Toward the quantification of a conceptual framework for movement ecology using circular statistical modeling.

Science.gov (United States)

Shimatani, Ichiro Ken; Yoda, Ken; Katsumata, Nobuhiro; Sato, Katsufumi

2012-01-01

To analyze an animal's movement trajectory, a basic model is required that satisfies the following conditions: the model must have an ecological basis and the parameters used in the model must have ecological interpretations, a broad range of movement patterns can be explained by that model, and equations and probability distributions in the model should be mathematically tractable. Random walk models used in previous studies do not necessarily satisfy these requirements, partly because movement trajectories are often more oriented or tortuous than expected from the models. By improving the modeling for turning angles, this study aims to propose a basic movement model. On the basis of the recently developed circular auto-regressive model, we introduced a new movement model and extended its applicability to capture the asymmetric effects of external factors such as wind. The model was applied to GPS trajectories of a seabird (Calonectris leucomelas) to demonstrate its applicability to various movement patterns and to explain how the model parameters are ecologically interpreted under a general conceptual framework for movement ecology. Although it is based on a simple extension of a generalized linear model to circular variables, the proposed model enables us to evaluate the effects of external factors on movement separately from the animal's internal state. For example, maximum likelihood estimates and model selection suggested that in one homing flight section, the seabird intended to fly toward the island, but misjudged its navigation and was driven off-course by strong winds, while in the subsequent flight section, the seabird reset the focal direction, navigated the flight under strong wind conditions, and succeeded in approaching the island.

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling.

Science.gov (United States)

Cressie, Noel; Calder, Catherine A; Clark, James S; Ver Hoef, Jay M; Wikle, Christopher K

2009-04-01

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Homogenization of Large-Scale Movement Models in Ecology

Science.gov (United States)

Garlick, M.J.; Powell, J.A.; Hooten, M.B.; McFarlane, L.R.

2011-01-01

A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10-100 m) habitat variability on large scale (10-100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models. ?? 2010 Society for Mathematical Biology.

Investigating ecological speciation in non-model organisms

DEFF Research Database (Denmark)

Foote, Andrew David

2012-01-01

Background: Studies of ecological speciation tend to focus on a few model biological systems. In contrast, few studies on non-model organisms have been able to infer ecological speciation as the underlying mechanism of evolutionary divergence. Questions: What are the pitfalls in studying ecological...... speciation in non-model organisms that lead to this bias? What alternative approaches might redress the balance? Organism: Genetically differentiated types of the killer whale (Orcinus orca) exhibiting differences in prey preference, habitat use, morphology, and behaviour. Methods: Review of the literature...... on killer whale evolutionary ecology in search of any difficulty in demonstrating causal links between variation in phenotype, ecology, and reproductive isolation in this non-model organism. Results: At present, we do not have enough evidence to conclude that adaptive phenotype traits linked to ecological...

Bridging the gap between theoretical ecology and real ecosystems: modeling invertebrate community composition in streams.

Science.gov (United States)

Schuwirth, Nele; Reichert, Peter

2013-02-01

For the first time, we combine concepts of theoretical food web modeling, the metabolic theory of ecology, and ecological stoichiometry with the use of functional trait databases to predict the coexistence of invertebrate taxa in streams. We developed a mechanistic model that describes growth, death, and respiration of different taxa dependent on various environmental influence factors to estimate survival or extinction. Parameter and input uncertainty is propagated to model results. Such a model is needed to test our current quantitative understanding of ecosystem structure and function and to predict effects of anthropogenic impacts and restoration efforts. The model was tested using macroinvertebrate monitoring data from a catchment of the Swiss Plateau. Even without fitting model parameters, the model is able to represent key patterns of the coexistence structure of invertebrates at sites varying in external conditions (litter input, shading, water quality). This confirms the suitability of the model concept. More comprehensive testing and resulting model adaptations will further increase the predictive accuracy of the model.

SPOTting Model Parameters Using a Ready-Made Python Package.

Directory of Open Access Journals (Sweden)

Tobias Houska

Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.

Vegetation-specific model parameters are not required for estimating gross primary production

Czech Academy of Sciences Publication Activity Database

Yuan, W.; Cai, W.; Liu, S.; Dong, W.; Chen, J.; Altaf Arain, M.; Blanken, P. D.; Cescatti, A.; Wohlfahrt, G.; Georgiadis, T.; Genesio, L.; Gianelle, D.; Grelle, A.; Kiely, G.; Knohl, A.; Liu, D.; Marek, Michal V.; Merbold, L.; Montagnani, L.; Panferov, O.; Peltoniemi, M.; Rambal, S.; Raschi, A.; Varlagin, A.; Xia, J.

2014-01-01

Roč. 292, NOV 24 2014 (2014), s. 1-10 ISSN 0304-3800 Institutional support: RVO:67179843 Keywords : light use efficiency * gross primary production * model parameters Subject RIV: EH - Ecology, Behaviour Impact factor: 2.321, year: 2014

Scale of association: hierarchical linear models and the measurement of ecological systems

Science.gov (United States)

Sean M. McMahon; Jeffrey M. Diez

2007-01-01

A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance-covariance parameters in hierarchically structured...

Optimization of exploring well laying place from parameter of regional ecological protection point of view

International Nuclear Information System (INIS)

Khairov, G.B.

1997-01-01

In this article an influence of petroleum industry and especially discovery of hydrocarbon deposits with high content of hydrogen sulfide to ecological safety and environment is shown. New criteria for zoning and geological estimation are presented. For the first time a parameter of territory ecological protection is offered. (author)

Quantitative retrieving forest ecological parameters based on remote sensing in Liping County of China

Science.gov (United States)

Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying

2006-09-01

Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.

MELA: Modelling in Ecology with Location Attributes

Directory of Open Access Journals (Sweden)

Ludovica Luisa Vissat

2016-10-01

Full Text Available Ecology studies the interactions between individuals, species and the environment. The ability to predict the dynamics of ecological systems would support the design and monitoring of control strategies and would help to address pressing global environmental issues. It is also important to plan for efficient use of natural resources and maintenance of critical ecosystem services. The mathematical modelling of ecological systems often includes nontrivial specifications of processes that influence the birth, death, development and movement of individuals in the environment, that take into account both biotic and abiotic interactions. To assist in the specification of such models, we introduce MELA, a process algebra for Modelling in Ecology with Location Attributes. Process algebras allow the modeller to describe concurrent systems in a high-level language. A key feature of concurrent systems is that they are composed of agents that can progress simultaneously but also interact - a good match to ecological systems. MELA aims to provide ecologists with a straightforward yet flexible tool for modelling ecological systems, with particular emphasis on the description of space and the environment. Here we present four example MELA models, illustrating the different spatial arrangements which can be accommodated and demonstrating the use of MELA in epidemiological and predator-prey scenarios.

Pattern-oriented modelling: a 'multi-scope' for predictive systems ecology.

Science.gov (United States)

Grimm, Volker; Railsback, Steven F

2012-01-19

Modern ecology recognizes that modelling systems across scales and at multiple levels-especially to link population and ecosystem dynamics to individual adaptive behaviour-is essential for making the science predictive. 'Pattern-oriented modelling' (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.

Sensitivity of ecological soil-screening levels for metals to exposure model parameterization and toxicity reference values.

Science.gov (United States)

Sample, Bradley E; Fairbrother, Anne; Kaiser, Ashley; Law, Sheryl; Adams, Bill

2014-10-01

Ecological soil-screening levels (Eco-SSLs) were developed by the United States Environmental Protection Agency (USEPA) for the purposes of setting conservative soil screening values that can be used to eliminate the need for further ecological assessment for specific analytes at a given site. Ecological soil-screening levels for wildlife represent a simplified dietary exposure model solved in terms of soil concentrations to produce exposure equal to a no-observed-adverse-effect toxicity reference value (TRV). Sensitivity analyses were performed for 6 avian and mammalian model species, and 16 metals/metalloids for which Eco-SSLs have been developed. The relative influence of model parameters was expressed as the absolute value of the range of variation observed in the resulting soil concentration when exposure is equal to the TRV. Rank analysis of variance was used to identify parameters with greatest influence on model output. For both birds and mammals, soil ingestion displayed the broadest overall range (variability), although TRVs consistently had the greatest influence on calculated soil concentrations; bioavailability in food was consistently the least influential parameter, although an important site-specific variable. Relative importance of parameters differed by trophic group. Soil ingestion ranked 2nd for carnivores and herbivores, but was 4th for invertivores. Different patterns were exhibited, depending on which parameter, trophic group, and analyte combination was considered. The approach for TRV selection was also examined in detail, with Cu as the representative analyte. The underlying assumption that generic body-weight-normalized TRVs can be used to derive protective levels for any species is not supported by the data. Whereas the use of site-, species-, and analyte-specific exposure parameters is recommended to reduce variation in exposure estimates (soil protection level), improvement of TRVs is more problematic. © 2014 The Authors

Identifying mechanisms that structure ecological communities by snapping model parameters to empirically observed tradeoffs.

Science.gov (United States)

Thomas Clark, Adam; Lehman, Clarence; Tilman, David

2018-04-01

Theory predicts that interspecific tradeoffs are primary determinants of coexistence and community composition. Using information from empirically observed tradeoffs to augment the parametrisation of mechanism-based models should therefore improve model predictions, provided that tradeoffs and mechanisms are chosen correctly. We developed and tested such a model for 35 grassland plant species using monoculture measurements of three species characteristics related to nitrogen uptake and retention, which previous experiments indicate as important at our site. Matching classical theoretical expectations, these characteristics defined a distinct tradeoff surface, and models parameterised with these characteristics closely matched observations from experimental multi-species mixtures. Importantly, predictions improved significantly when we incorporated information from tradeoffs by 'snapping' characteristics to the nearest location on the tradeoff surface, suggesting that the tradeoffs and mechanisms we identify are important determinants of local community structure. This 'snapping' method could therefore constitute a broadly applicable test for identifying influential tradeoffs and mechanisms. © 2018 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Applied systems ecology: models, data, and statistical methods

Energy Technology Data Exchange (ETDEWEB)

Eberhardt, L L

1976-01-01

In this report, systems ecology is largely equated to mathematical or computer simulation modelling. The need for models in ecology stems from the necessity to have an integrative device for the diversity of ecological data, much of which is observational, rather than experimental, as well as from the present lack of a theoretical structure for ecology. Different objectives in applied studies require specialized methods. The best predictive devices may be regression equations, often non-linear in form, extracted from much more detailed models. A variety of statistical aspects of modelling, including sampling, are discussed. Several aspects of population dynamics and food-chain kinetics are described, and it is suggested that the two presently separated approaches should be combined into a single theoretical framework. It is concluded that future efforts in systems ecology should emphasize actual data and statistical methods, as well as modelling.

Investigation of ecological parameters of four-stroke SI engine, with pneumatic fuel injection system

Science.gov (United States)

Marek, W.; Śliwiński, K.

2016-09-01

The publication presents the results of tests to determine the impact of using waste fuels, alcohol, to power the engine, on the ecological parameters of the combustion engine. Alternatively fuelled with a mixture of iso- and n-butanol, indicated with "X" and "END, and gasoline and a mixture of fuel and alcohol. The object of the study was a four-stroke engine with spark ignition designed to work with a generator. Motor power was held by the modified system of pneumatic injection using hot exhaust gases developed by Prof. Stanislaw Jarnuszkiewicz, controlled by modern mechatronic systems. Tests were conducted at a constant speed for the intended use of the engine. The subject of the research was to determine the control parameters such as ignition timing, mixture composition and the degree of exhaust gas recirculation on the ecological parameters of the engine. Tests were carried out using partially quality power control. In summary we present the findings of this phase of the study.

EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model

Science.gov (United States)

MA, S.; Huang, Y.; Stacy, M.; Jiang, J.; Sundi, N.; Ricciuto, D. M.; Hanson, P. J.; Luo, Y.; Saruta, V.

2017-12-01

Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our study presents a smart system - Ecological Platform for Assimilation of Data (EcoPAD) - which streamlines web request-response, data management, model execution, result storage and visualization. EcoPAD allows users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, (v) conduct ecological forecasting, and (vi) detect ecosystem acclimation to climate change. One of the key innovations of the web-based EcoPAD is the automated near- or real-time forecasting of ecosystem dynamics with uncertainty fully quantified. The user friendly webpage enables non-modelers to explore their data for simulation and data assimilation. As a case study, we applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment project in the northern peatland, assimilated multiple data streams into a process based ecosystem model, enhanced timely feedback between modelers and experimenters, ultimately improved ecosystem forecasting and made better use of current knowledge. Built in a framework with flexible API, EcoPAD is easily portable and will benefit scientific communities, policy makers as well as the general public.

A simple model of bipartite cooperation for ecological and organizational networks.

Science.gov (United States)

Saavedra, Serguei; Reed-Tsochas, Felix; Uzzi, Brian

2009-01-22

In theoretical ecology, simple stochastic models that satisfy two basic conditions about the distribution of niche values and feeding ranges have proved successful in reproducing the overall structural properties of real food webs, using species richness and connectance as the only input parameters. Recently, more detailed models have incorporated higher levels of constraint in order to reproduce the actual links observed in real food webs. Here, building on previous stochastic models of consumer-resource interactions between species, we propose a highly parsimonious model that can reproduce the overall bipartite structure of cooperative partner-partner interactions, as exemplified by plant-animal mutualistic networks. Our stochastic model of bipartite cooperation uses simple specialization and interaction rules, and only requires three empirical input parameters. We test the bipartite cooperation model on ten large pollination data sets that have been compiled in the literature, and find that it successfully replicates the degree distribution, nestedness and modularity of the empirical networks. These properties are regarded as key to understanding cooperation in mutualistic networks. We also apply our model to an extensive data set of two classes of company engaged in joint production in the garment industry. Using the same metrics, we find that the network of manufacturer-contractor interactions exhibits similar structural patterns to plant-animal pollination networks. This surprising correspondence between ecological and organizational networks suggests that the simple rules of cooperation that generate bipartite networks may be generic, and could prove relevant in many different domains, ranging from biological systems to human society.

Overview of climate information needs for ecological effects models

Energy Technology Data Exchange (ETDEWEB)

Peer, R.L.

1990-01-01

Atmospheric scientists engaged in climate change research require a basic understanding of how ecological effects models incorporate climate. The report provides an overview of existing ecological models that might be used to model climate change effects on vegetation. Some agricultural models and statistical methods are also discussed. The weather input data requirements, weather simulation methods, and other model characteristics relevant to climate change research are described for a selected number of models. The ecological models are classified as biome, ecosystem, or tree models; the ecosystem models are further subdivided into species dynamics or process models. In general, ecological modelers have had to rely on readily available meteorological data such as temperature and rainfall. Although models are becoming more sophisticated in their treatment of weather and require more kinds of data (such as wind, solar radiation, or potential evapotranspiration), modelers are still hampered by a lack of data for many applications. Future directions of ecological effects models and the climate variables that will be required by the models are discussed.

Estimation methods for nonlinear state-space models in ecology

DEFF Research Database (Denmark)

Pedersen, Martin Wæver; Berg, Casper Willestofte; Thygesen, Uffe Høgsbro

2011-01-01

The use of nonlinear state-space models for analyzing ecological systems is increasing. A wide range of estimation methods for such models are available to ecologists, however it is not always clear, which is the appropriate method to choose. To this end, three approaches to estimation in the theta...... logistic model for population dynamics were benchmarked by Wang (2007). Similarly, we examine and compare the estimation performance of three alternative methods using simulated data. The first approach is to partition the state-space into a finite number of states and formulate the problem as a hidden...... Markov model (HMM). The second method uses the mixed effects modeling and fast numerical integration framework of the AD Model Builder (ADMB) open-source software. The third alternative is to use the popular Bayesian framework of BUGS. The study showed that state and parameter estimation performance...

Agent-based modeling in ecological economics.

Science.gov (United States)

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

Ecological models and pesticide risk assessment: current modeling practice.

Science.gov (United States)

Schmolke, Amelie; Thorbek, Pernille; Chapman, Peter; Grimm, Volker

2010-04-01

Ecological risk assessments of pesticides usually focus on risk at the level of individuals, and are carried out by comparing exposure and toxicological endpoints. However, in most cases the protection goal is populations rather than individuals. On the population level, effects of pesticides depend not only on exposure and toxicity, but also on factors such as life history characteristics, population structure, timing of application, presence of refuges in time and space, and landscape structure. Ecological models can integrate such factors and have the potential to become important tools for the prediction of population-level effects of exposure to pesticides, thus allowing extrapolations, for example, from laboratory to field. Indeed, a broad range of ecological models have been applied to chemical risk assessment in the scientific literature, but so far such models have only rarely been used to support regulatory risk assessments of pesticides. To better understand the reasons for this situation, the current modeling practice in this field was assessed in the present study. The scientific literature was searched for relevant models and assessed according to nine characteristics: model type, model complexity, toxicity measure, exposure pattern, other factors, taxonomic group, risk assessment endpoint, parameterization, and model evaluation. The present study found that, although most models were of a high scientific standard, many of them would need modification before they are suitable for regulatory risk assessments. The main shortcomings of currently available models in the context of regulatory pesticide risk assessments were identified. When ecological models are applied to regulatory risk assessments, we recommend reviewing these models according to the nine characteristics evaluated here. (c) 2010 SETAC.

Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

Science.gov (United States)

Grimm, Volker; Railsback, Steven F.

2012-01-01

Modern ecology recognizes that modelling systems across scales and at multiple levels—especially to link population and ecosystem dynamics to individual adaptive behaviour—is essential for making the science predictive. ‘Pattern-oriented modelling’ (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions. PMID:22144392

A Conceptual Framework for Evaluating the Domains of Applicability of Ecological Models and its Implementation in the Ecological Production Function Library - International Society for Ecological Modelling Conference

Science.gov (United States)

The use of computational ecological models to inform environmental management and policy has proliferated in the past 25 years. These models have become essential tools as linkages and feedbacks between human actions and ecological responses can be complex, and as funds for sampl...

Lumped-parameter models

Energy Technology Data Exchange (ETDEWEB)

Ibsen, Lars Bo; Liingaard, M.

2006-12-15

A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)

Dynamically linking economic models to ecological condition for coastal zone management: Application to sustainable tourism planning.

Science.gov (United States)

Dvarskas, Anthony

2017-03-01

While the development of the tourism industry can bring economic benefits to an area, it is important to consider the long-run impact of the industry on a given location. Particularly when the tourism industry relies upon a certain ecological state, those weighing different development options need to consider the long-run impacts of increased tourist numbers upon measures of ecological condition. This paper presents one approach for linking a model of recreational visitor behavior with an ecological model that estimates the impact of the increased visitors upon the environment. Two simulations were run for the model using initial parameters available from survey data and water quality data for beach locations in Croatia. Results suggest that the resilience of a given tourist location to the changes brought by increasing tourism numbers is important in determining its long-run sustainability. Further work should investigate additional model components, including the tourism industry, refinement of the relationships assumed by the model, and application of the proposed model in additional areas. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States

Science.gov (United States)

Wu, Yiping; Liu, Shuguang; Li, Zhengpeng; Dahal, Devendra; Young, Claudia J.; Schmidt, Gail L.; Liu, Jinxun; Davis, Brian; Sohl, Terry L.; Werner, Jeremy M.; Oeding, Jennifer

2014-01-01

Process-oriented ecological models are frequently used for predicting potential impacts of global changes such as climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automatically derive optimal parameter values at different scales, especially at regional scale, and validate the model performance. In this study, we developed an automatic calibration (auto-calibration) function for a well-established biogeochemical model—the General Ensemble Biogeochemical Modeling System (GEMS)-Erosion Deposition Carbon Model (EDCM)—using data assimilation technique: the Shuffled Complex Evolution algorithm and a model-inversion R package—Flexible Modeling Environment (FME). The new functionality can support multi-parameter and multi-objective auto-calibration of EDCM at the both pixel and regional levels. We also developed a post-processing procedure for GEMS to provide options to save the pixel-based or aggregated county-land cover specific parameter values for subsequent simulations. In our case study, we successfully applied the updated model (EDCM-Auto) for a single crop pixel with a corn–wheat rotation and a large ecological region (Level II)—Central USA Plains. The evaluation results indicate that EDCM-Auto is applicable at multiple scales and is capable to handle land cover changes (e.g., crop rotations). The model also performs well in capturing the spatial pattern of grain yield production for crops and net primary production (NPP) for other ecosystems across the region, which is a good example for implementing calibration and validation of ecological models with readily available survey data (grain yield) and remote sensing data (NPP) at regional and national levels. The developed platform for auto-calibration can be readily expanded to incorporate other model inversion algorithms and potential R packages, and also be applied to other ecological models.

The logic of ecological patchiness.

Science.gov (United States)

Grünbaum, Daniel

2012-04-06

Most ecological interactions occur in environments that are spatially and temporally heterogeneous-'patchy'-across a wide range of scales. In contrast, most theoretical models of ecological interactions, especially large-scale models applied to societal issues such as climate change, resource management and human health, are based on 'mean field' approaches in which the underlying patchiness of interacting consumers and resources is intentionally averaged out. Mean field ecological models typically have the advantages of tractability, few parameters and clear interpretation; more technically complex spatially explicit models, which resolve ecological patchiness at some (or all relevant) scales, generally lack these advantages. This report presents a heuristic analysis that incorporates important elements of consumer-resource patchiness with minimal technical complexity. The analysis uses scaling arguments to establish conditions under which key mechanisms-movement, reproduction and consumption-strongly affect consumer-resource interactions in patchy environments. By very general arguments, the relative magnitudes of these three mechanisms are quantified by three non-dimensional ecological indices: the Frost, Strathmann and Lessard numbers. Qualitative analysis based on these ecological indices provides a basis for conjectures concerning the expected characteristics of organisms, species interactions and ecosystems in patchy environments.

Quantifying chaos for ecological stoichiometry.

Science.gov (United States)

Duarte, Jorge; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2010-09-01

The theory of ecological stoichiometry considers ecological interactions among species with different chemical compositions. Both experimental and theoretical investigations have shown the importance of species composition in the outcome of the population dynamics. A recent study of a theoretical three-species food chain model considering stoichiometry [B. Deng and I. Loladze, Chaos 17, 033108 (2007)] shows that coexistence between two consumers predating on the same prey is possible via chaos. In this work we study the topological and dynamical measures of the chaotic attractors found in such a model under ecological relevant parameters. By using the theory of symbolic dynamics, we first compute the topological entropy associated with unimodal Poincaré return maps obtained by Deng and Loladze from a dimension reduction. With this measure we numerically prove chaotic competitive coexistence, which is characterized by positive topological entropy and positive Lyapunov exponents, achieved when the first predator reduces its maximum growth rate, as happens at increasing δ1. However, for higher values of δ1 the dynamics become again stable due to an asymmetric bubble-like bifurcation scenario. We also show that a decrease in the efficiency of the predator sensitive to prey's quality (increasing parameter ζ) stabilizes the dynamics. Finally, we estimate the fractal dimension of the chaotic attractors for the stoichiometric ecological model.

Forensic Entomology: Evaluating Uncertainty Associated With Postmortem Interval (PMI) Estimates With Ecological Models.

Science.gov (United States)

Faris, A M; Wang, H-H; Tarone, A M; Grant, W E

2016-05-31

Estimates of insect age can be informative in death investigations and, when certain assumptions are met, can be useful for estimating the postmortem interval (PMI). Currently, the accuracy and precision of PMI estimates is unknown, as error can arise from sources of variation such as measurement error, environmental variation, or genetic variation. Ecological models are an abstract, mathematical representation of an ecological system that can make predictions about the dynamics of the real system. To quantify the variation associated with the pre-appearance interval (PAI), we developed an ecological model that simulates the colonization of vertebrate remains by Cochliomyia macellaria (Fabricius) (Diptera: Calliphoridae), a primary colonizer in the southern United States. The model is based on a development data set derived from a local population and represents the uncertainty in local temperature variability to address PMI estimates at local sites. After a PMI estimate is calculated for each individual, the model calculates the maximum, minimum, and mean PMI, as well as the range and standard deviation for stadia collected. The model framework presented here is one manner by which errors in PMI estimates can be addressed in court when no empirical data are available for the parameter of interest. We show that PAI is a potential important source of error and that an ecological model is one way to evaluate its impact. Such models can be re-parameterized with any development data set, PAI function, temperature regime, assumption of interest, etc., to estimate PMI and quantify uncertainty that arises from specific prediction systems. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A coregionalization model can assist specification of Geographically Weighted Poisson Regression: Application to an ecological study.

Science.gov (United States)

Ribeiro, Manuel Castro; Sousa, António Jorge; Pereira, Maria João

2016-05-01

The geographical distribution of health outcomes is influenced by socio-economic and environmental factors operating on different spatial scales. Geographical variations in relationships can be revealed with semi-parametric Geographically Weighted Poisson Regression (sGWPR), a model that can combine both geographically varying and geographically constant parameters. To decide whether a parameter should vary geographically, two models are compared: one in which all parameters are allowed to vary geographically and one in which all except the parameter being evaluated are allowed to vary geographically. The model with the lower corrected Akaike Information Criterion (AICc) is selected. Delivering model selection exclusively according to the AICc might hide important details in spatial variations of associations. We propose assisting the decision by using a Linear Model of Coregionalization (LMC). Here we show how LMC can refine sGWPR on ecological associations between socio-economic and environmental variables and low birth weight outcomes in the west-north-central region of Portugal. Copyright © 2016 Elsevier Ltd. All rights reserved.

When mechanism matters: Bayesian forecasting using models of ecological diffusion

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.; Russell, Robin E.; Walsh, Daniel P.; Powell, James A.

2017-01-01

Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

Spatial extrapolation of light use efficiency model parameters to predict gross primary production

Directory of Open Access Journals (Sweden)

Karsten Schulz

2011-12-01

Full Text Available To capture the spatial and temporal variability of the gross primary production as a key component of the global carbon cycle, the light use efficiency modeling approach in combination with remote sensing data has shown to be well suited. Typically, the model parameters, such as the maximum light use efficiency, are either set to a universal constant or to land class dependent values stored in look-up tables. In this study, we employ the machine learning technique support vector regression to explicitly relate the model parameters of a light use efficiency model calibrated at several FLUXNET sites to site-specific characteristics obtained by meteorological measurements, ecological estimations and remote sensing data. A feature selection algorithm extracts the relevant site characteristics in a cross-validation, and leads to an individual set of characteristic attributes for each parameter. With this set of attributes, the model parameters can be estimated at sites where a parameter calibration is not possible due to the absence of eddy covariance flux measurement data. This will finally allow a spatially continuous model application. The performance of the spatial extrapolation scheme is evaluated with a cross-validation approach, which shows the methodology to be well suited to recapture the variability of gross primary production across the study sites.

Introduction to Hierarchical Bayesian Modeling for Ecological Data

CERN Document Server

Parent, Eric

2012-01-01

Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It also helps readers get started on building their own statistical models. The text begins with simple models that progressively become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the authors gradually present the concepts a

An analytically tractable model for community ecology with many species

Science.gov (United States)

Dickens, Benjamin; Fisher, Charles; Mehta, Pankaj; Pankaj Mehta Biophysics Theory Group Team

A fundamental problem in community ecology is to understand how ecological processes such as selection, drift, and immigration yield observed patterns in species composition and diversity. Here, we present an analytically tractable, presence-absence (PA) model for community assembly and use it to ask how ecological traits such as the strength of competition, diversity in competition, and stochasticity affect species composition in a community. In our PA model, we treat species as stochastic binary variables that can either be present or absent in a community: species can immigrate into the community from a regional species pool and can go extinct due to competition and stochasticity. Despite its simplicity, the PA model reproduces the qualitative features of more complicated models of community assembly. In agreement with recent work on large, competitive Lotka-Volterra systems, the PA model exhibits distinct ecological behaviors organized around a special (``critical'') point corresponding to Hubbell's neutral theory of biodiversity. Our results suggest that the concepts of ``phases'' and phase diagrams can provide a powerful framework for thinking about community ecology and that the PA model captures the essential ecological dynamics of community assembly. Pm was supported by a Simons Investigator in the Mathematical Modeling of Living Systems and a Sloan Research Fellowship.

Putting the "Ecology" into Environmental Flows: Ecological Dynamics and Demographic Modelling

Science.gov (United States)

Shenton, Will; Bond, Nicholas R.; Yen, Jian D. L.; Mac Nally, Ralph

2012-07-01

There have been significant diversions of water from rivers and streams around the world; natural flow regimes have been perturbed by dams, barriers and excessive extractions. Many aspects of the ecological `health' of riverine systems have declined due to changes in water flows, which has stimulated the development of thinking about the maintenance and restoration of these systems, which we refer to as environmental flow methodologies (EFMs). Most existing EFMs cannot deliver information on the population viability of species because they: (1) use habitat suitability as a proxy for population status; (2) use historical time series (usually of short duration) to forecast future conditions and flow sequences; (3) cannot, or do not, handle extreme flow events associated with climate variability; and (4) assume process stationarity for flow sequences, which means the past sequences are treated as good indicators of the future. These assumptions undermine the capacity of EFMs to properly represent risks associated with different flow management options; assumption (4) is untenable given most climate-change predictions. We discuss these concerns and advocate the use of demographic modelling as a more appropriate tool for linking population dynamics to flow regime change. A `meta-species' approach to demographic modelling is discussed as a useful step from habitat based models towards modelling strategies grounded in ecological theory when limited data are available on flow-demographic relationships. Data requirements of demographic models will undoubtedly expose gaps in existing knowledge, but, in so doing, will strengthen future efforts to link changes in river flows with their ecological consequences.

Putting the "ecology" into environmental flows: ecological dynamics and demographic modelling.

