual arctic vegetation. In the future (2051-2080), a poleward advance of the forest-tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH4 emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH4, may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux.

  8. Trait contributions to fish community assembly emerge from trophicinteractions in an individual-based model

    Science.gov (United States)

    Giacomini, Henrique C.; DeAngelis, Donald; Trexler, Joel C.; Petrere, Miguel

    2013-01-01

    Community ecology seeks to understand and predict the characteristics of communities that can develop under different environmental conditions, but most theory has been built on analytical models that are limited in the diversity of species traits that can be considered simultaneously. We address that limitation with an individual-based model to simulate assembly of fish communities characterized by life history and trophic interactions with multiple physiological tradeoffs as constraints on species performance. Simulation experiments were carried out to evaluate the distribution of 6 life history and 4 feeding traits along gradients of resource productivity and prey accessibility. These experiments revealed that traits differ greatly in importance for species sorting along the gradients. Body growth rate emerged as a key factor distinguishing community types and defining patterns of community stability and coexistence, followed by egg size and maximum body size. Dominance by fast-growing, relatively large, and fecund species occurred more frequently in cases where functional responses were saturated (i.e. high productivity and/or prey accessibility). Such dominance was associated with large biomass fluctuations and priority effects, which prevented richness from increasing with productivity and may have limited selection on secondary traits, such as spawning strategies and relative size at maturation. Our results illustrate that the distribution of species traits and the consequences for community dynamics are intimately linked and strictly dependent on how the benefits and costs of these traits are balanced across different conditions.

  9. Changing relationships between land use and environmental characteristics and their consequences for spatially explicit land-use change prediction

    NARCIS (Netherlands)

    Bakker, M.; Veldkamp, A.

    2012-01-01

    Spatially explicit land-use change prediction is often based on environmental characteristics of land-use types, such as soil type and slope, as observed at one time instant. This approach presumes that relationships between land use and environment are constant over time. We argue that such

  10. Informed herbivore movement and interplant communication determine the effects of induced resistance in an individual-based model.

    Science.gov (United States)

    Rubin, Ilan N; Ellner, Stephen P; Kessler, André; Morrell, Kimberly A

    2015-09-01

    1. Plant induced resistance to herbivory affects the spatial distribution of herbivores, as well as their performance. In recent years, theories regarding the benefit to plants of induced resistance have shifted from ideas of optimal resource allocation towards a more eclectic set of theories that consider spatial and temporal plant variability and the spatial distribution of herbivores among plants. However, consensus is lacking on whether induced resistance causes increased herbivore aggregation or increased evenness, as both trends have been experimentally documented. 2. We created a spatial individual-based model that can describe many plant-herbivore systems with induced resistance, in order to analyse how different aspects of induced resistance might affect herbivore distribution, and the total damage to a plant population, during a growing season. 3. We analyse the specific effects on herbivore aggregation of informed herbivore movement (preferential movement to less-damaged plants) and of information transfer between plants about herbivore attacks, in order to identify mechanisms driving both aggregation and evenness. We also investigate how the resulting herbivore distributions affect the total damage to plants and aggregation of damage. 4. Even, random and aggregated herbivore distributions can all occur in our model with induced resistance. Highest levels of aggregation occurred in the models with informed herbivore movement, and the most even distributions occurred when the average number of herbivores per plant was low. With constitutive resistance, only random distributions occur. Damage to plants was spatially correlated, unless plants recover very quickly from damage; herbivore spatial autocorrelation was always weak. 5. Our model and results provide a simple explanation for the apparent conflict between experimental results, indicating that both increased aggregation and increased evenness of herbivores can result from induced resistance. We

  11. Tundra shrubification and tree-line advance amplify arctic climate warming: results from an individual-based dynamic vegetation model

    International Nuclear Information System (INIS)

    Zhang Wenxin; Miller, Paul A; Smith, Benjamin; Wania, Rita; Koenigk, Torben; Döscher, Ralf

    2013-01-01

    One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model–downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961–1990) agreed well with a composite map of actual arctic vegetation. In the future (2051–2080), a poleward advance of the forest–tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH 4 emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH 4 , may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux. (letter)

  12. The Dynamics of Avian Influenza: Individual-Based Model with Intervention Strategies in Traditional Trade Networks in Phitsanulok Province, Thailand

    Directory of Open Access Journals (Sweden)

    Chaiwat Wilasang

    2016-01-01

    Full Text Available Avian influenza virus subtype H5N1 is endemic to Southeast Asia. In Thailand, avian influenza viruses continue to cause large poultry stock losses. The spread of the disease has a serious impact on poultry production especially among rural households with backyard chickens. The movements and activities of chicken traders result in the spread of the disease through traditional trade networks. In this study, we investigate the dynamics of avian influenza in the traditional trade network in Phitsanulok Province, Thailand. We also propose an individual-based model with intervention strategies to control the spread of the disease. We found that the dynamics of the disease mainly depend on the transmission probability and the virus inactivation period. This study also illustrates the appropriate virus disinfection period and the target for intervention strategies on traditional trade network. The results suggest that good hygiene and cleanliness among household traders and trader of trader areas and ensuring that any equipment used is clean can lead to a decrease in transmission and final epidemic size. These results may be useful to epidemiologists, researchers, and relevant authorities in understanding the spread of avian influenza through traditional trade networks.

  13. Spatially-explicit modelling model for assessing wild dog control strategies in Western Australia

    Science.gov (United States)

    Large predators can significantly impact livestock industries. In Australia, wild dogs (Canis lupus familiaris, Canis lupus dingo, and hybrids) cause economic losses of more than AUD $40M annually. Landscape-scale exclusion fencing coupled with lethal techniques is a widely pract...

  14. Spatially explicit genetic structure in the freshwater sponge Ephydatia fluviatilis (Linnaeus, 1759 within the framework of the monopolisation hypothesis

    Directory of Open Access Journals (Sweden)

    Livia Lucentini

    2013-02-01

    Full Text Available An apparent paradox is known for crustaceans, rotifers and bryozoans living in inland small water bodies: a potential for wide distribution due to the presence of resting stages is coupled with marked genetic differences between nearby water bodies, with enclave distributions masking clear phylogeographic patterns. According to the monopolisation hypothesis, this is due to the accumulation of resting stages, monopolising each water body. Freshwater sponges could represent a useful system to assess the generality of the mo- nopolisation hypothesis: these organisms i live in the same habitats as crustaceans, rotifers and bryozoans, ii produce resting stages that can accumulate, and iii have indeed a wide distribution. Currently, no studies on spatially explicit genetic differentiation on fresh- water sponges are available. The aim of the present study is to provide additional empirical evidence in support of the generality of the scenario for small aquatic animals with resting stages by analysing genetic diversity at different spatial scales for an additional model system, the freshwater sponge ephydatia fluviatilis (Linnaeus, 1759. We expected that system genetic variability would follow enclave distributions, no clear phylogeographical patterns would be present, and nearby unconnected water bodies would show markedly different populations for this new model too. We analysed the ribosomal internal transcribed spacer regions 5.8S-ITS2-28S, the D3 domain of 28S subunit, the mitochondrial Cytochrome c Oxidase I (COI and ten specific microsatellite markers of nine Italian and one Hungarian populations. Mitochondrial and nuclear sequences showed no or very low genetic polymorphism, whereas high levels of differentiation among populations and a significant polymorphism were observed using microsatellites. Microsatellite loci also showed a high proportion of private alleles for each population and an overall correlation between geographic and genetic

  15. Spatially explicit analysis of metal transfer to biota: influence of soil contamination and landscape.

    Directory of Open Access Journals (Sweden)

    Clémentine Fritsch

    Full Text Available Concepts and developments for a new field in ecotoxicology, referred to as "landscape ecotoxicology," were proposed in the 1990s; however, to date, few studies have been developed in this emergent field. In fact, there is a strong interest in developing this area, both for renewing the concepts and tools used in ecotoxicology as well as for responding to practical issues, such as risk assessment. The aim of this study was to investigate the spatial heterogeneity of metal bioaccumulation in animals in order to identify the role of spatially explicit factors, such as landscape as well as total and extractable metal concentrations in soils. Over a smelter-impacted area, we studied the accumulation of trace metals (TMs: Cd, Pb and Zn in invertebrates (the grove snail Cepaea sp and the glass snail Oxychilus draparnaudi and vertebrates (the bank vole Myodes glareolus and the greater white-toothed shrew Crocidura russula. Total and CaCl(2-extractable concentrations of TMs were measured in soils from woody patches where the animals were captured. TM concentrations in animals exhibited a high spatial heterogeneity. They increased with soil pollution and were better explained by total rather than CaCl(2-extractable TM concentrations, except in Cepaea sp. TM levels in animals and their variations along the pollution gradient were modulated by the landscape, and this influence was species and metal specific. Median soil metal concentrations (predicted by universal kriging were calculated in buffers of increasing size and were related to bioaccumulation. The spatial scale at which TM concentrations in animals and soils showed the strongest correlations varied between metals, species and landscapes. The potential underlying mechanisms of landscape influence (community functioning, behaviour, etc. are discussed. Present results highlight the need for the further development of landscape ecotoxicology and multi-scale approaches, which would enhance our

  16. Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

    Science.gov (United States)

    Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

    2014-01-01

    Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution

  17. Predicting Fish Growth Potential and Identifying Water Quality Constraints: A Spatially-Explicit Bioenergetics Approach

    Science.gov (United States)

    Budy, Phaedra; Baker, Matthew; Dahle, Samuel K.

    2011-10-01

    Anthropogenic impairment of water bodies represents a global environmental concern, yet few attempts have successfully linked fish performance to thermal habitat suitability and fewer have distinguished co-varying water quality constraints. We interfaced fish bioenergetics, field measurements, and Thermal Remote Imaging to generate a spatially-explicit, high-resolution surface of fish growth potential, and next employed a structured hypothesis to detect relationships among measures of fish performance and co-varying water quality constraints. Our thermal surface of fish performance captured the amount and spatial-temporal arrangement of thermally-suitable habitat for three focal species in an extremely heterogeneous reservoir, but interpretation of this pattern was initially confounded by seasonal covariation of water residence time and water quality. Subsequent path analysis revealed that in terms of seasonal patterns in growth potential, catfish and walleye responded to temperature, positively and negatively, respectively; crappie and walleye responded to eutrophy (negatively). At the high eutrophy levels observed in this system, some desired fishes appear to suffer from excessive cultural eutrophication within the context of elevated temperatures whereas others appear to be largely unaffected or even enhanced. Our overall findings do not lead to the conclusion that this system is degraded by pollution; however, they do highlight the need to use a sensitive focal species in the process of determining allowable nutrient loading and as integrators of habitat suitability across multiple spatial and temporal scales. We provide an integrated approach useful for quantifying fish growth potential and identifying water quality constraints on fish performance at spatial scales appropriate for whole-system management.

  18. Simulation of Escherichia coli Dynamics in Biofilms and Submerged Colonies with an Individual-Based Model Including Metabolic Network Information.

    Science.gov (United States)

    Tack, Ignace L M M; Nimmegeers, Philippe; Akkermans, Simen; Hashem, Ihab; Van Impe, Jan F M

    2017-01-01

    Clustered microbial communities are omnipresent in the food industry, e.g., as colonies of microbial pathogens in/on food media or as biofilms on food processing surfaces. These clustered communities are often characterized by metabolic differentiation among their constituting cells as a result of heterogeneous environmental conditions in the cellular surroundings. This paper focuses on the role of metabolic differentiation due to oxygen gradients in the development of Escherichia coli cell communities, whereby low local oxygen concentrations lead to cellular secretion of weak acid products. For this reason, a metabolic model has been developed for the facultative anaerobe E. coli covering the range of aerobic, microaerobic, and anaerobic environmental conditions. This metabolic model is expressed as a multiparametric programming problem, in which the influence of low extracellular pH values and the presence of undissociated acid cell products in the environment has been taken into account. Furthermore, the developed metabolic model is incorporated in MICRODIMS, an in-house developed individual-based modeling framework to simulate microbial colony and biofilm dynamics. Two case studies have been elaborated using the MICRODIMS simulator: (i) biofilm growth on a substratum surface and (ii) submerged colony growth in a semi-solid mixed food product. In the first case study, the acidification of the biofilm environment and the emergence of typical biofilm morphologies have been observed, such as the mushroom-shaped structure of mature biofilms and the formation of cellular chains at the exterior surface of the biofilm. The simulations show that these morphological phenomena are respectively dependent on the initial affinity of pioneer cells for the substratum surface and the cell detachment process at the outer surface of the biofilm. In the second case study, a no-growth zone emerges in the colony center due to a local decline of the environmental pH. As a result

  19. Simulation of Escherichia coli Dynamics in Biofilms and Submerged Colonies with an Individual-Based Model Including Metabolic Network Information

    Directory of Open Access Journals (Sweden)

    Ignace L. M. M. Tack

    2017-12-01

    Full Text Available Clustered microbial communities are omnipresent in the food industry, e.g., as colonies of microbial pathogens in/on food media or as biofilms on food processing surfaces. These clustered communities are often characterized by metabolic differentiation among their constituting cells as a result of heterogeneous environmental conditions in the cellular surroundings. This paper focuses on the role of metabolic differentiation due to oxygen gradients in the development of Escherichia coli cell communities, whereby low local oxygen concentrations lead to cellular secretion of weak acid products. For this reason, a metabolic model has been developed for the facultative anaerobe E. coli covering the range of aerobic, microaerobic, and anaerobic environmental conditions. This metabolic model is expressed as a multiparametric programming problem, in which the influence of low extracellular pH values and the presence of undissociated acid cell products in the environment has been taken into account. Furthermore, the developed metabolic model is incorporated in MICRODIMS, an in-house developed individual-based modeling framework to simulate microbial colony and biofilm dynamics. Two case studies have been elaborated using the MICRODIMS simulator: (i biofilm growth on a substratum surface and (ii submerged colony growth in a semi-solid mixed food product. In the first case study, the acidification of the biofilm environment and the emergence of typical biofilm morphologies have been observed, such as the mushroom-shaped structure of mature biofilms and the formation of cellular chains at the exterior surface of the biofilm. The simulations show that these morphological phenomena are respectively dependent on the initial affinity of pioneer cells for the substratum surface and the cell detachment process at the outer surface of the biofilm. In the second case study, a no-growth zone emerges in the colony center due to a local decline of the environmental p

  20. A community model of ciliate Tetrahymena and bacteria E. coli. Part 1: Individual-based models of Tetrahymena and E. coli populations

    Energy Technology Data Exchange (ETDEWEB)

    Jaworska, J.S.; Hallam, T.G.; Schultz, T.W. [Univ. of Tennessee, Knoxville, TN (United States)

    1996-03-01

    The dynamics of a microbial community consisting of a eucaryotic ciliate Tetrahymena pyriformis and procaryotic. Escherichia coli in a batch culture is explored by employing an individual-based approach. In this portion of the article, Part 1, population models are presented. Because both models are individual-based, models of individual organisms are developed prior to construction of the population models. The individual models use an energy budget method in which growth depends on energy gain from feeding and energy sinks such as maintenance and reproduction. These models are not limited by simplifying assumptions about constant yield, constant energy sinks and Monod growth kinetics as are traditional models of microbial organisms. Population models are generated from individual models by creating distinct individual types and assigning to each type the number of real individuals they represent. A population is a compilation of individual types that vary in a phase of cell cycle and physiological parameters such as filtering rate for ciliates and maximum anabolic rate for bacteria. An advantage of the developed models is that they realistically describe the growth of the individual cells feeding on resource which varies in density and composition. Part 2, the core of the project, integrates models into a dynamic microbial community and provides model analysis based upon available data.

  1. A web-tool to find spatially explicit climate-smart solutions for the sector agriculture

    Science.gov (United States)

    Verzandvoort, Simone; Kuikman, Peter; Walvoort, Dennis

    2017-04-01

    Europe faces the challenge to produce more food and more biomass for the bio-economy, to adapt its agricultural sector to negative consequences of climate change, and to reduce greenhouse gas emissions from agriculture. Climate-smart agriculture (CSA) solutions and technologies improve agriculture's productivity and provide economic growth and stability, increase resilience, and help to reduce GHG emissions from agricultural activities. The Climate Smart Agriculture Booster (CSAb) (http://csabooster.climate-kic.org/) is a Flagship Program under Climate-KIC, aiming to facilitate the adoption of CSA solutions and technologies in the European agro-food sector. This adoption requires spatially explicit, contextual information on farming activities and risks and opportunities related to climate change in regions across Europe. Other spatial information supporting adoption includes Information on where successful implementations were already done, on where CSA would profit from enabling policy conditions, and where markets or business opportunities for selling or purchasing technology and knowledge are located or emerging. The Spatial Solution Finder is a web-based spatial tool aiming to help agri-food companies (supply and processing), authorities or agricultural organisations find CSA solutions and technologies that fit local farmers and regions, and to demonstrate examples of successful implementations as well as expected impact at the farm and regional level. The tool is based on state of the art (geo)datasets of environmental and socio-economic conditions (partly open access, partly derived from previous research) and open source web-technology. The philosophy of the tool is that combining existing datasets with contextual information on the region of interest with personalized information entered by the user provides a suitable basis for offering a basket of options for CSA solutions and technologies. Solutions and technologies are recommended to the user based on

  2. A small community model for the transmission of infectious diseases: comparison of school closure as an intervention in individual-based models of an influenza pandemic.

    Directory of Open Access Journals (Sweden)

    George J Milne

    Full Text Available BACKGROUND: In the absence of other evidence, modelling has been used extensively to help policy makers plan for a potential future influenza pandemic. METHOD: We have constructed an individual based model of a small community in the developed world with detail down to exact household structure obtained from census collection datasets and precise simulation of household demographics, movement within the community and individual contact patterns. We modelled the spread of pandemic influenza in this community and the effect on daily and final attack rates of four social distancing measures: school closure, increased case isolation, workplace non-attendance and community contact reduction. We compared the modelled results of final attack rates in the absence of any interventions and the effect of school closure as a single intervention with other published individual based models of pandemic influenza in the developed world. RESULTS: We showed that published individual based models estimate similar final attack rates over a range of values for R(0 in a pandemic where no interventions have been implemented; that multiple social distancing measures applied early and continuously can be very effective in interrupting transmission of the pandemic virus for R(0 values up to 2.5; and that different conclusions reached on the simulated benefit of school closure in published models appear to result from differences in assumptions about the timing and duration of school closure and flow-on effects on other social contacts resulting from school closure. CONCLUSION: Models of the spread and control of pandemic influenza have the potential to assist policy makers with decisions about which control strategies to adopt. However, attention needs to be given by policy makers to the assumptions underpinning both the models and the control strategies examined.

  3. Early engagement of stakeholders with individual-based modelling can inform research for improving invasive species management: the round goby as a case study

    DEFF Research Database (Denmark)

    Samson, Emma; Hirsch, Philipp E.; Palmer, Stephen C.

    2017-01-01

    Individual-based models (IBMs) incorporating realistic representations of key range-front processes such as dispersal can be used as tools to investigate the dynamics of invasive species. Managers can apply insights from these models to take effective action to prevent further spread and prioriti...

  4. Spatially explicit exposure assessment for small streams in catchments of the orchard growing region `Lake Constance

    Science.gov (United States)

    Golla, B.; Bach, M.; Krumpe, J.

    2009-04-01

    1. Introduction Small streams differ greatly from the standardised water body used in the context of aquatic risk assessment for the regulation of plant protection products in Germany. The standard water body is static, with a depth of 0.3 m and a width of 1.0 m. No dilution or water replacement takes place. Spray drift happens always in direction to the water body. There is no variability in drift deposition rate (90th percentile spray drift deposition values [2]). There is no spray drift filtering by vegetation. The application takes place directly adjacent to the water body. In order to establish a more realistic risk assessment procedure the Federal Office for Consumer Protection and Food Safety (BVL) and the Federal Environment Agency (UBA) aggreed to replace deterministic assumptions with data distributions and spatially explicit data and introduce probabilistic methods [3, 4, 5]. To consider the spatial and temporal variability in the exposure situations of small streams the hydraulic and morphological characteristics of catchments need to be described as well as the spatial distribution of fields treated with pesticides. As small streams are the dominant type of water body in most German orchard regions, we use the growing region Lake Constance as pilot region. 2. Materials and methods During field surveys we derive basic morphological parameters for small streams in the Lake Constance region. The mean water width/depth ratio is 13 with a mean depth of 0.12 m. The average residence time is 5.6 s/m (n=87) [1]. Orchards are mostly located in the upper parts of the catchments. Based on an authoritative dataset on rivers and streams of Germany (ATKIS DLM25) we constructed a directed network topology for the Lake Constance region. The gradient of the riverbed is calculated for river stretches of > 500 m length. The network for the pilot region consists of 2000 km rivers and streams. 500 km stream length are located within a distance of 150 m to orchards. Within

  5. Resilience in rural social-ecological systems : a spatially explicit agent-based modelling approach

    NARCIS (Netherlands)

    Schouten, M.A.H.

    2013-01-01

    Rural areas are increasingly changed by drivers on large spatial scales such as economic globalization and climate change. These international drivers may bring forth abrupt disturbances, such as high output price peaks and falls, water floods and droughts, and massive outbreaks of animal

  6. Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - SEEM

    Science.gov (United States)

    2015-06-01

    is Beltsville silt loam. Land use in the watershed is mainly upland or wetland forests, with significant urban and agricultural development. The...covered with extensive woodlands and wetlands that provide habitat for many animals, including white tail deer, foxes, and wild turkeys. The area is

  7. Improvement, Verification, and Refinement of Spatially Explicit Exposure Models in Risk Assessment - SEEM Demonstration

    Science.gov (United States)

    2015-06-01

    is Beltsville silt loam. Land use in the watershed is mainly upland or wetland forests, with significant urban and agricultural development. The...covered with extensive woodlands and wetlands that provide habitat for many animals, including white tail deer, foxes, and wild turkeys. The area is

  8. Spatially explicit groundwater vulnerability assessment to support the implementation of the Water Framework Directive – a practical approach with stakeholders

    Directory of Open Access Journals (Sweden)

    K. Berkhoff

    2008-01-01

    Full Text Available The main objective of the study presented in this paper was to develop an evaluation scheme which is suitable for spatially explicit groundwater vulnerability assessment according to the Water Framework Directive (WFD. Study area was the Hase river catchment, an area of about 3 000 km2 in north-west Germany which is dominated by livestock farming, in particular pig and poultry production. For the Hase river catchment, the first inventory of the WFD led to the conclusion that 98% of the catchment area is "unclear/unlikely" to reach a good groundwater status due to diffuse nitrogen emissions from agriculture. The groundwater vulnerability assessment was embedded in the PartizipA project ("Participative modelling, Actor and Ecosystem Analysis in Regions with Intensive Agriculture", www.partizipa.net, within which a so-called actors' platform was established in the study area. The objective of the participatory process was to investigate the effects of the WFD on agriculture as well as to discuss groundwater protection measures which are suitable for an integration in the programme of measures. The study was conducted according to the vulnerability assessment concept of the Intergovernmental Panel on Climate Change, considering sensitivity, exposure and adaptive capacity. Sensitivity was computed using the DRASTIC index of natural groundwater pollution potential. Exposure (for a reference scenario was computed using the STOFFBILANZ nutrient model. Several regional studies were analysed to evaluate the adaptive capacity. From these studies it was concluded that the adaptive capacity in the Hase river catchment is very low due to the economic importance of the agricultural sector which will be significantly affected by groundwater protection measures. As a consequence, the adaptive capacity was not considered any more in the vulnerability assessment. A groundwater vulnerability evaluation scheme is presented which enjoys the advantage that both

  9. Effects of streamflow diversion on a fish population: combining empirical data and individual-based models in a site-specific evaluation

    Science.gov (United States)

    Bret C. Harvey; Jason L. White; Rodney J. Nakamoto; Steven F. Railsback

    2014-01-01

    Resource managers commonly face the need to evaluate the ecological consequences of specific water diversions of small streams. We addressed this need by conducting 4 years of biophysical monitoring of stream reaches above and below a diversion and applying two individual-based models of salmonid fish that simulated different levels of behavioral complexity. The...

  10. Spatially explicit multi-threat assessment of food tree species in Burkina Faso: A fine-scale approach.

    Directory of Open Access Journals (Sweden)

    Hannes Gaisberger

    Full Text Available Over the last decades agroforestry parklands in Burkina Faso have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation and nutrition in rural households. Analyzing the threats as well as the species vulnerability to them is fundamental for priority setting in conservation planning. Guided by literature and local experts we selected 16 important food tree species (Acacia macrostachya, Acacia senegal, Adansonia digitata, Annona senegalensis, Balanites aegyptiaca, Bombax costatum, Boscia senegalensis, Detarium microcarpum, Lannea microcarpa, Parkia biglobosa, Sclerocarya birrea, Strychnos spinosa, Tamarindus indica, Vitellaria paradoxa, Ximenia americana, Ziziphus mauritiana and six key threats to them (overexploitation, overgrazing, fire, cotton production, mining and climate change. We developed a species-specific and spatially explicit approach combining freely accessible datasets, species distribution models (SDMs, climate models and expert survey results to predict, at fine scale, where these threats are likely to have the greatest impact. We find that all species face serious threats throughout much of their distribution in Burkina Faso and that climate change is predicted to be the most prevalent threat in the long term, whereas overexploitation and cotton production are the most important short-term threats. Tree populations growing in areas designated as 'highly threatened' due to climate change should be used as seed sources for ex situ conservation and planting in areas where future climate is predicting suitable habitats. Assisted regeneration is suggested for populations in areas where suitable habitat under future climate conditions coincides with high threat levels due to short-term threats. In the case of Vitellaria paradoxa, we suggest collecting seed along the northern margins of its distribution and considering assisted

  11. Renewable Energy Production from Waste to Mitigate Climate Change and Counteract Soil Degradation - A Spatial Explicit Assessment for Japan

    Science.gov (United States)

    Kraxner, Florian; Yoshikawa, Kunio; Leduc, Sylvain; Fuss, Sabine; Aoki, Kentaro; Yamagata, Yoshiki

    2014-05-01

    Waste production from urban areas is growing faster than urbanization itself, while at the same time urban areas are increasingly contributing substantial emissions causing climate change. Estimates indicate for urban residents a per capita solid waste (MSW) production of 1.2 kg per day, subject to further increase to 1.5 kg beyond 2025. Waste water and sewage production is estimated at about 260 liters per capita and day, also at increasing rates. Based on these figures, waste - including e.g. MSW, sewage and animal manure - can generally be assumed as a renewable resource with varying organic components and quantity. This paper demonstrates how new and innovative technologies in the field of Waste-to-Green Products can help in various ways not only to reduce costs for waste treatment, reduce the pressure on largely overloaded dump sites, and reduce also the effect of toxic materials at the landfill site and by that i.e. protect the groundwater. Moreover, Waste-to-Green Products can contribute actively to mitigating climate change through fossil fuel substitution and carbon sequestration while at the same time counteracting negative land use effects from other types of renewable energy and feedstock production through substitution. At the same time, the co-production and recycling of fertilizing elements and biochar can substantially counteract soil degradation and improve the soil organic carbon content of different land use types. The overall objective of this paper is to assess the total climate change mitigation potential of MSW, sewage and animal manure for Japan. A techno-economic approach is used to inform the policy discussion on the suitability of this substantial and sustainable mitigation option. We examine the spatial explicit technical mitigation potential from e.g. energy substitution and carbon sequestration through biochar in rural and urban Japan. For this exercise, processed information on respective Japanese waste production, energy demand

  12. Bacteria can form interconnected microcolonies when a self-excreted product reduces their surface motility: evidence from individual-based model simulations

    DEFF Research Database (Denmark)

    Mabrouk, Nabil; Deffuant, Guillaume; Tolker-Nielsen, Tim

    2010-01-01

    Recent experimental observations of Pseudomonas aeruginosa, a model bacterium in biofilm research, reveal that, under specific growth conditions, bacterial cells form patterns of interconnected microcolonies. In the present work, we use an individual-based model to assess the involvement of bacte......Recent experimental observations of Pseudomonas aeruginosa, a model bacterium in biofilm research, reveal that, under specific growth conditions, bacterial cells form patterns of interconnected microcolonies. In the present work, we use an individual-based model to assess the involvement...... of bacteria motility and self-produced extracellular substance in the formation of these patterns. In our simulations, the pattern of interconnected microcolonies appears only when bacteria motility is reduced by excreted extracellular macromolecules. Immotile bacteria form isolated microcolonies...... and constantly motile bacteria form flat biofilms. Based on experimental data and computer simulations, we suggest a mechanism that could be responsible for these interconnected microcolonies....

  13. Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

    Science.gov (United States)

    Poyatos, Rafael; Sus, Oliver; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi

    2018-05-01

    The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density) in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2). We simulated gaps at different missingness levels (10-80 %) in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN), ordinary and regression kriging, and multivariate imputation using chained equations (MICE) to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %), species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables allowed us to fill the gaps in

  14. Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

    Directory of Open Access Journals (Sweden)

    R. Poyatos

    2018-05-01

    Full Text Available The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2. We simulated gaps at different missingness levels (10–80 % in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN, ordinary and regression kriging, and multivariate imputation using chained equations (MICE to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %, species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables

  15. Spatially explicit characterization of acidifying and eutrophying air pollution in life-cycle assessment

    NARCIS (Netherlands)

    Huijbregts, Mark A J; Schöpp, Wolfgang; Verkuijlen, Evert; Heijungs, Reinout; Reijnders, Lucas

    2001-01-01

    Simple models are often used to assess the potential impact of acidifying and eutrophying substances released during the life cycle of products. As fate, background depositions, and ecosystem sensitivity are not included in these models, environmental life-cycle assessment of products (LCA) may

  16. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

    Science.gov (United States)

    Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.

    2014-04-01

    The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.

  17. Recovering the geographic origin of early modern humans by realistic and spatially explicit simulations

    OpenAIRE

    Ray, Nicolas; Currat, Mathias; Berthier, Pierre; Excoffier, Laurent

    2005-01-01

    Most genetic and archeological evidence argue in favor of a recent and unique origin of modern humans in sub-Saharan Africa, but no attempt has ever been made at quantifying the likelihood of this model, relative to alternative hypotheses of human evolution. In this paper, we investigate the possibility of using multilocus genetic data to correctly infer the geographic origin of humans, and to distinguish between a unique origin (UO) and a multiregional evolution (ME) model. We introduce here...

  18. Crucial nesting habitat for gunnison sage-grouse: A spatially explicit hierarchical approach

    Science.gov (United States)

    Aldridge, Cameron L.; Saher, D.J.; Childers, T.M.; Stahlnecker, K.E.; Bowen, Z.H.

    2012-01-01

    Gunnison sage-grouse (Centrocercus minimus) is a species of special concern and is currently considered a candidate species under Endangered Species Act. Careful management is therefore required to ensure that suitable habitat is maintained, particularly because much of the species' current distribution is faced with exurban development pressures. We assessed hierarchical nest site selection patterns of Gunnison sage-grouse inhabiting the western portion of the Gunnison Basin, Colorado, USA, at multiple spatial scales, using logistic regression-based resource selection functions. Models were selected using Akaike Information Criterion corrected for small sample sizes (AIC c) and predictive surfaces were generated using model averaged relative probabilities. Landscape-scale factors that had the most influence on nest site selection included the proportion of sagebrush cover >5%, mean productivity, and density of 2 wheel-drive roads. The landscape-scale predictive surface captured 97% of known Gunnison sage-grouse nests within the top 5 of 10 prediction bins, implicating 57% of the basin as crucial nesting habitat. Crucial habitat identified by the landscape model was used to define the extent for patch-scale modeling efforts. Patch-scale variables that had the greatest influence on nest site selection were the proportion of big sagebrush cover >10%, distance to residential development, distance to high volume paved roads, and mean productivity. This model accurately predicted independent nest locations. The unique hierarchical structure of our models more accurately captures the nested nature of habitat selection, and allowed for increased discrimination within larger landscapes of suitable habitat. We extrapolated the landscape-scale model to the entire Gunnison Basin because of conservation concerns for this species. We believe this predictive surface is a valuable tool which can be incorporated into land use and conservation planning as well the assessment of

  19. Spatially Explicit Simulation of Mesotopographic Controls on Peatland Hydrology and Carbon Fluxes

    Science.gov (United States)

    Sonnentag, O.; Chen, J. M.; Roulet, N. T.

