Bounding species distribution models

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Thomas J. STOHLGREN, Catherine S. JARNEVICH, Wayne E. ESAIAS,Jeffrey T. MORISETTE

2011-10-01

Full Text Available Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for “clamping” model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART and maximum entropy (Maxent models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5: 642–647, 2011].

Bounding Species Distribution Models

Science.gov (United States)

Stohlgren, Thomas J.; Jarnevich, Cahterine S.; Morisette, Jeffrey T.; Esaias, Wayne E.

2011-01-01

Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].

The temporal-relevance temporal-uncertainty model of prospective duration judgment.

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Zakay, Dan

2015-12-15

A model aimed at explaining prospective duration judgments in real life settings (as well as in the laboratory) is presented. The model is based on the assumption that situational meaning is continuously being extracted by humans' perceptual and cognitive information processing systems. Time is one of the important dimensions of situational meaning. Based on the situational meaning, a value for Temporal Relevance is set. Temporal Relevance reflects the importance of temporal aspects for enabling adaptive behavior in a specific moment in time. When Temporal Relevance is above a certain threshold a prospective duration judgment process is evoked automatically. In addition, a search for relevant temporal information is taking place and its outcomes determine the level of Temporal Uncertainty which reflects the degree of knowledge one has regarding temporal aspects of the task to be performed. The levels of Temporal Relevance and Temporal Uncertainty determine the amount of attentional resources allocated for timing by the executive system. The merit of the model is in connecting timing processes with the ongoing general information processing stream. The model rests on findings in various domains which indicate that cognitive-relevance and self-relevance are powerful determinants of resource allocation policy. The feasibility of the model is demonstrated by analyzing various temporal phenomena. Suggestions for further empirical validation of the model are presented. Copyright © 2015 Elsevier Inc. All rights reserved.

Habitat or matrix: which is more relevant to predict road-kill of vertebrates?

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C. Bueno

Full Text Available Abstract We believe that in tropics we need a community approach to evaluate road impacts on wildlife, and thus, suggest mitigation measures for groups of species instead a focal-species approach. Understanding which landscape characteristics indicate road-kill events may also provide models that can be applied in other regions. We intend to evaluate if habitat or matrix is more relevant to predict road-kill events for a group of species. Our hypothesis is: more permeable matrix is the most relevant factor to explain road-kill events. To test this hypothesis, we chose vertebrates as the studied assemblage and a highway crossing in an Atlantic Forest region in southeastern Brazil as the study site. Logistic regression models were designed using presence/absence of road-kill events as dependent variables and landscape characteristics as independent variables, which were selected by Akaike’s Information Criterion. We considered a set of candidate models containing four types of simple regression models: Habitat effect model; Matrix types effect models; Highway effect model; and, Reference models (intercept and buffer distance. Almost three hundred road-kills and 70 species were recorded. River proximity and herbaceous vegetation cover, both matrix effect models, were associated to most road-killed vertebrate groups. Matrix was more relevant than habitat to predict road-kill of vertebrates. The association between river proximity and road-kill indicates that rivers may be a preferential route for most species. We discuss multi-species mitigation measures and implications to movement ecology and conservation strategies.

Incorporating Context Dependency of Species Interactions in Species Distribution Models.

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Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A

2017-07-01

Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same

Seed germination methods for native Caribbean trees and shrubs : with emphasis on species relevant for Bonaire

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Burg, van der W.J.; Freitas, J.; Debrot, A.O.

2014-01-01

This paper is intended as a basis for nature restoration activities using seeds of trees and (larger) shrubs native to Bonaire with the aim of reforestation. It describes the main seed biology issues relevant for species from this region, to facilitate decisions on time and stage of harvesting, safe

Phylogeny and source climate impact seed dormancy and germination of restoration-relevant forb species.

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Seglias, Alexandra E; Williams, Evelyn; Bilge, Arman; Kramer, Andrea T

2018-01-01

For many species and seed sources used in restoration activities, specific seed germination requirements are often unknown. Because seed dormancy and germination traits can be constrained by phylogenetic history, related species are often assumed to have similar traits. However, significant variation in these traits is also present within species as a result of adaptation to local climatic conditions. A growing number of studies have attempted to disentangle how phylogeny and climate influence seed dormancy and germination traits, but they have focused primarily on species-level effects, ignoring potential population-level variation. We examined the relationships between phylogeny, climate, and seed dormancy and germination traits for 24 populations of eight native, restoration-relevant forb species found in a wide range of climatic conditions in the Southwest United States. The seeds were exposed to eight temperature and stratification length regimes designed to mimic regional climatic conditions. Phylogenetic relatedness, overall climatic conditions, and temperature conditions at the site were all significantly correlated with final germination response, with significant among-population variation in germination response across incubation treatments for seven of our eight study species. Notably, germination during stratification was significantly predicted by precipitation seasonality and differed significantly among populations for seven species. While previous studies have not examined germination during stratification as a potential trait influencing overall germination response, our results suggest that this trait should be included in germination studies as well as seed sourcing decisions. Results of this study deepen our understanding of the relationships between source climate, species identity, and germination, leading to improved seed sourcing decisions for restorations.

On relevant boundary perturbations of unitary minimal models

International Nuclear Information System (INIS)

Recknagel, A.; Roggenkamp, D.; Schomerus, V.

2000-01-01

We consider unitary Virasoro minimal models on the disk with Cardy boundary conditions and discuss deformations by certain relevant boundary operators, analogous to tachyon condensation in string theory. Concentrating on the least relevant boundary field, we can perform a perturbative analysis of renormalization group fixed points. We find that the systems always flow towards stable fixed points which admit no further (non-trivial) relevant perturbations. The new conformal boundary conditions are in general given by superpositions of 'pure' Cardy boundary conditions

Moving Towards Dynamic Ocean Management: How Well Do Modeled Ocean Products Predict Species Distributions?

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Elizabeth A. Becker

2016-02-01

Full Text Available Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ and remotely sensed oceanic variables (both are considered “measured data”, but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE, observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.

Nuclear models relevant to evaluation

International Nuclear Information System (INIS)

Arthur, E.D.; Chadwick, M.B.; Hale, G.M.; Young, P.G.

1991-01-01

The widespread use of nuclear models continues in the creation of data evaluations. The reasons include extension of data evaluations to higher energies, creation of data libraries for isotopic components of natural materials, and production of evaluations for radiative target species. In these cases, experimental data are often sparse or nonexistent. As this trend continues, the nuclear models employed in evaluation work move towards more microscopically-based theoretical methods, prompted in part by the availability of increasingly powerful computational resources. Advances in nuclear models applicable to evaluation will be reviewed. These include advances in optical model theory, microscopic and phenomenological state and level density theory, unified models that consistently describe both equilibrium and nonequilibrium reaction mechanism, and improved methodologies for calculation of prompt radiation from fission. 84 refs., 8 figs

Global Modeling of Uranium Molecular Species Formation Using Laser-Ablated Plasmas

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Curreli, Davide; Finko, Mikhail; Azer, Magdi; Armstrong, Mike; Crowhurst, Jonathan; Radousky, Harry; Rose, Timothy; Stavrou, Elissaios; Weisz, David; Zaug, Joseph

2016-10-01

Uranium is chemically fractionated from other refractory elements in post-detonation nuclear debris but the mechanism is poorly understood. Fractionation alters the chemistry of the nuclear debris so that it no longer reflects the chemistry of the source weapon. The conditions of a condensing fireball can be simulated by a low-temperature plasma formed by vaporizing a uranium sample via laser heating. We have developed a global plasma kinetic model in order to model the chemical evolution of U/UOx species within an ablated plasma plume. The model allows to track the time evolution of the density and energy of an uranium plasma plume moving through an oxygen atmosphere of given fugacity, as well as other relevant quantities such as average electron and gas temperature. Comparison of model predictions with absorption spectroscopy of uranium-ablated plasmas provide preliminary insights on the key chemical species and evolution pathways involved during the fractionation process. This project was sponsored by the DoD, Defense Threat Reduction Agency, Grant HDTRA1-16-1-0020. This work was performed in part under the auspices of the U.S. DoE by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

How can model comparison help improving species distribution models?

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Emmanuel Stephan Gritti

Full Text Available Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs. However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagussylvatica L., Quercusrobur L. and Pinussylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.

Stress and adaptation : Toward ecologically relevant animal models

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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.

Modelling patterns of pollinator species richness and diversity using satellite image texture.

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Sylvia Hofmann

Full Text Available Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013 from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees. While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

Modelling patterns of pollinator species richness and diversity using satellite image texture.

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Hofmann, Sylvia; Everaars, Jeroen; Schweiger, Oliver; Frenzel, Mark; Bannehr, Lutz; Cord, Anna F

2017-01-01

Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS) can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013) from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees). While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

New trends in species distribution modelling

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Zimmermann, Niklaus E.; Edwards, Thomas C.; Graham, Catherine H.; Pearman, Peter B.; Svenning, Jens-Christian

2010-01-01

Species distribution modelling has its origin in the late 1970s when computing capacity was limited. Early work in the field concentrated mostly on the development of methods to model effectively the shape of a species' response to environmental gradients (Austin 1987, Austin et al. 1990). The methodology and its framework were summarized in reviews 10–15 yr ago (Franklin 1995, Guisan and Zimmermann 2000), and these syntheses are still widely used as reference landmarks in the current distribution modelling literature. However, enormous advancements have occurred over the last decade, with hundreds – if not thousands – of publications on species distribution model (SDM) methodologies and their application to a broad set of conservation, ecological and evolutionary questions. With this special issue, originating from the third of a set of specialized SDM workshops (2008 Riederalp) entitled 'The Utility of Species Distribution Models as Tools for Conservation Ecology', we reflect on current trends and the progress achieved over the last decade.

Richards-like two species population dynamics model.

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Ribeiro, Fabiano; Cabella, Brenno Caetano Troca; Martinez, Alexandre Souto

2014-12-01

The two-species population dynamics model is the simplest paradigm of inter- and intra-species interaction. Here, we present a generalized Lotka-Volterra model with intraspecific competition, which retrieves as particular cases, some well-known models. The generalization parameter is related to the species habitat dimensionality and their interaction range. Contrary to standard models, the species coupling parameters are general, not restricted to non-negative values. Therefore, they may represent different ecological regimes, which are derived from the asymptotic solution stability analysis and are represented in a phase diagram. In this diagram, we have identified a forbidden region in the mutualism regime, and a survival/extinction transition with dependence on initial conditions for the competition regime. Also, we shed light on two types of predation and competition: weak, if there are species coexistence, or strong, if at least one species is extinguished.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

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Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

Science.gov (United States)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Experimental measurement and modelling of reactive species generation in TiO2 nanoparticle photocatalysis.

Science.gov (United States)

Turolla, Andrea; Piazzoli, Andrea; Budarz, Jeffrey Farner; Wiesner, Mark R; Antonelli, Manuela

2015-07-01

The generation of reactive species in titanium dioxide (TiO 2 ) nanoparticle photocatalysis was assessed in a laboratory scale setup, in which P25 Aeroxide TiO 2 suspensions were photoactivated by means of UV-A radiation. Photogenerated holes and hydroxyl radicals were monitored over time by observing their selective reaction with probe compounds, iodide and terephthalic acid, respectively. TiO 2 aggregate size and structure were characterized over the reaction time. Reactive species quenching was then described by a model, accounting for radiative phenomena, TiO 2 nanoparticle aggregation and kinetic reactions. The interaction between iodide and photogenerated holes was influenced by iodide adsorption on TiO 2 surface, described by a Langmuir-Hinshelwood mechanism, whose parameters were studied as a function of TiO 2 concentration and irradiation time. Iodide oxidation was effectively simulated by modelling the reaction volume as a completely stirred two-dimensional domain, in which irradiation phenomena were described by a two-flux model and the steady state for reactive species was assumed. The kinetic parameters for iodide adsorption and oxidation were estimated and successfully validated in a different experimental setup. The same model was adapted to describe the oxidation of terephthalic acid by hydroxyl radicals. The kinetic parameters for terephthalic acid oxidation were estimated and validated, while the issues in investigating the interaction mechanisms among the involved species have been discussed. The sensitivity of operating parameters on model response was assessed and the most relevant parameters were highlighted.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

OpenAIRE

Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...

Construction of analytically solvable models for interacting species. [biological species competition

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Rosen, G.

1976-01-01

The basic form of a model representation for systems of n interacting biological species is a set of essentially nonlinear autonomous ordinary differential equations. A generic canonical expression for the rate functions in the equations is reported which permits the analytical general solution to be obtained by elementary computation. It is shown that a general analytical solution is directly obtainable for models where the rate functions are prescribed by the generic canonical expression from the outset. Some illustrative examples are given which demonstrate that the generic canonical expression can be used to construct analytically solvable models for two interacting species with limit-cycle dynamics as well as for a three-species interdependence.

Minipig and beagle animal model genomes aid species selection in pharmaceutical discovery and development

Energy Technology Data Exchange (ETDEWEB)

Vamathevan, Jessica J., E-mail: jessica.j.vamathevan@gsk.com [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom); Hall, Matthew D.; Hasan, Samiul; Woollard, Peter M. [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom); Xu, Meng; Yang, Yulan; Li, Xin; Wang, Xiaoli [BGI-Shenzen, Shenzhen (China); Kenny, Steve [Safety Assessment, PTS, GlaxoSmithKline, Ware (United Kingdom); Brown, James R. [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Collegeville, PA (United States); Huxley-Jones, Julie [UK Platform Technology Sciences (PTS) Operations and Planning, PTS, GlaxoSmithKline, Stevenage (United Kingdom); Lyon, Jon; Haselden, John [Safety Assessment, PTS, GlaxoSmithKline, Ware (United Kingdom); Min, Jiumeng [BGI-Shenzen, Shenzhen (China); Sanseau, Philippe [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom)

2013-07-15

Improving drug attrition remains a challenge in pharmaceutical discovery and development. A major cause of early attrition is the demonstration of safety signals which can negate any therapeutic index previously established. Safety attrition needs to be put in context of clinical translation (i.e. human relevance) and is negatively impacted by differences between animal models and human. In order to minimize such an impact, an earlier assessment of pharmacological target homology across animal model species will enhance understanding of the context of animal safety signals and aid species selection during later regulatory toxicology studies. Here we sequenced the genomes of the Sus scrofa Göttingen minipig and the Canis familiaris beagle, two widely used animal species in regulatory safety studies. Comparative analyses of these new genomes with other key model organisms, namely mouse, rat, cynomolgus macaque, rhesus macaque, two related breeds (S. scrofa Duroc and C. familiaris boxer) and human reveal considerable variation in gene content. Key genes in toxicology and metabolism studies, such as the UGT2 family, CYP2D6, and SLCO1A2, displayed unique duplication patterns. Comparisons of 317 known human drug targets revealed surprising variation such as species-specific positive selection, duplication and higher occurrences of pseudogenized targets in beagle (41 genes) relative to minipig (19 genes). These data will facilitate the more effective use of animals in biomedical research. - Highlights: • Genomes of the minipig and beagle dog, two species used in pharmaceutical studies. • First systematic comparative genome analysis of human and six experimental animals. • Key drug toxicology genes display unique duplication patterns across species. • Comparison of 317 drug targets show species-specific evolutionary patterns.

Minipig and beagle animal model genomes aid species selection in pharmaceutical discovery and development

International Nuclear Information System (INIS)

Vamathevan, Jessica J.; Hall, Matthew D.; Hasan, Samiul; Woollard, Peter M.; Xu, Meng; Yang, Yulan; Li, Xin; Wang, Xiaoli; Kenny, Steve; Brown, James R.; Huxley-Jones, Julie; Lyon, Jon; Haselden, John; Min, Jiumeng; Sanseau, Philippe

2013-01-01

Improving drug attrition remains a challenge in pharmaceutical discovery and development. A major cause of early attrition is the demonstration of safety signals which can negate any therapeutic index previously established. Safety attrition needs to be put in context of clinical translation (i.e. human relevance) and is negatively impacted by differences between animal models and human. In order to minimize such an impact, an earlier assessment of pharmacological target homology across animal model species will enhance understanding of the context of animal safety signals and aid species selection during later regulatory toxicology studies. Here we sequenced the genomes of the Sus scrofa Göttingen minipig and the Canis familiaris beagle, two widely used animal species in regulatory safety studies. Comparative analyses of these new genomes with other key model organisms, namely mouse, rat, cynomolgus macaque, rhesus macaque, two related breeds (S. scrofa Duroc and C. familiaris boxer) and human reveal considerable variation in gene content. Key genes in toxicology and metabolism studies, such as the UGT2 family, CYP2D6, and SLCO1A2, displayed unique duplication patterns. Comparisons of 317 known human drug targets revealed surprising variation such as species-specific positive selection, duplication and higher occurrences of pseudogenized targets in beagle (41 genes) relative to minipig (19 genes). These data will facilitate the more effective use of animals in biomedical research. - Highlights: • Genomes of the minipig and beagle dog, two species used in pharmaceutical studies. • First systematic comparative genome analysis of human and six experimental animals. • Key drug toxicology genes display unique duplication patterns across species. • Comparison of 317 drug targets show species-specific evolutionary patterns

Marmosets as model species in neuroscience and evolutionary anthropology.

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Burkart, Judith M; Finkenwirth, Christa

2015-04-01

Marmosets are increasingly used as model species by both neuroscientists and evolutionary anthropologists, but with a different rationale for doing so. Whereas neuroscientists stress that marmosets share many cognitive traits with humans due to common descent, anthropologists stress those traits shared with marmosets - and callitrichid monkeys in general - due to convergent evolution, as a consequence of the cooperative breeding system that characterizes both humans and callitrichids. Similarities in socio-cognitive abilities due to convergence, rather than homology, raise the question whether these similarities also extend to the proximate regulatory mechanisms, which is particularly relevant for neuroscientific investigations. In this review, we first provide an overview of the convergent adaptations to cooperative breeding at the psychological and cognitive level in primates, which bear important implications for our understanding of human cognitive evolution. In the second part, we zoom in on two of these convergent adaptations, proactive prosociality and social learning, and compare their proximate regulation in marmosets and humans with regard to oxytocin and cognitive top down regulation. Our analysis suggests considerable similarity in these regulatory mechanisms presumably because the convergent traits emerged due to small motivational changes that define how pre-existing cognitive mechanisms are quantitatively combined. This finding reconciles the prima facie contradictory rationale for using marmosets as high priority model species in neuroscience and anthropology. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Towards increased policy relevance in energy modeling

Energy Technology Data Exchange (ETDEWEB)

Worrell, Ernst; Ramesohl, Stephan; Boyd, Gale

2003-07-29

Historically, most energy models were reasonably equipped to assess the impact of a subsidy or change in taxation, but are often insufficient to assess the impact of more innovative policy instruments. We evaluate the models used to assess future energy use, focusing on industrial energy use. We explore approaches to engineering-economic analysis that could help improve the realism and policy relevance of engineering-economic modeling frameworks. We also explore solutions to strengthen the policy usefulness of engineering-economic analysis that can be built from a framework of multi-disciplinary cooperation. We focus on the so-called ''engineering-economic'' (or ''bottom-up'') models, as they include the amount of detail that is commonly needed to model policy scenarios. We identify research priorities for the modeling framework, technology representation in models, policy evaluation and modeling of decision-making behavior.

A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance Model

Science.gov (United States)

Mathe, Nathalie; Chen, James

1994-01-01

Rapid and effective to information in large electronic documentation systems can be facilitated if information relevant in an individual user's content can be automatically supplied to this user. However most of this knowledge on contextual relevance is not found within the contents of documents, it is rather established incrementally by users during information access. We propose a new model for interactively learning contextual relevance during information retrieval, and incrementally adapting retrieved information to individual user profiles. The model, called a relevance network, records the relevance of references based on user feedback for specific queries and user profiles. It also generalizes such knowledge to later derive relevant references for similar queries and profiles. The relevance network lets users filter information by context of relevance. Compared to other approaches, it does not require any prior knowledge nor training. More importantly, our approach to adaptivity is user-centered. It facilitates acceptance and understanding by users by giving them shared control over the adaptation without disturbing their primary task. Users easily control when to adapt and when to use the adapted system. Lastly, the model is independent of the particular application used to access information, and supports sharing of adaptations among users.

Neonatal CNS infection and inflammation caused by Ureaplasma species: rare or relevant?

Science.gov (United States)

Glaser, Kirsten; Speer, Christian P

2015-02-01

Colonization with Ureaplasma species has been associated with adverse pregnancy outcome, and perinatal transmission has been implicated in the development of bronchopulmonary dysplasia in preterm neonates. Little is known about Ureaplasma-mediated infection and inflammation of the CNS in neonates. Controversy remains concerning its incidence and implication in the pathogenesis of neonatal brain injury. In vivo and in vitro data are limited. Despite improving care options for extremely immature preterm infants, relevant complications remain. Systematic knowledge of ureaplasmal infection may be of great benefit. This review aims to summarize pathogenic mechanisms, clinical data and diagnostic pitfalls. Studies in preterm and term neonates are critically discussed with regard to their limitations. Clinical questions concerning therapy or prophylaxis are posed. We conclude that ureaplasmas may be true pathogens, especially in preterm neonates, and may cause CNS inflammation in a complex interplay of host susceptibility, serovar pathogenicity and gestational age-dependent CNS vulnerability.

Assessment of relevant fungal species in clinical solid wastes.

Science.gov (United States)

Noman, Efaq Ali; Al-Gheethi, A A; Rahman, Nik Norulaini Nik Ab; Nagao, H; Ab Kadir, M O

2016-10-01

The study aimed to determine the fungal diversity in clinical waste samples from a healthcare facility in Penang Malaysia. Different fungi species were detected in 83.75 % of the 92 clinical waste samples that were screened from different sections of the healthcare facility. One hundred fifty fungal isolates comprising of 8 genera and 36 species were obtained. They were purified by using single spore isolation technique. Subsequently, the isolates were identified by phenotypic method based on morphological and culture characteristics on different culture media. Among all fungal isolates, Aspergillus spp. in section Nigri 10.2 %, Aspergillus niger 9.5 %, Aspergillus fumigatus 8.8 %, Penicillium. simplicissium 8 %, Aspergillus tubingensis 7.3 %, Aspergillus terreus var. terreus 6.6 %, Penicillium waksmanii 5.9 % and Curvularia lunata 6.5 % were the most frequent. Among five sections of the Wellness Centre, the clinical wastes collected from the diagnostic labs of haematology section had the highest numbers of fungal species (29 species). Glove wastes had the highest numbers of fungal species (19 species) among 17 types of clinical wastes screened. Among all fungal species, Aspergillus spp. exhibited higher growth at 37 °C than at 28 °C, indicating the potential of these opportunistic fungi to cause diseases in human. These results indicated the potential of hospital wastes as reservoirs for fungal species.

Silica desiccant packets for storage and transport of Streptococcus pneumoniae and other clinically relevant species.

Directory of Open Access Journals (Sweden)

Casey L Pell

Full Text Available Bacterial isolates are often transported between laboratories for research and diagnostic purposes. Silica desiccant packets (SDPs, which are inexpensive and do not require freezing, were evaluated for storage and recovery of bacterial isolates. Conditions such as inoculum size, swab type and temperature of storage were investigated using ten Streptococcus pneumoniae isolates. The optimized protocol was then tested using 49 additional S. pneumoniae isolates representing 40 serogroups. Overall, S. pneumoniae growth was considered satisfactory (>100 colony forming units for 98/109 (89.9% and 20/20 (100% swabs after 14 days at room temperature or 28 days at 4° C, respectively. Storage in SDPs did not impact on the ability of S. pneumoniae isolates to be subsequently serotyped. When the survival of nine other clinically relevant bacterial species was tested, seven were viable after 28 days at room temperature, the exceptions being Neisseria gonorrhoeae and Haemophilus influenzae. SDPs are suitable for transport and short-term storage of bacterial species including S. pneumoniae.

Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

Science.gov (United States)

Mainali, Kumar P; Warren, Dan L; Dhileepan, Kunjithapatham; McConnachie, Andrew; Strathie, Lorraine; Hassan, Gul; Karki, Debendra; Shrestha, Bharat B; Parmesan, Camille

2015-12-01

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium

BAYESIAN MODELS FOR SPECIES DISTRIBUTION MODELLING WITH ONLY-PRESENCE RECORDS

Directory of Open Access Journals (Sweden)

Bartolo de Jesús Villar-Hernández

2015-08-01

Full Text Available One of the central issues in ecology is the study of geographical distribution of species of flora and fauna through Species Distribution Models (SDM. Recently, scientific interest has focused on presence-only records. Two recent approaches have been proposed for this problem: a model based on maximum likelihood method (Maxlike and an inhomogeneous poisson process model (IPP. In this paper we discussed two bayesian approaches called MaxBayes and IPPBayes based on Maxlike and IPP model, respectively. To illustrate these proposals, we implemented two study examples: (1 both models were implemented on a simulated dataset, and (2 we modeled the potencial distribution of genus Dalea in the Tehuacan-Cuicatlán biosphere reserve with both models, the results was compared with that of Maxent. The results show that both models, MaxBayes and IPPBayes, are viable alternatives when species distribution are modeled with only-presence records. For simulated dataset, MaxBayes achieved prevalence estimation, even when the number of records was small. In the real dataset example, both models predict similar potential distributions like Maxent does. Â

Relevant criteria for testing the quality of turbulence models

DEFF Research Database (Denmark)

Frandsen, Sten Tronæs; Ejsing Jørgensen, Hans; Sørensen, J.D.

2007-01-01

Seeking relevant criteria for testing the quality of turbulence models, the scale of turbulence and the gust factor have been estimated from data and compared with predictions from first-order models of these two quantities. It is found that the mean of the measured length scales is approx. 10......% smaller than the IEC model, for wind turbine hub height levels. The mean is only marginally dependent on trends in time series. It is also found that the coefficient of variation of the measured length scales is about 50%. 3sec and 10sec pre-averaging of wind speed data are relevant for MW-size wind...... turbines when seeking wind characteristics that correspond to one blade and the entire rotor, respectively. For heights exceeding 50-60m the gust factor increases with wind speed. For heights larger the 60-80m, present assumptions on the value of the gust factor are significantly conservative, both for 3...

A simple model for skewed species-lifetime distributions

KAUST Repository

Murase, Yohsuke

2010-06-11

A simple model of a biological community assembly is studied. Communities are assembled by successive migrations and extinctions of species. In the model, species are interacting with each other. The intensity of the interaction between each pair of species is denoted by an interaction coefficient. At each time step, a new species is introduced to the system with randomly assigned interaction coefficients. If the sum of the coefficients, which we call the fitness of a species, is negative, the species goes extinct. The species-lifetime distribution is found to be well characterized by a stretched exponential function with an exponent close to 1/2. This profile agrees not only with more realistic population dynamics models but also with fossil records. We also find that an age-independent and inversely diversity-dependent mortality, which is confirmed in the simulation, is a key mechanism accounting for the distribution. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.

Using Species Distribution Models to Predict Potential Landscape Restoration Effects on Puma Conservation.

Science.gov (United States)

Angelieri, Cintia Camila Silva; Adams-Hosking, Christine; Ferraz, Katia Maria Paschoaletto Micchi de Barros; de Souza, Marcelo Pereira; McAlpine, Clive Alexander

2016-01-01

A mosaic of intact native and human-modified vegetation use can provide important habitat for top predators such as the puma (Puma concolor), avoiding negative effects on other species and ecological processes due to cascade trophic interactions. This study investigates the effects of restoration scenarios on the puma's habitat suitability in the most developed Brazilian region (São Paulo State). Species Distribution Models incorporating restoration scenarios were developed using the species' occurrence information to (1) map habitat suitability of pumas in São Paulo State, Southeast, Brazil; (2) test the relative contribution of environmental variables ecologically relevant to the species habitat suitability and (3) project the predicted habitat suitability to future native vegetation restoration scenarios. The Maximum Entropy algorithm was used (Test AUC of 0.84 ± 0.0228) based on seven environmental non-correlated variables and non-autocorrelated presence-only records (n = 342). The percentage of native vegetation (positive influence), elevation (positive influence) and density of roads (negative influence) were considered the most important environmental variables to the model. Model projections to restoration scenarios reflected the high positive relationship between pumas and native vegetation. These projections identified new high suitability areas for pumas (probability of presence >0.5) in highly deforested regions. High suitability areas were increased from 5.3% to 8.5% of the total State extension when the landscapes were restored for ≥ the minimum native vegetation cover rule (20%) established by the Brazilian Forest Code in private lands. This study highlights the importance of a landscape planning approach to improve the conservation outlook for pumas and other species, including not only the establishment and management of protected areas, but also the habitat restoration on private lands. Importantly, the results may inform environmental

Nyala and Bushbuck I: A Competing Species Model.

Science.gov (United States)

Fay, Temple H.; Greeff, Johanna C.

1999-01-01

Introduces a model of differential equations for students--a very real overpopulation problem is occurring in the Ndumu Game Reserve in KwaZulu-Natal, South Africa, where one species of antelope, the Nyala, is crowding out another species, the Bushbuck. Constructs a competing species model to mathematically describe what is occurring in Ndumu.…

Modeling of Alkane Oxidation Using Constituents and Species

Science.gov (United States)

Bellan, Jasette; Harstad, Kenneth G.

2010-01-01

It is currently not possible to perform simulations of turbulent reactive flows due in particular to complex chemistry, which may contain thousands of reactions and hundreds of species. This complex chemistry results in additional differential equations, making the numerical solution of the equation set computationally prohibitive. Reducing the chemical kinetics mathematical description is one of several important goals in turbulent reactive flow modeling. A chemical kinetics reduction model is proposed for alkane oxidation in air that is based on a parallel methodology to that used in turbulence modeling in the context of the Large Eddy Simulation. The objective of kinetic modeling is to predict the heat release and temperature evolution. This kinetic mechanism is valid over a pressure range from atmospheric to 60 bar, temperatures from 600 K to 2,500 K, and equivalence ratios from 0.125 to 8. This range encompasses diesel, HCCI, and gas-turbine engines, including cold ignition. A computationally efficient kinetic reduction has been proposed for alkanes that has been illustrated for n-heptane using the LLNL heptane mechanism. This model is consistent with turbulence modeling in that scales were first categorized into either those modeled or those computed as progress variables. Species were identified as being either light or heavy. The heavy species were decomposed into defined 13 constituents, and their total molar density was shown to evolve in a quasi-steady manner. The light species behave either in a quasi-steady or unsteady manner. The modeled scales are the total constituent molar density, Nc, and the molar density of the quasi-steady light species. The progress variables are the total constituent molar density rate evolution and the molar densities of the unsteady light species. The unsteady equations for the light species contain contributions of the type gain/loss rates from the heavy species that are modeled consistent with the developed mathematical

Genetic mouse models relevant to schizophrenia: taking stock and looking forward.

Science.gov (United States)

Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M

2012-03-01

Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mathematical Properties Relevant to Geomagnetic Field Modeling

DEFF Research Database (Denmark)

Sabaka, Terence J.; Hulot, Gauthier; Olsen, Nils

2010-01-01

be directly measured. In this chapter, the mathematical foundation of global (as opposed to regional) geomagnetic field modeling is reviewed, and the spatial modeling of the field in spherical coordinates is focussed. Time can be dealt with as an independent variable and is not explicitly considered......Geomagnetic field modeling consists in converting large numbers of magnetic observations into a linear combination of elementary mathematical functions that best describes those observations.The set of numerical coefficients defining this linear combination is then what one refers.......The relevant elementary mathematical functions are introduced, their properties are reviewed, and how they can be used to describe the magnetic field in a source-free (such as the Earth’s neutral atmosphere) or source-dense (such as the ionosphere) environment is explained. Completeness and uniqueness...

Mathematical Properties Relevant to Geomagnetic Field Modeling

DEFF Research Database (Denmark)

Sabaka, Terence J.; Hulot, Gauthier; Olsen, Nils

2014-01-01

be directly measured. In this chapter, the mathematical foundation of global (as opposed to regional) geomagnetic field modeling is reviewed, and the spatial modeling of the field in spherical coordinates is focused. Time can be dealt with as an independent variable and is not explicitly considered......Geomagnetic field modeling consists in converting large numbers of magnetic observations into a linear combination of elementary mathematical functions that best describes those observations. The set of numerical coefficients defining this linear combination is then what one refers....... The relevant elementary mathematical functions are introduced, their properties are reviewed, and how they can be used to describe the magnetic field in a source-free (such as the Earth’s neutral atmosphere) or source-dense (such as the ionosphere) environment is explained. Completeness and uniqueness...

Species distribution model transferability and model grain size - finer may not always be better.

Science.gov (United States)

Manzoor, Syed Amir; Griffiths, Geoffrey; Lukac, Martin

2018-05-08

Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.

Effect of species rarity on the accuracy of species distribution models for reptiles and amphibians in southern California

Science.gov (United States)

Franklin, J.; Wejnert, K.E.; Hathaway, S.A.; Rochester, C.J.; Fisher, R.N.

2009-01-01

Aim: Several studies have found that more accurate predictive models of species' occurrences can be developed for rarer species; however, one recent study found the relationship between range size and model performance to be an artefact of sample prevalence, that is, the proportion of presence versus absence observations in the data used to train the model. We examined the effect of model type, species rarity class, species' survey frequency, detectability and manipulated sample prevalence on the accuracy of distribution models developed for 30 reptile and amphibian species. Location: Coastal southern California, USA. Methods: Classification trees, generalized additive models and generalized linear models were developed using species presence and absence data from 420 locations. Model performance was measured using sensitivity, specificity and the area under the curve (AUC) of the receiver-operating characteristic (ROC) plot based on twofold cross-validation, or on bootstrapping. Predictors included climate, terrain, soil and vegetation variables. Species were assigned to rarity classes by experts. The data were sampled to generate subsets with varying ratios of presences and absences to test for the effect of sample prevalence. Join count statistics were used to characterize spatial dependence in the prediction errors. Results: Species in classes with higher rarity were more accurately predicted than common species, and this effect was independent of sample prevalence. Although positive spatial autocorrelation remained in the prediction errors, it was weaker than was observed in the species occurrence data. The differences in accuracy among model types were slight. Main conclusions: Using a variety of modelling methods, more accurate species distribution models were developed for rarer than for more common species. This was presumably because it is difficult to discriminate suitable from unsuitable habitat for habitat generalists, and not as an artefact of the

Other relevant numerical modelling papers

International Nuclear Information System (INIS)

Chartier, M.