Science.gov (United States)

Shenton, Will; Bond, Nicholas R; Yen, Jian D L; Mac Nally, Ralph

2012-07-01

There have been significant diversions of water from rivers and streams around the world; natural flow regimes have been perturbed by dams, barriers and excessive extractions. Many aspects of the ecological 'health' of riverine systems have declined due to changes in water flows, which has stimulated the development of thinking about the maintenance and restoration of these systems, which we refer to as environmental flow methodologies (EFMs). Most existing EFMs cannot deliver information on the population viability of species because they: (1) use habitat suitability as a proxy for population status; (2) use historical time series (usually of short duration) to forecast future conditions and flow sequences; (3) cannot, or do not, handle extreme flow events associated with climate variability; and (4) assume process stationarity for flow sequences, which means the past sequences are treated as good indicators of the future. These assumptions undermine the capacity of EFMs to properly represent risks associated with different flow management options; assumption (4) is untenable given most climate-change predictions. We discuss these concerns and advocate the use of demographic modelling as a more appropriate tool for linking population dynamics to flow regime change. A 'meta-species' approach to demographic modelling is discussed as a useful step from habitat based models towards modelling strategies grounded in ecological theory when limited data are available on flow-demographic relationships. Data requirements of demographic models will undoubtedly expose gaps in existing knowledge, but, in so doing, will strengthen future efforts to link changes in river flows with their ecological consequences.

Soil and deforestation use standards in Amazon and its global impacts: a regional dynamics economic and ecological model

International Nuclear Information System (INIS)

Sherrill, Elisabeth I.

1999-01-01

The aim of the work was to introduce a simulation model to analyze the deforestation causes in Amazon. The work describes the basic parameters and fundamental concepts to the performed modeling comprehension. The several agents soil utilization standards were going observed and the economic and ecological interactions simulated. The global impact aspects are also analyzed

Quantum mechanical analogy for solving a competitive coexistence model in ecology

International Nuclear Information System (INIS)

Wio, H.S.; Kuperman, M.N.; Haeften, B. von

1994-07-01

We have studied an ecological system of three species: a strong and a weak one, competing for a single food resource, modelled as a reaction-diffusion process. An exact analytical solution has been found through a quantum mechanical analogy. Such solution indicates that in certain situations the classical results on extinction and coexistence of Lotka-Volterra type equations are no longer valid, essentially, as a consequence of the weak species mobility. A stability analysis of this solution against changes in different parameters has been carried out. (author). 19 refs, 5 figs

A laboratory-calibrated model of coho salmon growth with utility for ecological analyses

Science.gov (United States)

Manhard, Christopher V.; Som, Nicholas A.; Perry, Russell W.; Plumb, John M.

2018-01-01

We conducted a meta-analysis of laboratory- and hatchery-based growth data to estimate broadly applicable parameters of mass- and temperature-dependent growth of juvenile coho salmon (Oncorhynchus kisutch). Following studies of other salmonid species, we incorporated the Ratkowsky growth model into an allometric model and fit this model to growth observations from eight studies spanning ten different populations. To account for changes in growth patterns with food availability, we reparameterized the Ratkowsky model to scale several of its parameters relative to ration. The resulting model was robust across a wide range of ration allocations and experimental conditions, accounting for 99% of the variation in final body mass. We fit this model to growth data from coho salmon inhabiting tributaries and constructed ponds in the Klamath Basin by estimating habitat-specific indices of food availability. The model produced evidence that constructed ponds provided higher food availability than natural tributaries. Because of their simplicity (only mass and temperature are required as inputs) and robustness, ration-varying Ratkowsky models have utility as an ecological tool for capturing growth in freshwater fish populations.

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

Science.gov (United States)

Ganju, Neil K.; Brush, Mark J.; Rashleigh, Brenda; Aretxabaleta, Alfredo L.; del Barrio, Pilar; Grear, Jason S.; Harris, Lora A.; Lake, Samuel J.; McCardell, Grant; O'Donnell, James; Ralston, David K.; Signell, Richard P.; Testa, Jeremy; Vaudrey, Jamie M. P.

2016-01-01

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Ecological plant epigenetics: Evidence from model and non-model species, and the way forward.

Science.gov (United States)

Richards, Christina L; Alonso, Conchita; Becker, Claude; Bossdorf, Oliver; Bucher, Etienne; Colomé-Tatché, Maria; Durka, Walter; Engelhardt, Jan; Gaspar, Bence; Gogol-Döring, Andreas; Grosse, Ivo; van Gurp, Thomas P; Heer, Katrin; Kronholm, Ilkka; Lampei, Christian; Latzel, Vít; Mirouze, Marie; Opgenoorth, Lars; Paun, Ovidiu; Prohaska, Sonja J; Rensing, Stefan A; Stadler, Peter F; Trucchi, Emiliano; Ullrich, Kristian; Verhoeven, Koen J F

2017-12-01

Growing evidence shows that epigenetic mechanisms contribute to complex traits, with implications across many fields of biology. In plant ecology, recent studies have attempted to merge ecological experiments with epigenetic analyses to elucidate the contribution of epigenetics to plant phenotypes, stress responses, adaptation to habitat, and range distributions. While there has been some progress in revealing the role of epigenetics in ecological processes, studies with non-model species have so far been limited to describing broad patterns based on anonymous markers of DNA methylation. In contrast, studies with model species have benefited from powerful genomic resources, which contribute to a more mechanistic understanding but have limited ecological realism. Understanding the significance of epigenetics for plant ecology requires increased transfer of knowledge and methods from model species research to genomes of evolutionarily divergent species, and examination of responses to complex natural environments at a more mechanistic level. This requires transforming genomics tools specifically for studying non-model species, which is challenging given the large and often polyploid genomes of plants. Collaboration among molecular geneticists, ecologists and bioinformaticians promises to enhance our understanding of the mutual links between genome function and ecological processes. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Mathematical models of ecology and evolution

DEFF Research Database (Denmark)

Zhang, Lai

2012-01-01

-history processes: net-assimilation mechanism of 􀀀rule and net-reproduction mechanism of size dependence using a simple model comprising a size-structured consumer Daphina and an unstructured resource alge. It is found that in contrast to the former mechanism, the latter tends to destabilize population...... dynamics but as a trade-o promotes species survival by shortening juvenile delay between birth and the onset of reproduction. Paper II compares the size-spectrum and food-web representations of communities using two traits (body size and habitat location) based unstructured population model of Lotka......) based size-structured population model, that is, interference in foraging, maintenance, survival, and recruitment. Their impacts on the ecology and evolution of size-structured populations and communities are explored. Ecologically, interference aects population demographic properties either negatively...

Calibration and analysis of genome-based models for microbial ecology.

Science.gov (United States)

Louca, Stilianos; Doebeli, Michael

2015-10-16

Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.

Guide for developing conceptual models for ecological risk assessments

International Nuclear Information System (INIS)

Suter, G.W., II.

1996-05-01

Ecological conceptual models are the result of the problem formulation phase of an ecological risk assessment, which is an important component of the Remedial Investigation process. They present hypotheses of how the site contaminants might affect the site ecology. The contaminant sources, routes, media, routes, and endpoint receptors are presented in the form of a flow chart. This guide is for preparing the conceptual models; use of this guide will standardize the models so that they will be of high quality, useful to the assessment process, and sufficiently consistent so that connections between sources of exposure and receptors can be extended across operable units (OU). Generic conceptual models are presented for source, aquatic integrator, groundwater integrator, and terrestrial OUs

Automated Techniques for the Qualitative Analysis of Ecological Models: Continuous Models

Directory of Open Access Journals (Sweden)

Lynn van Coller

1997-06-01

Full Text Available The mathematics required for a detailed analysis of the behavior of a model can be formidable. In this paper, I demonstrate how various computer packages can aid qualitative analyses by implementing techniques from dynamical systems theory. Because computer software is used to obtain the results, the techniques can be used by nonmathematicians as well as mathematicians. In-depth analyses of complicated models that were previously very difficult to study can now be done. Because the paper is intended as an introduction to applying the techniques to ecological models, I have included an appendix describing some of the ideas and terminology. A second appendix shows how the techniques can be applied to a fairly simple predator-prey model and establishes the reliability of the computer software. The main body of the paper discusses a ratio-dependent model. The new techniques highlight some limitations of isocline analyses in this three-dimensional setting and show that the model is structurally unstable. Another appendix describes a larger model of a sheep-pasture-hyrax-lynx system. Dynamical systems techniques are compared with a traditional sensitivity analysis and are found to give more information. As a result, an incomplete relationship in the model is highlighted. I also discuss the resilience of these models to both parameter and population perturbations.

[Urban ecological risk assessment: a review].

Science.gov (United States)

Wang, Mei-E; Chen, Wei-Ping; Peng, Chi

2014-03-01

With the development of urbanization and the degradation of urban living environment, urban ecological risks caused by urbanization have attracted more and more attentions. Based on urban ecology principles and ecological risk assessment frameworks, contents of urban ecological risk assessment were reviewed in terms of driven forces, risk resources, risk receptors, endpoints and integrated approaches for risk assessment. It was suggested that types and degrees of urban economical and social activities were the driven forces for urban ecological risks. Ecological functional components at different levels in urban ecosystems as well as the urban system as a whole were the risk receptors. Assessment endpoints involved in changes of urban ecological structures, processes, functional components and the integrity of characteristic and function. Social-ecological models should be the major approaches for urban ecological risk assessment. Trends for urban ecological risk assessment study should focus on setting a definite protection target and criteria corresponding to assessment endpoints, establishing a multiple-parameter assessment system and integrative assessment approaches.

Advances and Limitations of Disease Biogeography Using Ecological Niche Modeling.

Science.gov (United States)

Escobar, Luis E; Craft, Meggan E

2016-01-01

Mapping disease transmission risk is crucial in public and animal health for evidence based decision-making. Ecology and epidemiology are highly related disciplines that may contribute to improvements in mapping disease, which can be used to answer health related questions. Ecological niche modeling is increasingly used for understanding the biogeography of diseases in plants, animals, and humans. However, epidemiological applications of niche modeling approaches for disease mapping can fail to generate robust study designs, producing incomplete or incorrect inferences. This manuscript is an overview of the history and conceptual bases behind ecological niche modeling, specifically as applied to epidemiology and public health; it does not pretend to be an exhaustive and detailed description of ecological niche modeling literature and methods. Instead, this review includes selected state-of-the-science approaches and tools, providing a short guide to designing studies incorporating information on the type and quality of the input data (i.e., occurrences and environmental variables), identification and justification of the extent of the study area, and encourages users to explore and test diverse algorithms for more informed conclusions. We provide a friendly introduction to the field of disease biogeography presenting an updated guide for researchers looking to use ecological niche modeling for disease mapping. We anticipate that ecological niche modeling will soon be a critical tool for epidemiologists aiming to map disease transmission risk, forecast disease distribution under climate change scenarios, and identify landscape factors triggering outbreaks.

SPOTting model parameters using a ready-made Python package

Science.gov (United States)

Houska, Tobias; Kraft, Philipp; Breuer, Lutz

2015-04-01

The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for

Ecological Niche Modelling of Bank Voles in Western Europe

Directory of Open Access Journals (Sweden)

Sara Amirpour Haredasht

2013-01-01

Full Text Available The bank vole (Myodes glareolus is the natural host of Puumala virus (PUUV in vast areas of Europe. PUUV is one of the hantaviruses which are transmitted to humans by infected rodents. PUUV causes a general mild form of hemorrhagic fever with renal syndrome (HFRS called nephropathia epidemica (NE. Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover influences disease transmission by controlling both the spatial distribution of vectors or hosts, as well as by facilitating the human contact with them. In this study the use of ecological niche modelling (ENM for predicting the geographical distribution of bank vole population on the basis of spatial climate information is tested. The Genetic Algorithm for Rule-set Prediction (GARP is used to model the ecological niche of bank voles in Western Europe. The meteorological data, land cover types and geo-referenced points representing the locations of the bank voles (latitude/longitude in the study area are used as the primary model input value. The predictive accuracy of the bank vole ecologic niche model was significant (training accuracy of 86%. The output of the GARP models based on the 50% subsets of points used for testing the model showed an accuracy of 75%. Compared with random models, the probability of such high predictivity was low (χ2 tests, p < 10−6. As such, the GARP models were predictive and the used ecologic niche model indeed indicates the ecologic requirements of bank voles. This approach successfully identified the areas of infection risk across the study area. The result suggests that the niche modelling approach can be implemented in a next step towards the development of new tools for monitoring the bank vole’s population.

Ecological niche modelling of bank voles in Western Europe.

Science.gov (United States)

Amirpour Haredasht, Sara; Barrios, Miguel; Farifteh, Jamshid; Maes, Piet; Clement, Jan; Verstraeten, Willem W; Tersago, Katrien; Van Ranst, Marc; Coppin, Pol; Berckmans, Daniel; Aerts, Jean-Marie

2013-01-28

The bank vole (Myodes glareolus) is the natural host of Puumala virus (PUUV) in vast areas of Europe. PUUV is one of the hantaviruses which are transmitted to humans by infected rodents. PUUV causes a general mild form of hemorrhagic fever with renal syndrome (HFRS) called nephropathia epidemica (NE). Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover influences disease transmission by controlling both the spatial distribution of vectors or hosts, as well as by facilitating the human contact with them. In this study the use of ecological niche modelling (ENM) for predicting the geographical distribution of bank vole population on the basis of spatial climate information is tested. The Genetic Algorithm for Rule-set Prediction (GARP) is used to model the ecological niche of bank voles in Western Europe. The meteorological data, land cover types and geo-referenced points representing the locations of the bank voles (latitude/longitude) in the study area are used as the primary model input value. The predictive accuracy of the bank vole ecologic niche model was significant (training accuracy of 86%). The output of the GARP models based on the 50% subsets of points used for testing the model showed an accuracy of 75%. Compared with random models, the probability of such high predictivity was low (χ(2) tests, p < 10(-6)). As such, the GARP models were predictive and the used ecologic niche model indeed indicates the ecologic requirements of bank voles. This approach successfully identified the areas of infection risk across the study area. The result suggests that the niche modelling approach can be implemented in a next step towards the development of new tools for monitoring the bank vole's population.

Including Overweight or Obese Students in Physical Education: A Social Ecological Constraint Model

Science.gov (United States)

Li, Weidong; Rukavina, Paul

2012-01-01

In this review, we propose a social ecological constraint model to study inclusion of overweight or obese students in physical education by integrating key concepts and assumptions from ecological constraint theory in motor development and social ecological models in health promotion and behavior. The social ecological constraint model proposes…

Interval Optimization Model Considering Terrestrial Ecological Impacts for Water Rights Transfer from Agriculture to Industry in Ningxia, China.

Science.gov (United States)

Sun, Lian; Li, Chunhui; Cai, Yanpeng; Wang, Xuan

2017-06-14

In this study, an interval optimization model is developed to maximize the benefits of a water rights transfer system that comprises industry and agriculture sectors in the Ningxia Hui Autonomous Region in China. The model is subjected to a number of constraints including water saving potential from agriculture and ecological groundwater levels. Ecological groundwater levels serve as performance indicators of terrestrial ecology. The interval method is applied to present the uncertainty of parameters in the model. Two scenarios regarding dual industrial development targets (planned and unplanned ones) are used to investigate the difference in potential benefits of water rights transfer. Runoff of the Yellow River as the source of water rights fluctuates significantly in different years. Thus, compensation fees for agriculture are calculated to reflect the influence of differences in the runoff. Results show that there are more available water rights to transfer for industrial development. The benefits are considerable but unbalanced between buyers and sellers. The government should establish a water market that is freer and promote the interest of agriculture and farmers. Though there has been some success of water rights transfer, the ecological impacts and the relationship between sellers and buyers require additional studies.

Adaptive long-term monitoring of soil health in metal phytostabilization: ecological attributes and ecosystem services based on soil microbial parameters.

Science.gov (United States)

Epelde, Lur; Becerril, José M; Alkorta, Itziar; Garbisu, Carlos

2014-01-01

Phytostabilization is a promising option for the remediation of metal contaminated soils which requires the implementation of long-term monitoring programs. We here propose to incorporate the paradigm of "adaptive monitoring", which enables monitoring programs to evolve iteratively as new information emerges and research questions change, to metal phytostabilization. Posing good questions that cover the chemical, toxicological and ecological concerns associated to metal contaminated soils is critical for an efficient long-term phytostabilization monitoring program. Regarding the ecological concerns, soil microbial parameters are most valuable indicators of the effectiveness of metal phytostabilization processes in terms of recovery of soil health. We suggest to group soil microbial parameters in higher-level categories such as "ecological attributes" (vigor, organization, stability) or "ecosystem services" in order to facilitate interpretation and, most importantly, to provide long-term phytostabilization monitoring programs with the required stability through time against changes in techniques, methods, interests, etc. that will inevitably occur during the monitoring program. Finally, a Phytostabilization Monitoring Card, based on both ecological attributes and ecosystem services, for soil microbial properties is provided.

An ecological process model of systems change.

Science.gov (United States)

Peirson, Leslea J; Boydell, Katherine M; Ferguson, H Bruce; Ferris, Lorraine E

2011-06-01

In June 2007 the American Journal of Community Psychology published a special issue focused on theories, methods and interventions for systems change which included calls from the editors and authors for theoretical advancement in this field. We propose a conceptual model of systems change that integrates familiar and fundamental community psychology principles (succession, interdependence, cycling of resources, adaptation) and accentuates a process orientation. To situate our framework we offer a definition of systems change and a brief review of the ecological perspective and principles. The Ecological Process Model of Systems Change is depicted, described and applied to a case example of policy driven systems level change in publicly funded social programs. We conclude by identifying salient implications for thinking and action which flow from the Model.

Beyond positivist ecology: toward an integrated ecological ethics.

Science.gov (United States)

Norton, Bryan G

2008-12-01

A post-positivist understanding of ecological science and the call for an "ecological ethic" indicate the need for a radically new approach to evaluating environmental change. The positivist view of science cannot capture the essence of environmental sciences because the recent work of "reflexive" ecological modelers shows that this requires a reconceptualization of the way in which values and ecological models interact in scientific process. Reflexive modelers are ecological modelers who believe it is appropriate for ecologists to examine the motives for their choices in developing models; this self-reflexive approach opens the door to a new way of integrating values into public discourse and to a more comprehensive approach to evaluating ecological change. This reflexive building of ecological models is introduced through the transformative simile of Aldo Leopold, which shows that learning to "think like a mountain" involves a shift in both ecological modeling and in values and responsibility. An adequate, interdisciplinary approach to ecological valuation, requires a re-framing of the evaluation questions in entirely new ways, i.e., a review of the current status of interdisciplinary value theory with respect to ecological values reveals that neither of the widely accepted theories of environmental value-neither economic utilitarianism nor intrinsic value theory (environmental ethics)-provides a foundation for an ecologically sensitive evaluation process. Thus, a new, ecologically sensitive, and more comprehensive approach to evaluating ecological change would include an examination of the metaphors that motivate the models used to describe environmental change.

Simulation of socio-ecological impacts: Modeling a fishing village

Science.gov (United States)

Miller, Philip C.

1982-03-01

The interrelationship of society and environment is addressed here through the study of a remote fishing village of 750 people. An interdisciplinary study evaluated demographic, economic, and social aspects of the community, and simulation modeling was used to integrate these societal characteristics with environmental factors. The population of the village had grown gradually until the 1960's, when a decline began. Out-migration correlated with declining fish harvests and with increased communications with urban centers. Fishing had provided the greatest economic opportunity, followed by logging. A survey was conducted to investigate the costs and revenues of village fishermen. Diversification characterized the local fleet, and analysis showed that rates of return on investment in the current year were equal between vessel types. The variable levels and rate parameters of the demographic, economic, and social components of the model were specified through static and time series data. Sensitivity analysis to assess the effects of uncertainty, and validation tests against known historical changes were also conducted. Forecast scenarios identified the development options under several levels of fish abundance and investment. The weight given to ecological versus economic resource management registered disproportionate effects due to the interaction between investment and migration rates and resource stochasticity. This finding argues against a “golden mean” rule for evaluating policy trade-offs and argues for the importance of using a dynamic, socio-ecological perspective in designing development policies for rural communities.

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.

Of Models and Meanings: Cultural Resilience in Social-Ecological Systems

Directory of Open Access Journals (Sweden)

Todd A. Crane

2010-12-01

Full Text Available Modeling has emerged as a key technology in analysis of social-ecological systems. However, the tendency for modeling to focus on the mechanistic materiality of biophysical systems obscures the diversity of performative social behaviors and normative cultural positions of actors within the modeled system. The fact that changes in the biophysical system can be culturally constructed in different ways means that the perception and pursuit of adaptive pathways can be highly variable. Furthermore, the adoption of biophysically resilient livelihoods can occur under conditions that are subjectively experienced as the radical transformation of cultural systems. The objectives of this work are to: (1 highlight the importance of understanding the place of culture within social-ecological systems, (2 explore the tensions between empirical and normative positions in the analysis of social-ecological resilience, and (3 suggest how empirical modeling of social-ecological systems can synergistically interact with normative aspects of livelihoods and lifeways.

System dynamic modelling of industrial growth and landscape ecology in China.

Science.gov (United States)

Xu, Jian; Kang, Jian; Shao, Long; Zhao, Tianyu

2015-09-15

With the rapid development of large industrial corridors in China, the landscape ecology of the country is currently being affected. Therefore, in this study, a system dynamic model with multi-dimensional nonlinear dynamic prediction function that considers industrial growth and landscape ecology is developed and verified to allow for more sustainable development. Firstly, relationships between industrial development and landscape ecology in China are examined, and five subsystems are then established: industry, population, urban economy, environment and landscape ecology. The main influencing factors are then examined for each subsystem to establish flow charts connecting those factors. Consequently, by connecting the subsystems, an overall industry growth and landscape ecology model is established. Using actual data and landscape index calculated based on GIS of the Ha-Da-Qi industrial corridor, a typical industrial corridor in China, over the period 2005-2009, the model is validated in terms of historical behaviour, logical structure and future prediction, where for 84.8% of the factors, the error rate of the model is less than 5%, the mean error rate of all factors is 2.96% and the error of the simulation test for the landscape ecology subsystem is less than 2%. Moreover, a model application has been made to consider the changes in landscape indices under four industrial development modes, and the optimal industrial growth plan has been examined for landscape ecological protection through the simulation prediction results over 2015-2020. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints

Science.gov (United States)

Andrew D. Richardson; Mathew Williams; David Y. Hollinger; David J.P. Moore; D. Bryan Dail; Eric A. Davidson; Neal A. Scott; Robert S. Evans; Holly. Hughes

2010-01-01

We conducted an inverse modeling analysis, using a variety of data streams (tower-based eddy covariance measurements of net ecosystem exchange, NEE, of CO2, chamber-based measurements of soil respiration, and ancillary ecological measurements of leaf area index, litterfall, and woody biomass increment) to estimate parameters and initial carbon (C...

On the general procedure for modelling complex ecological systems

International Nuclear Information System (INIS)

He Shanyu.

1987-12-01

In this paper, the principle of a general procedure for modelling complex ecological systems, i.e. the Adaptive Superposition Procedure (ASP) is shortly stated. The result of application of ASP in a national project for ecological regionalization is also described. (author). 3 refs

A Global Lake Ecological Observatory Network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

Science.gov (United States)

David, Hamilton P; Carey, Cayelan C.; Arvola, Lauri; Arzberger, Peter; Brewer, Carol A.; Cole, Jon J; Gaiser, Evelyn; Hanson, Paul C.; Ibelings, Bas W; Jennings, Eleanor; Kratz, Tim K; Lin, Fang-Pang; McBride, Christopher G.; de Motta Marques, David; Muraoka, Kohji; Nishri, Ami; Qin, Boqiang; Read, Jordan S.; Rose, Kevin C.; Ryder, Elizabeth; Weathers, Kathleen C.; Zhu, Guangwei; Trolle, Dennis; Brookes, Justin D

2014-01-01

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process- based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

Using circuit theory to model connectivity in ecology, evolution, and conservation.

Science.gov (United States)

McRae, Brad H; Dickson, Brett G; Keitt, Timothy H; Shah, Viral B

2008-10-01

Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.

Validation of ecological state space models using the Laplace approximation

DEFF Research Database (Denmark)

Thygesen, Uffe Høgsbro; Albertsen, Christoffer Moesgaard; Berg, Casper Willestofte

2017-01-01

Many statistical models in ecology follow the state space paradigm. For such models, the important step of model validation rarely receives as much attention as estimation or hypothesis testing, perhaps due to lack of available algorithms and software. Model validation is often based on a naive...... for estimation in general mixed effects models. Implementing one-step predictions in the R package Template Model Builder, we demonstrate that it is possible to perform model validation with little effort, even if the ecological model is multivariate, has non-linear dynamics, and whether observations...... useful directions in which the model could be improved....

Ecological connectivity networks in rapidly expanding cities

Directory of Open Access Journals (Sweden)

Amal Najihah M. Nor

2017-06-01

Full Text Available Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow (Passer montanus and Yellow-vented bulbul (Pycnonotus goiavier in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines. The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such

A brief introduction to mixed effects modelling and multi-model inference in ecology.

Science.gov (United States)

Harrison, Xavier A; Donaldson, Lynda; Correa-Cano, Maria Eugenia; Evans, Julian; Fisher, David N; Goodwin, Cecily E D; Robinson, Beth S; Hodgson, David J; Inger, Richard

2018-01-01

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

Contemporary Ecological Interactions Improve Models of Past Trait Evolution.

Science.gov (United States)

Hutchinson, Matthew C; Gaiarsa, Marília P; Stouffer, Daniel B

2018-02-20

Despite the fact that natural selection underlies both traits and interactions, evolutionary models often neglect that ecological interactions may, and in many cases do, influence the evolution of traits. Here, we explore the interdependence of ecological interactions and functional traits in the pollination associations of hawkmoths and flowering plants. Specifically, we develop an adaptation of the Ornstein-Uhlenbeck model of trait evolution that allows us to study the influence of plant corolla depth and observed hawkmoth-plant interactions on the evolution of hawkmoth proboscis length. Across diverse modelling scenarios, we find that the inclusion of contemporary interactions can provide a better description of trait evolution than the null expectation. Moreover, we show that the pollination interactions provide more-likely models of hawkmoth trait evolution when interactions are considered at increasingly finescale groups of hawkmoths. Finally, we demonstrate how the results of best-fit modelling approaches can implicitly support the association between interactions and trait evolution that our method explicitly examines. In showing that contemporary interactions can provide insight into the historical evolution of hawkmoth proboscis length, we demonstrate the clear utility of incorporating additional ecological information to models designed to study past trait evolution.

Identifying the effects of parameter uncertainty on the reliability of riverbank stability modelling

Science.gov (United States)

Samadi, A.; Amiri-Tokaldany, E.; Darby, S. E.

2009-05-01

Bank retreat is a key process in fluvial dynamics affecting a wide range of physical, ecological and socioeconomic issues in the fluvial environment. To predict the undesirable effects of bank retreat and to inform effective measures to prevent it, a wide range of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of driving and resisting forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the bank profile (bank height and angle), the geotechnical properties of the bank materials, as well as the hydrological status of the riverbanks. In this paper we evaluate the extent to which uncertainties in the parameterization of these controlling factors feed through to influence the reliability of the resulting bank stability estimate. This is achieved by employing a simple model of riverbank stability with respect to planar failure (which is the most common type of bank stability model) in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. These identified parameter value ranges are compared to empirically derived parameter uncertainties to determine whether they are likely to confound the reliability of the resulting bank stability calculations. Our results show that parameter uncertainties are typically high enough that the likelihood of generating unreliable predictions is typically very high (> ˜ 80% for predictions requiring a precision of < ± 15%). Because parameter uncertainties are derived primarily from the natural variability of the parameters, rather than measurement errors, much more careful attention should be paid to field sampling strategies, such that the parameter uncertainties and consequent prediction unreliabilities can be quantified more

Cognitive Comparisons of Students' Systems Modeling in Ecology

Science.gov (United States)

Hogan, Kathleen; Thomas, David

2001-12-01

This study examined the cognition of five pairs of high school students over time as they built quantitative ecological models using STELLA software. One pair of students emerged as being particularly proficient at learning to model, and was able to use models productively to explore and explain ecological system behaviors. We present detailed contrasts between this and the other pairs of students' cognitive behaviors while modeling, in three areas that were crucial to their modeling productivity: (a) focusing on model output and net interactions versus on model input and individual relationships when building and revising models, (b) exploring the nature and implications of dependencies and feedbacks versus just creating these as properties of complex systems, and (c) using variables versus constants to represent continuous and periodic functions. We then apply theories of the multifaceted nature of cognition to describe object-level, metalevel, and emotional dimensions of cognitive performance that help to explain the observed differences among students' approaches to STELLA modeling. Finally, we suggest pedagogical strategies for supporting all types of students in learning the central scientific practice of model-based quantitative thinking.

Quantitative predictions from competition theory with incomplete information on model parameters tested against experiments across diverse taxa

OpenAIRE

Fort, Hugo

2017-01-01

We derive an analytical approximation for making quantitative predictions for ecological communities as a function of the mean intensity of the inter-specific competition and the species richness. This method, with only a fraction of the model parameters (carrying capacities and competition coefficients), is able to predict accurately empirical measurements covering a wide variety of taxa (algae, plants, protozoa).

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.

Dynamic ecological-economic modeling approach for management of shellfish aquaculture

CSIR Research Space (South Africa)

Nobre, AM

2008-02-01

Full Text Available The objective of this report is to conceptualize ecological and economic interactions in mariculture; to implement a dynamic ecological-economic model in order to: simulate the socio-economics of aquaculture production, simulate its effects...

A Sense of Place: Integrating Environmental Psychology into Marine Socio-Ecological Models

Science.gov (United States)

van Putten, I. E.; Fleming, A.; Fulton, E.; Plaganyi-Lloyd, E.

2016-02-01

Sense of place is a concept that is increasingly applied in different social research contexts where it can act as a bridge between disciplines that might otherwise work in parallel. A sense of place is a well established and flexible concept that has been empirically measured using different survey methods. The psychological principals and theories that underpin sense of place have been inextricably linked to the quality of ecological systems and the impact on development of the system, and vice versa. Ecological models and scenario analyses play an important role in characterising, assessing and predicting the potential impacts of alternative developments and other changes affecting ecological systems. To improve the predictive accuracy of ecological models, human drivers, interactions, and uses have been dynamically incorporated, for instance, through management strategy evaluation applied to marine ecosystem models. However, to date no socio-ecological models (whether terrestrial or marine) have been developed that incorporate a dynamic feedback between ecosystem characteristics and peoples' sense of place. These models thus essentially ignore the influence of environmental psychology on the way people use and interact with ecosystems. We develop a proof of concept and provide a mathematical basis for a Sense of Place Index (SoPI) that allows the quantitative integration of environmental psychology into socio-ecological models. Incorporating dynamic feedback between the SoPI for different resource user groups and the ecological system improves the accuracy and precision of predictions regarding future resource use as well as, ultimately, the potential state of the resource to be developed.