    2006-12-01

    A number of field carbon flux measurements, paleoecological records, and model simulations have acknowledged the importance of northern peatlands in terrestrial carbon cycling and methane emissions. An important parameter in peatlands that influences both net primary productivity, the net gain of carbon through photosynthesis, and decomposition under aerobic and anaerobic conditions, is the position of the water table. Biological and physical processes involved in peatland carbon dynamics and their hydrological controls operate at different spatial scales. The highly variable hydraulic characteristics of the peat profile and the overall shape of the peat body as defined by its surface topography at the mesoscale (104 m2) are of major importance for peatland water table dynamics. Common types of peatlands include bogs with a slightly domed centre. As a result of the convex profile, their water supply is restricted to atmospheric inputs, and water is mainly shed by shallow subsurface flow. From a modelling perspective the influence of mesotopographic controls on peatland hydrology and thus carbon balance requires that process-oriented models that examine the links between peatland hydrology, ecosystem functioning, and climate must incorporate some form of lateral subsurface flow consideration. Most hydrological and ecological modelling studies in complex terrain explicitly account for the topographic controls on lateral subsurface flow through digital elevation models. However, modelling studies in peatlands often employ simple empirical parameterizations of lateral subsurface flow, neglecting the influence of peatlands low relief mesoscale topography. Our objective is to explicitly simulate the mesotopographic controls on peatland hydrology and carbon fluxes using the Boreal Ecosystem Productivity Simulator (BEPS) adapted to northern peatlands. BEPS is a process-oriented ecosystem model in a remote sensing framework that takes into account peatlands multi

  20. Spatially explicit fate factors of waterborne nitrogen emissions at the global scale

    DEFF Research Database (Denmark)

    Cosme, Nuno Miguel Dias; Mayorga, Emilio; Hauschild, Michael Zwicky

    2017-01-01

    water. Spatial aggregation of the FFs at the continental level decreases this variation to 1 order of magnitude or less for all routes. Coastal water residence time was found to show inconsistency and scarcity of literature sources. Improvement of data quality for this parameter is suggested......Purpose: Marine eutrophication impacts due to waterborne nitrogen (N) emissions may vary significantly with their type and location. The environmental fate of dissolved inorganic nitrogen (DIN) forms is essential to understand the impacts they may trigger in receiving coastal waters. Current life...... and river basin resolution. Methods: The FF modelling work includes DIN removal processes in both inland (soil and river) and marine compartments. Model input parameters are the removal coefficients extracted from the Global NEWS 2-DIN model and residence time of receiving coastal waters. The resulting FFs...

  1. Spatio-temporal dynamics of growth and survival of Lesser Sandeel early life-stages in the North Sea: Predictions from a coupled individual-based and hydrodynamic-biogeochemical model

    DEFF Research Database (Denmark)

    Gurkan, Zeren; Christensen, Asbjørn; Maar, Marie

    2013-01-01

    Accounting for the individual variability and regional variations are important when predicting recruitment in fish species. Spatially explicit descriptions for recruitment in sandeels are necessary and sandeel growth and survival depend locally on zooplankton prey. We investigate the responses o...

  2. Effects of fishing effort allocation scenarios on energy efficiency and profitability: an individual-based model applied to Danish fisheries

    DEFF Research Database (Denmark)

    Bastardie, Francois; Nielsen, J. Rasmus; Andersen, Bo Sølgaard

    2010-01-01

    to the harbour, and (C) allocating effort towards optimising the expected area-specific profit per trip. The model is informed by data from each Danish fishing vessel >15 m after coupling its high resolution spatial and temporal effort data (VMS) with data from logbook landing declarations, sales slips, vessel...... effort allocation has actually been sub-optimal because increased profits from decreased fuel consumption and larger landings could have been obtained by applying a different spatial effort allocation. Based on recent advances in VMS and logbooks data analyses, this paper contributes to improve...

  3. Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska

    Science.gov (United States)

    Ji, Lei; Wylie, Bruce K.; Brown, Dana R. N.; Peterson, Birgit E.; Alexander, Heather D.; Mack, Michelle C.; Rover, Jennifer R.; Waldrop, Mark P.; McFarland, Jack W.; Chen, Xuexia; Pastick, Neal J.

    2015-01-01

    Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.

  4. Estimating black bear density in New Mexico using noninvasive genetic sampling coupled with spatially explicit capture-recapture methods

    Science.gov (United States)

    Gould, Matthew J.; Cain, James W.; Roemer, Gary W.; Gould, William R.

    2016-01-01

    During the 2004–2005 to 2015–2016 hunting seasons, the New Mexico Department of Game and Fish (NMDGF) estimated black bear abundance (Ursus americanus) across the state by coupling density estimates with the distribution of primary habitat generated by Costello et al. (2001). These estimates have been used to set harvest limits. For example, a density of 17 bears/100 km2 for the Sangre de Cristo and Sacramento Mountains and 13.2 bears/100 km2 for the Sandia Mountains were used to set harvest levels. The advancement and widespread acceptance of non-invasive sampling and mark-recapture methods, prompted the NMDGF to collaborate with the New Mexico Cooperative Fish and Wildlife Research Unit and New Mexico State University to update their density estimates for black bear populations in select mountain ranges across the state.We established 5 study areas in 3 mountain ranges: the northern (NSC; sampled in 2012) and southern Sangre de Cristo Mountains (SSC; sampled in 2013), the Sandia Mountains (Sandias; sampled in 2014), and the northern (NSacs) and southern Sacramento Mountains (SSacs; both sampled in 2014). We collected hair samples from black bears using two concurrent non-invasive sampling methods, hair traps and bear rubs. We used a gender marker and a suite of microsatellite loci to determine the individual identification of hair samples that were suitable for genetic analysis. We used these data to generate mark-recapture encounter histories for each bear and estimated density in a spatially explicit capture-recapture framework (SECR). We constructed a suite of SECR candidate models using sex, elevation, land cover type, and time to model heterogeneity in detection probability and the spatial scale over which detection probability declines. We used Akaike’s Information Criterion corrected for small sample size (AICc) to rank and select the most supported model from which we estimated density.We set 554 hair traps, 117 bear rubs and collected 4,083 hair

  5. Ecosystem services in agricultural landscapes: a spatially explicit approach to support sustainable soil management.

    Science.gov (United States)

    Forouzangohar, Mohsen; Crossman, Neville D; MacEwan, Richard J; Wallace, D Dugal; Bennett, Lauren T

    2014-01-01

    Soil degradation has been associated with a lack of adequate consideration of soil ecosystem services. We demonstrate a broadly applicable method for mapping changes in the supply of two priority soil ecosystem services to support decisions about sustainable land-use configurations. We used a landscape-scale study area of 302 km(2) in northern Victoria, south-eastern Australia, which has been cleared for intensive agriculture. Indicators representing priority soil services (soil carbon sequestration and soil water storage) were quantified and mapped under both a current and a future 25-year land-use scenario (the latter including a greater diversity of land uses and increased perennial crops and irrigation). We combined diverse methods, including soil analysis using mid-infrared spectroscopy, soil biophysical modelling, and geostatistical interpolation. Our analysis suggests that the future land-use scenario would increase the landscape-level supply of both services over 25 years. Soil organic carbon content and water storage to 30 cm depth were predicted to increase by about 11% and 22%, respectively. Our service maps revealed the locations of hotspots, as well as potential trade-offs in service supply under new land-use configurations. The study highlights the need to consider diverse land uses in sustainable management of soil services in changing agricultural landscapes.

  6. Comparing spatially explicit ecological and social values for natural areas to identify effective conservation strategies.

    Science.gov (United States)

    Bryan, Brett Anthony; Raymond, Christopher Mark; Crossman, Neville David; King, Darran

    2011-02-01

    Consideration of the social values people assign to relatively undisturbed native ecosystems is critical for the success of science-based conservation plans. We used an interview process to identify and map social values assigned to 31 ecosystem services provided by natural areas in an agricultural landscape in southern Australia. We then modeled the spatial distribution of 12 components of ecological value commonly used in setting spatial conservation priorities. We used the analytical hierarchy process to weight these components and used multiattribute utility theory to combine them into a single spatial layer of ecological value. Social values assigned to natural areas were negatively correlated with ecological values overall, but were positively correlated with some components of ecological value. In terms of the spatial distribution of values, people valued protected areas, whereas those natural areas underrepresented in the reserve system were of higher ecological value. The habitats of threatened animal species were assigned both high ecological value and high social value. Only small areas were assigned both high ecological value and high social value in the study area, whereas large areas of high ecological value were of low social value, and vice versa. We used the assigned ecological and social values to identify different conservation strategies (e.g., information sharing, community engagement, incentive payments) that may be effective for specific areas. We suggest that consideration of both ecological and social values in selection of conservation strategies can enhance the success of science-based conservation planning. ©2010 Society for Conservation Biology.

  7. Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth

    Science.gov (United States)

    Carr, Joel; D'Odorico, Paul; McGlathery, Karen; Wiberg, Patricia L.

    2016-01-01

    In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.

  8. Mapping the impacts of thermoelectric power generation: a global, spatially explicit database

    Science.gov (United States)

    Raptis, Catherine; Pfister, Stephan

    2017-04-01

    Thermoelectric power generation is associated with environmental pressures resulting from emissions to air and water, as well as water consumption. The need to achieve global coverage in related studies has become pressing in view of climate change. At the same time, the ability to quantify impacts from power production on a high resolution remains pertinent, given their highly regionalized nature, particularly when it comes to water-related impacts. Efforts towards global coverage have increased in recent years, but most work on the impacts of global electricity production presents a coarse geographical differentiation. Over the past few years we have begun a concerted effort to create and make available a global georeferenced inventory of thermoelectric power plant operational characteristics and emissions, by modelling the relevant processes on the highest possible level: that of a generating unit. Our work extends and enhances a commercially available global power plant database, and so far includes: - Georeferencing the generating units and populating the gaps in their steam properties. - Identifying the cooling system for 92% of the global installed thermoelectric power capacity. - Using the completed steam property data, along with local environmental temperature data, to systematically solve the Rankine cycle for each generating unit, involving: i) distinguishing between simple, reheat, and cogenerative cycles, and accounting for particularities in nuclear power cycles; ii) accounting for the effect of different cooling systems (once-through, recirculating (wet tower), dry cooling) on the thermodynamic cycle. One of the direct outcomes of solving the Rankine cycle is the cycle efficiency, an indispensable parameter in any study related to power production, including the quantification of air emissions and water consumption. Another direct output, for those units employing once-through cooling, is the rate of heat rejection to water, which can lead to

  9. An individual-based model of the evolution of pesticide resistance in heterogeneous environments: control of Meligethes aeneus population in oilseed rape crops.

    Science.gov (United States)

    Stratonovitch, Pierre; Elias, Jan; Denholm, Ian; Slater, Russell; Semenov, Mikhail A

    2014-01-01

    Preventing a pest population from damaging an agricultural crop and, at the same time, preventing the development of pesticide resistance is a major challenge in crop protection. Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a difficult and complex task. It is extremely challenging to investigate such interactions experimentally at realistic spatial and temporal scales. Mathematical modelling and computer simulation have, therefore, been used to analyse resistance evolution and to evaluate potential resistance management tactics. Of the many modelling approaches available, individual-based modelling of a pest population offers most flexibility to include and analyse numerous factors and their interactions. Here, a pollen beetle (Meligethes aeneus) population was modelled as an aggregate of individual insects inhabiting a spatially heterogeneous landscape. The development of the pest and host crop (oilseed rape) was driven by climatic variables. The agricultural land of the landscape was managed by farmers applying a specific rotation and crop protection strategy. The evolution of a single resistance allele to the pyrethroid lambda cyhalothrin was analysed for different combinations of crop management practices and for a recessive, intermediate and dominant resistance allele. While the spread of a recessive resistance allele was severely constrained, intermediate or dominant resistance alleles showed a similar response to the management regime imposed. Calendar treatments applied irrespective of pest density accelerated the development of resistance compared to ones applied in response to prescribed pest density thresholds. A greater proportion of spring-sown oilseed rape was also found to increase the speed of resistance as it increased the period of insecticide exposure. Our study demonstrates the flexibility and power of an individual-based model to simulate how farming

  10. An individual-based model of the evolution of pesticide resistance in heterogeneous environments: control of Meligethes aeneus population in oilseed rape crops.

    Directory of Open Access Journals (Sweden)

    Pierre Stratonovitch

    Full Text Available Preventing a pest population from damaging an agricultural crop and, at the same time, preventing the development of pesticide resistance is a major challenge in crop protection. Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a difficult and complex task. It is extremely challenging to investigate such interactions experimentally at realistic spatial and temporal scales. Mathematical modelling and computer simulation have, therefore, been used to analyse resistance evolution and to evaluate potential resistance management tactics. Of the many modelling approaches available, individual-based modelling of a pest population offers most flexibility to include and analyse numerous factors and their interactions. Here, a pollen beetle (Meligethes aeneus population was modelled as an aggregate of individual insects inhabiting a spatially heterogeneous landscape. The development of the pest and host crop (oilseed rape was driven by climatic variables. The agricultural land of the landscape was managed by farmers applying a specific rotation and crop protection strategy. The evolution of a single resistance allele to the pyrethroid lambda cyhalothrin was analysed for different combinations of crop management practices and for a recessive, intermediate and dominant resistance allele. While the spread of a recessive resistance allele was severely constrained, intermediate or dominant resistance alleles showed a similar response to the management regime imposed. Calendar treatments applied irrespective of pest density accelerated the development of resistance compared to ones applied in response to prescribed pest density thresholds. A greater proportion of spring-sown oilseed rape was also found to increase the speed of resistance as it increased the period of insecticide exposure. Our study demonstrates the flexibility and power of an individual-based model to

  11. Individual-Based Modeling of Tuberculosis in a User-Friendly Interface: Understanding the Epidemiological Role of Population Heterogeneity in a City.

    Science.gov (United States)

    Prats, Clara; Montañola-Sales, Cristina; Gilabert-Navarro, Joan F; Valls, Joaquim; Casanovas-Garcia, Josep; Vilaplana, Cristina; Cardona, Pere-Joan; López, Daniel

    2015-01-01

    For millennia tuberculosis (TB) has shown a successful strategy to survive, making it one of the world's deadliest infectious diseases. This resilient behavior is based not only on remaining hidden in most of the infected population, but also by showing slow evolution in most sick people. The course of the disease within a population is highly related to its heterogeneity. Thus, classic epidemiological approaches with a top-down perspective have not succeeded in understanding its dynamics. In the past decade a few individual-based models were built, but most of them preserved a top-down view that makes it difficult to study a heterogeneous population. We propose an individual-based model developed with a bottom-up approach to studying the dynamics of pulmonary TB in a certain population, considered constant. Individuals may belong to the following classes: healthy, infected, sick, under treatment, and treated with a probability of relapse. Several variables and parameters account for their age, origin (native or immigrant), immunodeficiency, diabetes, and other risk factors (smoking and alcoholism). The time within each infection state is controlled, and sick individuals may show a cavitated disease or not that conditions infectiousness. It was implemented in NetLogo because it allows non-modelers to perform virtual experiments with a user-friendly interface. The simulation was conducted with data from Ciutat Vella, a district of Barcelona with an incidence of 67 TB cases per 100,000 inhabitants in 2013. Several virtual experiments were performed to relate the disease dynamics with the structure of the infected subpopulation (e.g., the distribution of infected times). Moreover, the short-term effect of health control policies on modifying that structure was studied. Results show that the characteristics of the population are crucial for the local epidemiology of TB. The developed user-friendly tool is ready to test control strategies of disease in any city in the

  12. Modelling the Immune Response to Cancer: An Individual-Based Approach Accounting for the Difference in Movement Between Inactive and Activated T Cells.

    Science.gov (United States)

    Macfarlane, Fiona R; Lorenzi, Tommaso; Chaplain, Mark A J

    2018-06-01

    A growing body of experimental evidence indicates that immune cells move in an unrestricted search pattern if they are in the pre-activated state, whilst they tend to stay within a more restricted area upon activation induced by the presence of tumour antigens. This change in movement is not often considered in the existing mathematical models of the interactions between immune cells and cancer cells. With the aim to fill such a gap in the existing literature, in this work we present a spatially structured individual-based model of tumour-immune competition that takes explicitly into account the difference in movement between inactive and activated immune cells. In our model, a Lévy walk is used to capture the movement of inactive immune cells, whereas Brownian motion is used to describe the movement of antigen-activated immune cells. The effects of activation of immune cells, the proliferation of cancer cells and the immune destruction of cancer cells are also modelled. We illustrate the ability of our model to reproduce qualitatively the spatial trajectories of immune cells observed in experimental data of single-cell tracking. Computational simulations of our model further clarify the conditions for the onset of a successful immune action against cancer cells and may suggest possible targets to improve the efficacy of cancer immunotherapy. Overall, our theoretical work highlights the importance of taking into account spatial interactions when modelling the immune response to cancer cells.

  13. Fish Individual-based Numerical Simulator (FINS): A particle-based model of juvenile salmonid movement and dissolved gas exposure history in the Columbia River Basin

    International Nuclear Information System (INIS)

    Scheibe, Timothy D.; Richmond, Marshall C.

    2002-01-01

    This paper describes a numerical model of juvenile salmonid migration in the Columbia and Snake Rivers. The model, called the Fish Individual-based Numerical Simulator or FINS, employs a discrete, particle-based approach to simulate the migration and history of exposure to dissolved gases of individual fish. FINS is linked to a two-dimensional (vertically-averaged) hydrodynamic simulator that quantifies local water velocity, temperature, and dissolved gas levels as a function of river flow rates and dam operations. Simulated gas exposure histories can be input to biological mortality models to predict the effects of various river configurations on fish injury and mortality due to dissolved gas supersaturation. Therefore, FINS serves as a critical linkage between hydrodynamic models of the river system and models of biological impacts. FINS was parameterized and validated based on observations of individual fish movements collected using radiotelemetry methods during 1997 and 1998 . A quasi-inverse approach was used to decouple fish swimming movements from advection with the local water velocity, allowing inference of time series of non-advective displacements of individual fish from the radiotelemetry data. Statistical analyses of these displacements are presented, and confirm that strong temporal correlation of fish swimming behavior persists in some cases over several hours. A correlated random-walk model was employed to simulate the observed migration behavior, and parameters of the model were estimated that lead to close correspondence between predictions and observations

  14. Growth potential and habitat requirements of endangered age-0 pallid sturgeon (Scaphirhynchus albus) in the Missouri River, USA, determined using a individual-based model framework

    Science.gov (United States)

    Deslauriers, David; Heironimus, Laura B.; Rapp, Tobias; Graeb, Brian D. S.; Klumb, Robert A.; Chipps, Steven R.

    2018-01-01

    An individual-based model framework was used to evaluate growth potential of the federally endangered pallid sturgeon (Scaphirhynchus albus) in the Missouri River. The model, developed for age-0 sturgeon, combines information on functional feeding response, bioenergetics and swimming ability to regulate consumption and growth within a virtual foraging arena. Empirical data on water temperature, water velocity and prey density were obtained from three sites in the Missouri River and used as inputs in the model to evaluate hypotheses concerning factors affecting pallid sturgeon growth. The model was also used to evaluate the impacts of environmental heterogeneity and water velocity on individual growth variability, foraging success and dispersal ability. Growth was simulated for a period of 100 days using 100 individuals (first feeding; 19 mm and 0.035 g) per scenario. Higher growth was shown to occur at sites where high densities of Ephemeroptera and Chironomidae larvae occurred throughout the growing season. Highly heterogeneous habitats (i.e., wide range of environmental conditions) and moderate water velocities (0.3 m/s) were also found to positively affect growth rates. The model developed here provides an important management and conservation tool for evaluating growth hypotheses and(or) identifying habitats in the Missouri River that are favourable to age-0 pallid sturgeon growth.

  15. Factors affecting competitive dominance of rainbow trout over brook trout in southern Appalachian streams: Implications of an individual-based model

    Energy Technology Data Exchange (ETDEWEB)

    Clark, M.E. [Univ. of Tennessee, Knoxville, TN (United States); Rose, K.A. [Oak Ridge National Lab., TN (United States)

    1997-01-01

    We used an individual-based model to examine possible explanations for the dominance of rainbow trout Oncorhynchus mykiss over brook trout Salvelinus fontinalis in southern Appalachian streams. Model simulations were used to quantify the effects on interspecific competition of (1) competitive advantage for feeding sites by rainbow trout, (2) latitudinal differences in stream temperatures, flows, and daylight, (3) year-class failures, (4) lower fecundity of brook trout, and (5) reductions in spawning habitat. The model tracks the daily spawning, growth, and survival of individuals of both species throughout their lifetime in a series of connected stream habitat units (pools, runs, or riffles). Average densities of each species based on 100-year simulations were compared for several levels of each of the five factors and for sympatric and allopatric conditions. Based on model results and empirical information, we conclude that more frequent year-class failures and the lower fecundity of brook trout are both possible and likely explanations for rainbow trout dominance, that warmer temperatures due to latitude and limited spawning habitat are possible but unlikely explanations, and that competitive advantage for feeding sites by rainbow trout is an unlikely explanation. Additional field work should focus on comparative studies of the reproductive success and the early life stage mortalities of brook and rainbow trout among Appalachian streams with varying rainbow trout dominance. 53 refs., 11 figs.

  16. Digital Image Analysis of Yeast Single Cells Growing in Two Different Oxygen Concentrations to Analyze the Population Growth and to Assist Individual-Based Modeling.

    Science.gov (United States)

    Ginovart, Marta; Carbó, Rosa; Blanco, Mónica; Portell, Xavier

    2017-01-01

    Nowadays control of the growth of Saccharomyces to obtain biomass or cellular wall components is crucial for specific industrial applications. The general aim of this contribution is to deal with experimental data obtained from yeast cells and from yeast cultures to attempt the integration of the two levels of information, individual and population, to progress in the control of yeast biotechnological processes by means of the overall analysis of this set of experimental data, and to assist in the improvement of an individual-based model, namely, INDISIM- Saccha . Populations of S. cerevisiae growing in liquid batch culture, in aerobic and microaerophilic conditions, were studied. A set of digital images was taken during the population growth, and a protocol for the treatment and analyses of the images obtained was established. The piecewise linear model of Buchanan was adjusted to the temporal evolutions of the yeast populations to determine the kinetic parameters and changes of growth phases. In parallel, for all the yeast cells analyzed, values of direct morphological parameters, such as area, perimeter, major diameter, minor diameter, and derived ones, such as circularity and elongation, were obtained. Graphical and numerical methods from descriptive statistics were applied to these data to characterize the growth phases and the budding state of the yeast cells in both experimental conditions, and inferential statistical methods were used to compare the diverse groups of data achieved. Oxidative metabolism of yeast in a medium with oxygen available and low initial sugar concentration can be taken into account in order to obtain a greater number of cells or larger cells. Morphological parameters were analyzed statistically to identify which were the most useful for the discrimination of the different states, according to budding and/or growth phase, in aerobic and microaerophilic conditions. The use of the experimental data for subsequent modeling work was then

  17. Early Engagement of Stakeholders with Individual-Based Modeling Can Inform Research for Improving Invasive Species Management: The Round Goby as a Case Study

    Directory of Open Access Journals (Sweden)

    Emma Samson

    2017-11-01

    Full Text Available Individual-based models (IBMs incorporating realistic representations of key range-front processes such as dispersal can be used as tools to investigate the dynamics of invasive species. Managers can apply insights from these models to take effective action to prevent further spread and prioritize measures preventing establishment of invasive species. We highlight here how early-stage IBMs (constructed under constraints of time and data availability can also play an important role in defining key research priorities for providing key information on the biology of an invasive species in order that subsequent models can provide robust insight into potential management interventions. The round goby, Neogobius melanostomus, is currently spreading through the Baltic Sea, with major negative effects being reported in the wake of its invasion. Together with stakeholders, we parameterize an IBM to investigate the goby's potential spread pattern throughout the Gulf of Gdansk and the Baltic Sea. Model parameters were assigned by integrating information obtained through stakeholder interaction, from scientific literature, or estimated using an inverse modeling approach when not available. IBMs can provide valuable direction to research on invasive species even when there is limited data and/or time available to parameterize/fit them to the degree to which we might aspire in an ideal world. Co-development of models with stakeholders can be used to recognize important invasion patterns, in addition to identifying and estimating unknown environmental parameters, thereby guiding the direction of future research. Well-parameterized and validated models are not required in the earlier stages of the modeling cycle where their main utility is as a tool for thought.

  18. Seasonal patterns in growth, blood consumption, and effects on hosts by parasitic-phase sea lampreys in the Great Lakes: an individual-based model approach

    Science.gov (United States)

    Madenjian, Charles P.; Cochran, Philip A.; Bergstedt, Roger A.

    2003-01-01

    An individual-based model (IBM) was developed for sea lamprey (Petromyzon marinus) populations in the Laurentian Great Lakes. The IBM was then calibrated to observed growth, by season, for sea lampreys in northern Lake Huron under two different water temperature regimes: a regime experienced by Seneca-strain lake trout (Salvelinus namaycush) and a regime experienced by Marquettestrain lake trout. Modeling results indicated that seasonal blood consumption under the Seneca regime was very similar to that under the Marquette regime. Simulated mortality of lake trout directly due to blood removal by sea lampreys occurred at nearly twice the rate during August and September under the Marquette regime than under the Seneca regime. However, cumulative sea lamprey-induced mortality on lake trout over the entire duration of the sea lamprey's parasitic phase was only 7% higher for the Marquette regime compared with the Seneca regime. Thus, these modeling results indicated that the strain composition of the host (lake trout) population was not important in determining total number of lake trout deaths or total blood consumption attributable to the sea lamprey population, given the sea lamprey growth pattern. Regardless of water temperature regime, both blood consumption rate by sea lampreys and rate of sea lamprey-induced mortality on lake trout peaked in late October. Elevated blood consumption in late October appeared to be unrelated to changes in water temperature. The IBM approach should prove useful in optimizing control of sea lampreys in the Laurentian Great Lakes.

  19. Quantifying population-level risks using an individual-based model: sea otters, Harlequin Ducks, and the Exxon Valdez oil spill.

    Science.gov (United States)

    Harwell, Mark A; Gentile, John H; Parker, Keith R

    2012-07-01

    Ecological risk assessments need to advance beyond evaluating risks to individuals that are largely based on toxicity studies conducted on a few species under laboratory conditions, to assessing population-level risks to the environment, including considerations of variability and uncertainty. Two individual-based models (IBMs), recently developed to assess current risks to sea otters and seaducks in Prince William Sound more than 2 decades after the Exxon Valdez oil spill (EVOS), are used to explore population-level risks. In each case, the models had previously shown that there were essentially no remaining risks to individuals from polycyclic aromatic hydrocarbons (PAHs) derived from the EVOS. New sensitivity analyses are reported here in which hypothetical environmental exposures to PAHs were heuristically increased until assimilated doses reached toxicity reference values (TRVs) derived at the no-observed-adverse-effects and lowest-observed-adverse-effects levels (NOAEL and LOAEL, respectively). For the sea otters, this was accomplished by artificially increasing the number of sea otter pits that would intersect remaining patches of subsurface oil residues by orders of magnitude over actual estimated rates. Similarly, in the seaduck assessment, the PAH concentrations in the constituents of diet, sediments, and seawater were increased in proportion to their relative contributions to the assimilated doses by orders of magnitude over measured environmental concentrations, to reach the NOAEL and LOAEL thresholds. The stochastic IBMs simulated millions of individuals. From these outputs, frequency distributions were derived of assimilated doses for populations of 500,000 sea otters or seaducks in each of 7 or 8 classes, respectively. Doses to several selected quantiles were analyzed, ranging from the 1-in-1000th most-exposed individuals (99.9% quantile) to the median-exposed individuals (50% quantile). The resulting families of quantile curves provide the basis for

  20. Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China.

    Science.gov (United States)

    Chen, Qian; Ding, Mingjun; Yang, Xuchao; Hu, Kejia; Qi, Jiaguo

    2018-05-25

    The increase in the frequency and intensity of extreme heat events, which are potentially associated with climate change in the near future, highlights the importance of heat health risk assessment, a significant reference for heat-related death reduction and intervention. However, a spatiotemporal mismatch exists between gridded heat hazard and human exposure in risk assessment, which hinders the identification of high-risk areas at finer scales. A human settlement index integrated by nighttime light images, enhanced vegetation index, and digital elevation model data was utilized to assess the human exposure at high spatial resolution. Heat hazard and vulnerability index were generated by land surface temperature and demographic and socioeconomic census data, respectively. Spatially explicit assessment of heat health risk and its driving factors was conducted in the Yangtze River Delta (YRD), east China at 250 m pixel level. High-risk areas were mainly distributed in the urbanized areas of YRD, which were mostly driven by high human exposure and heat hazard index. In some less-urbanized cities and suburban and rural areas of mega-cities, the heat health risks are in second priority. The risks in some less-developed areas were high despite the low human exposure index because of high heat hazard and vulnerability index. This study illustrated a methodology for identifying high-risk areas by combining freely available multi-source data. Highly urbanized areas were considered hotspots of high heat health risks, which were largely driven by the increasing urban heat island effects and population density in urban areas. Repercussions of overheating were weakened due to the low social vulnerability in some central areas benefitting from the low proportion of sensitive population or the high level of socioeconomic development. By contrast, high social vulnerability intensifies heat health risks in some less-urbanized cities and suburban areas of mega-cities.

  1. Influence of Nutrient Availability and Quorum Sensing on the Formation of Metabolically Inactive Microcolonies Within Structurally Heterogeneous Bacterial Biofilms: An Individual-Based 3D Cellular Automata Model.

    Science.gov (United States)

    Machineni, Lakshmi; Rajapantul, Anil; Nandamuri, Vandana; Pawar, Parag D

    2017-03-01

    The resistance of bacterial biofilms to antibiotic treatment has been attributed to the emergence of structurally heterogeneous microenvironments containing metabolically inactive cell populations. In this study, we use a three-dimensional individual-based cellular automata model to investigate the influence of nutrient availability and quorum sensing on microbial heterogeneity in growing biofilms. Mature biofilms exhibited at least three structurally distinct strata: a high-volume, homogeneous region sandwiched between two compact sections of high heterogeneity. Cell death occurred preferentially in layers in close proximity to the substratum, resulting in increased heterogeneity in this section of the biofilm; the thickness and heterogeneity of this lowermost layer increased with time, ultimately leading to sloughing. The model predicted the formation of metabolically dormant cellular microniches embedded within faster-growing cell clusters. Biofilms utilizing quorum sensing were more heterogeneous compared to their non-quorum sensing counterparts, and resisted sloughing, featuring a cell-devoid layer of EPS atop the substratum upon which the remainder of the biofilm developed. Overall, our study provides a computational framework to analyze metabolic diversity and heterogeneity of biofilm-associated microorganisms and may pave the way toward gaining further insights into the biophysical mechanisms of antibiotic resistance.

  2. Heterozygosity in an isolated population of a large mammal founded by four individuals is predicted by an individual-based genetic model.

    Directory of Open Access Journals (Sweden)

    Jaana Kekkonen

    Full Text Available Within-population genetic diversity is expected to be dramatically reduced if a population is founded by a low number of individuals. Three females and one male white-tailed deer Odocoileus virginianus, a North American species, were successfully introduced in Finland in 1934 and the population has since been growing rapidly, but remained in complete isolation from other populations.Based on 14 microsatellite loci, the expected heterozygosity H was 0.692 with a mean allelic richness (AR of 5.36, which was significantly lower than what was found in Oklahoma, U.S.A. (H = 0.742; AR = 9.07, demonstrating that a bottleneck occurred. Observed H was in line with predictions from an individual-based model where the genealogy of the males and females in the population were tracked and the population's demography was included.Our findings provide a rare within-population empirical test of the founder effect and suggest that founding a population by a small number of individuals need not have a dramatic impact on heterozygosity in an iteroparous species.