1989-01-01

The ocean modelling is a rapidly evolving science and a large number of results have been published. Several categories of papers are of particular interest for this review: the papers published by the international atomic institutions, such as the NEA (for the CRESP or Subseabed Programs), the IAEA (for example the Safety Series, the Technical Report Series or the TECDOC), and the ICRP, and the papers concerned by more fundamental research, which are published in specific scientific literature. This paper aims to list some of the most relevant publications for the CRESP purposes. It means by no way to be exhaustive, but informative on the incontestable progress recently achieved in that field. One should note that some of these papers are so recent that their final version has not yet been published

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

Science.gov (United States)

Miller, Brian W.; Frid, Leonardo; Chang, Tony; Piekielek, N. B.; Hansen, Andrew J.; Morisette, Jeffrey T.

2015-01-01

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

Intertwining personal and reward relevance: evidence from the drift-diffusion model.

Science.gov (United States)

Yankouskaya, A; Bührle, R; Lugt, E; Stolte, M; Sui, J

2018-01-24

In their seminal paper 'Is our self nothing but reward', Northoff and Hayes (Biol Psychiatry 69(11):1019-1025, Northoff, Hayes, Biological Psychiatry 69(11):1019-1025, 2011) proposed three models of the relationship between self and reward and opened a continuing debate about how these different fields can be linked. To date, none of the proposed models received strong empirical support. The present study tested common and distinct effects of personal relevance and reward values by de-componenting different stages of perceptual decision making using a drift-diffusion approach. We employed a recently developed associative matching paradigm where participants (N = 40) formed mental associations between five geometric shapes and five labels referring personal relevance in the personal task, or five shape-label pairings with different reward values in the reward task and then performed a matching task by indicating whether a displayed shape-label pairing was correct or incorrect. We found that common effects of personal relevance and monetary reward were manifested in the facilitation of behavioural performance for high personal relevance and high reward value as socially important signals. The differential effects between personal and monetary relevance reflected non-decisional time in a perceptual decision process, and task-specific prioritization of stimuli. Our findings support the parallel processing model (Northoff & Hayes, Biol Psychiatry 69(11):1019-1025, Northoff, Hayes, Biological Psychiatry 69(11):1019-1025, 2011) and suggest that self-specific processing occurs in parallel with high reward processing. Limitations and further directions are discussed.

A simple model for skewed species-lifetime distributions

KAUST Repository

Murase, Yohsuke; Shimada, Takashi; Ito, Nobuyasu

2010-01-01

A simple model of a biological community assembly is studied. Communities are assembled by successive migrations and extinctions of species. In the model, species are interacting with each other. The intensity of the interaction between each pair

Species Distribution Modeling: Comparison of Fixed and Mixed Effects Models Using INLA

Directory of Open Access Journals (Sweden)

Lara Dutra Silva

2017-12-01

Full Text Available Invasive alien species are among the most important, least controlled, and least reversible of human impacts on the world’s ecosystems, with negative consequences affecting biodiversity and socioeconomic systems. Species distribution models have become a fundamental tool in assessing the potential spread of invasive species in face of their native counterparts. In this study we compared two different modeling techniques: (i fixed effects models accounting for the effect of ecogeographical variables (EGVs; and (ii mixed effects models including also a Gaussian random field (GRF to model spatial correlation (Matérn covariance function. To estimate the potential distribution of Pittosporum undulatum and Morella faya (respectively, invasive and native trees, we used geo-referenced data of their distribution in Pico and São Miguel islands (Azores and topographic, climatic and land use EGVs. Fixed effects models run with maximum likelihood or the INLA (Integrated Nested Laplace Approximation approach provided very similar results, even when reducing the size of the presences data set. The addition of the GRF increased model adjustment (lower Deviance Information Criterion, particularly for the less abundant tree, M. faya. However, the random field parameters were clearly affected by sample size and species distribution pattern. A high degree of spatial autocorrelation was found and should be taken into account when modeling species distribution.

Bias correction in species distribution models: pooling survey and collection data for multiple species.

Science.gov (United States)

Fithian, William; Elith, Jane; Hastie, Trevor; Keith, David A

2015-04-01

Presence-only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically haphazard collection schemes. Presence-absence or count data collected in systematic, planned surveys are more reliable but typically less abundant.We proposed a probabilistic model to allow for joint analysis of presence-only and survey data to exploit their complementary strengths. Our method pools presence-only and presence-absence data for many species and maximizes a joint likelihood, simultaneously estimating and adjusting for the sampling bias affecting the presence-only data. By assuming that the sampling bias is the same for all species, we can borrow strength across species to efficiently estimate the bias and improve our inference from presence-only data.We evaluate our model's performance on data for 36 eucalypt species in south-eastern Australia. We find that presence-only records exhibit a strong sampling bias towards the coast and towards Sydney, the largest city. Our data-pooling technique substantially improves the out-of-sample predictive performance of our model when the amount of available presence-absence data for a given species is scarceIf we have only presence-only data and no presence-absence data for a given species, but both types of data for several other species that suffer from the same spatial sampling bias, then our method can obtain an unbiased estimate of the first species' geographic range.

Experimental Models of Vaginal Candidiasis and Their Relevance to Human Candidiasis

Science.gov (United States)

Sobel, Jack D.

2016-01-01

Vulvovaginal candidiasis (VVC) is a high-incidence disease seriously affecting the quality of life of women worldwide, particularly in its chronic, recurrent forms (RVVC), and with no definitive cure or preventive measure. Experimental studies in currently used rat and mouse models of vaginal candidiasis have generated a large mass of data on pathogenicity determinants and inflammation and immune responses of potential importance for the control of human pathology. However, reflection is necessary about the relevance of these rodent models to RVVC. Here we examine the chemical, biochemical, and biological factors that determine or contrast the forms of the disease in rodent models and in women and highlight the differences between them. We also appeal for approaches to improve or replace the current models in order to enhance their relevance to human infection. PMID:26883592

High-resolution assessment of land use impacts on biodiversity in life cycle assessment using species habitat suitability models.

Science.gov (United States)

de Baan, Laura; Curran, Michael; Rondinini, Carlo; Visconti, Piero; Hellweg, Stefanie; Koellner, Thomas

2015-02-17

Agricultural land use is a main driver of global biodiversity loss. The assessment of land use impacts in decision-support tools such as life cycle assessment (LCA) requires spatially explicit models, but existing approaches are either not spatially differentiated or modeled at very coarse scales (e.g., biomes or ecoregions). In this paper, we develop a high-resolution (900 m) assessment method for land use impacts on biodiversity based on habitat suitability models (HSM) of mammal species. This method considers potential land use effects on individual species, and impacts are weighted by the species' conservation status and global rarity. We illustrate the method using a case study of crop production in East Africa, but the underlying HSMs developed by the Global Mammals Assessment are available globally. We calculate impacts of three major export crops and compare the results to two previously developed methods (focusing on local and regional impacts, respectively) to assess the relevance of the methodological innovations proposed in this paper. The results highlight hotspots of product-related biodiversity impacts that help characterize the links among agricultural production, consumption, and biodiversity loss.

Habitat or matrix: which is more relevant to predict road-kill of vertebrates?

OpenAIRE

Bueno,C.; Sousa,C. O. M.; Freitas,S. R.

2015-01-01

Abstract We believe that in tropics we need a community approach to evaluate road impacts on wildlife, and thus, suggest mitigation measures for groups of species instead a focal-species approach. Understanding which landscape characteristics indicate road-kill events may also provide models that can be applied in other regions. We intend to evaluate if habitat or matrix is more relevant to predict road-kill events for a group of species. Our hypothesis is: more permeable matrix is the most r...

Species-free species distribution models describe macroecological properties of protected area networks.

Science.gov (United States)

Robinson, Jason L; Fordyce, James A

2017-01-01

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have

Spectroscopic Properties of Tc(I) Tricarbonyl Species Relevant to the Hanford Tank Waste

Energy Technology Data Exchange (ETDEWEB)

Levitskaia, Tatiana G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Andersen, Amity [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chatterjee, Sayandev [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hall, Gabriel B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Walter, Eric D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Washton, Nancy M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-12-04

Technetium-99 (Tc) exists predominately in soluble forms in the liquid supernatant and salt cake fractions of the nuclear tank waste stored at the U.S. DOE Hanford Site. In the strongly alkaline environments prevalent in the tank waste, its dominant chemical form is pertechnetate (TcO4-, oxidation state +7). However, attempts to remove Tc from the Hanford tank waste using ion-exchange processes specific to TcO₄^- only met with limited success, particularly processing tank waste samples containing elevated concentrations of organic complexants. This suggests that a significant fraction of the soluble Tc can be present as non-pertechnetate low-valent Tc (oxidation state < +7) (non-pertechnetate). The chemical identities of these non-pertechnetate species are poorly understood. Previous analysis of the SY-101 and SY-103 tank waste samples provided strong evidence that non-pertechnetate can be comprised of [Tc(CO)₃]⁺ complexes containing Tc in oxidation state +1 (Lukens et al. 2004). During the last two years, our team has expanded this work and demonstrated that high-ionic-strength solutions typifying tank waste supernatants promote oxidative stability of the [Tc(CO)₃]⁺ species (Rapko et al. 2013; Levitskaia et al. 2014). It also was observed that high-ionic-strength alkaline matrices stabilize Tc(VI) and potentially Tc(IV) oxidation states, particularly in presence organic chelators, suggesting that the relevant Tc compounds can serve as important redox intermediates facilitating the reduction of Tc(VII) to Tc(I). Designing strategies for effective Tc processing, including separation and immobilization, necessitates understanding the molecular structure of these non-pertechnetate species and their identification in the actual tank waste samples. To-date, only limited information exists regarding the nature and characterization of the Tc(I), Tc(IV), and Tc(VI) species. One objective of this project is to

Towards Increased Relevance: Context-Adapted Models of the Learning Organization

Science.gov (United States)

Örtenblad, Anders

2015-01-01

Purpose: The purposes of this paper are to take a closer look at the relevance of the idea of the learning organization for organizations in different generalized organizational contexts; to open up for the existence of multiple, context-adapted models of the learning organization; and to suggest a number of such models.…

Thermochemical data for environmentally-relevant elements

International Nuclear Information System (INIS)

Markich, S.J.; Brown, P.L.

1999-01-01

This study provides an extensive stability constant (log K) database suitable for calculating the speciation of selected environmentally-relevant elements (H, Na, K, Ca, Mg, Fe, Mn, U, Al Pb, Zn, Cu and cd) in an aqueous system, where a model fulvic acid (comprising aspartic, citric, malonic, salicylic and tricarballylic acids) is used to simulate metal binding by dissolved organic material Stability constants for inorganic metal complexes and minerals were selected primarily from critical literature complications and/or reviews. In contrast, few critically evaluated data were available for metal complexes with aspartic, citric, malonic, salicylic and tricarballylic acids. Consequently, data from original research articles were carefully evaluated and compiled as part of the study, following defined selection criteria. to meet the objective of compiling a comprehensive and reliable database of stability constants, all relevant equilibria and species, ranging from simple binary metal complexes to more complex ternary and even quaternary, metal complexes were included where possible in addition to the selection of stability constants from empirical sources, estimates of stability constants were performed when this could be done reliably, based on the unified theory of metal ion complexation and/or linear tree energy relationships The stability constants are given as common logarithms (logo) in the form required by the HARPHRQ geochemical code and refer to the standard state, i.e 298.15 K (25 deg C), 10 5 Pa (1 atm) and, for all species, infinite dilution (ionic strength = 0 mol L -1 ). In addition to the compilation of stability constant data, an overview is given of geochemical speciation modelling in aqueous systems and available conceptual models of metal binding by humic substances. (authors)

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

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Conor P. McGowan

2017-10-01

Full Text Available Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises in transparent and explicit ways tailored to support decision making processes related to endangered species.

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Science.gov (United States)

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

2017-01-01

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Endangered species toxicity extrapolation using ICE models

Science.gov (United States)

The National Research Council’s (NRC) report on assessing pesticide risks to threatened and endangered species (T&E) included the recommendation of using interspecies correlation models (ICE) as an alternative to general safety factors for extrapolating across species. ...

Embryonic and larval development in the Midas cichlid fish species flock (Amphilophus spp.): a new evo-devo model for the investigation of adaptive novelties and species differences.

Science.gov (United States)

Kratochwil, Claudius F; Sefton, Maggie M; Meyer, Axel

2015-02-26

Central American crater lake cichlid fish of the Midas species complex (Amphilophus spp.) are a model system for sympatric speciation and fast ecological diversification and specialization. Midas cichlids have been intensively analyzed from an ecological and morphological perspective. Genomic resources such as transcriptomic and genomic data sets, and a high-quality draft genome are available now. Many ecologically relevant species-specific traits and differences such as pigmentation and cranial morphology arise during development. Detailed descriptions of the early development of the Midas cichlid in particular, will help to investigate the ontogeny of species differences and adaptations. We describe the embryonic and larval development of the crater lake cichlid, Amphilophus xiloaensis, until seven days after fertilization. Similar to previous studies on teleost development, we describe six periods of embryogenesis - the zygote, cleavage, blastula, gastrula, segmentation, and post-hatching period. Furthermore, we define homologous stages to well-described teleost models such as medaka and zebrafish, as well as other cichlid species such as the Nile tilapia and the South American cichlid Cichlasoma dimerus. Key morphological differences between the embryos of Midas cichlids and other teleosts are highlighted and discussed, including the presence of adhesive glands and different early chromatophore patterns, as well as variation in developmental timing. The developmental staging of the Midas cichlid will aid researchers in the comparative investigation of teleost ontogenies. It will facilitate comparative developmental biological studies of Neotropical and African cichlid fish in particular. In the past, the species flocks of the African Great Lakes have received the most attention from researchers, but some lineages of the 300-400 species of Central American lakes are fascinating model systems for adaptive radiation and rapid phenotypic evolution. The availability

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

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Brian W. Miller

2015-05-01

Full Text Available State-and-transition simulation models (STSMs are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM. SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis. We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae, and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

Impact of plasma jet vacuum ultraviolet radiation on reactive oxygen species generation in bio-relevant liquids

Energy Technology Data Exchange (ETDEWEB)

Jablonowski, H.; Hammer, M. U.; Reuter, S. [Center for Innovation Competence plasmatis, Felix-Hausdorff-Str. 2, 17489 Greifswald (Germany); Leibniz Institute for Plasma Science and Technology, INP Greifswald e.V. Felix-Hausdorff-Str. 2, 17489 Greifswald (Germany); Bussiahn, R.; Weltmann, K.-D.; Woedtke, Th. von [Leibniz Institute for Plasma Science and Technology, INP Greifswald e.V. Felix-Hausdorff-Str. 2, 17489 Greifswald (Germany)

2015-12-15

Plasma medicine utilizes the combined interaction of plasma produced reactive components. These are reactive atoms, molecules, ions, metastable species, and radiation. Here, ultraviolet (UV, 100–400 nm) and, in particular, vacuum ultraviolet (VUV, 10–200 nm) radiation generated by an atmospheric pressure argon plasma jet were investigated regarding plasma emission, absorption in a humidified atmosphere and in solutions relevant for plasma medicine. The energy absorption was obtained for simple solutions like distilled water (dH{sub 2}O) or ultrapure water and sodium chloride (NaCl) solution as well as for more complex ones, for example, Rosewell Park Memorial Institute (RPMI 1640) cell culture media. As moderate stable reactive oxygen species, hydrogen peroxide (H{sub 2}O{sub 2}) was studied. Highly reactive oxygen radicals, namely, superoxide anion (O{sub 2}{sup •−}) and hydroxyl radicals ({sup •}OH), were investigated by the use of electron paramagnetic resonance spectroscopy. All species amounts were detected for three different treatment cases: Plasma jet generated VUV and UV radiation, plasma jet generated UV radiation without VUV part, and complete plasma jet including all reactive components additionally to VUV and UV radiation. It was found that a considerable amount of radicals are generated by the plasma generated photoemission. From the experiments, estimation on the low hazard potential of plasma generated VUV radiation is discussed.

Using consensus bayesian network to model the reactive oxygen species regulatory pathway.

Directory of Open Access Journals (Sweden)

Liangdong Hu

Full Text Available Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the bayesian network from microarray data directly. Although large numbers of bayesian network learning algorithms have been developed, when applying them to learn bayesian networks from microarray data, the accuracies are low due to that the databases they used to learn bayesian networks contain too few microarray data. In this paper, we propose a consensus bayesian network which is constructed by combining bayesian networks from relevant literatures and bayesian networks learned from microarray data. It would have a higher accuracy than the bayesian networks learned from one database. In the experiment, we validated the bayesian network combination algorithm on several classic machine learning databases and used the consensus bayesian network to model the Escherichia coli's ROS pathway.

Bioprinting towards Physiologically Relevant Tissue Models for Pharmaceutics.

Science.gov (United States)

Peng, Weijie; Unutmaz, Derya; Ozbolat, Ibrahim T

2016-09-01

Improving the ability to predict the efficacy and toxicity of drug candidates earlier in the drug discovery process will speed up the introduction of new drugs into clinics. 3D in vitro systems have significantly advanced the drug screening process as 3D tissue models can closely mimic native tissues and, in some cases, the physiological response to drugs. Among various in vitro systems, bioprinting is a highly promising technology possessing several advantages such as tailored microarchitecture, high-throughput capability, coculture ability, and low risk of cross-contamination. In this opinion article, we discuss the currently available tissue models in pharmaceutics along with their limitations and highlight the possibilities of bioprinting physiologically relevant tissue models, which hold great potential in drug testing, high-throughput screening, and disease modeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Finessing atlas data for species distribution models

NARCIS (Netherlands)

Niamir, A.; Skidmore, A.K.; Toxopeus, A.G.; Munoz, A.R.; Real, R.

2011-01-01

Aim The spatial resolution of species atlases and therefore resulting model predictions are often too coarse for local applications. Collecting distribution data at a finer resolution for large numbers of species requires a comprehensive sampling effort, making it impractical and expensive. This

Regional climate model downscaling may improve the prediction of alien plant species distributions

Science.gov (United States)

Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

2014-12-01

Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Science.gov (United States)

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-02-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally

Models of the Economic Growth and their Relevance

Directory of Open Access Journals (Sweden)

Nicolae MOROIANU

2012-06-01

Full Text Available Until few years ago, the economic growth was something perfect normal, part of an era marked by the transformation speed. Normality itself has been transformed and we currently are influenced by other rules, unknown yet, which should answer the question: “How do we return to the economic growth?” The economic growth and the models aiming to solve this problem concern the economic history even since its beginnings. In this paper we would like to find out what is the relevance that the well-known macroeconomic models still have and which might be their applicability level in a framework created by a black swan event type.

Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts.

Science.gov (United States)

Bellamy, Chloe; Altringham, John

2015-01-01

Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m - 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the

Modelling survival: exposure pattern, species sensitivity and uncertainty.

Science.gov (United States)

Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

2016-07-06

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Development and application of two independent real-time PCR assays to detect clinically relevant Mucorales species.

Science.gov (United States)

Springer, Jan; Goldenberger, Daniel; Schmidt, Friderike; Weisser, Maja; Wehrle-Wieland, Elisabeth; Einsele, Hermann; Frei, Reno; Löffler, Jürgen

2016-03-01

PCR-based detection of Mucorales species could improve diagnosis of suspected invasive fungal infection, leading to a better patient outcome. This study describes two independent probe-based real-time PCR tests for detection of clinically relevant Mucorales, targeting specific fragments of the 18S and the 28S rRNA genes. Both assays have a short turnaround time, allow fast, specific and very sensitive detection of clinically relevant Mucorales and have the potential to be used as quantitative tests. They were validated on various clinical samples (fresh and formalin-fixed paraffin-embedded specimens, mainly biopsies, n = 17). The assays should be used as add-on tools to complement standard techniques; a combined approach of both real-time PCR assays has 100 % sensitivity. Genus identification by subsequent sequencing is possible for amplicons of the 18S PCR assay. In conclusion, combination of the two independent Mucorales assays described in this study, 18S and 28S, detected all clinical samples associated with proven Mucorales infection (n = 10). Reliable and specific identification of Mucorales is a prerequisite for successful antifungal therapy as these fungi show intrinsic resistance to voriconazole and caspofungin.

Control-relevant modeling and simulation of a SOFC-GT hybrid system

OpenAIRE

Rambabu Kandepu; Lars Imsland; Christoph Stiller; Bjarne A. Foss; Vinay Kariwala

2006-01-01

In this paper, control-relevant models of the most important components in a SOFC-GT hybrid system are described. Dynamic simulations are performed on the overall hybrid system. The model is used to develop a simple control structure, but the simulations show that more elaborate control is needed.

Theoretical microbial ecology without species

Science.gov (United States)

Tikhonov, Mikhail

2017-09-01

Ecosystems are commonly conceptualized as networks of interacting species. However, partitioning natural diversity of organisms into discrete units is notoriously problematic and mounting experimental evidence raises the intriguing question whether this perspective is appropriate for the microbial world. Here an alternative formalism is proposed that does not require postulating the existence of species as fundamental ecological variables and provides a naturally hierarchical description of community dynamics. This formalism allows approaching the species problem from the opposite direction. While the classical models treat a world of imperfectly clustered organism types as a perturbation around well-clustered species, the presented approach allows gradually adding structure to a fully disordered background. The relevance of this theoretical construct for describing highly diverse natural ecosystems is discussed.

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry for fast and accurate identification of clinically relevant Aspergillus species.

Science.gov (United States)

Alanio, A; Beretti, J-L; Dauphin, B; Mellado, E; Quesne, G; Lacroix, C; Amara, A; Berche, P; Nassif, X; Bougnoux, M-E

2011-05-01

New Aspergillus species have recently been described with the use of multilocus sequencing in refractory cases of invasive aspergillosis. The classical phenotypic identification methods routinely used in clinical laboratories failed to identify them adequately. Some of these Aspergillus species have specific patterns of susceptibility to antifungal agents, and misidentification may lead to inappropriate therapy. We developed a matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)-based strategy to adequately identify Aspergillus species to the species level. A database including the reference spectra of 28 clinically relevant species from seven Aspergillus sections (five common and 23 unusual species) was engineered. The profiles of young and mature colonies were analysed for each reference strain, and species-specific spectral fingerprints were identified. The performance of the database was then tested on 124 clinical and 16 environmental isolates previously characterized by partial sequencing of the β-tubulin and calmodulin genes. One hundred and thirty-eight isolates of 140 (98.6%) were correctly identified. Two atypical isolates could not be identified, but no isolate was misidentified (specificity: 100%). The database, including species-specific spectral fingerprints of young and mature colonies of the reference strains, allowed identification regardless of the maturity of the clinical isolate. These results indicate that MALDI-TOF MS is a powerful tool for rapid and accurate identification of both common and unusual species of Aspergillus. It can give better results than morphological identification in clinical laboratories. © 2010 The Authors. Clinical Microbiology and Infection © 2010 European Society of Clinical Microbiology and Infectious Diseases.

Predicting weed problems in maize cropping by species distribution modelling

Directory of Open Access Journals (Sweden)

Bürger, Jana

2014-02-01

Full Text Available Increasing maize cultivation and changed cropping practices promote the selection of typical maize weeds that may also profit strongly from climate change. Predicting potential weed problems is of high interest for plant production. Within the project KLIFF, experiments were combined with species distribution modelling for this task in the region of Lower Saxony, Germany. For our study, we modelled ecological and damage niches of nine weed species that are significant and wide spread in maize cropping in a number of European countries. Species distribution models describe the ecological niche of a species, these are the environmental conditions under which a species can maintain a vital population. It is also possible to estimate a damage niche, i.e. the conditions under which a species causes damage in agricultural crops. For this, we combined occurrence data of European national data bases with high resolution climate, soil and land use data. Models were also projected to simulated climate conditions for the time horizon 2070 - 2100 in order to estimate climate change effects. Modelling results indicate favourable conditions for typical maize weed occurrence virtually all over the study region, but only a few species are important in maize cropping. This is in good accordance with the findings of an earlier maize weed monitoring. Reaction to changing climate conditions is species-specific, for some species neutral (E. crus-galli, other species may gain (Polygonum persicaria or loose (Viola arvensis large areas of suitable habitats. All species with damage potential under present conditions will remain important in maize cropping, some more species will gain regional importance (Calystegia sepium, Setara viridis.

A Peep into the Uncertainty-Complexity-Relevance Modeling Trilemma through Global Sensitivity and Uncertainty Analysis

Science.gov (United States)

Munoz-Carpena, R.; Muller, S. J.; Chu, M.; Kiker, G. A.; Perz, S. G.

2014-12-01

Model Model complexity resulting from the need to integrate environmental system components cannot be understated. In particular, additional emphasis is urgently needed on rational approaches to guide decision making through uncertainties surrounding the integrated system across decision-relevant scales. However, in spite of the difficulties that the consideration of modeling uncertainty represent for the decision process, it should not be avoided or the value and science behind the models will be undermined. These two issues; i.e., the need for coupled models that can answer the pertinent questions and the need for models that do so with sufficient certainty, are the key indicators of a model's relevance. Model relevance is inextricably linked with model complexity. Although model complexity has advanced greatly in recent years there has been little work to rigorously characterize the threshold of relevance in integrated and complex models. Formally assessing the relevance of the model in the face of increasing complexity would be valuable because there is growing unease among developers and users of complex models about the cumulative effects of various sources of uncertainty on model outputs. In particular, this issue has prompted doubt over whether the considerable effort going into further elaborating complex models will in fact yield the expected payback. New approaches have been proposed recently to evaluate the uncertainty-complexity-relevance modeling trilemma (Muller, Muñoz-Carpena and Kiker, 2011) by incorporating state-of-the-art global sensitivity and uncertainty analysis (GSA/UA) in every step of the model development so as to quantify not only the uncertainty introduced by the addition of new environmental components, but the effect that these new components have over existing components (interactions, non-linear responses). Outputs from the analysis can also be used to quantify system resilience (stability, alternative states, thresholds or tipping

The Combined Use of Correlative and Mechanistic Species Distribution Models Benefits Low Conservation Status Species.

Directory of Open Access Journals (Sweden)

Thibaud Rougier

Full Text Available Species can respond to climate change by tracking appropriate environmental conditions in space, resulting in a range shift. Species Distribution Models (SDMs can help forecast such range shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa, an endangered anadromous fish species, is one of them. The main purpose of this study was to provide a framework for joint analyses of correlative and mechanistic SDMs projections in order to strengthen conservation measures for species of conservation concern. Guidelines for joint representation and subsequent interpretation of models outputs were defined and applied. The present joint analysis was based on the novel mechanistic model GR3D (Global Repositioning Dynamics of Diadromous fish Distribution which was parameterized on allis shad and then used to predict its future distribution along the European Atlantic coast under different climate change scenarios (RCP 4.5 and RCP 8.5. We then used a correlative SDM for this species to forecast its distribution across the same geographic area and under the same climate change scenarios. First, projections from correlative and mechanistic models provided congruent trends in probability of habitat suitability and population dynamics. This agreement was preferentially interpreted as referring to the species vulnerability to climate change. Climate change could not be accordingly listed as a major threat for allis shad. The congruence in predicted range limits between SDMs projections was the next point of interest. The difference, when noticed, required to deepen our understanding of the niche modelled by each approach. In this respect, the relative position of the northern range limit between the two methods strongly suggested here that a key biological process related to intraspecific variability was potentially lacking in the mechanistic SDM. Based on our knowledge, we hypothesized that local

Exploring internal features of 16S rRNA gene for identification of clinically relevant species of the genus Streptococcus

Science.gov (United States)

2011-01-01

Background Streptococcus is an economically important genus as a number of species belonging to this genus are human and animal pathogens. The genus has been divided into different groups based on 16S rRNA gene sequence similarity. The variability observed among the members of these groups is low and it is difficult to distinguish them. The present study was taken up to explore 16S rRNA gene sequence to develop methods that can be used for preliminary identification and can supplement the existing methods for identification of clinically-relevant isolates of the genus Streptococcus. Methods 16S rRNA gene sequences belonging to the isolates of S. dysgalactiae, S. equi, S. pyogenes, S. agalactiae, S. bovis, S. gallolyticus, S. mutans, S. sobrinus, S. mitis, S. pneumoniae, S. thermophilus and S. anginosus were analyzed with the purpose to define genetic variability within each species to generate a phylogenetic framework, to identify species-specific signatures and in-silico restriction enzyme analysis. Results The framework based analysis was used to segregate Streptococcus spp. previously identified upto genus level. This segregation was validated using species-specific signatures and in-silico restriction enzyme analysis. 43 uncharacterized Streptococcus spp. could be identified using this approach. Conclusions The markers generated exploring 16S rRNA gene sequences provided useful tool that can be further used for identification of different species of the genus Streptococcus. PMID:21702978

Control-relevant modeling and simulation of a SOFC-GT hybrid system

Directory of Open Access Journals (Sweden)

Rambabu Kandepu

2006-07-01

Full Text Available In this paper, control-relevant models of the most important components in a SOFC-GT hybrid system are described. Dynamic simulations are performed on the overall hybrid system. The model is used to develop a simple control structure, but the simulations show that more elaborate control is needed.

Molluscan indicator species and their potential use in ecological status assessment using species distribution modeling.

Science.gov (United States)

Moraitis, Manos L; Tsikopoulou, Irini; Geropoulos, Antonios; Dimitriou, Panagiotis D; Papageorgiou, Nafsika; Giannoulaki, Marianna; Valavanis, Vasilis D; Karakassis, Ioannis

2018-05-24

Marine habitat assessment using indicator species through Species Distribution Modeling (SDM) was investigated. The bivalves: Corbula gibba and Flexopecten hyalinus were the indicator species characterizing disturbed and undisturbed areas respectively in terms of chlorophyll a concentration in Greece. The habitat suitability maps of these species reflected the overall ecological status of the area. The C. gibba model successfully predicted the occurrence of this species in areas with increased physical disturbance driven by chlorophyll a concentration, whereas the habitat map for F. hyalinus showed an increased probability of occurrence in chlorophyll-poor areas, affected mainly by salinity. We advocate the use of C. gibba as a proxy for eutrophication and the incorporation of this species in monitoring studies through SDM methods. For the Mediterranean Sea we suggest the use of F. hyalinus in SDM as an indicator of environmental stability and a possible forecasting tool for salinity fluctuations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Using habitat suitability models to target invasive plant species surveys.

Science.gov (United States)

Crall, Alycia W; Jarnevich, Catherine S; Panke, Brendon; Young, Nick; Renz, Mark; Morisette, Jeffrey

2013-01-01

Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P guiding invasive species monitoring, and we support the use of an iterative sampling design for

CARBON-CHAIN SPECIES IN WARM-UP MODELS

International Nuclear Information System (INIS)

Hassel, George E.; Harada, Nanase; Herbst, Eric

2011-01-01

In previous warm-up chemical models of the low-mass star-forming region L1527, we investigated the evolution of carbon-chain unsaturated hydrocarbon species when the envelope temperature is slightly elevated to T ≈ 30 K. These models demonstrated that enhanced abundances of such species can be explained by gas-phase ion-molecule chemistry following the partial sublimation of methane from grain surfaces. We also concluded that the abundances of hydrocarbon radicals such as the C n H family should be further enhanced as the temperatures increase to higher values, but this conclusion stood in contrast with the lack of unambiguous detection of these species toward hot core and corino sources. Meanwhile, observational surveys have identified C 2 H, C 4 H, CH 3 CCH, and CH 3 OH toward hot corinos (especially IRAS 16293–2422) as well as toward L1527, with lower abundances for the carbon-chain radicals and higher abundances for the other two species toward the hot corinos. In addition, the Herschel Space Telescope has detected the bare linear chain C 3 in 50 K material surrounding young high-mass stellar objects. To understand these new results, we revisit previous warm-up models with an augmented gas-grain network that incorporated reactions from a gas-phase network that was constructed for use with increased temperature up to 800 K. Some of the newly adopted reactions between carbon-chain species and abundant H 2 possess chemical activation energy barriers. The revised model results now better reproduce the observed abundances of unsaturated carbon chains under hot corino (100 K) conditions and make predictions for the abundances of bare carbon chains in the 50 K regions observed by the Herschel HIFI detector.

Species Distribution Modelling: Contrasting presence-only models with plot abundance data.