Estimating demographic parameters using a combination of known-fate and open N-mixture models.

Science.gov (United States)

Schmidt, Joshua H; Johnson, Devin S; Lindberg, Mark S; Adams, Layne G

2015-10-01

Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark-resight data sets. We provide implementations in both the BUGS language and an R package.

[Altitude-belt zonality of wood vegetation within mountainous regions of the Sayan Mountains: a model of ecological second-order phase transitions ].

Science.gov (United States)

Sukhovol'skiĭ, V G; Ovchinnikova, T M; Baboĭ, S D

2014-01-01

As a description of altitude-belt zonality of wood vegetation, a model of ecological second-order transitions is proposed. Objects of the study have been chosen to be forest cenoses of the northern slope of Kulumyss Ridge (the Sayan Mauntains), while the results are comprised by the altitude profiles of wood vegetation. An ecological phase transition can be considered as the transition of cenoses at different altitudes from the state of presence of certain tree species within the studied territory to the state of their absence. By analogy with the physical model of second-order, phase transitions the order parameter is introduced (i.e., the area portion occupied by a single tree species at the certain altitude) as well as the control variable (i.e., the altitude of the wood vegetation belt). As the formal relation between them, an analog of the Landau's equation for phase transitions in physical systems is obtained. It is shown that the model is in a good accordance with the empirical data. Thus, the model can be used for estimation of upper and lower boundaries of altitude belts for individual tree species (like birch, aspen, Siberian fir, Siberian pine) as well as the breadth of their ecological niches with regard to altitude. The model includes also the parameters that describe numerically the interactions between different species of wood vegetation. The approach versatility allows to simplify description and modeling of wood vegetation altitude zonality, and enables assessment of vegetation cenoses response to climatic changes.

Ecological connectivity networks in rapidly expanding cities.

Science.gov (United States)

Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

2017-06-01

Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for

Increasing the reliability of ecological models using modern software engineering techniques

Science.gov (United States)

Robert M. Scheller; Brian R. Sturtevant; Eric J. Gustafson; Brendan C. Ward; David J. Mladenoff

2009-01-01

Modern software development techniques are largely unknown to ecologists. Typically, ecological models and other software tools are developed for limited research purposes, and additional capabilities are added later, usually in an ad hoc manner. Modern software engineering techniques can substantially increase scientific rigor and confidence in ecological models and...

Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

Science.gov (United States)

Royle, J. Andrew; Dorazio, Robert M.

2008-01-01

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

Framework for analyzing ecological trait-based models in multidimensional niche spaces

Science.gov (United States)

Biancalani, Tommaso; DeVille, Lee; Goldenfeld, Nigel

2015-05-01

We develop a theoretical framework for analyzing ecological models with a multidimensional niche space. Our approach relies on the fact that ecological niches are described by sequences of symbols, which allows us to include multiple phenotypic traits. Ecological drivers, such as competitive exclusion, are modeled by introducing the Hamming distance between two sequences. We show that a suitable transform diagonalizes the community interaction matrix of these models, making it possible to predict the conditions for niche differentiation and, close to the instability onset, the asymptotically long time population distributions of niches. We exemplify our method using the Lotka-Volterra equations with an exponential competition kernel.

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

A Conceptual Framework for Evaluating the Domains of Applicability of Ecological Models and its Implementation in the Ecological Production Function Library

Science.gov (United States)

The use of computational ecological models to inform environmental management and policy has proliferated in the past 25 years. These models have become essential tools as linkages and feedbacks between human actions and ecological responses can be complex, and as funds for sampl...

Stress and adaptation : Toward ecologically relevant animal models

NARCIS (Netherlands)

Koolhaas, Jaap M.; Boer, Sietse F. de; Buwalda, Bauke

Animal models have contributed considerably to the current understanding of mechanisms underlying the role of stress in health and disease. Despite the progress made already, much more can be made by more carefully exploiting animals' and humans' shared biology, using ecologically relevant models.

Stochastic dynamical models for ecological regime shifts

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Carstensen, Jacob; Madsen, Henrik

the physical and biological knowledge of the system, and nonlinearities introduced here can generate regime shifts or enhance the probability of regime shifts in the case of stochastic models, typically characterized by a threshold value for the known driver. A simple model for light competition between...... definition and stability of regimes become less subtle. Ecological regime shifts and their modeling must be viewed in a probabilistic manner, particularly if such model results are to be used in ecosystem management....

Rich dynamics of discrete delay ecological models

International Nuclear Information System (INIS)

Peng Mingshu

2005-01-01

We study multiple bifurcations and chaotic behavior of a discrete delay ecological model. New form of chaos for the 2-D map is observed: the combination of potential period doubling and reverse period-doubling leads to cascading bubbles

Integration of research infrastructures and ecosystem models toward development of predictive ecology

Science.gov (United States)

Luo, Y.; Huang, Y.; Jiang, J.; MA, S.; Saruta, V.; Liang, G.; Hanson, P. J.; Ricciuto, D. M.; Milcu, A.; Roy, J.

2017-12-01

The past two decades have witnessed rapid development in sensor technology. Built upon the sensor development, large research infrastructure facilities, such as National Ecological Observatory Network (NEON) and FLUXNET, have been established. Through networking different kinds of sensors and other data collections at many locations all over the world, those facilities generate large volumes of ecological data every day. The big data from those facilities offer an unprecedented opportunity for advancing our understanding of ecological processes, educating teachers and students, supporting decision-making, and testing ecological theory. The big data from the major research infrastructure facilities also provides foundation for developing predictive ecology. Indeed, the capability to predict future changes in our living environment and natural resources is critical to decision making in a world where the past is no longer a clear guide to the future. We are living in a period marked by rapid climate change, profound alteration of biogeochemical cycles, unsustainable depletion of natural resources, and deterioration of air and water quality. Projecting changes in future ecosystem services to the society becomes essential not only for science but also for policy making. We will use this panel format to outline major opportunities and challenges in integrating research infrastructure and ecosystem models toward developing predictive ecology. Meanwhile, we will also show results from an interactive model-experiment System - Ecological Platform for Assimilating Data into models (EcoPAD) - that have been implemented at the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in Northern Minnesota and Montpellier Ecotron, France. EcoPAD is developed by integrating web technology, eco-informatics, data assimilation techniques, and ecosystem modeling. EcoPAD is designed to streamline data transfer seamlessly from research infrastructure

Simulation of ecological processes using response functions method

International Nuclear Information System (INIS)

Malkina-Pykh, I.G.; Pykh, Yu. A.

1998-01-01

The article describes further development and applications of the already well-known response functions method (MRF). The method is used as a basis for the development of mathematical models of a wide set of ecological processes. The model of radioactive contamination of the ecosystems is chosen as an example. The mathematical model was elaborated for the description of 90 Sr dynamics in the elementary ecosystems of various geographical zones. The model includes the blocks corresponding with the main units of any elementary ecosystem: lower atmosphere, soil, vegetation, surface water. Parameters' evaluation was provided on a wide set of experimental data. A set of computer simulations was done on the model to prove the possibility of the model's use for ecological forecasting

Ecological model of the interprise danger of gas

International Nuclear Information System (INIS)

Sadygov, A.B.

2009-01-01

It has been looked into the basic problems for establishment of ecological model of the enterprise danger of gas. There have been established mathematical model in the base of equation of Novye-Stoks which consists of private reproductive second row differential equation system of three

Model parameter updating using Bayesian networks

International Nuclear Information System (INIS)

Treml, C.A.; Ross, Timothy J.

2004-01-01

This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.

Estimation and Application of Ecological Memory Functions in Time and Space

Science.gov (United States)

Itter, M.; Finley, A. O.; Dawson, A.

2017-12-01

A common goal in quantitative ecology is the estimation or prediction of ecological processes as a function of explanatory variables (or covariates). Frequently, the ecological process of interest and associated covariates vary in time, space, or both. Theory indicates many ecological processes exhibit memory to local, past conditions. Despite such theoretical understanding, few methods exist to integrate observations from the recent past or within a local neighborhood as drivers of these processes. We build upon recent methodological advances in ecology and spatial statistics to develop a Bayesian hierarchical framework to estimate so-called ecological memory functions; that is, weight-generating functions that specify the relative importance of local, past covariate observations to ecological processes. Memory functions are estimated using a set of basis functions in time and/or space, allowing for flexible ecological memory based on a reduced set of parameters. Ecological memory functions are entirely data driven under the Bayesian hierarchical framework—no a priori assumptions are made regarding functional forms. Memory function uncertainty follows directly from posterior distributions for model parameters allowing for tractable propagation of error to predictions of ecological processes. We apply the model framework to simulated spatio-temporal datasets generated using memory functions of varying complexity. The framework is also applied to estimate the ecological memory of annual boreal forest growth to local, past water availability. Consistent with ecological understanding of boreal forest growth dynamics, memory to past water availability peaks in the year previous to growth and slowly decays to zero in five to eight years. The Bayesian hierarchical framework has applicability to a broad range of ecosystems and processes allowing for increased understanding of ecosystem responses to local and past conditions and improved prediction of ecological

Modeling ecological and economic systems with STELLA : Part III

NARCIS (Netherlands)

Costanza, Robert; Voinov, Alexey

2001-01-01

This special issue contains a group of eight modeling studies covering a range of ecological and economic systems and problems. The models were all developed using Stella®, an icon-based software package specifically designed for dynamic systems modeling. Models included in the special issue were

Ecology and equity in global fisheries: Modelling policy options using theoretical distributions

NARCIS (Netherlands)

Rammelt, C.F.; van Schie, Maarten

2016-01-01

Global fisheries present a typical case of political ecology or environmental injustice, i.e. a problem of distribution of resources within ecological limits. We built a stock-flow model to visualize this challenge and its dynamics, with both an ecological and a social dimension. We incorporated

PARAMETER ESTIMATION IN BREAD BAKING MODEL

Directory of Open Access Journals (Sweden)

Hadiyanto Hadiyanto

2012-05-01

Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels.  Abstrak  PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan

The Effect of Learning Cycle Model on Students’ Reducing Ecological Footprints

Directory of Open Access Journals (Sweden)

Özgül Keleş

2011-12-01

Full Text Available The objective of this study is to investigate effect of ecological footprint education, in which 5E learning cycle model is used, in reducing primary school students’ ecological footprints. The working group of the study is composed of 124 primary school students studying in 4th, 5th, 6th, 7th, 8th classes. In this study, 5E learning model is used in teaching a course in order to increase the participating students’ knowledge about ecological footprints and to calculate ecological footprints. Experimental method is used in this study. In data analysis, the paired samples t-test is used in for relevant samplings. The findings gathered indicate that ecological footprints of the participating students to the study decreased at the end of the study. It is determined that the mean of primary students’ ecological footprints differ from meaningfully according to level of the class and sex. Prospective solution offers are developed by handling the prospective effects of conclusions of the study on sustainable life and environmental education and conclusions’ importance in terms of learning and developing learning programmes with a critical point of view

Samdrup Jongkhar Initiative : a Model of Integrated Ecologically ...

International Development Research Centre (IDRC) Digital Library (Canada)

Samdrup Jongkhar Initiative : a Model of Integrated Ecologically-friendly ... which endeavors to integrate social, economic, cultural and environmental objectives. ... Brown Cloud penetrates Bhutan : ambient air quality and trans-boundary ...

Emergence of scale-free characteristics in socio-ecological systems with bounded rationality

OpenAIRE

Kasthurirathna, Dharshana; Piraveenan, Mahendra

2015-01-01

Socio?ecological systems are increasingly modelled by games played on complex networks. While the concept of Nash equilibrium assumes perfect rationality, in reality players display heterogeneous bounded rationality. Here we present a topological model of bounded rationality in socio-ecological systems, using the rationality parameter of the Quantal Response Equilibrium. We argue that system rationality could be measured by the average Kullback?-Leibler divergence between Nash and Quantal Res...

[Measuring water ecological carrying capacity with the ecosystem-service-based ecological footprint (ESEF) method: Theory, models and application].

Science.gov (United States)

Jiao, Wen-jun; Min, Qing-wen; Li, Wen-hua; Fuller, Anthony M

2015-04-01

Integrated watershed management based on aquatic ecosystems has been increasingly acknowledged. Such a change in the philosophy of water environment management requires recognizing the carrying capacity of aquatic ecosystems for human society from a more general perspective. The concept of the water ecological carrying capacity is therefore put forward, which considers both water resources and water environment, connects socio-economic development to aquatic ecosystems and provides strong support for integrated watershed management. In this paper, the authors proposed an ESEF-based measure of water ecological carrying capacity and constructed ESEF-based models of water ecological footprint and capacity, aiming to evaluate water ecological carrying capacity with footprint methods. A regional model of Taihu Lake Basin was constructed and applied to evaluate the water ecological carrying capacity in Changzhou City which located in the upper reaches of the basin. Results showed that human demand for water ecosystem services in this city had exceeded the supply capacity of local aquatic ecosystems and the significant gap between demand and supply had jeopardized the sustainability of local aquatic ecosystems. Considering aqua-product provision, water supply and pollutant absorption in an integrated way, the scale of population and economy aquatic ecosystems in Changzhou could bear only 54% of the current status.

Ecological optimization for an irreversible magnetic Ericsson refrigeration cycle

International Nuclear Information System (INIS)

Wang Hao; Wu Guo-Xing

2013-01-01

An irreversible Ericsson refrigeration cycle model is established, in which multi-irreversibilities such as finite-rate heat transfer, regenerative loss, heat leakage, and the efficiency of the regenerator are taken into account. Expressions for several important performance parameters, such as the cooling rate, coefficient of performance (COP), power input, exergy output rate, entropy generation rate, and ecological function are derived. The influences of the heat leakage and the time of the regenerative processes on the ecological performance of the refrigerator are analyzed. The optimal regions of the ecological function, cooling rate, and COP are determined and evaluated. Furthermore, some important parameter relations of the refrigerator are revealed and discussed in detail. The results obtained here have general significance and will be helpful in gaining a deep understanding of the magnetic Ericsson refrigeration cycle. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

Comparison of models used for ecological risk assessment and human health risk assessment

International Nuclear Information System (INIS)

Ryti, R.T.; Gallegos, A.F.

1994-01-01

Models are used to derive action levels for site screening, or to estimate potential ecological or human health risks posed by potentially hazardous sites. At the Los Alamos National Laboratory (LANL), which is RCRA-regulated, the human-health screening action levels are based on hazardous constituents described in RCRA Subpart S and RESRAD-derived soil guidelines (based on 10 mRem/year) for radiological constituents. Also, an ecological risk screening model was developed for a former firing site, where the primary constituents include depleted uranium, beryllium and lead. Sites that fail the screening models are evaluated with site-specific human risk assessment (using RESRAD and other approaches) and a detailed ecological effect model (ECOTRAN). ECOTRAN is based on pharmacokinetics transport modeling within a multitrophic-level biological-growth dynamics model. ECOTRAN provides detailed temporal records of contaminant concentrations in biota, and annual averages of these body burdens are compared to equivalent site-specific runs of the RESRAD model. The results show that thoughtful interpretation of the results of these models must be applied before they can be used for evaluation of current risk posed by sites and the benefits of various remedial options. This presentation compares the concentrations of biological media in the RESRAD screening runs to the concentrations in ecological endpoints predicted by the ecological screening model. The assumptions and limitations of these screening models and the decision process where these are screening models are applied are discussed

Robust estimation of hydrological model parameters

Directory of Open Access Journals (Sweden)

A. Bárdossy

2008-11-01

Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.

Ecological models in support of regulatory risk assessments of pesticides: developing a strategy for the future.

Science.gov (United States)

Forbes, Valery E; Hommen, Udo; Thorbek, Pernille; Heimbach, Fred; Van den Brink, Paul J; Wogram, Jörn; Thulke, Hans-Hermann; Grimm, Volker

2009-01-01

This brief communication reports on the main findings of the LEMTOX workshop, held from 9 to 12 September 2007, at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. The workshop brought together a diverse group of stakeholders from academia, regulatory authorities, contract research organizations, and industry, representing Europe, the United States, and Asia, to discuss the role of ecological modeling in risk assessments of pesticides, particularly under the European regulatory framework. The following questions were addressed: What are the potential benefits of using ecological models in pesticide registration and risk assessment? What obstacles prevent ecological modeling from being used routinely in regulatory submissions? What actions are needed to overcome the identified obstacles? What recommendations should be made to ensure good modeling practice in this context? The workshop focused exclusively on population models, and discussion was focused on those categories of population models that link effects on individuals (e.g., survival, growth, reproduction, behavior) to effects on population dynamics. The workshop participants concluded that the overall benefits of ecological modeling are that it could bring more ecology into ecological risk assessment, and it could provide an excellent tool for exploring the importance of, and interactions among, ecological complexities. However, there are a number of challenges that need to be overcome before such models will receive wide acceptance for pesticide risk assessment, despite having been used extensively in other contexts (e.g., conservation biology). The need for guidance on Good Modeling Practice (on model development, analysis, interpretation, evaluation, documentation, and communication), as well as the need for case studies that can be used to explore the added value of ecological models for risk assessment, were identified as top priorities. Assessing recovery potential of exposed

Photovoltaic module parameters acquisition model

Energy Technology Data Exchange (ETDEWEB)

Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk

2014-09-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.

Photovoltaic module parameters acquisition model

International Nuclear Information System (INIS)

Cibira, Gabriel; Koščová, Marcela

2014-01-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model

[Assessment on the ecological suitability in Zhuhai City, Guangdong, China, based on minimum cumulative resistance model].

Science.gov (United States)

Li, Jian-fei; Li, Lin; Guo, Luo; Du, Shi-hong

2016-01-01

Urban landscape has the characteristics of spatial heterogeneity. Because the expansion process of urban constructive or ecological land has different resistance values, the land unit stimulates and promotes the expansion of ecological land with different intensity. To compare the effect of promoting and hindering functions in the same land unit, we firstly compared the minimum cumulative resistance value of promoting and hindering functions, and then looked for the balance of two landscape processes under the same standard. According to the ecology principle of minimum limit factor, taking the minimum cumulative resistance analysis method under two expansion processes as the evaluation method of urban land ecological suitability, this research took Zhuhai City as the study area to estimate urban ecological suitability by relative evaluation method with remote sensing image, field survey, and statistics data. With the support of ArcGIS, five types of indicators on landscape types, ecological value, soil erosion sensitivity, sensitivity of geological disasters, and ecological function were selected as input parameters in the minimum cumulative resistance model to compute urban ecological suitability. The results showed that the ecological suitability of the whole Zhuhai City was divided into five levels: constructive expansion prohibited zone (10.1%), constructive expansion restricted zone (32.9%), key construction zone (36.3%), priority development zone (2.3%), and basic cropland (18.4%). Ecological suitability of the central area of Zhuhai City was divided into four levels: constructive expansion prohibited zone (11.6%), constructive expansion restricted zone (25.6%), key construction zone (52.4%), priority development zone (10.4%). Finally, we put forward the sustainable development framework of Zhuhai City according to the research conclusion. On one hand, the government should strictly control the development of the urban center area. On the other hand, the

Unifying relationships between complexity and stability in mutualistic ecological communities.

Science.gov (United States)

Feng, Wenfeng; Bailey, Richard M

2018-02-14

Conserving ecosystem function and associated services requires deep understanding of the underlying basis of system stability. While the study of ecological dynamics is a mature and diverse field, the lack of a general model that predicts a broad range of theoretical and empirical observations has allowed unresolved contradictions to persist. Here we provide a general model of mutualistic ecological interactions between two groups and show for the first time how the conditions for bi-stability, the nature of critical transitions, and identifiable leading indicators in time-series can be derived from the basic parameters describing the underlying ecological interactions. Strong mutualism and nonlinearity in handling-time are found to be necessary conditions for the occurrence of critical transitions. We use the model to resolve open questions concerning the effects of heterogeneity in inter-species interactions on both resilience and abundance, and discuss these in terms of potential trade-offs in real systems. This framework provides a basis for rich investigations of ecological system dynamics, and may be generalizable across many ecological contexts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ecological-economic modeling for biodiversity management: potential, pitfalls, and prospects

NARCIS (Netherlands)

Wätzold, F.; Drechsler, M.; Armstrong, C.W.; Baumgärtner, S.; Grimm, V.; Huth, A.; Perrings, C.; Possingham, H.P.; Shogren, J.F.; Skonhoft, A.; Verboom-Vasiljev, J.; Wissel, C.

2006-01-01

Ecologists and economists both use models to help develop strategies for biodiversity management. The practical use of disciplinary models, however, can be limited because ecological models tend not to address the socioeconomic dimension of biodiversity management, whereas economic models tend to

[An emergy-ecological footprint model based evaluation of ecological security at the old industrial area in Northeast China: A case study of Liaoning Province.

Science.gov (United States)

Yang, Qing; Lu, Cheng Peng; Zhou, Feng; Geng, Yong; Jing, Hong Shuang; Ren, Wan Xia; Xue, Bing

2016-05-01

Based on the integrated model of emergy-ecological footprint approaches, the ecological security of Liaoning Province, a typical case for the old industrial area, was quantitatively evaluated from 2003 to 2012, followed by a scenario analysis on the development trend of the ecological secu-rity by employing the gray kinetic model. The results showed that, from 2003 to 2012, the value of emergy ecological-capacity per capita in Liaoning Province decreased from 3.13 hm 2 to 3.07 hm 2 , while the emergy-ecological footprint increased from 13.88 hm 2 to 21.96 hm 2 , which indicated that the ecological deficit existed in Liaoning Province and the situation was getting worse. The ecological pressure index increased from 4.43 to 7.16 during the studied period, and the alert level of ecological security changed from light to middle level. According to the development trend, the emergy ecological capacity per capita during 2013-2022 would correspondingly decrease from 3.04 hm 2 to 2.98 hm 2 , while the emergy ecological footprint would increase from 22.72 hm 2 to 35.87 hm 2 , the ecological pressure index would increase from 7.46 to 12.04, and the ecological deficit would keep increasing and the ecological security level would slide into slightly unsafe condition. The alert level of ecological security would turn to be middle or serious, suggesting the problems in ecological safety needed to be solved urgently.

Social Ecological Model Analysis for ICT Integration

Science.gov (United States)

Zagami, Jason

2013-01-01

ICT integration of teacher preparation programmes was undertaken by the Australian Teaching Teachers for the Future (TTF) project in all 39 Australian teacher education institutions and highlighted the need for guidelines to inform systemic ICT integration approaches. A Social Ecological Model (SEM) was used to positively inform integration…

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

Directory of Open Access Journals (Sweden)

Rachel D. Cavanagh

2017-09-01

Full Text Available Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer, there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

Violent Victimization and Perpetration during Adolescence: Developmental Stage Dependent Ecological Models

Science.gov (United States)

Matjasko, Jennifer L.; Needham, Belinda L.; Grunden, Leslie N.; Farb, Amy Feldman

2010-01-01

Using a variant of the ecological-transactional model and developmental theories of delinquency on a nationally representative sample of adolescents, the current study explored the ecological predictors of violent victimization, perpetration, and both for three different developmental stages during adolescence. We examined the relative influence…

Ecologic Niche Modeling of Blastomyces dermatitidis in Wisconsin

Science.gov (United States)

Reed, Kurt D.; Meece, Jennifer K.; Archer, John R.; Peterson, A. Townsend

2008-01-01

Background Blastomycosis is a potentially fatal mycosis that is acquired by inhaling infectious spores of Blastomyces dermatitidis present in the environment. The ecology of this pathogen is poorly understood, in part because it has been extremely difficult to identify the niche(s) it occupies based on culture isolation of the organism from environmental samples. Methodology/Principal Findings We investigated the ecology of blastomycosis by performing maximum entropy modeling of exposure sites from 156 cases of human and canine blastomycosis to provide a regional-scale perspective of the geographic and ecologic distribution of B. dermatitidis in Wisconsin. Based on analysis with climatic, topographic, surface reflectance and other environmental variables, we predicted that ecologic conditions favorable for maintaining the fungus in nature occur predominantly within northern counties and counties along the western shoreline of Lake Michigan. Areas of highest predicted occurrence were often in proximity to waterways, especially in northcentral Wisconsin, where incidence of infection is highest. Ecologic conditions suitable for B. dermatitidis are present in urban and rural environments, and may differ at the extremes of distribution of the species in the state. Conclusions/Significance Our results provide a framework for a more informed search for specific environmental factors modulating B. dermatitidis occurrence and transmission and will be useful for improving public health awareness of relative exposure risks. PMID:18446224

Using simulated annealing algorithm to optimize the parameters of Biome-BGC model%利用模拟退火算法优化Biome-BGC模型参数

Institute of Scientific and Technical Information of China (English)

张廷龙; 孙睿; 胡波; 冯丽超

2011-01-01

生态过程模型建立在明确的机理之上,能够较好地模拟陆地生态系统的行为和特征,但模型众多的参数,成为模型具体应用的瓶颈.本文以Biome-BGC模型为例,采用模拟退火算法,对其生理、生态参数进行优化.在优化过程中,先对待优化参数进行了选择,然后采取逐步优化的方法进行优化.结果表明,使用优化后的参数,模型模拟结果与实际观测更为接近,参数优化能有效地降低模型模拟的不确定性.文中参数优化的过程和方法,可为生态模型的参数识别和优化提供一种实例和思路,有助于生态模型应用区域的扩展.%Ecological process model based on defined mechanism can well simulate the dynamic behaviors and features of terrestrial ecosystem, but could become a bottleneck in application because of numerous parameters needed to be confirmed. In this paper, simulated annealing algorithm was used to optimize the physiological and ecological parameters of Biome-BGC model. The first step was to choose some of these parameters to optimize, and then, gradually optimized these parameters. By using the optimized parameters, the model simulation results were much more close to the observed data, and the parameter optimization could effectively reduce the uncertainty of model simulation. The parameter optimization method used in this paper could provide a case and an idea for the parameter identification and optimization of ecological process models,and also, help to expand the application area of the models.

A new quantitative model of ecological compensation based on ecosystem capital in Zhejiang Province, China*

Science.gov (United States)

Jin, Yan; Huang, Jing-feng; Peng, Dai-liang

2009-01-01

Ecological compensation is becoming one of key and multidiscipline issues in the field of resources and environmental management. Considering the change relation between gross domestic product (GDP) and ecological capital (EC) based on remote sensing estimation, we construct a new quantitative estimate model for ecological compensation, using county as study unit, and determine standard value so as to evaluate ecological compensation from 2001 to 2004 in Zhejiang Province, China. Spatial differences of the ecological compensation were significant among all the counties or districts. This model fills up the gap in the field of quantitative evaluation of regional ecological compensation and provides a feasible way to reconcile the conflicts among benefits in the economic, social, and ecological sectors. PMID:19353749

Ecological forecasting under climatic data uncertainty: a case study in phenological modeling

International Nuclear Information System (INIS)

Cook, Benjamin I; Terando, Adam; Steiner, Allison

2010-01-01

Forecasting ecological responses to climate change represents a challenge to the ecological community because models are often site-specific and climate data are lacking at appropriate spatial and temporal resolutions. We use a case study approach to demonstrate uncertainties in ecological predictions related to the driving climatic input data. We use observational records, derived observational datasets (e.g. interpolated observations from local weather stations and gridded data products) and output from general circulation models (GCM) in conjunction with site based phenology models to estimate the first flowering date (FFD) for three woody flowering species. Using derived observations over the modern time period, we find that cold biases and temperature trends lead to biased FFD simulations for all three species. Observational datasets resolved at the daily time step result in better FFD predictions compared to simulations using monthly resolution. Simulations using output from an ensemble of GCM and regional climate models over modern and future time periods have large intra-ensemble spreads and tend to underestimate observed FFD trends for the modern period. These results indicate that certain forcing datasets may be missing key features needed to generate accurate hindcasts at the local scale (e.g. trends, temporal resolution), and that standard modeling techniques (e.g. downscaling, ensemble mean, etc) may not necessarily improve the prediction of the ecological response. Studies attempting to simulate local ecological processes under modern and future climate forcing therefore need to quantify and propagate the climate data uncertainties in their simulations.

Ecological models for regulatory risk assessments of pesticides: Developing a strategy for the future.

NARCIS (Netherlands)

Thorbek, P.; Forbes, V.; Heimbach, F.; Hommen, U.; Thulke, H.H.; Brink, van den P.J.

2010-01-01

Ecological Models for Regulatory Risk Assessments of Pesticides: Developing a Strategy for the Future provides a coherent, science-based view on ecological modeling for regulatory risk assessments. It discusses the benefits of modeling in the context of registrations, identifies the obstacles that

Multi-Attribute Modelling of Economic and Ecological Impacts of Cropping Systems

NARCIS (Netherlands)

Bohanec, M.; Dzeroski, S.; Znidarsic, M.; Messéan, A.; Scatasta, S.; Wesseler, J.H.H.

2004-01-01

Modelling of economic and ecological impacts of genetically modified crops is a demanding task. We present some preliminary attempts made for the purpose of the ECOGEN project "Soil ecological and economic evaluation of genetically modified crops". One of the goals of the project is to develop a

Ecological Niche Modelling of the Bacillus anthracis A1.a sub-lineage in Kazakhstan

Science.gov (United States)

2011-01-01

Background Bacillus anthracis, the causative agent of anthrax, is a globally distributed zoonotic pathogen that continues to be a veterinary and human health problem in Central Asia. We used a database of anthrax outbreak locations in Kazakhstan and a subset of genotyped isolates to model the geographic distribution and ecological associations of B. anthracis in Kazakhstan. The aims of the study were to test the influence of soil variables on a previous ecological niche based prediction of B. anthracis in Kazakhstan and to determine if a single sub-lineage of B. anthracis occupies a unique ecological niche. Results The addition of soil variables to the previously developed ecological niche model did not appreciably alter the limits of the predicted geographic or ecological distribution of B. anthracis in Kazakhstan. The A1.a experiment predicted the sub-lineage to be present over a larger geographic area than did the outbreak based experiment containing multiple lineages. Within the geographic area predicted to be suitable for B. anthracis by all ten best subset models, the A1.a sub-lineage was associated with a wider range of ecological tolerances than the outbreak-soil experiment. Analysis of rule types showed that logit rules predominate in the outbreak-soil experiment and range rules in the A1.a sub-lineage experiment. Random sub-setting of locality points suggests that models of B. anthracis distribution may be sensitive to sample size. Conclusions Our analysis supports careful consideration of the taxonomic resolution of data used to create ecological niche models. Further investigations into the environmental affinities of individual lineages and sub-lineages of B. anthracis will be useful in understanding the ecology of the disease at large and small scales. With model based predictions serving as approximations of disease risk, these efforts will improve the efficacy of public health interventions for anthrax prevention and control. PMID:22152056

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling.