  3. A Method to Estimate the Size and Characteristics of HIV-positive Populations Using an Individual-based Stochastic Simulation Model

    DEFF Research Database (Denmark)

    Nakagawa, Fumiyo; van Sighem, Ard; Thiebaut, Rodolphe

    2016-01-01

    % plausibility range: 39,900-45,560) men who have sex with men were estimated to be living with HIV in the UK, of whom 10,400 (6,160-17,350) were undiagnosed. There were an estimated 3,210 (1,730-5,350) infections per year on average between 2010 and 2013. Sixty-two percent of the total HIV-positive population......It is important not only to collect epidemiologic data on HIV but to also fully utilize such information to understand the epidemic over time and to help inform and monitor the impact of policies and interventions. We describe and apply a novel method to estimate the size and characteristics of HIV-positive...... populations. The method was applied to data on men who have sex with men living in the UK and to a pseudo dataset to assess performance for different data availability. The individual-based simulation model was calibrated using an approximate Bayesian computation-based approach. In 2013, 48,310 (90...

  4. Legacy effects of wildfire on stream thermal regimes and rainbow trout ecology: an integrated analysis of observation and individual-based models

    Science.gov (United States)

    Rosenberger, Amanda E.; Dunham, Jason B.; Neuswanger, Jason R.; Railsback, Steven F.

    2015-01-01

    Management of aquatic resources in fire-prone areas requires understanding of fish species’ responses to wildfire and of the intermediate- and long-term consequences of these disturbances. We examined Rainbow Trout populations in 9 headwater streams 10 y after a major wildfire: 3 with no history of severe wildfire in the watershed (unburned), 3 in severely burned watersheds (burned), and 3 in severely burned watersheds subjected to immediate events that scoured the stream channel and eliminated streamside vegetation (burned and reorganized). Results of a previous study of this system suggested the primary lasting effects of this wildfire history on headwater stream habitat were differences in canopy cover and solar radiation, which led to higher summer stream temperatures. Nevertheless, trout were present throughout streams in burned watersheds. Older age classes were least abundant in streams draining watersheds with a burned and reorganized history, and individuals >1 y old were most abundant in streams draining watersheds with an unburned history. Burned history corresponded with fast growth, low lipid content, and early maturity of Rainbow Trout. We used an individual-based model of Rainbow Trout growth and demographic patterns to determine if temperature interactions with bioenergetics and competition among individuals could lead to observed phenotypic and ecological differences among populations in the absence of other plausible mechanisms. Modeling suggested that moderate warming associated with wildfire and channel disturbance history leads to faster individual growth, which exacerbates competition for limited food, leading to decreases in population densities. The inferred mechanisms from this modeling exercise suggest the transferability of ecological patterns to a variety of temperature-warming scenarios.

  5. The influence of agroforestry and other land-use types on the persistence of a Sumatran tiger (Panthera tigris sumatrae) population: an individual-based model approach.

    Science.gov (United States)

    Imron, Muhammad Ali; Herzog, Sven; Berger, Uta

    2011-08-01

    The importance of preserving both protected areas and their surrounding landscapes as one of the major conservation strategies for tigers has received attention over recent decades. However, the mechanism of how land-use surrounding protected areas affects the dynamics of tiger populations is poorly understood. We developed Panthera Population Persistence (PPP)--an individual-based model--to investigate the potential mechanism of the Sumatran tiger population dynamics in a protected area and under different land-use scenarios surrounding the reserve. We tested three main landscape compositions (single, combined and real land-uses of Tesso-Nilo National Park and its surrounding area) on the probability of and time to extinction of the Sumatran tiger over 20 years in Central Sumatra. The model successfully explains the mechanisms behind the population response of tigers under different habitat landscape compositions. Feeding and mating behaviours of tigers are key factors, which determined population persistence in a heterogeneous landscape. All single land-use scenarios resulted in tiger extinction but had a different probability of extinction within 20 years. If tropical forest was combined with other land-use types, the probability of extinction was smaller. The presence of agroforesty and logging concessions adjacent to protected areas encouraged the survival of tiger populations. However, with the real land-use scenario of Tesso-Nilo National Park, tigers could not survive for more than 10 years. Promoting the practice of agroforestry systems surrounding the park is probably the most reasonable way to steer land-use surrounding the Tesso-Nilo National Park to support tiger conservation.

  6. The Influence of Agroforestry and Other Land-Use Types on the Persistence of a Sumatran Tiger ( Panthera tigris sumatrae) Population: An Individual-Based Model Approach

    Science.gov (United States)

    Imron, Muhammad Ali; Herzog, Sven; Berger, Uta

    2011-08-01

    The importance of preserving both protected areas and their surrounding landscapes as one of the major conservation strategies for tigers has received attention over recent decades. However, the mechanism of how land-use surrounding protected areas affects the dynamics of tiger populations is poorly understood. We developed Panthera Population Persistence (PPP)—an individual-based model—to investigate the potential mechanism of the Sumatran tiger population dynamics in a protected area and under different land-use scenarios surrounding the reserve. We tested three main landscape compositions (single, combined and real land-uses of Tesso-Nilo National Park and its surrounding area) on the probability of and time to extinction of the Sumatran tiger over 20 years in Central Sumatra. The model successfully explains the mechanisms behind the population response of tigers under different habitat landscape compositions. Feeding and mating behaviours of tigers are key factors, which determined population persistence in a heterogeneous landscape. All single land-use scenarios resulted in tiger extinction but had a different probability of extinction within 20 years. If tropical forest was combined with other land-use types, the probability of extinction was smaller. The presence of agroforesty and logging concessions adjacent to protected areas encouraged the survival of tiger populations. However, with the real land-use scenario of Tesso-Nilo National Park, tigers could not survive for more than 10 years. Promoting the practice of agroforestry systems surrounding the park is probably the most reasonable way to steer land-use surrounding the Tesso-Nilo National Park to support tiger conservation.

  7. A spatial individual-based model predicting a great impact of copious sugar sources and resting sites on survival of Anopheles gambiae and malaria parasite transmission

    Science.gov (United States)

    Zhu, Lin; Qualls, Whitney A.; Marshall, John M; Arheart, Kris L.; DeAngelis, Donald L.; McManus, John W.; Traore, Sekou F.; Doumbia, Seydou; Schlein, Yosef; Muller, Gunter C.; Beier, John C.

    2015-01-01

    BackgroundAgent-based modelling (ABM) has been used to simulate mosquito life cycles and to evaluate vector control applications. However, most models lack sugar-feeding and resting behaviours or are based on mathematical equations lacking individual level randomness and spatial components of mosquito life. Here, a spatial individual-based model (IBM) incorporating sugar-feeding and resting behaviours of the malaria vector Anopheles gambiae was developed to estimate the impact of environmental sugar sources and resting sites on survival and biting behaviour.MethodsA spatial IBM containing An. gambiae mosquitoes and humans, as well as the village environment of houses, sugar sources, resting sites and larval habitat sites was developed. Anopheles gambiae behaviour rules were attributed at each step of the IBM: resting, host seeking, sugar feeding and breeding. Each step represented one second of time, and each simulation was set to run for 60 days and repeated 50 times. Scenarios of different densities and spatial distributions of sugar sources and outdoor resting sites were simulated and compared.ResultsWhen the number of natural sugar sources was increased from 0 to 100 while the number of resting sites was held constant, mean daily survival rate increased from 2.5% to 85.1% for males and from 2.5% to 94.5% for females, mean human biting rate increased from 0 to 0.94 bites per human per day, and mean daily abundance increased from 1 to 477 for males and from 1 to 1,428 for females. When the number of outdoor resting sites was increased from 0 to 50 while the number of sugar sources was held constant, mean daily survival rate increased from 77.3% to 84.3% for males and from 86.7% to 93.9% for females, mean human biting rate increased from 0 to 0.52 bites per human per day, and mean daily abundance increased from 62 to 349 for males and from 257 to 1120 for females. All increases were significant (P houses.ConclusionsIncreases in densities of sugar sources or

  8. Climate change and the economics of biomass energy feedstocks in semi-arid agricultural landscapes: A spatially explicit real options analysis.

    Science.gov (United States)

    Regan, Courtney M; Connor, Jeffery D; Raja Segaran, Ramesh; Meyer, Wayne S; Bryan, Brett A; Ostendorf, Bertram

    2017-05-01

    The economics of establishing perennial species as renewable energy feedstocks has been widely investigated as a climate change adapted diversification option for landholders, primarily using net present value (NPV) analysis. NPV does not account for key uncertainties likely to influence relevant landholder decision making. While real options analysis (ROA) is an alternative method that accounts for the uncertainty over future conditions and the large upfront irreversible investment involved in establishing perennials, there have been limited applications of ROA to evaluating land use change decision economics and even fewer applications considering climate change risks. Further, while the influence of spatially varying climate risk on biomass conversion economic has been widely evaluated using NPV methods, effects of spatial variability and climate on land use change have been scarcely assessed with ROA. In this study we applied a simulation-based ROA model to evaluate a landholder's decision to convert land from agriculture to biomass. This spatially explicit model considers price and yield risks under baseline climate and two climate change scenarios over a geographically diverse farming region. We found that underlying variability in primary productivity across the study area had a substantial effect on conversion thresholds required to trigger land use change when compared to results from NPV analysis. Areas traditionally thought of as being quite similar in average productive capacity can display large differences in response to the inclusion of production and price risks. The effects of climate change, broadly reduced returns required for land use change to biomass in low and medium rainfall zones and increased them in higher rainfall areas. Additionally, the risks posed by climate change can further exacerbate the tendency for NPV methods to underestimate true conversion thresholds. Our results show that even under severe drying and warming where crop yield

  9. Estimating impacts of plantation forestry on plant biodiversity in southern Chile-a spatially explicit modelling approach.

    Science.gov (United States)

    Braun, Andreas Christian; Koch, Barbara

    2016-10-01

    Monitoring the impacts of land-use practices is of particular importance with regard to biodiversity hotspots in developing countries. Here, conserving the high level of unique biodiversity is challenged by limited possibilities for data collection on site. Especially for such scenarios, assisting biodiversity assessments by remote sensing has proven useful. Remote sensing techniques can be applied to interpolate between biodiversity assessments taken in situ. Through this approach, estimates of biodiversity for entire landscapes can be produced, relating land-use intensity to biodiversity conditions. Such maps are a valuable basis for developing biodiversity conservation plans. Several approaches have been published so far to interpolate local biodiversity assessments in remote sensing data. In the following, a new approach is proposed. Instead of inferring biodiversity using environmental variables or the variability of spectral values, a hypothesis-based approach is applied. Empirical knowledge about biodiversity in relation to land-use is formalized and applied as ascription rules for image data. The method is exemplified for a large study site (over 67,000 km(2)) in central Chile, where forest industry heavily impacts plant diversity. The proposed approach yields a coefficient of correlation of 0.73 and produces a convincing estimate of regional biodiversity. The framework is broad enough to be applied to other study sites.

  10. Factors influencing export of dissolved inorganic nitrogen by major rivers: A new, seasonal, spatially explicit, global model

    Science.gov (United States)

    Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in depth. Much less is known, however, about seasonal patterns and controls of coastal DIN delivery across larg...

  11. Factors influencing export of dissolved inorganic nitrogen by major rivers: A new seasonal, spatially explicit, global model - 2012

    Science.gov (United States)

    Background/Question/Methods Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in some depth. Much less is known, however, about seasonal patterns and zone and ...

  12. The position of place in governing global problems: A mechanistic account of place-as-context, and analysis of transitions towards spatially explicit approaches to climate science and policy

    International Nuclear Information System (INIS)

    MacGillivray, Brian H.

    2015-01-01

    Highlights: • Place is a central yet undertheorised concept within sustainability science. • Introduces an account of place as the context in which social and environmental mechanisms operate. • Uses this account to critique historical aspatial approaches to climate science and policy. • Traces out shifts towards spatially explicit approaches to climate governance. • A focus on place, heterogeneity, and context maximizes the credibility and policy-relevance of climate science. - Abstract: Place is a central concept within the sustainability sciences, yet it remains somewhat undertheorised, and its relationship to generalisation and scale is unclear. Here, we develop a mechanistic account of place as the fundamental context in which social and environmental mechanisms operate. It is premised on the view that the social and environmental sciences are typically concerned with causal processes and their interaction with context, rather than with a search for laws. We deploy our mechanistic account to critique the neglect of place that characterised the early stages of climate governance, ranging from the highly idealised general circulation and integrated assessment models used to analyze climate change, to the global institutions and technologies designed to manage it. We implicate this neglect of place in the limited progress in tackling climate change in both public and policy spheres, before tracing out recent shifts towards more spatially explicit approaches to climate change science and policy-making. These shifts reflect a move towards an ontology which acknowledges that even where causal drivers are in a sense global in nature (e.g. atmospheric levels of greenhouse gases), their impacts are often mediated through variables that are spatially clustered at multiple scales, moderated by contextual features of the local environment, and interact with the presence of other (localised) stressors in synergistic rather than additive ways. We conclude that a

  13. Reconstructing satellite images to quantify spatially explicit land surface change caused by fires and succession: A demonstration in the Yukon River Basin of interior Alaska

    Science.gov (United States)

    Huang, Shengli; Jin, Suming; Dahal, Devendra; Chen, Xuexia; Young, Claudia; Liu, Heping; Liu, Shuguang

    2013-01-01

    Land surface change caused by fires and succession is confounded by many site-specific factors and requires further study. The objective of this study was to reveal the spatially explicit land surface change by minimizing the confounding factors of weather variability, seasonal offset, topography, land cover, and drainage. In a pilot study of the Yukon River Basin of interior Alaska, we retrieved Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) from a postfire Landsat image acquired on August 5th, 2004. With a Landsat reference image acquired on June 26th, 1986, we reconstructed NDVI, albedo, and LST of 1987–2004 fire scars for August 5th, 2004, assuming that these fires had not occurred. The difference between actual postfire and assuming-no-fire scenarios depicted the fires and succession impact. Our results demonstrated the following: (1) NDVI showed an immediate decrease after burning but gradually recovered to prefire levels in the following years, in which burn severity might play an important role during this process; (2) Albedo showed an immediate decrease after burning but then recovered and became higher than prefire levels; and (3) Most fires caused surface warming, but cooler surfaces did exist; time-since-fire affected the prefire and postfire LST difference but no absolute trend could be found. Our approach provided spatially explicit land surface change rather than average condition, enabling a better understanding of fires and succession impact on ecological consequences at the pixel level.

  14. Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China

    Directory of Open Access Journals (Sweden)

    Jian Gong

    2015-11-01

    Full Text Available Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution—severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems.

  15. Developing spatially explicit footprints of plausible land-use scenarios in the Santa Cruz Watershed, Arizona and Sonora

    Science.gov (United States)

    Norman, Laura M.; Feller, Mark; Villarreal, Miguel L.

    2012-01-01

    The SLEUTH urban growth model is applied to a binational dryland watershed to envision and evaluate plausible future scenarios of land use change into the year 2050. Our objective was to create a suite of geospatial footprints portraying potential land use change that can be used to aid binational decision-makers in assessing the impacts relative to sustainability of natural resources and potential socio-ecological consequences of proposed land-use management. Three alternatives are designed to simulate different conditions: (i) a Current Trends Scenario of unmanaged exponential growth, (ii) a Conservation Scenario with managed growth to protect the environment, and (iii) a Megalopolis Scenario in which growth is accentuated around a defined international trade corridor. The model was calibrated with historical data extracted from a time series of satellite images. Model materials, methodology, and results are presented. Our Current Trends Scenario predicts the footprint of urban growth to approximately triple from 2009 to 2050, which is corroborated by local population estimates. The Conservation Scenario results in protecting 46% more of the Evergreen class (more than 150,000 acres) than the Current Trends Scenario and approximately 95,000 acres of Barren Land, Crops, Deciduous Forest (Mesquite Bosque), Grassland/Herbaceous, Urban/Recreational Grasses, and Wetlands classes combined. The Megalopolis Scenario results also depict the preservation of some of these land-use classes compared to the Current Trends Scenario, most notably in the environmentally important headwaters region. Connectivity and areal extent of land cover types that provide wildlife habitat were preserved under the alternative scenarios when compared to Current Trends.

  16. A joint individual-based model coupling growth and mortality reveals that tree vigor is a key component of tropical forest dynamics.

    Science.gov (United States)

    Aubry-Kientz, Mélaine; Rossi, Vivien; Boreux, Jean-Jacques; Hérault, Bruno

    2015-06-01

    Tree vigor is often used as a covariate when tree mortality is predicted from tree growth in tropical forest dynamic models, but it is rarely explicitly accounted for in a coherent modeling framework. We quantify tree vigor at the individual tree level, based on the difference between expected and observed growth. The available methods to join nonlinear tree growth and mortality processes are not commonly used by forest ecologists so that we develop an inference methodology based on an MCMC approach, allowing us to sample the parameters of the growth and mortality model according to their posterior distribution using the joint model likelihood. We apply our framework to a set of data on the 20-year dynamics of a forest in Paracou, French Guiana, taking advantage of functional trait-based growth and mortality models already developed independently. Our results showed that growth and mortality are intimately linked and that the vigor estimator is an essential predictor of mortality, highlighting that trees growing more than expected have a far lower probability of dying. Our joint model methodology is sufficiently generic to be used to join two longitudinal and punctual linked processes and thus may be applied to a wide range of growth and mortality models. In the context of global changes, such joint models are urgently needed in tropical forests to analyze, and then predict, the effects of the ongoing changes on the tree dynamics in hyperdiverse tropical forests.

  17. Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

    Science.gov (United States)

    Zhan, Yu; Luo, Yuzhou; Deng, Xunfei; Chen, Huajin; Grieneisen, Michael L.; Shen, Xueyou; Zhu, Lizhong; Zhang, Minghua

    2017-04-01

    A high degree of uncertainty associated with the emission inventory for China tends to degrade the performance of chemical transport models in predicting PM2.5 concentrations especially on a daily basis. In this study a novel machine learning algorithm, Geographically-Weighted Gradient Boosting Machine (GW-GBM), was developed by improving GBM through building spatial smoothing kernels to weigh the loss function. This modification addressed the spatial nonstationarity of the relationships between PM2.5 concentrations and predictor variables such as aerosol optical depth (AOD) and meteorological conditions. GW-GBM also overcame the estimation bias of PM2.5 concentrations due to missing AOD retrievals, and thus potentially improved subsequent exposure analyses. GW-GBM showed good performance in predicting daily PM2.5 concentrations (R2 = 0.76, RMSE = 23.0 μg/m3) even with partially missing AOD data, which was better than the original GBM model (R2 = 0.71, RMSE = 25.3 μg/m3). On the basis of the continuous spatiotemporal prediction of PM2.5 concentrations, it was predicted that 95% of the population lived in areas where the estimated annual mean PM2.5 concentration was higher than 35 μg/m3, and 45% of the population was exposed to PM2.5 >75 μg/m3 for over 100 days in 2014. GW-GBM accurately predicted continuous daily PM2.5 concentrations in China for assessing acute human health effects.

  18. Individual-based ecology of coastal birds.

    Science.gov (United States)

    Stillman, Richard A; Goss-Custard, John D

    2010-08-01

    Conservation objectives for non-breeding coastal birds (shorebirds and wildfowl) are determined from their population size at coastal sites. To advise coastal managers, models must predict quantitatively the effects of environmental change on population size or the demographic rates (mortality and reproduction) that determine it. As habitat association models and depletion models are not able to do this, we developed an approach that has produced such predictions thereby enabling policy makers to make evidence-based decisions. Our conceptual framework is individual-based ecology, in which populations are viewed as having properties (e.g. size) that arise from the traits (e.g. behaviour, physiology) and interactions of their constituent individuals. The link between individuals and populations is made through individual-based models (IBMs) that follow the fitness-maximising decisions of individuals and predict population-level consequences (e.g. mortality rate) from the fates of these individuals. Our first IBM was for oystercatchers Haematopus ostralegus and accurately predicted their density-dependent mortality. Subsequently, IBMs were developed for several shorebird and wildfowl species at several European sites, and were shown to predict accurately overwinter mortality, and the foraging behaviour from which predictions are derived. They have been used to predict the effect on survival in coastal birds of sea level rise, habitat loss, wind farm development, shellfishing and human disturbance. This review emphasises the wider applicability of the approach, and identifies other systems to which it could be applied. We view the IBM approach as a very useful contribution to the general problem of how to advance ecology to the point where we can routinely make meaningful predictions of how populations respond to environmental change.

  19. Estimating Brownian motion dispersal rate, longevity and population density from spatially explicit mark-recapture data on tropical butterflies.

    Science.gov (United States)

    Tufto, Jarle; Lande, Russell; Ringsby, Thor-Harald; Engen, Steinar; Saether, Bernt-Erik; Walla, Thomas R; DeVries, Philip J

    2012-07-01

    1. We develop a Bayesian method for analysing mark-recapture data in continuous habitat using a model in which individuals movement paths are Brownian motions, life spans are exponentially distributed and capture events occur at given instants in time if individuals are within a certain attractive distance of the traps. 2. The joint posterior distribution of the dispersal rate, longevity, trap attraction distances and a number of latent variables representing the unobserved movement paths and time of death of all individuals is computed using Gibbs sampling. 3. An estimate of absolute local population density is obtained simply by dividing the Poisson counts of individuals captured at given points in time by the estimated total attraction area of all traps. Our approach for estimating population density in continuous habitat avoids the need to define an arbitrary effective trapping area that characterized previous mark-recapture methods in continuous habitat. 4. We applied our method to estimate spatial demography parameters in nine species of neotropical butterflies. Path analysis of interspecific variation in demographic parameters and mean wing length revealed a simple network of strong causation. Larger wing length increases dispersal rate, which in turn increases trap attraction distance. However, higher dispersal rate also decreases longevity, thus explaining the surprising observation of a negative correlation between wing length and longevity. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

  20. Streamflow effects on spawning, rearing, and outmigration of fall-run chinook salmon (Oncorhynchus tshawytscha) predicted by a spatial and individual-based model

    International Nuclear Information System (INIS)

    Jager, H.I.; Sale, M.J.; Cardwell, H.E.; Deangelis, D.L.; Bevelhimer, M.J.; Coutant, C.C.

    1994-01-01

    The thread posed to Pacific salmon by competing water demands is a great concern to regulators of the hydropower industry. Finding the balance between fish resource and economic objectives depends on our ability to quantify flow effects on salmon production. Because field experiments are impractical, simulation models are needed to predict the effects of minimum flows on chinook salmon during their freshwater residence. We have developed a model to simulate the survival and development of eggs and alevins in redds and the growth, survival, and movement of juvenile chinook in response to local stream conditions (flow, temperature, chinook and predator density). Model results suggest that smolt production during dry years can be increased by raising spring minimum flows

  1. Growth and survival of larval and early juvenile lesser sandeel in patchy prey field in the North Sea: An examination using individual-based modelling

    DEFF Research Database (Denmark)

    Gürkan, Zeren; Christensen, Asbjørn; Deurs, Mikael van

    2012-01-01

    -stages in the North Sea. Simulations of patchiness related starvation mortality are able to explain observed patterns of variation in sandeel growth. Reduced prey densities within patches decrease growth and survival rate of larvae and match–mismatch affect growth and survival of larvae with different hatch time due...... by modeling copepod size spectra dynamics and patchiness based on particle count transects and Continuous Plankton Recorder time series data. The study analyzes the effects of larval hatching time, presence of zooplankton patchiness and within patch abundance on growth and survival of sandeel early life...

  2. Evolving Ecological Social Dilemmas: A Spatial Individual-Based Model for the Evolution of Cooperation with a Minimal Number of Parameters

    International Nuclear Information System (INIS)

    Fort, H.

    2007-01-01

    Cooperation, both intraspecific and interspecific, is a well-documented phenomenon in nature that is not well understood. Evolutionary game theory is a powerful tool to approach this problem. However, it has important limitations. First, very often it is not obvious which game is more appropriate to use. Second, in general, identical payoff matrices are assumed for all players, a situation that is highly unlikely in nature. Third, slight changes in these payoff values can dramatically alter the outcomes. Here, I use an evolutionary spatial model in which players do not have a universal payoff matrix, so no payoff parameters are required. Instead, each is equipped with random values for the payoffs, fulfilling the constraints that define the game(s). These payoff matrices evolve by natural selection. Two versions of this model are studied. First is a simpler one, with just one evolving payoff. Second is the full version, with all the four payoffs evolving. The fraction of cooperator agents converges in both versions to nonzero values. In the case of the full version, the initial heterogeneity disappears and the selected game is the stag Hunt

  3. Investigating the Effect of Recruitment Variability on Length-Based Recruitment Indices for Antarctic Krill Using an Individual-Based Population Dynamics Model

    Science.gov (United States)

    Thanassekos, Stéphane; Cox, Martin J.; Reid, Keith

    2014-01-01

    Antarctic krill (Euphausia superba; herein krill) is monitored as part of an on-going fisheries observer program that collects length-frequency data. A krill feedback management programme is currently being developed, and as part of this development, the utility of data-derived indices describing population level processes is being assessed. To date, however, little work has been carried out on the selection of optimum recruitment indices and it has not been possible to assess the performance of length-based recruitment indices across a range of recruitment variability. Neither has there been an assessment of uncertainty in the relationship between an index and the actual level of recruitment. Thus, until now, it has not been possible to take into account recruitment index uncertainty in krill stock management or when investigating relationships between recruitment and environmental drivers. Using length-frequency samples from a simulated population – where recruitment is known – the performance of six potential length-based recruitment indices is assessed, by exploring the index-to-recruitment relationship under increasing levels of recruitment variability (from ±10% to ±100% around a mean annual recruitment). The annual minimum of the proportion of individuals smaller than 40 mm (F40 min, %) was selected because it had the most robust index-to-recruitment relationship across differing levels of recruitment variability. The relationship was curvilinear and best described by a power law. Model uncertainty was described using the 95% prediction intervals, which were used to calculate coverage probabilities and assess model performance. Despite being the optimum recruitment index, the performance of F40 min degraded under high (>50%) recruitment variability. Due to the persistence of cohorts in the population over several years, the inclusion of F40 min values from preceding years in the relationship used to estimate recruitment in a given year improved its

  4. Fragmentation of nest and foraging habitat affects time budgets of solitary bees, their fitness and pollination services, depending on traits: Results from an individual-based model

    Science.gov (United States)

    Settele, Josef; Dormann, Carsten F.

    2018-01-01

    Solitary bees are important but declining wild pollinators. During daily foraging in agricultural landscapes, they encounter a mosaic of patches with nest and foraging habitat and unsuitable matrix. It is insufficiently clear how spatial allocation of nesting and foraging resources and foraging traits of bees affect their daily foraging performance. We investigated potential brood cell construction (as proxy of fitness), number of visited flowers, foraging habitat visitation and foraging distance (pollination proxies) with the model SOLBEE (simulating pollen transport by solitary bees, tested and validated in an earlier study), for landscapes varying in landscape fragmentation and spatial allocation of nesting and foraging resources. Simulated bees varied in body size and nesting preference. We aimed to understand effects of landscape fragmentation and bee traits on bee fitness and the pollination services bees provide, as well as interactions between them, and the general consequences it has to our understanding of the system. This broad scope gives multiple key results. 1) Body size determines fitness more than landscape fragmentation, with large bees building fewer brood cells. High pollen requirements for large bees and the related high time budgets for visiting many flowers may not compensate for faster flight speeds and short handling times on flowers, giving them overall a disadvantage compared to small bees. 2) Nest preference does affect distribution of bees over the landscape, with cavity-nesting bees being restricted to nesting along field edges, which inevitably leads to performance reductions. Fragmentation mitigates this for cavity-nesting bees through increased edge habitat. 3) Landscape fragmentation alone had a relatively small effect on all responses. Instead, the local ratio of nest to foraging habitat affected bee fitness positively through reduced local competition. The spatial coverage of pollination increases steeply in response to this ratio

  5. Fragmentation of nest and foraging habitat affects time budgets of solitary bees, their fitness and pollination services, depending on traits: Results from an individual-based model.

    Science.gov (United States)

    Everaars, Jeroen; Settele, Josef; Dormann, Carsten F

    2018-01-01

    Solitary bees are important but declining wild pollinators. During daily foraging in agricultural landscapes, they encounter a mosaic of patches with nest and foraging habitat and unsuitable matrix. It is insufficiently clear how spatial allocation of nesting and foraging resources and foraging traits of bees affect their daily foraging performance. We investigated potential brood cell construction (as proxy of fitness), number of visited flowers, foraging habitat visitation and foraging distance (pollination proxies) with the model SOLBEE (simulating pollen transport by solitary bees, tested and validated in an earlier study), for landscapes varying in landscape fragmentation and spatial allocation of nesting and foraging resources. Simulated bees varied in body size and nesting preference. We aimed to understand effects of landscape fragmentation and bee traits on bee fitness and the pollination services bees provide, as well as interactions between them, and the general consequences it has to our understanding of the system. This broad scope gives multiple key results. 1) Body size determines fitness more than landscape fragmentation, with large bees building fewer brood cells. High pollen requirements for large bees and the related high time budgets for visiting many flowers may not compensate for faster flight speeds and short handling times on flowers, giving them overall a disadvantage compared to small bees. 2) Nest preference does affect distribution of bees over the landscape, with cavity-nesting bees being restricted to nesting along field edges, which inevitably leads to performance reductions. Fragmentation mitigates this for cavity-nesting bees through increased edge habitat. 3) Landscape fragmentation alone had a relatively small effect on all responses. Instead, the local ratio of nest to foraging habitat affected bee fitness positively through reduced local competition. The spatial coverage of pollination increases steeply in response to this ratio

  6. Fragmentation of nest and foraging habitat affects time budgets of solitary bees, their fitness and pollination services, depending on traits: Results from an individual-based model.

    Directory of Open Access Journals (Sweden)

    Jeroen Everaars

    Full Text Available Solitary bees are important but declining wild pollinators. During daily foraging in agricultural landscapes, they encounter a mosaic of patches with nest and foraging habitat and unsuitable matrix. It is insufficiently clear how spatial allocation of nesting and foraging resources and foraging traits of bees affect their daily foraging performance. We investigated potential brood cell construction (as proxy of fitness, number of visited flowers, foraging habitat visitation and foraging distance (pollination proxies with the model SOLBEE (simulating pollen transport by solitary bees, tested and validated in an earlier study, for landscapes varying in landscape fragmentation and spatial allocation of nesting and foraging resources. Simulated bees varied in body size and nesting preference. We aimed to understand effects of landscape fragmentation and bee traits on bee fitness and the pollination services bees provide, as well as interactions between them, and the general consequences it has to our understanding of the system. This broad scope gives multiple key results. 1 Body size determines fitness more than landscape fragmentation, with large bees building fewer brood cells. High pollen requirements for large bees and the related high time budgets for visiting many flowers may not compensate for faster flight speeds and short handling times on flowers, giving them overall a disadvantage compared to small bees. 2 Nest preference does affect distribution of bees over the landscape, with cavity-nesting bees being restricted to nesting along field edges, which inevitably leads to performance reductions. Fragmentation mitigates this for cavity-nesting bees through increased edge habitat. 3 Landscape fragmentation alone had a relatively small effect on all responses. Instead, the local ratio of nest to foraging habitat affected bee fitness positively through reduced local competition. The spatial coverage of pollination increases steeply in response

  7. Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom

    Science.gov (United States)

    Topp, Cairistiona F. E.; Moorby, Jon M.; Pásztor, László; Foyer, Christine H.