Science.gov (United States)

Gomes, Vitor H F; IJff, Stéphanie D; Raes, Niels; Amaral, Iêda Leão; Salomão, Rafael P; de Souza Coelho, Luiz; de Almeida Matos, Francisca Dionízia; Castilho, Carolina V; de Andrade Lima Filho, Diogenes; López, Dairon Cárdenas; Guevara, Juan Ernesto; Magnusson, William E; Phillips, Oliver L; Wittmann, Florian; de Jesus Veiga Carim, Marcelo; Martins, Maria Pires; Irume, Mariana Victória; Sabatier, Daniel; Molino, Jean-François; Bánki, Olaf S; da Silva Guimarães, José Renan; Pitman, Nigel C A; Piedade, Maria Teresa Fernandez; Mendoza, Abel Monteagudo; Luize, Bruno Garcia; Venticinque, Eduardo Martins; de Leão Novo, Evlyn Márcia Moraes; Vargas, Percy Núñez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S; Marimon, Ben-Hur; Coronado, Euridice N Honorio; Feldpausch, Ted R; Duque, Alvaro; Zartman, Charles Eugene; Arboleda, Nicolás Castaño; Killeen, Timothy J; Mostacedo, Bonifacio; Vasquez, Rodolfo; Schöngart, Jochen; Assis, Rafael L; Medeiros, Marcelo Brilhante; Simon, Marcelo Fragomeni; Andrade, Ana; Laurance, William F; Camargo, José Luís; Demarchi, Layon O; Laurance, Susan G W; de Sousa Farias, Emanuelle; Nascimento, Henrique Eduardo Mendonça; Revilla, Juan David Cardenas; Quaresma, Adriano; Costa, Flavia R C; Vieira, Ima Célia Guimarães; Cintra, Bruno Barçante Ladvocat; Castellanos, Hernán; Brienen, Roel; Stevenson, Pablo R; Feitosa, Yuri; Duivenvoorden, Joost F; Aymard C, Gerardo A; Mogollón, Hugo F; Targhetta, Natalia; Comiskey, James A; Vicentini, Alberto; Lopes, Aline; Damasco, Gabriel; Dávila, Nállarett; García-Villacorta, Roosevelt; Levis, Carolina; Schietti, Juliana; Souza, Priscila; Emilio, Thaise; Alonso, Alfonso; Neill, David; Dallmeier, Francisco; Ferreira, Leandro Valle; Araujo-Murakami, Alejandro; Praia, Daniel; do Amaral, Dário Dantas; Carvalho, Fernanda Antunes; de Souza, Fernanda Coelho; Feeley, Kenneth; Arroyo, Luzmila; Pansonato, Marcelo Petratti; Gribel, Rogerio; Villa, Boris; Licona, Juan Carlos; Fine, Paul V A; Cerón, Carlos; Baraloto, Chris; Jimenez, Eliana M; Stropp, Juliana; Engel, Julien; Silveira, Marcos; Mora, Maria Cristina Peñuela; Petronelli, Pascal; Maas, Paul; Thomas-Caesar, Raquel; Henkel, Terry W; Daly, Doug; Paredes, Marcos Ríos; Baker, Tim R; Fuentes, Alfredo; Peres, Carlos A; Chave, Jerome; Pena, Jose Luis Marcelo; Dexter, Kyle G; Silman, Miles R; Jørgensen, Peter Møller; Pennington, Toby; Di Fiore, Anthony; Valverde, Fernando Cornejo; Phillips, Juan Fernando; Rivas-Torres, Gonzalo; von Hildebrand, Patricio; van Andel, Tinde R; Ruschel, Ademir R; Prieto, Adriana; Rudas, Agustín; Hoffman, Bruce; Vela, César I A; Barbosa, Edelcilio Marques; Zent, Egleé L; Gonzales, George Pepe Gallardo; Doza, Hilda Paulette Dávila; de Andrade Miranda, Ires Paula; Guillaumet, Jean-Louis; Pinto, Linder Felipe Mozombite; de Matos Bonates, Luiz Carlos; Silva, Natalino; Gómez, Ricardo Zárate; Zent, Stanford; Gonzales, Therany; Vos, Vincent A; Malhi, Yadvinder; Oliveira, Alexandre A; Cano, Angela; Albuquerque, Bianca Weiss; Vriesendorp, Corine; Correa, Diego Felipe; Torre, Emilio Vilanova; van der Heijden, Geertje; Ramirez-Angulo, Hirma; Ramos, José Ferreira; Young, Kenneth R; Rocha, Maira; Nascimento, Marcelo Trindade; Medina, Maria Natalia Umaña; Tirado, Milton; Wang, Ophelia; Sierra, Rodrigo; Torres-Lezama, Armando; Mendoza, Casimiro; Ferreira, Cid; Baider, Cláudia; Villarroel, Daniel; Balslev, Henrik; Mesones, Italo; Giraldo, Ligia Estela Urrego; Casas, Luisa Fernanda; Reategui, Manuel Augusto Ahuite; Linares-Palomino, Reynaldo; Zagt, Roderick; Cárdenas, Sasha; Farfan-Rios, William; Sampaio, Adeilza Felipe; Pauletto, Daniela; Sandoval, Elvis H Valderrama; Arevalo, Freddy Ramirez; Huamantupa-Chuquimaco, Isau; Garcia-Cabrera, Karina; Hernandez, Lionel; Gamarra, Luis Valenzuela; Alexiades, Miguel N; Pansini, Susamar; Cuenca, Walter Palacios; Milliken, William; Ricardo, Joana; Lopez-Gonzalez, Gabriela; Pos, Edwin; Ter Steege, Hans

2018-01-17

Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.

Campylobacter species in animal, food, and environmental sources, and relevant testing programs in Canada.

Science.gov (United States)

Huang, Hongsheng; Brooks, Brian W; Lowman, Ruff; Carrillo, Catherine D

2015-10-01

Campylobacter species, particularly thermophilic campylobacters, have emerged as a leading cause of human foodborne gastroenteritis worldwide, with Campylobacter jejuni, Campylobacter coli, and Campylobacter lari responsible for the majority of human infections. Although most cases of campylobacteriosis are self-limiting, campylobacteriosis represents a significant public health burden. Human illness caused by infection with campylobacters has been reported across Canada since the early 1970s. Many studies have shown that dietary sources, including food, particularly raw poultry and other meat products, raw milk, and contaminated water, have contributed to outbreaks of campylobacteriosis in Canada. Campylobacter spp. have also been detected in a wide range of animal and environmental sources, including water, in Canada. The purpose of this article is to review (i) the prevalence of Campylobacter spp. in animals, food, and the environment, and (ii) the relevant testing programs in Canada with a focus on the potential links between campylobacters and human health in Canada.

Oxidative Stability of Tc(I) Tricarbonyl Species Relevant to the Hanford Tank Waste

Energy Technology Data Exchange (ETDEWEB)

Chatterjee, Sayandev [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hall, Gabriel B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Levitskaia, Tatiana G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Walter, Eric D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Washton, Nancy M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-12-17

Technetium (Tc), which exists predominately in the liquid supernatant and salt cake fractions of the nuclear tank waste stored at the U.S. DOE Hanford Site, is one of the most difficult contaminants to dispose of and/or remediate. In the strongly alkaline environments prevalent in the tank waste, its dominant chemical form is pertechnetate (TcO₄^-, oxidation state +7). However, based on experimentation to-date, a significant fraction of the soluble Tc cannot be effectively separated from the wastes and may be present as a non-pertechnetate species. The presence of a non pertechnetate species significantly complicates disposition of low-activity waste (LAW), and the development of methods to either convert them to pertechnetate or to separate the non-pertechnetate species directly is needed. The challenge is the uncertainty regarding the nature and stability of the alkaline-soluble, low-valence, non pertechnetate species in the liquid tank waste. One objective of the Tc management project is to address this knowledge gap. This fiscal year (FY) 2015 report summarizes experimental work exploring the oxidative stability of model low-valence Tc(I) tricarbonyl species, derived from the [Tc(CO)₃]⁺ moiety. These compounds are of interest due to their implied presence in several Hanford tank waste supernatants. Work in part was initiated in FY 2014, and a series of samples containing non-pertechnetate Tc generated ex situ or in situ in pseudo-Hanford tank supernatant simulant solutions was prepared and monitored for oxidation to Tc(VII) (Levitskaia et al. 2014). This experimentation continued in FY 2015, and new series of samples containing Tc(I) as [Tc(CO)₃]⁺•Ligand was tested. The monitoring method used for these studies was a combination of ⁹⁹Tc NMR and EPR spectroscopies.

SESAM – a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

DEFF Research Database (Denmark)

Guisan, Antoine; Rahbek, Carsten

2011-01-01

Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realized properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts...

Incorporating uncertainty in predictive species distribution modelling.

Science.gov (United States)

Beale, Colin M; Lennon, Jack J

2012-01-19

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

Deriving field-based species sensitivity distributions (f-SSDs) from stacked species distribution models (S-SDMs).

Science.gov (United States)

Schipper, Aafke M; Posthuma, Leo; de Zwart, Dick; Huijbregts, Mark A J

2014-12-16

Quantitative relationships between species richness and single environmental factors, also called species sensitivity distributions (SSDs), are helpful to understand and predict biodiversity patterns, identify environmental management options and set environmental quality standards. However, species richness is typically dependent on a variety of environmental factors, implying that it is not straightforward to quantify SSDs from field monitoring data. Here, we present a novel and flexible approach to solve this, based on the method of stacked species distribution modeling. First, a species distribution model (SDM) is established for each species, describing its probability of occurrence in relation to multiple environmental factors. Next, the predictions of the SDMs are stacked along the gradient of each environmental factor with the remaining environmental factors at fixed levels. By varying those fixed levels, our approach can be used to investigate how field-based SSDs for a given environmental factor change in relation to changing confounding influences, including for example optimal, typical, or extreme environmental conditions. This provides an asset in the evaluation of potential management measures to reach good ecological status.

Sample sizes and model comparison metrics for species distribution models

Science.gov (United States)

B.B. Hanberry; H.S. He; D.C. Dey

2012-01-01

Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....

The relevance of non-human primate and rodent malaria models for humans

Directory of Open Access Journals (Sweden)

Riley Eleanor

2011-02-01

Full Text Available Abstract At the 2010 Keystone Symposium on "Malaria: new approaches to understanding Host-Parasite interactions", an extra scientific session to discuss animal models in malaria research was convened at the request of participants. This was prompted by the concern of investigators that skepticism in the malaria community about the use and relevance of animal models, particularly rodent models of severe malaria, has impacted on funding decisions and publication of research using animal models. Several speakers took the opportunity to demonstrate the similarities between findings in rodent models and human severe disease, as well as points of difference. The variety of malaria presentations in the different experimental models parallels the wide diversity of human malaria disease and, therefore, might be viewed as a strength. Many of the key features of human malaria can be replicated in a variety of nonhuman primate models, which are very under-utilized. The importance of animal models in the discovery of new anti-malarial drugs was emphasized. The major conclusions of the session were that experimental and human studies should be more closely linked so that they inform each other, and that there should be wider access to relevant clinical material.

The effects of model and data complexity on predictions from species distributions models

DEFF Research Database (Denmark)

García-Callejas, David; Bastos, Miguel

2016-01-01

How complex does a model need to be to provide useful predictions is a matter of continuous debate across environmental sciences. In the species distributions modelling literature, studies have demonstrated that more complex models tend to provide better fits. However, studies have also shown...... that predictive performance does not always increase with complexity. Testing of species distributions models is challenging because independent data for testing are often lacking, but a more general problem is that model complexity has never been formally described in such studies. Here, we systematically...

Towards policy relevant environmental modeling: contextual validity and pragmatic models

Science.gov (United States)

Miles, Scott B.

2000-01-01

"What makes for a good model?" In various forms, this question is a question that, undoubtedly, many people, businesses, and institutions ponder with regards to their particular domain of modeling. One particular domain that is wrestling with this question is the multidisciplinary field of environmental modeling. Examples of environmental models range from models of contaminated ground water flow to the economic impact of natural disasters, such as earthquakes. One of the distinguishing claims of the field is the relevancy of environmental modeling to policy and environment-related decision-making in general. A pervasive view by both scientists and decision-makers is that a "good" model is one that is an accurate predictor. Thus, determining whether a model is "accurate" or "correct" is done by comparing model output to empirical observations. The expected outcome of this process, usually referred to as "validation" or "ground truthing," is a stamp on the model in question of "valid" or "not valid" that serves to indicate whether or not the model will be reliable before it is put into service in a decision-making context. In this paper, I begin by elaborating on the prevailing view of model validation and why this view must change. Drawing from concepts coming out of the studies of science and technology, I go on to propose a contextual view of validity that can overcome the problems associated with "ground truthing" models as an indicator of model goodness. The problem of how we talk about and determine model validity has much to do about how we perceive the utility of environmental models. In the remainder of the paper, I argue that we should adopt ideas of pragmatism in judging what makes for a good model and, in turn, developing good models. From such a perspective of model goodness, good environmental models should facilitate communication, convey—not bury or "eliminate"—uncertainties, and, thus, afford the active building of consensus decisions, instead

Predicting Environmental Suitability for a Rare and Threatened Species (Lao Newt, Laotriton laoensis) Using Validated Species Distribution Models

Science.gov (United States)

Chunco, Amanda J.; Phimmachak, Somphouthone; Sivongxay, Niane; Stuart, Bryan L.

2013-01-01

The Lao newt (Laotriton laoensis) is a recently described species currently known only from northern Laos. Little is known about the species, but it is threatened as a result of overharvesting. We integrated field survey results with climate and altitude data to predict the geographic distribution of this species using the niche modeling program Maxent, and we validated these predictions by using interviews with local residents to confirm model predictions of presence and absence. The results of the validated Maxent models were then used to characterize the environmental conditions of areas predicted suitable for L. laoensis. Finally, we overlaid the resulting model with a map of current national protected areas in Laos to determine whether or not any land predicted to be suitable for this species is coincident with a national protected area. We found that both area under the curve (AUC) values and interview data provided strong support for the predictive power of these models, and we suggest that interview data could be used more widely in species distribution niche modeling. Our results further indicated that this species is mostly likely geographically restricted to high altitude regions (i.e., over 1,000 m elevation) in northern Laos and that only a minute fraction of suitable habitat is currently protected. This work thus emphasizes that increased protection efforts, including listing this species as endangered and the establishment of protected areas in the region predicted to be suitable for L. laoensis, are urgently needed. PMID:23555808

Evaluation of P-glycoprotein expression in pain relevant tissues: understanding translation of efflux from preclinical species to human

Directory of Open Access Journals (Sweden)

Renu Singh Dhanikula

2016-10-01

Full Text Available Various efflux transporters, such as P-glycoprotein (P-gp are now widely accepted to have profound influence on the disposition of substrates. Nevertheless, there is paucity of information about their expression and functionality in the pain relevant tissues (such as brain, spinal cord and dorsal root ganglia (DRG across various species. Therefore, our attempts were directed at evaluating P-gp expression in these tissues to understand its effect on the central nervous system (CNS disposition. As a means of characterizing the normal tissue distribution of P-gp, immunohistochemistry was performed with two antibodies (C219 and H241 directed against different epitopes of MDR1 gene. Notable expression of P-gp was detected in the DRG of Sprague Dawley rat, Beagle Dog, Cynomolgous monkey as well as human. The expression of P-gp was observed in the CNS tissues with evident species differences, the expression of P-gp in human brain and spinal cord was lower than in rats and dogs but relatively comparable to that in monkeys. However, no species related differences were seen in the expression at the DRG level. Double-labelling using an antibody against a marker of endothelial cells confirmed that P-gp was exclusively localized in capillary endothelial cells. This study highlights the cross species similarities and differences in the expression of P-gp and thus serves as a vital step in understanding the translation of exposure of P-gp substrates to human.

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.

Near infra-red spectroscopy quantitative modelling of bivalve protein, lipid and glycogen composition using single-species versus multi-species calibration and validation sets

Science.gov (United States)

Bartlett, Jill K.; Maher, William A.; Purss, Matthew B. J.

2018-03-01

Near infrared spectroscopy (NIRS) quantitative modelling was used to measure the protein, lipid and glycogen composition of five marine bivalve species (Saccostrea glomerata, Ostrea angasi, Crassostrea gigas, Mytilus galloprovincialis and Anadara trapezia) from multiple locations and seasons. Predictive models were produced for each component using individual species and aggregated sample populations for the three oyster species (S. glomerata, O. angasi and C. gigas) and for all five bivalve species. Whole animal tissues were freeze dried, ground to > 20 μm and scanned by NIRS. Protein, lipid and glycogen composition were determined by traditional chemical analyses and calibration models developed to allow rapid NIRS-measurement of these components in the five bivalve species. Calibration modelling was performed using wavelet selection, genetic algorithms and partial least squares analysis. Model quality was assessed using RPIQ and RMESP. For protein composition, single species model results had RPIQ values between 2.4 and 3.5 and RMSEP between 8.6 and 18%, the three oyster model had an RPIQ of 2.6 and an RMSEP of 10.8% and the five bivalve species had an RPIQ of 3.6 and RMSEP of 8.7% respectively. For lipid composition, single species models achieved RPIQ values between 2.9 and 5.3 with RMSEP between 9.1 and 11.2%, the oyster model had an RPIQ of 3.6 and RMSEP of 6.8 and the five bivalve model had an RPIQ of 5.2 and RMSEP of 6.8% respectively. For glycogen composition, the single species models had RPIQs between 3.8 and 18.9 with RMSEP between 3.5 and 9.2%, the oyster model had an RPIQ of 5.5 and RMSEP of 7.1% and the five bivalve model had an RPIQ of 4 and RMSEP of 7.6% respectively. Comparison between individual species models and aggregated models for three oyster species and five bivalve species for each component indicate that aggregating data from like species produces high quality models with robust and reliable quantitative application. The benefit of

A comparison of fisheries biological reference points estimated from temperature-specific multi-species and single-species climate-enhanced stock assessment models

Science.gov (United States)

Holsman, Kirstin K.; Ianelli, James; Aydin, Kerim; Punt, André E.; Moffitt, Elizabeth A.

2016-12-01

Multi-species statistical catch at age models (MSCAA) can quantify interacting effects of climate and fisheries harvest on species populations, and evaluate management trade-offs for fisheries that target several species in a food web. We modified an existing MSCAA model to include temperature-specific growth and predation rates and applied the modified model to three fish species, walleye pollock (Gadus chalcogrammus), Pacific cod (Gadus macrocephalus) and arrowtooth flounder (Atheresthes stomias), from the eastern Bering Sea (USA). We fit the model to data from 1979 through 2012, with and without trophic interactions and temperature effects, and use projections to derive single- and multi-species biological reference points (BRP and MBRP, respectively) for fisheries management. The multi-species model achieved a higher over-all goodness of fit to the data (i.e. lower negative log-likelihood) for pollock and Pacific cod. Variability from water temperature typically resulted in 5-15% changes in spawning, survey, and total biomasses, but did not strongly impact recruitment estimates or mortality. Despite this, inclusion of temperature in projections did have a strong effect on BRPs, including recommended yield, which were higher in single-species models for Pacific cod and arrowtooth flounder that included temperature compared to the same models without temperature effects. While the temperature-driven multi-species model resulted in higher yield MBPRs for arrowtooth flounder than the same model without temperature, we did not observe the same patterns in multi-species models for pollock and Pacific cod, where variability between harvest scenarios and predation greatly exceeded temperature-driven variability in yield MBRPs. Annual predation on juvenile pollock (primarily cannibalism) in the multi-species model was 2-5 times the annual harvest of adult fish in the system, thus predation represents a strong control on population dynamics that exceeds temperature

Use of early phenotypic in vivo markers to assess human relevance of an unusual rodent non-genotoxic carcinogen in vitro

International Nuclear Information System (INIS)

Boess, Franziska; Lenz, Barbara; Funk, Juergen; Niederhauser, Urs; Bassett, Simon; Zhang, Jitao David; Singer, Thomas; Roth, Adrian B.

2017-01-01

Highlights: • RG3487 induced foci of altered hepatocytes and subsequent liver tumors in rats. • Early phenotypic markers preceding foci appearance in rats were identified. • These early foci markers could be recapitulated in cellular rat liver models. • A species comparison using rat, mouse and dog liver cell models qualified the approach. • In vitro human data support non-human-relevance for RG3487 induced foci formation. - Abstract: Foci of altered hepatocytes (FAH) are considered putative, pre-neoplastic lesions that can occur spontaneously in aging rodents, but can also be induced by chemicals or drugs. Progression of FAH to hepatocellular neoplasms has been reported repeatedly but increases in foci in rodents do not necessarily lead to tumors in carcinogenicity studies and the relevance for humans often remains unclear. Here we present the case of RG3487, a molecule which induced FAH and, later on, tumors in rats. Because the molecule was negative in genotoxicity assays it was classified as a non-genotoxic carcinogen. In order to assess the potential for liver tumor formation in humans, we analyzed treatment-induced changes in vivo to establish a possible mode of action (MoA). In vivo and in vitro gene expression analysis revealed that nuclear receptor signaling was unlikely to be the relevant MoA and no other known mechanism could be established. We therefore took an approach comparing phenotypic markers, including mRNA changes, proliferation and glycogen accumulation, in vitro using cells of different species to assess the human relevance of this finding. Since the alterations observed in rats were not seen in the liver of mice or dogs in vivo, we could validate the relevance of the cell models chosen by use of hepatocytes from these species in vitro. This ultimately allowed for a cross-species comparison, which suggested that the formation of FAH and liver tumors was rat specific and unlikely to translate to human. Our work showed that phenotypic

Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine

Directory of Open Access Journals (Sweden)

Hang-cheong Wong

2012-01-01

Full Text Available Engine power, brake-specific fuel consumption, and emissions relate closely to air ratio (i.e., lambda among all the engine variables. An accurate and adaptive model for lambda prediction is essential to effective lambda control for long term. This paper utilizes an emerging technique, relevance vector machine (RVM, to build a reliable time-dependent lambda model which can be continually updated whenever a sample is added to, or removed from, the estimated lambda model. The paper also presents a new model predictive control (MPC algorithm for air-ratio regulation based on RVM. This study shows that the accuracy, training, and updating time of the RVM model are superior to the latest modelling methods, such as diagonal recurrent neural network (DRNN and decremental least-squares support vector machine (DLSSVM. Moreover, the control algorithm has been implemented on a real car to test. Experimental results reveal that the control performance of the proposed relevance vector machine model predictive controller (RVMMPC is also superior to DRNNMPC, support vector machine-based MPC, and conventional proportional-integral (PI controller in production cars. Therefore, the proposed RVMMPC is a promising scheme to replace conventional PI controller for engine air-ratio control.

Biomass models to estimate carbon stocks for hardwood tree species

Energy Technology Data Exchange (ETDEWEB)

Ruiz-Peinado, R.; Montero, G.; Rio, M. del

2012-11-01

To estimate forest carbon pools from forest inventories it is necessary to have biomass models or biomass expansion factors. In this study, tree biomass models were developed for the main hardwood forest species in Spain: Alnus glutinosa, Castanea sativa, Ceratonia siliqua, Eucalyptus globulus, Fagus sylvatica, Fraxinus angustifolia, Olea europaea var. sylvestris, Populus x euramericana, Quercus canariensis, Quercus faginea, Quercus ilex, Quercus pyrenaica and Quercus suber. Different tree biomass components were considered: stem with bark, branches of different sizes, above and belowground biomass. For each species, a system of equations was fitted using seemingly unrelated regression, fulfilling the additivity property between biomass components. Diameter and total height were explored as independent variables. All models included tree diameter whereas for the majority of species, total height was only considered in the stem biomass models and in some of the branch models. The comparison of the new biomass models with previous models fitted separately for each tree component indicated an improvement in the accuracy of the models. A mean reduction of 20% in the root mean square error and a mean increase in the model efficiency of 7% in comparison with recently published models. So, the fitted models allow estimating more accurately the biomass stock in hardwood species from the Spanish National Forest Inventory data. (Author) 45 refs.

PDEAR model prediction of Protea species in years 2070-2100

Science.gov (United States)

Guo, Danni; Guo, Renkuan; Midgley, Guy F.; Rebelo, A. G.

2009-10-01

Global warming and climate changes are changing the environment and therefore changing the distribution and behaviour of the plant species. Plant species often move and change their distributions as they find their original habitats are no longer suitable to their needs. It is therefore important to establish a statistical model to catch up the movement and patterns of the endangered species in order to effectively manage environmental protection under the inevitable biodiversity changes that are taking place. In this paper, we are focusing on the population category of rare Proteas that has an estimated population size from 1 to 10 per sample site, which is very small. We used the partial differential equation associated regression (PDEAR) model, which merges the partial differential equation theory, (statistical) linear model theory and random fuzzy variable theory together into a efficient small-sample oriented model, for the spatial pattern changing analysis. The regression component in a PDEAR model is in nature a special random fuzzy multivariate regression model. We developed a bivariate model for investigating the impacts from rainfall and temperature on the Protea species in average sense in the population size of 1 to 10, in the Cape Floristic Region, from 1992 to 2002, South Africa. Under same the average biodiversity structure assumptions, we explore the future spatial change patterns of Protea species in the population size of 1 to 10 with future (average) predicted rainfall and temperature. The spatial distribution and patterns are clearly will help us to explore global climate changing impacts on endangered species.

Benchmarking novel approaches for modelling species range dynamics.

Science.gov (United States)

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

Model-based uncertainty in species range prediction

DEFF Research Database (Denmark)

Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

2006-01-01

Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions...

A multiple relevance feedback strategy with positive and negative models.

Directory of Open Access Journals (Sweden)

Yunlong Ma

Full Text Available A commonly used strategy to improve search accuracy is through feedback techniques. Most existing work on feedback relies on positive information, and has been extensively studied in information retrieval. However, when a query topic is difficult and the results from the first-pass retrieval are very poor, it is impossible to extract enough useful terms from a few positive documents. Therefore, the positive feedback strategy is incapable to improve retrieval in this situation. Contrarily, there is a relatively large number of negative documents in the top of the result list, and it has been confirmed that negative feedback strategy is an important and useful way for adapting this scenario by several recent studies. In this paper, we consider a scenario when the search results are so poor that there are at most three relevant documents in the top twenty documents. Then, we conduct a novel study of multiple strategies for relevance feedback using both positive and negative examples from the first-pass retrieval to improve retrieval accuracy for such difficult queries. Experimental results on these TREC collections show that the proposed language model based multiple model feedback method which is generally more effective than both the baseline method and the methods using only positive or negative model.

Modeling of the Dorsal Gradient across Species Reveals Interaction between Embryo Morphology and Toll Signaling Pathway during Evolution

Science.gov (United States)

Koslen, Hannah R.; Chiel, Hillel J.; Mizutani, Claudia Mieko

2014-01-01

Morphogenetic gradients are essential to allocate cell fates in embryos of varying sizes within and across closely related species. We previously showed that the maternal NF-κB/Dorsal (Dl) gradient has acquired different shapes in Drosophila species, which result in unequally scaled germ layers along the dorso-ventral axis and the repositioning of the neuroectodermal borders. Here we combined experimentation and mathematical modeling to investigate which factors might have contributed to the fast evolutionary changes of this gradient. To this end, we modified a previously developed model that employs differential equations of the main biochemical interactions of the Toll (Tl) signaling pathway, which regulates Dl nuclear transport. The original model simulations fit well the D. melanogaster wild type, but not mutant conditions. To broaden the applicability of this model and probe evolutionary changes in gradient distributions, we adjusted a set of 19 independent parameters to reproduce three quantified experimental conditions (i.e. Dl levels lowered, nuclear size and density increased or decreased). We next searched for the most relevant parameters that reproduce the species-specific Dl gradients. We show that adjusting parameters relative to morphological traits (i.e. embryo diameter, nuclear size and density) alone is not sufficient to reproduce the species Dl gradients. Since components of the Tl pathway simulated by the model are fast-evolving, we next asked which parameters related to Tl would most effectively reproduce these gradients and identified a particular subset. A sensitivity analysis reveals the existence of nonlinear interactions between the two fast-evolving traits tested above, namely the embryonic morphological changes and Tl pathway components. Our modeling further suggests that distinct Dl gradient shapes observed in closely related melanogaster sub-group lineages may be caused by similar sequence modifications in Tl pathway components, which

Solvable Catalyzed Birth-Death-Exchange Competition Model of Three Species

International Nuclear Information System (INIS)

Wang Haifeng; Gao Yan; Zhang Heng; Lin Zhenquan

2009-01-01

A competition model of three species in exchange-driven aggregation growth is proposed. In the model, three distinct aggregates grow by exchange of monomers and in parallel, birth of species A is catalyzed by species B and death of species A is catalyzed by species C. The rates for both catalysis processes are proportional to kj ν and kj ω respectively, where ν(Ω) is a parameter reflecting the dependence of the catalysis reaction rate of birth (death) on the catalyst aggregate's size. The kinetic evolution behaviors of the three species are investigated by the rate equation approach based on the mean-field theory. The form of the aggregate size distribution of A-species a k (t) is found to be dependent crucially on the two catalysis rate kernel parameters. The results show that (i) in case of μ ≤ 0, the form of a k (t) mainly depends on the competition between self-exchange of species A and species-C-catalyzed death of species A; (ii) in case of ν > 0, the form of a k (t) mainly depends on the competition between species-B-catalyzed birth of species A and species-C-catalyzed death of species A. (interdisciplinary physics and related areas of science and technology)

Structural Model Error and Decision Relevancy

Science.gov (United States)

Goldsby, M.; Lusk, G.

2017-12-01

The extent to which climate models can underwrite specific climate policies has long been a contentious issue. Skeptics frequently deny that climate models are trustworthy in an attempt to undermine climate action, whereas policy makers often desire information that exceeds the capabilities of extant models. While not skeptics, a group of mathematicians and philosophers [Frigg et al. (2014)] recently argued that even tiny differences between the structure of a complex dynamical model and its target system can lead to dramatic predictive errors, possibly resulting in disastrous consequences when policy decisions are based upon those predictions. They call this result the Hawkmoth effect (HME), and seemingly use it to rebuke rightwing proposals to forgo mitigation in favor of adaptation. However, a vigorous debate has emerged between Frigg et al. on one side and another philosopher-mathematician pair [Winsberg and Goodwin (2016)] on the other. On one hand, Frigg et al. argue that their result shifts the burden to climate scientists to demonstrate that their models do not fall prey to the HME. On the other hand, Winsberg and Goodwin suggest that arguments like those asserted by Frigg et al. can be, if taken seriously, "dangerous": they fail to consider the variety of purposes for which models can be used, and thus too hastily undermine large swaths of climate science. They put the burden back on Frigg et al. to show their result has any effect on climate science. This paper seeks to attenuate this debate by establishing an irenic middle position; we find that there is more agreement between sides than it first seems. We distinguish a `decision standard' from a `burden of proof', which helps clarify the contributions to the debate from both sides. In making this distinction, we argue that scientists bear the burden of assessing the consequences of HME, but that the standard Frigg et al. adopt for decision relevancy is too strict.

The relevance of non-human primate and rodent malaria models for humans

OpenAIRE

Langhorne, Jean; Buffet, Pierre; Galinski, Mary; Good, Michael; Harty, John; Leroy, Didier; Mota, Maria M; Pasini, Erica; Renia, Laurent; Riley, Eleanor; Stins, Monique; Duffy, Patrick

2011-01-01

Abstract At the 2010 Keystone Symposium on "Malaria: new approaches to understanding Host-Parasite interactions", an extra scientific session to discuss animal models in malaria research was convened at the request of participants. This was prompted by the concern of investigators that skepticism in the malaria community about the use and relevance of animal models, particularly rodent models of severe malaria, has impacted on funding decisions and publication of research using animal models....

Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species.

Directory of Open Access Journals (Sweden)

Matthew Geary

Full Text Available Accurate predictions of the impacts of future land use change on species of conservation concern can help to inform policy-makers and improve conservation measures. If predictions are spatially explicit, predicted consequences of likely land use changes could be accessible to land managers at a scale relevant to their working landscape. We introduce a method, based on open source software, which integrates habitat suitability modelling with scenario-building, and illustrate its use by investigating the effects of alternative land use change scenarios on landscape suitability for black grouse Tetrao tetrix. Expert opinion was used to construct five near-future (twenty years scenarios for the 800 km2 study site in upland Scotland. For each scenario, the cover of different land use types was altered by 5-30% from 20 random starting locations and changes in habitat suitability assessed by projecting a MaxEnt suitability model onto each simulated landscape. A scenario converting grazed land to moorland and open forestry was the most beneficial for black grouse, and 'increased grazing' (the opposite conversion the most detrimental. Positioning of new landscape blocks was shown to be important in some situations. Increasing the area of open-canopy forestry caused a proportional decrease in suitability, but suitability gains for the 'reduced grazing' scenario were nonlinear. 'Scenario-led' landscape simulation models can be applied in assessments of the impacts of land use change both on individual species and also on diversity and community measures, or ecosystem services. A next step would be to include landscape configuration more explicitly in the simulation models, both to make them more realistic, and to examine the effects of habitat placement more thoroughly. In this example, the recommended policy would be incentives on grazing reduction to benefit black grouse.

Control Relevant Modeling and Design of Scramjet-Powered Hypersonic Vehicles

Science.gov (United States)

Dickeson, Jeffrey James

This report provides an overview of scramjet-powered hypersonic vehicle modeling and control challenges. Such vehicles are characterized by unstable non-minimum phase dynamics with significant coupling and low thrust margins. Recent trends in hypersonic vehicle research are summarized. To illustrate control relevant design issues and tradeoffs, a generic nonlinear 3DOF longitudinal dynamics model capturing aero-elastic-propulsive interactions for wedge-shaped vehicle is used. Limitations of the model are discussed and numerous modifications have been made to address control relevant needs. Two different baseline configurations are examined over a two-stage to orbit ascent trajectory. The report highlights how vehicle level-flight static (trim) and dynamic properties change over the trajectory. Thermal choking constraints are imposed on control system design as a direct consequence of having a finite FER margin. The implication of this state-dependent nonlinear FER margin constraint, the right half plane (RHP) zero, and lightly damped flexible modes, on control system bandwidth (BW) and FPA tracking has been discussed. A control methodology has been proposed that addresses the above dynamics while providing some robustness to modeling uncertainty. Vehicle closure (the ability to fly a trajectory segment subject to constraints) is provided through a proposed vehicle design methodology. The design method attempts to use open loop metrics whenever possible to design the vehicle. The design method is applied to a vehicle/control law closed loop nonlinear simulation for validation. The 3DOF longitudinal modeling results are validated against a newly released NASA 6DOF code.

Thematic and spatial resolutions affect model-based predictions of tree species distribution.

Science.gov (United States)

Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

Comparison of a species distribution model and a process model from a hierarchical perspective to quantify effects of projected climate change on tree species

Science.gov (United States)

Jeffrey E. Schneiderman; Hong S. He; Frank R. Thompson; William D. Dijak; Jacob S. Fraser

2015-01-01

Tree species distribution and abundance are affected by forces operating across a hierarchy of ecological scales. Process and species distribution models have been developed emphasizing forces at different scales. Understanding model agreement across hierarchical scales provides perspective on prediction uncertainty and ultimately enables policy makers and managers to...

On Feature Relevance in Image-Based Prediction Models: An Empirical Study

DEFF Research Database (Denmark)

Konukoglu, E.; Ganz, Melanie; Van Leemput, Koen

2013-01-01

Determining disease-related variations of the anatomy and function is an important step in better understanding diseases and developing early diagnostic systems. In particular, image-based multivariate prediction models and the “relevant features” they produce are attracting attention from the co...

Oxidative muscular injury and its relevance to hyperthyroidism.

Science.gov (United States)

Asayama, K; Kato, K

1990-01-01

In experimental hyperthyroidism, acceleration of lipid peroxidation occurs in heart and slow-oxidative muscles, suggesting the contribution of reactive oxygen species to the muscular injury caused by thyroid hormones. This article reviews various models of oxidative muscular injury and considers the relevance of the accompanying metabolic derangements to thyrotoxic myopathy and cardiomyopathy, which are the major complications of hyperthyroidism. The muscular injury models in which reactive oxygen species are supposed to play a role are ischemia/reperfusion syndrome, exercise-induced myopathy, heart and skeletal muscle diseases related to the nutritional deficiency of selenium and vitamin E and related disorders, and genetic muscular dystrophies. These models provide evidence that mitochondrial function and the glutathione-dependent antioxidant system are important for the maintenance of the structural and functional integrity of muscular tissues. Thyroid hormones have a profound effect on mitochondrial oxidative activity, synthesis and degradation of proteins and vitamin E, the sensitivity of the tissues to catecholamine, the differentiation of muscle fibers, and the levels of antioxidant enzymes. The large volume of circumstantial evidence presented here indicates that hyperthyroid muscular tissues undergo several biochemical changes that predispose them to free radical-mediated injury.