Science.gov (United States)

Iglesias, Virginia; Yospin, Gabriel I; Whitlock, Cathy

2014-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity.

Range bagging: a new method for ecological niche modelling from presence-only data.

Science.gov (United States)

Drake, John M

2015-06-06

The ecological niche is the set of environments in which a population of a species can persist without introduction of individuals from other locations. A good mathematical or computational representation of the niche is a prerequisite to addressing many questions in ecology, biogeography, evolutionary biology and conservation. A particularly challenging question for ecological niche modelling is the problem of presence-only modelling. That is, can an ecological niche be identified from records drawn only from the set of niche environments without records from non-niche environments for comparison? Here, I introduce a new method for ecological niche modelling from presence-only data called range bagging. Range bagging draws on the concept of a species' environmental range, but was inspired by the empirical performance of ensemble learning algorithms in other areas of ecological research. This paper extends the concept of environmental range to multiple dimensions and shows that range bagging is computationally feasible even when the number of environmental dimensions is large. The target of the range bagging base learner is an environmental tolerance of the species in a projection of its niche and is therefore an ecologically interpretable property of a species' biological requirements. The computational complexity of range bagging is linear in the number of examples, which compares favourably with the main alternative, Qhull. In conclusion, range bagging appears to be a reasonable choice for niche modelling in applications in which a presence-only method is desired and may provide a solution to problems in other disciplines where one-class classification is required, such as outlier detection and concept learning.

Integrated ecological-economic fisheries models - evaluation, review and challenges for implementation

DEFF Research Database (Denmark)

Nielsen, J. Rasmus; Thunberg, Eric; Holland, Daniel S.

2018-01-01

and comparative evaluation of 35 IESFM´s applied to marine fisheries and marine ecosystem resources to identify the characteristics that determine their usefulness, effectiveness and implementation. The focus is on fully integrated models that allow for feedbacks between ecological and human processes though......Marine ecosystems evolve under many interconnected and area-specific pressures. In order to fulfill society's intensifying and diversifying needs whilst ensuring ecologically sustainable development, more effective marine spatial planning and broader-scope management of marine resources...... is necessary. Integrated ecological–socioeconomic fisheries models (IESFM) of marine systems are nee¬ded to evaluate impacts and sustainability of potential management actions and understand, and anti¬ci¬pate ecological, economic, and social dynamics at a range of scales from local to national and regional...

Estimating the ecology of extinct species with paleoecological data assimilation

Science.gov (United States)

Raiho, A.; McLachlan, J. S.; Dietze, M.

2017-12-01

In order to understand long term, unobservable ecosystem processes, ecologists must use both paleoecoloigcal data and ecosystem models. Models parameterize species competitive interactions using modern data. But, modern ecological or physiological observations are not available for extinct species, making it difficult for models to conceptualize their ecology. For instance, American chestnut (Castanea dentata), who played a large role in forests of northeastern US, was decimated by disease to virtual extinction. Since chestnut's demise, defining its ecology has been controversial. Models typically assume that chestnut's ecology was very similar to oak; They parameterize chestnut like oak species. These assumptions are drawn from paleoecological data, but these data are often reported without uncertainty. Since the paleoecological data are often reported without uncertainty, paleoecological data has never been directly incorporated with ecosystem models. We developed a Bayesian statistical model to estimate fractional composition from paleoecological data with uncertainty. Then, we assimilated this data product into an ecosystem model for long term forest succession using a generalized ensemble adjustment filter to determine which species demographic parameters lead to changes in species composition over the last 2,000 years at Harvard Forest. We found that chestnut was strongly negatively correlated with white pine (Pinus strobus) and red oak (Quercus rubra) in the process covariance matrix, suggesting a strong competitive interaction that is not currently understood by models for forest succession. These findings provide support for utilizing a data assimilation framework to ecologically interpret paleoecological data or data products to learn about the ecology of extinct species.

Of Models and Meanings: Cultural Resilience in Social–Ecological Systems

NARCIS (Netherlands)

Crane, T.A.

2010-01-01

Modeling has emerged as a key technology in analysis of social–ecological systems. However, the tendency for modeling to focus on the mechanistic materiality of biophysical systems obscures the diversity of performative social behaviors and normative cultural positions of actors within the modeled

Crisis in Context Theory: An Ecological Model

Science.gov (United States)

Myer, Rick A.; Moore, Holly B.

2006-01-01

This article outlines a theory for understanding the impact of a crisis on individuals and organizations. Crisis in context theory (CCT) is grounded in an ecological model and based on literature in the field of crisis intervention and on personal experiences of the authors. A graphic representation denotes key components and premises of CCT,…

Evaluating the influence of epidemiological parameters and host ecology on the spread of phocine distemper virus through populations of harbour seals.

Directory of Open Access Journals (Sweden)

Catriona M Harris

Full Text Available BACKGROUND: Outbreaks of phocine distemper virus (PDV in Europe during 1988 and 2002 were responsible for the death of around 23,000 and 30,000 harbour seals, respectively. These epidemics, particularly the one in 2002, provided an unusual opportunity to estimate epidemic parameters for a wildlife disease. There were marked regional differences in the values of some parameters both within and between epidemics. METHODOLOGY AND PRINCIPAL FINDINGS: We used an individual-based model of seal movement that allowed us to incorporate realistic representations of space, time and animal behaviour into a traditional epidemiological modelling framework. We explored the potential influence of a range of ecological (foraging trip duration, time of epidemic onset, population size and epidemiological (length of infectious period, contact rate between infectious and susceptible individuals, case mortality parameters on four readily-measurable epidemic characteristics (number of dead individuals, duration of epidemic, peak mortality date and prevalence and on the probability that an epidemic would occur in a particular region. We analysed the outputs as if they were the results of a series of virtual experiments, using Generalised Linear Modelling. All six variables had a significant effect on the probability that an epidemic would be recognised as an unusual mortality event by human observers. CONCLUSIONS: Regional and temporal variation in contact rate was the most likely cause of the observed differences between the two epidemics. This variation could be a consequence of differences in the way individuals divide their time between land and sea at different times of the year.

Parameter Estimation of Partial Differential Equation Models.

Science.gov (United States)

Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

2013-01-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.

Building Better Ecological Machines: Complexity Theory and Alternative Economic Models

Directory of Open Access Journals (Sweden)

Jess Bier

2016-12-01

Full Text Available Computer models of the economy are regularly used to predict economic phenomena and set financial policy. However, the conventional macroeconomic models are currently being reimagined after they failed to foresee the current economic crisis, the outlines of which began to be understood only in 2007-2008. In this article we analyze the most prominent of this reimagining: Agent-Based models (ABMs. ABMs are an influential alternative to standard economic models, and they are one focus of complexity theory, a discipline that is a more open successor to the conventional chaos and fractal modeling of the 1990s. The modelers who create ABMs claim that their models depict markets as ecologies, and that they are more responsive than conventional models that depict markets as machines. We challenge this presentation, arguing instead that recent modeling efforts amount to the creation of models as ecological machines. Our paper aims to contribute to an understanding of the organizing metaphors of macroeconomic models, which we argue is relevant conceptually and politically, e.g., when models are used for regulatory purposes.

Designing Industrial Networks Using Ecological Food Web Metrics.

Science.gov (United States)

Layton, Astrid; Bras, Bert; Weissburg, Marc

2016-10-18

Biologically Inspired Design (biomimicry) and Industrial Ecology both look to natural systems to enhance the sustainability and performance of engineered products, systems and industries. Bioinspired design (BID) traditionally has focused on a unit operation and single product level. In contrast, this paper describes how principles of network organization derived from analysis of ecosystem properties can be applied to industrial system networks. Specifically, this paper examines the applicability of particular food web matrix properties as design rules for economically and biologically sustainable industrial networks, using an optimization model developed for a carpet recycling network. Carpet recycling network designs based on traditional cost and emissions based optimization are compared to designs obtained using optimizations based solely on ecological food web metrics. The analysis suggests that networks optimized using food web metrics also were superior from a traditional cost and emissions perspective; correlations between optimization using ecological metrics and traditional optimization ranged generally from 0.70 to 0.96, with flow-based metrics being superior to structural parameters. Four structural food parameters provided correlations nearly the same as that obtained using all structural parameters, but individual structural parameters provided much less satisfactory correlations. The analysis indicates that bioinspired design principles from ecosystems can lead to both environmentally and economically sustainable industrial resource networks, and represent guidelines for designing sustainable industry networks.

Adding Value to Ecological Risk Assessment with Population Modeling

DEFF Research Database (Denmark)

Forbes, Valery E.; Calow, Peter; Grimm, Volker

2011-01-01

population models can provide a powerful basis for expressing ecological risks that better inform the environmental management process and thus that are more likely to be used by managers. Here we provide at least five reasons why population modeling should play an important role in bridging the gap between...

Development of a zoning-based environmental-ecological-coupled model for lakes to assess lake restoration effect

Science.gov (United States)

Xu, Mengjia; Zou, Changxin; Zhao, Yanwei

2017-04-01

Environmental/ecological models are widely used for lake management as they provide a means to understand physical, chemical and biological processes in highly complex ecosystems. Most research focused on the development of environmental (water quality) and ecological models, separately. Limited studies were developed to couple the two models, and in these limited coupled models, a lake was regarded as a whole for analysis (i.e., considering the lake to be one well-mixed box), which was appropriate for small-scale lakes and was not sufficient to capture spatial variations within middle-scale or large-scale lakes. This paper seeks to establish a zoning-based environmental-ecological-coupled model for a lake. The Baiyangdian Lake, the largest freshwater lake in Northern China, was adopted as the study case. The coupled lake models including a hydrodynamics and water quality model established by MIKE21 and a compartmental ecological model used STELLA software have been established for middle-sized Baiyangdian Lake to realize the simulation of spatial variations of ecological conditions. On the basis of the flow field distribution results generated by MIKE21 hydrodynamics model, four water area zones were used as an example for compartmental ecological model calibration and validation. The results revealed that the developed coupled lake models can reasonably reflected the changes of the key state variables although there remain some state variables that are not well represented by the model due to the low quality of field monitoring data. Monitoring sites in a compartment may not be representative of the water quality and ecological conditions in the entire compartment even though that is the intention of compartment-based model design. There was only one ecological observation from a single monitoring site for some periods. This single-measurement issue may cause large discrepancies particularly when sampled site is not representative of the whole compartment. The

Quality assessment for radiological model parameters

International Nuclear Information System (INIS)

Funtowicz, S.O.

1989-01-01

A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)

Improving the Algae Bloom Prediction through the Assimilation of the Remotely Sensed Chlorophyll-A Data in a Generic Ecological Model in the North Sea

Science.gov (United States)

El Serafy, Ghada

2010-05-01

Harmful algae can cause damage to co-existing organisms, tourism and farmers. Accurate predictions of algal future composition and abundance as well as when and where algal blooms may occur could help early warning and mitigating. The Generic Ecological Model, GEM, [Blauw et al 2008] is an instrument that can be applied to any water system (fresh, transitional or coastal) to calculate the primary production, chlorophyll-a concentration and phytoplankton species composition. It consists of physical, chemical and ecological model components which are coupled together to build one generic and flexible modeling tool. For the North Sea, the model has been analyzed to assess sensitivity of the simulated chlorophyll-a concentration to a subset of ecologically significant set of factors. The research led to the definition of the most significant set of parameters to the algae blooming process in the North Sea [Salacinska et al 2009]. In order to improve the prediction of the model, the set of parameters and the chlorophyll-a concentration can be further estimated through the use of data assimilation. In this research, the Ensemble Kalman Filter (EnKF) data assimilation technique is used to assimilate the chlorophyll-a data of the North Sea, retrieved from MEdium Resolution Imaging Sensor (MERIS) spectrometer data [Peters et al 2005], in the GEM model. The chlorophyll-a data includes concentrations and error information that enable their use in data assimilation. For the same purpose, the uncertainty of the ecological generic model, GEM has been quantified by means of Monte Carlo approach. Through a study covering the year of 2003, the research demonstrates that both data and model are sufficiently robust for a successful assimilation. The results show that through the assimilation of the satellite data, a better description of the algae bloom has been achieved and an improvement of the capability of the model to predict the algae bloom for the North Sea has been confirmed

Integrating human and natural systems in community psychology: an ecological model of stewardship behavior.

Science.gov (United States)

Moskell, Christine; Allred, Shorna Broussard

2013-03-01

Community psychology (CP) research on the natural environment lacks a theoretical framework for analyzing the complex relationship between human systems and the natural world. We introduce other academic fields concerned with the interactions between humans and the natural environment, including environmental sociology and coupled human and natural systems. To demonstrate how the natural environment can be included within CP's ecological framework, we propose an ecological model of urban forest stewardship action. Although ecological models of behavior in CP have previously modeled health behaviors, we argue that these frameworks are also applicable to actions that positively influence the natural environment. We chose the environmental action of urban forest stewardship because cities across the United States are planting millions of trees and increased citizen participation in urban tree planting and stewardship will be needed to sustain the benefits provided by urban trees. We used the framework of an ecological model of behavior to illustrate multiple levels of factors that may promote or hinder involvement in urban forest stewardship actions. The implications of our model for the development of multi-level ecological interventions to foster stewardship actions are discussed, as well as directions for future research to further test and refine the model.

On the specification of structural equation models for ecological systems

Science.gov (United States)

Grace, J.B.; Michael, Anderson T.; Han, O.; Scheiner, S.M.

2010-01-01

The use of structural equation modeling (SEM) is often motivated by its utility for investigating complex networks of relationships, but also because of its promise as a means of representing theoretical concepts using latent variables. In this paper, we discuss characteristics of ecological theory and some of the challenges for proper specification of theoretical ideas in structural equation models (SE models). In our presentation, we describe some of the requirements for classical latent variable models in which observed variables (indicators) are interpreted as the effects of underlying causes. We also describe alternative model specifications in which indicators are interpreted as having causal influences on the theoretical concepts. We suggest that this latter nonclassical specification (which involves another variable type-the composite) will often be appropriate for ecological studies because of the multifaceted nature of our theoretical concepts. In this paper, we employ the use of meta-models to aid the translation of theory into SE models and also to facilitate our ability to relate results back to our theories. We demonstrate our approach by showing how a synthetic theory of grassland biodiversity can be evaluated using SEM and data from a coastal grassland. In this example, the theory focuses on the responses of species richness to abiotic stress and disturbance, both directly and through intervening effects on community biomass. Models examined include both those based on classical forms (where each concept is represented using a single latent variable) and also ones in which the concepts are recognized to be multifaceted and modeled as such. To address the challenge of matching SE models with the conceptual level of our theory, two approaches are illustrated, compositing and aggregation. Both approaches are shown to have merits, with the former being preferable for cases where the multiple facets of a concept have widely differing effects in the

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

Science.gov (United States)

Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

2014-01-01

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

Global qualitative analysis of a quartic ecological model

NARCIS (Netherlands)

Broer, Hendrik; Gaiko, Valery A.

2010-01-01

in this paper we complete the global qualitative analysis of a quartic ecological model. In particular, studying global bifurcations of singular points and limit cycles, we prove that the corresponding dynamical system has at most two limit cycles. (C) 2009 Elsevier Ltd. All rights reserved.

INTEGRATION OF AN ECONOMIC WITH AN ECOLOGICAL MODEL

Science.gov (United States)

We summarize our work on integration of an economy under imperfect competition with a simple Lotka-Volterra type ecological model. Firms and households operate within a single period planning horizon, thus there is no savings or investment. Wages are set by a dominant employer. P...

Improvement of ecological characteristics of the hydrogen diesel engine

Science.gov (United States)

Natriashvili, T.; Kavtaradze, R.; Glonti, M.

2018-02-01

In the article are considered the questions of influence of a swirl intensity of the shot and injector design on the ecological indices of the hydrogen diesel, little-investigated till now. The necessity of solution of these problems arises at conversion of the serial diesel engine into the hydrogen diesel. The mathematical model consists of the three-dimensional non-stationary equations of transfer and also models of turbulence and combustion. The numerical experiments have been carried out with the use of program code FIRE. The optimal values of parameters of the working process, ensuring improvement of the effective and ecological indices of the hydrogen diesel are determined.

Emerging Network-Based Tools in Movement Ecology.

Science.gov (United States)

Jacoby, David M P; Freeman, Robin

2016-04-01

New technologies have vastly increased the available data on animal movement and behaviour. Consequently, new methods deciphering the spatial and temporal interactions between individuals and their environments are vital. Network analyses offer a powerful suite of tools to disentangle the complexity within these dynamic systems, and we review these tools, their application, and how they have generated new ecological and behavioural insights. We suggest that network theory can be used to model and predict the influence of ecological and environmental parameters on animal movement, focusing on spatial and social connectivity, with fundamental implications for conservation. Refining how we construct and randomise spatial networks at different temporal scales will help to establish network theory as a prominent, hypothesis-generating tool in movement ecology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational modeling for eco engineering: Making the connections between engineering and ecology (Invited)

Science.gov (United States)

Bowles, C.

2013-12-01

Ecological engineering, or eco engineering, is an emerging field in the study of integrating ecology and engineering, concerned with the design, monitoring, and construction of ecosystems. According to Mitsch (1996) 'the design of sustainable ecosystems intends to integrate human society with its natural environment for the benefit of both'. Eco engineering emerged as a new idea in the early 1960s, and the concept has seen refinement since then. As a commonly practiced field of engineering it is relatively novel. Howard Odum (1963) and others first introduced it as 'utilizing natural energy sources as the predominant input to manipulate and control environmental systems'. Mtisch and Jorgensen (1989) were the first to define eco engineering, to provide eco engineering principles and conceptual eco engineering models. Later they refined the definition and increased the number of principles. They suggested that the goals of eco engineering are: a) the restoration of ecosystems that have been substantially disturbed by human activities such as environmental pollution or land disturbance, and b) the development of new sustainable ecosystems that have both human and ecological values. Here a more detailed overview of eco engineering is provided, particularly with regard to how engineers and ecologists are utilizing multi-dimensional computational models to link ecology and engineering, resulting in increasingly successful project implementation. Descriptions are provided pertaining to 1-, 2- and 3-dimensional hydrodynamic models and their use at small- and large-scale applications. A range of conceptual models that have been developed to aid the in the creation of linkages between ecology and engineering are discussed. Finally, several case studies that link ecology and engineering via computational modeling are provided. These studies include localized stream rehabilitation, spawning gravel enhancement on a large river system, and watershed-wide floodplain modeling of

Selected developments and applications of Leontief models in industrial ecology

International Nuclear Information System (INIS)

Stroemman, Anders Hammer

2005-01-01

Thesis Outline: This thesis investigates issues of environmental repercussions on processes of three spatial scales; a single process plant, a regional value chain and the global economy. The first paper investigates environmental repercussions caused by a single process plant using an open Leontief model with combined physical and monetary units in what is commonly referred to as a hybrid life cycle model. Physical capital requirements are treated as any other good. Resources and environmental stressors, thousands in total, are accounted for and assessed by aggregation using standard life cycle impact assessment methods. The second paper presents a methodology for establishing and combining input-output matrices and life-cycle inventories in a hybrid life cycle inventory. Information contained within different requirements matrices are combined and issues of double counting that arise are addressed and methods for eliminating these are developed and presented. The third paper is an extension of the first paper. Here the system analyzed is increased from a single plant and component in the production network to a series of nodes, constituting a value chain. The hybrid framework proposed in paper two is applied to analyze the use of natural gas, methanol and hydrogen as transportation fuels. The fourth paper presents the development of a World Trade Model with Bilateral Trade, an extension of the World Trade Model (Duchin, 2005). The model is based on comparative advantage and is formulated as a linear program. It endogenously determines the regional output of sectors and bilateral trade flows between regions. The model may be considered a Leontief substitution model where substitution of production is allowed between regions. The primal objective of the model requires the minimization of global factor costs. The fifth paper demonstrates how the World Trade Model with Bilateral Trade can be applied to address questions relevant for industrial ecology. The model is

European larch phenology in the Alps: can we grasp the role of ecological factors by combining field observations and inverse modelling?

Science.gov (United States)

Migliavacca, M.; Cremonese, E.; Colombo, R.; Busetto, L.; Galvagno, M.; Ganis, L.; Meroni, M.; Pari, E.; Rossini, M.; Siniscalco, C.; Morra di Cella, U.

2008-09-01

Vegetation phenology is strongly influenced by climatic factors. Climate changes may cause phenological variations, especially in the Alps which are considered to be extremely vulnerable to global warming. The main goal of our study is to analyze European larch ( Larix decidua Mill.) phenology in alpine environments and the role of the ecological factors involved, using an integrated approach based on accurate field observations and modelling techniques. We present 2 years of field-collected larch phenological data, obtained following a specifically designed observation protocol. We observed that both spring and autumn larch phenology is strongly influenced by altitude. We propose an approach for the optimization of a spring warming model (SW) and the growing season index model (GSI) consisting of a model inversion technique, based on simulated look-up tables (LUTs), that provides robust parameter estimates. The optimized models showed excellent agreement between modelled and observed data: the SW model predicts the beginning of the growing season (BGS) with a mean RMSE of 4 days, while GSI gives a prediction of the growing season length (LGS) with a RMSE of 5 days. Moreover, we showed that the original GSI parameters led to consistent errors, while the optimized ones significantly increased model accuracy. Finally, we used GSI to investigate interactions of ecological factors during springtime development and autumn senescence. We found that temperature is the most effective factor during spring recovery while photoperiod plays an important role during autumn senescence: photoperiod shows a contrasting effect with altitude decreasing its influence with increasing altitude.

Parameter Estimation of Partial Differential Equation Models

KAUST Repository

Xun, Xiaolei

2013-09-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.

Parameter Estimation for Thurstone Choice Models

Energy Technology Data Exchange (ETDEWEB)

Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-04-24

We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.

Double coupling: modeling subjectivity and asymmetric organization in social-ecological systems

Directory of Open Access Journals (Sweden)

David Manuel-Navarrete

2015-09-01

Full Text Available Social-ecological organization is a multidimensional phenomenon that combines material and symbolic processes. However, the coupling between social and ecological subsystem is often conceptualized as purely material, thus reducing the symbolic dimension to its behavioral and actionable expressions. In this paper I conceptualize social-ecological systems as doubly coupled. On the one hand, material expressions of socio-cultural processes affect and are affected by ecological dynamics. On the other hand, coupled social-ecological material dynamics are concurrently coupled with subjective dynamics via coding, decoding, personal experience, and human agency. This second coupling operates across two organizationally heterogeneous dimensions: material and symbolic. Although resilience thinking builds on the recognition of organizational asymmetry between living and nonliving systems, it has overlooked the equivalent asymmetry between ecological and socio-cultural subsystems. Three guiding concepts are proposed to formalize double coupling. The first one, social-ecological asymmetry, expands on past seminal work on ecological self-organization to incorporate reflexivity and subjectivity in social-ecological modeling. Organizational asymmetry is based in the distinction between social rules, which are symbolically produced and changed through human agents' reflexivity and purpose, and biophysical rules, which are determined by functional relations between ecological components. The second guiding concept, conscious power, brings to the fore human agents' distinctive capacity to produce our own subjective identity and the consequences of this capacity for social-ecological organization. The third concept, congruence between subjective and objective dynamics, redefines sustainability as contingent on congruent relations between material and symbolic processes. Social-ecological theories and analyses based on these three guiding concepts would support the

Assessing ecological sustainability in urban planning - EcoBalance model

Energy Technology Data Exchange (ETDEWEB)

Wahlgren, I., Email: irmeli.wahlgren@vtt.fi

2012-06-15

Urban planning solutions and decisions have large-scale significance for ecological sustainability (eco-efficiency) the consumption of energy and other natural resources, the production of greenhouse gas and other emissions and the costs caused by urban form. Climate change brings new and growing challenges for urban planning. The EcoBalance model was developed to assess the sustainability of urban form and has been applied at various planning levels: regional plans, local master plans and detailed plans. The EcoBalance model estimates the total consumption of energy and other natural resources, the production of emissions and wastes and the costs caused directly and indirectly by urban form on a life cycle basis. The results of the case studies provide information about the ecological impacts of various solutions in urban development. (orig.)

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

Science.gov (United States)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2017-11-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

Ecological prediction with nonlinear multivariate time-frequency functional data models

Science.gov (United States)

Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

2013-01-01

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

Modelling ecological and human exposure to POPs in Venice lagoon - Part II: Quantitative uncertainty and sensitivity analysis in coupled exposure models.

Science.gov (United States)

Radomyski, Artur; Giubilato, Elisa; Ciffroy, Philippe; Critto, Andrea; Brochot, Céline; Marcomini, Antonio

2016-11-01

The study is focused on applying uncertainty and sensitivity analysis to support the application and evaluation of large exposure models where a significant number of parameters and complex exposure scenarios might be involved. The recently developed MERLIN-Expo exposure modelling tool was applied to probabilistically assess the ecological and human exposure to PCB 126 and 2,3,7,8-TCDD in the Venice lagoon (Italy). The 'Phytoplankton', 'Aquatic Invertebrate', 'Fish', 'Human intake' and PBPK models available in MERLIN-Expo library were integrated to create a specific food web to dynamically simulate bioaccumulation in various aquatic species and in the human body over individual lifetimes from 1932 until 1998. MERLIN-Expo is a high tier exposure modelling tool allowing propagation of uncertainty on the model predictions through Monte Carlo simulation. Uncertainty in model output can be further apportioned between parameters by applying built-in sensitivity analysis tools. In this study, uncertainty has been extensively addressed in the distribution functions to describe the data input and the effect on model results by applying sensitivity analysis techniques (screening Morris method, regression analysis, and variance-based method EFAST). In the exposure scenario developed for the Lagoon of Venice, the concentrations of 2,3,7,8-TCDD and PCB 126 in human blood turned out to be mainly influenced by a combination of parameters (half-lives of the chemicals, body weight variability, lipid fraction, food assimilation efficiency), physiological processes (uptake/elimination rates), environmental exposure concentrations (sediment, water, food) and eating behaviours (amount of food eaten). In conclusion, this case study demonstrated feasibility of MERLIN-Expo to be successfully employed in integrated, high tier exposure assessment. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites

Science.gov (United States)

Post, Hanna; Vrugt, Jasper A.; Fox, Andrew; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

2017-03-01

The Community Land Model (CLM) contains many parameters whose values are uncertain and thus require careful estimation for model application at individual sites. Here we used Bayesian inference with the DiffeRential Evolution Adaptive Metropolis (DREAM(zs)) algorithm to estimate eight CLM v.4.5 ecosystem parameters using 1 year records of half-hourly net ecosystem CO2 exchange (NEE) observations of four central European sites with different plant functional types (PFTs). The posterior CLM parameter distributions of each site were estimated per individual season and on a yearly basis. These estimates were then evaluated using NEE data from an independent evaluation period and data from "nearby" FLUXNET sites at 600 km distance to the original sites. Latent variables (multipliers) were used to treat explicitly uncertainty in the initial carbon-nitrogen pools. The posterior parameter estimates were superior to their default values in their ability to track and explain the measured NEE data of each site. The seasonal parameter values reduced with more than 50% (averaged over all sites) the bias in the simulated NEE values. The most consistent performance of CLM during the evaluation period was found for the posterior parameter values of the forest PFTs, and contrary to the C3-grass and C3-crop sites, the latent variables of the initial pools further enhanced the quality-of-fit. The carbon sink function of the forest PFTs significantly increased with the posterior parameter estimates. We thus conclude that land surface model predictions of carbon stocks and fluxes require careful consideration of uncertain ecological parameters and initial states.

ECOMOD - An ecological approach to radioecological modelling

International Nuclear Information System (INIS)

Sazykina, Tatiana G.

2000-01-01

A unified methodology is proposed to simulate the dynamic processes of radionuclide migration in aquatic food chains in parallel with their stable analogue elements. The distinguishing feature of the unified radioecological/ecological approach is the description of radionuclide migration along with dynamic equations for the ecosystem. The ability of the methodology to predict the results of radioecological experiments is demonstrated by an example of radionuclide (iron group) accumulation by a laboratory culture of the algae Platymonas viridis. Based on the unified methodology, the 'ECOMOD' radioecological model was developed to simulate dynamic radioecological processes in aquatic ecosystems. It comprises three basic modules, which are operated as a set of inter-related programs. The 'ECOSYSTEM' module solves non-linear ecological equations, describing the biomass dynamics of essential ecosystem components. The 'RADIONUCLIDE DISTRIBUTION' module calculates the radionuclide distribution in abiotic and biotic components of the aquatic ecosystem. The 'DOSE ASSESSMENT' module calculates doses to aquatic biota and doses to man from aquatic food chains. The application of the ECOMOD model to reconstruct the radionuclide distribution in the Chernobyl Cooling Pond ecosystem in the early period after the accident shows good agreement with observations

Sampling in ecology and evolution - bridging the gap between theory and practice

Science.gov (United States)

Albert, C.H.; Yoccoz, N.G.; Edwards, T.C.; Graham, C.H.; Zimmermann, N.E.; Thuiller, W.

2010-01-01

Sampling is a key issue for answering most ecological and evolutionary questions. The importance of developing a rigorous sampling design tailored to specific questions has already been discussed in the ecological and sampling literature and has provided useful tools and recommendations to sample and analyse ecological data. However, sampling issues are often difficult to overcome in ecological studies due to apparent inconsistencies between theory and practice, often leading to the implementation of simplified sampling designs that suffer from unknown biases. Moreover, we believe that classical sampling principles which are based on estimation of means and variances are insufficient to fully address many ecological questions that rely on estimating relationships between a response and a set of predictor variables over time and space. Our objective is thus to highlight the importance of selecting an appropriate sampling space and an appropriate sampling design. We also emphasize the importance of using prior knowledge of the study system to estimate models or complex parameters and thus better understand ecological patterns and processes generating these patterns. Using a semi-virtual simulation study as an illustration we reveal how the selection of the space (e.g. geographic, climatic), in which the sampling is designed, influences the patterns that can be ultimately detected. We also demonstrate the inefficiency of common sampling designs to reveal response curves between ecological variables and climatic gradients. Further, we show that response-surface methodology, which has rarely been used in ecology, is much more efficient than more traditional methods. Finally, we discuss the use of prior knowledge, simulation studies and model-based designs in defining appropriate sampling designs. We conclude by a call for development of methods to unbiasedly estimate nonlinear ecologically relevant parameters, in order to make inferences while fulfilling requirements of

Automated parameter estimation for biological models using Bayesian statistical model checking.