    2018-01-01

    Dairy farming is one the most important sectors of United Kingdom (UK) agriculture. It faces major challenges due to climate change, which will have direct impacts on dairy cows as a result of heat stress. In the absence of adaptations, this could potentially lead to considerable milk loss. Using an 11-member climate projection ensemble, as well as an ensemble of 18 milk loss estimation methods, temporal changes in milk production of UK dairy cows were estimated for the 21st century at a 25 km resolution in a spatially-explicit way. While increases in UK temperatures are projected to lead to relatively low average annual milk losses, even for southern UK regions (cow), the ‘hottest’ 25×25 km grid cell in the hottest year in the 2090s, showed an annual milk loss exceeding 1300 kg/cow. This figure represents approximately 17% of the potential milk production of today’s average cow. Despite the potential considerable inter-annual variability of annual milk loss, as well as the large differences between the climate projections, the variety of calculation methods is likely to introduce even greater uncertainty into milk loss estimations. To address this issue, a novel, more biologically-appropriate mechanism of estimating milk loss is proposed that provides more realistic future projections. We conclude that South West England is the region most vulnerable to climate change economically, because it is characterised by a high dairy herd density and therefore potentially high heat stress-related milk loss. In the absence of mitigation measures, estimated heat stress-related annual income loss for this region by the end of this century may reach £13.4M in average years and £33.8M in extreme years. PMID:29738581

  8. Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom.

    Directory of Open Access Journals (Sweden)

    Nándor Fodor

    Full Text Available Dairy farming is one the most important sectors of United Kingdom (UK agriculture. It faces major challenges due to climate change, which will have direct impacts on dairy cows as a result of heat stress. In the absence of adaptations, this could potentially lead to considerable milk loss. Using an 11-member climate projection ensemble, as well as an ensemble of 18 milk loss estimation methods, temporal changes in milk production of UK dairy cows were estimated for the 21st century at a 25 km resolution in a spatially-explicit way. While increases in UK temperatures are projected to lead to relatively low average annual milk losses, even for southern UK regions (<180 kg/cow, the 'hottest' 25×25 km grid cell in the hottest year in the 2090s, showed an annual milk loss exceeding 1300 kg/cow. This figure represents approximately 17% of the potential milk production of today's average cow. Despite the potential considerable inter-annual variability of annual milk loss, as well as the large differences between the climate projections, the variety of calculation methods is likely to introduce even greater uncertainty into milk loss estimations. To address this issue, a novel, more biologically-appropriate mechanism of estimating milk loss is proposed that provides more realistic future projections. We conclude that South West England is the region most vulnerable to climate change economically, because it is characterised by a high dairy herd density and therefore potentially high heat stress-related milk loss. In the absence of mitigation measures, estimated heat stress-related annual income loss for this region by the end of this century may reach £13.4M in average years and £33.8M in extreme years.

  9. Temporal and Spatial Explicit Modelling of Renewable Energy Systems : Modelling variable renewable energy systems to address climate change mitigation and universal electricity access

    NARCIS (Netherlands)

    Zeyringer, Marianne

    2017-01-01

    Two major global challenges climate change mitigation and universal electricity access, can be addressed by large scale deployment of renewable energy sources (Alstone et al., 2015). Around 60% of greenhouse gas emissions originate from energy generation and 90% of CO2 emissions are caused by fossil

  10. The Small Breathing Amplitude at the Upper Lobes Favors the Attraction of Polymorphonuclear Neutrophils to Mycobacterium tuberculosis Lesions and Helps to Understand the Evolution toward Active Disease in An Individual-Based Model.

    Science.gov (United States)

    Cardona, Pere-Joan; Prats, Clara

    2016-01-01

    Infection with Mycobacterium tuberculosis (Mtb) can induce two kinds of lesions, namely proliferative and exudative. The former are based on the presence of macrophages with controlled induction of intragranulomatous necrosis, and are even able to stop its physical progression, thus avoiding the induction of active tuberculosis (TB). In contrast, the most significant characteristic of exudative lesions is their massive infiltration with polymorphonuclear neutrophils (PMNs), which favor enlargement of the lesions and extracellular growth of the bacilli. We have built an individual-based model (IBM) (known as "TBPATCH") using the NetLogo interface to better understand the progression from Mtb infection to TB. We have tested four main factors previously identified as being able to favor the infiltration of Mtb-infected lesions with PMNs, namely the tolerability of infected macrophages to the bacillary load; the capacity to modulate the Th17 response; the breathing amplitude (BAM) (large or small in the lower and upper lobes respectively), which influences bacillary drainage at the alveoli; and the encapsulation of Mtb-infected lesions by the interlobular septae that structure the pulmonary parenchyma into secondary lobes. Overall, although all the factors analyzed play some role, the small BAM is the major factor determining whether Mtb-infected lesions become exudative, and thus induce TB, thereby helping to understand why this usually takes place in the upper lobes. This information will be very useful for the design of future prophylactic and therapeutic approaches against TB.

  11. Projecting deforestation trends on Espiritu Santo island, Vanuatu, using a spatial modeling approach : a case study to develop a spatially explicit forest reference emission level for REDD+

    OpenAIRE

    Méndez Zeballos, Dorys

    2015-01-01

    As agreed under United Nations Framework Convention on Climate Change, activities reducing emissions from deforestation, forest degradation, sustainable management of forests, enhancement and conservation of forest carbon stocks (REDD+) provide financial incentives to countries mitigating climate change. Countries are requested to develop so-called national forest reference levels (FRLs) as a benchmark to measure performance of land-use policy adjustments. FRLs are constructed combining infor...

  12. Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.

    Science.gov (United States)

    Ferrer, Jordi; Prats, Clara; López, Daniel; Vives-Rego, Josep

    2009-08-31

    Predictive microbiology is the area of food microbiology that attempts to forecast the quantitative evolution of microbial populations over time. This is achieved to a great extent through models that include the mechanisms governing population dynamics. Traditionally, the models used in predictive microbiology are whole-system continuous models that describe population dynamics by means of equations applied to extensive or averaged variables of the whole system. Many existing models can be classified by specific criteria. We can distinguish between survival and growth models by seeing whether they tackle mortality or cell duplication. We can distinguish between empirical (phenomenological) models, which mathematically describe specific behaviour, and theoretical (mechanistic) models with a biological basis, which search for the underlying mechanisms driving already observed phenomena. We can also distinguish between primary, secondary and tertiary models, by examining their treatment of the effects of external factors and constraints on the microbial community. Recently, the use of spatially explicit Individual-based Models (IbMs) has spread through predictive microbiology, due to the current technological capacity of performing measurements on single individual cells and thanks to the consolidation of computational modelling. Spatially explicit IbMs are bottom-up approaches to microbial communities that build bridges between the description of micro-organisms at the cell level and macroscopic observations at the population level. They provide greater insight into the mesoscale phenomena that link unicellular and population levels. Every model is built in response to a particular question and with different aims. Even so, in this research we conducted a SWOT (Strength, Weaknesses, Opportunities and Threats) analysis of the different approaches (population continuous modelling and Individual-based Modelling), which we hope will be helpful for current and future

  13. Development and assessment of 30-meter pine density maps for landscape-level modeling of mountain pine beetle dynamics

    Science.gov (United States)

    Benjamin A. Crabb; James A. Powell; Barbara J. Bentz

    2012-01-01

    Forecasting spatial patterns of mountain pine beetle (MPB) population success requires spatially explicit information on host pine distribution. We developed a means of producing spatially explicit datasets of pine density at 30-m resolution using existing geospatial datasets of vegetation composition and structure. Because our ultimate goal is to model MPB population...

  14. Individual based population inference using tagging data

    DEFF Research Database (Denmark)

    Pedersen, Martin Wæver; Thygesen, Uffe Høgsbro; Baktoft, Henrik

    A hierarchical framework for simultaneous analysis of multiple related individual datasets is presented. The approach is very similar to mixed effects modelling as known from statistical theory. The model used at the individual level is, in principle, irrelevant as long as a maximum likelihood...... estimate and its uncertainty (Hessian) can be computed. The individual model used in this text is a hidden Markov model. A simulation study concerning a two-dimensional biased random walk is examined to verify the consistency of the hierarchical estimation framework. In addition, a study based on acoustic...... telemetry data from pike illustrates how the framework can identify individuals that deviate from the remaining population....

  15. Can landscape-level ecological restoration influence fire risk? A spatially-explicit assessment of a northern temperate-southern boreal forest landscape

    Science.gov (United States)

    Douglas J. Shinneman; Brian J. Palik; Meredith W. Cornett

    2012-01-01

    Management strategies to restore forest landscapes are often designed to concurrently reduce fire risk. However, the compatibility of these two objectives is not always clear, and uncoordinated management among landowners may have unintended consequences. We used a forest landscape simulation model to compare the effects of contemporary management and hypothetical...

  16. Designing Optimal LNG Station Network for U.S. Heavy-Duty Freight Trucks using Temporally and Spatially Explicit Supply Chain Optimization

    Science.gov (United States)

    Lee, Allen

    The recent natural gas boom has opened much discussion about the potential of natural gas and specifically Liquefied Natural Gas (LNG) in the United States transportation sector. The switch from diesel to natural gas vehicles would reduce foreign dependence on oil, spur domestic economic growth, and potentially reduce greenhouse gas emissions. LNG provides the most potential for the medium to heavy-duty vehicle market partially due to unstable oil prices and stagnant natural gas prices. As long as the abundance of unconventional gas in the United States remains cheap, fuel switching to natural gas could provide significant cost savings for long haul freight industry. Amid a growing LNG station network and ever increasing demand for freight movement, LNG heavy-duty truck sales are less than anticipated and the industry as a whole is less economic than expected. In spite of much existing and mature natural gas infrastructure, the supply chain for LNG is different and requires explicit and careful planning. This thesis proposes research to explore the claim that the largest obstacle to widespread LNG market penetration is sub-optimal infrastructure planning. No other study we are aware of has explicitly explored the LNG transportation fuel supply chain for heavy-duty freight trucks. This thesis presents a novel methodology that links a network infrastructure optimization model (represents supply side) with a vehicle stock and economic payback model (represents demand side). The model characterizes both a temporal and spatial optimization model of future LNG transportation fuel supply chains in the United States. The principal research goal is to assess the economic feasibility of the current LNG transportation fuel industry and to determine an optimal pathway to achieve ubiquitous commercialization of LNG vehicles in the heavy-duty transport sector. The results indicate that LNG is not economic as a heavy-duty truck fuel until 2030 under current market conditions

  17. Spatially-Explicit Assessments of Genetic Biodiversity and Dispersal in Gopher Tortoises for Evaluation of Habitat Fragmentation at DoD Sites

    Science.gov (United States)

    2008-10-01

    crocodilian population genetics questions. J. Herpetology . 35: 541-544. Diemer JE. 1992. Home range and movements of the tortoise Gopherus...polyphemus in northern Florida. Journal of Herpetology 26:158–162 Diffendorfer JE. 1998. Testing models of source-sink dynamics and balanced dispersal...associated with tortoise (Gopherus polyphemus) burrows in four habitats in south-central Florida. Journal of Herpetology 25:477-481. Luikart G, Cornuet J-M

  18. Interplay between spatially explicit sediment sourcing, hierarchical river-network structure, and in-channel bed material sediment transport and storage dynamics

    Science.gov (United States)

    Czuba, Jonathan A.; Foufoula-Georgiou, Efi; Gran, Karen B.; Belmont, Patrick; Wilcock, Peter R.

    2017-05-01

    Understanding how sediment moves along source to sink pathways through watersheds—from hillslopes to channels and in and out of floodplains—is a fundamental problem in geomorphology. We contribute to advancing this understanding by modeling the transport and in-channel storage dynamics of bed material sediment on a river network over a 600 year time period. Specifically, we present spatiotemporal changes in bed sediment thickness along an entire river network to elucidate how river networks organize and process sediment supply. We apply our model to sand transport in the agricultural Greater Blue Earth River Basin in Minnesota. By casting the arrival of sediment to links of the network as a Poisson process, we derive analytically (under supply-limited conditions) the time-averaged probability distribution function of bed sediment thickness for each link of the river network for any spatial distribution of inputs. Under transport-limited conditions, the analytical assumptions of the Poisson arrival process are violated (due to in-channel storage dynamics) where we find large fluctuations and periodicity in the time series of bed sediment thickness. The time series of bed sediment thickness is the result of dynamics on a network in propagating, altering, and amalgamating sediment inputs in sometimes unexpected ways. One key insight gleaned from the model is that there can be a small fraction of reaches with relatively low-transport capacity within a nonequilibrium river network acting as "bottlenecks" that control sediment to downstream reaches, whereby fluctuations in bed elevation can dissociate from signals in sediment supply.

  19. Crop water productivity under increasing irrigation capacities in Romania. A spatially-explicit assessment of winter wheat and maize cropping systems in the southern lowlands of the country

    Science.gov (United States)

    Dogaru, Diana

    2016-04-01

    Improved water use efficiency in agriculture is a key issue in terms of sustainable management and consumption of water resources in the context of peoples' increasing food demands and preferences, economic growth and agricultural adaptation options to climate variability and change. Crop Water Productivity (CWP), defined as the ratio of yield (or value of harvested crop) to actual evapotranspiration or as the ratio of yield (or value of harvested crop) to volume of supplied irrigation water (Molden et al., 1998), is a useful indicator in the evaluation of water use efficiency and ultimately of cropland management, particularly in the case of regions affected by or prone to drought and where irrigation application is essential for achieving expected productions. The present study investigates the productivity of water in winter wheat and maize cropping systems in the Romanian Plain (49 594 sq. km), an important agricultural region in the southern part of the country which is increasingly affected by drought and dry spells (Sandu and Mateescu, 2014). The scope of the analysis is to assess the gains and losses in CWP for the two crops, by considering increased irrigated cropland and improved fertilization, these being the most common measures potentially and already implemented by the farmers. In order to capture the effects of such measures on agricultural water use, the GIS-based EPIC crop-growth model (GEPIC) (Williams et al., 1989; Liu, 2009) was employed to simulate yields, seasonal evapotranspiration from crops and volume of irrigation water in the Romanian Plain for the 2002 - 2013 interval with focus on 2007 and 2010, two representative years for dry and wet periods, respectively. The GEPIC model operates on a daily time step, while the geospatial input datasets for this analysis (e.g. climate data, soil classes and soil parameters, land use) were harmonized at 1km resolution grid cell. The sources of the spatial data are mainly the national profile agencies

  20. Assessing Wildfire Risk in Cultural Heritage Properties Using High Spatial and Temporal Resolution Satellite Imagery and Spatially Explicit Fire Simulations: The Case of Holy Mount Athos, Greece

    Directory of Open Access Journals (Sweden)

    Giorgos Mallinis

    2016-02-01

    Full Text Available Fire management implications and the design of conservation strategies on fire prone landscapes within the UNESCO World Heritage Properties require the application of wildfire risk assessment at landscape level. The objective of this study was to analyze the spatial variation of wildfire risk on Holy Mount Athos in Greece. Mt. Athos includes 20 monasteries and other structures that are threatened by increasing frequency of wildfires. Site-specific fuel models were created by measuring in the field several fuel parameters in representative natural fuel complexes, while the spatial extent of the fuel types was determined using a synergy of high-resolution imagery and high temporal information from medium spatial resolution imagery classified through object-based analysis and a machine learning classifier. The Minimum Travel Time (MTT algorithm, as it is embedded in FlamMap software, was applied in order to evaluate Burn Probability (BP, Conditional Flame Length (CFL, Fire Size (FS, and Source-Sink Ratio (SSR. The results revealed low burn probabilities for the monasteries; however, nine out of the 20 monasteries have high fire potential in terms of fire intensity, which means that if an ignition occurs, an intense fire is expected. The outputs of this study may be used for decision-making for short-term predictions of wildfire risk at an operational level, contributing to fire suppression and management of UNESCO World Heritage Properties.

  1. A spatially explicit assessment of current and future hotspots of hunger in Sub-Saharan Africa in the context of global change

    Science.gov (United States)

    Liu, Junguo; Fritz, Steffen; van Wesenbeeck, C. F. A.; Fuchs, Michael; You, Liangzhi; Obersteiner, Michael; Yang, Hong

    2008-12-01

    Hunger knows no boundaries or borders. While much research has focused on undernutrition on a national scale, this report evaluates it at subnational levels for Sub-Saharan Africa (SSA) to pinpoint hotspots where the greatest challenges exist. Undernutrition is assessed with a spatial resolution of 30 arc-minutes by investigating anthropometric data on weight and length of individuals. The impact of climate change on production of six major crops (cassava, maize, wheat, sorghum, rice and millet) is analyzed with a GIS-based Environmental Policy Integrated Climate (GEPIC) model with the same spatial resolution. Future hotspots of hunger are projected in the context of the anticipated climate, social, economic, and bio-physical changes. The results show that some regions in northern and southwestern Nigeria, Sudan and Angola with a currently high number of people with undernutrition might be able to improve their food security situation mainly through increasing purchasing power. In the near future, regions located in Ethiopia, Uganda, Rwanda and Burundi, southwestern Niger, and Madagascar are likely to remain hotspots of food insecurity, while regions located in Tanzania, Mozambique and the Democratic Republic of Congo might face more serious undernutrition. It is likely that both the groups of regions will suffer from lower capacity of importing food as well as lower per capita calorie availability, while the latter group will probably have sharper reduction in per capita calorie availability. Special attention must be paid to the hotspot areas in order to meet the hunger alleviation goals in SSA.

  2. Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

    Science.gov (United States)

    Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.

    2017-12-01

    Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

  3. GLOFRIM v1.0-A globally applicable computational framework for integrated hydrological-hydrodynamic modelling

    NARCIS (Netherlands)

    Hoch, Jannis M.; Neal, Jeffrey C.; Baart, Fedor; Van Beek, Rens; Winsemius, Hessel C.; Bates, Paul D.; Bierkens, Marc F.P.

    2017-01-01

    We here present GLOFRIM, a globally applicable computational framework for integrated hydrological-hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global

  4. GLOFRIM v1.0 – A globally applicable computational framework for integrated hydrological–hydrodynamic modelling

    NARCIS (Netherlands)

    Hoch, J.M.; Neal, Jeffrey; Baart, Fedor; van Beek, L.P.H.; Winsemius, Hessel; Bates, Paul; Bierkens, M.F.P.

    2017-01-01

    We here present GLOFRIM, a globally applicable computational framework for integrated hydrological–hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global

  5. Landscape fragmentation and pollinator movement within agricultural environments: a modelling framework for exploring foraging and movement ecology

    Directory of Open Access Journals (Sweden)

    Sean A. Rands

    2014-02-01

    Full Text Available Pollinator decline has been linked to landscape change, through both habitat fragmentation and the loss of habitat suitable for the pollinators to live within. One method for exploring why landscape change should affect pollinator populations is to combine individual-level behavioural ecological techniques with larger-scale landscape ecology. A modelling framework is described that uses spatially-explicit individual-based models to explore the effects of individual behavioural rules within a landscape. The technique described gives a simple method for exploring the effects of the removal of wild corridors, and the creation of wild set-aside fields: interventions that are common to many national agricultural policies. The effects of these manipulations on central-place nesting pollinators are varied, and depend upon the behavioural rules that the pollinators are using to move through the environment. The value of this modelling framework is discussed, and future directions for exploration are identified.

  6. Landscape fragmentation and pollinator movement within agricultural environments: a modelling framework for exploring foraging and movement ecology.

    Science.gov (United States)

    Rands, Sean A

    2014-01-01

    Pollinator decline has been linked to landscape change, through both habitat fragmentation and the loss of habitat suitable for the pollinators to live within. One method for exploring why landscape change should affect pollinator populations is to combine individual-level behavioural ecological techniques with larger-scale landscape ecology. A modelling framework is described that uses spatially-explicit individual-based models to explore the effects of individual behavioural rules within a landscape. The technique described gives a simple method for exploring the effects of the removal of wild corridors, and the creation of wild set-aside fields: interventions that are common to many national agricultural policies. The effects of these manipulations on central-place nesting pollinators are varied, and depend upon the behavioural rules that the pollinators are using to move through the environment. The value of this modelling framework is discussed, and future directions for exploration are identified.

  7. The spatial limitations of current neutral models of biodiversity.

    Directory of Open Access Journals (Sweden)

    Rampal S Etienne

    Full Text Available The unified neutral theory of biodiversity and biogeography is increasingly accepted as an informative null model of community composition and dynamics. It has successfully produced macro-ecological patterns such as species-area relationships and species abundance distributions. However, the models employed make many unrealistic auxiliary assumptions. For example, the popular spatially implicit version assumes a local plot exchanging migrants with a large panmictic regional source pool. This simple structure allows rigorous testing of its fit to data. In contrast, spatially explicit models assume that offspring disperse only limited distances from their parents, but one cannot as yet test the significance of their fit to data. Here we compare the spatially explicit and the spatially implicit model, fitting the most-used implicit model (with two levels, local and regional to data simulated by the most-used spatially explicit model (where offspring are distributed about their parent on a grid according to either a radially symmetric Gaussian or a 'fat-tailed' distribution. Based on these fits, we express spatially implicit parameters in terms of spatially explicit parameters. This suggests how we may obtain estimates of spatially explicit parameters from spatially implicit ones. The relationship between these parameters, however, makes no intuitive sense. Furthermore, the spatially implicit model usually fits observed species-abundance distributions better than those calculated from the spatially explicit model's simulated data. Current spatially explicit neutral models therefore have limited descriptive power. However, our results suggest that a fatter tail of the dispersal kernel seems to improve the fit, suggesting that dispersal kernels with even fatter tails should be studied in future. We conclude that more advanced spatially explicit models and tools to analyze them need to be developed.

  8. A new spatial multiple discrete-continuous modeling approach to land use change analysis.

    Science.gov (United States)

    2013-09-01

    This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

  9. MODELING THE EFFECT OF STREAM NETWORK CHARACTERISTICS AND JUVENILE MOVEMENT ON COHO SALMON

    Science.gov (United States)

    Simulation modeling can be a valuable tool for improving our scientific understanding of the mechanisms that affect fish abundance and sustainability. Spatially explicit models, in particular, can be used to study interactions between fish biology and spatiotemporal habitat patt...

  10. Unifying ecology and macroevolution with individual-based theory.

    Science.gov (United States)

    Rosindell, James; Harmon, Luke J; Etienne, Rampal S

    2015-05-01

    A contemporary goal in both ecology and evolutionary biology is to develop theory that transcends the boundary between the two disciplines, to understand phenomena that cannot be explained by either field in isolation. This is challenging because macroevolution typically uses lineage-based models, whereas ecology often focuses on individual organisms. Here, we develop a new parsimonious individual-based theory by adding mild selection to the neutral theory of biodiversity. We show that this model generates realistic phylogenies showing a slowdown in diversification and also improves on the ecological predictions of neutral theory by explaining the occurrence of very common species. Moreover, we find the distribution of individual fitness changes over time, with average fitness increasing at a pace that depends positively on community size. Consequently, large communities tend to produce fitter species than smaller communities. These findings have broad implications beyond biodiversity theory, potentially impacting, for example, invasion biology and paleontology. © 2015 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

  11. Relationships between migration rates and landscape resistance assessed using individual-based simulations

    Science.gov (United States)

    E. L. Landguth; S. A. Cushman; M. A. Murphy; G. Luikart

    2010-01-01

    Linking landscape effects on gene flow to processes such as dispersal and mating is essential to provide a conceptual foundation for landscape genetics. It is particularly important to determine how classical population genetic models relate to recent individual-based landscape genetic models when assessing individual movement and its influence on population genetic...

  12. AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT: A GIS-BASED HYDROLOGIC MODELING TOOL

    Science.gov (United States)

    Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extens...

  13. Integrating Individual-Based Indices of Contaminant Effects

    Directory of Open Access Journals (Sweden)

    Christopher L. Rowe

    2001-01-01

    contaminants for long periods of time, research focused on one or few sublethal responses could substantially underestimate overall effects on individuals. We suggest that investigators adopt a more integrated perspective on contaminant-induced biological changes so that studies of individual-based effects can be better integrated into analyses of mechanisms of population change.

  14. Importance of the habitat choice behavior assumed when modeling the effects of food and temperature on fish populations

    Science.gov (United States)

    Wildhaber, Mark L.; Lamberson, Peter J.

    2004-01-01

    Various mechanisms of habitat choice in fishes based on food and/or temperature have been proposed: optimal foraging for food alone; behavioral thermoregulation for temperature alone; and behavioral energetics and discounted matching for food and temperature combined. Along with development of habitat choice mechanisms, there has been a major push to develop and apply to fish populations individual-based models that incorporate various forms of these mechanisms. However, it is not known how the wide variation in observed and hypothesized mechanisms of fish habitat choice could alter fish population predictions (e.g. growth, size distributions, etc.). We used spatially explicit, individual-based modeling to compare predicted fish populations using different submodels of patch choice behavior under various food and temperature distributions. We compared predicted growth, temperature experience, food consumption, and final spatial distribution using the different models. Our results demonstrated that the habitat choice mechanism assumed in fish population modeling simulations was critical to predictions of fish distribution and growth rates. Hence, resource managers who use modeling results to predict fish population trends should be very aware of and understand the underlying patch choice mechanisms used in their models to assure that those mechanisms correctly represent the fish populations being modeled.

  15. Modelo espacialmente explícito de la migración estacional del pez vela (Istiophorus platypterus) en el Pacífico mexicano Spatial explicit model for seasonal migration of sailfish (Istiophorus platypterus) in the Mexican Pacific

    OpenAIRE

    René Macías-Zamora; Aramis Olivos-Ortiz; Ana Luisa Vidaurri-Sotelo; Miguel Ángel Carrasco-Águila; Ernesto Torres-Orozco

    2011-01-01

    Utilizando los datos de captura y esfuerzo registrados en la pesca deportiva realizada en los puertos de Mazatlán, Sinaloa y Buena Vista, Baja California Sur, México, durante los periodos 1979-2005 y 1985-2006 respectivamente, se construyó un año "tipo" o promedio, y se elaboró un modelo espacial determinístico en tiempo discreto para simular los movimientos masivos estacionales que realiza el pez vela (Istiophorus platypterus) en la Zona Económica Exclusiva del Pacífico mexicano. Los parámet...

  16. Pattern formation in individual-based systems with time-varying parameters

    Science.gov (United States)

    Ashcroft, Peter; Galla, Tobias

    2013-12-01

    We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

  17. Modeling fuels and fire effects in 3D: Model description and applications

    Science.gov (United States)

    Francois Pimont; Russell Parsons; Eric Rigolot; Francois de Coligny; Jean-Luc Dupuy; Philippe Dreyfus; Rodman R. Linn

    2016-01-01

    Scientists and managers critically need ways to assess how fuel treatments alter fire behavior, yet few tools currently exist for this purpose.We present a spatially-explicit-fuel-modeling system, FuelManager, which models fuels, vegetation growth, fire behavior (using a physics-based model, FIRETEC), and fire effects. FuelManager's flexible approach facilitates...

  18. Agent-based modelling of cholera diffusion

    NARCIS (Netherlands)

    Augustijn-Beckers, Petronella; Doldersum, Tom; Useya, Juliana; Augustijn, Dionysius C.M.

    2016-01-01

    This paper introduces a spatially explicit agent-based simulation model for micro-scale cholera diffusion. The model simulates both an environmental reservoir of naturally occurring V.cholerae bacteria and hyperinfectious V. cholerae. Objective of the research is to test if runoff from open refuse

  19. Empirically derived neighbourhood rules for urban land-use modelling

    DEFF Research Database (Denmark)

    Hansen, Henning Sten

    2012-01-01

    Land-use modelling and spatial scenarios have gained attention as a means to meet the challenge of reducing uncertainty in spatial planning and decision making. Many of the recent modelling efforts incorporate cellular automata to accomplish spatially explicit land-use-change modelling. Spatial...

  20. Exploring component-based approaches in forest landscape modeling

    Science.gov (United States)

    H. S. He; D. R. Larsen; D. J. Mladenoff

    2002-01-01

    Forest management issues are increasingly required to be addressed in a spatial context, which has led to the development of spatially explicit forest landscape models. The numerous processes, complex spatial interactions, and diverse applications in spatial modeling make the development of forest landscape models difficult for any single research group. New...

  1. Unifying ecology and macroevolution with individual-based theory

    NARCIS (Netherlands)

    Rosindell, James; Harmon, Luke J.; Etienne, Rampal S.

    A contemporary goal in both ecology and evolutionary biology is to develop theory that transcends the boundary between the two disciplines, to understand phenomena that cannot be explained by either field in isolation. This is challenging because macroevolution typically uses lineage-based models,

  2. An individual-based approach to SIR epidemics in contact networks.

    Science.gov (United States)

    Youssef, Mina; Scoglio, Caterina

    2011-08-21

    Many approaches have recently been proposed to model the spread of epidemics on networks. For instance, the Susceptible/Infected/Recovered (SIR) compartmental model has successfully been applied to different types of diseases that spread out among humans and animals. When this model is applied on a contact network, the centrality characteristics of the network plays an important role in the spreading process. However, current approaches only consider an aggregate representation of the network structure, which can result in inaccurate analysis. In this paper, we propose a new individual-based SIR approach, which considers the whole description of the network structure. The individual-based approach is built on a continuous time Markov chain, and it is capable of evaluating the state probability for every individual in the network. Through mathematical analysis, we rigorously confirm the existence of an epidemic threshold below which an epidemic does not propagate in the network. We also show that the epidemic threshold is inversely proportional to the maximum eigenvalue of the network. Additionally, we study the role of the whole spectrum of the network, and determine the relationship between the maximum number of infected individuals and the set of eigenvalues and eigenvectors. To validate our approach, we analytically study the deviation with respect to the continuous time Markov chain model, and we show that the new approach is accurate for a large range of infection strength. Furthermore, we compare the new approach with the well-known heterogeneous mean field approach in the literature. Ultimately, we support our theoretical results through extensive numerical evaluations and Monte Carlo simulations. Published by Elsevier Ltd.

  3. The importance of realistic dispersal models in conservation planning: application of a novel modelling platform to evaluate management scenarios in an Afrotropical biodiversity hotspot.

    Science.gov (United States)

    Aben, Job; Bocedi, Greta; Palmer, Stephen C F; Pellikka, Petri; Strubbe, Diederik; Hallmann, Caspar; Travis, Justin M J; Lens, Luc; Matthysen, Erik

    2016-08-01

    As biodiversity hotspots are often characterized by high human population densities, implementation of conservation management practices that focus only on the protection and enlargement of pristine habitats is potentially unrealistic. An alternative approach to curb species extinction risk involves improving connectivity among existing habitat patches. However, evaluation of spatially explicit management strategies is challenging, as predictive models must account for the process of dispersal, which is difficult in terms of both empirical data collection and modelling.Here, we use a novel, individual-based modelling platform that couples demographic and mechanistic dispersal models to evaluate the effectiveness of realistic management scenarios tailored to conserve forest birds in a highly fragmented biodiversity hotspot. Scenario performance is evaluated based on the spatial population dynamics of a well-studied forest bird species.The largest population increase was predicted to occur under scenarios increasing habitat area. However, the effectiveness was sensitive to spatial planning. Compared to adding one large patch to the habitat network, adding several small patches yielded mixed benefits: although overall population sizes increased, specific newly created patches acted as dispersal sinks, which compromised population persistence in some existing patches. Increasing matrix connectivity by the creation of stepping stones is likely to result in enhanced dispersal success and occupancy of smaller patches. Synthesis and applications . We show that the effectiveness of spatial management is strongly driven by patterns of individual dispersal across landscapes. For species conservation planning, we advocate the use of models that incorporate adequate realism in demography and, particularly, in dispersal behaviours.