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

DEFF Research Database (Denmark)

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

2007-01-01

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

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.

Talaromyces atroroseus, a new species efficiently producing industrially relevant red pigments

DEFF Research Database (Denmark)

Frisvad, Jens Christian; Yilmaz, Neriman; Thrane, Ulf

2013-01-01

., described in this study, produces the azaphilone biosynthetic families mitorubrins and Monascus pigments without any production of mycotoxins. Within the red pigment producing clade, T. atroroseus resolved in a distinct clade separate from all the other species in multigene phylogenies (ITS, β......Some species of Talaromyces secrete large amounts of red pigments. Literature has linked this character to species such as Talaromyces purpurogenus, T. albobiverticillius, T. marneffei, and T. minioluteus often under earlier Penicillium names. Isolates identified as T. purpurogenus have been...... reported to be interesting industrially and they can produce extracellular enzymes and red pigments, but they can also produce mycotoxins such as rubratoxin A and B and luteoskyrin. Production of mycotoxins limits the use of isolates of a particular species in biotechnology. Talaromyces atroroseus sp. nov...

Updating known distribution models for forecasting climate change impact on endangered species.

Science.gov (United States)

Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

2013-01-01

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only.

Highly Relevant Mentoring (HRM) as a Faculty Development Model for Web-Based Instruction

Science.gov (United States)

Carter, Lorraine; Salyers, Vincent; Page, Aroha; Williams, Lynda; Albl, Liz; Hofsink, Clarence

2012-01-01

This paper describes a faculty development model called the highly relevant mentoring (HRM) model; the model includes a framework as well as some practical strategies for meeting the professional development needs of faculty who teach web-based courses. The paper further emphasizes the need for faculty and administrative buy-in for HRM and…

Selection bias in species distribution models: An econometric approach on forest trees based on structural modeling

Science.gov (United States)

Martin-StPaul, N. K.; Ay, J. S.; Guillemot, J.; Doyen, L.; Leadley, P.

2014-12-01

Species distribution models (SDMs) are widely used to study and predict the outcome of global changes on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of applications on forest trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8km). We also compared the outputs of the SSDM with outputs of a classical SDM (i.e. Biomod ensemble modelling) in terms of bioclimatic response curves and potential distributions under current climate and climate change scenarios. The shapes of the bioclimatic response curves and the modelled species distribution maps differed markedly between SSDM and classical SDMs, with contrasted patterns according to species and spatial resolutions. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents

Mouse models of ageing and their relevance to disease.

Science.gov (United States)

Kõks, Sulev; Dogan, Soner; Tuna, Bilge Guvenc; González-Navarro, Herminia; Potter, Paul; Vandenbroucke, Roosmarijn E

2016-12-01

Ageing is a process that gradually increases the organism's vulnerability to death. It affects different biological pathways, and the underlying cellular mechanisms are complex. In view of the growing disease burden of ageing populations, increasing efforts are being invested in understanding the pathways and mechanisms of ageing. We review some mouse models commonly used in studies on ageing, highlight the advantages and disadvantages of the different strategies, and discuss their relevance to disease susceptibility. In addition to addressing the genetics and phenotypic analysis of mice, we discuss examples of models of delayed or accelerated ageing and their modulation by caloric restriction. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

The Bifurcation and Control of a Single-Species Fish Population Logistic Model with the Invasion of Alien Species

OpenAIRE

Zhang, Yi; Zhang, Qiaoling; Li, Jinghao; Zhang, Qingling

2014-01-01

The objective of this paper is to study systematically the bifurcation and control of a single-species fish population logistic model with the invasion of alien species based on the theory of singular system and bifurcation. It regards Spartina anglica as an invasive species, which invades the fisheries and aquaculture. Firstly, the stabilities of equilibria in this model are discussed. Moreover, the sufficient conditions for existence of the trans-critical bifurcation and the singularity ind...

Species distribution models of tropical deep-sea snappers.

Directory of Open Access Journals (Sweden)

Céline Gomez

Full Text Available Deep-sea fisheries provide an important source of protein to Pacific Island countries and territories that are highly dependent on fish for food security. However, spatial management of these deep-sea habitats is hindered by insufficient data. We developed species distribution models using spatially limited presence data for the main harvested species in the Western Central Pacific Ocean. We used bathymetric and water temperature data to develop presence-only species distribution models for the commercially exploited deep-sea snappers Etelis Cuvier 1828, Pristipomoides Valenciennes 1830, and Aphareus Cuvier 1830. We evaluated the performance of four different algorithms (CTA, GLM, MARS, and MAXENT within the BIOMOD framework to obtain an ensemble of predicted distributions. We projected these predictions across the Western Central Pacific Ocean to produce maps of potential deep-sea snapper distributions in 32 countries and territories. Depth was consistently the best predictor of presence for all species groups across all models. Bathymetric slope was consistently the poorest predictor. Temperature at depth was a good predictor of presence for GLM only. Model precision was highest for MAXENT and CTA. There were strong regional patterns in predicted distribution of suitable habitat, with the largest areas of suitable habitat (> 35% of the Exclusive Economic Zone predicted in seven South Pacific countries and territories (Fiji, Matthew & Hunter, Nauru, New Caledonia, Tonga, Vanuatu and Wallis & Futuna. Predicted habitat also varied among species, with the proportion of predicted habitat highest for Aphareus and lowest for Etelis. Despite data paucity, the relationship between deep-sea snapper presence and their environments was sufficiently strong to predict their distribution across a large area of the Pacific Ocean. Our results therefore provide a strong baseline for designing monitoring programs that balance resource exploitation and

Talaromyces atroroseus, a new species efficiently producing industrially relevant red pigments.

Directory of Open Access Journals (Sweden)

Jens C Frisvad

Full Text Available Some species of Talaromyces secrete large amounts of red pigments. Literature has linked this character to species such as Talaromyces purpurogenus, T. albobiverticillius, T. marneffei, and T. minioluteus often under earlier Penicillium names. Isolates identified as T. purpurogenus have been reported to be interesting industrially and they can produce extracellular enzymes and red pigments, but they can also produce mycotoxins such as rubratoxin A and B and luteoskyrin. Production of mycotoxins limits the use of isolates of a particular species in biotechnology. Talaromyces atroroseus sp. nov., described in this study, produces the azaphilone biosynthetic families mitorubrins and Monascus pigments without any production of mycotoxins. Within the red pigment producing clade, T. atroroseus resolved in a distinct clade separate from all the other species in multigene phylogenies (ITS, β-tubulin and RPB1, which confirm its unique nature. Talaromyces atroroseus resembles T. purpurogenus and T. albobiverticillius in producing red diffusible pigments, but differs from the latter two species by the production of glauconic acid, purpuride and ZG-1494α and by the dull to dark green, thick walled ellipsoidal conidia produced. The type strain of Talaromyces atroroseus is CBS 133442.

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.

Model uncertainties do not affect observed patterns of species richness in the Amazon

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Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo

2017-01-01

Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of

A multi-species exchange model for fully fluctuating polymer field theory simulations.

Science.gov (United States)

Düchs, Dominik; Delaney, Kris T; Fredrickson, Glenn H

2014-11-07

Field-theoretic models have been used extensively to study the phase behavior of inhomogeneous polymer melts and solutions, both in self-consistent mean-field calculations and in numerical simulations of the full theory capturing composition fluctuations. The models commonly used can be grouped into two categories, namely, species models and exchange models. Species models involve integrations of functionals that explicitly depend on fields originating both from species density operators and their conjugate chemical potential fields. In contrast, exchange models retain only linear combinations of the chemical potential fields. In the two-component case, development of exchange models has been instrumental in enabling stable complex Langevin (CL) simulations of the full complex-valued theory. No comparable stable CL approach has yet been established for field theories of the species type. Here, we introduce an extension of the exchange model to an arbitrary number of components, namely, the multi-species exchange (MSE) model, which greatly expands the classes of soft material systems that can be accessed by the complex Langevin simulation technique. We demonstrate the stability and accuracy of the MSE-CL sampling approach using numerical simulations of triblock and tetrablock terpolymer melts, and tetrablock quaterpolymer melts. This method should enable studies of a wide range of fluctuation phenomena in multiblock/multi-species polymer blends and composites.

Using species abundance distribution models and diversity indices for biogeographical analyses

Science.gov (United States)

Fattorini, Simone; Rigal, François; Cardoso, Pedro; Borges, Paulo A. V.

2016-01-01

We examine whether Species Abundance Distribution models (SADs) and diversity indices can describe how species colonization status influences species community assembly on oceanic islands. Our hypothesis is that, because of the lack of source-sink dynamics at the archipelago scale, Single Island Endemics (SIEs), i.e. endemic species restricted to only one island, should be represented by few rare species and consequently have abundance patterns that differ from those of more widespread species. To test our hypothesis, we used arthropod data from the Azorean archipelago (North Atlantic). We divided the species into three colonization categories: SIEs, archipelagic endemics (AZEs, present in at least two islands) and native non-endemics (NATs). For each category, we modelled rank-abundance plots using both the geometric series and the Gambin model, a measure of distributional amplitude. We also calculated Shannon entropy and Buzas and Gibson's evenness. We show that the slopes of the regression lines modelling SADs were significantly higher for SIEs, which indicates a relative predominance of a few highly abundant species and a lack of rare species, which also depresses diversity indices. This may be a consequence of two factors: (i) some forest specialist SIEs may be at advantage over other, less adapted species; (ii) the entire populations of SIEs are by definition concentrated on a single island, without possibility for inter-island source-sink dynamics; hence all populations must have a minimum number of individuals to survive natural, often unpredictable, fluctuations. These findings are supported by higher values of the α parameter of the Gambin mode for SIEs. In contrast, AZEs and NATs had lower regression slopes, lower α but higher diversity indices, resulting from their widespread distribution over several islands. We conclude that these differences in the SAD models and diversity indices demonstrate that the study of these metrics is useful for

Simplifying biochemical models with intermediate species

DEFF Research Database (Denmark)

Feliu, Elisenda; Wiuf, Carsten

2013-01-01

techniques, we study systematically the effects of intermediate, or transient, species in biochemical systems and provide a simple, yet rigorous mathematical classification of all models obtained from a core model by including intermediates. Main examples include enzymatic and post-translational modification...... systems, where intermediates often are considered insignificant and neglected in a model, or they are not included because we are unaware of their existence. All possible models obtained from the core model are classified into a finite number of classes. Each class is defined by a mathematically simple...... canonical model that characterizes crucial dynamical properties, such as mono- and multistationarity and stability of steady states, of all models in the class. We show that if the core model does not have conservation laws, then the introduction of intermediates does not change the steady...

Political economy models and agricultural policy formation : empirical applicability and relevance for the CAP

NARCIS (Netherlands)

Zee, van der F.A.

1997-01-01

This study explores the relevance and applicability of political economy models for the explanation of agricultural policies. Part I (chapters 4-7) takes a general perspective and evaluates the empirical applicability of voting models and interest group models to agricultural policy

Time-Domain Simulations of Transient Species in Experimentally Relevant Environments

Energy Technology Data Exchange (ETDEWEB)

Ueltschi, Tyler W.; Fischer, Sean A.; Apra, Edoardo; Tarnovsky, Alexander N.; Govind, Niranjan; El-Khoury, Patrick Z.; Hess, Wayne P.

2016-02-04

Simulating the spectroscopic properties of short-lived thermal and photochemical reaction intermediates and products is a challenging task, as these species often feature atypical molecular and electronic structures. The complex environments in which such species typically reside in practice add further complexity to the problem. Herein, we tackle this problem in silico using ab initio molecular dynamics (AIMD) simulations, employing iso-CHBr3, namely H(Br)C-Br-Br, as a prototypical system. This species was chosen because it features both a non-conventional C-Br-Br bonding pattern, as well as a strong dependence of its spectral features on the local environment in which it resides, as illustrated in recent experimental reports. The spectroscopic properties of iso-CHBr3 were measured by several groups that captured this transient intermediate in the photochemistry of CHBr3 in the gas phase, in rare gas matrices at 5K, and in solution under ambient laboratory conditions. We simulate the UV-Vis and IR spectra of iso-CHBr3 in all three media, including a Ne cluster (64 atoms) and a methylcyclohexane cage (14 solvent molecules) representative of the matrix isolated and solvated species. We exclusively perform fully quantum mechanical static and dynamic simulations. By comparing our condensed phase simulations to their experimental analogues, we stress the importance of (i) conformational sampling, even at cryogenic temperatures, and (ii) using a fully quantum mechanical description of both solute and bath to properly account for the experimental observables.

Models of alien species richness show moderate predictive accuracy and poor transferability

Directory of Open Access Journals (Sweden)

César Capinha

2018-06-01

Full Text Available Robust predictions of alien species richness are useful to assess global biodiversity change. Nevertheless, the capacity to predict spatial patterns of alien species richness remains largely unassessed. Using 22 data sets of alien species richness from diverse taxonomic groups and covering various parts of the world, we evaluated whether different statistical models were able to provide useful predictions of absolute and relative alien species richness, as a function of explanatory variables representing geographical, environmental and socio-economic factors. Five state-of-the-art count data modelling techniques were used and compared: Poisson and negative binomial generalised linear models (GLMs, multivariate adaptive regression splines (MARS, random forests (RF and boosted regression trees (BRT. We found that predictions of absolute alien species richness had a low to moderate accuracy in the region where the models were developed and a consistently poor accuracy in new regions. Predictions of relative richness performed in a superior manner in both geographical settings, but still were not good. Flexible tree ensembles-type techniques (RF and BRT were shown to be significantly better in modelling alien species richness than parametric linear models (such as GLM, despite the latter being more commonly applied for this purpose. Importantly, the poor spatial transferability of models also warrants caution in assuming the generality of the relationships they identify, e.g. by applying projections under future scenario conditions. Ultimately, our results strongly suggest that predictability of spatial variation in richness of alien species richness is limited. The somewhat more robust ability to rank regions according to the number of aliens they have (i.e. relative richness, suggests that models of aliens species richness may be useful for prioritising and comparing regions, but not for predicting exact species numbers.

Life histories of microalgal species causing harmful blooms: Haploids, diploids and the relevance of benthic stages.

Science.gov (United States)

Figueroa, Rosa Isabel; Estrada, Marta; Garcés, Esther

2018-03-01

In coastal and offshore waters, Harmful Algal Blooms (HABs) currently threaten the well-being of coastal countries. These events, which can be localized or involve wide-ranging areas, pose risks to human health, marine ecosystems, and economic resources, such as tourism, fisheries, and aquaculture. Dynamics of HABs vary from one site to another, depending on the hydrographic and ecological conditions. The challenge in investigating HABs is that they are caused by organisms from multiple algal classes, each with its own unique features, including different life histories. The complete algal life cycle has been determined in life cycles of bloom-forming species is essential in developing preventative measures. The knowledge obtained thus far has confirmed the complexity of the algal life cycle, which is composed of discrete life stages whose morphology, ecological niche (plankton/benthos), function, and lifespan vary. The factors that trigger transitions between the different stages in nature are mostly unknown, but it is clear that an understanding of this process provides the key to effectively forecasting bloom recurrence, maintenance, and decline. Planktonic stages constitute an ephemeral phase of the life cycle of most species whereas resistant, benthic stages enable a species to withstand adverse conditions for prolonged periods, thus providing dormant reservoirs for eventual blooms and facilitating organismal dispersal. Here we review current knowledge of the life cycle strategies of major groups of HAB producers in marine and brackish waters. Rather than providing a comprehensive discussion, the objective was to highlight several of the research milestones that have changed our understanding of the plasticity and frequency of the different life cycle stages as well as the transitions between them. We also discuss the relevance of benthic and planktonic forms and their implications for HAB dynamics. Copyright © 2018. Published by Elsevier B.V.

ConSpeciFix: Classifying prokaryotic species based on gene flow.

Science.gov (United States)

Bobay, Louis-Marie; Ellis, Brian Shin-Hua; Ochman, Howard

2018-05-16

Classification of prokaryotic species is usually based on sequence similarity thresholds, which are easy to apply but lack a biologically-relevant foundation. Here, we present ConSpeciFix, a program that classifies prokaryotes into species using criteria set forth by the Biological Species Concept, thereby unifying species definition in all domains of life. ConSpeciFix's webserver is freely available at www.conspecifix.com. The local version of the program can be freely downloaded from https://github.com/Bobay-Ochman/ConSpeciFix. ConSpeciFix is written in Python 2.7 and requires the following dependencies: Usearch, MCL, MAFFT and RAxML. ljbobay@uncg.edu.

Mapping National Plant Biodiversity Patterns in South Korea with the MARS Species Distribution Model.

Directory of Open Access Journals (Sweden)

Hyeyeong Choe

Full Text Available Accurate information on the distribution of existing species is crucial to assess regional biodiversity. However, data inventories are insufficient in many areas. We examine the ability of Multivariate Adaptive Regression Splines (MARS multi-response species distribution model to overcome species' data limitations and portray plant species distribution patterns for 199 South Korean plant species. The study models species with two or more observations, examines their contribution to national patterns of species richness, provides a sensitivity analysis of different range threshold cutoff approaches for modeling species' ranges, and presents considerations for species modeling at fine spatial resolution. We ran MARS models for each species and tested four threshold methods to transform occurrence probabilities into presence or absence range maps. Modeled occurrence probabilities were extracted at each species' presence points, and the mean, median, and one standard deviation (SD calculated to define data-driven thresholds. A maximum sum of sensitivity and specificity threshold was also calculated, and the range maps from the four cutoffs were tested using independent plant survey data. The single SD values were the best threshold tested for minimizing omission errors and limiting species ranges to areas where the associated occurrence data were correctly classed. Eight individual species range maps for rare plant species were identified that are potentially affected by resampling predictor variables to fine spatial scales. We portray spatial patterns of high species richness by assessing the combined range maps from three classes of species: all species, endangered and endemic species, and range-size rarity of all species, which could be used in conservation planning for South Korea. The MARS model is promising for addressing the common problem of few species occurrence records. However, projected species ranges are highly dependent on the

The selection of a model microalgal species as biomaterial for a novel aquatic phytotoxicity assay

Energy Technology Data Exchange (ETDEWEB)

Bengtson Nash, S.M. [National Research Centre for Environmental Toxicology, University of Queensland, Brisbane QLD 4108 (Australia)]. E-mail: s.nash@uq.edu.au; Quayle, P.A. [National Research Centre for Environmental Toxicology, University of Queensland, Brisbane QLD 4108 (Australia); Schreiber, U. [Lehrstuhl Botanik I, Julius-von-Sachs-Institut fuer Biowissenschaften, Universitaet Wuerzburg, D-97082 Wuerzburg (Germany); Mueller, J.F. [National Research Centre for Environmental Toxicology, University of Queensland, Brisbane QLD 4108 (Australia)

2005-05-15

A phytotoxicity assay based on the ToxY-PAM dual-channel yield analyser has been developed and successfully incorporated into field assessments for the detection of phytotoxicants in water. As a means of further exploring the scope of the assay application and of selecting a model biomaterial to complement the instrument design, nine algal species were exposed to four chemical substances deemed of priority for water quality monitoring purposes (chlorpyrifos, copper, diuron and nonylphenol ethoxylate). Inter-species differences in sensitivity to the four toxicants varied by a factor of 1.9-100. Measurements of photosystem-II quantum yield using these nine single-celled microalgae as biomaterial corroborated previous studies which have shown that the ToxY-PAM dual-channel yield analyser is a highly sensitive method for the detection of PS-II impacting herbicides. Besides Phaeodactylum tricornutum, the previously applied biomaterial, three other species consistently performed well (Nitzschia closterium, Chlorella vulgaris and Dunaliella tertiolecta) and will be used in further test optimisation experiments. In addition to sensitivity, response time was evaluated and revealed a high degree of variation between species and toxicants. While most species displayed relatively weak and slow responses to copper, C. vulgaris demonstrated an IC{sub 10} of 51 {mu}g L{sup -1}, with maximum response measured within 25 minutes and inhibition being accompanied by a large decrease in fluorescence yield. The potential for this C. vulgaris-based bioassay to be used for the detection of copper is discussed. There was no evidence that the standard ToxY-PAM protocol, using these unicellular algae species, could be used for the detection of chlorpyrifos or nonylphenol ethoxylate at environmentally relevant levels.

The selection of a model microalgal species as biomaterial for a novel aquatic phytotoxicity assay

International Nuclear Information System (INIS)

Bengtson Nash, S.M.; Quayle, P.A.; Schreiber, U.; Mueller, J.F.

2005-01-01

A phytotoxicity assay based on the ToxY-PAM dual-channel yield analyser has been developed and successfully incorporated into field assessments for the detection of phytotoxicants in water. As a means of further exploring the scope of the assay application and of selecting a model biomaterial to complement the instrument design, nine algal species were exposed to four chemical substances deemed of priority for water quality monitoring purposes (chlorpyrifos, copper, diuron and nonylphenol ethoxylate). Inter-species differences in sensitivity to the four toxicants varied by a factor of 1.9-100. Measurements of photosystem-II quantum yield using these nine single-celled microalgae as biomaterial corroborated previous studies which have shown that the ToxY-PAM dual-channel yield analyser is a highly sensitive method for the detection of PS-II impacting herbicides. Besides Phaeodactylum tricornutum, the previously applied biomaterial, three other species consistently performed well (Nitzschia closterium, Chlorella vulgaris and Dunaliella tertiolecta) and will be used in further test optimisation experiments. In addition to sensitivity, response time was evaluated and revealed a high degree of variation between species and toxicants. While most species displayed relatively weak and slow responses to copper, C. vulgaris demonstrated an IC 10 of 51 μg L -1 , with maximum response measured within 25 minutes and inhibition being accompanied by a large decrease in fluorescence yield. The potential for this C. vulgaris-based bioassay to be used for the detection of copper is discussed. There was no evidence that the standard ToxY-PAM protocol, using these unicellular algae species, could be used for the detection of chlorpyrifos or nonylphenol ethoxylate at environmentally relevant levels

Infusing considerations of trophic dependencies into species distribution modelling.

Science.gov (United States)

Trainor, Anne M; Schmitz, Oswald J

2014-12-01

Community ecology involves studying the interdependence of species with each other and their environment to predict their geographical distribution and abundance. Modern species distribution analyses characterise species-environment dependency well, but offer only crude approximations of species interdependency. Typically, the dependency between focal species and other species is characterised using other species' point occurrences as spatial covariates to constrain the focal species' predicted range. This implicitly assumes that the strength of interdependency is homogeneous across space, which is not generally supported by analyses of species interactions. This discrepancy has an important bearing on the accuracy of inferences about habitat suitability for species. We introduce a framework that integrates principles from consumer-resource analyses, resource selection theory and species distribution modelling to enhance quantitative prediction of species geographical distributions. We show how to apply the framework using a case study of lynx and snowshoe hare interactions with each other and their environment. The analysis shows how the framework offers a spatially refined understanding of species distribution that is sensitive to nuances in biophysical attributes of the environment that determine the location and strength of species interactions. © 2014 John Wiley & Sons Ltd/CNRS.

The role of demography, intra-species variation, and species distribution models in species’ projections under climate change

DEFF Research Database (Denmark)

Swab, Rebecca Marie; Regan, Helen M.; Matthies, Diethart

2015-01-01

Organisms are projected to shift their distribution ranges under climate change. The typical way to assess range shifts is by species distribution models (SDMs), which predict species’ responses to climate based solely on projected climatic suitability. However, life history traits can impact...... species’ responses to shifting habitat suitability. Additionally, it remains unclear if differences in vital rates across populations within a species can offset or exacerbate the effects of predicted changes in climatic suitability on population viability. In order to obtain a fuller understanding...... of the response of one species to projected climatic changes, we coupled demographic processes with predicted changes in suitable habitat for the monocarpic thistle Carlina vulgaris across northern Europe. We first developed a life history model with species-specific average fecundity and survival rates...

Five (or so) challenges for species distribution modelling

DEFF Research Database (Denmark)

Bastos Araujo, Miguel; Guisan, Antoine

2006-01-01

Species distribution modelling is central to both fundamental and applied research in biogeography. Despite widespread use of models, there are still important conceptual ambiguities as well as biotic and algorithmic uncertainties that need to be investigated in order to increase confidence in mo...

Analysis of multi-species point patterns using multivariate log Gaussian Cox processes

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Guan, Yongtao; Jalilian, Abdollah

Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address t...... of the data. The selected number of common latent fields provides an index of complexity of the multivariate covariance structure. Hierarchical clustering is used to identify groups of species with similar patterns of dependence on the common latent fields.......Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address...... the problems of identifying parsimonious models and of extracting biologically relevant information from the fitted models. The latent multivariate Gaussian field is decomposed into components given in terms of random fields common to all species and components which are species specific. This allows...

Species distribution modeling based on the automated identification of citizen observations.

Science.gov (United States)

Botella, Christophe; Joly, Alexis; Bonnet, Pierre; Monestiez, Pascal; Munoz, François

2018-02-01

A species distribution model computed with automatically identified plant observations was developed and evaluated to contribute to future ecological studies. We used deep learning techniques to automatically identify opportunistic plant observations made by citizens through a popular mobile application. We compared species distribution modeling of invasive alien plants based on these data to inventories made by experts. The trained models have a reasonable predictive effectiveness for some species, but they are biased by the massive presence of cultivated specimens. The method proposed here allows for fine-grained and regular monitoring of some species of interest based on opportunistic observations. More in-depth investigation of the typology of the observations and the sampling bias should help improve the approach in the future.

Linking an ecosystem model and a landscape model to study forest species response to climate warming

Science.gov (United States)

Hong S. He; David J. Mladenoff; Thomas R. Crow

1999-01-01

No single model can address forest change from single tree to regional scales. We discuss a framework linking an ecosystem process model {LINKAGES) with a spatial landscape model (LANDIS) to examine forest species responses to climate warming for a large, heterogeneous landscape in northern Wisconsin, USA. Individual species response at the ecosystem scale was...

Do laboratory species protect endangered species? Interspecies variation in responses to 17β-estradiol, a model endocrine active compound

Science.gov (United States)

Jorgenson, Zachary G.; Buhl, Kevin J.; Bartell, Stephen E.; Schoenfuss, Heiko L.

2015-01-01

Although the effects of estrogens on model laboratory species are well documented, their utility as surrogates for other species, including those listed as endangered, are less clear. Traditionally, conservation policies are evaluated based on model organism responses but are intended to protect all species in an environment. We tested the hypothesis that the endangered Rio Grande silvery minnow (Hybognathus amarus) is more vulnerable to endocrine disruption—as assessed through its larval predator-escape performance, survival, juvenile sex ratios, and whole-body vitellogenin concentration—than the commonly used toxicological model species fathead minnow (Pimephales promelas) and the bluegill sunfish (Lepomis macrochirus). Fish were exposed concurrently for 21 days to the model endocrine active compound (EAC) 17ß-estradiol (E2) at 10 ng E2/L and 30 ng E2/L in a flow-through system using reconstituted water that simulated the physicochemical conditions of the Middle Rio Grande in New Mexico, USA. No significant differences were observed between the fathead and silvery minnow in larval predator-escape response or juvenile sex ratio. Rio Grande silvery minnow survival decreased significantly at day 14 compared with the other two species; by day 21, both cyprinid species (silvery minnow and fathead minnow) exhibited a significant decrease in survival compared with bluegill sunfish, a member of the family Centrarchidae. Male Rio Grande silvery minnow showed a significant increase in whole-body vitellogenin concentration in the 10 ng/L treatment, whereas fathead minnow and bluegill sunfish showed no significant increases in vitellogenin concentrations across treatments. Our study showed response differences to estrogen exposures between the two cyprinid species and further divergence in responses between the families Cyprinidae and Centrarchidae. These results suggest that commonly used laboratory model organisms may be less sensitive to EACs than the endangered

Do laboratory species protect endangered species? Interspecies variation in responses to 17β-estradiol, a model endocrine active compound.

Science.gov (United States)

Jorgenson, Z G; Buhl, K; Bartell, S E; Schoenfuss, H L

2015-01-01

Although the effects of estrogens on model laboratory species are well documented, their utility as surrogates for other species, including those listed as endangered, are less clear. Traditionally, conservation policies are evaluated based on model organism responses but are intended to protect all species in an environment. We tested the hypothesis that the endangered Rio Grande silvery minnow (Hybognathus amarus) is more vulnerable to endocrine disruption-as assessed through its larval predator-escape performance, survival, juvenile sex ratios, and whole-body vitellogenin concentration-than the commonly used toxicological model species fathead minnow (Pimephales promelas) and the bluegill sunfish (Lepomis macrochirus). Fish were exposed concurrently for 21 days to the model endocrine active compound (EAC) 17ß-estradiol (E2) at 10 ng E2/L and 30 ng E2/L in a flow-through system using reconstituted water that simulated the physicochemical conditions of the Middle Rio Grande in New Mexico, USA. No significant differences were observed between the fathead and silvery minnow in larval predator-escape response or juvenile sex ratio. Rio Grande silvery minnow survival decreased significantly at day 14 compared with the other two species; by day 21, both cyprinid species (silvery minnow and fathead minnow) exhibited a significant decrease in survival compared with bluegill sunfish, a member of the family Centrarchidae. Male Rio Grande silvery minnow showed a significant increase in whole-body vitellogenin concentration in the 10 ng/L treatment, whereas fathead minnow and bluegill sunfish showed no significant increases in vitellogenin concentrations across treatments. Our study showed response differences to estrogen exposures between the two cyprinid species and further divergence in responses between the families Cyprinidae and Centrarchidae. These results suggest that commonly used laboratory model organisms may be less sensitive to EACs than the endangered Rio

Modeling the Distribution of Rare or Cryptic Bird Species of Taiwan

Directory of Open Access Journals (Sweden)

Tsai-Yu Wu

2012-12-01

Full Text Available For the study of the macroecology and conservation of Taiwan’s birds, there was an urgent need to develop distribution models of bird species whose distribution had never before been modeled. Therefore, we here model the distributions of 27 mostly rare and cryptic breeding bird species using a statistical approach which has been shown to be especially reliable for modeling species with a low sample size of presence localities, namely the maximum entropy (Maxent modeling technique. For this purpose, we began with a dedicated attempt to collate as much high-quality distributional data as possible, assembling databases from several scientific reports, contacting individual data recorders and searching publicly accessible database, the internet and the available literature. This effort resulted in 2022 grid cells of 1 × 1 km size being associated with a presence record for one of the 27 species. These records and 10 pre-selected environmental variables were then used to model each species’ probability distribution which we show here with all grid cells below the lowest presence threshold being converted to zeros. We then in detail discuss the interpretation and applicability of these distributions, whereby we pay close attention to habitat requirements, the intactness and fragmentation of their habitat, the general detectability of the species and data reliability. This study is another one in an ongoing series of studies which highlight the usefulness of using large electronic databases and modern analytical methods to help with the monitoring and assessment of Taiwan’s bird species.

Complementary models of tree species-soil relationships in old-growth temperate forests

Science.gov (United States)

Cross, Alison; Perakis, Steven S.

2011-01-01

Ecosystem level studies identify plant soil feed backs as important controls on soil nutrient availability,particularly for nitrogen and phosphorus. Although site and species specific studies of tree species soil relationships are relatively common,comparatively fewer studies consider multiple coexisting speciesin old-growth forests across a range of sites that vary underlying soil fertility. We characterized patterns in forest floor and mineral soil nutrients associated with four common tree species across eight undisturbed old-growth forests in Oregon, USA, and used two complementary conceptual models to assess tree species soil relationships. Plant soil feedbacks that could reinforce sitelevel differences in nutrient availability were assessed using the context dependent relationships model, where by relative species based differences in each soil nutrient divergedorconvergedas nutrient status changed across sites. Tree species soil relationships that did not reflect strong feedbacks were evaluated using a site independent relationships model, where by forest floor and surface mineral soil nutrient tools differed consistently by tree species across sites,without variation in deeper mineral soils. We found that theorganically cycled elements carbon, nitrogen, and phosphorus exhibited context-dependent differences among species in both forest floor and mineral soil, and most of ten followed adivergence model,where by species differences were greatest at high-nutrient sites. These patterns are consistent with the oryemphasizing biotic control of these elements through plant soil feedback mechanisms. Site independent species differences were strongest for pool so if the weather able cations calcium, magnesium, potassium,as well as phosphorus, in mineral soils. Site independent species differences in forest floor nutrients we reattributable too nespecies that displayed significant greater forest floor mass accumulation. Our finding confirmed that site-independent and

A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction

Science.gov (United States)

De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David

2016-01-01

Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. PMID:25281847

A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction.

Science.gov (United States)

De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David

2016-05-01

Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

Use of Occupancy Models to Evaluate Expert Knowledge-based Species-Habitat Relationships

Directory of Open Access Journals (Sweden)

Monica N. Iglecia

2012-12-01

Full Text Available Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens and Brown-headed Nuthatch (Sitta pusilla, occupancy was strongly influenced by vegetation types classified as "optimal habitat" by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

Equation of state experiments and theory relevant to planetary modelling

International Nuclear Information System (INIS)

Ross, M.; Graboske, H.C. Jr.; Nellis, W.J.

1981-01-01

In recent years there have been a number of static and shockwave experiments on the properties of planetary materials. The highest pressure measurements, and the ones most relevant to planetary modelling, have been obtained by shock compression. Of particular interest to the Jovian group are results for H 2 , H 2 O, CH 4 and NH 3 . Although the properties of metallic hydrogen have not been measured, they have been the subject of extensive calculations. In addition recent shock wave experiments on iron report to have detected melting under Earth core conditions. From this data theoretical models have been developed for computing the equations of state of materials used in planetary studies. A compelling feature that has followed from the use of improved material properties is a simplification in the planetary models. (author)

Relevant Criteria for Testing the Quality of Models for Turbulent Wind Speed Fluctuations

DEFF Research Database (Denmark)

Frandsen, Sten Tronæs; Ejsing Jørgensen, Hans; Sørensen, John Dalsgaard

2008-01-01

Seeking relevant criteria for testing the quality of turbulence models, the scale of turbulence and the gust factor have been estimated from data and compared with predictions from first-order models of these two quantities. It is found that the mean of the measured length scales is approximately...... 10% smaller than the IEC model for wind turbine hub height levels. The mean is only marginally dependent on trends in time series. It is also found that the coefficient of variation of the measured length scales is about 50%. 3  s and 10  s preaveraging of wind speed data are relevant for megawatt......-size wind turbines when seeking wind characteristics that correspond to one blade and the entire rotor, respectively. For heights exceeding 50-60  m, the gust factor increases with wind speed. For heights larger than 60-80  m, present assumptions on the value of the gust factor are significantly...