Science.gov (United States)

Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

2015-01-01

Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

Analysis of the Nevada-Applied-Ecology-Group model of transuranic radionuclide transport and dose

International Nuclear Information System (INIS)

Kercher, J.R.; Anspaugh, L.R.

1991-01-01

The authors analyze the model for estimating the dose from 239 Pu developed for the Nevada Applied Ecology Group (NAEG) by using sensitivity analysis and uncertainty analysis. Sensitivity analysis results suggest that the inhalation pathway is the critical pathway for the organs receiving the highest dose. Soil concentration and the factors controlling air concentration are the most important parameters. The only organ whose dose is sensitive to parameters in the ingestion pathway is the GI tract. The inhalation pathway accounts for 100% of the dose to lung, upper respiratory tract and thoracic lymph nodes; and 95% of the dose to liver, bone, kidney and total body. The GI tract receives 99% of its dose via ingestion. Leafy vegetable ingestion accounts for 70% of the dose from the ingestion pathway regardless of organ, peeled vegetables 20%; accidental soil ingestion 5% ingestion of beef liver 4%; beef muscle 1%. Uncertainty analysis indicates that choosing a uniform distribution for the input parameters produces a lognormal distribution of the dose. The ratio of the square root of the variance to the mean is three times greater for the doses than it is for the individual parameters. As found by the sensitivity analysis, the uncertainty analysis suggests that only a few parameters control the dose for each organ. All organs have similar distributions and variance to mean ratios except for the lymph nodes. (author)

Comparison of varying operating parameters on heavy metals ecological risk during anaerobic co-digestion of chicken manure and corn stover.

Science.gov (United States)

Yan, Yilong; Zhang, Liqiu; Feng, Li; Sun, Dezhi; Dang, Yan

2018-01-01

In this study, the potential ecological risk of heavy metals (Mn, Zn, Cu, Ni, As, Cd, Pb, Cr) accumulation from anaerobic co-digestion of chicken manure (CM) and corn stover (CS) was evaluated by comparing different initial substrate concentrations, digestion temperatures, and mixture ratios. Results showed that the highest volumetric methane yield of 20.3±1.4L/L reactor was achieved with a CS:CM ratio of 3:1 (on volatile solid basis) in mesophilic solid state anaerobic digestion (SS-AD). Although co-digestion increased the concentrations of all tested heavy metals and the direct toxicity of some heavy metals, the potential ecological risk index indicated that the digestates were all classified as low ecological risk. The biogasification and risk variation of heavy metals were affected by the operating parameters. These results are significant and should be taken into consideration when optimizing co-digestion of animal manure and crop residues during full-scale projects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Developing predictive systems models to address complexity and relevance for ecological risk assessment.

Science.gov (United States)

Forbes, Valery E; Calow, Peter

2013-07-01

Ecological risk assessments (ERAs) are not used as well as they could be in risk management. Part of the problem is that they often lack ecological relevance; that is, they fail to grasp necessary ecological complexities. Adding realism and complexity can be difficult and costly. We argue that predictive systems models (PSMs) can provide a way of capturing complexity and ecological relevance cost-effectively. However, addressing complexity and ecological relevance is only part of the problem. Ecological risk assessments often fail to meet the needs of risk managers by not providing assessments that relate to protection goals and by expressing risk in ratios that cannot be weighed against the costs of interventions. Once more, PSMs can be designed to provide outputs in terms of value-relevant effects that are modulated against exposure and that can provide a better basis for decision making than arbitrary ratios or threshold values. Recent developments in the modeling and its potential for implementation by risk assessors and risk managers are beginning to demonstrate how PSMs can be practically applied in risk assessment and the advantages that doing so could have. Copyright © 2013 SETAC.

Collection and analysis of remotely sensed data from the Rhode River Estuary Watershed. [ecological parameters of Chesapeake Bay

Science.gov (United States)

Jenkins, D. W.

1972-01-01

NASA chose the watershed of Rhode River, a small sub-estuary of the Bay, as a representative test area for intensive studies of remote sensing, the results of which could be extrapolated to other estuarine watersheds around the Bay. A broad program of ecological research was already underway within the watershed, conducted by the Smithsonian Institution's Chesapeake Bay Center for Environmental Studies (CBCES) and cooperating universities. This research program offered a unique opportunity to explore potential applications for remote sensing techniques. This led to a joint NASA-CBCES project with two basic objectives: to evaluate remote sensing data for the interpretation of ecological parameters, and to provide essential data for ongoing research at the CBCES. A third objective, dependent upon realization of the first two, was to extrapolate photointerpretive expertise gained at the Rhode River watershed to other portions of the Chesapeake Bay.

Sensitivity analysis of reactive ecological dynamics.

Science.gov (United States)

Verdy, Ariane; Caswell, Hal

2008-08-01

Ecological systems with asymptotically stable equilibria may exhibit significant transient dynamics following perturbations. In some cases, these transient dynamics include the possibility of excursions away from the equilibrium before the eventual return; systems that exhibit such amplification of perturbations are called reactive. Reactivity is a common property of ecological systems, and the amplification can be large and long-lasting. The transient response of a reactive ecosystem depends on the parameters of the underlying model. To investigate this dependence, we develop sensitivity analyses for indices of transient dynamics (reactivity, the amplification envelope, and the optimal perturbation) in both continuous- and discrete-time models written in matrix form. The sensitivity calculations require expressions, some of them new, for the derivatives of equilibria, eigenvalues, singular values, and singular vectors, obtained using matrix calculus. Sensitivity analysis provides a quantitative framework for investigating the mechanisms leading to transient growth. We apply the methodology to a predator-prey model and a size-structured food web model. The results suggest predator-driven and prey-driven mechanisms for transient amplification resulting from multispecies interactions.

The influence of model parameters on catchment-response

International Nuclear Information System (INIS)

Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.

2002-01-01

This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)

On parameter estimation in deformable models

DEFF Research Database (Denmark)

Fisker, Rune; Carstensen, Jens Michael

1998-01-01

Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...

Evaluation of Ecological Environmental Quality in a Coal Mining Area by Modelling Approach

Directory of Open Access Journals (Sweden)

Chaodong Yan

2017-07-01

Full Text Available The purpose of this study was to explore the effective method of the comprehensive evaluation of ecological environmental quality in a coal mining area. Firstly, we analyzed the ecological environmental effect of the coal mining area according to Pigovian Tax theory and, according to the results of the analysis and the demand for the selection of evaluation indices by the comprehensive evaluation, built the corresponding comprehensive evaluation index system. We then used the correlation function method to determine the relative weights of each index. We determined the basic standards of a comprehensive evaluation of ecological environmental quality in a coal mining area according to the actual situation of ecological environmental quality assessments in coal mining areas in our country and the relevant provisions of the government. On this basis, we built the two-level extension comprehensive evaluation model for the evaluation of ecological environmental quality in mining areas. Finally, we chose a certain coal mining area of Yanzhou Coal Mining Company Limited as the specific case. We used the relevant statistic data, technical and economic indices and the extension evaluation model to do the applied research of the comprehensive evaluation and tested the effectiveness of the comprehensive evaluation model.

Importance of ocean circulation in ecological modeling: An example from the North Sea

Science.gov (United States)

Skogen, Morten D.; Moll, Andreas

2005-09-01

There is an increasing number of ecological models for the North Sea around. Skogen and Moll (2000) [Skogen, M.D., Moll, A. 2000. Interannual variability of the North Sea primary production: comparison from two model studies. Continental Shelf Research 20 (2), 129-151] compared the interannual variability of the North Sea primary production using two state-of-the-art ecological models, NORWECOM and ECOHAM1. Their conclusion was that the two models agreed on an annual mean primary production, its variability and the timing and size of the peak production. On the other hand, there was a low (even negative dependent of area) correlation in the production in different years between the two models. In the present work, these conclusions are brought further. To try to better understand the observed differences between the two models, the two ecological models are run in an identical physical setting. With such a set-up also the interannual variability between the two models is in agreement, and it is concluded that the single most important factor for a reliable modeling of phytoplankton and nutrient distributions and transports within the North Sea is a proper physical model.

[A process of aquatic ecological function regionalization: The dual tree framework and conceptual model].

Science.gov (United States)

Guo, Shu Hai; Wu, Bo

2017-12-01

Aquatic ecological regionalization and aquatic ecological function regionalization are the basis of water environmental management of a river basin and rational utilization of an aquatic ecosystem, and have been studied in China for more than ten years. Regarding the common problems in this field, the relationship between aquatic ecological regionalization and aquatic ecological function regionalization was discussed in this study by systematic analysis of the aquatic ecological zoning and the types of aquatic ecological function. Based on the dual tree structure, we put forward the RFCH process and the diamond conceptual model. Taking Liaohe River basin as an example and referring to the results of existing regionalization studies, we classified the aquatic ecological function regions based on three-class aquatic ecological regionalization. This study provided a process framework for aquatic ecological function regionalization of a river basin.

An empirical model of the Baltic Sea reveals the importance of social dynamics for ecological regime shifts.

Science.gov (United States)

Lade, Steven J; Niiranen, Susa; Hentati-Sundberg, Jonas; Blenckner, Thorsten; Boonstra, Wiebren J; Orach, Kirill; Quaas, Martin F; Österblom, Henrik; Schlüter, Maja

2015-09-01

Regime shifts triggered by human activities and environmental changes have led to significant ecological and socioeconomic consequences in marine and terrestrial ecosystems worldwide. Ecological processes and feedbacks associated with regime shifts have received considerable attention, but human individual and collective behavior is rarely treated as an integrated component of such shifts. Here, we used generalized modeling to develop a coupled social-ecological model that integrated rich social and ecological data to investigate the role of social dynamics in the 1980s Baltic Sea cod boom and collapse. We showed that psychological, economic, and regulatory aspects of fisher decision making, in addition to ecological interactions, contributed both to the temporary persistence of the cod boom and to its subsequent collapse. These features of the social-ecological system also would have limited the effectiveness of stronger fishery regulations. Our results provide quantitative, empirical evidence that incorporating social dynamics into models of natural resources is critical for understanding how resources can be managed sustainably. We also show that generalized modeling, which is well-suited to collaborative model development and does not require detailed specification of causal relationships between system variables, can help tackle the complexities involved in creating and analyzing social-ecological models.

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 ...

Complexity, parameter sensitivity and parameter transferability in the modelling of floodplain inundation

Science.gov (United States)

Bates, P. D.; Neal, J. C.; Fewtrell, T. J.

2012-12-01

In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound

Social network models predict movement and connectivity in ecological landscapes

Science.gov (United States)

Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

2011-01-01

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Social network models predict movement and connectivity in ecological landscapes.

Science.gov (United States)

Fletcher, Robert J; Acevedo, Miguel A; Reichert, Brian E; Pias, Kyle E; Kitchens, Wiley M

2011-11-29

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

Science.gov (United States)

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

A practical method to assess model sensitivity and parameter uncertainty in C cycle models

Science.gov (United States)

Delahaies, Sylvain; Roulstone, Ian; Nichols, Nancy

2015-04-01

data streams or by considering longer observation windows no systematic analysis has been carried out so far to explain the large differences among results. We consider adjoint based methods to investigate inverse problems using DALEC and various data streams. Using resolution matrices we study the nature of the inverse problems (solution existence, uniqueness and stability) and show how standard regularization techniques affect resolution and stability properties. Instead of using standard prior information as a penalty term in the cost function to regularize the problems we constraint the parameter space using ecological balance conditions and inequality constraints. The efficiency and rapidity of this approach allows us to compute ensembles of solutions to the inverse problems from which we can establish the robustness of the variational method and obtain non Gaussian posterior distributions for the model parameters and initial carbon stocks.

Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

Science.gov (United States)

Kang, Ling; Zhou, Liwei

2018-02-01

Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.

Catastrophic regime shifts in model ecological communities are true phase transitions

International Nuclear Information System (INIS)

Capitán, J A; Cuesta, J A

2010-01-01

Ecosystems often undergo abrupt regime shifts in response to gradual external changes. These shifts are theoretically understood as a regime switch between alternative stable states of the ecosystem dynamical response to smooth changes in external conditions. Usual models introduce nonlinearities in the macroscopic dynamics of the ecosystem that lead to different stable attractors among which the shift takes place. Here we propose an alternative explanation of catastrophic regime shifts based on a recent model that pictures ecological communities as systems in continuous fluctuation, according to certain transition probabilities, between different micro-states in the phase space of viable communities. We introduce a spontaneous extinction rate that accounts for gradual changes in external conditions, and upon variations on this control parameter the system undergoes a regime shift with similar features to those previously reported. Under our microscopic viewpoint we recover the main results obtained in previous theoretical and empirical work (anomalous variance, hysteresis cycles, trophic cascades). The model predicts a gradual loss of species in trophic levels from bottom to top near the transition. But more importantly, the spectral analysis of the transition probability matrix allows us to rigorously establish that we are observing the fingerprints, in a finite size system, of a true phase transition driven by background extinctions

Sustainability and profitability in ecological systems with harvesting

International Nuclear Information System (INIS)

Gaff, S.J.; Protopopescu, V.

1992-08-01

A simple model of economic and ecological interplay for a system of two interacting populations grown in a closed environment and harvested periodically for economic purposes was analyzed. The analysis was carried out by exploring the parameter space of the model, defined by a discrete map, a harvesting strategy, and an objective functional. Results showed nonmonotonicities of the outcome and sharp sensitivities that depend on the values of the parameters and that are caused by the discrete nature of the system. This approach may prove useful for solving problems that cannot be solved analytically and for providing some guidance in the management of complex systems

Temporal variation in the ecology of Kuramo water, Lagos Nigeria ...

African Journals Online (AJOL)

Temporal variation in the ecology of Kuramo water was studied in the Lagos lagoon complex. Physicochemical parameters and heavy metals concentration were analyzed. Eight sites were marked using the geographical positioning system (GPS model-12). Water chemistry was determined for 8 months and sampling was ...

Sensitivity analysis of Repast computational ecology models with R/Repast.

Science.gov (United States)

Prestes García, Antonio; Rodríguez-Patón, Alfonso

2016-12-01

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom-up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in-silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results.

Application of an Ecological Model for the Cibolo Creek Watershed

National Research Council Canada - National Science Library

Price, David

2004-01-01

The U.S. Army Engineer District, Fort Worth (CESWF) is involved in demon- strating the utility of an ecological model in the performance and interpretation of a comprehensive General Investigations (GI...

Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

Directory of Open Access Journals (Sweden)

Jonathan R Karr

2015-05-01

Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Systematic parameter inference in stochastic mesoscopic modeling

Energy Technology Data Exchange (ETDEWEB)

Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

Sensitivity Analysis in Agent-Based Models of Socio-Ecological Systems: An Example in Agricultural Land Conservation for Lake Water Quality Improvement

Science.gov (United States)

Ligmann-Zielinska, A.; Kramer, D. B.; Spence Cheruvelil, K.; Soranno, P.

2012-12-01

Socio-ecological systems are dynamic and nonlinear. To account for this complexity, we employ agent-based models (ABMs) to study macro-scale phenomena resulting from micro-scale interactions among system components. Because ABMs typically have many parameters, it is challenging to identify which parameters contribute to the emerging macro-scale patterns. In this paper, we address the following question: What is the extent of participation in agricultural land conservation programs given heterogeneous landscape, economic, social, and individual decision making criteria in complex lakesheds? To answer this question, we: [1] built an ABM for our model system; [2] simulated land use change resulting from agent decision making, [3] estimated the uncertainty of the model output, decomposed it and apportioned it to each of the parameters in the model. Our model system is a freshwater socio-ecological system - that of farmland and lake water quality within a region containing a large number of lakes and high proportions of agricultural lands. Our study focuses on examining how agricultural land conversion from active to fallow reduces freshwater nutrient loading and improves water quality. Consequently, our ABM is composed of farmer agents who make decisions related to participation in a government-sponsored Conservation Reserve Program (CRP) managed by the Farm Service Agency (FSA). We also include an FSA agent, who selects enrollment offers made by farmers and announces the signup results leading to land use change. The model is executed in a Monte Carlo simulation framework to generate a distribution of maps of fallow lands that are used for calculating nutrient loading to lakes. What follows is a variance-based sensitivity analysis of the results. We compute sensitivity indices for individual parameters and their combinations, allowing for identification of the most influential as well as the insignificant inputs. In the case study, we observe that farmland

Biological soil crusts (biocrusts) as a model system in community, landscape and ecosystem ecology

Science.gov (United States)

Bowker, Matthew A.; Maestre, Fernando T.; Eldridge, David; Belnap, Jayne; Castillo-Monroy, Andrea; Escolar, Cristina; Soliveres, Santiago

2014-01-01

Model systems have had a profound influence on the development of ecological theory and general principles. Compared to alternatives, the most effective models share some combination of the following characteristics: simpler, smaller, faster, general, idiosyncratic or manipulable. We argue that biological soil crusts (biocrusts) have unique combinations of these features that should be more widely exploited in community, landscape and ecosystem ecology. In community ecology, biocrusts are elucidating the importance of biodiversity and spatial pattern for maintaining ecosystem multifunctionality due to their manipulability in experiments. Due to idiosyncrasies in their modes of facilitation and competition, biocrusts have led to new models on the interplay between environmental stress and biotic interactions and on the maintenance of biodiversity by competitive processes. Biocrusts are perhaps one of the best examples of micro-landscapes—real landscapes that are small in size. Although they exhibit varying patch heterogeneity, aggregation, connectivity and fragmentation, like macro-landscapes, they are also compatible with well-replicated experiments (unlike macro-landscapes). In ecosystem ecology, a number of studies are imposing small-scale, low cost manipulations of global change or state factors in biocrust micro-landscapes. The versatility of biocrusts to inform such disparate lines of inquiry suggests that they are an especially useful model system that can enable researchers to see ecological principles more clearly and quickly.

Statistical ecology comes of age

Science.gov (United States)

Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-01-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data. PMID:25540151

Statistical ecology comes of age.

Science.gov (United States)

Gimenez, Olivier; Buckland, Stephen T; Morgan, Byron J T; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-12-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

[Regional ecological construction and mission of landscape ecology].

Science.gov (United States)

Xiao, Duning; Xie, Fuju; Wei, Jianbing

2004-10-01

The eco-construction on regional and landscape scale is the one which can be used to specific landscape and intercrossing ecosystem in specific region including performing scientific administration of ecosystem and optimizing environmental function. Recently, the government has taken a series of significant projects into action, such as national forest protection item, partly forest restoration, and adjustment of water, etc. Enforcing regional eco-construction and maintaining the ecology security of the nation have become the strategic requisition. In various regions, different eco-construction should be applied, for example, performing ecological safeguard measure in ecological sensitive zone, accommodating the ecological load in ecological fragile zone, etc., which can control the activities of human being, so that, sustainable development can be reached. Facing opportunity and challenge in the development of landscape ecology, we have some key topics: landscape pattern of ecological security, land use and ecological process, landscape changes under human activity stress, quantitative evaluation of the influence on human being activities, evaluation of zonal ecological security and advance warning of ecological risk, and planning and optimizing of model in landscape eco-construction.

Test models for improving filtering with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

Gershgorin, B.; Harlim, J.; Majda, A.J.

2010-01-01

The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.

Dynamic complexities in a parasitoid-host-parasitoid ecological model

International Nuclear Information System (INIS)

Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili

2009-01-01

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model

Dynamic complexities in a parasitoid-host-parasitoid ecological model

Energy Technology Data Exchange (ETDEWEB)

Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)

2009-01-15

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.

Local Geostatistical Models and Big Data in Hydrological and Ecological Applications

Science.gov (United States)

Hristopulos, Dionissios

2015-04-01

The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property

Benefits of using a Social-Ecological Systems Approach to Conceptualize and Model Wetlands Restoration

Science.gov (United States)

Using a social-ecological systems (SES) perspective to examine wetland restoration helps decision-makers recognize interdependencies and relations between ecological and social components of coupled systems. Conceptual models are an invaluable tool to capture, visualize, and orga...

Using observation-level random effects to model overdispersion in count data in ecology and evolution

Directory of Open Access Journals (Sweden)

Xavier A. Harrison

2014-10-01

Full Text Available Overdispersion is common in models of count data in ecology and evolutionary biology, and can occur due to missing covariates, non-independent (aggregated data, or an excess frequency of zeroes (zero-inflation. Accounting for overdispersion in such models is vital, as failing to do so can lead to biased parameter estimates, and false conclusions regarding hypotheses of interest. Observation-level random effects (OLRE, where each data point receives a unique level of a random effect that models the extra-Poisson variation present in the data, are commonly employed to cope with overdispersion in count data. However studies investigating the efficacy of observation-level random effects as a means to deal with overdispersion are scarce. Here I use simulations to show that in cases where overdispersion is caused by random extra-Poisson noise, or aggregation in the count data, observation-level random effects yield more accurate parameter estimates compared to when overdispersion is simply ignored. Conversely, OLRE fail to reduce bias in zero-inflated data, and in some cases increase bias at high levels of overdispersion. There was a positive relationship between the magnitude of overdispersion and the degree of bias in parameter estimates. Critically, the simulations reveal that failing to account for overdispersion in mixed models can erroneously inflate measures of explained variance (r2, which may lead to researchers overestimating the predictive power of variables of interest. This work suggests use of observation-level random effects provides a simple and robust means to account for overdispersion in count data, but also that their ability to minimise bias is not uniform across all types of overdispersion and must be applied judiciously.

Macroscale hydrologic modeling of ecologically relevant flow metrics

Science.gov (United States)

Wenger, Seth J.; Luce, Charles H.; Hamlet, Alan F.; Isaak, Daniel J.; Neville, Helen M.

2010-09-01

Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe and forecast hydrologic changes but has been calibrated and applied mainly to large rivers. An important question is how well VIC runoff simulations serve to answer questions about hydrologic changes in smaller streams, which are important habitat for many fish species. To answer this question, we aggregated gridded VIC outputs within the drainage basins of 55 streamflow gages in the Pacific Northwest United States and compared modeled hydrographs and summary metrics to observations. For most streams, several ecologically relevant aspects of the hydrologic regime were accurately modeled, including center of flow timing, mean annual and summer flows and frequency of winter floods. Frequencies of high and low flows in the summer were not well predicted, however. Predictions were worse for sites with strong groundwater influence, and some sites showed errors that may result from limitations in the forcing climate data. Higher resolution (1/16th degree) modeling provided small improvements over lower resolution (1/8th degree). Despite some limitations, the VIC model appears capable of representing several ecologically relevant hydrologic characteristics in streams, making it a useful tool for understanding the effects of hydrology in delimiting species distributions and predicting the potential effects of climate shifts on aquatic organisms.

Introduction. Antarctic ecology: from genes to ecosystems. Part 2. Evolution, diversity and functional ecology.

Science.gov (United States)

Rogers, Alex D; Murphy, Eugene J; Johnston, Nadine M; Clarke, Andrew

2007-12-29

The Antarctic biota has evolved over the last 100 million years in increasingly isolated and cold conditions. As a result, Antarctic species, from micro-organisms to vertebrates, have adapted to life at extremely low temperatures, including changes in the genome, physiology and ecological traits such as life history. Coupled with cycles of glaciation that have promoted speciation in the Antarctic, this has led to a unique biota in terms of biogeography, patterns of species distribution and endemism. Specialization in the Antarctic biota has led to trade-offs in many ecologically important functions and Antarctic species may have a limited capacity to adapt to present climate change. These include the direct effects of changes in environmental parameters and indirect effects of increased competition and predation resulting from altered life histories of Antarctic species and the impacts of invasive species. Ultimately, climate change may alter the responses of Antarctic ecosystems to harvesting from humans. The unique adaptations of Antarctic species mean that they provide unique models of molecular evolution in natural populations. The simplicity of Antarctic communities, especially from terrestrial systems, makes them ideal to investigate the ecological implications of climate change, which are difficult to identify in more complex systems.

Increasing connectivity between metapopulation ecology and landscape ecology.

Science.gov (United States)

Howell, Paige E; Muths, Erin; Hossack, Blake R; Sigafus, Brent H; Chandler, Richard B

2018-05-01

Metapopulation ecology and landscape ecology aim to understand how spatial structure influences ecological processes, yet these disciplines address the problem using fundamentally different modeling approaches. Metapopulation models describe how the spatial distribution of patches affects colonization and extinction, but often do not account for the heterogeneity in the landscape between patches. Models in landscape ecology use detailed descriptions of landscape structure, but often without considering colonization and extinction dynamics. We present a novel spatially explicit modeling framework for narrowing the divide between these disciplines to advance understanding of the effects of landscape structure on metapopulation dynamics. Unlike previous efforts, this framework allows for statistical inference on landscape resistance to colonization using empirical data. We demonstrate the approach using 11 yr of data on a threatened amphibian in a desert ecosystem. Occupancy data for Lithobates chiricahuensis (Chiricahua leopard frog) were collected on the Buenos Aires National Wildlife Refuge (BANWR), Arizona, USA from 2007 to 2017 following a reintroduction in 2003. Results indicated that colonization dynamics were influenced by both patch characteristics and landscape structure. Landscape resistance increased with increasing elevation and distance to the nearest streambed. Colonization rate was also influenced by patch quality, with semi-permanent and permanent ponds contributing substantially more to the colonization of neighboring ponds relative to intermittent ponds. Ponds that only hold water intermittently also had the highest extinction rate. Our modeling framework can be widely applied to understand metapopulation dynamics in complex landscapes, particularly in systems in which the environment between habitat patches influences the colonization process. © 2018 by the Ecological Society of America.

Spatial agent-based models for socio-ecological systems: challenges and prospects

NARCIS (Netherlands)

de Filatova, T.; Verburg, P.H.; Parker, D.C.; Stannard, S.R.

2013-01-01

Departing from the comprehensive reviews carried out in the field, we identify the key challenges that agent-based methodology faces when modeling coupled socio-ecological systems. Focusing primarily on the papers presented in this thematic issue, we review progress in spatial agent-based models

Exploiting intrinsic fluctuations to identify model parameters.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

2015-04-01

Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.

Using ecological production functions to link ecological ...

Science.gov (United States)

Ecological production functions (EPFs) link ecosystems, stressors, and management actions to ecosystem services (ES) production. Although EPFs are acknowledged as being essential to improve environmental management, their use in ecological risk assessment has received relatively little attention. Ecological production functions may be defined as usable expressions (i.e., models) of the processes by which ecosystems produce ES, often including external influences on those processes. We identify key attributes of EPFs and discuss both actual and idealized examples of their use to inform decision making. Whenever possible, EPFs should estimate final, rather than intermediate, ES. Although various types of EPFs have been developed, we suggest that EPFs are more useful for decision making if they quantify ES outcomes, respond to ecosystem condition, respond to stressor levels or management scenarios, reflect ecological complexity, rely on data with broad coverage, have performed well previously, are practical to use, and are open and transparent. In an example using pesticides, we illustrate how EPFs with these attributes could enable the inclusion of ES in ecological risk assessment. The biggest challenges to ES inclusion are limited data sets that are easily adapted for use in modeling EPFs and generally poor understanding of linkages among ecological components and the processes that ultimately deliver the ES. We conclude by advocating for the incorporation into E

Incorporating model parameter uncertainty into inverse treatment planning

International Nuclear Information System (INIS)

Lian Jun; Xing Lei

2004-01-01

Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

Review of the ecological parameters of radionuclide turnover in vertebrate food chains

International Nuclear Information System (INIS)

Kitchings, T.; DiGregorio, D.; Van Voris, P.

1976-01-01

Ecological studies of radionuclides in the environment have a long tradition in developing the capability to identify and predict movement and concentration of nuclides in agricultural food chains leading to man. Food chain pathways and transfer coefficients for the nonagricultural portions of natural and managed ecosystems characteristic of affected habitats adjacent to nuclear facilities have not been adequately characterized to establish reliable models for radionuclide releases. This information is necessary in order to assess the impact that such installations will have on the biota of natural ecosystems. Since food chains are the major processes transferring elements from one trophic level to another in terrestrial ecosystems, information is needed on the (a) food-chain transfer pathways, (b) bioconcentration by each trophic component and (c) turnover rates by receptor organisms. These data are prerequisite inputs for food-chain transport models and can be correlated with species characteristics (e.g., body weight and feeding habits), to provide indices for predictive calculations. Application of these models for radionuclide transfer can aid in the assessment of radioactive releases from nuclear reactor facilities to terrestrial nonagricultural food chains

Model Configuration and Innovative Design of College Students’ Ecological Civilization Construction

Science.gov (United States)

Chengwen, Yang

2018-02-01

This study is based on Marxist eco-civilization thought, combining with Eco management theory, puts forward solutions for college students’ ecological civilization construction. The paper based on the perspective of ecological management theory to analyze the main elements of eco-civilization construction of college students, mainly including five categories. In view of above-mentioned analyze, constructed the model of college students’ eco-civilization which is based on the theory of eco-management, and put forward on concrete methods to improve it.