  4. A stochastic population model to evaluate Moapa dace (Moapa coriacea) population growth under alternative management scenarios

    Science.gov (United States)

    Perry, Russell W.; Jones, Edward; Scoppettone, G. Gary

    2015-07-14

    The primary goal of this research project was to evaluate the response of Moapa dace (Moapa coriacea) to the potential effects of changes in the amount of available habitat due to human influences such as ground water pumping, barriers to movement, and extirpation of Moapa dace from the mainstem Muddy River. To understand how these factors affect Moapa dace populations and to provide a tool to guide recovery actions, we developed a stochastic model to simulate Moapa dace population dynamics. Specifically, we developed an individual based model (IBM) to incorporate the critical components that drive Moapa dace population dynamics. Our model is composed of several interlinked submodels that describe changes in Moapa dace habitat as translated into carrying capacity, the influence of carrying capacity on demographic rates of dace, and the consequent effect on equilibrium population sizes. The model is spatially explicit and represents the stream network as eight discrete stream segments. The model operates at a monthly time step to incorporate seasonally varying reproduction. Growth rates of individuals vary among stream segments, with growth rates increasing along a headwater to mainstem gradient. Movement and survival of individuals are driven by density-dependent relationships that are influenced by the carrying capacity of each stream segment.

  5. Empirical methods for modeling landscape change, ecosystem services, and biodiversity

    Science.gov (United States)

    David Lewis; Ralph. Alig

    2009-01-01

    The purpose of this paper is to synthesize recent economics research aimed at integrating discrete-choice econometric models of land-use change with spatially-explicit landscape simulations and quantitative ecology. This research explicitly models changes in the spatial pattern of landscapes in two steps: 1) econometric estimation of parcel-scale transition...

  6. Model-based optimization biofilm based systems performing autotrophic nitrogen removal using the comprehensive NDHA model

    DEFF Research Database (Denmark)

    Valverde Pérez, Borja; Ma, Yunjie; Morset, Martin

    Completely autotrophic nitrogen removal (CANR) can be obtained in single stage biofilm-based bioreactors. However, their environmental footprint is compromised due to elevated N2O emissions. We developed novel spatially explicit biochemical process model of biofilm based CANR systems that predicts...

  7. Empirical phylogenies and species abundance distributions are consistent with pre-equilibrium dynamics of neutral community models with gene flow

    KAUST Repository

    Bonnet-Lebrun, Anne-Sophie

    2017-03-17

    Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modelled communities - i.e., with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities - from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual-based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species-abundance distribution), consistent with gene flow being a key process in macro-evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in pre-equilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under pre-equilibrium conditions. This article is protected by copyright. All rights reserved.

  8. Empirical phylogenies and species abundance distributions are consistent with pre-equilibrium dynamics of neutral community models with gene flow

    KAUST Repository

    Bonnet-Lebrun, Anne-Sophie; Manica, Andrea; Eriksson, Anders; Rodrigues, Ana S.L.

    2017-01-01

    Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modelled communities - i.e., with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities - from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual-based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species-abundance distribution), consistent with gene flow being a key process in macro-evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in pre-equilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under pre-equilibrium conditions. This article is protected by copyright. All rights reserved.

  9. Spatially explicit trends in the global conservation status of vertebrates.

    Science.gov (United States)

    Rodrigues, Ana S L; Brooks, Thomas M; Butchart, Stuart H M; Chanson, Janice; Cox, Neil; Hoffmann, Michael; Stuart, Simon N

    2014-01-01

    The world's governments have committed to preventing the extinction of threatened species and improving their conservation status by 2020. However, biodiversity is not evenly distributed across space, and neither are the drivers of its decline, and so different regions face very different challenges. Here, we quantify the contribution of regions and countries towards recent global trends in vertebrate conservation status (as measured by the Red List Index), to guide action towards the 2020 target. We found that>50% of the global deterioration in the conservation status of birds, mammals and amphibians is concentrated in nations (e.g. Cook Islands, Fiji, Mauritius, Seychelles, and Tonga), have achieved net improvements. Per capita wealth does not explain these patterns, with two of the richest countries - United States and Australia - fairing conspicuously poorly. Different countries were affected by different combinations of threats. Reducing global rates of biodiversity loss will require investment in the regions and countries with the highest responsibility for the world's biodiversity, focusing on conserving those species and areas most in peril and on reducing the drivers with the highest impacts.

  10. Spatially explicit basal area growth of Norway spruce

    Czech Academy of Sciences Publication Activity Database

    Krejza, Jan; Světlík, J.; Pokorný, Radek

    2015-01-01

    Roč. 29, č. 5 (2015), s. 1545-1558 ISSN 0931-1890 R&D Projects: GA TA ČR TA02010945 Institutional support: RVO:67179843 Keywords : competition * social area * Weighted Voronoi polygons * increment * Picea abies Subject RIV: GK - Forestry Impact factor: 1.706, year: 2015

  11. Spatially explicit data: stewardship and ethical challenges in science.

    Science.gov (United States)

    Hartter, Joel; Ryan, Sadie J; Mackenzie, Catrina A; Parker, John N; Strasser, Carly A

    2013-09-01

    Scholarly communication is at an unprecedented turning point created in part by the increasing saliency of data stewardship and data sharing. Formal data management plans represent a new emphasis in research, enabling access to data at higher volumes and more quickly, and the potential for replication and augmentation of existing research. Data sharing has recently transformed the practice, scope, content, and applicability of research in several disciplines, in particular in relation to spatially specific data. This lends exciting potentiality, but the most effective ways in which to implement such changes, particularly for disciplines involving human subjects and other sensitive information, demand consideration. Data management plans, stewardship, and sharing, impart distinctive technical, sociological, and ethical challenges that remain to be adequately identified and remedied. Here, we consider these and propose potential solutions for their amelioration.

  12. Spatially explicit prioritization of human antibiotics and antineoplastics in Europe.

    Science.gov (United States)

    Oldenkamp, Rik; Huijbregts, Mark A J; Hollander, Anne; Versporten, Ann; Goossens, Herman; Ragas, Ad M J

    2013-01-01

    This paper presents a screening tool for the location-specific prioritization of human pharmaceutical emissions in Europe, based on risk quotients for the aquatic environment and human health. The tool provides direction towards either monitoring activities or additional research. Its application is illustrated for a set of 11 human antibiotics and 7 antineoplastics. Risk quotients for the aquatic environment were highest for levofloxacin, doxycycline and ciprofloxacin, located in Northern Italy (Milan region; particularly levofloxacin) and other densely populated areas in Europe (e.g. London, Krakow and the Ruhr area). Risk quotients for human health not only depend on pharmaceutical and location, but also on behavioral characteristics, such as consumption patterns. Infants in eastern Spain that consume locally produced food and conventionally treated drinking water were predicted to run the highest risks. A limited comparison with measured concentrations in surface water showed that predicted and measured concentrations are approximately within one order of magnitude. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Influence of spatial temperature estimation method in ecohydrologic modeling in the western Oregon Cascades

    Science.gov (United States)

    E. Garcia; C.L. Tague; J. Choate

    2013-01-01

    Most spatially explicit hydrologic models require estimates of air temperature patterns. For these models, empirical relationships between elevation and air temperature are frequently used to upscale point measurements or downscale regional and global climate model estimates of air temperature. Mountainous environments are particularly sensitive to air temperature...

  14. The Application of FIA-based Data to Wildlife Habitat Modeling: A Comparative Study

    Science.gov (United States)

    Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino; Randall J. Schultz

    2005-01-01

    We evaluated the capability of two types of models, one based on spatially explicit variables derived from FIA data and one using so-called traditional habitat evaluation methods, for predicting the presence of cavity-nesting bird habitat in Fishlake National Forest, Utah. Both models performed equally well, in measures of predictive accuracy, with the FIA-based model...

  15. Representing climate, disturbance, and vegetation interactions in landscape models

    Science.gov (United States)

    Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg

    2015-01-01

    The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...

  16. Effects of stand composition and thinning in mixed-species forests : a modeling approach applied to Douglas-fir and beech

    NARCIS (Netherlands)

    Bartelink, H.H.

    2000-01-01

    Models estimating growth and yield of forest stands provide important tools for forest management. Pure stands have been modeled extensively and successfully for decades; however, relatively few models for mixed-species stands have been developed. A spatially explicit, mechanistic model (COMMIX) is

  17. Modeling the effects of trophy selection and environmental disturbance on a simulated population of African lions.

    Science.gov (United States)

    Whitman, Karyl L; Starfield, Anthony M; Quadling, Henley; Packer, Craig

    2007-06-01

    Tanzania is a premier destination for trophy hunting of African lions (Panthera leo) and is home to the most extensive long-term study of unhunted lions. Thus, it provides a unique opportunity to apply data from a long-term field study to a conservation dilemma: How can a trophy-hunted species whose reproductive success is closely tied to social stability be harvested sustainably? We used an individually based, spatially explicit, stochastic model, parameterized with nearly 40 years of behavioral and demographic data on lions in the Serengeti, to examine the separate effects of trophy selection and environmental disturbance on the viability of a simulated lion population in response to annual harvesting. Female population size was sensitive to the harvesting of young males (> or = 3 years), whereas hunting represented a relatively trivial threat to population viability when the harvest was restricted to mature males (> or = 6 years). Overall model performance was robust to environmental disturbance and to errors in age assessment based on nose coloration as an index used to age potential trophies. Introducing an environmental disturbance did not eliminate the capacity to maintain a viable breeding population when harvesting only older males, and initially depleted populations recovered within 15-25 years after the disturbance to levels comparable to hunted populations that did not experience a catastrophic event. These results are consistent with empirical observations of lion resilience to environmental stochasticity.

  18. The influence of multi-season imagery on models of canopy cover: A case study

    Science.gov (United States)

    John W. Coulston; Dennis M. Jacobs; Chris R. King; Ivey C. Elmore

    2013-01-01

    Quantifying tree canopy cover in a spatially explicit fashion is important for broad-scale monitoring of ecosystems and for management of natural resources. Researchers have developed empirical models of tree canopy cover to produce geospatial products. For subpixel models, percent tree canopy cover estimates (derived from fine-scale imagery) serve as the response...

  19. Integrated modeling of long-term vegetation and hydrologic dynamics in Rocky Mountain watersheds

    Science.gov (United States)

    Robert Steven Ahl

    2007-01-01

    Changes in forest structure resulting from natural disturbances, or managed treatments, can have negative and long lasting impacts on water resources. To facilitate integrated management of forest and water resources, a System for Long-Term Integrated Management Modeling (SLIMM) was developed. By combining two spatially explicit, continuous time models, vegetation...

  20. Modeling carbon stocks in a secondary tropical dry forest in the Yucatan Peninsula, Mexico

    Science.gov (United States)

    Zhaohua Dai; Richard A. Birdsey; Kristofer D. Johnson; Juan Manuel Dupuy; Jose Luis Hernandez-Stefanoni; Karen. Richardson

    2014-01-01

    The carbon balance of secondary dry tropical forests of Mexico’s Yucatan Peninsula is sensitive to human and natural disturbances and climate change. The spatially explicit process model Forest-DeNitrification-DeComposition (DNDC) was used to estimate forest carbon dynamics in this region, including the effects of disturbance on carbon stocks. Model evaluation using...

  1. Turing patterns and long-time behavior in a three-species food-chain model

    KAUST Repository

    Parshad, Rana D.; Kumari, Nitu Krishna; Kasimov, Aslan R.; Ait Abderrahmane, Hamid

    2014-01-01

    We consider a spatially explicit three-species food chain model, describing generalist top predator-specialist middle predator-prey dynamics. We investigate the long-time dynamics of the model and show the existence of a finite dimensional global

  2. Exploring the role of fire, succession, climate, and weather on landscape dynamics using comparative modeling

    Science.gov (United States)

    Robert E. Keane; Geoffrey J. Cary; Mike D. Flannigan; Russell A. Parsons; Ian D. Davies; Karen J. King; Chao Li; Ross A. Bradstock; Malcolm Gill

    2013-01-01

    An assessment of the relative importance of vegetation change and disturbance as agents of landscape change under current and future climates would (1) provide insight into the controls of landscape dynamics, (2) help inform the design and development of coarse scale spatially explicit ecosystem models such as Dynamic Global Vegetation Models (DGVMs), and (3) guide...

  3. Using a cellular model to explore human-facilitated spread of risk of EAB in Minnesota

    Science.gov (United States)

    Anantha Prasad; Louis Iverson; Matthew Peters; Steve. Matthews

    2011-01-01

    The Emerald Ash Borer has made inroads to Minnesota in the past two years, killing ash trees. We use our spatially explicit cell based model called EAB-SHIFT to calculate the risk of infestation owing to flight characteristics and short distance movement of the insect (insect flight model, IFM), and the human facilitated agents like roads, campgrounds etc. (insect ride...

  4. Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS

    NARCIS (Netherlands)

    Peck, Myron A.; Arvanitidis, Christos; Butenschön, Momme; Canu, Donata Melaku; Chatzinikolaou, Eva; Cucco, Andrea; Domenici, Paolo; Fernandes, Jose A.; Gasche, Loic; Huebert, Klaus B.; Hufnagl, Marc; Jones, Miranda C.; Kempf, Alexander; Keyl, Friedemann; Maar, Marie; Mahévas, Stéphanie; Marchal, Paul; Nicolas, Delphine; Pinnegar, John K.; Rivot, Etienne; Rochette, Sébastien; Sell, Anne F.; Sinerchia, Matteo; Solidoro, Cosimo; Somerfield, Paul J.; Teal, Lorna R.; Travers-trolet, Morgan; De Wolfshaar, Van Karen E.

    2018-01-01

    We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of

  5. Breeding success of a marine central place forager in the context of climate change: A modeling approach.

    Directory of Open Access Journals (Sweden)

    Lauriane Massardier-Galatà

    Full Text Available In response to climate warming, a southward shift in productive frontal systems serving as the main foraging sites for many top predator species is likely to occur in Subantarctic areas. Central place foragers, such as seabirds and pinnipeds, are thus likely to cope with an increase in the distance between foraging locations and their land-based breeding colonies. Understanding how central place foragers should modify their foraging behavior in response to changes in prey accessibility appears crucial. A spatially explicit individual-based simulation model (Marine Central Place Forager Simulator (MarCPFS, including bio-energetic components, was built to evaluate effects of possible changes in prey resources accessibility on individual performances and breeding success. The study was calibrated on a particular example: the Antarctic fur seal (Arctocephalus gazella, which alternates between oceanic areas in which females feed and the land-based colony in which they suckle their young over a 120 days rearing period. Our model shows the importance of the distance covered to feed and prey aggregation which appeared to be key factors to which animals are highly sensitive. Memorization and learning abilities also appear to be essential breeding success traits. Females were found to be most successful for intermediate levels of prey aggregation and short distance to the resource, resulting in optimal female body length. Increased distance to resources due to climate warming should hinder pups' growth and survival while female body length should increase.

  6. Development of input data layers for the FARSITE fire growth model for the Selway-Bitterroot Wilderness Complex, USA

    Science.gov (United States)

    Robert E. Keane; Janice L. Garner; Kirsten M. Schmidt; Donald G. Long; James P. Menakis; Mark A. Finney

    1998-01-01

    Fuel and vegetation spatial data layers required by the spatially explicit fire growth model FARSITE were developed for all lands in and around the Selway-Bitterroot Wilderness Area in Idaho and Montana. Satellite imagery and terrain modeling were used to create the three base vegetation spatial data layers of potential vegetation, cover type, and structural stage....

  7. Modeling the impacts of climate variability and hurricane on carbon sequestration in a coastal forested wetland in South Carolina

    Science.gov (United States)

    Zhaohua Dai; Carl C. Trettin; Changsheng Li; Ge Sun; Devendra M. Amatya; Harbin Li

    2013-01-01

    The impacts of hurricane disturbance and climate variability on carbon dynamics in a coastal forested wetland in South Carolina of USA were simulated using the Forest-DNDC model with a spatially explicit approach. The model was validated using the measured biomass before and after Hurricane Hugo and the biomass inventories in 2006 and 2007, showed that the Forest-DNDC...

  8. Spatial pattern formation of coastal vegetation in response to external gradients and positive feedbacks affecting soil porewater salinity: A model study

    Science.gov (United States)

    Jiang, J.; DeAngelis, D.L.; Smith, T. J.; Teh, S.Y.; Koh, H. L.

    2012-01-01

    Coastal vegetation of South Florida typically comprises salinity-tolerant mangroves bordering salinity-intolerant hardwood hammocks and fresh water marshes. Two primary ecological factors appear to influence the maintenance of mangrove/hammock ecotones against changes that might occur due to disturbances. One of these is a gradient in one or more environmental factors. The other is the action of positive feedback mechanisms, in which each vegetation community influences its local environment to favor itself, reinforcing the boundary between communities. The relative contributions of these two factors, however, can be hard to discern. A spatially explicit individual-based model of vegetation, coupled with a model of soil hydrology and salinity dynamics is presented here to simulate mangrove/hammock ecotones in the coastal margin habitats of South Florida. The model simulation results indicate that an environmental gradient of salinity, caused by tidal flux, is the key factor separating vegetation communities, while positive feedback involving the different interaction of each vegetation type with the vadose zone salinity increases the sharpness of boundaries, and maintains the ecological resilience of mangrove/hammock ecotones against small disturbances. Investigation of effects of precipitation on positive feedback indicates that the dry season, with its low precipitation, is the period of strongest positive feedback. ?? 2011 Springer Science+Business Media B.V. (outside the USA).

  9. Using occupancy and population models to assess habitat conservation opportunities for an isolated carnivore population

    Science.gov (United States)

    Wayne Spencer; Heather Rustigian-Romsos; James Strittholt; Robert Scheller; William Zielinski; Richard Truex

    2011-01-01

    An isolated population of the fisher (Martes pennanti) in the southern Sierra Nevada, California, is threatened by small size and habitat alteration from wildfires, fuels management, and other factors. We assessed the population’s status and conservation options for its habitat using a spatially explicit population model coupled with a...

  10. Assessing accuracy of point fire intervals across landscapes with simulation modelling

    Science.gov (United States)

    Russell A. Parsons; Emily K. Heyerdahl; Robert E. Keane; Brigitte Dorner; Joseph Fall

    2007-01-01

    We assessed accuracy in point fire intervals using a simulation model that sampled four spatially explicit simulated fire histories. These histories varied in fire frequency and size and were simulated on a flat landscape with two forest types (dry versus mesic). We used three sampling designs (random, systematic grids, and stratified). We assessed the sensitivity of...

  11. Climate Change and Agricultural Productivity in Sub-Saharan Africa: A Spatial Sample Selection Model

    NARCIS (Netherlands)

    Ward, P.S.; Florax, R.J.G.M.; Flores-Lagunes, A.

    2014-01-01

    Using spatially explicit data, we estimate a cereal yield response function using a recently developed estimator for spatial error models when endogenous sample selection is of concern. Our results suggest that yields across Sub-Saharan Africa will decline with projected climatic changes, and that

  12. Models for mapping potential habitat at landscape scales: an example using northern spotted owls.

    Science.gov (United States)

    William C. McComb; Michael T. McGrath; Thomas A. Spies; David. Vesely

    2002-01-01

    We are assessing the potential for current and alternative policies in the Oregon Coast Range to affect habitat capability for a suite of forest resources. We provide an example of a spatially explicit habitat capability model for northern spotted owls (Strix occidentalis caurina)to illustrate the approach we are taking to assess potential changes...

  13. Application of spatial models to the stopover ecology of trans-Gulf migrants

    Science.gov (United States)

    Theodore R. Simons; Scott M. Pearson; Frank R. Moore

    2000-01-01

    Studies at migratory stopover sites along the northern coast of the Gulf of Mexico are providing an understanding of how weather, habitat, and energetic factors combine to shape the stopover ecology of trans-Gulf migrants. We are coupling this understanding with analyses of landscape-level patterns of habitat availability by using spatially explicit models to simulate...

  14. A polygon-based modeling approach to assess exposure of resources and assets to wildfire

    Science.gov (United States)

    Matthew P. Thompson; Joe Scott; Jeffrey D. Kaiden; Julie W. Gilbertson-Day

    2013-01-01

    Spatially explicit burn probability modeling is increasingly applied to assess wildfire risk and inform mitigation strategy development. Burn probabilities are typically expressed on a per-pixel basis, calculated as the number of times a pixel burns divided by the number of simulation iterations. Spatial intersection of highly valued resources and assets (HVRAs) with...

  15. A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock

    Directory of Open Access Journals (Sweden)

    Richard A Bradhurst

    2015-03-01

    Full Text Available Foot-and-mouth disease (FMD is a highly contagious and economically important viral disease of cloven-hoofed animals. Australia's freedom from FMD underpins a valuable trade in live animals and animal products. An outbreak of FMD would result in the loss of export markets and cause severe disruption to domestic markets. The prevention of, and contingency planning for, FMD are of key importance to government, industry, producers and the community. The spread and control of FMD is complex and dynamic due to a highly contagious multi-host pathogen operating in a heterogeneous environment across multiple jurisdictions. Epidemiological modelling is increasingly being recognized as a valuable tool for investigating the spread of disease under different conditions and the effectiveness of control strategies. Models of infectious disease can be broadly classified as: population-based models that are formulated from the top-down and employ population-level relationships to describe individual-level behaviour, individual-based models that are formulated from the bottom-up and aggregate individual-level behaviour to reveal population-level relationships, or hybrid models which combine the two approaches into a single model.The Australian Animal Disease Spread (AADIS hybrid model employs a deterministic equation-based model (EBM to model within-herd spread of FMD, and a stochastic, spatially-explicit agent-based model (ABM to model between-herd spread and control. The EBM provides concise and computationally efficient predictions of herd prevalence and clinical signs over time. The ABM captures the complex, stochastic and heterogeneous environment in which an FMD epidemic operates. The AADIS event-driven hybrid EBM/ABM architecture is a flexible, efficient and extensible framework for modelling the spread and control of disease in livestock on a national scale. We present an overview of the AADIS hybrid approach and a description of the model

  16. What can and can't we say about indirect land-use change in Brazil using an integrated economic - land-use change model?

    NARCIS (Netherlands)

    Verstegen, J.A.; Hilst, van der Floor; Woltjer, Geert; Karssenberg, Derek; Jong, de S.M.; Faaij, André P.C.

    2016-01-01

    It is commonly recognized that large uncertainties exist in modelled biofuel-induced indirect land-use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this study, we demonstrate a general

  17. Developing a cellular automata model of urban growth to inform spatial policy for flood mitigation : A case study in Kampala, Uganda

    NARCIS (Netherlands)

    Pérez-Molina, Eduardo; Sliuzas, R.V.; Flacke, J.; Jetten, V.G.

    2017-01-01

    Urban growth may intensify local flooding problems. Understanding the spatially explicit flood consequences of possible future land cover patterns contributes to inform policy for mitigating these impacts. A cellular automata model has been coupled with the openLISEM integrated flood modeling tool

  18. Combination of process-oriented and pattern-oriented models of land-use change in a mountain area of Vietnam

    NARCIS (Netherlands)

    Castella, J.C.; Verburg, P.H.

    2007-01-01

    The tools and methods developed by different scientific communities to simulate the dynamics of land use have emphasised either processes or patterns of changes. Agent-based models (ABM) belong to the former category while many spatially explicit simulation models belong to the latter. These two

  19. Individual-based and group-based occupational exposure assessment: some equations to evaluate different strategies.

    NARCIS (Netherlands)

    Tielemans, E.; Kupper, L.L.; Kromhout, H.; Heederik, D.; Houba, R.

    1998-01-01

    Basically, two strategies can be considered for the analysis of hazardous pollutants in the work environment: group-based and individual-based strategies. This paper provides existing and recently derived equations for both strategies describing the influence of several factors on attenuation and on

  20. Individual-Based Compulsive Sexual Behavior Scale: Its Development and Importance in Examining Compulsive Sexual Behavior.

    Science.gov (United States)

    Efrati, Yaniv; Mikulincer, Mario

    2018-04-03

    Compulsive sexual behavior comprises individual-based (e.g., sexual fantasies, compulsive sexual thoughts, masturbation) and partnered (e.g., interpersonal sexual conquests, repeated infidelity) facets. Most instruments for assessing compulsive sexual behavior, however, focus less on the individual-based facet and specifically on fantasies and compulsive thoughts. In the current research, we developed and validated an individual-based compulsive sexual behavior scale (I-CSB). In Study 1 (N = 492), the factorial structure of the I-CSB was examined. In Study 2 (N = 406), we assessed I-CSB's convergent validity. In Study 3 (N = 112), we examined whether the I-CSB differentiates between individuals who suffer from compulsive sexual behavior and those who do not. Results revealed a four-factor structure for individual-based compulsive sexual behavior that is associated with an intense inner conflict regarding sexuality (high arousal contrasting with high sexual anxiety), and that accounts for approximately 75% of the differences between people with compulsive sexual behavior and controls. Results are discussed in light of the need for a broader understanding of compulsive sexual behavior.

  1. Model-based scenario planning to develop climate change adaptation strategies for rare plant populations in grassland reserves

    Science.gov (United States)

    Laura Phillips-Mao; Susan M. Galatowitsch; Stephanie A. Snyder; Robert G. Haight

    2016-01-01

    Incorporating climate change into conservation decision-making at site and population scales is challenging due to uncertainties associated with localized climate change impacts and population responses to multiple interacting impacts and adaptation strategies. We explore the use of spatially explicit population models to facilitate scenario analysis, a conservation...

  2. Spatial structure of an individual-based plant–pollinator network

    DEFF Research Database (Denmark)

    Dupont, Yoko Luise; Nielsen, Kristian Trøjelsgaard; Hagen, Melanie

    2014-01-01

    The influence of space on the structure (e.g. modularity) of complex ecological networks remains largely unknown. Here, we sampled an individual-based plant–pollinator network by following the movements and flower visits of marked bumblebee individuals within a population of thistle plants...... for which the identities and spatial locations of stems were mapped in a 50  50 m study plot. The plant–pollinator network was dominated by parasitic male bumblebees and had a significantly modular structure, with four identified modules being clearly separated in space. This indicated that individual....... This demonstrated that individual-based plant–pollinator networks are influenced by both the spatial structure of plant populations and individual-specific plant traits. Additionally, bumblebee individuals with long observation times were important for both the connectivity between and within modules. The latter...

  3. Evaluating the Effectiveness of Contact Tracing on Tuberculosis Outcomes in Saskatchewan Using Individual-Based Modeling

    Science.gov (United States)

    Tian, Yuan; Osgood, Nathaniel D.; Al-Azem, Assaad; Hoeppner, Vernon H.

    2013-01-01

    Tuberculosis (TB) is a potentially fatal disease spread by an airborne pathogen infecting approximately one third of the globe. For decades, contact tracing (CT) has served a key role in the control of TB and many other notifiable communicable diseases. Unfortunately, CT is a labor-intensive and time-consuming process and is often conducted by a…

  4. An individual-based process model to simulate landscape-scale forest ecosystem dynamics

    Science.gov (United States)

    Rupert Seidl; Werner Rammer; Robert M. Scheller; Thomas Spies

    2012-01-01

    Forest ecosystem dynamics emerges from nonlinear interactions between adaptive biotic agents (i.e., individual trees) and their relationship with a spatially and temporally heterogeneous abiotic environment. Understanding and predicting the dynamics resulting from these complex interactions is crucial for the sustainable stewardship of ecosystems, particularly in the...

  5. An individual-based modeling approach to simulating recreation use in wilderness settings

    Science.gov (United States)

    Randy Gimblett; Terry Daniel; Michael J. Meitner

    2000-01-01

    Landscapes protect biological diversity and provide unique opportunities for human-nature interactions. Too often, these desirable settings suffer from extremely high visitation. Given the complexity of social, environmental and economic interactions, resource managers need tools that provide insights into the cause and effect relationships between management actions...

  6. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    KAUST Repository

    Matsumoto, Tomotaka; Mineta, Katsuhiko; Osada, Naoki; Araki, Hitoshi

    2015-01-01

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics

  7. INDIVIDUAL BASED MODELLING APPROACH TO THERMAL REFUGE USE BY MIGRATING ADULT SALMON AND STEELHEAD

    Science.gov (United States)

    Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating ...

  8. PISCATOR, an individual-based model to analyze the dynamics of lake fish communities

    NARCIS (Netherlands)

    Nes, van E.H.; Lammens, E.H.R.R.; Scheffer, M.

    2002-01-01

    Unraveling the mechanisms that drive dynamics of multi-species fish communities is notoriously difficult. Not only are the interactions between fish populations complex, but also the functional niche of individual animals changes profoundly as they grow, making variation in size within populations

  9. Sources and delivery of carbon, nitrogen, and phosphorus to the coastal zone: An overview of global Nutrient Export from Watersheds (NEWS) models and their application

    NARCIS (Netherlands)

    Seitzinger, S.P.; Harrison, J.A.; Dumont, E.L.; Beusen, A.H.W.; Bouwman, A.F.

    2005-01-01

    An overview of the first spatially explicit, multielement (N, P, and C), multiform (dissolved inorganic: DIN, DIP; dissolved organic: DOC, DON, DOP; and particulate: POC, PN, PP) predictive model system of river nutrient export from watersheds (Global Nutrient Export from Watersheds (NEWS)) is

  10. Moving forward socio-economically focused models of deforestation

    OpenAIRE

    DEZÉCACHE CAMILLE; SALLES JEAN-MICHEL; VIEILLEDENT GHISLAIN; HÉRAULT BRUNO

    2017-01-01

    While high resolution spatial variables contribute to a good fit of spatially-explicit deforestation models, socio-economic processes are often beyond the scope of these models. Such a low level of interest in the socio-economic dimension of deforestation limits the relevancy of these models for decision making and may be the cause of their failure to accurately predict observed deforestation trends in the medium term. This study aims to propose a flexible methodology for taking into account ...

  11. Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes

    Science.gov (United States)

    Wiens, J. David; Schumaker, Nathan H.; Inman, Richard D.; Esque, Todd C.; Longshore, Kathleen M.; Nussear, Kenneth E

    2017-01-01

    Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land use and anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (Aquila chrysaetos). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, U.S.A. We developed a spatially explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire prey resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative effects. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative effects of proposed management options to Golden Eagles and their habitats.

  12. An individual-based approach to explain plasmid invasion in bacterial populations

    DEFF Research Database (Denmark)

    Seoane, Jose Miguel; Yankelevich, Tatiana; Dechesne, Arnaud

    2011-01-01

    We present an individual-based experimental framework to identify and estimate the main parameters governing bacterial conjugation at the individual cell scale. From this analysis, we have established that transient periods of unregulated plasmid transfer within newly formed transconjugant cells...... of the growth cycle and that nongrowing cells, even when exposed to high nutrient concentrations, do not display conjugal activity. These results do not support previous hypotheses relating conjugation decay in the deeper cell layers of bacterial biofilms to nutrient depletion and low physiological activity. We...

  13. Turing patterns and long-time behavior in a three-species food-chain model

    KAUST Repository

    Parshad, Rana D.

    2014-08-01

    We consider a spatially explicit three-species food chain model, describing generalist top predator-specialist middle predator-prey dynamics. We investigate the long-time dynamics of the model and show the existence of a finite dimensional global attractor in the product space, L2(Ω). We perform linear stability analysis and show that the model exhibits the phenomenon of Turing instability, as well as diffusion induced chaos. Various Turing patterns such as stripe patterns, mesh patterns, spot patterns, labyrinth patterns and weaving patterns are obtained, via numerical simulations in 1d as well as in 2d. The Turing and non-Turing space, in terms of model parameters, is also explored. Finally, we use methods from nonlinear time series analysis to reconstruct a low dimensional chaotic attractor of the model, and estimate its fractal dimension. This provides a lower bound, for the fractal dimension of the attractor, of the spatially explicit model. © 2014 Elsevier Inc.

  14. A validated agent-based model to study the spatial and temporal heterogeneities of malaria incidence in the rainforest environment.