Establishing endangered species recovery criteria using predictive simulation modeling

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McGowan, Conor P.; Catlin, Daniel H.; Shaffer, Terry L.; Gratto-Trevor, Cheri L.; Aron, Carol

2014-01-01

Listing a species under the Endangered Species Act (ESA) and developing a recovery plan requires U.S. Fish and Wildlife Service to establish specific and measurable criteria for delisting. Generally, species are listed because they face (or are perceived to face) elevated risk of extinction due to issues such as habitat loss, invasive species, or other factors. Recovery plans identify recovery criteria that reduce extinction risk to an acceptable level. It logically follows that the recovery criteria, the defined conditions for removing a species from ESA protections, need to be closely related to extinction risk. Extinction probability is a population parameter estimated with a model that uses current demographic information to project the population into the future over a number of replicates, calculating the proportion of replicated populations that go extinct. We simulated extinction probabilities of piping plovers in the Great Plains and estimated the relationship between extinction probability and various demographic parameters. We tested the fit of regression models linking initial abundance, productivity, or population growth rate to extinction risk, and then, using the regression parameter estimates, determined the conditions required to reduce extinction probability to some pre-defined acceptable threshold. Binomial regression models with mean population growth rate and the natural log of initial abundance were the best predictors of extinction probability 50 years into the future. For example, based on our regression models, an initial abundance of approximately 2400 females with an expected mean population growth rate of 1.0 will limit extinction risk for piping plovers in the Great Plains to less than 0.048. Our method provides a straightforward way of developing specific and measurable recovery criteria linked directly to the core issue of extinction risk. Published by Elsevier Ltd.

Utility of population models to reduce uncertainty and increase value relevance in ecological risk assessments of pesticides: an example based on acute mortality data for daphnids.

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Hanson, Niklas; Stark, John D

2012-04-01

Traditionally, ecological risk assessments (ERA) of pesticides have been based on risk ratios, where the predicted concentration of the chemical is compared to the concentration that causes biological effects. The concentration that causes biological effect is mostly determined from laboratory experiments using endpoints on the level of the individual (e.g., mortality and reproduction). However, the protection goals are mostly defined at the population level. To deal with the uncertainty in the necessary extrapolations, safety factors are used. Major disadvantages with this simplified approach is that it is difficult to relate a risk ratio to the environmental protection goals, and that the use of fixed safety factors can result in over- as well as underprotective assessments. To reduce uncertainty and increase value relevance in ERA, it has been argued that population models should be used more frequently. In the present study, we have used matrix population models for 3 daphnid species (Ceriodaphnia dubia, Daphnia magna, and D. pulex) to reduce uncertainty and increase value relevance in the ERA of a pesticide (spinosad). The survival rates in the models were reduced in accordance with data from traditional acute mortality tests. As no data on reproductive effects were available, the conservative assumption that no reproduction occurred during the exposure period was made. The models were used to calculate the minimum population size and the time to recovery. These endpoints can be related to the European Union (EU) protection goals for aquatic ecosystems in the vicinity of agricultural fields, which state that reversible population level effects are acceptable if there is recovery within an acceptable (undefined) time frame. The results of the population models were compared to the acceptable (according to EU documents) toxicity exposure ratio (TER) that was based on the same data. At the acceptable TER, which was based on the most sensitive species (C. dubia

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

Science.gov (United States)

Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

2016-01-01

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied

Presence-only Species Distribution Modeling for King Mackerel (Scomberomorus cavalla) and its 31 Prey Species in the Gulf of Mexico

Science.gov (United States)

Cai, X.; Simons, J.; Carollo, C.; Sterba-Boatwright, B.; Sadovski, A.

2016-02-01

Ecosystem based fisheries management has been broadly recognized throughout the world as a way to achieve better conservation. Therefore, there is a strong need for mapping of multi-species interactions or spatial distributions. Species distribution models are widely applied since information regarding the presence of species is usually only available for limited locations due to the high cost of fisheries surveys. Instead of regular presence and absence records, a large proportion of the fisheries survey data have only presence records. This makes the modeling problem one of one-class classification (presence only), which is much more complex than the regular two-class classification (presence/absence). In this study, four different presence-only species distribution algorithms (Bioclim, Domain, Mahal and Maxent) were applied using 13 environmental parameters (e.g., depth, DO, bottom types) as predictors to model the distribution of king mackerel (Scomberomorus cavalla) and its 31 prey species in the Gulf of Mexico (a total of 13625 georeferenced presence records from OBIS and GBIF were used). Five-fold cross validations were applied for each of the 128 (4 algorithms × 32 species) models. Area under curve (AUC) and correlation coefficient (R) were used to evaluate the model performances. The AUC of the models based on these four algorithms were 0.83±0.14, 0.77±0.16, 0.94±0.06 and 0.94±0.06, respectively; while R for the models were 0.47±0.27, 0.43±0.24, 0.27±0.16 and 0.76±0.16, respectively. Post hoc with Tukey's test showed that AUC for the Maxent-based models were significantly (pMexico to help managers better manage related fisheries resources.

Habitat Modeling of Alien Plant Species at Varying Levels of Occupancy

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Jennifer A. Brown

2012-09-01

Full Text Available Distribution models of invasive plants are very useful tools for conservation management. There are challenges in modeling expanding populations, especially in a dynamic environment, and when data are limited. In this paper, predictive habitat models were assessed for three invasive plant species, at differing levels of occurrence, using two different habitat modeling techniques: logistic regression and maximum entropy. The influence of disturbance, spatial and temporal heterogeneity, and other landscape characteristics is assessed by creating regional level models based on occurrence records from the USDA Forest Service’s Forest Inventory and Analysis database. Logistic regression and maximum entropy models were assessed independently. Ensemble models were developed to combine the predictions of the two analysis approaches to obtain a more robust prediction estimate. All species had strong models with Area Under the receiver operator Curve (AUC of >0.75. The species with the highest occurrence, Ligustrum spp., had the greatest agreement between the models (93%. Lolium arundinaceum had the most disagreement between models at 33% and the lowest AUC values. Overall, the strength of integrative modeling in assessing and understanding habitat modeling was demonstrated.

Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination.

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Yau, Christopher; Holmes, Chris

2011-07-01

We propose a hierarchical Bayesian nonparametric mixture model for clustering when some of the covariates are assumed to be of varying relevance to the clustering problem. This can be thought of as an issue in variable selection for unsupervised learning. We demonstrate that by defining a hierarchical population based nonparametric prior on the cluster locations scaled by the inverse covariance matrices of the likelihood we arrive at a 'sparsity prior' representation which admits a conditionally conjugate prior. This allows us to perform full Gibbs sampling to obtain posterior distributions over parameters of interest including an explicit measure of each covariate's relevance and a distribution over the number of potential clusters present in the data. This also allows for individual cluster specific variable selection. We demonstrate improved inference on a number of canonical problems.

VisTrails SAHM: visualization and workflow management for species habitat modeling

Science.gov (United States)

Morisette, Jeffrey T.; Jarnevich, Catherine S.; Holcombe, Tracy R.; Talbert, Colin B.; Ignizio, Drew A.; Talbert, Marian; Silva, Claudio; Koop, David; Swanson, Alan; Young, Nicholas E.

2013-01-01

The Software for Assisted Habitat Modeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model through the established workflow management and visualization VisTrails software. This paper provides an overview of the VisTrails:SAHM software including a link to the open source code, a table detailing the current SAHM modules, and a simple example modeling an invasive weed species in Rocky Mountain National Park, USA.

What do we gain from simplicity versus complexity in species distribution models?

Science.gov (United States)

Merow, Cory; Smith, Matthew J.; Edwards, Thomas C.; Guisan, Antoine; McMahon, Sean M.; Normand, Signe; Thuiller, Wilfried; Wuest, Rafael O.; Zimmermann, Niklaus E.; Elith, Jane

2014-01-01

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species

Modelling tree ring cellulose δ18O variations in two temperature-sensitive tree species from North and South America

Directory of Open Access Journals (Sweden)

A. Lavergne

2017-11-01

Full Text Available Oxygen isotopes in tree rings (δ18OTR are widely used to reconstruct past climates. However, the complexity of climatic and biological processes controlling isotopic fractionation is not yet fully understood. Here, we use the MAIDENiso model to decipher the variability in δ18OTR of two temperature-sensitive species of relevant palaeoclimatological interest (Picea mariana and Nothofagus pumilio and growing at cold high latitudes in North and South America. In this first modelling study on δ18OTR values in both northeastern Canada (53.86° N and western Argentina (41.10° S, we specifically aim at (1 evaluating the predictive skill of MAIDENiso to simulate δ18OTR values, (2 identifying the physical processes controlling δ18OTR by mechanistic modelling and (3 defining the origin of the temperature signal recorded in the two species. Although the linear regression models used here to predict daily δ18O of precipitation (δ18OP may need to be improved in the future, the resulting daily δ18OP values adequately reproduce observed (from weather stations and simulated (by global circulation model δ18OP series. The δ18OTR values of the two species are correctly simulated using the δ18OP estimation as MAIDENiso input, although some offset in mean δ18OTR levels is observed for the South American site. For both species, the variability in δ18OTR series is primarily linked to the effect of temperature on isotopic enrichment of the leaf water. We show that MAIDENiso is a powerful tool for investigating isotopic fractionation processes but that the lack of a denser isotope-enabled monitoring network recording oxygen fractionation in the soil–vegetation–atmosphere compartments limits our capacity to decipher the processes at play. This study proves that the eco-physiological modelling of δ18OTR values is necessary to interpret the recorded climate signal more reliably.

Political economy models and agricultural policy formation : empirical applicability and relevance for the CAP

OpenAIRE

Zee, van der, F.A.

1997-01-01

This study explores the relevance and applicability of political economy models for the explanation of agricultural policies. Part I (chapters 4-7) takes a general perspective and evaluates the empirical applicability of voting models and interest group models to agricultural policy formation in industrialised market economics. Part II (chapters 8-11) focuses on the empirical applicability of political economy models to agricultural policy formation and agricultural policy developmen...

Drought resilience across ecologically dominant species: An experiment-model integration approach

Science.gov (United States)

Felton, A. J.; Warren, J.; Ricciuto, D. M.; Smith, M. D.

2017-12-01

Poorly understood are the mechanisms contributing to variability in ecosystem recovery following drought. Grasslands of the central U.S. are ecologically and economically important ecosystems, yet are also highly sensitive to drought. Although characteristics of these ecosystems change across gradients of temperature and precipitation, a consistent feature among these systems is the presence of highly abundant, dominant grass species that control biomass production. As a result, the incorporation of these species' traits into terrestrial biosphere models may constrain predictions amid increases in climatic variability. Here we report the results of a modeling-experiment (MODEX) research approach. We investigated the physiological, morphological and growth responses of the dominant grass species from each of the four major grasslands of the central U.S. (ranging from tallgrass prairie to desert grassland) following severe drought. Despite significant differences in baseline values, full recovery in leaf physiological function was evident across species, of which was consistently driven by the production of new leaves. Further, recovery in whole-plant carbon uptake tended to be driven by shifts in allocation from belowground to aboveground structures. However, there was clear variability among species in the magnitude of this dynamic as well as the relative allocation to stem versus leaf production. As a result, all species harbored the physiological capacity to recover from drought, yet we posit that variability in the recovery of whole-plant carbon uptake to be more strongly driven by variability in the sensitivity of species' morphology to soil moisture increases. The next step of this project will be to incorporate these and other existing data on these species and ecosystems into the community land model in an effort to test the sensitivity of this model to these data.

Culturally relevant model program to prevent and reduce agricultural injuries.

Science.gov (United States)

Helitzer, D L; Hathorn, G; Benally, J; Ortega, C

2014-07-01

Limited research has explored pesticide injury prevention among American Indian farmers. In a five-year agricultural intervention, a university-community partnership, including the University of New Mexico School of Medicine, New Mexico State University, Shiprock Area Cooperative Extension Service, and Navajo Nation communities, used a culturally relevant model to introduce and maintain safe use of integrated pest management techniques. We applied the Diffusion of Innovations theory and community-based approaches to tailor health promotion strategies for our intervention. In a longitudinal study with repeated measures, we trained six "model farmers" to be crop management experts in pesticide safety, application, and control. Subsequently, these model farmers worked with 120 farm families randomized into two groups: intervention (Group 1) and delayed intervention (Group 2). Measurements included a walk-through analysis, test of knowledge and attitudes, and yield analysis. Both groups demonstrated improvements in pesticide storage behaviors after training. Test scores regarding safety practices improved significantly: from 57.3 to 72.4 for Group 1 and from 52.6 to 76.3 for Group 2. Group 1 maintained their knowledge and safety practices after the intervention. Attitudes about pesticides and communication of viewpoints changed across the study years. With pesticides and fertilizer, the number of corn ears increased by 56.3% and yield (kg m(-2)) of alfalfa increased by 41.2%. The study combined traditional farming practices with culturally relevant approaches and behavior change theory to affect knowledge, safety practices, attitudes, communication channels, and crop yield. Storage behaviors, use of pesticides and safety and application equipment, and safety practice knowledge changed significantly, as did attitudes about social networking, social support, and the compatibility and relative advantage of pesticides for farms.

Woody-Herbaceous Species Coexistence in Mulga Hillslopes: Modelling Structure and Function

Science.gov (United States)

Soltanjalili, M. J.; Saco, P. M.; Willgoose, G. R.

2016-12-01

The fundamental processes underlying the coexistence of woody and herbaceous species in arid and semi-arid areas have been a topic of intense research during the last few decades. Experimental and modelling studies have both supported and disputed alternative hypotheses explaining this phenomenon. Vegetation models including the key processes that drive coexistence can be used to understand vegetation pattern dynamics and structure under current climate conditions, and to predict changes under future conditions. Here we present work done towards linking the observations to modelling. The model captures woody-herbaceous coexistence along a rainfall gradient characteristic of typical conditions on Mulga ecosystems in Australia. The dynamic vegetation model simulates the spatial dynamics of overland flow, soil moisture and vegetation growth of two species. It incorporates key mechanisms for coexistence and pattern formation, including facilitation by evaporation reduction through shading, and infiltration feedbacks, local and non-local seed dispersal, competition for water uptake. Model outcomes, obtained including diflerent mechanisms, are qualitatively compared to typical vegetation cover patterns in the Australian Mulga bioregion where bush fire is very infrequent and the fate of vegetation cover is mostly determined by intra- and interspecies interactions. Through these comparisons, and by drawing on the large number of recent studies that have delivered new insights into the dynamics of such ecosystems, we identify main mechanisms that need an improved representation in the dynamic vegetation models. We show that a realistic parameterization of the model leads to results which are aligned with the observations reported in the literature. At the lower end of the rainfall gradient woody species coexist with herbaceous species within a sparse banded pattern, while at higher rainfall woody species tend to dominate the landscape.

Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model.

Science.gov (United States)

Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L

2018-05-01

A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.

The relevance of morphology for habitat use and locomotion in two species of wall lizards

Science.gov (United States)

Gomes, Verónica; Carretero, Miguel A.; Kaliontzopoulou, Antigoni

2016-01-01

Understanding if morphological differences between organisms that occupy different environments are associated to differences in functional performance can suggest a functional link between environmental and morphological variation. In this study we examined three components of the ecomorphological paradigm - morphology, locomotor performance and habitat use - using two syntopic wall lizards endemic to the Iberian Peninsula as a case study to establish whether morphological variation is associated with habitat use and determine the potential relevance of locomotor performance for such an association. Differences in habitat use between both lizards matched patterns of morphological variation. Indeed, individuals of Podarcis guadarramae lusitanicus, which are more flattened, used more rocky environments, whereas Podarcis bocagei, which have higher heads, used more vegetation than rocks. These patterns translated into a significant association between morphology and habitat use. Nevertheless, the two species were only differentiated in some of the functional traits quantified, and locomotor performance did not exhibit an association with morphological traits. Our results suggest that the link between morphology and habitat use is mediated by refuge use, rather than locomotor performance, in this system, and advise caution when extrapolating morphology-performance-environment associations across organisms.

Analysis of a Fishery Model with two competing prey species in the presence of a predator species for Optimal Harvesting

Science.gov (United States)

Sutimin; Khabibah, Siti; Munawwaroh, Dita Anis

2018-02-01

A harvesting fishery model is proposed to analyze the effects of the presence of red devil fish population, as a predator in an ecosystem. In this paper, we consider an ecological model of three species by taking into account two competing species and presence of a predator (red devil), the third species, which incorporates the harvesting efforts of each fish species. The stability of the dynamical system is discussed and the existence of biological and bionomic equilibrium is examined. The optimal harvest policy is studied and the solution is derived in the equilibrium case applying Pontryagin's maximal principle. The simulation results is presented to simulate the dynamical behavior of the model and show that the optimal equilibrium solution is globally asymptotically stable. The results show that the optimal harvesting effort is obtained regarding to bionomic and biological equilibrium.

Accounting for selection bias in species distribution models: An econometric approach on forested trees based on structural modeling

Science.gov (United States)

Ay, Jean-Sauveur; Guillemot, Joannès; Martin-StPaul, Nicolas K.; Doyen, Luc; Leadley, Paul

2015-04-01

Species distribution models (SDMs) are widely used to study and predict the outcome of global change on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of application on forested trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8 km). We also compared the output of the SSDM with outputs of a classical SDM in term of bioclimatic response curves and potential distribution under current climate. According to the species and the spatial resolution of the calibration dataset, shapes of bioclimatic response curves the modelled species distribution maps differed markedly between the SSDM and classical SDMs. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents a crucial step to account for economic constraints on tree

Mechanistic species distribution modeling reveals a niche shift during invasion.

Science.gov (United States)

Chapman, Daniel S; Scalone, Romain; Štefanić, Edita; Bullock, James M

2017-06-01

Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern-origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual

Using Environmental DNA to Improve Species Distribution Models for Freshwater Invaders

Directory of Open Access Journals (Sweden)

Teja P. Muha

2017-12-01

Full Text Available Species Distribution Models (SDMs have been reported as a useful tool for the risk assessment and modeling of the pathways of dispersal of freshwater invasive alien species (IAS. Environmental DNA (eDNA is a novel tool that can help detect IAS at their early stage of introduction and additionally improve the data available for a more efficient management. SDMs rely on presence and absence of the species in the study area to infer the predictors affecting species distributions. Presence is verified once a species is detected, but confirmation of absence can be problematic because this depends both on the detectability of the species and the sampling strategy. eDNA is a technique that presents higher detectability and accuracy in comparison to conventional sampling techniques, and can effectively differentiate between presence or absence of specific species or entire communities by using a barcoding or metabarcoding approach. However, a number of potential bias can be introduced during (i sampling, (ii amplification, (iii sequencing, or (iv through the usage of bioinformatics pipelines. Therefore, it is important to report and conduct the field and laboratory procedures in a consistent way, by (i introducing eDNA independent observations, (ii amplifying and sequencing control samples, (iii achieving quality sequence reads by appropriate clean-up steps, (iv controlling primer amplification preferences, (v introducing PCR-free sequence capturing, (vi estimating primer detection capabilities through controlled experiments and/or (vii post-hoc introduction of “site occupancy-detection models.” With eDNA methodology becoming increasingly routine, its use is strongly recommended to retrieve species distributional data for SDMs.

Behavioral Relevance of Species-Specific Vasotocin Anatomy in Gregarious Finches

Directory of Open Access Journals (Sweden)

Aubrey M Kelly

2013-12-01

Full Text Available Despite substantial species differences in the vasotocin/vasopressin (VT/VP circuitry of the medial bed nucleus of the stria terminalis (BSTm and lateral septum (LS; a primary projection target of BSTm VT/VP cells, functional consequences of this variation are poorly known. Previous experiments in the highly gregarious zebra finch (Estrildidae: Taeniopygia guttata demonstrate that BSTm VT neurons promote gregariousness in a male-specific manner and reduce anxiety in both sexes. However, in contrast to the zebra finch, the less gregarious Angolan blue waxbill (Estrildidae: Uraeginthus angolensis exhibits fewer VT-immunoreactive cells in the BSTm as well as differences in receptor distribution across the LS subnuclei, suggesting that knockdown of VT production in the BSTm would produce behavioral effects in Angolan blue waxbills that are distinct from zebra finches. Thus, we here quantified social contact, gregariousness (i.e. preference for the larger of two groups, and anxiety-like behavior following bilateral antisense knockdown of VT production in the BSTm of male and female Angolan blue waxbills. We find that BSTm VT neurons promote social contact, but not gregariousness (as in male zebra finches, and that antisense effects on social contact are significantly stronger in male waxbills than in females. Knockdown of BSTm VT production has no effect on anxiety-like behavior. These data provide novel evidence that species differences in the VT/VP circuitry arising in the BSTm are accompanied by species-specific effects on affiliation behaviors.

Model of Peatland Vegetation Species using HyMap Image and Machine Learning

Science.gov (United States)

Dayuf Jusuf, Muhammad; Danoedoro, Projo; Muljo Sukojo, Bangun; Hartono

2017-12-01

Species Tumih / Parepat (Combretocarpus-rotundatus Mig. Dancer) family Anisophylleaceae and Meranti (Shorea Belangerang, Shorea Teysmanniana Dyer ex Brandis) family Dipterocarpaceae is a group of vegetation species distribution model. Species pioneer is predicted as an indicator of the succession of ecosystem restoration of tropical peatland characteristics and extremely fragile (unique) in the endemic hot spot of Sundaland. Climate change projections and conservation planning are hot topics of current discussion, analysis of alternative approaches and the development of combinations of species projection modelling algorithms through geospatial information systems technology. Approach model to find out the research problem of vegetation level based on the machine learning hybrid method, wavelet and artificial neural networks. Field data are used as a reference collection of natural resource field sample objects and biodiversity assessment. The testing and training ANN data set iterations times 28, achieve a performance value of 0.0867 MSE value is smaller than the ANN training data, above 50%, and spectral accuracy 82.1 %. Identify the location of the sample point position of the Tumih / Parepat vegetation species using HyMap Image is good enough, at least the modelling, design of the species distribution can reach the target in this study. The computation validation rate above 90% proves the calculation can be considered.

Development of Solar Drying Model for Selected Cambodian Fish Species

Science.gov (United States)

Hubackova, Anna; Kucerova, Iva; Chrun, Rithy; Chaloupkova, Petra; Banout, Jan

2014-01-01

A solar drying was investigated as one of perspective techniques for fish processing in Cambodia. The solar drying was compared to conventional drying in electric oven. Five typical Cambodian fish species were selected for this study. Mean solar drying temperature and drying air relative humidity were 55.6°C and 19.9%, respectively. The overall solar dryer efficiency was 12.37%, which is typical for natural convection solar dryers. An average evaporative capacity of solar dryer was 0.049 kg·h−1. Based on coefficient of determination (R 2), chi-square (χ 2) test, and root-mean-square error (RMSE), the most suitable models describing natural convection solar drying kinetics were Logarithmic model, Diffusion approximate model, and Two-term model for climbing perch and Nile tilapia, swamp eel and walking catfish and Channa fish, respectively. In case of electric oven drying, the Modified Page 1 model shows the best results for all investigated fish species except Channa fish where the two-term model is the best one. Sensory evaluation shows that most preferable fish is climbing perch, followed by Nile tilapia and walking catfish. This study brings new knowledge about drying kinetics of fresh water fish species in Cambodia and confirms the solar drying as acceptable technology for fish processing. PMID:25250381

The relevance of existing health communication models in the email age: An

Science.gov (United States)

Fage-Butler, Antoinette Mary; Jensen, Matilde Nisbeth

2015-01-01

Email communication is being integrated relatively slowly into doctor–patient communication. Patients have expressed enthusiasm for the medium, while doctors are generally more reluctant. As existing health communication models have characteristically assumed the co-presence of doctor and patient and primarily reflect medical practitioners’ perspectives, their suitability in relation to email communication and patients’ perspectives warrants further investigation. Following a two-step process and using the methodology of the integrative literature review, 29 articles from 2004–2014 are analysed with the aim of investigating the advantages and disadvantages of the medium of email from the patient’s perspective. The findings are compared to the health communication models of biomedicine, patient-centeredness, patient education and patient empowerment to investigate these models’ relevance for doctor–patient email communication. Results show that patients identify numerous advantages with email communication, including improved convenience and access, more detailed informational exchanges, greater reflection opportunities, freedom from the medical gaze and the potential to level out power imbalances, as well as a number of primarily medium-related disadvantages. The findings indicate that email can counteract some of the communicative problems associated with biomedicine and suggest the ongoing relevance of aspects of the models of patient empowerment, patient-centeredness and patient education for email communication.

Malaria in Africa: vector species' niche models and relative risk maps.

Directory of Open Access Journals (Sweden)

Alexander Moffett

2007-09-01

Full Text Available A central theoretical goal of epidemiology is the construction of spatial models of disease prevalence and risk, including maps for the potential spread of infectious disease. We provide three continent-wide maps representing the relative risk of malaria in Africa based on ecological niche models of vector species and risk analysis at a spatial resolution of 1 arc-minute (9 185 275 cells of approximately 4 sq km. Using a maximum entropy method we construct niche models for 10 malaria vector species based on species occurrence records since 1980, 19 climatic variables, altitude, and land cover data (in 14 classes. For seven vectors (Anopheles coustani, A. funestus, A. melas, A. merus, A. moucheti, A. nili, and A. paludis these are the first published niche models. We predict that Central Africa has poor habitat for both A. arabiensis and A. gambiae, and that A. quadriannulatus and A. arabiensis have restricted habitats in Southern Africa as claimed by field experts in criticism of previous models. The results of the niche models are incorporated into three relative risk models which assume different ecological interactions between vector species. The "additive" model assumes no interaction; the "minimax" model assumes maximum relative risk due to any vector in a cell; and the "competitive exclusion" model assumes the relative risk that arises from the most suitable vector for a cell. All models include variable anthrophilicity of vectors and spatial variation in human population density. Relative risk maps are produced from these models. All models predict that human population density is the critical factor determining malaria risk. Our method of constructing relative risk maps is equally general. We discuss the limits of the relative risk maps reported here, and the additional data that are required for their improvement. The protocol developed here can be used for any other vector-borne disease.

Species Distribution Modelling: Contrasting presence-only models with plot abundance data

NARCIS (Netherlands)

Gomes, Vitor H.F.; Ijff, Stéphanie D.; Raes, Niels; Amaral, Iêda Leão; Salomão, Rafael P.; Coelho, Luiz De Souza; Matos, Francisca Dionízia De Almeida; Castilho, Carolina V.; Filho, Diogenes De Andrade Lima; López, Dairon Cárdenas; Guevara, Juan Ernesto; Magnusson, William E.; Phillips, Oliver L.; Wittmann, Florian; Carim, Marcelo De Jesus Veiga; Martins, Maria Pires; Irume, Mariana Victória; Sabatier, Daniel; Molino, Jean François; Bánki, Olaf S.; Guimarães, José Renan Da Silva; Pitman, Nigel C.A.; Piedade, Maria Teresa Fernandez; Mendoza, Abel Monteagudo; Luize, Bruno Garcia; Venticinque, Eduardo Martins; Novo, Evlyn Márcia Moraes De Leão; Vargas, Percy Núñez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S.; Marimon, Ben Hur; Coronado, Euridice N.Honorio; Feldpausch, Ted R.; Duque, Alvaro; Zartman, Charles Eugene; Arboleda, Nicolás Castaño; Killeen, Timothy J.; Mostacedo, Bonifacio; Vasquez, Rodolfo; Schöngart, Jochen; Assis, Rafael L.; Medeiros, Marcelo Brilhante; Simon, Marcelo Fragomeni; Andrade, Ana; Laurance, William F.; Camargo, José Luís; Demarchi, Layon O.; Laurance, Susan G.W.; Farias, Emanuelle De Sousa; Nascimento, Henrique Eduardo Mendonça; Revilla, Juan David Cardenas; Quaresma, Adriano; Costa, Flavia R.C.; Vieira, Ima Célia Guimarães; Cintra, Bruno Barçante Ladvocat; Castellanos, Hernán; Brienen, Roel; Stevenson, Pablo R.; Feitosa, Yuri; Duivenvoorden, Joost F.; Aymard, Gerardo A.C.; Mogollón, Hugo F.; Targhetta, Natalia; Comiskey, James A.; Vicentini, Alberto; Lopes, Aline; Damasco, Gabriel; Dávila, Nállarett; García-Villacorta, Roosevelt; Levis, Carolina; Schietti, Juliana; Souza, Priscila; Emilio, Thaise; Alonso, Alfonso; Neill, David; Dallmeier, Francisco; Ferreira, Leandro Valle; Araujo-Murakami, Alejandro; Praia, Daniel; Do Amaral, Dário Dantas; Carvalho, Fernanda Antunes; De Souza, Fernanda Coelho; Feeley, Kenneth; Arroyo, Luzmila; Pansonato, Marcelo Petratti; Gribel, Rogerio; Villa, Boris; Licona, Juan Carlos; Fine, Paul V.A.; Cerón, Carlos; Baraloto, Chris; Jimenez, Eliana M.; Stropp, Juliana; Engel, Julien; Silveira, Marcos; Mora, Maria Cristina Peñuela; Petronelli, Pascal; Maas, Paul; Thomas-Caesar, Raquel; Henkel, Terry W.; Daly, Doug; Paredes, Marcos Ríos; Baker, Tim R.; Fuentes, Alfredo; Peres, Carlos A.; Chave, Jerome; Pena, Jose Luis Marcelo; Dexter, Kyle G.; Silman, Miles R.; Jørgensen, Peter Møller; Pennington, Toby; Di Fiore, Anthony; Valverde, Fernando Cornejo; Phillips, Juan Fernando; Rivas-Torres, Gonzalo; Von Hildebrand, Patricio; Van Andel, Tinde R.; Ruschel, Ademir R.; Prieto, Adriana; Rudas, Agustín; Hoffman, Bruce; Vela, César I.A.; Barbosa, Edelcilio Marques; Zent, Egleé L.; Gonzales, George Pepe Gallardo; Doza, Hilda Paulette Dávila; Miranda, Ires Paula De Andrade; Guillaumet, Jean Louis; Pinto, Linder Felipe Mozombite; Bonates, Luiz Carlos De Matos; Silva, Natalino; Gómez, Ricardo Zárate; Zent, Stanford; Gonzales, Therany; Vos, Vincent A.; Malhi, Yadvinder; Oliveira, Alexandre A.; Cano, Angela; Albuquerque, Bianca Weiss; Vriesendorp, Corine; Correa, Diego Felipe; Torre, Emilio Vilanova; Van Der Heijden, Geertje; Ramirez-Angulo, Hirma; Ramos, José Ferreira; Young, Kenneth R.; Rocha, Maira; Nascimento, Marcelo Trindade; Medina, Maria Natalia Umaña; Tirado, Milton; Wang, Ophelia; Sierra, Rodrigo; Torres-Lezama, Armando; Mendoza, Casimiro; Ferreira, Cid; Baider, Cláudia; Villarroel, Daniel; Balslev, Henrik; Mesones, Italo; Giraldo, Ligia Estela Urrego; Casas, Luisa Fernanda; Reategui, Manuel Augusto Ahuite; Linares-Palomino, Reynaldo; Zagt, Roderick; Cárdenas, Sasha; Farfan-Rios, William; Sampaio, Adeilza Felipe; Pauletto, Daniela; Sandoval, Elvis H.Valderrama; Arevalo, Freddy Ramirez; Huamantupa-Chuquimaco, Isau; Garcia-Cabrera, Karina; Hernandez, Lionel; Gamarra, Luis Valenzuela; Alexiades, Miguel N.; Pansini, Susamar; Cuenca, Walter Palacios; Milliken, William; Ricardo, Joana; Lopez-Gonzalez, Gabriela; Pos, Edwin; Ter Steege, Hans

2018-01-01

Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs.

A development of multi-Species mass transport model considering thermodynamic phase equilibrium

DEFF Research Database (Denmark)

Hosokawa, Yoshifumi; Yamada, Kazuo; Johannesson, Björn

2008-01-01

) variation in solid-phase composition when using different types of cement, (ii) physicochemical evaluation of steel corrosion initiation behaviour by calculating the molar ratio of chloride ion to hydroxide ion [Cl]/[OH] in pore solution, (iii) complicated changes of solid-phase composition caused......In this paper, a multi-species mass transport model, which can predict time dependent variation of pore solution and solid-phase composition due to the mass transport into the hardened cement paste, has been developed. Since most of the multi-species models established previously, based...... on the Poisson-Nernst-Planck theory, did not involve the modeling of chemical process, it has been coupled to thermodynamic equilibrium model in this study. By the coupling of thermodynamic equilibrium model, the multi-species model could simulate many different behaviours in hardened cement paste such as: (i...

Family influences on mania-relevant cognitions and beliefs: a cognitive model of mania and reward.

Science.gov (United States)

Chen, Stephen H; Johnson, Sheri L

2012-07-01

The present study proposed and tested a cognitive model of mania and reward. Undergraduates (N = 284; 68.4% female; mean age = 20.99 years, standard deviation ± 3.37) completed measures of family goal setting and achievement values, personal reward-related beliefs, cognitive symptoms of mania, and risk for mania. Correlational analyses and structural equation modeling supported two distinct, but related facets of mania-relevant cognition: stably present reward-related beliefs and state-dependent cognitive symptoms in response to success and positive emotion. Results also indicated that family emphasis on achievement and highly ambitious extrinsic goals were associated with these mania-relevant cognitions. Finally, controlling for other factors, cognitive symptoms in response to success and positive emotion were uniquely associated with lifetime propensity towards mania symptoms. Results support the merit of distinguishing between facets of mania-relevant cognition and the importance of the family in shaping both aspects of cognition. © 2012 Wiley Periodicals, Inc.

Are plant species able to keep pace with the rapidly changing climate?

Directory of Open Access Journals (Sweden)

Sarah Cunze

Full Text Available Future climate change is predicted to advance faster than the postglacial warming. Migration may therefore become a key driver for future development of biodiversity and ecosystem functioning. For 140 European plant species we computed past range shifts since the last glacial maximum and future range shifts for a variety of Intergovernmental Panel on Climate Change (IPCC scenarios and global circulation models (GCMs. Range shift rates were estimated by means of species distribution modelling (SDM. With process-based seed dispersal models we estimated species-specific migration rates for 27 dispersal modes addressing dispersal by wind (anemochory for different wind conditions, as well as dispersal by mammals (dispersal on animal's coat - epizoochory and dispersal by animals after feeding and digestion - endozoochory considering different animal species. Our process-based modelled migration rates generally exceeded the postglacial range shift rates indicating that the process-based models we used are capable of predicting migration rates that are in accordance with realized past migration. For most of the considered species, the modelled migration rates were considerably lower than the expected future climate change induced range shift rates. This implies that most plant species will not entirely be able to follow future climate-change-induced range shifts due to dispersal limitation. Animals with large day- and home-ranges are highly important for achieving high migration rates for many plant species, whereas anemochory is relevant for only few species.