An ecological assessment of pasturelands in the Balkhash area of Kazakhstan with remote sensing and models

International Nuclear Information System (INIS)

Lebed, L; Qi, J; Heilman, P

2012-01-01

The 187 million hectares of pasturelands in Kazakhstan play a key role in the nation’s economy, as livestock production accounted for 54% of total agricultural production in 2010. However, more than half of these lands have been degraded as a result of unregulated grazing practices. Therefore, effective long term ecological monitoring of pasturelands in Kazakhstan is imperative to ensure sustainable pastureland management. As a case study in this research, we demonstrated how the ecological conditions could be assessed with remote sensing technologies and pastureland models. The example focuses on the southern Balkhash area with study sites on a foothill plain with Artemisia-ephemeral plants and a sandy plain with psammophilic vegetation in the Turan Desert. The assessment was based on remotely sensed imagery and meteorological data, a geobotanical archive and periodic ground sampling. The Pasture agrometeorological model was used to calculate biological, ecological and economic indicators to assess pastureland condition. The results showed that field surveys, meteorological observations, remote sensing and ecological models, such as Pasture, could be combined to effectively assess the ecological conditions of pasturelands and provide information about forage production that is critically important for balancing grazing and ecological conservation. (letter)

Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example%生态过程模型敏感参数最优取值的时空异质性分析——以BIOME-BGC模型为例

Institute of Scientific and Technical Information of China (English)

李一哲; 张廷龙; 刘秋雨; 李英

2018-01-01

The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present.However,there are many parameters for these models,and weather the reasonable values of these parameters were taken,have important impact on the models simulation results.In the past,the sensitivity and the optimization of model parameters were analyzed and discussed in many researches.But the temporal and spatial heterogeneity of the optimal parameters is less concerned.In this paper,the BIOME-BGC model was used as an example.In the evergreen broad-leaved forest,deciduous broad-leaved forest and C3 grassland,the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type.The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site.Then we constructed the temporal heterogeneity judgment index,the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters.The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types,but the selected sensitive parameters were mostly consistent.The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types.The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity.In addition,the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

Science.gov (United States)

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Integrated Ecological-Economic Modeling of Regions with the use of GIS Technologies

Directory of Open Access Journals (Sweden)

G.N. Bulatova

2017-11-01

Full Text Available The paper shows the process of modeling the integrated map “Scheme of the ecological and economic regionalization of the territory of the Russian Federation on the basis of the mineral and raw materials base of natural adsorbents” using GIS technologies. The map is based on three main groups of indicators: natural, economic and environmental. The ecological content of the map is characterized by indicators that are potential or actual sources of pollutant release into the environment (nuclear power plants, nuclear reactors, radioactive waste storage and disposal sites, nuclear test sites, industrial enterprises, railways, operating and under construction oil pipelines, hydrocarbon fields, etc.. The economic component of the map is the reserves estimated by the indicators of study and development, the relationship to the subsoil fund and forecast resources. The natural group of indicators is represented by the mineral and raw material base of natural adsorbents (fields and objects of forecast resources that can be used to prevent harmful emissions and for the ecological and economic rehabilitation of contaminated areas. Based on the analysis of cartographic data, the ecological and economic areas of the territorial distribution of man-caused environmental impacts and the presence of adsorption raw materials are identified. As an example, a description is given of the ecological and economic model of the regionalization of the Privolzhsky Federal District using the GIS “Mineral resource base of natural adsorbents of Russia” developed at the Federal State Unitary Enterprise TsNIIgeolnerud.

Establishing statistical models of manufacturing parameters

International Nuclear Information System (INIS)

Senevat, J.; Pape, J.L.; Deshayes, J.F.

1991-01-01

This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature

Some tests for parameter constancy in cointegrated VAR-models

DEFF Research Database (Denmark)

Hansen, Henrik; Johansen, Søren

1999-01-01

Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ......Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations......, and another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...

Edge Modeling by Two Blur Parameters in Varying Contrasts.

Science.gov (United States)

Seo, Suyoung

2018-06-01

This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.

Emergence of scale-free characteristics in socio-ecological systems with bounded rationality.

Science.gov (United States)

Kasthurirathna, Dharshana; Piraveenan, Mahendra

2015-06-11

Socio-ecological systems are increasingly modelled by games played on complex networks. While the concept of Nash equilibrium assumes perfect rationality, in reality players display heterogeneous bounded rationality. Here we present a topological model of bounded rationality in socio-ecological systems, using the rationality parameter of the Quantal Response Equilibrium. We argue that system rationality could be measured by the average Kullback--Leibler divergence between Nash and Quantal Response Equilibria, and that the convergence towards Nash equilibria on average corresponds to increased system rationality. Using this model, we show that when a randomly connected socio-ecological system is topologically optimised to converge towards Nash equilibria, scale-free and small world features emerge. Therefore, optimising system rationality is an evolutionary reason for the emergence of scale-free and small-world features in socio-ecological systems. Further, we show that in games where multiple equilibria are possible, the correlation between the scale-freeness of the system and the fraction of links with multiple equilibria goes through a rapid transition when the average system rationality increases. Our results explain the influence of the topological structure of socio-ecological systems in shaping their collective cognitive behaviour, and provide an explanation for the prevalence of scale-free and small-world characteristics in such systems.

Informative-Consulting Model for Ecological Estimation of Influence of NPP on Surrounding Environment

International Nuclear Information System (INIS)

Vlasenko, N.I.; Vlasova, E.V.; Korotenko, M.N.; Pyshnaya, D.V.

2006-01-01

In the NAEK 'Energoatom' the development of informative-consulting model (ICM) for ecological estimation of influence of NPP on surrounding an environment has began. In ICM the use of modern program complexes is foreseen that will allow to analyses data of the radio ecological monitoring in the real-time mode and promote the validity of administrative decisions

Ecological hierarchies and self-organisation - Pattern analysis, modelling and process integration across scales

Science.gov (United States)

Reuter, H.; Jopp, F.; Blanco-Moreno, J. M.; Damgaard, C.; Matsinos, Y.; DeAngelis, D.L.

2010-01-01

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an 'across-scale-approach', closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems. ?? 2010 Gesellschaft f??r ??kologie.

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

Science.gov (United States)

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

Explanatory models for ecological response surfaces

International Nuclear Information System (INIS)

Jager, H.I.; Overton, W.S.

1991-01-01

Understanding the spatial organization of ecological systems is a fundamental part of ecosystem study. While discovering the causal relationships of this organization is an important goal, our purpose of spatial description on a regional scale is best met by use of explanatory variables that are somewhat removed from the mechanistic causal level. Regional level understanding is best obtained from explanatory variables that reflect spatial gradients at the regional scale and from categorical variables that describe the discrete constituents of (statistical) populations, such as lakes. In this paper, we use a regression model to predict lake acid neutralizing capacity (ANC) based on environmental predictor variables over a large region. These predictions are used to produce model-based population estimates. Two key features of our modeling approach are that is honors the spatial context and the design of the sample data. The spatial context of the data are brought into the analysis of model residuals through the interpretation of residual maps and semivariograms. The sampling design is taken into account by including stratification variables from the design in the model. This ensures that the model applies to a real population of lakes (the target population), rather than whatever hypothetical population the sample is a random sample of

Integrated models to support multiobjective ecological restoration decisions.

Science.gov (United States)

Fraser, Hannah; Rumpff, Libby; Yen, Jian D L; Robinson, Doug; Wintle, Brendan A

2017-12-01

Many objectives motivate ecological restoration, including improving vegetation condition, increasing the range and abundance of threatened species, and improving species richness and diversity. Although models have been used to examine the outcomes of ecological restoration, few researchers have attempted to develop models to account for multiple, potentially competing objectives. We developed a combined state-and-transition, species-distribution model to predict the effects of restoration actions on vegetation condition and extent, bird diversity, and the distribution of several bird species in southeastern Australian woodlands. The actions reflected several management objectives. We then validated the models against an independent data set and investigated how the best management decision might change when objectives were valued differently. We also used model results to identify effective restoration options for vegetation and bird species under a constrained budget. In the examples we evaluated, no one action (improving vegetation condition and extent, increasing bird diversity, or increasing the probability of occurrence for threatened species) provided the best outcome across all objectives. In agricultural lands, the optimal management actions for promoting the occurrence of the Brown Treecreeper (Climacteris picumnus), an iconic threatened species, resulted in little improvement in the extent of the vegetation and a high probability of decreased vegetation condition. This result highlights that the best management action in any situation depends on how much the different objectives are valued. In our example scenario, no management or weed control were most likely to be the best management options to satisfy multiple restoration objectives. Our approach to exploring trade-offs in management outcomes through integrated modeling and structured decision-support approaches has wide application for situations in which trade-offs exist between competing

Seveso 1986, Chernobyl 1976: a physicist' look at 2 ecological disasters

Science.gov (United States)

Ratti, S.

2004-05-01

Seveso suffered a chemical accident with a severe loss of supertoxic material (TCCD) released in the atmosphere; Chernobyl was a world known nuclear accident. The pollution induced by the two accident are analysed in term of fractal models. The first case involved a limited micro ecological system; the second one spread over a macro ecological system. The pollution is reproduced by means of simple Fractal Sum of Pulses models in the Seveso region; for the Chernobyl accident in northern Italy and in several european Countries. The 2 accidents are also analysed in terms of Universal Multifractals showing that thethe parameters α and C1 are those describing respectively rainfall (Seveso) and cloud formation (Chernobyl).

ecological geological maps: GIS-based evaluation of the Geo-Ecological Quality Index (GEQUI) in Sicily (Central Mediterranean)

Science.gov (United States)

Nigro, Fabrizio; Arisco, Giuseppe; Perricone, Marcella; Renda, Pietro; Favara, Rocco

2010-05-01

synthetic way. The first, characterized or estimated, prognosticated one or several indexes of geological ecological conditions. In the second type of maps, the whole complex is reflected, which defined the modern or prognosticable ecological geological situation. Regarding the ecological geological zoning maps, the contemporary state of ecological geological conditions may be evaluated by a range of parameters into classes of conditions and, on the basis of these informations, the estimation from the position of comfort and safety of human life and function of ecosystem is given. Otherwise, the concept of geoecological land evaluation has become established in the study of landscape/environmental plannings in recent years. It requires different thematic data-sets, deriving from the natural-, social- and amenity-environmental resources analysis, that may be translate in environmental (vulnerability/quality) indexes. There have been some attempts to develop integrated indices related to various aspects of the environment within the framework of sustainable development (e.g.: United Nations Commission on Sustainable Development, World Economic Forum, Advisory Board on Indicators of Sustainable Development of the International Institute for Sustainable Development, Living Planet Index established by the World Wide Fund for Nature, etc.). So, the ecological geological maps represent the basic tool for the geoecological land evaluation policies and may be computed in terms of index-maps. On these basis, a GIS application for assessing the ecological geological zoning is presented for Sicily (Central Mediterranean). The Geo-Ecological Quality Index (GEQUI) map was computed by considering a lot of variables. Ten variables (lithology, climate, landslide distribution, erosion rate, soil type, land cover, habitat, groundwater pollution, roads density and buildings density) generated from available data, were used in the model, in which weighting values to each informative layer were

Ecological Interventionist Causal Models in Psychosis: Targeting Psychological Mechanisms in Daily Life

Science.gov (United States)

Reininghaus, Ulrich; Depp, Colin A.; Myin-Germeys, Inez

2016-01-01

Integrated models of psychotic disorders have posited a number of putative psychological mechanisms that may contribute to the development of psychotic symptoms, but it is only recently that a modest amount of experience sampling research has provided evidence on their role in daily life, outside the research laboratory. A number of methodological challenges remain in evaluating specificity of potential causal links between a given psychological mechanism and psychosis outcomes in a systematic fashion, capitalizing on longitudinal data to investigate temporal ordering. In this article, we argue for testing ecological interventionist causal models that draw on real world and real-time delivered, ecological momentary interventions for generating evidence on several causal criteria (association, time order, and direction/sole plausibility) under real-world conditions, while maximizing generalizability to social contexts and experiences in heterogeneous populations. Specifically, this approach tests whether ecological momentary interventions can (1) modify a putative mechanism and (2) produce changes in the mechanism that lead to sustainable changes in intended psychosis outcomes in individuals’ daily lives. Future research using this approach will provide translational evidence on the active ingredients of mobile health and in-person interventions that promote sustained effectiveness of ecological momentary interventions and, thereby, contribute to ongoing efforts that seek to enhance effectiveness of psychological interventions under real-world conditions. PMID:26707864

Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-06-27

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699

Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Wasiolek, M. A.

2003-01-01

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699], Section 6.2). Parameter values

Parameter estimation in stochastic rainfall-runoff models

DEFF Research Database (Denmark)

Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

2006-01-01

A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...

On Bayesian shared component disease mapping and ecological regression with errors in covariates.

Science.gov (United States)

MacNab, Ying C

2010-05-20

Recent literature on Bayesian disease mapping presents shared component models (SCMs) for joint spatial modeling of two or more diseases with common risk factors. In this study, Bayesian hierarchical formulations of shared component disease mapping and ecological models are explored and developed in the context of ecological regression, taking into consideration errors in covariates. A review of multivariate disease mapping models (MultiVMs) such as the multivariate conditional autoregressive models that are also part of the more recent Bayesian disease mapping literature is presented. Some insights into the connections and distinctions between the SCM and MultiVM procedures are communicated. Important issues surrounding (appropriate) formulation of shared- and disease-specific components, consideration/choice of spatial or non-spatial random effects priors, and identification of model parameters in SCMs are explored and discussed in the context of spatial and ecological analysis of small area multivariate disease or health outcome rates and associated ecological risk factors. The methods are illustrated through an in-depth analysis of four-variate road traffic accident injury (RTAI) data: gender-specific fatal and non-fatal RTAI rates in 84 local health areas in British Columbia (Canada). Fully Bayesian inference via Markov chain Monte Carlo simulations is presented. Copyright 2010 John Wiley & Sons, Ltd.

Evolving Approaches and Technologies to Enhance the Role of Ecological Modeling in Decision Making

Science.gov (United States)

Eric Gustafson; John Nestler; Louis Gross; Keith M. Reynolds; Daniel Yaussy; Thomas P. Maxwell; Virginia H. Dale

2002-01-01

Understanding the effects of management activities is difficult for natural resource managers and decision makers because ecological systems are highly complex and their behavior is difficult to predict. Furthermore, the empirical studies necessary to illuminate all management questions quickly become logistically complicated and cost prohibitive. Ecological models...

Modeling socioeconomic and ecologic aspects of land-use change

International Nuclear Information System (INIS)

Dale, V.H.; Pedlowski, M.A.; O'Neill, R.V.; Southworth, F.

1992-01-01

Land use change is one of the major factors affecting global environmental conditions. Prevalent types of land-use change include replacing forests with agriculture, mines or ranches; forest degradation from collection of firewood; and forest logging. A global effect of wide-scale deforestation is an increase in atmospheric carbon dioxide concentration, which may affect climate. Regional effects include loss of biodiversity and disruption of hydrologic regimes. Local effects include soil erosion, siltation and decreases in soil fertility, loss of extractive reserves, and disruption of indigenous people. Modeling land use change requires combining socioeconomic and ecological factors because socioeconomic forces frequently initiate land-use change and are affected by the subsequent ecological degradation. This paper describes a modeling system that integrates submodels of human colonization and impacts to estimate patterns and rates of deforestation under different immigration and land use scenarios. Immigration which follows road building or paving is a major factor in the rapid deforestation of previously inaccessible areas. Roads facilitate colonization, allow access for large machines, and provide transportation routes for mort of raw materials and produce

A method for model identification and parameter estimation

International Nuclear Information System (INIS)

Bambach, M; Heinkenschloss, M; Herty, M

2013-01-01

We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)

Place prioritization for biodiversity content using species ecological niche modeling

OpenAIRE

Víctor Sánchez-Cordero; Verónica Cirelli; Mariana Munguial; Sahotra Sarkar

2005-01-01

Place prioritization for biodiversity representation is essential for conservation planning, particularly in megadiverse countries where high deforestation threatens biodiversity. Given the collecting biases and uneven sampling of biological inventories, there is a need to develop robust models of species’ distributions. By modeling species’ ecological niches using point occurrence data and digitized environmental feature maps, we can predict potential and extant distributions of species in u...

Least square method of estimation of ecological half-lives of radionuclides in sediments

International Nuclear Information System (INIS)

Ranade, A.K.; Pandey, M.; Datta, D.; Ravi, P.M.

2012-01-01

Long term behavior of radionuclides in the environment is an important issue for estimating probable radiological consequences and associated risks. It is also useful for evaluating potential use of contaminated areas and the possible effectiveness of remediation activities. The long term behavior is quantified by means of ecological half life, a parameter that aggregates all processes except radioactive decay which causes a decrease of activity in a specific medium. The process involved in ecological half life depends upon the environmental condition of the medium involved. A fitting model based on least square regression approach was used to evaluate the ecological half life. This least square method has to run several times to evaluate the number of ecological half lives present in the medium for the radionuclide. The case study data considered here is for 137 Cs in Mumbai Harbour Bay. The study shows the trend of 137 Cs over the years at a location in Mumbai Harbour Bay. First iteration model illustrate the ecological half life as 4.94 y and subsequently it passes through a number of runs for more number of ecological half-life present by goodness of fit test. The paper presents a methodology for evaluating ecological half life and exemplifies it with a case study of 137 Cs. (author)

Modeling Forest Succession among Ecological Land Units in Northern Minnesota

Directory of Open Access Journals (Sweden)

George Host

1998-12-01

Full Text Available Field and modeling studies were used to quantify potential successional pathways among fine-scale ecological classification units within two geomorphic regions of north-central Minnesota. Soil and overstory data were collected on plots stratified across low-relief ground moraines and undulating sand dunes. Each geomorphic feature was sampled across gradients of topography or soil texture. Overstory conditions were sampled using five variable-radius point samples per plot; soil samples were analyzed for carbon and nitrogen content. Climatic, forest composition, and soil data were used to parameterize the sample plots for use with LINKAGES, a forest growth model that simulates changes in composition and soil characteristics over time. Forest composition and soil properties varied within and among geomorphic features. LINKAGES simulations were using "bare ground" and the current overstory as starting conditions. Northern hardwoods or pines dominated the late-successional communities of morainal and dune landforms, respectively. The morainal landforms were dominated by yellow birch and sugar maple; yellow birch reached its maximum abundance in intermediate landscape positions. On the dune sites, pine was most abundant in drier landscape positions, with white spruce increasing in abundance with increasing soil moisture and N content. The differences in measured soil properties and predicted late-successional composition indicate that ecological land units incorporate some of the key variables that govern forest composition and structure. They further show the value of ecological classification and modeling for developing forest management strategies that incorporate the spatial and temporal dynamics of forest ecosystems.

Ecological aspects in sustainable development model

International Nuclear Information System (INIS)

Kurlapov, L.I.

1996-01-01

Environment problems are caused by intensive use of natural resources due to scientific progress in combination with the present structure of unlimited consumption. To prevent the impending ecological disaster a model of sustainable development has been worked out. It is aimed at satisfying the ever-growing requirements of the modern man without damaging the environment. Scientifically grounded use of nature mat contribute to solution of the problem. The acceptable use of nature should take account of the land ecosystem resources which is ensured by reliable model including flow balance in particular. Irreversible flows generate entropy which could be the universal measure of technic genetics impact. Entropic condition of the acceptable (sustainable) development are started: techno-genic entropy production must be less than natural entropy production. Particular sciences should be re-oriented towards environmental problems. Environmental monitoring strategy should provide for determination of macro properties as well as flows. (author)

On the specification of structural equation models for ecological systems

NARCIS (Netherlands)

Grace, James B.; Anderson, T. Michael; Olff, Han; Scheiner, Samuel M.

The use of structural equation modeling (SEM) is often motivated by its utility for investigating complex networks of relationships, but also because of its promise as a means of representing theoretical Concepts using latent variables. In this paper, we discuss characteristics of ecological theory

Ecology, distribution, and predictive occurrence modeling of Palmers chipmunk (Tamias palmeri): a high-elevation small mammal endemic to the Spring Mountains in southern Nevada, USA

Science.gov (United States)

Lowrey, Chris E.; Longshore, Kathleen M.; Riddle, Brett R.; Mantooth, Stacy

2016-01-01

Although montane sky islands surrounded by desert scrub and shrub steppe comprise a large part of the biological diversity of the Basin and Range Province of southwestern North America, comprehensive ecological and population demographic studies for high-elevation small mammals within these areas are rare. Here, we examine the ecology and population parameters of the Palmer’s chipmunk (Tamias palmeri) in the Spring Mountains of southern Nevada, and present a predictive GIS-based distribution and probability of occurrence model at both home range and geographic spatial scales. Logistic regression analyses and Akaike Information Criterion model selection found variables of forest type, slope, and distance to water sources as predictive of chipmunk occurrence at the geographic scale. At the home range scale, increasing population density, decreasing overstory canopy cover, and decreasing understory canopy cover contributed to increased survival rates.

Scaling up watershed model parameters--Flow and load simulations of the Edisto River Basin

Science.gov (United States)

Feaster, Toby D.; Benedict, Stephen T.; Clark, Jimmy M.; Bradley, Paul M.; Conrads, Paul

2014-01-01

The Edisto River is the longest and largest river system completely contained in South Carolina and is one of the longest free flowing blackwater rivers in the United States. The Edisto River basin also has fish-tissue mercury concentrations that are some of the highest recorded in the United States. As part of an effort by the U.S. Geological Survey to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River basin, analyses and simulations of the hydrology of the Edisto River basin were made with the topography-based hydrological model (TOPMODEL). The potential for scaling up a previous application of TOPMODEL for the McTier Creek watershed, which is a small headwater catchment to the Edisto River basin, was assessed. Scaling up was done in a step-wise process beginning with applying the calibration parameters, meteorological data, and topographic wetness index data from the McTier Creek TOPMODEL to the Edisto River TOPMODEL. Additional changes were made with subsequent simulations culminating in the best simulation, which included meteorological and topographic wetness index data from the Edisto River basin and updated calibration parameters for some of the TOPMODEL calibration parameters. Comparison of goodness-of-fit statistics between measured and simulated daily mean streamflow for the two models showed that with calibration, the Edisto River TOPMODEL produced slightly better results than the McTier Creek model, despite the significant difference in the drainage-area size at the outlet locations for the two models (30.7 and 2,725 square miles, respectively). Along with the TOPMODEL hydrologic simulations, a visualization tool (the Edisto River Data Viewer) was developed to help assess trends and influencing variables in the stream ecosystem. Incorporated into the visualization tool were the water-quality load models TOPLOAD, TOPLOAD-H, and LOADEST

Applying ecological models to communities of genetic elements: the case of neutral theory.

Science.gov (United States)

Linquist, Stefan; Cottenie, Karl; Elliott, Tyler A; Saylor, Brent; Kremer, Stefan C; Gregory, T Ryan

2015-07-01

A promising recent development in molecular biology involves viewing the genome as a mini-ecosystem, where genetic elements are compared to organisms and the surrounding cellular and genomic structures are regarded as the local environment. Here, we critically evaluate the prospects of ecological neutral theory (ENT), a popular model in ecology, as it applies at the genomic level. This assessment requires an overview of the controversy surrounding neutral models in community ecology. In particular, we discuss the limitations of using ENT both as an explanation of community dynamics and as a null hypothesis. We then analyse a case study in which ENT has been applied to genomic data. Our central finding is that genetic elements do not conform to the requirements of ENT once its assumptions and limitations are made explicit. We further compare this genome-level application of ENT to two other, more familiar approaches in genomics that rely on neutral mechanisms: Kimura's molecular neutral theory and Lynch's mutational-hazard model. Interestingly, this comparison reveals that there are two distinct concepts of neutrality associated with these models, which we dub 'fitness neutrality' and 'competitive neutrality'. This distinction helps to clarify the various roles for neutral models in genomics, for example in explaining the evolution of genome size. © 2015 John Wiley & Sons Ltd.

Application of lumped-parameter models

DEFF Research Database (Denmark)

Ibsen, Lars Bo; Liingaard, Morten

This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...

A DPSIR model for ecological security assessment through indicator screening: a case study at Dianchi Lake in China.

Directory of Open Access Journals (Sweden)

Zhen Wang

Full Text Available Given the important role of lake ecosystems in social and economic development, and the current severe environmental degradation in China, a systematic diagnosis of the ecological security of lakes is essential for sustainable development. A Driving-force, Pressure, Status, Impact, and Risk (DPSIR model, combined with data screening for lake ecological security assessment was developed to overcome the disadvantages of data selection in existing assessment methods. Correlation and principal component analysis were used to select independent and representative data. The DPSIR model was then applied to evaluate the ecological security of Dianchi Lake in China during 1988-2007 using an ecological security index. The results revealed a V-shaped trend. The application of the DPSIR model with data screening provided useful information regarding the status of the lake's ecosystem, while ensuring information efficiency and eliminating multicollinearity. The modeling approach described here is practical and operationally efficient, and provides an attractive alternative approach to assess the ecological security of lakes.

A simulation of water pollution model parameter estimation

Science.gov (United States)

Kibler, J. F.

1976-01-01

A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.

Equation-free modeling unravels the behavior of complex ecological systems

Science.gov (United States)

DeAngelis, Donald L.; Yurek, Simeon

2015-01-01

Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.

Estimating population parameters of longsnout seahorses, Hippocampus reidi (Teleostei: Syngnathidae through mark-recapture

Directory of Open Access Journals (Sweden)

Alexandre C. Siqueira

2017-12-01

Full Text Available ABSTRACT Estimating population parameters is essential for understanding the ecology of species, which ultimately helps to assess their conservation status. The seahorse Hippocampus reidi is directly exposed to anthropogenic threats along the Brazilian coast, but the species still figures as Data Deficient (DD at IUCN’s Red List. To provide better information on the ecology of this species, we studied how population parameters vary over time in a natural subtropical environment. By combing mark-recapture models for open and closed populations, we estimated abundance, survival rate, emigration probability, and capture probability. We marked 111 individuals, which showed a 1:1 sex ratio, and an average size of 10.5 cm. The population showed high survival rate, low temporary emigration probability and variable capture probability and abundance. Our models considering relevant biological criteria illuminate the relatively poorly known population ecology and life history of seahorses. It is our hope that this study inspires the use of mark-recapture methods in other populations of H. reidi in a collective effort to properly assess their conservation status.

Identification of ecosystem parameters by SDE-modelling

DEFF Research Database (Denmark)

Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation experiments in order to analyse how system noise propagates through the ordinary differential equation formulation of ecosystem...... models. Estimation of parameters in SDEs is, however, possible by combining Kalman filter techniques and likelihood estimation. By modelling parameters as random walks it is possible to identify linear as well as non-linear interactions between ecosystem components. By formulating a simple linear SDE...

A Framework for Linking Population Model Development with Ecological Risk Assessment Objectives.

Science.gov (United States)

The value of models that link organism‐level impacts to the responses of a population in ecological risk assessments (ERAs) has been demonstrated extensively over the past few decades. There is little debate about the utility of these models to translate multiple organism&#...

Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions

Directory of Open Access Journals (Sweden)

Aloah J Pope

2015-08-01

Full Text Available Interdependencies of ecologic, hydrologic, and social systems challenge traditional approaches to natural resource management in semi-arid regions. As a complex social-ecological system, water demands in the Sonoran Desert from agricultural and urban users often conflicts with water needs for its ecologically-significant riparian corridors. To explore this system, we developed an agent-based model to simulate complex feedbacks between human decisions and environmental conditions in the Rio Sonora Watershed. Cognitive mapping in conjunction with stakeholder participation produced a Bayesian model of conditional probabilities of local human decision-making processes resulting to changes in water demand. Probabilities created in the Bayesian model were incorporated into the agent-based model, so that each agent had a unique probability to make a positive decision based on its perceived environment at each point in time and space. By using a Bayesian approach, uncertainty in the human decision-making process could be incorporated. The spatially-explicit agent-based model simulated changes in depth-to-groundwater by well pumping based on an agent’s water demand. Changes in depth-to-groundwater feedback to influence agent behavior, as well as determine unique vegetation classes within the riparian corridor. Each vegetation class then provides varying stakeholder-defined quality values of ecosystem services. Using this modeling approach allowed us to examine effects on both the ecological and social system of semi-arid riparian corridors under various scenarios. The insight provided by the model contributes to understanding how specific interventions may alter the complex social-ecological system in the future.

Review of the ecological parameters of radionuclide turnover in vertebrate food chains

International Nuclear Information System (INIS)

Kitchings, T.; DiGregorio, D.; Van Voris, P.

1975-01-01

Ecological studies of radionuclides in the environment have a long tradition in developing the capability to identify and predict movement and concentration of nuclides in agronomic food chains leading to man. Food chain pathways and transfer coefficients for the non-agronomic portions of natural and managed ecosystems characteristic of affected habitats adjacent to nuclear facilities have not been adequately characterized to establish reliable dispersion models for radionuclide releases. This information is necessary in order to assess the impact that such installations will have on the biota of natural ecosystems. Since food chains are the major processes transferring elements from one trophic level to another in terrestrial ecosystems, information is needed on the food-chain transfer pathways, bioconcentration by each trophic component, and turnover rates by receptor organisms. These data are prerequisite inputs for food-chain transport models and can be correlated with species characteristics (e.g., body weight and feeding habitats), to provide indices for predictive dispersion calculations. Application of these models for radionuclide transfer can aid in the assessment of radioactive releases from nuclear reactor facilities to terrestrial non-agronomic food chains. (U.S.)

An online database for informing ecological network models: http://kelpforest.ucsc.edu.

Science.gov (United States)

Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H; Tinker, Martin T; Black, August; Caselle, Jennifer E; Hoban, Michael; Malone, Dan; Iles, Alison

2014-01-01

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).

Spatio-temporal modeling of nonlinear distributed parameter systems

CERN Document Server

Li, Han-Xiong

2011-01-01

The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s

Models for estimating photosynthesis parameters from in situ production profiles

Science.gov (United States)

Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana

2017-12-01

The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of

System dynamic modelling to assess economic viability and risk trade-offs for ecological restoration in South Africa.

Science.gov (United States)

Crookes, D J; Blignaut, J N; de Wit, M P; Esler, K J; Le Maitre, D C; Milton, S J; Mitchell, S A; Cloete, J; de Abreu, P; Fourie nee Vlok, H; Gull, K; Marx, D; Mugido, W; Ndhlovu, T; Nowell, M; Pauw, M; Rebelo, A

2013-05-15

Can markets assist by providing support for ecological restoration, and if so, under what conditions? The first step in addressing this question is to develop a consistent methodology for economic evaluation of ecological restoration projects. A risk analysis process was followed in which a system dynamics model was constructed for eight diverse case study sites where ecological restoration is currently being pursued. Restoration costs vary across each of these sites, as do the benefits associated with restored ecosystem functioning. The system dynamics model simulates the ecological, hydrological and economic benefits of ecological restoration and informs a portfolio mapping exercise where payoffs are matched against the likelihood of success of a project, as well as a number of other factors (such as project costs and risk measures). This is the first known application that couples ecological restoration with system dynamics and portfolio mapping. The results suggest an approach that is able to move beyond traditional indicators of project success, since the effect of discounting is virtually eliminated. We conclude that systems dynamic modelling with portfolio mapping can guide decisions on when markets for restoration activities may be feasible. Copyright © 2013 Elsevier Ltd. All rights reserved.