    Science.gov (United States)

    Pizzitutti, Francesco; Pan, William; Barbieri, Alisson; Miranda, J Jaime; Feingold, Beth; Guedes, Gilvan R; Alarcon-Valenzuela, Javiera; Mena, Carlos F

    2015-12-22

    The Amazon environment has been exposed in the last decades to radical changes that have been accompanied by a remarkable rise of both Plasmodium falciparum and Plasmodium vivax malaria. The malaria transmission process is highly influenced by factors such as spatial and temporal heterogeneities of the environment and individual-based characteristics of mosquitoes and humans populations. All these determinant factors can be simulated effectively trough agent-based models. This paper presents a validated agent-based model of local-scale malaria transmission. The model reproduces the environment of a typical riverine village in the northern Peruvian Amazon, where the malaria transmission is highly seasonal and apparently associated with flooding of large areas caused by the neighbouring river. Agents representing humans, mosquitoes and the two species of Plasmodium (P. falciparum and P. vivax) are simulated in a spatially explicit representation of the environment around the village. The model environment includes: climate, people houses positions and elevation. A representation of changes in the mosquito breeding areas extension caused by the river flooding is also included in the simulation environment. A calibration process was carried out to reproduce the variations of the malaria monthly incidence over a period of 3 years. The calibrated model is also able to reproduce the spatial heterogeneities of local scale malaria transmission. A "what if" eradication strategy scenario is proposed: if the mosquito breeding sites are eliminated through mosquito larva habitat management in a buffer area extended at least 200 m around the village, the malaria transmission is eradicated from the village. The use of agent-based models can reproduce effectively the spatiotemporal variations of the malaria transmission in a low endemicity environment dominated by river floodings like in the Amazon.

  15. Modeling spatial patterns of plant distribution as a consequence of hydrological dynamic processes in a Venezuelan flooding savanna = Modelo espacial de distribución de plantas como consecuencia de la dinámica hidrológica en una sabana inundable Venezolana

    NARCIS (Netherlands)

    Chacón-Moreno, E.J.; Smith, J.K.; Skidmore, A.K.; Prins, H.H.T.; Toxopeus, A.G.

    2007-01-01

    This study presents the main results of the analysis and integration of ecological ordination and spatially explicit relationships into an ecological-spatial model. This allows understanding, evaluating and predicting the distribution of dominant plant species in a changing flooding savanna

  16. Individual-based versus aggregate meta-analysis in multi-database studies of pregnancy outcomes

    DEFF Research Database (Denmark)

    Selmer, Randi; Haglund, Bengt; Furu, Kari

    2016-01-01

    Purpose: Compare analyses of a pooled data set on the individual level with aggregate meta-analysis in a multi-database study. Methods: We reanalysed data on 2.3 million births in a Nordic register based cohort study. We compared estimated odds ratios (OR) for the effect of selective serotonin...... covariates in the pooled data set, and 1.53 (1.19–1.96) after country-optimized adjustment. Country-specific adjusted analyses at the substance level were not possible for RVOTO. Conclusion: Results of fixed effects meta-analysis and individual-based analyses of a pooled dataset were similar in this study...... reuptake inhibitors (SSRI) and venlafaxine use in pregnancy on any cardiovascular birth defect and the rare outcome right ventricular outflow tract obstructions (RVOTO). Common covariates included maternal age, calendar year, birth order, maternal diabetes, and co-medication. Additional covariates were...

  17. Individual-based ant-plant networks: diurnal-nocturnal structure and species-area relationship.

    Directory of Open Access Journals (Sweden)

    Wesley Dáttilo

    Full Text Available Despite the importance and increasing knowledge of ecological networks, sampling effort and intrapopulation variation has been widely overlooked. Using continuous daily sampling of ants visiting three plant species in the Brazilian Neotropical savanna, we evaluated for the first time the topological structure over 24 h and species-area relationships (based on the number of extrafloral nectaries available in individual-based ant-plant networks. We observed that diurnal and nocturnal ant-plant networks exhibited the same pattern of interactions: a nested and non-modular pattern and an average level of network specialization. Despite the high similarity in the ants' composition between the two collection periods, ant species found in the central core of highly interacting species totally changed between diurnal and nocturnal sampling for all plant species. In other words, this "night-turnover" suggests that the ecological dynamics of these ant-plant interactions can be temporally partitioned (day and night at a small spatial scale. Thus, it is possible that in some cases processes shaping mutualistic networks formed by protective ants and plants may be underestimated by diurnal sampling alone. Moreover, we did not observe any effect of the number of extrafloral nectaries on ant richness and their foraging on such plants in any of the studied ant-plant networks. We hypothesize that competitively superior ants could monopolize individual plants and allow the coexistence of only a few other ant species, however, other alternative hypotheses are also discussed. Thus, sampling period and species-area relationship produces basic information that increases our confidence in how individual-based ant-plant networks are structured, and the need to consider nocturnal records in ant-plant network sampling design so as to decrease inappropriate inferences.

  18. Modelling parasite transmission in a grazing system: the importance of host behaviour and immunity.

    Directory of Open Access Journals (Sweden)

    Naomi J Fox

    Full Text Available Parasitic helminths present one of the most pervasive challenges to grazing herbivores. Many macro-parasite transmission models focus on host physiological defence strategies, omitting more complex interactions between hosts and their environments. This work represents the first model that integrates both the behavioural and physiological elements of gastro-intestinal nematode transmission dynamics in a managed grazing system. A spatially explicit, individual-based, stochastic model is developed, that incorporates both the hosts' immunological responses to parasitism, and key grazing behaviours including faecal avoidance. The results demonstrate that grazing behaviour affects both the timing and intensity of parasite outbreaks, through generating spatial heterogeneity in parasite risk and nutritional resources, and changing the timing of exposure to the parasites' free-living stages. The influence of grazing behaviour varies with the host-parasite combination, dependent on the development times of different parasite species and variations in host immune response. Our outputs include the counterintuitive finding that under certain conditions perceived parasite avoidance behaviours (faecal avoidance can increase parasite risk, for certain host-parasite combinations. Through incorporating the two-way interaction between infection dynamics and grazing behaviour, the potential benefits of parasite-induced anorexia are also demonstrated. Hosts with phenotypic plasticity in grazing behaviour, that make grazing decisions dependent on current parasite burden, can reduce infection with minimal loss of intake over the grazing season. This paper explores how both host behaviours and immunity influence macro-parasite transmission in a spatially and temporally heterogeneous environment. The magnitude and timing of parasite outbreaks is influenced by host immunity and behaviour, and the interactions between them; the incorporation of both regulatory processes

  19. Cultural ecosystem services of mountain regions: Modelling the aesthetic value

    OpenAIRE

    Schirpke, Uta; Timmermann, Florian; Tappeiner, Ulrike; Tasser, Erich

    2016-01-01

    Mountain regions meet an increasing demand for pleasant landscapes, offering many cultural ecosystem services to both their residents and tourists. As a result of global change, land managers and policy makers are faced with changes to this landscape and need efficient evaluation techniques to assess cultural ecosystem services. This study provides a spatially explicit modelling approach to estimating aesthetic landscape values by relating spatial landscape patterns to human perceptions via a...

  20. Individual-based analyses reveal limited functional overlap in a coral reef fish community.

    Science.gov (United States)

    Brandl, Simon J; Bellwood, David R

    2014-05-01

    Detailed knowledge of a species' functional niche is crucial for the study of ecological communities and processes. The extent of niche overlap, functional redundancy and functional complementarity is of particular importance if we are to understand ecosystem processes and their vulnerability to disturbances. Coral reefs are among the most threatened marine systems, and anthropogenic activity is changing the functional composition of reefs. The loss of herbivorous fishes is particularly concerning as the removal of algae is crucial for the growth and survival of corals. Yet, the foraging patterns of the various herbivorous fish species are poorly understood. Using a multidimensional framework, we present novel individual-based analyses of species' realized functional niches, which we apply to a herbivorous coral reef fish community. In calculating niche volumes for 21 species, based on their microhabitat utilization patterns during foraging, and computing functional overlaps, we provide a measurement of functional redundancy or complementarity. Complementarity is the inverse of redundancy and is defined as less than 50% overlap in niche volumes. The analyses reveal extensive complementarity with an average functional overlap of just 15.2%. Furthermore, the analyses divide herbivorous reef fishes into two broad groups. The first group (predominantly surgeonfishes and parrotfishes) comprises species feeding on exposed surfaces and predominantly open reef matrix or sandy substrata, resulting in small niche volumes and extensive complementarity. In contrast, the second group consists of species (predominantly rabbitfishes) that feed over a wider range of microhabitats, penetrating the reef matrix to exploit concealed surfaces of various substratum types. These species show high variation among individuals, leading to large niche volumes, more overlap and less complementarity. These results may have crucial consequences for our understanding of herbivorous processes on

  1. Modelling climate change effects on Atlantic salmon: Implications for mitigation in regulated rivers.

    Science.gov (United States)

    Sundt-Hansen, L E; Hedger, R D; Ugedal, O; Diserud, O H; Finstad, A G; Sauterleute, J F; Tøfte, L; Alfredsen, K; Forseth, T

    2018-08-01

    Climate change is expected to alter future temperature and discharge regimes of rivers. These regimes have a strong influence on the life history of most aquatic river species, and are key variables controlling the growth and survival of Atlantic salmon. This study explores how the future abundance of Atlantic salmon may be influenced by climate-induced changes in water temperature and discharge in a regulated river, and investigates how negative impacts in the future can be mitigated by applying different regulated discharge regimes during critical periods for salmon survival. A spatially explicit individual-based model was used to predict juvenile Atlantic salmon population abundance in a regulated river under a range of future water temperature and discharge scenarios (derived from climate data predicted by the Hadley Centre's Global Climate Model (GCM) HadAm3H and the Max Plank Institute's GCM ECHAM4), which were then compared with populations predicted under control scenarios representing past conditions. Parr abundance decreased in all future scenarios compared to the control scenarios due to reduced wetted areas (with the effect depending on climate scenario, GCM, and GCM spatial domain). To examine the potential for mitigation of climate change-induced reductions in wetted area, simulations were run with specific minimum discharge regimes. An increase in abundance of both parr and smolt occurred with an increase in the limit of minimum permitted discharge for three of the four GCM/GCM spatial domains examined. This study shows that, in regulated rivers with upstream storage capacity, negative effects of climate change on Atlantic salmon populations can potentially be mitigated by release of water from reservoirs during critical periods for juvenile salmon. Copyright © 2018. Published by Elsevier B.V.

  2. Modelling cholera epidemics: the role of waterways, human mobility and sanitation

    OpenAIRE

    Mari, L.; Bertuzzo, E.; Righetto, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2011-01-01

    We investigate the role of human mobility as a driver for long-range spreading of cholera infections, which primarily propagate through hydrologically controlled ecological corridors. Our aim is to build a spatially explicit model of a disease epidemic, which is relevant to both social and scientific issues. We present a two-layer network model that accounts for the interplay between epidemiological dynamics, hydrological transport and long-distance dissemination of the pathogen Vibrio choler...

  3. A pilot study combining individual-based smoking cessation counseling, pharmacotherapy, and dental hygiene intervention

    Directory of Open Access Journals (Sweden)

    Madrid Carlos

    2010-06-01

    Full Text Available Abstract Background Dentists are in a unique position to advise smokers to quit by providing effective counseling on the various aspects of tobacco-induced diseases. The present study assessed the feasibility and acceptability of integrating dentists in a medical smoking cessation intervention. Methods Smokers willing to quit underwent an 8-week smoking cessation intervention combining individual-based counseling and nicotine replacement therapy and/or bupropion, provided by a general internist. In addition, a dentist performed a dental exam, followed by an oral hygiene treatment and gave information about chronic effects of smoking on oral health. Outcomes were acceptability, global satisfaction of the dentist's intervention, and smoking abstinence at 6-month. Results 39 adult smokers were included, and 27 (69% completed the study. Global acceptability of the dental intervention was very high (94% yes, 6% mostly yes. Annoyances at the dental exam were described as acceptable by participants (61% yes, 23% mostly yes, 6%, mostly no, 10% no. Participants provided very positive qualitative comments about the dentist counseling, the oral exam, and the resulting motivational effect, emphasizing the feeling of oral cleanliness and health that encouraged smoking abstinence. At the end of the intervention (week 8, 17 (44% participants reported smoking abstinence. After 6 months, 6 (15%, 95% CI 3.5 to 27.2 reported a confirmed continuous smoking abstinence. Discussion We explored a new multi-disciplinary approach to smoking cessation, which included medical and dental interventions. Despite the small sample size and non-controlled study design, the observed rate was similar to that found in standard medical care. In terms of acceptability and feasibility, our results support further investigations in this field. Trial Registration number ISRCTN67470159

  4. Simulating natural selection in landscape genetics

    Science.gov (United States)

    E. L. Landguth; S. A. Cushman; N. Johnson

    2012-01-01

    Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially- explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal...

  5. Characterization of waterborne nitrogen emissions for marine eutrophication modelling in life cycle impact assessment at the damage level and global scale

    DEFF Research Database (Denmark)

    Cosme, Nuno Miguel Dias; Hauschild, Michael Zwicky

    2017-01-01

    Current life cycle impact assessment (LCIA) methods lack a consistent and globally applicable characterization model relating nitrogen (N, as dissolved inorganic nitrogen, DIN) enrichment of coastal waters to the marine eutrophication impacts at the endpoint level. This paper introduces a method...... to calculate spatially explicit characterization factors (CFs) at endpoint and damage to ecosystems levels, for waterborne nitrogen emissions, reflecting their hypoxia-related marine eutrophication impacts, modelled for 5772 river basins of the world....

  6. Scale dependent inference in landscape genetics

    Science.gov (United States)

    Samuel A. Cushman; Erin L. Landguth

    2010-01-01

    Ecological relationships between patterns and processes are highly scale dependent. This paper reports the first formal exploration of how changing scale of research away from the scale of the processes governing gene flow affects the results of landscape genetic analysis. We used an individual-based, spatially explicit simulation model to generate patterns of genetic...

  7. Latent spatial models and sampling design for landscape genetics

    Science.gov (United States)

    Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

    2016-01-01

    We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  8. Evaluating Effects of Pump-Storage Water Withdrawals Using an Individual-Based Metapopulation Model of a Benthic Fish Species

    Science.gov (United States)

    2011-04-01

    Bunn S. E. and Arthington A.H. 2002. Basic principles and ecological consequences of altered flow regimes on aquatic biodiversity . Environmental...cycling in streams: can fish create biogeochemical hotspots ? Ecology 89: 2335-2346. Matthews W.J. and Marsh-Matthews E. 2003. Effects of drought on

  9. The role of ocean currents in the temperature selection of plankton : Insights from an individual-based model

    NARCIS (Netherlands)

    Hellweger, Ferdi L.; Van Sebille, Erik; Calfee, Benjamin C.; Chandler, Jeremy W.; Zinser, Erik R.; Swan, Brandon K.; Fredrick, Neil D.

    2016-01-01

    Biogeography studies that correlate the observed distribution of organisms to environmental variables are typically based on local conditions. However, in cases with substantial translocation, like planktonic organisms carried by ocean currents, selection may happen upstream and local environmental

  10. A spatially and temporally explicit, individual-based, life-history and productivity modeling approach for aquatic species

    Science.gov (United States)

    Realized life history expression and productivity in aquatic species, and salmonid fishes in particular, is the result of multiple interacting factors including genetics, habitat, growth potential and condition, and the thermal regime individuals experience, both at critical stag...

  11. Population-level consequences of spatially heterogeneous exposure to heavy metals in soil: An individual-based model of springtails

    DEFF Research Database (Denmark)

    Meli, Mattia; Auclerc, Apolline; Palmqvist, Annemette

    2013-01-01

    Contamination of soil with toxic heavy metals poses a major threat to the environment and human health. Anthropogenic sources include smelting of ores, municipal wastes, fertilizers, and pesticides. In assessing soil quality and the environmental and ecological risk of contamination with heavy...... metals, often homogeneous contamination of the soil is assumed. However, soils are very heterogeneous environments. Consequently, both contamination and the response of soil organisms can be assumed to be heterogeneous. This might have consequences for the exposure of soil organisms...

  12. An example of population-level risk assessments for small mammals using individual-based population models

    DEFF Research Database (Denmark)

    Schmitt, Walter; Auteri, Domenica; Bastiansen, Finn

    2016-01-01

    effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report...... assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios....

  13. Advances and limitations of individual-based models to analyze and predict dynamics of mangrove forests : A review

    NARCIS (Netherlands)

    Berger, Uta; Rivera-Monroy, Victor H.; Doyle, Thomas W.; Dahdouh-Guebas, Farid; Duke, Norman C.; Fontalvo-Herazo, Martha L.; Hildenbrandt, Hanno; Koedam, Nico; Mehlig, Ulf; Piou, Cyril; Twilley, Robert R.

    Mangrove ecosystems are considered vulnerable to climate change as coastal development limits the ecosystem services and adaptations important to their survival. Although they appear rather simple in terms of species diversity, their ecology is complex due to interacting geophysical forces of tides,

  14. Population viability and reintroduction strategies: a spatially explicit landscape-level approach

    Czech Academy of Sciences Publication Activity Database

    Münzbergová, Zuzana; Mildén, M.; Ehrlén, J.; Herben, Tomáš

    2005-01-01

    Roč. 15, č. 4 (2005), s. 1377-1386 ISSN 1051-0761 R&D Projects: GA ČR(CZ) GD206/03/H137; GA ČR(CZ) GA206/02/0590 Institutional research plan: CEZ:AV0Z60050516 Keywords : extinction threshold * habitat fragmentation * metapopulation capacity Subject RIV: EF - Botanics Impact factor: 3.804, year: 2005

  15. Spatially explicit scenario analysis for hydrologic services in an urbanizing agricultural watershed

    Science.gov (United States)

    Qiu, J.; Booth, E.; Carpenter, S. R.; Turner, M.

    2013-12-01

    The sustainability of hydrologic services (benefits to people generated by terrestrial ecosystem effects on freshwater) is challenged by changes in climate and land use. Despite the importance of hydrologic services, few studies have investigated how the provision of ecosystem services related to freshwater quantity and quality may vary in magnitude and spatial pattern for alternative future trajectories. Such analyses may provide useful information for sustaining freshwater resources in the face of a complex and uncertain future. We analyzed the supply of multiple hydrologic services from 2010 to 2070 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) What are the potential trajectories for the supply of hydrologic services under contrasting but plausible future scenarios? (ii) Where on the landscape is the delivery of hydrologic services most vulnerable to future changes? The Nested Watershed scenario represents extreme climate change (warmer temperatures and more frequent extreme events) and a concerted response from institutions, whereas in the Investment in Innovation scenario, climate change is less severe and technological innovations play a major role. Despite more extreme climate in the Nested Watershed scenario, all hydrologic services (i.e., freshwater supply, surface water quality, flood regulation) were maintained or enhanced (~30%) compared to the 2010 baseline, by strict government interventions that prioritized freshwater resources. Despite less extreme climate in the Investment in Innovation scenario and advances in green technology, only surface water quality and flood regulation were maintained or increased (~80%); freshwater supply declined by 25%, indicating a potential future tradeoff between water quality and quantity. Spatially, the locations of greatest vulnerability (i.e., decline) differed by service and among scenarios. In the Nested Watershed scenario, although freshwater supply and surface water quality were sustained or enhanced overall, these hydrologic services declined in ~60% and 20% of the landscape, respectively. The greatest improvement for most hydrologic services corresponded to areas of restored wetland, forest and perennial crops, which were less vulnerable to future degradation. In the Investment in Innovation scenario, freshwater supply declined in almost the entire watershed; improvement of surface water quality and flood regulation occurred mainly in urban areas, where highly engineered systems made them less vulnerable. Overall, our results indicated that hydrologic services will respond differently to future climate and land-use change, and sustaining one may involve tradeoffs of another. Technological progress can conserve particular services but might not be the panacea for the future. How society reacts in the face of changes can have an important role in determining the pathways to the future and the provision and spatial patterns of ecosystem services.

  16. Assessing Sustainability of Coral Reef Ecosystem Services using a Spatially-Explicit Decision Support Tool

    Science.gov (United States)

    Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...

  17. EnviroAtlas: A Spatially Explicit Tool Combining Climate Change Scenarios with Ecosystem Services Indicators

    Science.gov (United States)

    While discussions of global climate change tend to center on greenhouse gases and seal level rise, other factors, such as technological developments, land and energy use, economics, and population growth all play a critical role in understanding climate change. There is increasi...

  18. EnviroAtlas: A Spatially Explicit Tool Combining Climate Change Scenarios and Ecosystem ServicesIndicators

    Science.gov (United States)

    While discussions of global climate change tend to center on greenhouse gases and sea level rise, other factors, such as technological developments, land and energy use, economics, and population growth all play a critical role in understanding climate change. There is increasin...

  19. Spatially explicit simulation of peatland hydrology and carbon dioxide exchange: Influence of mesoscale topography

    Science.gov (United States)

    Sonnentag, O.; Chen, J. M.; Roulet, N. T.; Ju, W.; Govind, A.

    2008-06-01

    Carbon dynamics in peatlands are controlled, in large part, by their wetness as defined by water table depth and volumetric liquid soil moisture content. A common type of peatland is raised bogs that typically have a multiple-layer canopy of vascular plants over a Sphagnum moss ground cover. Their convex form restricts water supply to precipitation and water is shed toward the margins, usually by lateral subsurface flow. The hydraulic gradient for lateral subsurface flow is governed by the peat surface topography at the mesoscale (˜200 m to 5 km). To investigate the influence of mesoscale topography on wetness, evapotranspiration (ET), and gross primary productivity (GPP) in a bog during the snow-free period, we compare the outputs of a further developed version of the daily Boreal Ecosystem Productivity Simulator (BEPS) with observations made at the Mer Bleue peatland, located near Ottawa, Canada. Explicitly considering mesoscale topography, simulated total ET and GPP correlate well with measured ET (r = 0.91) and derived gross ecosystem productivity (GEP; r = 0.92). Both measured ET and derived GEP are simulated similarly well when mesoscale topography is neglected, but daily simulated values are systematically underestimated by about 10% and 12% on average, respectively, due to greater wetness resulting from the lack of lateral subsurface flow. Owing to the differences in moss surface conductances of water vapor and carbon dioxide with increasing moss water content, the differences in the spatial patterns of simulated total ET and GPP are controlled by the mesotopographic position of the moss ground cover.

  20. Spatially explicit analysis of land use change : a case study for Ecuador

    NARCIS (Netherlands)

    Koning, de F.

    1999-01-01

    Introduction and objectives

    Within agricultural research increasing attention is paid to the integrated study of agro-ecosystems in order to address issues related to sustainable food production at the eco-regional level. This has been stimulated by

  1. European vulnerability to global change: a spatially explicit and quantitative assessment

    NARCIS (Netherlands)

    Metzger, M.J.

    2005-01-01

    Many aspects of our planet are changing rapidly because of to human activities and these changes are expected to accelerate during the next decades. For example, forest area in the tropics is declining, many species are threatened with extinction, and rising atmospheric carbon dioxide results in

  2. The shift from plant-plant facilitation to competition under severe water deficit is spatially explicit.

    Science.gov (United States)

    O'Brien, Michael J; Pugnaire, Francisco I; Armas, Cristina; Rodríguez-Echeverría, Susana; Schöb, Christian

    2017-04-01

    The stress-gradient hypothesis predicts a higher frequency of facilitative interactions as resource limitation increases. Under severe resource limitation, it has been suggested that facilitation may revert to competition, and identifying the presence as well as determining the magnitude of this shift is important for predicting the effect of climate change on biodiversity and plant community dynamics. In this study, we perform a meta-analysis to compare temporal differences of species diversity and productivity under a nurse plant ( Retama sphaerocarpa ) with varying annual rainfall quantity to test the effect of water limitation on facilitation. Furthermore, we assess spatial differences in the herbaceous community under nurse plants in situ during a year with below-average rainfall. We found evidence that severe rainfall deficit reduced species diversity and plant productivity under nurse plants relative to open areas. Our results indicate that the switch from facilitation to competition in response to rainfall quantity is nonlinear. The magnitude of this switch depended on the aspect around the nurse plant. Hotter south aspects under nurse plants resulted in negative effects on beneficiary species, while the north aspect still showed facilitation. Combined, these results emphasize the importance of spatial heterogeneity under nurse plants for mediating species loss under reduced precipitation, as predicted by future climate change scenarios. However, the decreased water availability expected under climate change will likely reduce overall facilitation and limit the role of nurse plants as refugia, amplifying biodiversity loss.

  3. The need for spatially explicit quantification of benefits in invasive-species management.

    Science.gov (United States)

    Januchowski-Hartley, Stephanie R; Adams, Vanessa M; Hermoso, Virgilio

    2018-04-01

    Worldwide, invasive species are a leading driver of environmental change across terrestrial, marine, and freshwater environments and cost billions of dollars annually in ecological damages and economic losses. Resources limit invasive-species control, and planning processes are needed to identify cost-effective solutions. Thus, studies are increasingly considering spatially variable natural and socioeconomic assets (e.g., species persistence, recreational fishing) when planning the allocation of actions for invasive-species management. There is a need to improve understanding of how such assets are considered in invasive-species management. We reviewed over 1600 studies focused on management of invasive species, including flora and fauna. Eighty-four of these studies were included in our final analysis because they focused on the prioritization of actions for invasive species management. Forty-five percent (n = 38) of these studies were based on spatial optimization methods, and 35% (n = 13) accounted for spatially variable assets. Across all 84 optimization studies considered, 27% (n = 23) explicitly accounted for spatially variable assets. Based on our findings, we further explored the potential costs and benefits to invasive species management when spatially variable assets are explicitly considered or not. To include spatially variable assets in decision-making processes that guide invasive-species management there is a need to quantify environmental responses to invasive species and to enhance understanding of potential impacts of invasive species on different natural or socioeconomic assets. We suggest these gaps could be filled by systematic reviews, quantifying invasive species impacts on native species at different periods, and broadening sources and enhancing sharing of knowledge. © 2017 Society for Conservation Biology.

  4. Developing and testing a global-scale regression model to quantify mean annual streamflow

    Science.gov (United States)

    Barbarossa, Valerio; Huijbregts, Mark A. J.; Hendriks, A. Jan; Beusen, Arthur H. W.; Clavreul, Julie; King, Henry; Schipper, Aafke M.

    2017-01-01

    Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 106 km2. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area and catchment averaged mean annual precipitation and air temperature, slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error (RMSE) values were lower (0.29-0.38 compared to 0.49-0.57) and the modified index of agreement (d) was higher (0.80-0.83 compared to 0.72-0.75). Our regression model can be applied globally to estimate MAF at any point of the river network, thus providing a feasible alternative to spatially explicit process-based global hydrological models.

  5. Travelling Waves in Hybrid Chemotaxis Models

    KAUST Repository

    Franz, Benjamin; Xue, Chuan; Painter, Kevin J.; Erban, Radek

    2013-01-01

    . Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death

  6. Tropical forest fragmentation affects floral visitors but not the structure of individual-based palm-pollinator networks.

    Science.gov (United States)

    Dáttilo, Wesley; Aguirre, Armando; Quesada, Mauricio; Dirzo, Rodolfo

    2015-01-01

    Despite increasing knowledge about the effects of habitat loss on pollinators in natural landscapes, information is very limited regarding the underlying mechanisms of forest fragmentation affecting plant-pollinator interactions in such landscapes. Here, we used a network approach to describe the effects of forest fragmentation on the patterns of interactions involving the understory dominant palm Astrocaryum mexicanum (Arecaceae) and its floral visitors (including both effective and non-effective pollinators) at the individual level in a Mexican tropical rainforest landscape. Specifically, we asked: (i) Does fragment size affect the structure of individual-based plant-pollinator networks? (ii) Does the core of highly interacting visitor species change along the fragmentation size gradient? (iii) Does forest fragment size influence the abundance of effective pollinators of A. mexicanum? We found that fragment size did not affect the topological structure of the individual-based palm-pollinator network. Furthermore, while the composition of peripheral non-effective pollinators changed depending on fragment size, effective core generalist species of pollinators remained stable. We also observed that both abundance and variance of effective pollinators of male and female flowers of A. mexicanum increased with forest fragment size. These findings indicate that the presence of effective pollinators in the core of all forest fragments could keep the network structure stable along the gradient of forest fragmentation. In addition, pollination of A. mexicanum could be more effective in larger fragments, since the greater abundance of pollinators in these fragments may increase the amount of pollen and diversity of pollen donors between flowers of individual plants. Given the prevalence of fragmentation in tropical ecosystems, our results indicate that the current patterns of land use will have consequences on the underlying mechanisms of pollination in remnant forests.

  7. Tropical forest fragmentation affects floral visitors but not the structure of individual-based palm-pollinator networks.

    Directory of Open Access Journals (Sweden)

    Wesley Dáttilo

    Full Text Available Despite increasing knowledge about the effects of habitat loss on pollinators in natural landscapes, information is very limited regarding the underlying mechanisms of forest fragmentation affecting plant-pollinator interactions in such landscapes. Here, we used a network approach to describe the effects of forest fragmentation on the patterns of interactions involving the understory dominant palm Astrocaryum mexicanum (Arecaceae and its floral visitors (including both effective and non-effective pollinators at the individual level in a Mexican tropical rainforest landscape. Specifically, we asked: (i Does fragment size affect the structure of individual-based plant-pollinator networks? (ii Does the core of highly interacting visitor species change along the fragmentation size gradient? (iii Does forest fragment size influence the abundance of effective pollinators of A. mexicanum? We found that fragment size did not affect the topological structure of the individual-based palm-pollinator network. Furthermore, while the composition of peripheral non-effective pollinators changed depending on fragment size, effective core generalist species of pollinators remained stable. We also observed that both abundance and variance of effective pollinators of male and female flowers of A. mexicanum increased with forest fragment size. These findings indicate that the presence of effective pollinators in the core of all forest fragments could keep the network structure stable along the gradient of forest fragmentation. In addition, pollination of A. mexicanum could be more effective in larger fragments, since the greater abundance of pollinators in these fragments may increase the amount of pollen and diversity of pollen donors between flowers of individual plants. Given the prevalence of fragmentation in tropical ecosystems, our results indicate that the current patterns of land use will have consequences on the underlying mechanisms of pollination in

  8. Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

    Directory of Open Access Journals (Sweden)

    Laura Alfonsina Chang-Martínez

    2015-09-01

    Full Text Available Spatially-explicit land cover land use change (LCLUC models are becoming increasingly useful tools for historians and archaeologists. Such kinds of models have been developed and used by geographers, ecologists and land managers over the last few decades to carry out prospective scenarios. In this paper, we review historical models to compare them with prospective models, with the assumption that the ample experience gained in the development of models of prospective simulation can benefit the development of models having as their objective the simulation of changes that happened in the past. The review is divided into three sections: in the first section, we explain the functioning of contemporary LCLUC models; in the second section, we analyze historical LCLUC models; in the third section, we compare the former two types of models, and finally, we discuss the contributions to historical LCLUC models of contemporary LCLUC models.

  9. Rapid Response Tools and Datasets for Post-fire Hydrological Modeling

    Science.gov (United States)

    Miller, Mary Ellen; MacDonald, Lee H.; Billmire, Michael; Elliot, William J.; Robichaud, Pete R.