Suberized transport barriers in Arabidopsis, barley and rice roots: From the model plant to crop species.

Science.gov (United States)

Kreszies, Tino; Schreiber, Lukas; Ranathunge, Kosala

2018-02-07

Water is the most important prerequisite for life and plays a major role during uptake and transport of nutrients. Roots are the plant organs that take up the major part of water, from the surrounding soil. Water uptake is related to the root system architecture, root growth, age and species dependent complex developmental changes in the anatomical structures. The latter is mainly attributed to the deposition of suberized barriers in certain layers of cell walls, such as endo- and exodermis. With respect to water permeability, changes in the suberization of roots are most relevant. Water transport or hydraulic conductivity of roots (Lp r ) can be described by the composite transport model and is known to be very variable between plant species and growth conditions and root developmental states. In this review, we summarize how anatomical structures and apoplastic barriers of roots can diversely affect water transport, comparing the model plant Arabidopsis with crop plants, such as barley and rice. Results comparing the suberin amounts and water transport properties indicate that the common assumption that suberin amount negatively correlates with water and solute transport through roots may not always be true. The composition, microstructure and localization of suberin may also have a great impact on the formation of efficient barriers to water and solutes. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Location Criteria Relevant for Sustainability of Social Housing Model

Directory of Open Access Journals (Sweden)

Petković-Grozdanović Nataša

2016-01-01

Full Text Available Social housing models, which had began to develop during the last century, for their only objective had a need to overcome the housing problems of socially vulnerable categories. However, numerous studies have shown that these social categories, because of their low social status, are highly susceptible to various psychological and sociological problems. On the other hand a low level of quality, which was common for social housing dwellings, has further aggravated these problems by initiating trouble behaviours among tenants, affecting social exclusion and segregation. Contemporary social housing models are therefore conceptualized in a way to provide a positive psycho-sociological impact on their tenants. Therefore the planning approach in social housing should be such to: support important functions in daily life routines; promote tolerance and cooperation; influence on a sense of social order and belonging; affect the socialization of the tenant and their integration into the wider community; and improve social cohesion. Analysis of the influential location parameters of immediate and wider social housing environment strive to define the ones relevant to the life quality of social housing tenants and therefore influence on the sustainability of social housing model.

Mechanistic species distribution modelling as a link between physiology and conservation.

Science.gov (United States)

Evans, Tyler G; Diamond, Sarah E; Kelly, Morgan W

2015-01-01

Climate change conservation planning relies heavily on correlative species distribution models that estimate future areas of occupancy based on environmental conditions encountered in present-day ranges. The approach benefits from rapid assessment of vulnerability over a large number of organisms, but can have poor predictive power when transposed to novel environments and reveals little in the way of causal mechanisms that define changes in species distribution or abundance. Having conservation planning rely largely on this single approach also increases the risk of policy failure. Mechanistic models that are parameterized with physiological information are expected to be more robust when extrapolating distributions to future environmental conditions and can identify physiological processes that set range boundaries. Implementation of mechanistic species distribution models requires knowledge of how environmental change influences physiological performance, and because this information is currently restricted to a comparatively small number of well-studied organisms, use of mechanistic modelling in the context of climate change conservation is limited. In this review, we propose that the need to develop mechanistic models that incorporate physiological data presents an opportunity for physiologists to contribute more directly to climate change conservation and advance the field of conservation physiology. We begin by describing the prevalence of species distribution modelling in climate change conservation, highlighting the benefits and drawbacks of both mechanistic and correlative approaches. Next, we emphasize the need to expand mechanistic models and discuss potential metrics of physiological performance suitable for integration into mechanistic models. We conclude by summarizing other factors, such as the need to consider demography, limiting broader application of mechanistic models in climate change conservation. Ideally, modellers, physiologists and

Algorithmic approaches to aid species' delimitation in multidimensional morphospace

Directory of Open Access Journals (Sweden)

Pearson Paul N

2010-06-01

Full Text Available Abstract Background The species is a fundamental unit of biological pattern and process, but its delimitation has proven a ready source of argument and disagreement. Here, we discuss four key steps that utilize statistical thresholds to describe the morphological variability within a sample and hence assess whether there is evidence for one or multiple species. Once the initial set of biologically relevant traits on comparable individuals has been identified, there is no need for the investigator to hypothesise how specimens might be divided among groups, nor the traits on which groups might be separated. Results Principal components are obtained using robust covariance estimates and retained only if they exceed threshold amounts of explanatory power, before model-based clustering is performed on the dimension-reduced space. We apply these steps in an attempt to resolve ongoing debates among taxonomists working on the extinct Eocene planktonic foraminifera Turborotalia, providing statistical evidence for two species shortly before the lineage's extinction near the Eocene/Oligocene boundary. Conclusion By estimating variance robustly (samples containing incipient species are unlikely to be scaled optimally by means and standard deviations and identifying thresholds relevant to a particular system rather than universal standards, the steps of the framework aim to optimize the chances of delineation without imposing pre-conceived patterns onto estimates of species limits.

Development of Multiplexed Marker Sets to Identify the Most Relevant Poplar Species for Breeding

Directory of Open Access Journals (Sweden)

Hilke Schroeder

2017-12-01

Full Text Available Within the genus Populus, about 30 species are classified into six sections, of which some are cross-compatible. Besides naturally occurring hybrids, huge breeding programs have led to a high number of artificially produced hybrids, for which the determination of genetically involved species by morphological characteristics is often difficult. This necessitates the use of molecular markers for the identification of both maternal as well as paternal species, and in the case of complex hybrids, the genealogy. For this reason, we developed new chloroplast and nuclear markers for the differentiation of up to 19 poplar species, with one to 32 individuals per species regularly used in breeding programs based on already known barcoding, other chloroplast regions, and nuclear genes of interest. We developed methods to identify species by either species-specific nucleotide variations or, when no initial information for the species was given, by using a set of markers either in a procedure of exclusion or in a multiplexed marker set. The developed markers can all be used with low-cost equipment, and some can additionally be applied using a genetic analyzer. We combined these markers in multiplexes for a very fast and easy-to-use application for the identification of poplar species and their hybrids.

Applications of species distribution modeling to paleobiology

DEFF Research Database (Denmark)

Svenning, Jens-Christian; Fløjgaard, Camilla; Marske, Katharine Ann

2011-01-01

-Pleistocene megafaunal extinctions, past community assembly, human paleobiogeography, Holocene paleoecology, and even deep-time biogeography (notably, providing insights into biogeographic dynamics >400 million years ago). We discuss important assumptions and uncertainties that affect the SDM approach to paleobiology......Species distribution modeling (SDM: statistical and/or mechanistic approaches to the assessment of range determinants and prediction of species occurrence) offers new possibilities for estimating and studying past organism distributions. SDM complements fossil and genetic evidence by providing (i......) quantitative and potentially high-resolution predictions of the past organism distributions, (ii) statistically formulated, testable ecological hypotheses regarding past distributions and communities, and (iii) statistical assessment of range determinants. In this article, we provide an overview...

Present status on atomic and molecular data relevant to fusion plasma diagnostics and modeling

International Nuclear Information System (INIS)

Tawara, H.

1997-01-01

This issue is the collection of the paper presented status on atomic and molecular data relevant to fusion plasma diagnostics and modeling. The 10 of the presented papers are indexed individually. (J.P.N.)

Predicting plant invasions under climate change: are species distribution models validated by field trials?

Science.gov (United States)

Sheppard, Christine S; Burns, Bruce R; Stanley, Margaret C

2014-09-01

Climate change may facilitate alien species invasion into new areas, particularly for species from warm native ranges introduced into areas currently marginal for temperature. Although conclusions from modelling approaches and experimental studies are generally similar, combining the two approaches has rarely occurred. The aim of this study was to validate species distribution models by conducting field trials in sites of differing suitability as predicted by the models, thus increasing confidence in their ability to assess invasion risk. Three recently naturalized alien plants in New Zealand were used as study species (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla): they originate from warm native ranges, are woody bird-dispersed species and of concern as potential weeds. Seedlings were grown in six sites across the country, differing both in climate and suitability (as predicted by the species distribution models). Seedling growth and survival were recorded over two summers and one or two winter seasons, and temperature and precipitation were monitored hourly at each site. Additionally, alien seedling performances were compared to those of closely related native species (Rhopalostylis sapida, Lophomyrtus bullata and Schefflera digitata). Furthermore, half of the seedlings were sprayed with pesticide, to investigate whether enemy release may influence performance. The results showed large differences in growth and survival of the alien species among the six sites. In the more suitable sites, performance was frequently higher compared to the native species. Leaf damage from invertebrate herbivory was low for both alien and native seedlings, with little evidence that the alien species should have an advantage over the native species because of enemy release. Correlations between performance in the field and predicted suitability of species distribution models were generally high. The projected increase in minimum temperature and reduced

Development of Solar Drying Model for Selected Cambodian Fish Species

Directory of Open Access Journals (Sweden)

Anna Hubackova

2014-01-01

Full Text Available A solar drying was investigated as one of perspective techniques for fish processing in Cambodia. The solar drying was compared to conventional drying in electric oven. Five typical Cambodian fish species were selected for this study. Mean solar drying temperature and drying air relative humidity were 55.6°C and 19.9%, respectively. The overall solar dryer efficiency was 12.37%, which is typical for natural convection solar dryers. An average evaporative capacity of solar dryer was 0.049 kg·h−1. Based on coefficient of determination (R2, chi-square (χ2 test, and root-mean-square error (RMSE, the most suitable models describing natural convection solar drying kinetics were Logarithmic model, Diffusion approximate model, and Two-term model for climbing perch and Nile tilapia, swamp eel and walking catfish and Channa fish, respectively. In case of electric oven drying, the Modified Page 1 model shows the best results for all investigated fish species except Channa fish where the two-term model is the best one. Sensory evaluation shows that most preferable fish is climbing perch, followed by Nile tilapia and walking catfish. This study brings new knowledge about drying kinetics of fresh water fish species in Cambodia and confirms the solar drying as acceptable technology for fish processing.

Cadmium toxicity investigated at the physiological and biophysical levels under environmentally relevant conditions using the aquatic model plant Ceratophyllum demersum

DEFF Research Database (Denmark)

Andresen, Elisa; Kappel, Sophie; Stärk, Hans-Joachim

2016-01-01

Cadmium (Cd) is an important environmental pollutant and is poisonous to most organisms. We aimed to unravel the mechanisms of Cd toxicity in the model water plant Ceratophyllum demersum exposed to low (nM) concentrations of Cd as are present in nature. Experiments were conducted under environmen......Cadmium (Cd) is an important environmental pollutant and is poisonous to most organisms. We aimed to unravel the mechanisms of Cd toxicity in the model water plant Ceratophyllum demersum exposed to low (nM) concentrations of Cd as are present in nature. Experiments were conducted under...... environmentally relevant conditions, including nature-like light and temperature cycles, and a low biomass to water ratio. We measured chlorophyll (Chl) fluorescence kinetics, oxygen exchange, the concentrations of reactive oxygen species and pigments, metal binding to proteins, and the accumulation of starch...... and metals. The inhibition threshold concentration for most parameters was 20 nM. Below this concentration, hardly any stress symptoms were observed. The first site of inhibition was photosynthetic light reactions (the maximal quantum yield of photosystem II (PSII) reaction centre measured as Fv /Fm , light...

Improving niche projections of plant species under climate change: Silene acaulis on the British Isles as a case study

Science.gov (United States)

Ferrarini, Alessandro; Alsafran, Mohammed H. S. A.; Dai, Junhu; Alatalo, Juha M.

2018-04-01

Empirical works to assist in choosing climatically relevant variables in the attempt to predict climate change impacts on plant species are limited. Further uncertainties arise in choice of an appropriate niche model. In this study we devised and tested a sharp methodological framework, based on stringent variable ranking and filtering and flexible model selection, to minimize uncertainty in both niche modelling and successive projection of plant species distributions. We used our approach to develop an accurate, parsimonious model of Silene acaulis (L.) presence/absence on the British Isles and to project its presence/absence under climate change. The approach suggests the importance of (a) defining a reduced set of climate variables, actually relevant to species presence/absence, from an extensive list of climate predictors, and (b) considering climate extremes instead of, or together with, climate averages in projections of plant species presence/absence under future climate scenarios. Our methodological approach reduced the number of relevant climate predictors by 95.23% (from 84 to only 4), while simultaneously achieving high cross-validated accuracy (97.84%) confirming enhanced model performance. Projections produced under different climate scenarios suggest that S. acaulis will likely face climate-driven fast decline in suitable areas on the British Isles, and that upward and northward shifts to occupy new climatically suitable areas are improbable in the future. Our results also imply that conservation measures for S. acaulis based upon assisted colonization are unlikely to succeed on the British Isles due to the absence of climatically suitable habitat, so different conservation actions (seed banks and/or botanical gardens) are needed.

Balancing energy development and conservation: A method utilizing species distribution models

Science.gov (United States)

Jarnevich, C.S.; Laubhan, M.K.

2011-01-01

Alternative energy development is increasing, potentially leading to negative impacts on wildlife populations already stressed by other factors. Resource managers require a scientifically based methodology to balance energy development and species conservation, so we investigated modeling habitat suitability using Maximum Entropy to develop maps that could be used with other information to help site energy developments. We selected one species of concern, the Lesser Prairie-Chicken (LPCH; Tympanuchus pallidicinctus) found on the southern Great Plains of North America, as our case study. LPCH populations have been declining and are potentially further impacted by energy development. We used LPCH lek locations in the state of Kansas along with several environmental and anthropogenic parameters to develop models that predict the probability of lek occurrence across the landscape. The models all performed well as indicated by the high test area under the curve (AUC) scores (all >0.9). The inclusion of anthropogenic parameters in models resulted in slightly better performance based on AUC values, indicating that anthropogenic features may impact LPCH lek habitat suitability. Given the positive model results, this methodology may provide additional guidance in designing future survey protocols, as well as siting of energy development in areas of marginal or unsuitable habitat for species of concern. This technique could help to standardize and quantify the impacts various developments have upon at-risk species. ?? 2011 Springer Science+Business Media, LLC (outside the USA).

Modelling the potential spatial distribution of mosquito species using three different techniques

NARCIS (Netherlands)

Cianci, D.; Hartemink, N.; Ibáñez-Justicia, A.

2015-01-01

Background: Models for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species

Species distribution modeling in regions of high need and limited data: waterfowl of China

Science.gov (United States)

Prosser, Diann J.; Ding, Changqing; Erwin, R. Michael; Mundkur, Taej; Sullivan, Jeffery D.; Ellis, Erle C.

2018-01-01

BackgroundA number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and extent desired, resulting in inefficient use of conservation resources. Such a situation presented itself in our attempt to develop waterfowl distribution models as part of a multi-disciplinary team targeting the control of the highly pathogenic H5N1 avian influenza virus in China.MethodsFaced with limited data, we built species distribution models using a habitat suitability approach for China’s breeding and non-breeding (hereafter, wintering) waterfowl. An extensive review of the literature was used to determine model parameters for habitat modeling. Habitat relationships were implemented in GIS using land cover covariates. Wintering models were validated using waterfowl census data, while breeding models, though developed for many species, were only validated for the one species with sufficient telemetry data available.ResultsWe developed suitability models for 42 waterfowl species (30 breeding and 39 wintering) at 1 km resolution for the extent of China, along with cumulative and genus level species richness maps. Breeding season models showed highest waterfowl suitability in wetlands of the high-elevation west-central plateau and northeastern China. Wintering waterfowl suitability was highest in the lowland regions of southeastern China. Validation measures indicated strong performance in predicting species presence. Comparing our model outputs to China’s protected areas indicated that breeding habitat was generally better covered than wintering habitat, and identified locations for which additional research and protection should be prioritized.ConclusionsThese suitability models are the first available for many of China’s waterfowl species, and have direct utility to conservation and habitat planning and prioritizing management of critically

A HIERARCHICAL SET OF MODELS FOR SPECIES RESPONSE ANALYSIS

NARCIS (Netherlands)

HUISMAN, J; OLFF, H; FRESCO, LFM

Variation in the abundance of species in space and/or time can be caused by a wide range of underlying processes. Before such causes can be analysed we need simple mathematical models which can describe the observed response patterns. For this purpose a hierarchical set of models is presented. These

A hierarchical set of models for species response analysis

NARCIS (Netherlands)

Huisman, J.; Olff, H.; Fresco, L.F.M.

1993-01-01

Variation in the abundance of species in space and/or time can be caused by a wide range of underlying processes. Before such causes can be analysed we need simple mathematical models which can describe the observed response patterns. For this purpose a hierarchical set of models is presented. These

Relevance of multiple spatial scales in habitat models: A case study with amphibians and grasshoppers

Science.gov (United States)

Altmoos, Michael; Henle, Klaus

2010-11-01

Habitat models for animal species are important tools in conservation planning. We assessed the need to consider several scales in a case study for three amphibian and two grasshopper species in the post-mining landscapes near Leipzig (Germany). The two species groups were selected because habitat analyses for grasshoppers are usually conducted on one scale only whereas amphibians are thought to depend on more than one spatial scale. First, we analysed how the preference to single habitat variables changed across nested scales. Most environmental variables were only significant for a habitat model on one or two scales, with the smallest scale being particularly important. On larger scales, other variables became significant, which cannot be recognized on lower scales. Similar preferences across scales occurred in only 13 out of 79 cases and in 3 out of 79 cases the preference and avoidance for the same variable were even reversed among scales. Second, we developed habitat models by using a logistic regression on every scale and for all combinations of scales and analysed how the quality of habitat models changed with the scales considered. To achieve a sufficient accuracy of the habitat models with a minimum number of variables, at least two scales were required for all species except for Bufo viridis, for which a single scale, the microscale, was sufficient. Only for the European tree frog ( Hyla arborea), at least three scales were required. The results indicate that the quality of habitat models increases with the number of surveyed variables and with the number of scales, but costs increase too. Searching for simplifications in multi-scaled habitat models, we suggest that 2 or 3 scales should be a suitable trade-off, when attempting to define a suitable microscale.

Patterns and causes of species richness: a general simulation model for macroecology

DEFF Research Database (Denmark)

Gotelli, Nicholas J; Anderson, Marti J; Arita, Hector T

2009-01-01

to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non-linearity. However, curve-fitting approaches are problematic because most theoretical models...... in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges...... in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell...

New models for estimating the carbon sink capacity of Spanish softwood species

Energy Technology Data Exchange (ETDEWEB)

Ruiz-Peinado, R.; Rio, M. del; Montero, G.

2011-07-01

Quantifying the carbon balance in forests is one of the main challenges in forest management. Forest carbon stocks are usually estimated indirectly through biomass equations applied to forest inventories, frequently considering different tree biomass components. The aim of this study is to develop systems of equations for predicting tree biomass components for the main forest softwood species in Spain: Abies alba Mill., A. pinsapo Boiss., Juniperus thurifera L., Pinus canariensis Sweet ex Spreng., P. halepensis Mill., P. nigra Arn., P. pinaster Ait., P. pinea L., P. sylvestris L., P. uncinata Mill. For each species, a system of additive biomass models was fitted using seemingly unrelated regression. Diameter at the breast height and total height were used as independent variables. Diameter appears in all component models, while tree height was included in the stem component model of all species and in some branch component equations. Total height was included in order to improve biomass estimations at different sites. These biomass models were compared to previously available equations in order to test their accuracy and it was found that they yielded better fitting statistics in all cases. Moreover, the models fulfil the additivity property. We also developed root:shoot ratios in order to determine the partitioning into aboveground and belowground biomass. A number of differences were found between species, with a minimum of 0.183 for A. alba and a maximum of 0.385 for P. uncinata. The mean value for the softwood species studied was 0.265. Since the Spanish National Forest Inventory (NFI) records species, tree diameter and height of sample trees, these biomass models and ratios can be used to accurately estimate carbon stocks from NFI data. (Author) 55 refs.

New models for estimating the carbon sink capacity of Spanish softwood species

International Nuclear Information System (INIS)

Ruiz-Peinado, R.; Rio, M. del; Montero, G.

2011-01-01

Quantifying the carbon balance in forests is one of the main challenges in forest management. Forest carbon stocks are usually estimated indirectly through biomass equations applied to forest inventories, frequently considering different tree biomass components. The aim of this study is to develop systems of equations for predicting tree biomass components for the main forest softwood species in Spain: Abies alba Mill., A. pinsapo Boiss., Juniperus thurifera L., Pinus canariensis Sweet ex Spreng., P. halepensis Mill., P. nigra Arn., P. pinaster Ait., P. pinea L., P. sylvestris L., P. uncinata Mill. For each species, a system of additive biomass models was fitted using seemingly unrelated regression. Diameter at the breast height and total height were used as independent variables. Diameter appears in all component models, while tree height was included in the stem component model of all species and in some branch component equations. Total height was included in order to improve biomass estimations at different sites. These biomass models were compared to previously available equations in order to test their accuracy and it was found that they yielded better fitting statistics in all cases. Moreover, the models fulfil the additivity property. We also developed root:shoot ratios in order to determine the partitioning into aboveground and belowground biomass. A number of differences were found between species, with a minimum of 0.183 for A. alba and a maximum of 0.385 for P. uncinata. The mean value for the softwood species studied was 0.265. Since the Spanish National Forest Inventory (NFI) records species, tree diameter and height of sample trees, these biomass models and ratios can be used to accurately estimate carbon stocks from NFI data. (Author) 55 refs.

A Framework for Spatial Risk Assessments: Potential Impacts of Nonindigenous Invasive Species on Native Species

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Craig R. Allen

2006-06-01

Full Text Available Many populations of wild animals and plants are declining and face increasing threats from habitat fragmentation and loss as well as exposure to stressors ranging from toxicants to diseases to invasive nonindigenous species. We describe and demonstrate a spatially explicit ecological risk assessment that allows for the incorporation of a broad array of information that may influence the distribution of an invasive species, toxicants, or other stressors, and the incorporation of landscape variables that may influence the spread of a species or substances. The first step in our analyses is to develop species models and quantify spatial overlap between stressor and target organisms. Risk is assessed as the product of spatial overlap and a hazard index based on target species vulnerabilities to the stressor of interest. We illustrate our methods with an example in which the stressor is the ecologically destructive nonindigenous ant, Solenopsis invicta, and the targets are two declining vertebrate species in the state of South Carolina, USA. A risk approach that focuses on landscapes and that is explicitly spatial is of particular relevance as remaining undeveloped lands become increasingly uncommon and isolated and more important in the management and recovery of species and ecological systems. Effective ecosystem management includes the control of multiple stressors, including invasive species with large impacts, understanding where those impacts may be the most severe, and implementing management strategies to reduce impacts.

General two-species interacting Lotka-Volterra system: Population dynamics and wave propagation

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Zhu, Haoqi; Wang, Mao-Xiang; Lai, Pik-Yin

2018-05-01

The population dynamics of two interacting species modeled by the Lotka-Volterra (LV) model with general parameters that can promote or suppress the other species is studied. It is found that the properties of the two species' isoclines determine the interaction of species, leading to six regimes in the phase diagram of interspecies interaction; i.e., there are six different interspecific relationships described by the LV model. Four regimes allow for nontrivial species coexistence, among which it is found that three of them are stable, namely, weak competition, mutualism, and predator-prey scenarios can lead to win-win coexistence situations. The Lyapunov function for general nontrivial two-species coexistence is also constructed. Furthermore, in the presence of spatial diffusion of the species, the dynamics can lead to steady wavefront propagation and can alter the population map. Propagating wavefront solutions in one dimension are investigated analytically and by numerical solutions. The steady wavefront speeds are obtained analytically via nonlinear dynamics analysis and verified by numerical solutions. In addition to the inter- and intraspecific interaction parameters, the intrinsic speed parameters of each species play a decisive role in species populations and wave properties. In some regimes, both species can copropagate with the same wave speeds in a finite range of parameters. Our results are further discussed in the light of possible biological relevance and ecological implications.

Testing species distribution models across space and time: high latitude butterflies and recent warming

DEFF Research Database (Denmark)

Eskildsen, Anne; LeRoux, Peter C.; Heikkinen, Risto K.

2013-01-01

changes at expanding range margins can be predicted accurately. Location. Finland. Methods. Using 10-km resolution butterfly atlas data from two periods, 1992–1999 (t1) and 2002–2009 (t2), with a significant between-period temperature increase, we modelled the effects of climatic warming on butterfly...... butterfly distributions under climate change. Model performance was lower with independent compared to non-independent validation and improved when land cover and soil type variables were included, compared to climate-only models. SDMs performed less well for highly mobile species and for species with long......Aim. To quantify whether species distribution models (SDMs) can reliably forecast species distributions under observed climate change. In particular, to test whether the predictive ability of SDMs depends on species traits or the inclusion of land cover and soil type, and whether distributional...

Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

Science.gov (United States)

Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

2014-08-01

Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

BROA: An agent-based model to recommend relevant Learning Objects from Repository Federations adapted to learner profile

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Paula A. Rodríguez

2013-03-01

Full Text Available Learning Objects (LOs are distinguished from traditional educational resources for their easy and quickly availability through Web-based repositories, from which they are accessed through their metadata. In addition, having a user profile allows an educational recommender system to help the learner to find the most relevant LOs based on their needs and preferences. The aim of this paper is to propose an agent-based model so-called BROA to recommend relevant LOs recovered from Repository Federations as well as LOs adapted to learner profile. The model proposed uses both role and service models of GAIA methodology, and the analysis models of the MAS-CommonKADS methodology. A prototype was built based on this model and validated to obtain some assessing results that are finally presented.

The Bifurcation and Control of a Single-Species Fish Population Logistic Model with the Invasion of Alien Species

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Yi Zhang

2014-01-01

Full Text Available The objective of this paper is to study systematically the bifurcation and control of a single-species fish population logistic model with the invasion of alien species based on the theory of singular system and bifurcation. It regards Spartina anglica as an invasive species, which invades the fisheries and aquaculture. Firstly, the stabilities of equilibria in this model are discussed. Moreover, the sufficient conditions for existence of the trans-critical bifurcation and the singularity induced bifurcation are obtained. Secondly, the state feedback controller is designed to eliminate the unexpected singularity induced bifurcation by combining harvested effort with the purification capacity. It obviously inhibits the switch of population and makes the system stable. Finally, the numerical simulation is proposed to show the practical significance of the bifurcation and control from the biological point of view.

The LAILAPS search engine: a feature model for relevance ranking in life science databases.

Science.gov (United States)

Lange, Matthias; Spies, Karl; Colmsee, Christian; Flemming, Steffen; Klapperstück, Matthias; Scholz, Uwe

2010-03-25

Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking. In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. These features are intuitively used by scientists, who briefly screen database entries for potential relevance. The features are both sufficient to estimate the potential relevance, and efficiently quantifiable. The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries. Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.de.

Fit-for-purpose: species distribution model performance depends on evaluation criteria - Dutch Hoverflies as a case study.

Science.gov (United States)

Aguirre-Gutiérrez, Jesús; Carvalheiro, Luísa G; Polce, Chiara; van Loon, E Emiel; Raes, Niels; Reemer, Menno; Biesmeijer, Jacobus C

2013-01-01

Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data

Species-specific differences in adaptive phenotypic plasticity in an ecologically relevant trophic trait: hypertrophic lips in Midas cichlid fishes.

Science.gov (United States)

Machado-Schiaffino, Gonzalo; Henning, Frederico; Meyer, Axel

2014-07-01

The spectacular species richness of cichlids and their diversity in morphology, coloration, and behavior have made them an ideal model for the study of speciation and adaptive evolution. Hypertrophic lips evolved repeatedly and independently in African and Neotropical cichlid radiations. Cichlids with hypertrophic lips forage predominantly in rocky crevices and it has been hypothesized that mechanical stress caused by friction could result in larger lips through phenotypic plasticity. To test the influence of the environment on the size and development of lips, we conducted a series of breeding and feeding experiments on Midas cichlids. Full-sibs of Amphilophus labiatus (thick-lipped) and Amphilophus citrinellus (thin-lipped) each were split into a control group which was fed food from the water column and a treatment group whose food was fixed to substrates. We found strong evidence for phenotypic plasticity on lip area in the thick-lipped species, but not in the thin-lipped species. Intermediate phenotypic values were observed in hybrids from thick- and thin-lipped species reared under "control" conditions. Thus, both a genetic, but also a phenotypic plastic component is involved in the development of hypertrophic lips in Neotropical cichlids. Moreover, species-specific adaptive phenotypic plasticity was found, suggesting that plasticity is selected for in recent thick-lipped species. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Pig BMSCs Transfected with Human TFPI Combat Species Incompatibility and Regulate the Human TF Pathway in Vitro and in a Rodent Model

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Hongchen Ji

2015-05-01

Full Text Available Background: The activation of tissue factor (TF is one of the major reasons for coagulation dysregulation after pig-to-primate xenotransplantation. Tissue factor pathway inhibitor (TFPI is the most important inhibitor of TF. Studies have demonstrated species incompatibility between pig TFPI and human TF. Methods: A pig-to-macaque heterotopic auxiliary liver transplantation model was established to determine the origin of activated TF. Chimeric proteins of human and pig TFPI were constructed to assess the role of Kunitz domains in species incompatibility. Immortalised pig bone marrow mesenchymal stem cells transfected with human TFPI were tested for their ability to inhibit clotting in vitro. Results: TF from recipient was activated early after liver xenotransplantation. Pig TFPI Kunitz domain 2 bound human FXa, but Kunitz domain 1 did not effectively inhibit human TF/FVIIa. Immortalised pig bone marrow mesenchymal cells (BMSCs transfected with human TFPI showed a prolonged recalcification time in vitro and in a rodent model. Conclusion: Recipient TF is relevant to dysregulated coagulation after xenotransplantation. Kunitz domain 1 plays the most important role in species incompatibility between pig TFPI and human TF, and clotting can be inhibited by human TFPI-transfected pig BMSCs. Our study shows a possible way to resolve the incompatibility of pig TFPI.

Alien species recorded in the United Arab Emirates: an initial list of terrestrial and freshwater species

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Pritpal Soorae

2015-10-01

Full Text Available Little is documented on the alien terrestrial and freshwater species in the United Arab Emirates. To address this, an assessment of terrestrial and freshwater alien species was conducted using various techniques such as a questionnaire, fieldwork data, networking with relevant people, and a detailed literature review. The results of the initial assessment show that there are 146 alien species recorded in the following seven major taxonomic groups: invertebrates 49 species, freshwater fish five species, amphibian one species, reptiles six species, birds 71 species, mammals six species and plants eight species. To inform decision makers a full list of the 146 species identified in this assessment is presented. 

Current state of the art for statistical modeling of species distributions [Chapter 16

Science.gov (United States)

Troy M. Hegel; Samuel A. Cushman; Jeffrey Evans; Falk Huettmann

2010-01-01

Over the past decade the number of statistical modelling tools available to ecologists to model species' distributions has increased at a rapid pace (e.g. Elith et al. 2006; Austin 2007), as have the number of species distribution models (SDM) published in the literature (e.g. Scott et al. 2002). Ten years ago, basic logistic regression (Hosmer and Lemeshow 2000)...

Malaria in pregnancy: the relevance of animal models for vaccine development.

Science.gov (United States)

Doritchamou, Justin; Teo, Andrew; Fried, Michal; Duffy, Patrick E

2017-10-06

Malaria during pregnancy due to Plasmodium falciparum or P. vivax is a major public health problem in endemic areas, with P. falciparum causing the greatest burden of disease. Increasing resistance of parasites and mosquitoes to existing tools, such as preventive antimalarial treatments and insecticide-treated bed nets respectively, is eroding the partial protection that they offer to pregnant women. Thus, development of effective vaccines against malaria during pregnancy is an urgent priority. Relevant animal models that recapitulate key features of the pathophysiology and immunology of malaria in pregnant women could be used to accelerate vaccine development. This review summarizes available rodent and nonhuman primate models of malaria in pregnancy, and discusses their suitability for studies of biologics intended to prevent or treat malaria in this vulnerable population.

Relevance of Discrecionary Accruals in Ohlson Model: the Case of Mexico

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Rocío Durán-Vázquez

2012-01-01

Full Text Available This study applied the modified Jones´ model (1991 for selected companies of Mexico. This model aims to assess the impact of Discretionary Accrual Information (DAI on financial reporting statements, in order to identify the value relevance of “earnings quality”. We applied methodological criteria of Chung et al (2005 and Mukit & Iskandar (2009. We analyzed financial information of the 35 stock included in the Index of Prices and Quotations (IPC of the Mexican Stock Exchange (BMV for the period 2000 to 2011. 19 companies met the specifications of the model, for 48 quarters of information. The analysis was done in three parts: first, an analysis of the modified Jones´ model under panel data considerations by using fixed effects and adjustments of performing autocorrelation of order 1; second, a correlation analysis between the residuals of the modified Jones´ model and the return of stock price in 3 annual closings years of study: 2007, 2008 and 2009; and third, we incorporated this variable (DAI in the Ohlson model (of the financial and corporate accounting literature and we tested it with panel data analysis, under fixed effects, throughout the study period.

Controlled comparison of species- and community-level models across novel climates and communities

Science.gov (United States)

Maguire, Kaitlin C.; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.; Ferrier, Simon; Lorenz, David J.

2016-01-01

Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa. PMID:26962143

Linking electricity and water models to assess electricity choices at water-relevant scales

International Nuclear Information System (INIS)

Sattler, S; Rogers, J; Macknick, J; Lopez, A; Yates, D; Flores-Lopez, F

2012-01-01

Hydrology/water management and electricity generation projections have been modeled separately, but there has been little effort in intentionally and explicitly linking the two sides of the water–energy nexus. This paper describes a platform for assessing power plant cooling water withdrawals and consumption under different electricity pathways at geographic and time scales appropriate for both electricity and hydrology/water management. This platform uses estimates of regional electricity generation by the Regional Energy Deployment System (ReEDS) as input to a hydrologic and water management model—the Water Evaluation and Planning (WEAP) system. In WEAP, this electricity use represents thermoelectric cooling water withdrawals and consumption within the broader, regional water resource context. Here we describe linking the electricity and water models, including translating electricity generation results from ReEDS-relevant geographies to the water-relevant geographies of WEAP. The result of this analysis is water use by the electric sector at the regional watershed level, which is used to examine the water resource implications of these electricity pathways. (letter)

Solution of the spatial neutral model yields new bounds on the Amazonian species richness

Science.gov (United States)

Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.