A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive

Energy Technology Data Exchange (ETDEWEB)

Hughes, Samantha Jane, E-mail: shughes@utad.pt [Fluvial Ecology Laboratory, CITAB – Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real (Portugal); Cabral, João Alexandre, E-mail: jcabral@utad.pt [Laboratory of Applied Ecology, CITAB – Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real (Portugal); Bastos, Rita, E-mail: ritabastos@utad.pt [Laboratory of Applied Ecology, CITAB – Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real (Portugal); Cortes, Rui, E-mail: rcortes@utad.pt [Fluvial Ecology Laboratory, CITAB – Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real (Portugal); Vicente, Joana, E-mail: jsvicente@fc.up.pt [Centro de Investigacão em Biodiversidade e Recursos Genéticos (CIBIO), Faculdade de Ciências, Universidade do Porto, Porto (Portugal); Eitelberg, David, E-mail: d.a.eitelberg@vu.nl [Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam (Netherlands); Yu, Huirong, E-mail: h.yu@vu.nl [Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam (Netherlands); College of Resources and Environmental Sciences, China Agricultural University, 2 Yuanmingyuan W. Road, Haidian District, Beijing 100193 (China); and others

2016-09-15

This method development paper outlines an integrative stochastic dynamic methodology (StDM) framework to anticipate land use (LU) change effects on the ecological status of monitored and non-monitored lotic surface waters under the Water Framework Directive (WFD). Tested in the Alto Minho River Basin District in North West Portugal, the model is an innovative step towards developing a decision-making and planning tool to assess the influence impacts such as LU change and climate change on these complex systems. Comprising a series of sequential steps, a Generalized Linear Model based, competing model Multi Model Inference (MMI) approach was used for parameter estimation to identify principal land use types (distal factors) driving change in biological and physicochemical support elements (proximal factors) in monitored water bodies. The framework integrated MMI constants and coefficients of selected LU categories in the StDM simulations and spatial projections to simulate the ecological status of monitored and non-monitored lotic waterbodies in the test area under 2 scenarios of (1) LU intensification and (2) LU extensification. A total of 100 simulations were run for a 50 year period for each scenario. Spatially dynamic projections of WFD metrics were obtained, taking into account the occurrence of stochastic wildfire events which typically occur in the study region and are exacerbated by LU change. A marked projected decline to “Moderate” ecological status for most waterbodies was detected under intensification but little change under extensification; only a few waterbodies fell to “moderate” status. The latter scenario describes the actual regional socio-economic situation of agricultural abandonment due to rural poverty, partly explaining the projected lack of change in ecological status. Based on the WFD “one out all out” criterion, projected downward shifts in ecological status were due to physicochemical support elements, namely increased

A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive

International Nuclear Information System (INIS)

Hughes, Samantha Jane; Cabral, João Alexandre; Bastos, Rita; Cortes, Rui; Vicente, Joana; Eitelberg, David; Yu, Huirong

2016-01-01

This method development paper outlines an integrative stochastic dynamic methodology (StDM) framework to anticipate land use (LU) change effects on the ecological status of monitored and non-monitored lotic surface waters under the Water Framework Directive (WFD). Tested in the Alto Minho River Basin District in North West Portugal, the model is an innovative step towards developing a decision-making and planning tool to assess the influence impacts such as LU change and climate change on these complex systems. Comprising a series of sequential steps, a Generalized Linear Model based, competing model Multi Model Inference (MMI) approach was used for parameter estimation to identify principal land use types (distal factors) driving change in biological and physicochemical support elements (proximal factors) in monitored water bodies. The framework integrated MMI constants and coefficients of selected LU categories in the StDM simulations and spatial projections to simulate the ecological status of monitored and non-monitored lotic waterbodies in the test area under 2 scenarios of (1) LU intensification and (2) LU extensification. A total of 100 simulations were run for a 50 year period for each scenario. Spatially dynamic projections of WFD metrics were obtained, taking into account the occurrence of stochastic wildfire events which typically occur in the study region and are exacerbated by LU change. A marked projected decline to “Moderate” ecological status for most waterbodies was detected under intensification but little change under extensification; only a few waterbodies fell to “moderate” status. The latter scenario describes the actual regional socio-economic situation of agricultural abandonment due to rural poverty, partly explaining the projected lack of change in ecological status. Based on the WFD “one out all out” criterion, projected downward shifts in ecological status were due to physicochemical support elements, namely increased

GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

2015-01-01

Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and

Quantitative plant ecology

DEFF Research Database (Denmark)

Damgaard, Christian

2014-01-01

This e-book is written in the Wolfram' CDF format (download free CDF player from Wolfram.com) The objective of this e-book is to introduce the population ecological concepts for measuring and predicting the ecological success of plant species. This will be done by focusing on the measurement...... and statistical modelling of plant species abundance and the relevant ecological processes that control species abundance. The focus on statistical modelling and likelihood function based methods also means that more algorithm based methods, e.g. ordination techniques and boosted regression tress...

Identification of parameters of discrete-continuous models

International Nuclear Information System (INIS)

Cekus, Dawid; Warys, Pawel

2015-01-01

In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible

Identification of parameters of discrete-continuous models

Energy Technology Data Exchange (ETDEWEB)

Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)

2015-03-10

In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.

Identifying the connective strength between model parameters and performance criteria

Directory of Open Access Journals (Sweden)

B. Guse

2017-11-01

Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria

Agricultural and Environmental Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-01-01

This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN

Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

Science.gov (United States)

Wentworth, Mami Tonoe

Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

Energy Technology Data Exchange (ETDEWEB)

Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilcox, Ian Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandoval, Andrew J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reza, Shahed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-12-01

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.

Social Interface Model: Theorizing Ecological Post-Delivery Processes for Intervention Effects.

Science.gov (United States)

Pettigrew, Jonathan; Segrott, Jeremy; Ray, Colter D; Littlecott, Hannah

2018-01-03

Successful prevention programs depend on a complex interplay among aspects of the intervention, the participant, the specific intervention setting, and the broader set of contexts with which a participant interacts. There is a need to theorize what happens as participants bring intervention ideas and behaviors into other life-contexts, and theory has not yet specified how social interactions about interventions may influence outcomes. To address this gap, we use an ecological perspective to develop the social interface model. This paper presents the key components of the model and its potential to aid the design and implementation of prevention interventions. The model is predicated on the idea that intervention message effectiveness depends not only on message aspects but also on the participants' adoption and adaptation of the message vis-à-vis their social ecology. The model depicts processes by which intervention messages are received and enacted by participants through social processes occurring within and between relevant microsystems. Mesosystem interfaces (negligible interface, transference, co-dependence, and interdependence) can facilitate or detract from intervention effects. The social interface model advances prevention science by theorizing that practitioners can create better quality interventions by planning for what occurs after interventions are delivered.

Developing ecological site and state-and-transition models for grazed riparian pastures at Tejon Ranch, California

Science.gov (United States)

Felix P. Ratcliff; James Bartolome; Michele Hammond; Sheri Spiegal; Michael White

2015-01-01

Ecological site descriptions and associated state-and-transition models are useful tools for understanding the variable effects of management and environment on range resources. Models for woody riparian sites have yet to be fully developed. At Tejon Ranch, in the southern San Joaquin Valley of California, we are using ecological site theory to investigate the role of...

Ecological risk estimation

International Nuclear Information System (INIS)

Bartell, S.M.; Gardner, R.H.; O'Neill, R.V.

1992-01-01

Ecological risk assessment, the process that evaluates the likelihood that adverse ecological effects may occur or are occurring as a result of exposure to one or more stressors, is being developed by the US EPA as a tool for decision making. This book presents one approach to risk assessment-that of applying laboratory toxicity data within an ecosystem model to predict the potential ecological consequences of toxic chemicals. Both Standard Water Column Model (SWACOM), using zooplankton and fish, and Monte Carlo simulations are discussed in detail, along with quantitative explanations for many responses. Simplifying assumptions are explicitly presented. The final chapter discusses strengths, weaknesses, and future directions of the approach. The book is appropriate for anyone who does or uses ecological risk assessment methodologies

Brownian motion model with stochastic parameters for asset prices

Science.gov (United States)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.

Study on Parameters Modeling of Wind Turbines Using SCADA Data

Directory of Open Access Journals (Sweden)

Yonglong YAN

2014-08-01

Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.

Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors

Science.gov (United States)

Part of the ecological risk assessment process involves examining the potential for environmental stressors and ecological receptors to co-occur across a landscape. In this study, we introduce a Bayesian joint modeling framework for use in evaluating and mapping the co-occurrence...

From patterns to causal understanding: Structural equation modeling (SEM) in soil ecology

Science.gov (United States)

Eisenhauer, Nico; Powell, Jeff R; Grace, James B.; Bowker, Matthew A.

2015-01-01

In this perspectives paper we highlight a heretofore underused statistical method in soil ecological research, structural equation modeling (SEM). SEM is commonly used in the general ecological literature to develop causal understanding from observational data, but has been more slowly adopted by soil ecologists. We provide some basic information on the many advantages and possibilities associated with using SEM and provide some examples of how SEM can be used by soil ecologists to shift focus from describing patterns to developing causal understanding and inspiring new types of experimental tests. SEM is a promising tool to aid the growth of soil ecology as a discipline, particularly by supporting research that is increasingly hypothesis-driven and interdisciplinary, thus shining light into the black box of interactions belowground.

Seven-parameter statistical model for BRDF in the UV band.

Science.gov (United States)

Bai, Lu; Wu, Zhensen; Zou, Xiren; Cao, Yunhua

2012-05-21

A new semi-empirical seven-parameter BRDF model is developed in the UV band using experimentally measured data. The model is based on the five-parameter model of Wu and the fourteen-parameter model of Renhorn and Boreman. Surface scatter, bulk scatter and retro-reflection scatter are considered. An optimizing modeling method, the artificial immune network genetic algorithm, is used to fit the BRDF measurement data over a wide range of incident angles. The calculation time and accuracy of the five- and seven-parameter models are compared. After fixing the seven parameters, the model can well describe scattering data in the UV band.

Lumped-parameter Model of a Bucket Foundation

DEFF Research Database (Denmark)

Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten

2009-01-01

efficient model that can be applied in aero-elastic codes for fast evaluation of the dynamic structural response of wind turbines. The target solutions, utilised for calibration of the lumped-parameter models, are obtained by a coupled finite-element/boundaryelement scheme in the frequency domain......, and the quality of the models are tested in the time and frequency domains. It is found that precise results are achieved by lumped-parameter models with two to four internal degrees of freedom per displacement or rotation of the foundation. Further, coupling between the horizontal sliding and rocking cannot...

Source term modelling parameters for Project-90

International Nuclear Information System (INIS)

Shaw, W.; Smith, G.; Worgan, K.; Hodgkinson, D.; Andersson, K.

1992-04-01

This document summarises the input parameters for the source term modelling within Project-90. In the first place, the parameters relate to the CALIBRE near-field code which was developed for the Swedish Nuclear Power Inspectorate's (SKI) Project-90 reference repository safety assessment exercise. An attempt has been made to give best estimate values and, where appropriate, a range which is related to variations around base cases. It should be noted that the data sets contain amendments to those considered by KBS-3. In particular, a completely new set of inventory data has been incorporated. The information given here does not constitute a complete set of parameter values for all parts of the CALIBRE code. Rather, it gives the key parameter values which are used in the constituent models within CALIBRE and the associated studies. For example, the inventory data acts as an input to the calculation of the oxidant production rates, which influence the generation of a redox front. The same data is also an initial value data set for the radionuclide migration component of CALIBRE. Similarly, the geometrical parameters of the near-field are common to both sub-models. The principal common parameters are gathered here for ease of reference and avoidance of unnecessary duplication and transcription errors. (au)

Investigations of some elements distribution in dental tissues by INAA as a function of ecological and some other parameters

International Nuclear Information System (INIS)

Draskovic, R.J.; Jacimovic, Lj.; Stojicevic, M.; Pajic, P.; Filipovic, V.

1982-01-01

Distribution of some elements (Hg, Zn, Sb, Co and Sc) in dental tissues (enamel, dentine, pulp) has been investiaated by instrumental neutron activation analysis (INAA). Teeth samples were taken from patients living in different regions (mine and mineralized areas, plain), taking into account the following parameters: ecological conditions, age of patients, stomatological operations and use of local cosmetic preparations containig mercury. Samples of vegetation (beech, moss, pine) from two locations belonging to regions of mineralized areas also were analyzed. Results of our investigations are presented and discussed. (author)

Agricultural and Environmental Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-06-20

This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.

Coupled economic-ecological models for ecosystem-based fishery management: Exploration of trade-offs between model complexity and management needs

DEFF Research Database (Denmark)

Thunberg, Eric; Holland, Dan; Nielsen, J. Rasmus

2012-01-01

Ecosystem based fishery management has moved beyond rhetorical statements calling for a more holistic approach to resource management, to implementing decisions on resource use that are compatible with goals of maintaining ecosystem health and resilience. Coupled economic-ecological models...... are a primary tool for informing these decisions. Recognizing the importance of these models, the International Council for the Exploration of the Seas (ICES) formed a Study Group on Integration of Economics, Stock Assessment and Fisheries Management (SGIMM) to explore alternative modelling approaches...... and ecological systems are inherently complex, models are abstractions of these systems incorporating varying levels of complexity depending on available data and the management issues to be addressed. The objective of this special session was to assess the pros and cons of increasing model complexity...

Automated experimentation in ecological networks.

Science.gov (United States)

Lurgi, Miguel; Robertson, David

2011-05-09

In ecological networks, natural communities are studied from a complex systems perspective by representing interactions among species within them in the form of a graph, which is in turn analysed using mathematical tools. Topological features encountered in complex networks have been proved to provide the systems they represent with interesting attributes such as robustness and stability, which in ecological systems translates into the ability of communities to resist perturbations of different kinds. A focus of research in community ecology is on understanding the mechanisms by which these complex networks of interactions among species in a community arise. We employ an agent-based approach to model ecological processes operating at the species' interaction level for the study of the emergence of organisation in ecological networks. We have designed protocols of interaction among agents in a multi-agent system based on ecological processes occurring at the interaction level between species in plant-animal mutualistic communities. Interaction models for agents coordination thus engineered facilitate the emergence of network features such as those found in ecological networks of interacting species, in our artificial societies of agents. Agent based models developed in this way facilitate the automation of the design an execution of simulation experiments that allow for the exploration of diverse behavioural mechanisms believed to be responsible for community organisation in ecological communities. This automated way of conducting experiments empowers the study of ecological networks by exploiting the expressive power of interaction models specification in agent systems.

The mobilisation model and parameter sensitivity

International Nuclear Information System (INIS)

Blok, B.M.

1993-12-01

In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)

Quantifying the dilution effect for models in ecological epidemiology.

Science.gov (United States)

Roberts, M G; Heesterbeek, J A P

2018-03-01

The dilution effect , where an increase in biodiversity results in a reduction in the prevalence of an infectious disease, has been the subject of speculation and controversy. Conversely, an amplification effect occurs when increased biodiversity is related to an increase in prevalence. We explore the conditions under which these effects arise, using multi species compartmental models that integrate ecological and epidemiological interactions. We introduce three potential metrics for quantifying dilution and amplification, one based on infection prevalence in a focal host species, one based on the size of the infected subpopulation of that species and one based on the basic reproduction number. We introduce our approach in the simplest epidemiological setting with two species, and show that the existence and strength of a dilution effect is influenced strongly by the choices made to describe the system and the metric used to gauge the effect. We show that our method can be generalized to any number of species and to more complicated ecological and epidemiological dynamics. Our method allows a rigorous analysis of ecological systems where dilution effects have been postulated, and contributes to future progress in understanding the phenomenon of dilution in the context of infectious disease dynamics and infection risk. © 2018 The Author(s).

System for ecological monitoring and assessment for NPP site environment

International Nuclear Information System (INIS)

Vorob'ev, E.I.; Olejnikov, N.F.; Reznichenko, V.Yu.

1987-01-01

On the basis of the Leningrad NPP named after V.I. Lenin the development of a system for ecological monitoring and assessment (EMA) of the environment state and health of personnel and population has started in the EMA program framework. The program of ecological monitoring and assessment coordinates the works on the study of NPP effect on the nature and people, effect of separate factors and their combination, methods and models for the description of the effects, forecasting and evaluation, selection of the optimal protection strategies. Scientific foundations, structure and content of the EMA program are given to coordinate the works carried out according to the program with other works carried out in the country in this direction. The paper deals with the composition of monitoring parameters of the standard system of ecological monitoring of the environment for NPP

Ecological optimization and performance study of irreversible Stirling and Ericsson heat engines

International Nuclear Information System (INIS)

Tyagi, S K; Kaushik, S C; Salhotra, R

2002-01-01

The concept of finite time thermodynamics is used to determine the ecological function of irreversible Stirling and Ericsson heat engine cycles. The ecological function is defined as the power output minus power loss (irreversibility), which is the ambient temperature times, the entropy generation rate. The ecological function is maximized with respect to cycle temperature ratio and the expressions for the corresponding power output and thermal efficiency are derived at the optimal operating conditions. The effect of different operating parameters, the effectiveness on the hot, cold and the regenerative side heat exchangers, the cycle temperature ratio, heat capacitance ratio and the internal irreversibility parameter on the maximum ecological function are studied. It is found that the effect of regenerator effectiveness is more than the hot and cold side heat exchangers and the effect of the effectiveness on cold side heat exchanger is more than the effectiveness on the hot side heat exchanger on the maximum ecological function. It is also found that the effect of internal irreversibility parameter is more than the other parameters not only on the maximum ecological function but also on the corresponding power output and the thermal efficiency

Ecological optimization and performance study of irreversible Stirling and Ericsson heat engines

Science.gov (United States)

Tyagi, S. K.; Kaushik, S. C.; Salhotra, R.

2002-10-01

The concept of finite time thermodynamics is used to determine the ecological function of irreversible Stirling and Ericsson heat engine cycles. The ecological function is defined as the power output minus power loss (irreversibility), which is the ambient temperature times, the entropy generation rate. The ecological function is maximized with respect to cycle temperature ratio and the expressions for the corresponding power output and thermal efficiency are derived at the optimal operating conditions. The effect of different operating parameters, the effectiveness on the hot, cold and the regenerative side heat exchangers, the cycle temperature ratio, heat capacitance ratio and the internal irreversibility parameter on the maximum ecological function are studied. It is found that the effect of regenerator effectiveness is more than the hot and cold side heat exchangers and the effect of the effectiveness on cold side heat exchanger is more than the effectiveness on the hot side heat exchanger on the maximum ecological function. It is also found that the effect of internal irreversibility parameter is more than the other parameters not only on the maximum ecological function but also on the corresponding power output and the thermal efficiency.

Bayesian estimation of parameters in a regional hydrological model

Directory of Open Access Journals (Sweden)

K. Engeland

2002-01-01

Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests.

Energy Technology Data Exchange (ETDEWEB)

Parresol, Bernard, R.; Scott, Joe, H.; Andreu, Anne; Prichard, Susan; Kurth, Laurie

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or thousands of measured surface fuelbeds representing the fine scale variation in fire behavior on the landscape is constrained in terms of creating compatible custom fire behavior fuel models. In this study, we demonstrate an objective method for taking ecologically complex fuelbeds from inventory observations and converting those into a set of custom fuel models that can be mapped to the original landscape. We use an original set of 629 fuel inventory plots measured on an 80,000 ha contiguous landscape in the upper Atlantic Coastal Plain of the southeastern United States. From models linking stand conditions to component fuel loads, we impute fuelbeds for over 6000 stands. These imputed fuelbeds were then converted to fire behavior parameters under extreme fuel moisture and wind conditions (97th percentile) using the fuel characteristic classification system (FCCS) to estimate surface fire rate of spread, surface fire flame length, shrub layer reaction intensity (heat load), non-woody layer reaction intensity, woody layer reaction intensity, and litter-lichen-moss layer reaction intensity. We performed hierarchical cluster analysis of the stands based on the values of the fire behavior parameters. The resulting 7 clusters were the basis for the development of 7 custom fire behavior fuel models from the cluster centroids that were calibrated against the FCCS point data for wind and fuel moisture. The latter process resulted in calibration against flame length as it was difficult to obtain a simultaneous calibration against both rate of spread and flame length. The clusters based on FCCS fire behavior

Perspectives on why digital ecologies matter: combining population genetics and ecologically informed agent-based models with GIS for managing dipteran livestock pests.

Science.gov (United States)

Peck, Steven L

2014-10-01

It is becoming clear that handling the inherent complexity found in ecological systems is an essential task for finding ways to control insect pests of tropical livestock such as tsetse flies, and old and new world screwworms. In particular, challenging multivalent management programs, such as Area Wide Integrated Pest Management (AW-IPM), face daunting problems of complexity at multiple spatial scales, ranging from landscape level processes to those of smaller scales such as the parasite loads of individual animals. Daunting temporal challenges also await resolution, such as matching management time frames to those found on ecological and even evolutionary temporal scales. How does one deal with representing processes with models that involve multiple spatial and temporal scales? Agent-based models (ABM), combined with geographic information systems (GIS), may allow for understanding, predicting and managing pest control efforts in livestock pests. This paper argues that by incorporating digital ecologies in our management efforts clearer and more informed decisions can be made. I also point out the power of these models in making better predictions in order to anticipate the range of outcomes possible or likely. Copyright © 2014 International Atomic Energy Agency 2014. Published by Elsevier B.V. All rights reserved.

Ecological and general systems an introduction to systems ecology

CERN Document Server

Odum, Howard T.

1994-01-01

Using an energy systems language that combines energetics, kinetics, information, cybernetics, and simulation, Ecological and General Systems compares models of many fields of science, helping to derive general systems principles. First published as Systems Ecology in 1983, Ecological and General Systems proposes principles of self-organization and the designs that prevail by maximizing power and efficiency. Comparisons to fifty other systems languages are provided. Innovative presentations are given on earth homeostasis (Gaia); the inadequacy of presenting equations without network relationships and energy constraints; the alternative interpretation of high entropy complexity as adaptive structure; basic equations of ecological economics; and the energy basis of scientific hierarchy.

Models and parameters for environmental radiological assessments

International Nuclear Information System (INIS)

Miller, C.W.

1983-01-01

This article reviews the forthcoming book Models and Parameters for Environmental Radiological Assessments, which presents a unified compilation of models and parameters for assessing the impact on man of radioactive discharges, both routine and accidental, into the environment. Models presented in this book include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Summaries are presented for each of the transport and dosimetry areas previously for each of the transport and dosimetry areas previously mentioned, and details are available in the literature cited. A chapter of example problems illustrates many of the methodologies presented throughout the text. Models and parameters presented are based on the results of extensive literature reviews and evaluations performed primarily by the staff of the Health and Safety Research Division of Oak Ridge National Laboratory

Parameter Estimation of Nonlinear Models in Forestry.

OpenAIRE

Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.

1999-01-01

Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...

Learning about physical parameters: the importance of model discrepancy

International Nuclear Information System (INIS)

Brynjarsdóttir, Jenný; O'Hagan, Anthony

2014-01-01

Science-based simulation models are widely used to predict the behavior of complex physical systems. It is also common to use observations of the physical system to solve the inverse problem, that is, to learn about the values of parameters within the model, a process which is often called calibration. The main goal of calibration is usually to improve the predictive performance of the simulator but the values of the parameters in the model may also be of intrinsic scientific interest in their own right. In order to make appropriate use of observations of the physical system it is important to recognize model discrepancy, the difference between reality and the simulator output. We illustrate through a simple example that an analysis that does not account for model discrepancy may lead to biased and over-confident parameter estimates and predictions. The challenge with incorporating model discrepancy in statistical inverse problems is being confounded with calibration parameters, which will only be resolved with meaningful priors. For our simple example, we model the model-discrepancy via a Gaussian process and demonstrate that through accounting for model discrepancy our prediction within the range of data is correct. However, only with realistic priors on the model discrepancy do we uncover the true parameter values. Through theoretical arguments we show that these findings are typical of the general problem of learning about physical parameters and the underlying physical system using science-based mechanistic models. (paper)

Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

2010-01-01

Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

Optimizing incomplete sample designs for item response model parameters

NARCIS (Netherlands)

van der Linden, Willem J.

Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with

Ecological Interventionist Causal Models in Psychosis: Targeting Psychological Mechanisms in Daily Life.

Science.gov (United States)

Reininghaus, Ulrich; Depp, Colin A; Myin-Germeys, Inez

2016-03-01

Integrated models of psychotic disorders have posited a number of putative psychological mechanisms that may contribute to the development of psychotic symptoms, but it is only recently that a modest amount of experience sampling research has provided evidence on their role in daily life, outside the research laboratory. A number of methodological challenges remain in evaluating specificity of potential causal links between a given psychological mechanism and psychosis outcomes in a systematic fashion, capitalizing on longitudinal data to investigate temporal ordering. In this article, we argue for testing ecological interventionist causal models that draw on real world and real-time delivered, ecological momentary interventions for generating evidence on several causal criteria (association, time order, and direction/sole plausibility) under real-world conditions, while maximizing generalizability to social contexts and experiences in heterogeneous populations. Specifically, this approach tests whether ecological momentary interventions can (1) modify a putative mechanism and (2) produce changes in the mechanism that lead to sustainable changes in intended psychosis outcomes in individuals' daily lives. Future research using this approach will provide translational evidence on the active ingredients of mobile health and in-person interventions that promote sustained effectiveness of ecological momentary interventions and, thereby, contribute to ongoing efforts that seek to enhance effectiveness of psychological interventions under real-world conditions. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Wildfire Risk Main Model

Data.gov (United States)

Earth Data Analysis Center, University of New Mexico — The model combines three modeled fire behavior parameters (rate of spread, flame length, crown fire potential) and one modeled ecological health measure (fire regime...

Ecological monitoring in a discrete-time prey-predator model.

Science.gov (United States)

Gámez, M; López, I; Rodríguez, C; Varga, Z; Garay, J

2017-09-21

The paper is aimed at the methodological development of ecological monitoring in discrete-time dynamic models. In earlier papers, in the framework of continuous-time models, we have shown how a systems-theoretical methodology can be applied to the monitoring of the state process of a system of interacting populations, also estimating certain abiotic environmental changes such as pollution, climatic or seasonal changes. In practice, however, there may be good reasons to use discrete-time models. (For instance, there may be discrete cycles in the development of the populations, or observations can be made only at discrete time steps.) Therefore the present paper is devoted to the development of the monitoring methodology in the framework of discrete-time models of population ecology. By monitoring we mean that, observing only certain component(s) of the system, we reconstruct the whole state process. This may be necessary, e.g., when in a complex ecosystem the observation of the densities of certain species is impossible, or too expensive. For the first presentation of the offered methodology, we have chosen a discrete-time version of the classical Lotka-Volterra prey-predator model. This is a minimal but not trivial system where the methodology can still be presented. We also show how this methodology can be applied to estimate the effect of an abiotic environmental change, using a component of the population system as an environmental indicator. Although this approach is illustrated in a simplest possible case, it can be easily extended to larger ecosystems with several interacting populations and different types of abiotic environmental effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573])

Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-10

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis

Parameters and error of a theoretical model

International Nuclear Information System (INIS)

Moeller, P.; Nix, J.R.; Swiatecki, W.

1986-09-01

We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs

The spatial optimism model research for the regional land use based on the ecological constraint

Science.gov (United States)

XU, K.; Lu, J.; Chi, Y.

2013-12-01

The study focuses on the Yunnan-Guizhou (i.e. Yunnan province and Guizhou province) Plateau in China. Since the Yunnan-Guizhou region consists of closed basins, the land resources suiting for development are in a shortage, and the ecological problems in the area are quite complicated. In such circumstance, in order to get the applicable basins area and distribution, certain spatial optimism model is needed. In this research, Digital Elevation Model (DEM) and land use data are used to get the boundary rules of the basins distribution. Furthermore, natural risks, ecological risks and human-made ecological risks are integrated to be analyzed. Finally, the spatial overlay analysis method is used to model the developable basins area and distribution for industries and urbanization. The study process can be divided into six steps. First, basins and their distribution need to be recognized. In this way, the DEM data is used to extract the geomorphology characteristics. The plaque regions with gradient under eight degrees are selected. Among these regions, the total area of the plaque with the area above 8 km2 is 54,000 km2, 10% of the total area. These regions are selected to the potential application of industries and urbanization. In the later five steps, analyses are aimed at these regions. Secondly, the natural risks are analyzed. The conditions of the earthquake, debris flow and rainstorm and flood are combined to classify the natural risks. Thirdly, the ecological risks are analyzed containing the ecological sensibility and ecosystem service function importance. According to the regional ecologic features, the sensibility containing the soil erosion, acid rain, stony desertification and survive condition factors is derived and classified according to the medium value to get the ecological sensibility partition. The ecosystem service function importance is classified and divided considering the biology variation protection and water conservation factors. The fourth

The painted turtle, Chrysemys picta: a model system for vertebrate evolution, ecology, and human health.

Science.gov (United States)

Valenzuela, Nicole

2009-07-01

Painted turtles (Chrysemys picta) are representatives of a vertebrate clade whose biology and phylogenetic position hold a key to our understanding of fundamental aspects of vertebrate evolution. These features make them an ideal emerging model system. Extensive ecological and physiological research provide the context in which to place new research advances in evolutionary genetics, genomics, evolutionary developmental biology, and ecological developmental biology which are enabled by current resources, such as a bacterial artificial chromosome (BAC) library of C. picta, and the imminent development of additional ones such as genome sequences and cDNA and expressed sequence tag (EST) libraries. This integrative approach will allow the research community to continue making advances to provide functional and evolutionary explanations for the lability of biological traits found not only among reptiles but vertebrates in general. Moreover, because humans and reptiles share a common ancestor, and given the ease of using nonplacental vertebrates in experimental biology compared with mammalian embryos, painted turtles are also an emerging model system for biomedical research. For example, painted turtles have been studied to understand many biological responses to overwintering and anoxia, as potential sentinels for environmental xenobiotics, and as a model to decipher the ecology and evolution of sexual development and reproduction. Thus, painted turtles are an excellent reptilian model system for studies with human health, environmental, ecological, and evolutionary significance.