    2016-04-01

    Rapid response is critical following natural disasters. Flooding, erosion, and debris flows are a major threat to life, property and municipal water supplies after moderate and high severity wildfires. The problem is that mitigation measures must be rapidly implemented if they are to be effective, but they are expensive and cannot be applied everywhere. Fires, runoff, and erosion risks also are highly heterogeneous in space, so there is an urgent need for a rapid, spatially-explicit assessment. Past post-fire modeling efforts have usually relied on lumped, conceptual models because of the lack of readily available, spatially-explicit data layers on the key controls of topography, vegetation type, climate, and soil characteristics. The purpose of this project is to develop a set of spatially-explicit data layers for use in process-based models such as WEPP, and to make these data layers freely available. The resulting interactive online modeling database (http://geodjango.mtri.org/geowepp/) is now operational and publically available for 17 western states in the USA. After a fire, users only need to upload a soil burn severity map, and this is combined with the pre-existing data layers to generate the model inputs needed for spatially explicit models such as GeoWEPP (Renschler, 2003). The development of this online database has allowed us to predict post-fire erosion and various remediation scenarios in just 1-7 days for six fires ranging in size from 4-540 km2. These initial successes have stimulated efforts to further improve the spatial extent and amount of data, and add functionality to support the USGS debris flow model, batch processing for Disturbed WEPP (Elliot et al., 2004) and ERMiT (Robichaud et al., 2007), and to support erosion modeling for other land uses, such as agriculture or mining. The design and techniques used to create the database and the modeling interface are readily repeatable for any area or country that has the necessary topography

  10. Modeling the impacts of hunting on the population dynamics of red howler monkeys (Alouatta seniculus)

    Science.gov (United States)

    Wiederholt, Ruscena; Fernandez-Duque, Eduardo; Diefenbach, Duane R.; Rudran, Rasanayagam

    2010-01-01

    Overexploitation of wildlife populations occurs across the humid tropics and is a significant threat to the long-term survival of large-bodied primates. To investigate the impacts of hunting on primates and ways to mitigate them, we developed a spatially explicit, individual-based model for a landscape that included hunted and un-hunted areas. We used the large-bodied neotropical red howler monkey (Alouatta seniculus) as our case study species because its life history characteristics make it vulnerable to hunting. We modeled the influence of different rates of harvest and proportions of landscape dedicated to un-hunted reserves on population persistence, population size, social dynamics, and hunting yields of red howler monkeys. In most scenarios, the un-hunted populations maintained a constant density regardless of hunting pressure elsewhere, and allowed the overall population to persist. Therefore, the overall population was quite resilient to extinction; only in scenarios without any un-hunted areas did the population go extinct. However, the total and hunted populations did experience large declines over 100 years under moderate and high hunting pressure. In addition, when reserve area decreased, population losses and losses per unit area increased disproportionately. Furthermore, hunting disrupted the social structure of troops. The number of male turnovers and infanticides increased in hunted populations, while birth rates decreased and exacerbated population losses due to hunting. Finally, our results indicated that when more than 55% of the landscape was harvested at high (30%) rates, hunting yields, as measured by kilograms of biomass, were less than those obtained from moderate harvest rates. Additionally, hunting yields, expressed as the number of individuals hunted/year/km2, increased in proximity to un-hunted areas, and suggested that dispersal from un-hunted areas may have contributed to hunting sustainability. These results indicate that un

  11. Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

    Science.gov (United States)

    Alexandridis, Konstantinos T.

    This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land

  12. Modelling spatial and temporal dynamics of gross primary production in the Sahel from earth-observation-based photosynthetic capacity and quantum efficiency

    DEFF Research Database (Denmark)

    Tagesson, Håkan Torbern; Ardoe, Jonas; Cappelaere, Bernard

    2017-01-01

    based on earth observation (EO) (normalized difference vegetation index (NDVI), renormalized difference vegetation index (RDVI), enhanced vegetation index (EVI) and shortwave infrared water stress index (SIWSI)); and (3) to study the applicability of EO upscaled Fopt and α for GPP modelling purposes...... impacted by anthropogenic land use. Upscaled GPP for the Sahel 2001-2014 was 736 ± 39 gCm-2yr-1. This study indicates the strong applicability of EO as a tool for spatially explicit estimates of GPP, Fopt and α incorporating EO-based Fopt and α in dynamic global vegetation models could improve estimates...

  13. A spatial model of white sturgeon rearing habitat in the lower Columbia River, USA

    Science.gov (United States)

    Hatten, J.R.; Parsley, M.J.

    2009-01-01

    Concerns over the potential effects of in-water placement of dredged materials prompted us to develop a GIS-based model that characterizes in a spatially explicit manner white sturgeon Acipenser transmontanus rearing habitat in the lower Columbia River, USA. The spatial model was developed using water depth, riverbed slope and roughness, fish positions collected in 2002, and Mahalanobis distance (D2). We created a habitat suitability map by identifying a Mahalanobis distance under which >50% of white sturgeon locations occurred in 2002 (i.e., high-probability habitat). White sturgeon preferred relatively moderate to high water depths, and low to moderate riverbed slope and roughness values. The eigenvectors indicated that riverbed slope and roughness were slightly more important than water depth, but all three variables were important. We estimated the impacts that fill might have on sturgeon habitat by simulating the addition of fill to the thalweg, in 3-m increments, and recomputing Mahalanobis distances. Channel filling simulations revealed that up to 9 m of fill would have little impact on high-probability habitat, but 12 and 15 m of fill resulted in habitat declines of ???12% and ???45%, respectively. This is the first spatially explicit predictive model of white sturgeon rearing habitat in the lower Columbia River, and the first to quantitatively predict the impacts of dredging operations on sturgeon habitat. Future research should consider whether water velocity improves the accuracy and specificity of the model, and to assess its applicability to other areas in the Columbia River.

  14. Analyzing historical land use changes using a Historical Land Use Reconstruction Model: a case study in Zhenlai County, northeastern China

    Science.gov (United States)

    Yang, Yuanyuan; Zhang, Shuwen; Liu, Yansui; Xing, Xiaoshi; de Sherbinin, Alex

    2017-01-01

    Historical land use information is essential to understanding the impact of anthropogenic modification of land use/cover on the temporal dynamics of environmental and ecological issues. However, due to a lack of spatial explicitness, complete thematic details and the conversion types for historical land use changes, the majority of historical land use reconstructions do not sufficiently meet the requirements for an adequate model. Considering these shortcomings, we explored the possibility of constructing a spatially-explicit modeling framework (HLURM: Historical Land Use Reconstruction Model). Then a three-map comparison method was adopted to validate the projected reconstruction map. The reconstruction suggested that the HLURM model performed well in the spatial reconstruction of various land-use categories, and had a higher figure of merit (48.19%) than models used in other case studies. The largest land use/cover type in the study area was determined to be grassland, followed by arable land and wetland. Using the three-map comparison, we noticed that the major discrepancies in land use changes among the three maps were as a result of inconsistencies in the classification of land-use categories during the study period, rather than as a result of the simulation model. PMID:28134342

  15. Ecological Impacts of the Cerro Grande Fire: Predicting Elk Movement and Distribution Patterns in Response to Vegetative Recovery through Simulation Modeling October 2005

    Energy Technology Data Exchange (ETDEWEB)

    Rupp, Susan P. [Texas Tech Univ., Lubbock, TX (United States)

    2005-10-01

    In May 2000, the Cerro Grande Fire burned approximately 17,200 ha in north-central New Mexico as the result of an escaped prescribed burn initiated by Bandelier National Monument. The interaction of large-scale fires, vegetation, and elk is an important management issue, but few studies have addressed the ecological implications of vegetative succession and landscape heterogeneity on ungulate populations following large-scale disturbance events. Primary objectives of this research were to identify elk movement pathways on local and landscape scales, to determine environmental factors that influence elk movement, and to evaluate movement and distribution patterns in relation to spatial and temporal aspects of the Cerro Grande Fire. Data collection and assimilation reflect the collaborative efforts of National Park Service, U.S. Forest Service, and Department of Energy (Los Alamos National Laboratory) personnel. Geographic positioning system (GPS) collars were used to track 54 elk over a period of 3+ years and locational data were incorporated into a multi-layered geographic information system (GIS) for analysis. Preliminary tests of GPS collar accuracy indicated a strong effect of 2D fixes on position acquisition rates (PARs) depending on time of day and season of year. Slope, aspect, elevation, and land cover type affected dilution of precision (DOP) values for both 2D and 3D fixes, although significant relationships varied from positive to negative making it difficult to delineate the mechanism behind significant responses. Two-dimensional fixes accounted for 34% of all successfully acquired locations and may affect results in which those data were used. Overall position acquisition rate was 93.3% and mean DOP values were consistently in the range of 4.0 to 6.0 leading to the conclusion collar accuracy was acceptable for modeling purposes. SAVANNA, a spatially explicit, process-oriented ecosystem model, was used to simulate successional dynamics. Inputs to the

  16. A Computer Model of Insect Traps in a Landscape

    Science.gov (United States)

    Manoukis, Nicholas C.; Hall, Brian; Geib, Scott M.

    2014-11-01

    Attractant-based trap networks are important elements of invasive insect detection, pest control, and basic research programs. We present a landscape-level, spatially explicit model of trap networks, focused on detection, that incorporates variable attractiveness of traps and a movement model for insect dispersion. We describe the model and validate its behavior using field trap data on networks targeting two species, Ceratitis capitata and Anoplophora glabripennis. Our model will assist efforts to optimize trap networks by 1) introducing an accessible and realistic mathematical characterization of the operation of a single trap that lends itself easily to parametrization via field experiments and 2) allowing direct quantification and comparison of sensitivity between trap networks. Results from the two case studies indicate that the relationship between number of traps and their spatial distribution and capture probability under the model is qualitatively dependent on the attractiveness of the traps, a result with important practical consequences.

  17. Modelling and predicting biogeographical patterns in river networks

    Directory of Open Access Journals (Sweden)

    Sabela Lois

    2016-04-01

    Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

  18. A spatially-based modeling framework for assessing the risks of soil-associated metals to bats

    International Nuclear Information System (INIS)

    Hernout, Béatrice V.; Somerwill, Kate E.; Arnold, Kathryn E.; McClean, Colin J.; Boxall, Alistair B.A.

    2013-01-01

    Populations of some species of bats are declining in some regions of Europe. These declines are probably due to a range of pressures, including climate change, urbanization and exposure to toxins such as metals. This paper describes the development, paramaterisation and application of a spatially explicit modeling framework to predict the risks of soil-associated metals (lead, copper, zinc and cadmium) to bat health. Around 5.9% of areas where bats reside were predicted to have lead levels that pose a risk to bat health. For copper, this value was 2.8%, for cadmium it was 0.6% and for zinc 0.5%. Further work is therefore warranted to explore the impacts of soil-associated metals on bat populations in the UK. - Highlights: ► A modeling framework is presented to estimate risks of contaminants to wildlife. ► The model has been applied to soil metal contamination and bat species. ► Results indicate that lead and copper pose the greatest risk to bat health. ► A risk is predicted for up to 6% of areas where bats reside in England and Wales. - Application of a novel, spatially explicit risk assessment framework indicates that the health of insectivorous bat species in some regions of the UK may be at threat from exposure to soil associated metals.

  19. Revealing the maternal demographic history of Panthera leo using ancient DNA and a spatially explicit genealogical analysis.

    Science.gov (United States)

    Barnett, Ross; Yamaguchi, Nobuyuki; Shapiro, Beth; Ho, Simon Y W; Barnes, Ian; Sabin, Richard; Werdelin, Lars; Cuisin, Jacques; Larson, Greger

    2014-04-02

    Understanding the demographic history of a population is critical to conservation and to our broader understanding of evolutionary processes. For many tropical large mammals, however, this aim is confounded by the absence of fossil material and by the misleading signal obtained from genetic data of recently fragmented and isolated populations. This is particularly true for the lion which as a consequence of millennia of human persecution, has large gaps in its natural distribution and several recently extinct populations. We sequenced mitochondrial DNA from museum-preserved individuals, including the extinct Barbary lion (Panthera leo leo) and Iranian lion (P. l. persica), as well as lions from West and Central Africa. We added these to a broader sample of lion sequences, resulting in a data set spanning the historical range of lions. Our Bayesian phylogeographical analyses provide evidence for highly supported, reciprocally monophyletic lion clades. Using a molecular clock, we estimated that recent lion lineages began to diverge in the Late Pleistocene. Expanding equatorial rainforest probably separated lions in South and East Africa from other populations. West African lions then expanded into Central Africa during periods of rainforest contraction. Lastly, we found evidence of two separate incursions into Asia from North Africa, first into India and later into the Middle East. We have identified deep, well-supported splits within the mitochondrial phylogeny of African lions, arguing for recognition of some regional populations as worthy of independent conservation. More morphological and nuclear DNA data are now needed to test these subdivisions.

  20. A spatially-explicit data driven approach to assess the effect of agricultural land occupation on species groups

    Science.gov (United States)

    Elshout, P.; van Zelm, R.; Karuppiah, R.; Laurenzi, I.; Huijbregts, M.

    2013-12-01

    Change of vegetation cover and increased land use intensity can directly affect the natural habitat and the wildlife it houses. The actual impact of agricultural land use is region specific as crops are grown under various climatic conditions and ways of cultivation and refining. Furthermore, growing a specific crop in a tropical region may require clearance of rainforest while the same crop may replace natural grasslands in temperate regions. Within life cycle impact assessment (LCIA), methods to address impacts of land use on a global scale are still in need of development. We aim to extend existing methods to improve the robustness of LCIA by allowing spatial differentiation of agricultural land use impacts. The goal of this study is to develop characterization factors for the direct impact of land use on biodiversity, which results from the replacement of natural habitat with farmland. The characterization factor expresses the change in species richness under crop cultivation compared to the species richness in the natural situation over a certain area. A second goal was to identify the differences in impacts caused by cultivation of different crop types, sensitivity of different taxonomic groups, and differences in natural land cover. Empirical data on species richness were collected from literature for both natural reference situations and agricultural land use situations. Reference situations were selected on an ecoregion or biome basis. We calculated characterization factors for four crop groups (oil palm, low crops, cereals, and perennial grasses), four species groups (arthropods, birds, mammals, vascular plants), and six biomes.

  1. A Global and Spatially Explicit Assessment of Climate Change Impacts on Crop Production and Consumptive Water Use

    Science.gov (United States)

    Liu, Junguo; Folberth, Christian; Yang, Hong; Röckström, Johan; Abbaspour, Karim; Zehnder, Alexander J. B.

    2013-01-01

    Food security and water scarcity have become two major concerns for future human's sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security. PMID:23460901

  2. Cannabis (Cannabis sativa or C. indica) agriculture and the environment: a systematic, spatially-explicit survey and potential impacts

    Science.gov (United States)

    Butsic, Van; Brenner, Jacob C.

    2016-04-01

    Cannabis agriculture is a multi-billion dollar industry in the United States that is changing rapidly with policy liberalization. Anecdotal observations fuel speculation about associated environmental impacts, and there is an urgent need for systematic empirical research. An example from Humboldt County California, a principal cannabis-producing region, involved digitizing 4428 grow sites in 60 watersheds with Google Earth imagery. Grows were clustered, suggesting disproportionate impacts in ecologically important locales. Sixty-eight percent of grows were >500 m from developed roads, suggesting risk of landscape fragmentation. Twenty-two percent were on steep slopes, suggesting risk of erosion, sedimentation, and landslides. Five percent were cannabis agriculture documented in our study demands that it be regulated and researched on par with conventional agriculture.

  3. Exploring future agricultural development and biodiversity in Uganda, Rwanda and Burundi: a spatially explicit scenario-based assessment

    NARCIS (Netherlands)

    van Soesbergen, Arnout; Arnell, Andrew P.; Sassen, Marieke; Stuch, Benjamin; Schaldach, Rüdiger; Göpel, Jan; Vervoort, Joost; Mason-D’Croz, Daniel; Islam, Shahnila; Palazzo, Amanda

    2017-01-01

    Competition for land is increasing as a consequence of the growing demands for food and other commodities and the need to conserve biodiversity and ecosystem services. Land conversion and the intensification of current agricultural systems continues to lead to a loss of biodiversity and trade-offs

  4. A global and spatially explicit assessment of climate change impacts on crop production and consumptive water use.

    Directory of Open Access Journals (Sweden)

    Junguo Liu

    Full Text Available Food security and water scarcity have become two major concerns for future human's sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term and the 2090s (long term, respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental but lower on smaller spatial scales (e.g., national and grid cell. Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security.

  5. Spatially explicit power analysis for occupancy-based monitoring of wolverine populations in the U.S

    Science.gov (United States)

    Martha M. Ellis; Jacob S. Ivan; Michael K. Schwartz

    2014-01-01

    Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a...

  6. Calculating the wind energy input to a system using a spatially explicit method that considers atmospheric stability

    Science.gov (United States)

    Atmospheric stability has a major effect in determining the wind energy doing work in the atmospheric boundary layer (ABL); however, it is seldom considered in determining this value in emergy analyses. One reason that atmospheric stability is not usually considered is that a sui...

  7. Spatially explicit estimates of stock sizes, structure and biomass of herring and blue whiting, and catch data of bluefin tuna

    DEFF Research Database (Denmark)

    Huse, G.; MacKenzie, B. R.; Trenkel, V.

    2015-01-01

    The North Atlantic is a productive marine region which has supported important commercial fisheries for centuries. Many of these fisheries have exploited the pelagic species, including herring, blue whiting and tuna. Here we present data on the distribution of herring and blue whiting based on th...

  8. Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands.

    Science.gov (United States)

    Miller, Brian W; Breckheimer, Ian; McCleary, Amy L; Guzmán-Ramirez, Liza; Caplow, Susan C; Jones-Smith, Jessica C; Walsh, Stephen J

    2010-05-01

    Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands - tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps.

  9. Accounting for small scale heterogeneity in ecohydrologic watershed models

    Science.gov (United States)

    Burke, W.; Tague, C.

    2017-12-01

    Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach

  10. Modeling global distribution of agricultural insecticides in surface waters.

    Science.gov (United States)

    Ippolito, Alessio; Kattwinkel, Mira; Rasmussen, Jes J; Schäfer, Ralf B; Fornaroli, Riccardo; Liess, Matthias

    2015-03-01

    Agricultural insecticides constitute a major driver of animal biodiversity loss in freshwater ecosystems. However, the global extent of their effects and the spatial extent of exposure remain largely unknown. We applied a spatially explicit model to estimate the potential for agricultural insecticide runoff into streams. Water bodies within 40% of the global land surface were at risk of insecticide runoff. We separated the influence of natural factors and variables under human control determining insecticide runoff. In the northern hemisphere, insecticide runoff presented a latitudinal gradient mainly driven by insecticide application rate; in the southern hemisphere, a combination of daily rainfall intensity, terrain slope, agricultural intensity and insecticide application rate determined the process. The model predicted the upper limit of observed insecticide exposure measured in water bodies (n = 82) in five different countries reasonably well. The study provides a global map of hotspots for insecticide contamination guiding future freshwater management and conservation efforts. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Can We Use Regression Modeling to Quantify Mean Annual Streamflow at a Global-Scale?

    Science.gov (United States)

    Barbarossa, V.; Huijbregts, M. A. J.; Hendriks, J. A.; Beusen, A.; Clavreul, J.; King, H.; Schipper, A.

    2016-12-01

    Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF using observations of discharge and catchment characteristics from 1,885 catchments worldwide, ranging from 2 to 106 km2 in size. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB [van Beek et al., 2011] by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area, mean annual precipitation and air temperature, average slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error values were lower (0.29 - 0.38 compared to 0.49 - 0.57) and the modified index of agreement was higher (0.80 - 0.83 compared to 0.72 - 0.75). Our regression model can be applied globally at any point of the river network, provided that the input parameters are within the range of values employed in the calibration of the model. The performance is reduced for water scarce regions and further research should focus on improving such an aspect for regression-based global hydrological models.

  12. Classifying individuals based on a densely captured sequence of vital signs: An example using repeated blood pressure measurements during hemodialysis treatment.

    Science.gov (United States)

    Goldstein, Benjamin A; Chang, Tara I; Winkelmayer, Wolfgang C

    2015-10-01

    Electronic Health Records (EHRs) present the opportunity to observe serial measurements on patients. While potentially informative, analyzing these data can be challenging. In this work we present a means to classify individuals based on a series of measurements collected by an EHR. Using patients undergoing hemodialysis, we categorized people based on their intradialytic blood pressure. Our primary criteria were that the classifications were time dependent and independent of other subjects. We fit a curve of intradialytic blood pressure using regression splines and then calculated first and second derivatives to come up with four mutually exclusive classifications at different time points. We show that these classifications relate to near term risk of cardiac events and are moderately stable over a succeeding two-week period. This work has general application for analyzing dense EHR data. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Quantifying and Analysing Neighbourhood Characteristics Supporting Urban Land-Use Modelling

    DEFF Research Database (Denmark)

    Hansen, Henning Sten

    2009-01-01

    Land-use modelling and spatial scenarios have gained increased attention as a means to meet the challenge of reducing uncertainty in the spatial planning and decision-making. Several organisations have developed software for land-use modelling. Many of the recent modelling efforts incorporate...... cellular automata (CA) to accomplish spatially explicit land-use change modelling. Spatial interaction between neighbour land-uses is an important component in urban cellular automata. Nevertheless, this component is calibrated through trial-and-error estimation. The aim of the current research project has...... been to quantify and analyse land-use neighbourhood characteristics and impart useful information for cell based land-use modelling. The results of our research is a major step forward, because we have estimated rules for neighbourhood interaction from really observed land-use changes at a yearly basis...

  14. An individual-based versus group-based exercise and counselling intervention for improving quality of life in breast cancer survivors. A feasibility and efficacy study.

    Science.gov (United States)

    Naumann, Fiona; Munro, Aime; Martin, Eric; Magrani, Paula; Buchan, Jena; Smith, Cathie; Piggott, Ben; Philpott, Martin

    2012-10-01

    Cancer and its treatments produce lingering side-effects that undermine the quality of life (QOL) of survivors. Exercise and psycho-therapies increase QOL among survivors, however, research is needed to identify intervention characteristics most associated with such improvements. This research aimed to assess the feasibility of a 9 week individual or group based exercise and counselling program, and to examine if a group based intervention is as effective at improving the QOL of breast cancer survivors as an individual-based intervention. A three group design was implemented to compare the efficacy of a 9 week individual (IEC n = 12) and group based exercise and counselling (GEC n = 14) intervention to a usual care (UsC n = 10) group on QOL of thirty-six breast cancer survivors. Across all groups, 90% of participants completed the interventions, with no adverse effects documented. At the completion of the intervention, there was a significant difference between groups for change in global QOL across time (p group (1.8 points). The effect size was moderate (0.70). Although the GEC improved QOL by almost 10.0 points, this increase did not reach significance. Both increases were above the minimally important difference of 7-8 points. These preliminary results suggest a combined exercise and psychological counseling program is both a feasible and acceptable intervention for breast cancer survivors. Whilst both the individual and group interventions improved QOL above the clinically important difference, only the individual based intervention was significant when compared to UsC. Copyright © 2011 John Wiley & Sons, Ltd.

  15. Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

    Science.gov (United States)

    Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

    2010-01-01

    Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

  16. From complex spatial dynamics to simple Markov chain models: do predators and prey leave footprints?

    DEFF Research Database (Denmark)

    Nachman, Gøsta Støger; Borregaard, Michael Krabbe

    2010-01-01

    to another, are then depicted in a state transition diagram, constituting the "footprints" of the underlying population dynamics. We investigate to what extent changes in the population processes modeled in the complex simulation (i.e. the predator's functional response and the dispersal rates of both......In this paper we present a concept for using presence-absence data to recover information on the population dynamics of predator-prey systems. We use a highly complex and spatially explicit simulation model of a predator-prey mite system to generate simple presence-absence data: the number...... of transition probabilities on state variables, and combine this information in a Markov chain transition matrix model. Finally, we use this extended model to predict the long-term dynamics of the system and to reveal its asymptotic steady state properties....

  17. Speciation in the Derrida-Higgs model with finite genomes and spatial populations

    Science.gov (United States)

    de Aguiar, Marcus A. M.

    2017-02-01

    The speciation model proposed by Derrida and Higgs demonstrated that a sexually reproducing population can split into different species in the absence of natural selection or any type of geographic isolation, provided that mating is assortative and the number of genes involved in the process is infinite. Here we revisit this model and simulate it for finite genomes, focusing on the question of how many genes it actually takes to trigger neutral sympatric speciation. We find that, for typical parameters used in the original model, it takes the order of 105 genes. We compare the results with a similar spatially explicit model where about 100 genes suffice for speciation. We show that when the number of genes is small the species that emerge are strongly segregated in space. For a larger number of genes, on the other hand, the spatial structure of the population is less important and the species distribution overlap considerably.

  18. Genetic and environmental influences on height from infancy to early adulthood: An individual-based pooled analysis of 45 twin cohorts.

    Science.gov (United States)

    Jelenkovic, Aline; Sund, Reijo; Hur, Yoon-Mi; Yokoyama, Yoshie; Hjelmborg, Jacob V B; Möller, Sören; Honda, Chika; Magnusson, Patrik K E; Pedersen, Nancy L; Ooki, Syuichi; Aaltonen, Sari; Stazi, Maria A; Fagnani, Corrado; D'Ippolito, Cristina; Freitas, Duarte L; Maia, José Antonio; Ji, Fuling; Ning, Feng; Pang, Zengchang; Rebato, Esther; Busjahn, Andreas; Kandler, Christian; Saudino, Kimberly J; Jang, Kerry L; Cozen, Wendy; Hwang, Amie E; Mack, Thomas M; Gao, Wenjing; Yu, Canqing; Li, Liming; Corley, Robin P; Huibregtse, Brooke M; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth J F; Heikkilä, Kauko; Wardle, Jane; Llewellyn, Clare H; Fisher, Abigail; McAdams, Tom A; Eley, Thalia C; Gregory, Alice M; He, Mingguang; Ding, Xiaohu; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Tarnoki, Adam D; Tarnoki, David L; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Burt, S Alexandra; Klump, Kelly L; Silberg, Judy L; Eaves, Lindon J; Maes, Hermine H; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Gatz, Margaret; Butler, David A; Bartels, Meike; van Beijsterveldt, Toos C E M; Craig, Jeffrey M; Saffery, Richard; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Martin, Nicholas G; Medland, Sarah E; Montgomery, Grant W; Swan, Gary E; Krasnow, Ruth; Tynelius, Per; Lichtenstein, Paul; Haworth, Claire M A; Plomin, Robert; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Harden, K Paige; Tucker-Drob, Elliot M; Spector, Timothy; Mangino, Massimo; Lachance, Genevieve; Baker, Laura A; Tuvblad, Catherine; Duncan, Glen E; Buchwald, Dedra; Willemsen, Gonneke; Skytthe, Axel; Kyvik, Kirsten O; Christensen, Kaare; Öncel, Sevgi Y; Aliev, Fazil; Rasmussen, Finn; Goldberg, Jack H; Sørensen, Thorkild I A; Boomsma, Dorret I; Kaprio, Jaakko; Silventoinen, Karri

    2016-06-23

    Height variation is known to be determined by both genetic and environmental factors, but a systematic description of how their influences differ by sex, age and global regions is lacking. We conducted an individual-based pooled analysis of 45 twin cohorts from 20 countries, including 180,520 paired measurements at ages 1-19 years. The proportion of height variation explained by shared environmental factors was greatest in early childhood, but these effects remained present until early adulthood. Accordingly, the relative genetic contribution increased with age and was greatest in adolescence (up to 0.83 in boys and 0.76 in girls). Comparing geographic-cultural regions (Europe, North-America and Australia, and East-Asia), genetic variance was greatest in North-America and Australia and lowest in East-Asia, but the relative proportion of genetic variation was roughly similar across these regions. Our findings provide further insights into height variation during childhood and adolescence in populations representing different ethnicities and exposed to different environments.

  19. Prognostic relevance of motor talent predictors in early adolescence: A group- and individual-based evaluation considering different levels of achievement in youth football.

    Science.gov (United States)

    Höner, Oliver; Votteler, Andreas

    2016-12-01

    In the debate about the usefulness of motor diagnostics in the talent identification process, the prognostic validity for tests conducted in early adolescence is of critical interest. Using a group- and individual-based statistical approach, this prospective cohort study evaluated a nationwide assessment of speed abilities and technical skills regarding its relevance for future achievement levels. The sample consisted of 22,843 U12-players belonging to the top 4% in German football. The U12-results in five tests served as predictors for players' selection levels in U16-U19 (youth national team, regional association, youth academy, not selected). Group-mean differences proved the prognostic relevance for all predictors. Low individual selection probabilities demonstrated limited predictive values, while excellent test results proved their particular prognostic relevance. Players scoring percentile ranks (PRs) ≥ 99 had a 12 times higher chance to become youth national team players than players scoring PR talents) but also led to lower sensitivity (loss of talents). Extending the current research, these different approaches revealed the ambiguity of the diagnostics' prognostic relevance, representing both the usefulness and several pitfalls of nationwide diagnostics. Therefore, the present diagnostics can support but not substitute for coaches' subjective decisions for talent identification, and multidisciplinary designs are required.

  20. Creating a Ruggedness Layer for Use in Habitat Suitability Modeling for Ikh Nart Nature Reserve, Mongolia

    Directory of Open Access Journals (Sweden)

    Nanette Bragin

    2013-12-01

    Full Text Available Spatially-explicit wildlife habitat models are increasingly used to study optimal habitat for species of conservation focus. A ruggedness layer, that summarizes aspect and slope, provides a useful tool for analyses conducted in a Geographic Information System (GIS, such as developing a habitat suitability index model to measure species habitat use. Ruggedness layers prove especially useful in areas where topography represents a key habitat component. We created a ruggedness layer for the Ikh Nart Nature Reserve and surrounding areas in northern Dornogobi Aimag (province, Mongolia. Using a 90 m Shuttle Radar Topography Mission (SRTM digital elevation model (DEM and ArcGIS 10 spatial analyst, we created 9 categories for ruggedness. When combined with other thematic layers such as vegetation, the ruggedness layer becomes a powerful tool for analyzing habitat use by individual animals. The results of such analyses may inform decision makers in protected area planning and conservation of endangered species.

  1. A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar.

    Science.gov (United States)

    Brown, Jason L; Cameron, Alison; Yoder, Anne D; Vences, Miguel

    2014-10-09

    Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixed-spatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A 'one-size-fits-all' model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar's biota.

  2. River export of triclosan from land to sea: A global modelling approach.

    Science.gov (United States)

    van Wijnen, Jikke; Ragas, Ad M J; Kroeze, Carolien

    2018-04-15

    Triclosan (TCS) is an antibacterial agent that is added to commonly used personal care products. Emitted to the aquatic environment in large quantities, it poses a potential threat to aquatic organisms. Triclosan enters the aquatic environment mainly through sewage effluent. We developed a global, spatially explicit model, the Global TCS model, to simulate triclosan transport by rivers to coastal areas. With this model we analysed annual, basin-wide triclosan export for the year 2000 and two future scenarios for the year 2050. Our analyses for 2000 indicate that triclosan export to coastal areas in Western Europe, Southeast Asia and the East Coast of the USA is higher than in the rest of the world. For future scenarios, the Global TCS model predicts an increase in river export of triclosan in Southeast Asia and a small decrease in Europe. The number of rivers with an annual average triclosan concentration at the river mouth that exceeds a PNEC of 26.2ng/L is projected to double between 2000 and 2050. This increase is most prominent in Southeast Asia, as a result of fast population growth, increasing urbanisation and increasing numbers of people connected to sewerage systems with poor wastewater treatment. Predicted triclosan loads correspond reasonably well with measured values. However, basin-specific predictions have considerable uncertainty due to lacking knowledge and location-specific data on the processes determining the fate of triclosan in river water, e.g. sorption, degradation and sedimentation. Additional research on the fate of triclosan in river systems is therefore recommended. We developed a global spatially explicit model to simulate triclosan export by rivers to coastal seas. For two future scenarios this Global TCS model projects an increase in river export of triclosan to several seas around the world. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Model analysis of riparian buffer effectiveness for reducing nutrient inputs to streams in agricultural landscapes

    Science.gov (United States)

    McKane, R. B.; M, S.; F, P.; Kwiatkowski, B. L.; Rastetter, E. B.