2017-02-01

Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).

Habitat-Based Density Models for Three Cetacean Species off Southern California Illustrate Pronounced Seasonal Differences

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Elizabeth A. Becker

2017-05-01

Full Text Available Managing marine species effectively requires spatially and temporally explicit knowledge of their density and distribution. Habitat-based density models, a type of species distribution model (SDM that uses habitat covariates to estimate species density and distribution patterns, are increasingly used for marine management and conservation because they provide a tool for assessing potential impacts (e.g., from fishery bycatch, ship strikes, anthropogenic sound over a variety of spatial and temporal scales. The abundance and distribution of many pelagic species exhibit substantial seasonal variability, highlighting the importance of predicting density specific to the season of interest. This is particularly true in dynamic regions like the California Current, where significant seasonal shifts in cetacean distribution have been documented at coarse scales. Finer scale (10 km habitat-based density models were previously developed for many cetacean species occurring in this region, but most models were limited to summer/fall. The objectives of our study were two-fold: (1 develop spatially-explicit density estimates for winter/spring to support management applications, and (2 compare model-predicted density and distribution patterns to previously developed summer/fall model results in the context of species ecology. We used a well-established Generalized Additive Modeling framework to develop cetacean SDMs based on 20 California Cooperative Oceanic Fisheries Investigations (CalCOFI shipboard surveys conducted during winter and spring between 2005 and 2015. Models were fit for short-beaked common dolphin (Delphinus delphis delphis, Dall's porpoise (Phocoenoides dalli, and humpback whale (Megaptera novaeangliae. Model performance was evaluated based on a variety of established metrics, including the percentage of explained deviance, ratios of observed to predicted density, and visual inspection of predicted and observed distributions. Final models were

Spatial Complementarity and the Coexistence of Species

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Velázquez, Jorge; Garrahan, Juan P.; Eichhorn, Markus P.

2014-01-01

Coexistence of apparently similar species remains an enduring paradox in ecology. Spatial structure has been predicted to enable coexistence even when population-level models predict competitive exclusion if it causes each species to limit its own population more than that of its competitor. Nevertheless, existing hypotheses conflict with regard to whether clustering favours or precludes coexistence. The spatial segregation hypothesis predicts that in clustered populations the frequency of intra-specific interactions will be increased, causing each species to be self-limiting. Alternatively, individuals of the same species might compete over greater distances, known as heteromyopia, breaking down clusters and opening space for a second species to invade. In this study we create an individual-based model in homogeneous two-dimensional space for two putative sessile species differing only in their demographic rates and the range and strength of their competitive interactions. We fully characterise the parameter space within which coexistence occurs beyond population-level predictions, thereby revealing a region of coexistence generated by a previously-unrecognised process which we term the triadic mechanism. Here coexistence occurs due to the ability of a second generation of offspring of the rarer species to escape competition from their ancestors. We diagnose the conditions under which each of three spatial coexistence mechanisms operates and their characteristic spatial signatures. Deriving insights from a novel metric — ecological pressure — we demonstrate that coexistence is not solely determined by features of the numerically-dominant species. This results in a common framework for predicting, given any pair of species and knowledge of the relevant parameters, whether they will coexist, the mechanism by which they will do so, and the resultant spatial pattern of the community. Spatial coexistence arises from complementary combinations of traits in each

How fear-relevant illusory correlations might develop and persist in anxiety disorders: A model of contributing factors.

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Wiemer, Julian; Pauli, Paul

2016-12-01

Fear-relevant illusory correlations (ICs) are defined as the overestimation of the relationship between a fear-relevant stimulus and aversive consequences. ICs reflect biased cognitions affecting the learning and unlearning of fear in anxiety disorders, and a deeper understanding might help to improve treatment. A model for the maintenance of ICs is proposed that highlights the importance of amplified aversiveness and salience of fear-relevant outcomes, impaired executive contingency monitoring and an availability heuristic. The model explains why ICs are enhanced in high fearful individuals and allows for some implications that might be applied to augment the effectiveness of cognitive behavior therapy, such as emotion regulation and the direction of attention to non-aversive experiences. Finally, we suggest possible future research directions and an alternative measure of ICs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Models of Stress in Nonhuman Primates and Their Relevance for Human Psychopathology and Endocrine Dysfunction

Science.gov (United States)

Meyer, Jerrold S.; Hamel, Amanda F.

2014-01-01

Stressful life events have been linked to the onset of severe psychopathology and endocrine dysfunction in many patients. Moreover, vulnerability to the later development of such disorders can be increased by stress or adversity during development (e.g., childhood neglect, abuse, or trauma). This review discusses the methodological features and results of various models of stress in nonhuman primates in the context of their potential relevance for human psychopathology and endocrine dysfunction, particularly mood disorders and dysregulation of the hypothalamic-pituitary-adrenocortical (HPA) system. Such models have typically examined the effects of stress on the animals' behavior, endocrine function (primarily the HPA and hypothalamic-pituitary-gonadal systems), and, in some cases, immune status. Manipulations such as relocation and/or removal of an animal from its current social group or, alternatively, formation of a new social group can have adverse effects on all of these outcome measures that may be either transient or more persistent depending on the species, sex, and other experimental conditions. Social primates may also experience significant stress associated with their rank in the group's dominance hierarchy. Finally, stress during prenatal development or during the early postnatal period may have long-lasting neurobiological and endocrine effects that manifest in an altered ability to cope behaviorally and physiologically with later challenges. Whereas early exposure to severe stress usually results in deficient coping abilities, certain kinds of milder stressors can promote subsequent resilience in the animal. We conclude that studies of stress in nonhuman primates can model many features of stress exposure in human populations and that such studies can play a valuable role in helping to elucidate the mechanisms underlying the role of stress in human psychopathology and endocrine dysfunction. PMID:25225311

Models of stress in nonhuman primates and their relevance for human psychopathology and endocrine dysfunction.

Science.gov (United States)

Meyer, Jerrold S; Hamel, Amanda F

2014-01-01

Stressful life events have been linked to the onset of severe psychopathology and endocrine dysfunction in many patients. Moreover, vulnerability to the later development of such disorders can be increased by stress or adversity during development (e.g., childhood neglect, abuse, or trauma). This review discusses the methodological features and results of various models of stress in nonhuman primates in the context of their potential relevance for human psychopathology and endocrine dysfunction, particularly mood disorders and dysregulation of the hypothalamic-pituitary-adrenocortical (HPA) system. Such models have typically examined the effects of stress on the animals' behavior, endocrine function (primarily the HPA and hypothalamic-pituitary-gonadal systems), and, in some cases, immune status. Manipulations such as relocation and/or removal of an animal from its current social group or, alternatively, formation of a new social group can have adverse effects on all of these outcome measures that may be either transient or more persistent depending on the species, sex, and other experimental conditions. Social primates may also experience significant stress associated with their rank in the group's dominance hierarchy. Finally, stress during prenatal development or during the early postnatal period may have long-lasting neurobiological and endocrine effects that manifest in an altered ability to cope behaviorally and physiologically with later challenges. Whereas early exposure to severe stress usually results in deficient coping abilities, certain kinds of milder stressors can promote subsequent resilience in the animal. We conclude that studies of stress in nonhuman primates can model many features of stress exposure in human populations and that such studies can play a valuable role in helping to elucidate the mechanisms underlying the role of stress in human psychopathology and endocrine dysfunction. © The Author 2014. Published by Oxford University Press on

Species abundance distributions in neutral models with immigration or mutation and general lifetimes.

Science.gov (United States)

Lambert, Amaury

2011-07-01

We consider a general, neutral, dynamical model of biodiversity. Individuals have i.i.d. lifetime durations, which are not necessarily exponentially distributed, and each individual gives birth independently at constant rate λ. Thus, the population size is a homogeneous, binary Crump-Mode-Jagers process (which is not necessarily a Markov process). We assume that types are clonally inherited. We consider two classes of speciation models in this setting. In the immigration model, new individuals of an entirely new species singly enter the population at constant rate μ (e.g., from the mainland into the island). In the mutation model, each individual independently experiences point mutations in its germ line, at constant rate θ. We are interested in the species abundance distribution, i.e., in the numbers, denoted I(n)(k) in the immigration model and A(n)(k) in the mutation model, of species represented by k individuals, k = 1, 2, . . . , n, when there are n individuals in the total population. In the immigration model, we prove that the numbers (I(t)(k); k ≥ 1) of species represented by k individuals at time t, are independent Poisson variables with parameters as in Fisher's log-series. When conditioning on the total size of the population to equal n, this results in species abundance distributions given by Ewens' sampling formula. In particular, I(n)(k) converges as n → ∞ to a Poisson r.v. with mean γ/k, where γ : = μ/λ. In the mutation model, as n → ∞, we obtain the almost sure convergence of n (-1) A(n)(k) to a nonrandom explicit constant. In the case of a critical, linear birth-death process, this constant is given by Fisher's log-series, namely n(-1) A(n)(k) converges to α(k)/k, where α : = λ/(λ + θ). In both models, the abundances of the most abundant species are briefly discussed.

Wet thermal accumulation modeling of germination of western U.S. rangeland species

Science.gov (United States)

Jennifer K. Rawlins

2009-01-01

The key to stopping high-frequency or catastrophic wildfires in the western U.S. is the successful restoration of burned lands to native plant communities. Developing models of establishment for invasive and native species will help in the selection of species for restoration projects that are able to establish and compete with invasive species given the abiotic...

To eat and not be eaten: modelling resources and safety in multi-species animal groups.

Directory of Open Access Journals (Sweden)

Umesh Srinivasan

Full Text Available Using mixed-species bird flocks as an example, we model the payoffs for two types of species from participating in multi-species animal groups. Salliers feed on mobile prey, are good sentinels and do not affect prey capture rates of gleaners; gleaners feed on prey on substrates and can enhance the prey capture rate of salliers by flushing prey, but are poor sentinels. These functional types are known from various animal taxa that form multi-species associations. We model costs and benefits of joining groups for a wide range of group compositions under varying abundances of two types of prey-prey on substrates and mobile prey. Our model predicts that gleaners and salliers show a conflict of interest in multi-species groups, because gleaners benefit from increasing numbers of salliers in the group, whereas salliers benefit from increasing gleaner numbers. The model also predicts that the limits to size and variability in composition of multi-species groups are driven by the relative abundance of different types of prey, independent of predation pressure. Our model emphasises resources as a primary driver of temporal and spatial group dynamics, rather than reproductive activity or predation per se, which have hitherto been thought to explain patterns of multi-species group formation and cohesion. The qualitative predictions of the model are supported by empirical patterns from both terrestrial and marine multi-species groups, suggesting that similar mechanisms might underlie group dynamics in a range of taxa. The model also makes novel predictions about group dynamics that can be tested using variation across space and time.

Diversity-interaction modeling: estimating contributions of species identities and interactions to ecosystem function

DEFF Research Database (Denmark)

Kirwan, L; Connolly, J; Finn, J A

2009-01-01

to the roles of evenness, functional groups, and functional redundancy. These more parsimonious descriptions can be especially useful in identifying general diversity-function relationships in communities with large numbers of species. We provide an example of the application of the modeling framework......We develop a modeling framework that estimates the effects of species identity and diversity on ecosystem function and permits prediction of the diversity-function relationship across different types of community composition. Rather than just measure an overall effect of diversity, we separately....... These models describe community-level performance and thus do not require separate measurement of the performance of individual species. This flexible modeling approach can be tailored to test many hypotheses in biodiversity research and can suggest the interaction mechanisms that may be acting....

Structural characterisation of medically relevant protein assemblies by integrating mass spectrometry with computational modelling.

Science.gov (United States)

Politis, Argyris; Schmidt, Carla

2018-03-20

Structural mass spectrometry with its various techniques is a powerful tool for the structural elucidation of medically relevant protein assemblies. It delivers information on the composition, stoichiometries, interactions and topologies of these assemblies. Most importantly it can deal with heterogeneous mixtures and assemblies which makes it universal among the conventional structural techniques. In this review we summarise recent advances and challenges in structural mass spectrometric techniques. We describe how the combination of the different mass spectrometry-based methods with computational strategies enable structural models at molecular levels of resolution. These models hold significant potential for helping us in characterizing the function of protein assemblies related to human health and disease. In this review we summarise the techniques of structural mass spectrometry often applied when studying protein-ligand complexes. We exemplify these techniques through recent examples from literature that helped in the understanding of medically relevant protein assemblies. We further provide a detailed introduction into various computational approaches that can be integrated with these mass spectrometric techniques. Last but not least we discuss case studies that integrated mass spectrometry and computational modelling approaches and yielded models of medically important protein assembly states such as fibrils and amyloids. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

Science.gov (United States)

Gogol-Prokurat, Melanie

2011-01-01

If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables

Repository environmental parameters and models/methodologies relevant to assessing the performance of high-level waste packages in basalt, tuff, and salt

Energy Technology Data Exchange (ETDEWEB)

Claiborne, H.C.; Croff, A.G.; Griess, J.C.; Smith, F.J.

1987-09-01

This document provides specifications for models/methodologies that could be employed in determining postclosure repository environmental parameters relevant to the performance of high-level waste packages for the Basalt Waste Isolation Project (BWIP) at Richland, Washington, the tuff at Yucca Mountain by the Nevada Test Site, and the bedded salt in Deaf Smith County, Texas. Guidance is provided on the identify of the relevant repository environmental parameters; the models/methodologies employed to determine the parameters, and the input data base for the models/methodologies. Supporting studies included are an analysis of potential waste package failure modes leading to identification of the relevant repository environmental parameters, an evaluation of the credible range of the repository environmental parameters, and a summary of the review of existing models/methodologies currently employed in determining repository environmental parameters relevant to waste package performance. 327 refs., 26 figs., 19 tabs.

Repository environmental parameters and models/methodologies relevant to assessing the performance of high-level waste packages in basalt, tuff, and salt

International Nuclear Information System (INIS)

Claiborne, H.C.; Croff, A.G.; Griess, J.C.; Smith, F.J.

1987-09-01

This document provides specifications for models/methodologies that could be employed in determining postclosure repository environmental parameters relevant to the performance of high-level waste packages for the Basalt Waste Isolation Project (BWIP) at Richland, Washington, the tuff at Yucca Mountain by the Nevada Test Site, and the bedded salt in Deaf Smith County, Texas. Guidance is provided on the identify of the relevant repository environmental parameters; the models/methodologies employed to determine the parameters, and the input data base for the models/methodologies. Supporting studies included are an analysis of potential waste package failure modes leading to identification of the relevant repository environmental parameters, an evaluation of the credible range of the repository environmental parameters, and a summary of the review of existing models/methodologies currently employed in determining repository environmental parameters relevant to waste package performance. 327 refs., 26 figs., 19 tabs

Modelling planktic foraminifer growth and distribution using an ecophysiological multi-species approach

Directory of Open Access Journals (Sweden)

F. Lombard

2011-04-01

Full Text Available We present an eco-physiological model reproducing the growth of eight foraminifer species (Neogloboquadrina pachyderma, Neogloboquadrina incompta, Neogloboquadrina dutertrei, Globigerina bulloides, Globigerinoides ruber, Globigerinoides sacculifer, Globigerinella siphonifera and Orbulina universa. By using the main physiological rates of foraminifers (nutrition, respiration, symbiotic photosynthesis, this model estimates their growth as a function of temperature, light availability, and food concentration. Model parameters are directly derived or calibrated from experimental observations and only the influence of food concentration (estimated via Chlorophyll-a concentration was calibrated against field observations. Growth rates estimated from the model show positive correlation with observed abundance from plankton net data suggesting close coupling between individual growth and population abundance. This observation was used to directly estimate potential abundance from the model-derived growth. Using satellite data, the model simulate the dominant foraminifer species with a 70.5% efficiency when compared to a data set of 576 field observations worldwide. Using outputs of a biogeochemical model of the global ocean (PISCES instead of satellite images as forcing variables gives also good results, but with lower efficiency (58.9%. Compared to core tops observations, the model also correctly reproduces the relative worldwide abundance and the diversity of the eight species when using either satellite data either PISCES results. This model allows prediction of the season and water depth at which each species has its maximum abundance potential. This offers promising perspectives for both an improved quantification of paleoceanographic reconstructions and for a better understanding of the foraminiferal role in the marine carbon cycle.

Modeling for Endangered-Species Recovery: Gray Wolves in the Western Great Lakes Region

Science.gov (United States)

Jean Fitts Cochrane; Robert G. Haight; Anthony M. Starfield

2003-01-01

The Federal Endangered Species Act is intended to conserve endangered and threatened species and their habitats and to improve the species' status so that they no longer need protection under the Act. In the process of planning the recovery of threatened or endangered species, the U.S. Fish and Wildlife Service increasingly uses demographic models to predict...

The role of advection in a two-species competition model

CERN Document Server

Averill, Isabel; Lou, Yuan

2017-01-01

The effects of weak and strong advection on the dynamics of reaction-diffusion models have long been studied. In contrast, the role of intermediate advection remains poorly understood. For example, concentration phenomena can occur when advection is strong, providing a mechanism for the coexistence of multiple populations, in contrast with the situation of weak advection where coexistence may not be possible. The transition of the dynamics from weak to strong advection is generally difficult to determine. In this work the authors consider a mathematical model of two competing populations in a spatially varying but temporally constant environment, where both species have the same population dynamics but different dispersal strategies: one species adopts random dispersal, while the dispersal strategy for the other species is a combination of random dispersal and advection upward along the resource gradient. For any given diffusion rates the authors consider the bifurcation diagram of positive steady states by u...

Setting maximum sustainable yield targets when yield of one species affects that of other species

DEFF Research Database (Denmark)

Rindorf, Anna; Reid, David; Mackinson, Steve

2012-01-01

species. But how should we prioritize and identify most appropriate targets? Do we prefer to maximize by focusing on total yield in biomass across species, or are other measures targeting maximization of profits or preserving high living qualities more relevant? And how do we ensure that targets remain...

A comparative approach using ecotoxicological methods from single-species bioassays to model ecosystems.

Science.gov (United States)

Haegerbaeumer, Arne; Höss, Sebastian; Ristau, Kai; Claus, Evelyn; Möhlenkamp, Christel; Heininger, Peter; Traunspurger, Walter

2016-12-01

Soft sediments are often hotspots of chemical contamination, and a thorough ecotoxicological assessment of this habitat can help to identify the causes of stress and to improve the health of the respective ecosystems. As an important component of the ecologically relevant meiobenthic fauna, nematodes can be used for sediment assessments, with various assay tools ranging from single-species toxicity tests to field studies. In the present study, microcosms containing sediment were used to investigate direct and indirect effects of zinc on natural nematode assemblages, and acute community toxicity tests considering only direct toxicity were conducted. The responses of the various freshwater nematode species in both approaches were compared with those of Caenorhabditis elegans, determined in standardized tests (ISO 10872). At a median lethal concentration (LC50) of 20 mg Zn/L, C. elegans represented the median susceptibility of 15 examined nematode species examined in the acute community toxicity tests. In the microcosms, Zn affected the nematodes dose-dependently, with changes in species composition first detected at 13 mg Zn/kg to 19 mg Zn/kg sediment dry weight. The observed species sensitivities in the microcosms corresponded better to field observations than to the results of the acute community toxicity tests. Environ Toxicol Chem 2016;35:2987-2997. © 2016 SETAC. © 2016 SETAC.

Microbiological Features and Clinical Relevance of New Species of the Genus Mycobacterium

Science.gov (United States)

2014-01-01

SUMMARY Nontuberculous mycobacteria (NTM) are present in the environment, mainly in water, and are occasionally responsible for opportunistic infections in humans. Despite the fact that NTM are characterized by a moderate pathogenicity, the diseases caused by NTM at various body sites are increasing on a worldwide level. Among over 150 officially recognized NTM species, only two or three dozen are familiar to clinicians, and even to most microbiologists. In this paper, approximately 50 new species described in the last 8 years are reviewed, and their role in human infections is assessed on the basis of reported clinical cases. The small number of reports concerning most of the “new” mycobacterial species is responsible for the widespread conviction that they are very rare. Their role is actually largely underestimated, mainly because they often remain unrecognized and misidentified. Aiming to minimize such bias, emphasis has been placed on more common identification pitfalls. Together with new NTM, new members of the Mycobacterium tuberculosis complex described in the last few years are also an object of the present review. PMID:25278573

Modelling low energy electron and positron tracks in biologically relevant media

International Nuclear Information System (INIS)

Blanco, F.; Munoz, A.; Almeida, D.; Ferreira da Silva, F.; Limao-Vieira, P.; Fuss, M.C.; Sanz, A.G.; Garcia, G.

2013-01-01

This colloquium describes an approach to incorporate into radiation damage models the effect of low and intermediate energy (0-100 eV) electrons and positrons, slowing down in biologically relevant materials (water and representative biomolecules). The core of the modelling procedure is a C++ computing programme named 'Low Energy Particle Track Simulation (LEPTS)', which is compatible with available general purpose Monte Carlo packages. Input parameters are carefully selected from theoretical and experimental cross section data and energy loss distribution functions. Data sources used for this purpose are reviewed showing examples of electron and positron cross section and energy loss data for interactions with different media of increasing complexity: atoms, molecules, clusters and condense matter. Finally, we show how such a model can be used to develop an effective dosimetric tool at the molecular level (i.e. nanodosimetry). Recent experimental developments to study the fragmentation induced in biologically material by charge transfer from neutrals and negative ions are also included. (authors)

Modeling of the spatial distribution of ten endangered bird species in jurisdiction of Corantioquia

International Nuclear Information System (INIS)

Gomez M, Ana Maria; Alvarez, Esteban

2006-01-01

Recently, thanks to advances made in Geographic Information Systems (GIS), techniques have been developed for the construction of models that predict the spatial distribution of species and other attributes of biodiversity. These methods have allowed for the development of objective criteria that are fundamental for making decisions regarding the creation of protected areas systems throughout the world. In this research, the spatial distribution of ten endangered species of birds found within the jurisdiction of CORANTIOQUIA (JDC from here on) was modelled, using GIS techniques. The JDC was divided into 177 squares of 15 x 10 Km and the following variables were quantified within each one: presence or absence of endangered species of birds, rainfall, temperature, sun brightness, relative humidity, day duration, altitude, vegetal cover, slope and primary net productivity. With the help of logistic regression were made predictive models. Based on logistic regressions techniques predictive models were made. These models allow to explain a percentage between 24% and 80% of spatial distribution variability of these species. Those results can help in the identification of valuable zones for the biodiversity conservation. In places where there are neither the time or the economic resources to carry out exhaustive analyses of biodiversity, the models can predict the probable presence of this endangered species

On the well posedness and further regularity of a diffusive three species aquatic model

KAUST Repository

Parshad, R.D.; Upadhyay, R.K.; Thakur, N.K.

2012-01-01

We consider Upadhay's three species aquatic food chain model, with the inclusion of spatial spread. This is a well established food chain model for the interaction of three given aquatic species. It exhibits rich dynamical behavior, including chaos

Using small XML elements to support relevance

NARCIS (Netherlands)

G. Ramirez Camps (Georgina); T.H.W. Westerveld (Thijs); A.P. de Vries (Arjen)

2006-01-01

htmlabstractSmall XML elements are often estimated relevant by the retrieval model but they are not desirable retrieval units. This paper presents a generic model that exploits the information obtained from small elements. We identify relationships between small and relevant elements and use this

Characterization of Non-pertechnetate Species Relevant to the Hanford Tank Waste

Energy Technology Data Exchange (ETDEWEB)

Chatterjee, Sayandev [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Andersen, Amity [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Du, Yingge [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Engelhard, Mark H. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hall, Gabriel B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Levitskaia, Tatiana G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lukens, Wayne W. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shutthanandan, Vaithiyalingam [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Walter, Eric D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Washton, Nancy M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2017-03-27

Among radioactive constituents present in the tank waste stored at the U.S. DOE Hanford Site, technetium-99 (Tc), which is generated from the fission of ²³⁵U and ²³⁹Pu in high yields, presents a unique challenge in that it has a long half-life ( = 292 keV; T1/2 = 2.11105 y) and exists predominately in soluble forms in the liquid supernatant and salt cake fractions of the waste. In the strongly alkaline environments prevalent in most of the tank waste, its dominant chemical form is pertechnetate (TcO₄^-, oxidation state +7). However, attempts to remove Tc from the Hanford tank waste using ion-exchange processes specific to TcO₄^- only met with limited success, particularly when processing tank waste samples containing elevated concentrations of organic complexants. This suggests that a significant fraction of the soluble Tc can be present as low-valent Tc (oxidation state < +7) (non-pertechnetate). The chemical identities of these non-pertechnetate species are poorly understood. Previous analysis of the SY-101 and SY-103 tank waste samples provided strong evidence that non-pertechnetate can be comprised of [fac-Tc(CO)₃]⁺ complexes containing Tc in oxidation state +1 (Lukens et al. 2004). During the last three years, our team has expanded this work and demonstrated that high-ionic-strength solutions typifying tank waste supernatants promote oxidative stability of the [fac-Tc(CO)₃]⁺ species (Rapko et al. 2013a; 2013b; Levitskaia et al. 2014; Chatterjee et al. 2015). Obtained results also suggest possible stabilization of Tc(VI) and potentially Tc(IV) oxidation states in the high-ionic-strength alkaline matrices particularly in the presence of organic chelators, so that Tc(IV, VI) can serve as important redox intermediates facilitating the reduction of Tc(VII) to Tc(I). Designing strategies for effective Tc management, including separation and immobilization

EVALUATING THE NOVEL METHODS ON SPECIES DISTRIBUTION MODELING IN COMPLEX FOREST

Directory of Open Access Journals (Sweden)

C. H. Tu

2012-07-01

Full Text Available The prediction of species distribution has become a focus in ecology. For predicting a result more effectively and accurately, some novel methods have been proposed recently, like support vector machine (SVM and maximum entropy (MAXENT. However, high complexity in the forest, like that in Taiwan, will make the modeling become even harder. In this study, we aim to explore which method is more applicable to species distribution modeling in the complex forest. Castanopsis carlesii (long-leaf chinkapin, LLC, growing widely in Taiwan, was chosen as the target species because its seeds are an important food source for animals. We overlaid the tree samples on the layers of altitude, slope, aspect, terrain position, and vegetation index derived from SOPT-5 images, and developed three models, MAXENT, SVM, and decision tree (DT, to predict the potential habitat of LLCs. We evaluated these models by two sets of independent samples in different site and the effect on the complexity of forest by changing the background sample size (BSZ. In the forest with low complex (small BSZ, the accuracies of SVM (kappa = 0.87 and DT (0.86 models were slightly higher than that of MAXENT (0.84. In the more complex situation (large BSZ, MAXENT kept high kappa value (0.85, whereas SVM (0.61 and DT (0.57 models dropped significantly due to limiting the habitat close to samples. Therefore, MAXENT model was more applicable to predict species’ potential habitat in the complex forest; whereas SVM and DT models would tend to underestimate the potential habitat of LLCs.

Determinants of dermal exposure relevant for exposure modelling in regulatory risk assessment.

Science.gov (United States)

Marquart, J; Brouwer, D H; Gijsbers, J H J; Links, I H M; Warren, N; van Hemmen, J J

2003-11-01

Risk assessment of chemicals requires assessment of the exposure levels of workers. In the absence of adequate specific measured data, models are often used to estimate exposure levels. For dermal exposure only a few models exist, which are not validated externally. In the scope of a large European research programme, an analysis of potential dermal exposure determinants was made based on the available studies and models and on the expert judgement of the authors of this publication. Only a few potential determinants appear to have been studied in depth. Several studies have included clusters of determinants into vaguely defined parameters, such as 'task' or 'cleaning and maintenance of clothing'. Other studies include several highly correlated parameters, such as 'amount of product handled', 'duration of task' and 'area treated', and separation of these parameters to study their individual influence is not possible. However, based on the available information, a number of determinants could clearly be defined as proven or highly plausible determinants of dermal exposure in one or more exposure situation. This information was combined with expert judgement on the scientific plausibility of the influence of parameters that have not been extensively studied and on the possibilities to gather relevant information during a risk assessment process. The result of this effort is a list of determinants relevant for dermal exposure models in the scope of regulatory risk assessment. The determinants have been divided into the major categories 'substance and product characteristics', 'task done by the worker', 'process technique and equipment', 'exposure control measures', 'worker characteristics and habits' and 'area and situation'. To account for the complex nature of the dermal exposure processes, a further subdivision was made into the three major processes 'direct contact', 'surface contact' and 'deposition'.

Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock

Science.gov (United States)

Loman, Zachary G.; Monroe, Adrian; Riffell, Samuel K.; Miller, Darren A.; Vilella, Francisco; Wheat, Bradley R.; Rush, Scott A.; Martin, James A.

2018-01-01

Switchgrass (Panicum virgatum) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (Pinus taeda) plantations in Mississippi, USA.We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species.Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters.Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival.Synthesis and applications. Community models represent a viable

Mode of action human relevance (species concordance) framework: Evolution of the Bradford Hill considerations and comparative analysis of weight of evidence

Science.gov (United States)

Meek, M E (Bette); Palermo, Christine M; Bachman, Ammie N; North, Colin M; Jeffrey Lewis, R

2014-01-01

The mode of action human relevance (MOA/HR) framework increases transparency in systematically considering data on MOA for end (adverse) effects and their relevance to humans. This framework continues to evolve as experience increases in its application. Though the MOA/HR framework is not designed to address the question of “how much information is enough” to support a hypothesized MOA in animals or its relevance to humans, its organizing construct has potential value in considering relative weight of evidence (WOE) among different cases and hypothesized MOA(s). This context is explored based on MOA analyses in published assessments to illustrate the relative extent of supporting data and their implications for dose–response analysis and involved comparisons for chemical assessments on trichloropropane, and carbon tetrachloride with several hypothesized MOA(s) for cancer. The WOE for each hypothesized MOA was summarized in narrative tables based on comparison and contrast of the extent and nature of the supporting database versus potentially inconsistent or missing information. The comparison was based on evolved Bradford Hill considerations rank ordered to reflect their relative contribution to WOE determinations of MOA taking into account increasing experience in their application internationally. This clarification of considerations for WOE determinations as a basis for comparative analysis is anticipated to contribute to increasing consistency in the application of MOA/HR analysis and potentially, transparency in separating science judgment from public policy considerations in regulatory risk assessment. Copyright © 2014. The Authors. Journal of Applied Toxicology Published by John Wiley & Sons Ltd. The potential value of the mode of action (MOA)/human relevance (species concordance) framework in considering relative weight of evidence (WOE) amongst different cases and hypothesized MOA(s) is explored based on the content of several published assessments

Profiles of Dialogue for Relevance

Directory of Open Access Journals (Sweden)

Douglas Walton

2016-12-01

Full Text Available This paper uses argument diagrams, argumentation schemes, and some tools from formal argumentation systems developed in artificial intelligence to build a graph-theoretic model of relevance shown to be applicable (with some extensions as a practical method for helping a third party judge issues of relevance or irrelevance of an argument in real examples. Examples used to illustrate how the method works are drawn from disputes about relevance in natural language discourse, including a criminal trial and a parliamentary debate.

High Resolution Habitat Suitability Modelling For Restricted-Range Hawaiian Alpine Arthropod Species

Science.gov (United States)

Stephenson, N. M.

2016-12-01

Mapping potentially suitable habitat is critical for effective species conservation and management but can be challenging in areas exhibiting complex heterogeneity. An approach that combines non-intrusive spatial data collection techniques and field data can lead to a better understanding of landscapes and species distributions. Nysius wekiuicola, commonly known as the wēkiu bug, is the most studied arthropod species endemic to the Maunakea summit in Hawai`i, yet details about its geographic distribution and habitat use remain poorly understood. To predict the geographic distribution of N. wekiuicola, MaxEnt habitat suitability models were generated from a diverse set of input variables, including fifteen years of species occurrence data, high resolution digital elevation models, surface mineralogy maps derived from hyperspectral remote sensing, and climate data. Model results indicate that elevation (78.2 percent), and the presence of nanocrystalline hematite surface minerals (13.7 percent) had the highest influence, with lesser contributions from aspect, slope, and other surface mineral classes. Climatic variables were not included in the final analysis due to auto-correlation and coarse spatial resolution. Biotic factors relating to predation and competition also likely dictate wēkiu bug capture patterns and influence our results. The wēkiu bug range and habitat suitability models generated as a result of this study will be directly incorporated into management and restoration goals for the summit region and can also be adapted for other arthropod species present, leading to a more holistic understanding of metacommunity dynamics. Key words: Microhabitat, Structure from Motion, Lidar, MaxEnt, Habitat Suitability

Predicting geographic distributions of Phacellodomus species (Aves: Furnariidae in South America based on ecological niche modeling

Directory of Open Access Journals (Sweden)

Maria da Salete Gurgel Costa

2014-08-01

Full Text Available Phacellodomus Reichenbach, 1853, comprises nine species of Furnariids that occur in South America in open and generally dry areas. This study estimated the geographic distributions of Phacellodomus species in South America by ecological niche modeling. Applying maximum entropy method, models were produced for eight species based on six climatic variables and 949 occurrence records. Since highest climatic suitability for Phacellodomus species has been estimated in open and dry areas, the Amazon rainforest areas are not very suitable for these species. Annual precipitation and minimum temperature of the coldest month are the variables that most influence the models. Phacellodomus species occurred in 35 ecoregions of South America. Chaco and Uruguayan savannas were the ecoregions with the highest number of species. Despite the overall connection of Phacellodomus species with dry areas, species such as P. ruber, P. rufifrons, P. ferrugineigula and P. erythrophthalmus occurred in wet forests and wetland ecoregions.

Review: To be or not to be an identifiable model. Is this a relevant question in animal science modelling?