Application of multi-parameter chorus and plasmaspheric hiss wave models in radiation belt modeling

Science.gov (United States)

Aryan, H.; Kang, S. B.; Balikhin, M. A.; Fok, M. C. H.; Agapitov, O. V.; Komar, C. M.; Kanekal, S. G.; Nagai, T.; Sibeck, D. G.

2017-12-01

Numerical simulation studies of the Earth's radiation belts are important to understand the acceleration and loss of energetic electrons. The Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model along with many other radiation belt models require inputs for pitch angle, energy, and cross diffusion of electrons, due to chorus and plasmaspheric hiss waves. These parameters are calculated using statistical wave distribution models of chorus and plasmaspheric hiss amplitudes. In this study we incorporate recently developed multi-parameter chorus and plasmaspheric hiss wave models based on geomagnetic index and solar wind parameters. We perform CIMI simulations for two geomagnetic storms and compare the flux enhancement of MeV electrons with data from the Van Allen Probes and Akebono satellites. We show that the relativistic electron fluxes calculated with multi-parameter wave models resembles the observations more accurately than the relativistic electron fluxes calculated with single-parameter wave models. This indicates that wave models based on a combination of geomagnetic index and solar wind parameters are more effective as inputs to radiation belt models.

Modelling hydrodynamic parameters to predict flow assisted corrosion

International Nuclear Information System (INIS)

Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.

1992-01-01

During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model

Transdisciplinary application of the cross-scale resilience model

Science.gov (United States)

Sundstrom, Shana M.; Angeler, David G.; Garmestani, Ahjond S.; Garcia, Jorge H.; Allen, Craig R.

2014-01-01

The cross-scale resilience model was developed in ecology to explain the emergence of resilience from the distribution of ecological functions within and across scales, and as a tool to assess resilience. We propose that the model and the underlying discontinuity hypothesis are relevant to other complex adaptive systems, and can be used to identify and track changes in system parameters related to resilience. We explain the theory behind the cross-scale resilience model, review the cases where it has been applied to non-ecological systems, and discuss some examples of social-ecological, archaeological/ anthropological, and economic systems where a cross-scale resilience analysis could add a quantitative dimension to our current understanding of system dynamics and resilience. We argue that the scaling and diversity parameters suitable for a resilience analysis of ecological systems are appropriate for a broad suite of systems where non-normative quantitative assessments of resilience are desired. Our planet is currently characterized by fast environmental and social change, and the cross-scale resilience model has the potential to quantify resilience across many types of complex adaptive systems.

WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...

African Journals Online (AJOL)

Preferred Customer

Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...

Development of a socio-ecological environmental justice model for watershed-based management

Science.gov (United States)

Sanchez, Georgina M.; Nejadhashemi, A. Pouyan; Zhang, Zhen; Woznicki, Sean A.; Habron, Geoffrey; Marquart-Pyatt, Sandra; Shortridge, Ashton

2014-10-01

The dynamics and relationships between society and nature are complex and difficult to predict. Anthropogenic activities affect the ecological integrity of our natural resources, specifically our streams. Further, it is well-established that the costs of these activities are born unequally by different human communities. This study considered the utility of integrating stream health metrics, based on stream health indicators, with socio-economic measures of communities, to better characterize these effects. This study used a spatial multi-factor model and bivariate mapping to produce a novel assessment for watershed management, identification of vulnerable areas, and allocation of resources. The study area is the Saginaw River watershed located in Michigan. In-stream hydrological and water quality data were used to predict fish and macroinvertebrate measures of stream health. These measures include the Index of Biological Integrity (IBI), Hilsenhoff Biotic Index (HBI), Family IBI, and total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa. Stream health indicators were then compared to spatially coincident socio-economic data, obtained from the United States Census Bureau (2010), including race, income, education, housing, and population size. Statistical analysis including spatial regression and cluster analysis were used to examine the correlation between vulnerable human populations and environmental conditions. Overall, limited correlation was observed between the socio-economic data and ecological measures of stream health, with the highest being a negative correlation of 0.18 between HBI and the social parameter household size. Clustering was observed in the datasets with urban areas representing a second order clustering effect over the watershed. Regions with the worst stream health and most vulnerable social populations were most commonly located nearby or down-stream to highly populated areas and agricultural lands.

Forest Fire Ecology.

Science.gov (United States)

Zucca, Carol; And Others

1995-01-01

Presents a model that integrates high school science with the needs of the local scientific community. Describes how a high school ecology class conducted scientific research in fire ecology that benefited the students and a state park forest ecologist. (MKR)

Sensibility and time heterogeneity of Biome-BGC model parameters%Biome-BGC模型参数的敏感性和时间异质性

Institute of Scientific and Technical Information of China (English)

刘秋雨; 张廷龙; 孙睿; 王博闻; 叶欣欣; 李一哲

2017-01-01

生态过程模型为研究陆表生态系统水、碳、氮等物质的循环提供了一种有效的手段.模型与数据同化结合可建立模拟与观测之间的桥梁,同时提高模型与观测两种方法揭示地表真实状况的有效性.但模型参数的特性,将直接影响到模型模拟及数据同化的精度.传统观念认为,生态过程模型参数在相同植被类型条件下是固定不变的,但近期研究已开始关注其时空异质性.本文以Biome-BGC模型为例,利用美国哈佛森林Environmental Monitoring Site (EMS)通量观测站的相关数据,对哈佛森林地区水、碳通量进行模拟.首先对模型参数进行敏感性分析;然后应用模拟退火算法,构造目标函数,使待优化的敏感参数在合理阈值范围内不断变动反复迭代,获取逐月的最优参数值;通过引入变异系数,对敏感参数的时间异质性进行分析.结果表明:生态过程模型参数最优值并非常量,而会随时间表现出异质性,而且各参数时间异质性大小差异显著.文中对Biome-BGC模型的敏感参数按时间异质性大小划分了相应的等级.研究结果有助于加深对生态过程模型参数特性的认识,为参数的合理取值及动态优化提供思路与依据,有助于进一步提高模型模拟和数据同化的精度与效率.%Ecological process model provides an effective way for studying water,carbon and nitrogen cycles of terrestrial ecosystem.The combination of the model and data assimilation could build a link between observation and simulation,which improves the effectiveness of model and observation methods to reveal the real state of land surface,but the accuracy of simulation and assimilation is directly affected by model parameters.Parameters are constants in traditional opinion;however,some current studies have focused on the time-space heterogeneity of parameters.In this paper,we used Harvard Forest Environmental Monitoring Site (EMS) data to simulate

Assessing the Impact of Model Parameter Uncertainty in Simulating Grass Biomass Using a Hybrid Carbon Allocation Strategy

Science.gov (United States)

Reyes, J. J.; Adam, J. C.; Tague, C.

2016-12-01

Grasslands play an important role in agricultural production as forage for livestock; they also provide a diverse set of ecosystem services including soil carbon (C) storage. The partitioning of C between above and belowground plant compartments (i.e. allocation) is influenced by both plant characteristics and environmental conditions. The objectives of this study are to 1) develop and evaluate a hybrid C allocation strategy suitable for grasslands, and 2) apply this strategy to examine the importance of various parameters related to biogeochemical cycling, photosynthesis, allocation, and soil water drainage on above and belowground biomass. We include allocation as an important process in quantifying the model parameter uncertainty, which identifies the most influential parameters and what processes may require further refinement. For this, we use the Regional Hydro-ecologic Simulation System, a mechanistic model that simulates coupled water and biogeochemical processes. A Latin hypercube sampling scheme was used to develop parameter sets for calibration and evaluation of allocation strategies, as well as parameter uncertainty analysis. We developed the hybrid allocation strategy to integrate both growth-based and resource-limited allocation mechanisms. When evaluating the new strategy simultaneously for above and belowground biomass, it produced a larger number of less biased parameter sets: 16% more compared to resource-limited and 9% more compared to growth-based. This also demonstrates its flexible application across diverse plant types and environmental conditions. We found that higher parameter importance corresponded to sub- or supra-optimal resource availability (i.e. water, nutrients) and temperature ranges (i.e. too hot or cold). For example, photosynthesis-related parameters were more important at sites warmer than the theoretical optimal growth temperature. Therefore, larger values of parameter importance indicate greater relative sensitivity in

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

Science.gov (United States)

Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

2014-05-20

Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

Modelling of intermittent microwave convective drying: parameter sensitivity

Directory of Open Access Journals (Sweden)

Zhang Zhijun

2017-06-01

Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.

An ecological model of the impact of sexual assault on women's mental health.

Science.gov (United States)

Campbell, Rebecca; Dworkin, Emily; Cabral, Giannina

2009-07-01

This review examines the psychological impact of adult sexual assault through an ecological theoretical perspective to understand how factors at multiple levels of the social ecology contribute to post-assault sequelae. Using Bronfenbrenner's (1979, 1986, 1995) ecological theory of human development, we examine how individual-level factors (e.g., sociodemographics, biological/genetic factors), assault characteristics (e.g., victim-offender relationship, injury, alcohol use), microsystem factors (e.g., informal support from family and friends), meso/ exosystem factors (e.g., contact with the legal, medical, and mental health systems, and rape crisis centers), macrosystem factors (e.g., societal rape myth acceptance), and chronosystem factors (e.g., sexual revictimization and history of other victimizations) affect adult sexual assault survivors' mental health outcomes (e.g., post-traumatic stress disorder, depression, suicidality, and substance use). Self-blame is conceptualized as meta-construct that stems from all levels of this ecological model. Implications for curbing and/or preventing the negative mental health effects of sexual assault are discussed.

The possibility of coexistence and co-development in language competition: ecology-society computational model and simulation.

Science.gov (United States)

Yun, Jian; Shang, Song-Chao; Wei, Xiao-Dan; Liu, Shuang; Li, Zhi-Jie

2016-01-01

Language is characterized by both ecological properties and social properties, and competition is the basic form of language evolution. The rise and decline of one language is a result of competition between languages. Moreover, this rise and decline directly influences the diversity of human culture. Mathematics and computer modeling for language competition has been a popular topic in the fields of linguistics, mathematics, computer science, ecology, and other disciplines. Currently, there are several problems in the research on language competition modeling. First, comprehensive mathematical analysis is absent in most studies of language competition models. Next, most language competition models are based on the assumption that one language in the model is stronger than the other. These studies tend to ignore cases where there is a balance of power in the competition. The competition between two well-matched languages is more practical, because it can facilitate the co-development of two languages. A third issue with current studies is that many studies have an evolution result where the weaker language inevitably goes extinct. From the integrated point of view of ecology and sociology, this paper improves the Lotka-Volterra model and basic reaction-diffusion model to propose an "ecology-society" computational model for describing language competition. Furthermore, a strict and comprehensive mathematical analysis was made for the stability of the equilibria. Two languages in competition may be either well-matched or greatly different in strength, which was reflected in the experimental design. The results revealed that language coexistence, and even co-development, are likely to occur during language competition.

Retrospective forecast of ETAS model with daily parameters estimate

Science.gov (United States)

Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang

2016-04-01

We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.

Definition of the generalized criterion of estimation of ecological purity of textile products

International Nuclear Information System (INIS)

Gintibidze, N.; Valishvili, T.

2009-01-01

One of actual problems is the estimation of hygienic and ecological properties of fabrics on the basis of the data on the properties of initial fiber. In the present article, the definition of generalized criterion of the estimation of ecological purity of textile products is discussed. The estimation is based on the International Standard EKO-TEX-100, regulating the contents of inorganic and organic compounds in textile production. The determination of all listed substances is made according to appropriate techniques for each parameter. The quantity of substances is determined and compared with norms. The judgement about ecological purity is made by separate parameters. There is no uniform parameter which could estimate the degree of ecological purity of textile products. For calculating the generalized criterion of estimation of ecological purity of textile products, it is offered to estimate each criterion by the points corresponding to each factor. The textile product is recognized as ecologically pure (environment friendly) if the total estimate is more than 1. (author)

Parameter identification in multinomial processing tree models

NARCIS (Netherlands)

Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.

2010-01-01

Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis

Microbial ecology-based methods to characterize the bacterial communities of non-model insects.

Science.gov (United States)

Prosdocimi, Erica M; Mapelli, Francesca; Gonella, Elena; Borin, Sara; Crotti, Elena

2015-12-01

Among the animals of the Kingdom Animalia, insects are unparalleled for their widespread diffusion, diversity and number of occupied ecological niches. In recent years they have raised researcher interest not only because of their importance as human and agricultural pests, disease vectors and as useful breeding species (e.g. honeybee and silkworm), but also because of their suitability as animal models. It is now fully recognized that microorganisms form symbiotic relationships with insects, influencing their survival, fitness, development, mating habits and the immune system and other aspects of the biology and ecology of the insect host. Thus, any research aimed at deepening the knowledge of any given insect species (perhaps species of applied interest or species emerging as novel pests or vectors) must consider the characterization of the associated microbiome. The present review critically examines the microbiology and molecular ecology techniques that can be applied to the taxonomical and functional analysis of the microbiome of non-model insects. Our goal is to provide an overview of current approaches and methods addressing the ecology and functions of microorganisms and microbiomes associated with insects. Our focus is on operational details, aiming to provide a concise guide to currently available advanced techniques, in an effort to extend insect microbiome research beyond simple descriptions of microbial communities. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving communication and validation of ecological models : a case study on the dispersal of aquatic macroinvertebrates

NARCIS (Netherlands)

Augusiak, Jacqueline A.

2016-01-01

In recent years, ecological effect models have been put forward as tools for supporting environmental decision-making. Often they are the only way to take the relevant spatial and temporal scales and the multitude of processes characteristic to ecological systems into account. Particularly for

Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps.

Science.gov (United States)

Kimball, J. S.; Keyser, A. R.; Running, S. W.; Saatchi, S. S.

2000-06-01

An ecological process model (BIOME-BGC) was used to assess boreal forest regional net primary production (NPP) and response to short-term, year-to-year weather fluctuations based on spatially explicit, land cover and biomass maps derived by radar remote sensing, as well as soil, terrain and daily weather information. Simulations were conducted at a 30-m spatial resolution, over a 1205 km(2) portion of the BOREAS Southern Study Area of central Saskatchewan, Canada, over a 3-year period (1994-1996). Simulations of NPP for the study region were spatially and temporally complex, averaging 2.2 (+/- 0.6), 1.8 (+/- 0.5) and 1.7 (+/- 0.5) Mg C ha(-1) year(-1) for 1994, 1995 and 1996, respectively. Spatial variability of NPP was strongly controlled by the amount of aboveground biomass, particularly photosynthetic leaf area, whereas biophysical differences between broadleaf deciduous and evergreen coniferous vegetation were of secondary importance. Simulations of NPP were strongly sensitive to year-to-year variations in seasonal weather patterns, which influenced the timing of spring thaw and deciduous bud-burst. Reductions in annual NPP of approximately 17 and 22% for 1995 and 1996, respectively, were attributed to 3- and 5-week delays in spring thaw relative to 1994. Boreal forest stands with greater proportions of deciduous vegetation were more sensitive to the timing of spring thaw than evergreen coniferous stands. Similar relationships were found by comparing simulated snow depth records with 10-year records of aboveground NPP measurements obtained from biomass harvest plots within the BOREAS region. These results highlight the importance of sub-grid scale land cover complexity in controlling boreal forest regional productivity, the dynamic response of the biome to short-term interannual climate variations, and the potential implications of climate change and other large-scale disturbances.

Southern marl prairies conceptual ecological model

Science.gov (United States)

Davis, S.M.; Loftus, W.F.; Gaiser, E.E.; Huffman, A.E.

2005-01-01

About 190,000 ha of higher-elevation marl prairies flank either side of Shark River Slough in the southern Everglades. Water levels typically drop below the ground surface each year in this landscape. Consequently, peat soil accretion is inhibited, and substrates consist either of calcitic marl produced by algal periphyton mats or exposed limestone bedrock. The southern marl prairies support complex mosaics of wet prairie, sawgrass sawgrass (Cladium jamaicense), tree islands, and tropical hammock communities and a high diversity of plant species. However, relatively short hydroperiods and annual dry downs provide stressful conditions for aquatic fauna, affecting survival in the dry season when surface water is absent. Here, we present a conceptual ecological model developed for this landscape through scientific concensus, use of empirical data, and modeling. The two major societal drivers affecting the southern marl prairies are water management practices and agricultural and urban development. These drivers lead to five groups of ecosystem stressors: loss of spatial extent and connectivity, shortened hydroperiod and increased drought severity, extended hydroperiod and drying pattern reversals, introduction and spread of non-native trees, and introduction and spread of non-native fishes. Major ecological attributes include periphyton mats, plant species diversity and community mosaic, Cape Sable seaside sparrow (Ammodramus maritimus mirabilis), marsh fishes and associated aquatic fauna prey base, American alligator (Alligator mississippiensis), and wading bird early dry season foraging. Water management and development are hypothesized to have a negative effect on the ecological attributes of the southern marl prairies in the following ways. Periphyton mats have decreased in cover in areas where hydroperiod has been significantly reduced and changed in community composition due to inverse responses to increased nutrient availability. Plant species diversity and

Economic and ecological impacts of bioenergy crop production—a modeling approach applied in Southwestern Germany

Directory of Open Access Journals (Sweden)

Hans-Georg Schwarz-v. Raumer

2017-03-01

Full Text Available This paper considers scenarios of cultivating energy crops in the German Federal State of Baden-Württemberg to identify potentials and limitations of a sustainable bioenergy production. Trade-offs are analyzed among income and production structure in agriculture, bioenergy crop production, greenhouse gas emissions, and the interests of soil, water and species habitat protection. An integrated modelling approach (IMA was implemented coupling ecological and economic models in a model chain. IMA combines the Economic Farm Emission Model (EFEM; key input: parameter sets on farm production activities, the Environmental Policy Integrated Climate model (EPIC; key input: parameter sets on environmental cropping effects and GIS geo-processing models. EFEM is a supply model that maximizes total gross margins on farm level with simultaneous calculation of greenhouse gas emission from agriculture production. Calculations by EPIC result in estimates for soil erosion by water, nitrate leaching, Soil Organic Carbon and greenhouse gas emissions from soil. GIS routines provide land suitability analyses, scenario settings concerning nature conservation and habitat models for target species and help to enable spatial explicit results. The model chain is used to calculate scenarios representing different intensities of energy crop cultivation. To design scenarios which are detailed and in step to practice, comprehensive data research as well as fact and effect analyses were carried out. The scenarios indicate that, not in general but when considering specific farm types, energy crop share extremely increases if not restricted and leads to an increase in income. If so this leads to significant increase in soil erosion by water, nitrate leaching and greenhouse gas emissions. It has to be expected that an extension of nature conservation leads to an intensification of the remaining grassland and of the arable land, which were not part of nature conservation measures

Optimal parameters for the FFA-Beddoes dynamic stall model

Energy Technology Data Exchange (ETDEWEB)

Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)

1999-03-01

Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)

Near Real-time Ecological Forecasting of Peatland Responses to Warming and CO2 Treatment through EcoPAD-SPRUCE

Science.gov (United States)

Huang, Y.; Jiang, J.; Stacy, M.; Ricciuto, D. M.; Hanson, P. J.; Sundi, N.; Luo, Y.

2016-12-01

Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our Ecological Platform for Assimilation of Data (EcoPAD) facilitates the integration of current best knowledge from models, manipulative experimentations, observations and other modern techniques and provides both near real-time and long-term forecasting of ecosystem dynamics. As a case study, the web-based EcoPAD platform synchronizes real- or near real-time field measurements from the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment experiment, assimilates multiple data streams into process based models, enhances timely feedback between modelers and experimenters, and ultimately improves ecosystem forecasting and makes best utilization of current knowledge. In addition to enable users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, and (v) conduct ecological forecasting, EcoPAD-SPRUCE automated the workflow from real-time data acquisition, model simulation to result visualization. EcoPAD-SPRUCE promotes seamless feedback between modelers and experimenters, hand in hand to make better forecasting of future changes. The framework of EcoPAD-SPRUCE (with flexible API, Application Programming Interface) is easily portable and will benefit scientific communities, policy makers as well as the general public.

A 3-level Bayesian mixed effects location scale model with an application to ecological momentary assessment data.

Science.gov (United States)

Lin, Xiaolei; Mermelstein, Robin J; Hedeker, Donald

2018-06-15

Ecological momentary assessment studies usually produce intensively measured longitudinal data with large numbers of observations per unit, and research interest is often centered around understanding the changes in variation of people's thoughts, emotions and behaviors. Hedeker et al developed a 2-level mixed effects location scale model that allows observed covariates as well as unobserved variables to influence both the mean and the within-subjects variance, for a 2-level data structure where observations are nested within subjects. In some ecological momentary assessment studies, subjects are measured at multiple waves, and within each wave, subjects are measured over time. Li and Hedeker extended the original 2-level model to a 3-level data structure where observations are nested within days and days are then nested within subjects, by including a random location and scale intercept at the intermediate wave level. However, the 3-level random intercept model assumes constant response change rate for both the mean and variance. To account for changes in variance across waves, as well as clustering attributable to waves, we propose a more comprehensive location scale model that allows subject heterogeneity at baseline as well as across different waves, for a 3-level data structure where observations are nested within waves and waves are then further nested within subjects. The model parameters are estimated using Markov chain Monte Carlo methods. We provide details on the Bayesian estimation approach and demonstrate how the Stan statistical software can be used to sample from the desired distributions and achieve consistent estimates. The proposed model is validated via a series of simulation studies. Data from an adolescent smoking study are analyzed to demonstrate this approach. The analyses clearly favor the proposed model and show significant subject heterogeneity at baseline as well as change over time, for both mood mean and variance. The proposed 3-level

Ecological validity of cost-effectiveness models of universal HPV vaccination: A systematic literature review.

Science.gov (United States)

Favato, Giampiero; Easton, Tania; Vecchiato, Riccardo; Noikokyris, Emmanouil

2017-05-09

The protective (herd) effect of the selective vaccination of pubertal girls against human papillomavirus (HPV) implies a high probability that one of the two partners involved in intercourse is immunised, hence preventing the other from this sexually transmitted infection. The dynamic transmission models used to inform immunisation policy should include consideration of sexual behaviours and population mixing in order to demonstrate an ecological validity, whereby the scenarios modelled remain faithful to the real-life social and cultural context. The primary aim of this review is to test the ecological validity of the universal HPV vaccination cost-effectiveness modelling available in the published literature. The research protocol related to this systematic review has been registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD42016034145). Eight published economic evaluations were reviewed. None of the studies showed due consideration of the complexities of human sexual behaviour and the impact this may have on the transmission of HPV. Our findings indicate that all the included models might be affected by a different degree of ecological bias, which implies an inability to reflect the natural demographic and behavioural trends in their outcomes and, consequently, to accurately inform public healthcare policy. In particular, ecological bias have the effect to over-estimate the preference-based outcomes of selective immunisation. A relatively small (15-20%) over-estimation of quality-adjusted life years (QALYs) gained with selective immunisation programmes could induce a significant error in the estimate of cost-effectiveness of universal immunisation, by inflating its incremental cost effectiveness ratio (ICER) beyond the acceptability threshold. The results modelled here demonstrate the limitations of the cost-effectiveness studies for HPV vaccination, and highlight the concern that public healthcare policy might have been

Lumped-parameters equivalent circuit for condenser microphones modeling.

Science.gov (United States)

Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar

2017-10-01

This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.

Optimising the management of complex dynamic ecosystems. An ecological-economic modelling approach

NARCIS (Netherlands)

Hein, L.G.

2005-01-01

Keywords: ecological-economic modelling; ecosystem services; resource use; efficient; sustainability; wetlands, rangelands.

Analysis of Modeling Parameters on Threaded Screws.

Energy Technology Data Exchange (ETDEWEB)

Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-06-01

Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

Parameter Estimates in Differential Equation Models for Chemical Kinetics

Science.gov (United States)

Winkel, Brian

2011-01-01

We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…

Simultaneous inference for model averaging of derived parameters

DEFF Research Database (Denmark)

Jensen, Signe Marie; Ritz, Christian

2015-01-01

Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous...... inference for derived parameters calculated in an after-fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model-averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family...

Parameter identification in the logistic STAR model

DEFF Research Database (Denmark)

Ekner, Line Elvstrøm; Nejstgaard, Emil

We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...

Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds

Directory of Open Access Journals (Sweden)

Indrajeet Chaubey

2010-11-01

Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.

Soil-related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

A. J. Smith

2003-01-01

This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash

Ecological Applications of Qualitative Reasoning

NARCIS (Netherlands)

Bredeweg, B.; Salles, P.; Neumann, M.; Recknagel, F.

2006-01-01

Representing qualitative ecological knowledge is of great interest for ecological modelling. QR provides means to build conceptual models and to make qualitative knowledge explicit, organized and manageable by means of symbolic computing. This chapter discusses the main characteristics of QR using

Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

K. Rautenstrauch

2004-09-10

This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.

Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

K. Rautenstrauch

2004-01-01

This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception

Modeling and Parameter Estimation of a Small Wind Generation System

Directory of Open Access Journals (Sweden)

Carlos A. Ramírez Gómez

2013-11-01

Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.

Improving weather predictability by including land-surface model parameter uncertainty

Science.gov (United States)

Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

2016-04-01

The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by

Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

Science.gov (United States)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

2012-12-01

Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root

[Uncertainty analysis of ecological risk assessment caused by heavy-metals deposition from MSWI emission].

Science.gov (United States)

Liao, Zhi-Heng; Sun, Jia-Ren; Wu, Dui; Fan, Shao-Jia; Ren, Ming-Zhong; Lü, Jia-Yang

2014-06-01

The CALPUFF model was applied to simulate the ground-level atmospheric concentrations of Pb and Cd from municipal solid waste incineration (MSWI) plants, and the soil concentration model was used to estimate soil concentration increments after atmospheric deposition based on Monte Carlo simulation, then ecological risk assessment was conducted by the potential ecological risk index method. The results showed that the largest atmospheric concentrations of Pb and Cd were 5.59 x 109-3) microg x m(-3) and 5.57 x 10(-4) microg x m(-3), respectively, while the maxima of soil concentration incremental medium of Pb and Cd were 2.26 mg x kg(-1) and 0.21 mg x kg(-1), respectively; High risk areas were located next to the incinerators, Cd contributed the most to the ecological risk, and Pb was basically free of pollution risk; Higher ecological hazard level was predicted at the most polluted point in urban areas with a 55.30% probability, while in rural areas, the most polluted point was assessed to moderate ecological hazard level with a 72.92% probability. In addition, sensitivity analysis of calculation parameters in the soil concentration model was conducted, which showed the simulated results of urban and rural area were most sensitive to soil mix depth and dry deposition rate, respectively.

Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

Science.gov (United States)

Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

2017-11-20

A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

Science.gov (United States)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Directory of Open Access Journals (Sweden)

Xiao-meng Song

2013-01-01

Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

Updating parameters of the chicken processing line model

DEFF Research Database (Denmark)

Kurowicka, Dorota; Nauta, Maarten; Jozwiak, Katarzyna

2010-01-01

A mathematical model of chicken processing that quantitatively describes the transmission of Campylobacter on chicken carcasses from slaughter to chicken meat product has been developed in Nauta et al. (2005). This model was quantified with expert judgment. Recent availability of data allows...... updating parameters of the model to better describe processes observed in slaughterhouses. We propose Bayesian updating as a suitable technique to update expert judgment with microbiological data. Berrang and Dickens’s data are used to demonstrate performance of this method in updating parameters...... of the chicken processing line model....

Avian malaria: a new lease of life for an old experimental model to study the evolutionary ecology of Plasmodium.

Science.gov (United States)

Pigeault, Romain; Vézilier, Julien; Cornet, Stéphane; Zélé, Flore; Nicot, Antoine; Perret, Philippe; Gandon, Sylvain; Rivero, Ana

2015-08-19

Avian malaria has historically played an important role as a model in the study of human malaria, being a stimulus for the development of medical parasitology. Avian malaria has recently come back to the research scene as a unique animal model to understand the ecology and evolution of the disease, both in the field and in the laboratory. Avian malaria is highly prevalent in birds and mosquitoes around the world and is amenable to laboratory experimentation at each stage of the parasite's life cycle. Here, we take stock of 5 years of experimental laboratory research carried out using Plasmodium relictum SGS1, the most prevalent avian malaria lineage in Europe, and its natural vector, the mosquito Culex pipiens. For this purpose, we compile and analyse data obtained in our laboratory in 14 different experiments. We provide statistical relationships between different infection-related parameters, including parasitaemia, gametocytaemia, host morbidity (anaemia) and transmission rates to mosquitoes. This analysis provides a wide-ranging picture of the within-host and between-host parameters that may bear on malaria transmission and epidemiology. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Effect of an intervention based on socio-ecological model in promoting physical activity of female employees

Directory of Open Access Journals (Sweden)

Amineh Sahranavard Gargari

2018-03-01

Full Text Available Although active life style is one of the main determining factors of health, the level of regular physical activities in women is less than in men and even this level decreases with aging. The aim of this study was to determine the effect of an intervention based on the social ecological model on promotion of physical activity among female employees. In this study, 160 women employed at Shabestar universities were selected, and randomly divided into two groups of control (n=80 and intervention (n=80. The intervention group received an instructional program according to the model, including one session for general instruction and four sessions for group discussion along with daily walking for 30 minutes within 8 weeks. In order to objectively measure the physical activity, the pedometer was used and to measure the perceived physical activity, the long form of International Physical Activity Questionnaire (IPAQ was applied. The variables related to the components of socio-ecological model were measured using the socio-ecological model questionnaire. A significant difference was found between two groups after the intervention in terms of That is, the average number of steps in walking in the intervention group increased significantly (from 4204 to 7882 steps per day, while it did not significantly increase in the control group. Thus, it can be argued that designing and implementing the interventional programs based on the socio-ecological model can promote physical activity behavior among employed women

Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species

Science.gov (United States)

Haak, Danielle M.; Fath, Brian D.; Forbes, Valery E.; Martin, Dustin R.; Pope, Kevin L.

2017-01-01

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensisalters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

Seasonal and spatial variation in broadleaf forest model parameters