    2006-12-01

    Federal and state agencies responsible for protecting water quality rely mainly on statistically-based methods to assess and manage risks to the nation's streams, lakes and estuaries. Although statistical approaches provide valuable information on current trends in water quality, process-based simulation models are essential for understanding and forecasting how changes in human activities across complex landscapes impact the transport of nutrients and contaminants to surface waters. To address this need, we developed a broadly applicable, process-based watershed simulator that links a spatially-explicit hydrologic model and a terrestrial biogeochemistry model (MEL). See Stieglitz et al. and Pan et al., this meeting, for details on the design and verification of this simulator. Here we apply the watershed simulator to a generalized agricultural setting to demonstrate its potential for informing policy and management decisions concerning water quality. This demonstration specifically explores the effectiveness of riparian buffers for reducing the transport of nitrogenous fertilizers from agricultural fields to streams. The interaction of hydrologic and biogeochemical processes represented in our simulator allows several important questions to be addressed. (1) For a range of upland fertilization rates, to what extent do riparian buffers reduce nitrogen inputs to streams? (2) How does buffer effectiveness change over time as the plant-soil system approaches N-saturation? (3) How can buffers be managed to increase their effectiveness, e.g., through periodic harvest and replanting? The model results illustrate that, while the answers to these questions depend to some extent on site factors (climatic regime, soil properties and vegetation type), in all cases riparian buffers have a limited capacity to reduce nitrogen inputs to streams where fertilization rates approach those typically used for intensive agriculture (e.g., 200 kg N per ha per year for corn in the U

  4. Modeling the impact of future development and public conservation orientation on landscape connectivity for conservation planning

    DEFF Research Database (Denmark)

    Lechner, Alex Mark; Brown, Greg; Raymond, Christopher Mark

    2015-01-01

    aspects of conservation planning. Objectives We present an approach for characterizing the potential effects of public conservation orientation and projected future development land use scenarios on landscape connectivity. Methods Using public participation GIS techniques (mail-based surveys linked...... to a mapping component), we classified spatially explicit conservation values and preferences into a conservation orientation index consisting of positive, negative, or neutral scores. Connectivity was then modeled using a least-cost path and graph-network approach for a range of conservation orientation...... and development scenarios in the Lower Hunter region, Australia. Scenarios were modelled through either adding vegetation (positive orientation) or removing vegetation (negative orientation, development). Results Scenarios that included positive conservation orientation link the isolated eastern and western...

  5. Economics of wildfire management the development and application of suppression expenditure models

    CERN Document Server

    Hand, Michael S; Liang, Jingjing; Thompson, Matthew P

    2014-01-01

    In this age of climatic and financial uncertainty, it becomes increasingly important to balance the cost, benefits and risk of wildfire management. In the United States, increased wildland fire activity over the last 15 years has resulted in drastic damage and loss of life. An associated rapid increase in fire management costs has consumed higher portions of budgets of public entities involved in wildfire management, challenging their ability to fulfill other responsibilities. Increased public scrutiny highlights the need to improve wildland fire management for cost effectiveness. This book closely examines the development of basic wildfire suppression cost models for the United States and their application to a wide range of settings from informing incident decision making to programmatic review. The book also explores emerging trends in suppression costs and introduces new spatially explicit cost models to account for characteristics of the burned landscape. Finally, it discusses how emerging risk assessmen...

  6. The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

    Science.gov (United States)

    Ciddio, Manuela; Mari, Lorenzo; Sokolow, Susanne H.; De Leo, Giulio A.; Casagrandi, Renato; Gatto, Marino

    2017-10-01

    Schistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. Here we study the spatial spread of this disease within a network of connected villages in the endemic region of the Lower Basin of the Senegal River, in Senegal. The analysis is performed by means of a spatially explicit metapopulation model that couples local-scale eco-epidemiological dynamics with spatial mechanisms related to human mobility (estimated from anonymized mobile phone records), snail dispersal and hydrological transport of schistosome larvae along the main water bodies of the region. Results show that the model produces epidemiological patterns consistent with field observations, and point out the key role of spatial connectivity on the spread of the disease. These findings underline the importance of considering different transport pathways in order to elaborate disease control strategies that can be effective within a network of connected populations.

  7. Intelligent spatial ecosystem modeling using parallel processors

    International Nuclear Information System (INIS)

    Maxwell, T.; Costanza, R.

    1993-01-01

    Spatial modeling of ecosystems is essential if one's modeling goals include developing a relatively realistic description of past behavior and predictions of the impacts of alternative management policies on future ecosystem behavior. Development of these models has been limited in the past by the large amount of input data required and the difficulty of even large mainframe serial computers in dealing with large spatial arrays. These two limitations have begun to erode with the increasing availability of remote sensing data and GIS systems to manipulate it, and the development of parallel computer systems which allow computation of large, complex, spatial arrays. Although many forms of dynamic spatial modeling are highly amenable to parallel processing, the primary focus in this project is on process-based landscape models. These models simulate spatial structure by first compartmentalizing the landscape into some geometric design and then describing flows within compartments and spatial processes between compartments according to location-specific algorithms. The authors are currently building and running parallel spatial models at the regional scale for the Patuxent River region in Maryland, the Everglades in Florida, and Barataria Basin in Louisiana. The authors are also planning a project to construct a series of spatially explicit linked ecological and economic simulation models aimed at assessing the long-term potential impacts of global climate change

  8. Sources of variation in innate immunity in great tit nestlings living along a metal pollution gradient: An individual-based approach

    International Nuclear Information System (INIS)

    Vermeulen, Anke; Müller, Wendt; Matson, Kevin D.; Irene Tieleman, B.; Bervoets, Lieven; Eens, Marcel

    2015-01-01

    Excessive deposition of metals in the environment is a well-known example of pollution worldwide. Chronic exposure of organisms to metals can have a detrimental effect on reproduction, behavior, health and survival, due to the negative effects on components of the immune system. However, little is known about the effects of chronic sublethal metal exposure on immunity, especially for wildlife. In our study, we examined the constitutive innate immunity of great tit (Parus major) nestlings (N = 234) living in four populations along a metal pollution gradient. For each nestling, we determined the individual metal concentrations (lead, cadmium, arsenic) present in the red blood cells and measured four different innate immune parameters (agglutination, lysis, haptoglobin concentrations and nitric oxide concentrations) to investigate the relationship between metal exposure and immunological condition. While we found significant differences in endogenous metal concentrations among populations with the highest concentrations closest to the pollution source, we did not observe corresponding patterns in our immune measures. However, when evaluating relationships between metal concentrations and immune parameters at the individual level, we found negative effects of lead and, to a lesser extent, arsenic and cadmium on lysis. In addition, high arsenic concentrations appear to elicit inflammation, as reflected by elevated haptoglobin concentrations. Thus despite the lack of a geographic association between pollution and immunity, this type of association was present at the individual level at a very early life stage. The high variation in metal concentrations and immune measures observed within populations indicates a high level of heterogeneity along an existing pollution gradient. Interestingly, we also found substantial within nest variation, for which the sources remain unclear, and which highlights the need of an individual-based approach. - Highlights: • Innate immunity

  9. Sources of variation in innate immunity in great tit nestlings living along a metal pollution gradient: An individual-based approach

    Energy Technology Data Exchange (ETDEWEB)

    Vermeulen, Anke, E-mail: anke.vermeulen@uantwerpen.be [Department of Biology — Ethology, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium); Müller, Wendt, E-mail: wendt.mueller@uantwerpen.be [Department of Biology — Ethology, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium); Matson, Kevin D., E-mail: k.d.matson@rug.nl [Animal Ecology Group, Centre for Ecological and Evolutionary Studies, University of Groningen, P.O. Box 11103, 9700 CC Groningen (Netherlands); The Resource Ecology Group, Department of Environmental Sciences, Wageningen University, Droevendaalsesteeg 3a, 6708PB Wageningen (Netherlands); Irene Tieleman, B., E-mail: b.i.tieleman@rug.nl [Animal Ecology Group, Centre for Ecological and Evolutionary Studies, University of Groningen, P.O. Box 11103, 9700 CC Groningen (Netherlands); Bervoets, Lieven, E-mail: lieven.bervoets@uantwerpen.be [Department of Biology — SPHERE, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerpen (Belgium); Eens, Marcel, E-mail: marcel.eens@uantwerpen.be [Department of Biology — Ethology, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium)

    2015-03-01

    Excessive deposition of metals in the environment is a well-known example of pollution worldwide. Chronic exposure of organisms to metals can have a detrimental effect on reproduction, behavior, health and survival, due to the negative effects on components of the immune system. However, little is known about the effects of chronic sublethal metal exposure on immunity, especially for wildlife. In our study, we examined the constitutive innate immunity of great tit (Parus major) nestlings (N = 234) living in four populations along a metal pollution gradient. For each nestling, we determined the individual metal concentrations (lead, cadmium, arsenic) present in the red blood cells and measured four different innate immune parameters (agglutination, lysis, haptoglobin concentrations and nitric oxide concentrations) to investigate the relationship between metal exposure and immunological condition. While we found significant differences in endogenous metal concentrations among populations with the highest concentrations closest to the pollution source, we did not observe corresponding patterns in our immune measures. However, when evaluating relationships between metal concentrations and immune parameters at the individual level, we found negative effects of lead and, to a lesser extent, arsenic and cadmium on lysis. In addition, high arsenic concentrations appear to elicit inflammation, as reflected by elevated haptoglobin concentrations. Thus despite the lack of a geographic association between pollution and immunity, this type of association was present at the individual level at a very early life stage. The high variation in metal concentrations and immune measures observed within populations indicates a high level of heterogeneity along an existing pollution gradient. Interestingly, we also found substantial within nest variation, for which the sources remain unclear, and which highlights the need of an individual-based approach. - Highlights: • Innate immunity

  10. Estimating temporal trend in the presence of spatial complexity: a Bayesian hierarchical model for a wetland plant population undergoing restoration.

    Directory of Open Access Journals (Sweden)

    Thomas J Rodhouse

    Full Text Available Monitoring programs that evaluate restoration and inform adaptive management are important for addressing environmental degradation. These efforts may be well served by spatially explicit hierarchical approaches to modeling because of unavoidable spatial structure inherited from past land use patterns and other factors. We developed bayesian hierarchical models to estimate trends from annual density counts observed in a spatially structured wetland forb (Camassia quamash [camas] population following the cessation of grazing and mowing on the study area, and in a separate reference population of camas. The restoration site was bisected by roads and drainage ditches, resulting in distinct subpopulations ("zones" with different land use histories. We modeled this spatial structure by fitting zone-specific intercepts and slopes. We allowed spatial covariance parameters in the model to vary by zone, as in stratified kriging, accommodating anisotropy and improving computation and biological interpretation. Trend estimates provided evidence of a positive effect of passive restoration, and the strength of evidence was influenced by the amount of spatial structure in the model. Allowing trends to vary among zones and accounting for topographic heterogeneity increased precision of trend estimates. Accounting for spatial autocorrelation shifted parameter coefficients in ways that varied among zones depending on strength of statistical shrinkage, autocorrelation and topographic heterogeneity--a phenomenon not widely described. Spatially explicit estimates of trend from hierarchical models will generally be more useful to land managers than pooled regional estimates and provide more realistic assessments of uncertainty. The ability to grapple with historical contingency is an appealing benefit of this approach.

  11. Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal

    Science.gov (United States)

    Dieye, A.M.; Roy, David P.; Hanan, N.P.; Liu, S.; Hansen, M.; Toure, A.

    2012-01-01

    Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.

  12. Lotka-Volterra competition models for sessile organisms.

    Science.gov (United States)

    Spencer, Matthew; Tanner, Jason E

    2008-04-01

    Markov models are widely used to describe the dynamics of communities of sessile organisms, because they are easily fitted to field data and provide a rich set of analytical tools. In typical ecological applications, at any point in time, each point in space is in one of a finite set of states (e.g., species, empty space). The models aim to describe the probabilities of transitions between states. In most Markov models for communities, these transition probabilities are assumed to be independent of state abundances. This assumption is often suspected to be false and is rarely justified explicitly. Here, we start with simple assumptions about the interactions among sessile organisms and derive a model in which transition probabilities depend on the abundance of destination states. This model is formulated in continuous time and is equivalent to a Lotka-Volterra competition model. We fit this model and a variety of alternatives in which transition probabilities do not depend on state abundances to a long-term coral reef data set. The Lotka-Volterra model describes the data much better than all models we consider other than a saturated model (a model with a separate parameter for each transition at each time interval, which by definition fits the data perfectly). Our approach provides a basis for further development of stochastic models of sessile communities, and many of the methods we use are relevant to other types of community. We discuss possible extensions to spatially explicit models.

  13. European-scale modelling of groundwater denitrification and associated N2O production

    KAUST Repository

    Keuskamp, J.A.

    2012-06-01

    This paper presents a spatially explicit model for simulating the fate of nitrogen (N) in soil and groundwater and nitrous oxide (N 2O) production in groundwater with a 1 km resolution at the European scale. The results show large heterogeneity of nitrate outflow from groundwater to surface water and production of N 2O. This heterogeneity is the result of variability in agricultural and hydrological systems. Large parts of Europe have no groundwater aquifers and short travel times from soil to surface water. In these regions no groundwater denitrification and N 2O production is expected. Predicted N leaching (16% of the N inputs) and N 2O emissions (0.014% of N leaching) are much less than the IPCC default leaching rate and combined emission factor for groundwater and riparian zones, respectively. © 2012 Elsevier Ltd. All rights reserved.

  14. Life cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services.

    Science.gov (United States)

    Chaplin-Kramer, Rebecca; Sim, Sarah; Hamel, Perrine; Bryant, Benjamin; Noe, Ryan; Mueller, Carina; Rigarlsford, Giles; Kulak, Michal; Kowal, Virginia; Sharp, Richard; Clavreul, Julie; Price, Edward; Polasky, Stephen; Ruckelshaus, Mary; Daily, Gretchen

    2017-04-21

    International corporations in an increasingly globalized economy exert a major influence on the planet's land use and resources through their product design and material sourcing decisions. Many companies use life cycle assessment (LCA) to evaluate their sustainability, yet commonly-used LCA methodologies lack the spatial resolution and predictive ecological information to reveal key impacts on climate, water and biodiversity. We present advances for LCA that integrate spatially explicit modelling of land change and ecosystem services in a Land-Use Change Improved (LUCI)-LCA. Comparing increased demand for bioplastics derived from two alternative feedstock-location scenarios for maize and sugarcane, we find that the LUCI-LCA approach yields results opposite to those of standard LCA for greenhouse gas emissions and water consumption, and of different magnitudes for soil erosion and biodiversity. This approach highlights the importance of including information about where and how land-use change and related impacts will occur in supply chain and innovation decisions.

  15. Life cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services

    Science.gov (United States)

    Chaplin-Kramer, Rebecca; Sim, Sarah; Hamel, Perrine; Bryant, Benjamin; Noe, Ryan; Mueller, Carina; Rigarlsford, Giles; Kulak, Michal; Kowal, Virginia; Sharp, Richard; Clavreul, Julie; Price, Edward; Polasky, Stephen; Ruckelshaus, Mary; Daily, Gretchen

    2017-04-01

    International corporations in an increasingly globalized economy exert a major influence on the planet's land use and resources through their product design and material sourcing decisions. Many companies use life cycle assessment (LCA) to evaluate their sustainability, yet commonly-used LCA methodologies lack the spatial resolution and predictive ecological information to reveal key impacts on climate, water and biodiversity. We present advances for LCA that integrate spatially explicit modelling of land change and ecosystem services in a Land-Use Change Improved (LUCI)-LCA. Comparing increased demand for bioplastics derived from two alternative feedstock-location scenarios for maize and sugarcane, we find that the LUCI-LCA approach yields results opposite to those of standard LCA for greenhouse gas emissions and water consumption, and of different magnitudes for soil erosion and biodiversity. This approach highlights the importance of including information about where and how land-use change and related impacts will occur in supply chain and innovation decisions.

  16. LAPSUS: soil erosion - landscape evolution model

    Science.gov (United States)

    van Gorp, Wouter; Temme, Arnaud; Schoorl, Jeroen

    2015-04-01

    LAPSUS is a soil erosion - landscape evolution model which is capable of simulating landscape evolution of a gridded DEM by using multiple water, mass movement and human driven processes on multiple temporal and spatial scales. It is able to deal with a variety of human landscape interventions such as landuse management and tillage and it can model their interactions with natural processes. The complex spatially explicit feedbacks the model simulates demonstrate the importance of spatial interaction of human activity and erosion deposition patterns. In addition LAPSUS can model shallow landsliding, slope collapse, creep, solifluction, biological and frost weathering, fluvial behaviour. Furthermore, an algorithm to deal with natural depressions has been added and event-based modelling with an improved infiltration description and dust deposition has been pursued. LAPSUS has been used for case studies in many parts of the world and is continuously developing and expanding. it is now available for third-party and educational use. It has a comprehensive user interface and it is accompanied by a manual and exercises. The LAPSUS model is highly suitable to quantify and understand catchment-scale erosion processes. More information and a download link is available on www.lapsusmodel.nl.

  17. Continuous Long-Term Modeling of Shallow Groundwater-Surface Water Interaction: Implications for a Wet Prairie Restoration

    Science.gov (United States)

    Wijayarathne, D. B.; Gomezdelcampo, E.

    2017-12-01

    The existence of wet prairies is wholly dependent on the groundwater and surface water interaction. Any process that alters this interaction has a significant impact on the eco-hydrology of wet prairies. The Oak Openings Region (OOR) in Northwest Ohio supports globally rare wet prairie habitats and the precious few remaining have been drained by ditches, altering their natural flow and making them an unusually variable and artificial system. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model from the US Army Engineer Research and Development Center was used to assess the long-term impacts of land-use change on wet prairie restoration. This study is the first spatially explicit, continuous, long-term modeling approach for understanding the response of the shallow groundwater system of the OOR to human intervention, both positive and negative. The GSSHA model was calibrated using a 2-year weekly time series of water table elevations collected with an array of piezometers in the field. Basic statistical analysis indicates a good fit between observed and simulated water table elevations on a weekly level, though the model was run on an hourly time step and a pixel size of 10 m. Spatially-explicit results show that removal of a local ditch may not drastically change the amount of ponding in the area during spring storms, but large flooding over the entire area would occur if two other ditches are removed. This model is being used by The Nature Conservancy and Toledo Metroparks to develop different scenarios for prairie restoration that minimize its effect on local homeowners.

  18. Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

    Science.gov (United States)

    Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

    2016-12-01

    State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

  19. A spatial model to assess the effects of hydropower operations on Columbia River fall Chinook Salmon spawning habitat

    Science.gov (United States)

    Hatten, James R.; Tiffan, Kenneth F.; Anglin, Donald R.; Haeseker, Steven L.; Skalicky, Joseph J.; Schaller, Howard

    2009-01-01

    Priest Rapids Dam on the Columbia River produces large daily and hourly streamflow fluctuations throughout the Hanford Reach during the period when fall Chinook salmon Oncorhynchus tshawytscha are selecting spawning habitat, constructing redds, and actively engaged in spawning. Concern over the detrimental effects of these fluctuations prompted us to quantify the effects of variable flows on the amount and persistence of fall Chinook salmon spawning habitat in the Hanford Reach. Specifically, our goal was to develop a management tool capable of quantifying the effects of current and alternative hydrographs on predicted spawning habitat in a spatially explicit manner. Toward this goal, we modeled the water velocities and depths that fall Chinook salmon experienced during the 2004 spawning season, plus what they would probably have experienced under several alternative (i.e., synthetic) hydrographs, using both one- and two-dimensional hydrodynamic models. To estimate spawning habitat under existing or alternative hydrographs, we used cell-based modeling and logistic regression to construct and compare numerous spatial habitat models. We found that fall Chinook salmon were more likely to spawn at locations where velocities were persistently greater than 1 m/s and in areas where fluctuating water velocities were reduced. Simulations of alternative dam operations indicate that the quantity of spawning habitat is expected to increase as streamflow fluctuations are reduced during the spawning season. The spatial habitat models that we developed provide management agencies with a quantitative tool for predicting, in a spatially explicit manner, the effects of different flow regimes on fall Chinook salmon spawning habitat in the Hanford Reach. In addition to characterizing temporally varying habitat conditions, our research describes an analytical approach that could be applied in other highly variable aquatic systems.

  20. Density threshold for Mopeia virus invasion and persistence in its host Mastomys natalensis

    DEFF Research Database (Denmark)

    Goyens, J.; Reijniers, J.; Borremans, B.

    2013-01-01

    . We developed a spatially explicit and individual-based SEIR model of Mopeia virus in multimammate mice Mastomys natalensis. This is an interesting model system for studying abundance thresholds because the host is the most common African rodent, populations fluctuate considerably and the virus...... is closely related to Lassa virus but non-pathogenic to humans so can be studied safely in the field. The simulations show that, while host density clearly is important, sharp thresholds are only to be expected for persistence (and not for invasion), since at short time-spans (as during invasion...

  1. Supporting the operational use of process based hydrological models and NASA Earth Observations for use in land management and post-fire remediation through a Rapid Response Erosion Database (RRED).

    Science.gov (United States)

    Miller, M. E.; Elliot, W.; Billmire, M.; Robichaud, P. R.; Banach, D. M.

    2017-12-01

    We have built a Rapid Response Erosion Database (RRED, http://rred.mtri.org/rred/) for the continental United States to allow land managers to access properly formatted spatial model inputs for the Water Erosion Prediction Project (WEPP). Spatially-explicit process-based models like WEPP require spatial inputs that include digital elevation models (DEMs), soil, climate and land cover. The online database delivers either a 10m or 30m USGS DEM, land cover derived from the Landfire project, and soil data derived from SSURGO and STATSGO datasets. The spatial layers are projected into UTM coordinates and pre-registered for modeling. WEPP soil parameter files are also created along with linkage files to match both spatial land cover and soils data with the appropriate WEPP parameter files. Our goal is to make process-based models more accessible by preparing spatial inputs ahead of time allowing modelers to focus on addressing scenarios of concern. The database provides comprehensive support for post-fire hydrological modeling by allowing users to upload spatial soil burn severity maps, and within moments returns spatial model inputs. Rapid response is critical following natural disasters. After moderate and high severity wildfires, flooding, erosion, and debris flows are a major threat to life, property and municipal water supplies. Mitigation measures must be rapidly implemented if they are to be effective, but they are expensive and cannot be applied everywhere. Fire, runoff, and erosion risks also are highly heterogeneous in space, creating an urgent need for rapid, spatially-explicit assessment. The database has been used to help assess and plan remediation on over a dozen wildfires in the Western US. Future plans include expanding spatial coverage, improving model input data and supporting additional models. Our goal is to facilitate the use of the best possible datasets and models to support the conservation of soil and water.

  2. Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model.

    Science.gov (United States)

    Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di

    2016-07-15

    We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.

  3. Dynamic models in research and management of biological invasions.

    Science.gov (United States)

    Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R

    2017-07-01

    Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Wildfire risk for main vegetation units in a biodiversity hotspot: modeling approach in New Caledonia, South Pacific.

    Science.gov (United States)

    Gomez, Céline; Mangeas, Morgan; Curt, Thomas; Ibanez, Thomas; Munzinger, Jérôme; Dumas, Pascal; Jérémy, André; Despinoy, Marc; Hély, Christelle

    2015-01-01

    Wildfire has been recognized as one of the most ubiquitous disturbance agents to impact on natural environments. In this study, our main objective was to propose a modeling approach to investigate the potential impact of wildfire on biodiversity. The method is illustrated with an application example in New Caledonia where conservation and sustainable biodiversity management represent an important challenge. Firstly, a biodiversity loss index, including the diversity and the vulnerability indexes, was calculated for every vegetation unit in New Caledonia and mapped according to its distribution over the New Caledonian mainland. Then, based on spatially explicit fire behavior simulations (using the FLAMMAP software) and fire ignition probabilities, two original fire risk assessment approaches were proposed: a one-off event model and a multi-event burn probability model. The spatial distribution of fire risk across New Caledonia was similar for both indices with very small localized spots having high risk. The patterns relating to highest risk are all located around the remaining sclerophyll forest fragments and are representing 0.012% of the mainland surface. A small part of maquis and areas adjacent to dense humid forest on ultramafic substrates should also be monitored. Vegetation interfaces between secondary and primary units displayed high risk and should represent priority zones for fire effects mitigation. Low fire ignition probability in anthropogenic-free areas decreases drastically the risk. A one-off event associated risk allowed localizing of the most likely ignition areas with potential for extensive damage. Emergency actions could aim limiting specific fire spread known to have high impact or consist of on targeting high risk areas to limit one-off fire ignitions. Spatially explicit information on burning probability is necessary for setting strategic fire and fuel management planning. Both risk indices provide clues to preserve New Caledonia hot spot of

  5. UPSCALING OF SOLAR INDUCED CHLOROPHYLL FLUORESCENCE FROM LEAF TO CANOPY USING THE DART MODEL AND A REALISTIC 3D FOREST SCENE

    Directory of Open Access Journals (Sweden)

    W. Liu

    2017-10-01

    Full Text Available Solar induced chlorophyll a fluorescence (SIF has been shown to be an excellent proxy of photosynthesis at multiple scales. However, the mechanical linkages between fluorescence and photosynthesis at the leaf level cannot be directly applied at canopy or field scales, as the larger scale SIF emission depends on canopy structure. This is especially true for the forest canopies characterized by high horizontal and vertical heterogeneity. While most of the current studies on SIF radiative transfer in plant canopies are based on the assumption of a homogeneous canopy, recently codes have been developed capable of simulation of fluorescence signal in explicit 3-D forest canopies. Here we present a canopy SIF upscaling method consisting of the integration of the 3-D radiative transfer model DART and a 3-D object model BLENDER. Our aim was to better understand the effect of boreal forest canopy structure on SIF for a spatially explicit forest canopy.

  6. Modelling long-distance seed dispersal in heterogeneous landscapes.

    Energy Technology Data Exchange (ETDEWEB)

    Levey, Douglas, J.; Tewlsbury, Joshua, J.; Bolker, Benjamin, M.

    2008-01-01

    1. Long-distance seed dispersal is difficult to measure, yet key to understanding plant population dynamics and community composition. 2. We used a spatially explicit model to predict the distribution of seeds dispersed long distances by birds into habitat patches of different shapes. All patches were the same type of habitat and size, but varied in shape. They occurred in eight experimental landscapes, each with five patches of four different shapes, 150 m apart in a matrix of mature forest. The model was parameterized with smallscale movement data collected from field observations of birds. In a previous study we validated the model by testing its predictions against observed patterns of seed dispersal in real landscapes with the same types and spatial configuration of patches as in the model. 3. Here we apply the model more broadly, examining how patch shape influences the probability of seed deposition by birds into patches, how dispersal kernels (distributions of dispersal distances) vary with patch shape and starting location, and how movement of seeds between patches is affected by patch shape. 4. The model predicts that patches with corridors or other narrow extensions receive higher numbers of seeds than patches without corridors or extensions. This pattern is explained by edgefollowing behaviour of birds. Dispersal distances are generally shorter in heterogeneous landscapes (containing patchy habitat) than in homogeneous landscapes, suggesting that patches divert the movement of seed dispersers, ‘holding’ them long enough to increase the probability of seed defecation in the patches. Dispersal kernels for seeds in homogeneous landscapes were smooth, whereas those in heterogenous landscapes were irregular. In both cases, long-distance (> 150 m) dispersal was surprisingly common, usually comprising approximately 50% of all dispersal events. 5. Synthesis . Landscape heterogeneity has a large influence on patterns of long-distance seed dispersal. Our

  7. Robustness of movement models: can models bridge the gap between temporal scales of data sets and behavioural processes?

    Science.gov (United States)

    Schlägel, Ulrike E; Lewis, Mark A

    2016-12-01

    Discrete-time random walks and their extensions are common tools for analyzing animal movement data. In these analyses, resolution of temporal discretization is a critical feature. Ideally, a model both mirrors the relevant temporal scale of the biological process of interest and matches the data sampling rate. Challenges arise when resolution of data is too coarse due to technological constraints, or when we wish to extrapolate results or compare results obtained from data with different resolutions. Drawing loosely on the concept of robustness in statistics, we propose a rigorous mathematical framework for studying movement models' robustness against changes in temporal resolution. In this framework, we define varying levels of robustness as formal model properties, focusing on random walk models with spatially-explicit component. With the new framework, we can investigate whether models can validly be applied to data across varying temporal resolutions and how we can account for these different resolutions in statistical inference results. We apply the new framework to movement-based resource selection models, demonstrating both analytical and numerical calculations, as well as a Monte Carlo simulation approach. While exact robustness is rare, the concept of approximate robustness provides a promising new direction for analyzing movement models.

  8. Generalized additive models used to predict species abundance in the Gulf of Mexico: an ecosystem modeling tool.

    Directory of Open Access Journals (Sweden)

    Michael Drexler

    Full Text Available Spatially explicit ecosystem models of all types require an initial allocation of biomass, often in areas where fisheries independent abundance estimates do not exist. A generalized additive modelling (GAM approach is used to describe the abundance of 40 species groups (i.e. functional groups across the Gulf of Mexico (GoM using a large fisheries independent data set (SEAMAP and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. Despite the presence of a large number of zeros in the data, a single GAM using a negative binomial distribution was suitable to make predictions of abundance for multiple functional groups. We present an example case study using pink shrimp (Farfantepenaeus duroarum and compare the results to known distributions. The model successfully predicts the known areas of high abundance in the GoM, including those areas where no data was inputted into the model fitting. Overall, the model reliably captures areas of high and low abundance for the large majority of functional groups observed in SEAMAP. The result of this method allows for the objective setting of spatial distributions for numerous functional groups across a modeling domain, even where abundance data may not exist.

  9. Covariation in community- and individual-based community capacity and health behavior: a multilevel analysis of populations in Seoul, South Korea.

    Science.gov (United States)

    Jung, Minsoo

    2012-01-01

    Community capacity is defined as the degree to which the human, physical, and potential resources of a neighborhood are organized based on mutual solidarity among the residents. The aim of this study was to elucidate the relationship between community capacity and health behaviors in Seoul, South Korea. Multilevel models controlling for socioeconomic variables were used to measure the association between community capacity and health behaviors in 25 districts and 404 subdistricts (n = 14 228). Community capacity was determined to be significant at the more local community level, as it was a significant variable in the subdistrict analysis for explaining health behaviors such as smoking, drinking, and exercising. Community capacity exists not only at the individual level but also at the community level. High community capacity further enhanced the positive effects of individual capacity on health behavior and further weakened the negative effects.

  10. Modelling vesicular release at hippocampal synapses.

    Directory of Open Access Journals (Sweden)

    Suhita Nadkarni

    2010-11-01

    Full Text Available We study local calcium dynamics leading to a vesicle fusion in a stochastic, and spatially explicit, biophysical model of the CA3-CA1 presynaptic bouton. The kinetic model for vesicle release has two calcium sensors, a sensor for fast synchronous release that lasts a few tens of milliseconds and a separate sensor for slow asynchronous release that lasts a few hundred milliseconds. A wide range of data can be accounted for consistently only when a refractory period lasting a few milliseconds between releases is included. The inclusion of a second sensor for asynchronous release with a slow unbinding site, and thereby a long memory, affects short-term plasticity by facilitating release. Our simulations also reveal a third time scale of vesicle release that is correlated with the stimulus and is distinct from the fast and the slow releases. In these detailed Monte Carlo simulations all three time scales of vesicle release are insensitive to the spatial details of the synaptic ultrastructure. Furthermore, our simulations allow us to identify features of synaptic transmission that are universal and those that are modulated by structure.

  11. Reconstruction of historical changes in northern fur seal prey availability and diversity in the western North Pacific through individual-based analysis of dietary records

    Science.gov (United States)

    Kiyota, Masashi; Yonezaki, Shiroh

    2017-06-01

    We analyzed long-term dietary records of northern fur seals (Callorhinus ursinus) to reconstruct historical changes in prey availability and diversity in the western North Pacific off northeastern Japan. The nominal relationships between the occurrence frequencies of fishes or squids in fur seal stomachs and the sampling locations reflected the spatial heterogeneity of fish and squid distributions along the shelf-slope-offshore continuum off northeastern Japan, whereas changes in the temporal occurrence frequencies reflected mainly the migration and foraging patterns of the fur seals. The occurrence probabilities of fishes and squids in fur seal stomachs were standardized by using generalized linear models to compensate for sampling biases in space and time. The reconstructed historical trends revealed decadal shifts in relatively high prey abundance-from mackerels in the 1970s to Japanese sardine in the 1980s and myctophids/sparkling enope squids in the 1990s-that were related to decadal shifts in the oceanographic regime. The sequential increase in mackerel and Japanese sardine abundances coincided with the annual catch trends of commercial fisheries. The index of overall prey availability calculated from the standardized occurrence probabilities of fishes and squids in fur seal stomachs was fairly stable over the decades.

  12. Amino