Science.gov (United States)

Muñoz-Tamayo, R; Puillet, L; Daniel, J B; Sauvant, D; Martin, O; Taghipoor, M; Blavy, P

2018-04-01

What is a good (useful) mathematical model in animal science? For models constructed for prediction purposes, the question of model adequacy (usefulness) has been traditionally tackled by statistical analysis applied to observed experimental data relative to model-predicted variables. However, little attention has been paid to analytic tools that exploit the mathematical properties of the model equations. For example, in the context of model calibration, before attempting a numerical estimation of the model parameters, we might want to know if we have any chance of success in estimating a unique best value of the model parameters from available measurements. This question of uniqueness is referred to as structural identifiability; a mathematical property that is defined on the sole basis of the model structure within a hypothetical ideal experiment determined by a setting of model inputs (stimuli) and observable variables (measurements). Structural identifiability analysis applied to dynamic models described by ordinary differential equations (ODEs) is a common practice in control engineering and system identification. This analysis demands mathematical technicalities that are beyond the academic background of animal science, which might explain the lack of pervasiveness of identifiability analysis in animal science modelling. To fill this gap, in this paper we address the analysis of structural identifiability from a practitioner perspective by capitalizing on the use of dedicated software tools. Our objectives are (i) to provide a comprehensive explanation of the structural identifiability notion for the community of animal science modelling, (ii) to assess the relevance of identifiability analysis in animal science modelling and (iii) to motivate the community to use identifiability analysis in the modelling practice (when the identifiability question is relevant). We focus our study on ODE models. By using illustrative examples that include published

New Perspectives on Rodent Models of Advanced Paternal Age: Relevance to Autism

Directory of Open Access Journals (Sweden)

Claire J Foldi

2011-06-01

Full Text Available Offspring of older fathers have an increased risk of various adverse health outcomes, including autism and schizophrenia. With respect to biological mechanisms for this association, there are many more germline cell divisions in the life history of a sperm relative to that of an oocyte. This leads to more opportunities for copy error mutations in germ cells from older fathers. Evidence also suggests that epigenetic patterning in the sperm from older men is altered. Rodent models provide an experimental platform to examine the association between paternal age and brain development. Several rodent models of advanced paternal age (APA have been published with relevance to intermediate phenotypes related to autism. All four published APA models vary in key features creating a lack of consistency with respect to behavioural phenotypes. A consideration of common phenotypes that emerge from these APA-related mouse models may be informative in the exploration of the molecular and neurobiological correlates of APA.

Nostalgia's place among self-relevant emotions.

Science.gov (United States)

van Tilburg, Wijnand A P; Wildschut, Tim; Sedikides, Constantine

2017-07-24

How is nostalgia positioned among self-relevant emotions? We tested, in six studies, which self-relevant emotions are perceived as most similar versus least similar to nostalgia, and what underlies these similarities/differences. We used multidimensional scaling to chart the perceived similarities/differences among self-relevant emotions, resulting in two-dimensional models. The results were revealing. Nostalgia is positioned among self-relevant emotions characterised by positive valence, an approach orientation, and low arousal. Nostalgia most resembles pride and self-compassion, and least resembles embarrassment and shame. Our research pioneered the integration of nostalgia among self-relevant emotions.

Tree Species Abundance Predictions in a Tropical Agricultural Landscape with a Supervised Classification Model and Imbalanced Data

Directory of Open Access Journals (Sweden)

Sarah J. Graves

2016-02-01

Full Text Available Mapping species through classification of imaging spectroscopy data is facilitating research to understand tree species distributions at increasingly greater spatial scales. Classification requires a dataset of field observations matched to the image, which will often reflect natural species distributions, resulting in an imbalanced dataset with many samples for common species and few samples for less common species. Despite the high prevalence of imbalanced datasets in multiclass species predictions, the effect on species prediction accuracy and landscape species abundance has not yet been quantified. First, we trained and assessed the accuracy of a support vector machine (SVM model with a highly imbalanced dataset of 20 tropical species and one mixed-species class of 24 species identified in a hyperspectral image mosaic (350–2500 nm of Panamanian farmland and secondary forest fragments. The model, with an overall accuracy of 62% ± 2.3% and F-score of 59% ± 2.7%, was applied to the full image mosaic (23,000 ha at a 2-m resolution to produce a species prediction map, which suggested that this tropical agricultural landscape is more diverse than what has been presented in field-based studies. Second, we quantified the effect of class imbalance on model accuracy. Model assessment showed a trend where species with more samples were consistently over predicted while species with fewer samples were under predicted. Standardizing sample size reduced model accuracy, but also reduced the level of species over- and under-prediction. This study advances operational species mapping of diverse tropical landscapes by detailing the effect of imbalanced data on classification accuracy and providing estimates of tree species abundance in an agricultural landscape. Species maps using data and methods presented here can be used in landscape analyses of species distributions to understand human or environmental effects, in addition to focusing conservation

Impact relevance and usability of high resolution climate modeling and data

Energy Technology Data Exchange (ETDEWEB)

Arnott, James C. [Aspen Global Change Inst., Basalt, CO (United States)

2016-10-30

The Aspen Global Change Institute hosted a technical science workshop entitled, “Impact Relevance and Usability of High-Resolution Climate Modeling and Datasets,” on August 2-7, 2015 in Aspen, CO. Kate Calvin (Pacific Northwest National Laboratory), Andrew Jones (Lawrence Berkeley National Laboratory) and Jean-François Lamarque (NCAR) served as co-chairs for the workshop. The meeting included the participation of 29 scientists for a total of 145 participant days. Following the workshop, workshop co-chairs authored a meeting report published in Eos on April 27, 2016. Insights from the workshop directly contributed to the formation of a new DOE-supported project co-led by workshop co-chair Andy Jones. A subset of meeting participants continue to work on a publication on institutional innovations that can support the usability of high resolution modeling, among other sources of climate information.

Species Distribution Modelling of Aedes aegypti in two dengue-endemic regions of Pakistan.

Science.gov (United States)

Fatima, Syeda Hira; Atif, Salman; Rasheed, Syed Basit; Zaidi, Farrah; Hussain, Ejaz

2016-03-01

Statistical tools are effectively used to determine the distribution of mosquitoes and to make ecological inferences about the vector-borne disease dynamics. In this study, we utilised species distribution models to understand spatial patterns of Aedes aegypti in two dengue-prevalent regions of Pakistan, Lahore and Swat. Species distribution models can potentially indicate the probability of suitability of Ae. aegypti once introduced to new regions like Swat, where invasion of this species is a recent phenomenon. The distribution of Ae. aegypti was determined by applying the MaxEnt algorithm on a set of potential environmental factors and species sample records. The ecological dependency of species on each environmental variable was analysed using response curves. We quantified the statistical performance of the models based on accuracy assessment and spatial predictions. Our results suggest that Ae. aegypti is widely distributed in Lahore. Human population density and urban infrastructure are primarily responsible for greater probability of mosquito occurrence in this region. In Swat, Ae. aegypti has clumped distribution, where urban patches provide refuge to the species in an otherwise hostile heterogeneous environment and road networks are assumed to have facilitated in passive-mediated dispersal of species. In Pakistan, Ae. aegypti is expanding its range northwards; this could be associated with rapid urbanisation, trade and travel. The main implication of this expansion is that more people are at risk of dengue fever in the northern highlands of Pakistan. © 2016 John Wiley & Sons Ltd.

COMPLEMENTARY APPROACHES TO THE DETERMINATION OF ARSENIC SPECIES RELEVANT TO CONCENTRATED ANIMAL FEEDING OPERATIONS

Science.gov (United States)

Ion-exchange chromatography is the most often used analytical approach for arsenicspeciation, due to the weak-acid nature of several of its species. However, no singletechnique can determine all potentially occurring arsenic species, especially in complexe...

The predictive skill of species distribution models for plankton in a changing climate

DEFF Research Database (Denmark)

Brun, Philipp Georg; Kiørboe, Thomas; Licandro, Priscilla

2016-01-01

Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real-world are rare. Here, we use data from the Continuous Plankton Recorder program, one...... null models, is essential to assess the robustness of projections of marine planktonic species under climate change...

Functionally relevant climate variables for arid lands: Aclimatic water deficit approach for modelling desert shrub distributions

Science.gov (United States)

Thomas E. Dilts; Peter J. Weisberg; Camie M. Dencker; Jeanne C. Chambers

2015-01-01

We have three goals. (1) To develop a suite of functionally relevant climate variables for modelling vegetation distribution on arid and semi-arid landscapes of the Great Basin, USA. (2) To compare the predictive power of vegetation distribution models based on mechanistically proximate factors (water deficit variables) and factors that are more mechanistically removed...

Development of a novel, physiologically relevant cytotoxicity model: Application to the study of chemotherapeutic damage to mesenchymal stromal cells

International Nuclear Information System (INIS)

May, Jennifer E.; Morse, H. Ruth; Xu, Jinsheng; Donaldson, Craig

2012-01-01

There is an increasing need for development of physiologically relevant in-vitro models for testing toxicity, however determining toxic effects of agents which undergo extensive hepatic metabolism can be particularly challenging. If a source of such metabolic enzymes is inadequate within a model system, toxicity from prodrugs may be grossly underestimated. Conversely, the vast majority of agents are detoxified by the liver, consequently toxicity from such agents may be overestimated. In this study we describe the development of a novel in-vitro model, which could be adapted for any toxicology setting. The model utilises HepG2 liver spheroids as a source of metabolic enzymes, which have been shown to more closely resemble human liver than traditional monolayer cultures. A co-culture model has been developed enabling the effect of any metabolised agent on another cell type to be assessed. This has been optimised to enable the study of damaging effects of chemotherapy on mesenchymal stem cells (MSC), the supportive stem cells of the bone marrow. Several optimisation steps were undertaken, including determining optimal culture conditions, confirmation of hepatic P450 enzyme activity and ensuring physiologically relevant doses of chemotherapeutic agents were appropriate for use within the model. The developed model was subsequently validated using several chemotherapeutic agents, both prodrugs and active drugs, with resulting MSC damage closely resembling effects seen in patients following chemotherapy. Minimal modifications would enable this novel co-culture model to be utilised as a general toxicity model, contributing to the drive to reduce animal safety testing and enabling physiologically relevant in-vitro study. -- Highlights: ► An in vitro model was developed for study of drugs requiring hepatic metabolism ► HepG2 spheroids were utilised as a physiologically relevant source of liver enzymes ► The model was optimised to enable study of chemotherapeutic

Development of a novel, physiologically relevant cytotoxicity model: Application to the study of chemotherapeutic damage to mesenchymal stromal cells

Energy Technology Data Exchange (ETDEWEB)

May, Jennifer E., E-mail: Jennifer2.May@uwe.ac.uk; Morse, H. Ruth, E-mail: Ruth.Morse@uwe.ac.uk; Xu, Jinsheng, E-mail: Jinsheng.Xu@uwe.ac.uk; Donaldson, Craig, E-mail: Craig.Donaldson@uwe.ac.uk

2012-09-15

There is an increasing need for development of physiologically relevant in-vitro models for testing toxicity, however determining toxic effects of agents which undergo extensive hepatic metabolism can be particularly challenging. If a source of such metabolic enzymes is inadequate within a model system, toxicity from prodrugs may be grossly underestimated. Conversely, the vast majority of agents are detoxified by the liver, consequently toxicity from such agents may be overestimated. In this study we describe the development of a novel in-vitro model, which could be adapted for any toxicology setting. The model utilises HepG2 liver spheroids as a source of metabolic enzymes, which have been shown to more closely resemble human liver than traditional monolayer cultures. A co-culture model has been developed enabling the effect of any metabolised agent on another cell type to be assessed. This has been optimised to enable the study of damaging effects of chemotherapy on mesenchymal stem cells (MSC), the supportive stem cells of the bone marrow. Several optimisation steps were undertaken, including determining optimal culture conditions, confirmation of hepatic P450 enzyme activity and ensuring physiologically relevant doses of chemotherapeutic agents were appropriate for use within the model. The developed model was subsequently validated using several chemotherapeutic agents, both prodrugs and active drugs, with resulting MSC damage closely resembling effects seen in patients following chemotherapy. Minimal modifications would enable this novel co-culture model to be utilised as a general toxicity model, contributing to the drive to reduce animal safety testing and enabling physiologically relevant in-vitro study. -- Highlights: ► An in vitro model was developed for study of drugs requiring hepatic metabolism ► HepG2 spheroids were utilised as a physiologically relevant source of liver enzymes ► The model was optimised to enable study of chemotherapeutic

Reranking candidate gene models with cross-species comparison for improved gene prediction

Directory of Open Access Journals (Sweden)

Pereira Fernando CN

2008-10-01

Full Text Available Abstract Background Most gene finders score candidate gene models with state-based methods, typically HMMs, by combining local properties (coding potential, splice donor and acceptor patterns, etc. Competing models with similar state-based scores may be distinguishable with additional information. In particular, functional and comparative genomics datasets may help to select among competing models of comparable probability by exploiting features likely to be associated with the correct gene models, such as conserved exon/intron structure or protein sequence features. Results We have investigated the utility of a simple post-processing step for selecting among a set of alternative gene models, using global scoring rules to rerank competing models for more accurate prediction. For each gene locus, we first generate the K best candidate gene models using the gene finder Evigan, and then rerank these models using comparisons with putative orthologous genes from closely-related species. Candidate gene models with lower scores in the original gene finder may be selected if they exhibit strong similarity to probable orthologs in coding sequence, splice site location, or signal peptide occurrence. Experiments on Drosophila melanogaster demonstrate that reranking based on cross-species comparison outperforms the best gene models identified by Evigan alone, and also outperforms the comparative gene finders GeneWise and Augustus+. Conclusion Reranking gene models with cross-species comparison improves gene prediction accuracy. This straightforward method can be readily adapted to incorporate additional lines of evidence, as it requires only a ranked source of candidate gene models.

Fine-spatial scale predictions of understory species using climate- and LiDAR-derived terrain and canopy metrics

Science.gov (United States)

Nijland, Wiebe; Nielsen, Scott E.; Coops, Nicholas C.; Wulder, Michael A.; Stenhouse, Gordon B.

2014-01-01

Food and habitat resources are critical components of wildlife management and conservation efforts. The grizzly bear (Ursus arctos) has diverse diets and habitat requirements particularly for understory plant species, which are impacted by human developments and forest management activities. We use light detection and ranging (LiDAR) data to predict the occurrence of 14 understory plant species relevant to bear forage and compare our predictions with more conventional climate- and land cover-based models. We use boosted regression trees to model each of the 14 understory species across 4435 km2 using occurrence (presence-absence) data from 1941 field plots. Three sets of models were fitted: climate only, climate and basic land and forest covers from Landsat 30-m imagery, and a climate- and LiDAR-derived model describing both the terrain and forest canopy. Resulting model accuracies varied widely among species. Overall, 8 of 14 species models were improved by including the LiDAR-derived variables. For climate-only models, mean annual precipitation and frost-free periods were the most important variables. With inclusion of LiDAR-derived attributes, depth-to-water table, terrain-intercepted annual radiation, and elevation were most often selected. This suggests that fine-scale terrain conditions affect the distribution of the studied species more than canopy conditions.

Stem cell therapy for joint problems using the horse as a clinically relevant animal model

DEFF Research Database (Denmark)

Koch, Thomas Gadegaard; Betts, Dean H.

2007-01-01

of experimentally induced lesions. The horse lends itself as a good animal model of spontaneous joint disorders that are clinically relevant to similar human disorders. Equine stem cell and tissue engineering studies may be financially feasible to principal investigators and small biotechnology companies...

Searching for animal models and potential target species for emerging pathogens: Experience gained from Middle East respiratory syndrome (MERS coronavirus

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Júlia Vergara-Alert

2017-06-01

Full Text Available Emerging and re-emerging pathogens represent a substantial threat to public health, as demonstrated with numerous outbreaks over the past years, including the 2013–2016 outbreak of Ebola virus in western Africa. Coronaviruses are also a threat for humans, as evidenced in 2002/2003 with infection by the severe acute respiratory syndrome coronavirus (SARS-CoV, which caused more than 8000 human infections with 10% fatality rate in 37 countries. Ten years later, a novel human coronavirus (Middle East respiratory syndrome coronavirus, MERS-CoV, associated with severe pneumonia, arose in the Kingdom of Saudi Arabia. Until December 2016, MERS has accounted for more than 1800 cases and 35% fatality rate. Finding an animal model of disease is key to develop vaccines or antivirals against such emerging pathogens and to understand its pathogenesis. Knowledge of the potential role of domestic livestock and other animal species in the transmission of pathogens is of importance to understand the epidemiology of the disease. Little is known about MERS-CoV animal host range. In this paper, experimental data on potential hosts for MERS-CoV is reviewed. Advantages and limitations of different animal models are evaluated in relation to viral pathogenesis and transmission studies. Finally, the relevance of potential new target species is discussed.

Relevant Subspace Clustering

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

2009-01-01

Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace...... clusters. Their results are typically highly redundant, i.e. many clusters are detected multiple times in several projections. In this work, we propose a novel model for relevant subspace clustering (RESCU). We present a global optimization which detects the most interesting non-redundant subspace clusters...... achieves top clustering quality while competing approaches show greatly varying performance....

Metapopulation modelling of riparian tree species persistence in river networks under climate change.

Science.gov (United States)

Van Looy, Kris; Piffady, Jérémy

2017-11-01

Floodplain landscapes are highly fragmented by river regulation resulting in habitat degradation and flood regime perturbation, posing risks to population persistence. Climate change is expected to pose supplementary risks in this context of fragmented landscapes, and especially for river systems adaptation management programs are developed. The association of habitat quality and quantity with the landscape dynamics and resilience to human-induced disturbances is still poorly understood in the context of species survival and colonization processes, but essential to prioritize conservation and restoration actions. We present a modelling approach that elucidates network connectivity and landscape dynamics in spatial and temporal context to identify vital corridors and conservation priorities in the Loire river and its tributaries. Alteration of flooding and flow regimes is believed to be critical to population dynamics in river ecosystems. Still, little is known of critical levels of alteration both spatially and temporally. We applied metapopulation modelling approaches for a dispersal-limited tree species, white elm; and a recruitment-limited tree species, black poplar. In different model steps the connectivity and natural dynamics of the river landscape are confronted with physical alterations (dams/dykes) to species survival and then future scenarios for climatic changes and potential adaptation measures are entered in the model and translated in population persistence over the river basin. For the two tree species we highlighted crucial network zones in relation to habitat quality and connectivity. Where the human impact model already shows currently restricted metapopulation development, climate change is projected to aggravate this persistence perspective substantially. For both species a significant drawback to the basin population is observed, with 1/3 for elm and ¼ for poplar after 25 years already. But proposed adaptation measures prove effective to even

Looking for a relevant potential evapotranspiration model at the watershed scale

Science.gov (United States)

Oudin, L.; Hervieu, F.; Michel, C.; Perrin, C.; Anctil, F.; Andréassian, V.

2003-04-01

In this paper, we try to identify the most relevant approach to calculate Potential Evapotranspiration (PET) for use in a daily watershed model, to try to bring an answer to the following question: "how can we use commonly available atmospheric parameters to represent the evaporative demand at the catchment scale?". Hydrologists generally see the Penman model as the ideal model regarding to its good adequacy with lysimeter measurements and its physically-based formulation. However, in real-world engineering situations, where meteorological stations are scarce, hydrologists are often constrained to use other PET formulae with less data requirements or/and long-term average of PET values (the rationale being that PET is an inherently conservative variable). We chose to test 28 commonly used PET models coupled with 4 different daily watershed models. For each test, we compare both PET input options: actual data and long-term average data. The comparison is made in terms of streamflow simulation efficiency, over a large sample of 308 watersheds. The watersheds are located in France, Australia and the United States of America and represent varied climates. Strikingly, we find no systematic improvements of the watershed model efficiencies when using actual PET series instead of long-term averages. This suggests either that watershed models may not conveniently use the climatic information contained in PET values or that formulae are only awkward indicators of the real PET which watershed models need.

Modelling planktic foraminifer growth and distribution using an ecophysiological multi-species approach

DEFF Research Database (Denmark)

Lombard, Fabien; Labeyrie, L.; Michel, E.

2011-01-01

We present an eco-physiological model reproducing the growth of eight foraminifer species (Neogloboquadrina pachyderma, Neogloboquadrina incompta, Neogloboquadrina dutertrei, Globigerina bulloides, Globigerinoides ruber, Globigerinoides sacculifer, Globigerinella siphonifera and Orbulina universa...... in the marine carbon cycle....... ocean (PISCES) instead of satellite images as forcing variables gives also good results, but with lower efficiency (58.9%). Compared to core tops observations, the model also correctly reproduces the relative worldwide abundance and the diversity of the eight species when using either satellite data...

Determining species expansion and extinction possibilities using probabilistic and graphical models

Directory of Open Access Journals (Sweden)

Chaturvedi Rajesh

2015-03-01

Full Text Available Survival of plant species is governed by a number of functions. The participation of each function in species survival and the impact of the contrary behaviour of the species vary from function to function. The probability of extinction of species varies in all such scenarios and has to be calculated separately. Secondly, species follow different patterns of dispersal and localisation at different stages of occupancy state of the site, therefore, the scenarios of competition for resources with climatic shifts leading to deterioration and loss of biodiversity resulting in extinction needs to be studied. Furthermore, most possible deviations of species from climax community states needs to be calculated before species become extinct due to sudden environmental disruption. Globally, various types of anthropogenic disturbances threaten the diversity of biological systems. The impact of these anthropogenic activities needs to be analysed to identify extinction patterns with respect to these activities. All the analyses mentioned above have been tried to be achieved through probabilistic or graphical models in this study.

Translational genomics from model species Medicago truncatula to crop legume Trifolium pratense

NARCIS (Netherlands)

Lang Chunting, Chunting

2012-01-01

The legume Trifolium pratense (red clover) is an important fodder crop and produces important secondary metabolites. This makes red clover an interesting species. In this thesis, the red clover genome is compared to the legume model species Medicago truncatula, of which the

Uranium(VI) speciation: modelling, uncertainty and relevance to bioavailability models. Application to uranium uptake by the gills of a freshwater bivalve

International Nuclear Information System (INIS)

Denison, F.H.

2004-07-01

The effects of varying solution composition on the interactions between uranium(VI) and excised gills of the freshwater bivalve Corbicula fluminea have been investigated in well defined solution media. A significant reduction in the uptake of uranium was observed on increasing the concentrations of the uranium complexing ligands citrate and carbonate. Saturation kinetics as a function of uranium concentration at a pH value of 5.0 were observed, indicating that the uptake of uranium is a facilitated process, probably involving one or several trans-membrane transport systems. A relatively small change in the uptake of uranium was found as a function of pH (factor of ca. 2), despite the extremely large changes to the solution speciation of uranium within the range of pH investigated (5.0 - 7.5). A comprehensive review of the thermodynamic data relevant to the solution composition domain employed for this study was performed. Estimates of the uncertainties for the formation constants of aqueous uranium(VI) species were integrated into a thermodynamic database. A computer program was written to predict the equilibrium distribution of uranium(VI) in simple aqueous systems, using thermodynamic parameter mean-values. The program was extended to perform Monte Carlo and Quasi Monte Carlo uncertainty analyses, incorporating the thermodynamic database uncertainty estimates, to quantitatively predict the uncertainties inherent in predicting the solution speciation of uranium. The use of thermodynamic equilibrium modelling as a tool for interpreting the bioavailability of uranium(VI) was investigated. Observed uranium(VI) uptake behaviour was interpreted as a function of the predicted changes to the solution speciation of uranium. Different steady-state or pre-equilibrium approaches to modelling uranium uptake were tested. Alternative modelling approaches were also tested, considering the potential changes to membrane transport system activity or sorption characteristics on

A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

Science.gov (United States)

Williams, C.J.; Heglund, P.J.

2009-01-01

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance- based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods. ?? 2008 Springer Science+Business Media, LLC.

Scaling local species-habitat relations to the larger landscape with a hierarchical spatial count model

Science.gov (United States)

Thogmartin, W.E.; Knutson, M.G.

2007-01-01

Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species. ?? 2006 Springer Science+Business Media B.V.

The geography of demography: long-term demographic studies and species distribution models reveal a species border limited by adaptation.

Science.gov (United States)

Eckhart, V M; Geber, M A; Morris, W F; Fabio, E S; Tiffin, P; Moeller, D A

2011-10-01

Potential causes of species' geographic distribution limits fall into two broad classes: (1) limited adaptation across spatially variable environments and (2) limited opportunities to colonize unoccupied areas. Combining demographic studies, analyses of demographic responses to environmental variation, and species distribution models, we investigated the causes of range limits in a model system, the eastern border of the California annual plant Clarkia xantiana ssp. xantiana. Vital rates of 20 populations varied with growing season temperature and precipitation: fruit number and overwinter survival of 1-year-old seeds declined steeply, while current-year seed germination increased modestly along west-to-east gradients in decreasing temperature, decreasing mean precipitation, and increasing variation in precipitation. Long-term stochastic finite rate of increase, λ(s), exhibited a fourfold range and varied among geologic surface materials as well as with temperature and precipitation. Growth rate declined significantly toward the eastern border, falling below 1 in three of the five easternmost populations. Distribution models employing demographically important environmental variables predicted low habitat favorability beyond the eastern border. Models that filtered or weighted population presences by λ(s) predicted steeper eastward declines in favorability and assigned greater roles in setting the distribution to among-year variation in precipitation and to geologic surface material. These analyses reveal a species border likely set by limited adaptation to declining environmental quality.

The interplay of various sources of noise on reliability of species distribution models hinges on ecological specialisation.

Science.gov (United States)

Soultan, Alaaeldin; Safi, Kamran

2017-01-01

Digitized species occurrence data provide an unprecedented source of information for ecologists and conservationists. Species distribution model (SDM) has become a popular method to utilise these data for understanding the spatial and temporal distribution of species, and for modelling biodiversity patterns. Our objective is to study the impact of noise in species occurrence data (namely sample size and positional accuracy) on the performance and reliability of SDM, considering the multiplicative impact of SDM algorithms, species specialisation, and grid resolution. We created a set of four 'virtual' species characterized by different specialisation levels. For each of these species, we built the suitable habitat models using five algorithms at two grid resolutions, with varying sample sizes and different levels of positional accuracy. We assessed the performance and reliability of the SDM according to classic model evaluation metrics (Area Under the Curve and True Skill Statistic) and model agreement metrics (Overall Concordance Correlation Coefficient and geographic niche overlap) respectively. Our study revealed that species specialisation had by far the most dominant impact on the SDM. In contrast to previous studies, we found that for widespread species, low sample size and low positional accuracy were acceptable, and useful distribution ranges could be predicted with as few as 10 species occurrences. Range predictions for narrow-ranged species, however, were sensitive to sample size and positional accuracy, such that useful distribution ranges required at least 20 species occurrences. Against expectations, the MAXENT algorithm poorly predicted the distribution of specialist species at low sample size.

Crack propagation rate modelling for 316SS exposed to PWR-relevant conditions

International Nuclear Information System (INIS)

Vankeerberghen, M.; Weyns, G.; Gavrilov, S.; Martens, B.; Deconinck, J.

2009-01-01

The crack propagation rate of Type 316 stainless steel in boric acid-lithium hydroxide solutions under PWR-relevant conditions was modelled. A film rupture/dissolution/repassivation mechanism is assumed and extended to cold worked materials by including a stress-dependent bare metal dissolution current density. The chemical and electrochemical conditions within the crack are calculated by finite element calculations, an analytical expression is used for the crack-tip strain rate and the crack-tip stress is assumed equal to 2.5 times the yield stress (plane-strain). First the model was calibrated against a literature published data set. Afterwards, the influence of various variables - dissolved hydrogen, boric acid and lithium hydroxide content, stress intensity, crack length, temperature, flow rate - was studied. Finally, other published crack growth rate tests were modelled and the calculated crack growth rates were found to be in reasonable agreement with the reported ones

Single-locus species delimitation: a test of the mixed Yule-coalescent model, with an empirical application to Philippine round-leaf bats.

Science.gov (United States)

Esselstyn, Jacob A; Evans, Ben J; Sedlock, Jodi L; Anwarali Khan, Faisal Ali; Heaney, Lawrence R

2012-09-22

Prospects for a comprehensive inventory of global biodiversity would be greatly improved by automating methods of species delimitation. The general mixed Yule-coalescent (GMYC) was recently proposed as a potential means of increasing the rate of biodiversity exploration. We tested this method with simulated data and applied it to a group of poorly known bats (Hipposideros) from the Philippines. We then used echolocation call characteristics to evaluate the plausibility of species boundaries suggested by GMYC. In our simulations, GMYC performed relatively well (errors in estimated species diversity less than 25%) when the product of the haploid effective population size (N(e)) and speciation rate (SR; per lineage per million years) was less than or equal to 10(5), while interspecific variation in N(e) was twofold or less. However, at higher but also biologically relevant values of N(e) × SR and when N(e) varied tenfold among species, performance was very poor. GMYC analyses of mitochondrial DNA sequences from Philippine Hipposideros suggest actual diversity may be approximately twice the current estimate, and available echolocation call data are mostly consistent with GMYC delimitations. In conclusion, we consider the GMYC model useful under some conditions, but additional information on N(e), SR and/or corroboration from independent character data are needed to allow meaningful interpretation of results.

Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence

Directory of Open Access Journals (Sweden)

Chunrong Mi

2017-01-01

Full Text Available Species distribution models (SDMs have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane (Grus monacha, n = 33, White-naped Crane (Grus vipio, n = 40, and Black-necked Crane (Grus nigricollis, n = 75 in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model, Random Forest, CART (Classification and Regression Tree and Maxent (Maximum Entropy Models. In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC and true skill statistic (TSS were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid

Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence.

Science.gov (United States)

Mi, Chunrong; Huettmann, Falk; Guo, Yumin; Han, Xuesong; Wen, Lijia

2017-01-01

Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane ( Grus monacha , n  = 33), White-naped Crane ( Grus vipio , n  = 40), and Black-necked Crane ( Grus nigricollis , n  = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models). In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC) and true skill statistic (TSS)) were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial) ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid

Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts

Science.gov (United States)

Alcaraz-Segura, Domingo; Lomba, Angela; Sousa-Silva, Rita; Nieto-Lugilde, Diego; Alves, Paulo; Georges, Damien; Vicente, Joana R.; Honrado, João P.

2017-05-01

In a world facing rapid environmental changes, anticipating their impacts on biodiversity is of utmost relevance. Remotely-sensed Ecosystem Functional Attributes (EFAs) are promising predictors for Species Distribution Models (SDMs) by offering an early and integrative response of vegetation performance to environmental drivers. Species of high conservation concern would benefit the most from a better ability to anticipate changes in habitat suitability. Here we illustrate how yearly projections from SDMs based on EFAs could reveal short-term changes in potential habitat suitability, anticipating mid-term shifts predicted by climate-change-scenario models. We fitted two sets of SDMs for 41 plant species of conservation concern in the Iberian Peninsula: one calibrated with climate variables for baseline conditions and projected under two climate-change-scenarios (future conditions); and the other calibrated with EFAs for 2001 and projected annually from 2001 to 2013. Range shifts predicted by climate-based models for future conditions were compared to the 2001-2013 trends from EFAs-based models. Projections of EFAs-based models estimated changes (mostly contractions) in habitat suitability that anticipated, for the majority (up to 64%) of species, the mid-term shifts projected by traditional climate-change-scenario forecasting, and showed greater agreement with the business-as-usual scenario than with the sustainable-development one. This study shows how satellite-derived EFAs can be used as meaningful essential biodiversity variables in SDMs to provide early-warnings of range shifts and predictions of short-term fluctuations in suitable conditions for multiple species.

A climate change context for the decline of a foundation tree species in south-western Australia: insights from phylogeography and species distribution modelling.

Science.gov (United States)

Dalmaris, Eleftheria; Ramalho, Cristina E; Poot, Pieter; Veneklaas, Erik J; Byrne, Margaret

2015-11-01

A worldwide increase in tree decline and mortality has been linked to climate change and, where these represent foundation species, this can have important implications for ecosystem functions. This study tests a combined approach of phylogeographic analysis and species distribution modelling to provide a climate change context for an observed decline in crown health and an increase in mortality in Eucalyptus wandoo, an endemic tree of south-western Australia. Phylogeographic analyses were undertaken using restriction fragment length polymorphism analysis of chloroplast DNA in 26 populations across the species distribution. Parsimony analysis of haplotype relationships was conducted, a haplotype network was prepared, and haplotype and nucleotide diversity were calculated. Species distribution modelling was undertaken using Maxent models based on extant species occurrences and projected to climate models of the last glacial maximum (LGM). A structured pattern of diversity was identified, with the presence of two groups that followed a climatic gradient from mesic to semi-arid regions. Most populations were represented by a single haplotype, but many haplotypes were shared among populations, with some having widespread distributions. A putative refugial area with high haplotype diversity was identified at the centre of the species distribution. Species distribution modelling showed high climatic suitability at the LGM and high climatic stability in the central region where higher genetic diversity was found, and low suitability elsewhere, consistent with a pattern of range contraction. Combination of phylogeography and paleo-distribution modelling can provide an evolutionary context for climate-driven tree decline, as both can be used to cross-validate evidence for refugia and contraction under harsh climatic conditions. This approach identified a central refugial area in the test species E. wandoo, with more recent expansion into peripheral areas from where it had

Dynamical behavior of a three species food chain model with Beddington-DeAngelis functional response

International Nuclear Information System (INIS)

Naji, Raid Kamel; Balasim, Alla Tariq

2007-01-01

A three species food chain model with Beddington-DeAngelis functional response is investigated. The local stability analysis is carried out and global behavior is simulated numerically for a biologically feasible choice of parameters. The persistence conditions of a food chain model are established. The bifurcation diagrams are obtained for different parameters of the model after intensive numerical simulations. The results of simulations show that the model could exhibit chaotic dynamics for realistic and biologically feasible parametric values. Finally, the effect of immigration within prey species is investigated. It is observed that adding small amount of constant immigration to prey species stabilize the system

Tackling Biocomplexity with Meta-models for Species Risk Assessment

Directory of Open Access Journals (Sweden)

Philip J. Nyhus

2007-06-01

Full Text Available We describe results of a multi-year effort to strengthen consideration of the human dimension into endangered species risk assessments and to strengthen research capacity to understand biodiversity risk assessment in the context of coupled human-natural systems. A core group of social and biological scientists have worked with a network of more than 50 individuals from four countries to develop a conceptual framework illustrating how human-mediated processes influence biological systems and to develop tools to gather, translate, and incorporate these data into existing simulation models. A central theme of our research focused on (1 the difficulties often encountered in identifying and securing diverse bodies of expertise and information that is necessary to adequately address complex species conservation issues; and (2 the development of quantitative simulation modeling tools that could explicitly link these datasets as a way to gain deeper insight into these issues. To address these important challenges, we promote a "meta-modeling" approach where computational links are constructed between discipline-specific models already in existence. In this approach, each model can function as a powerful stand-alone program, but interaction between applications is achieved by passing data structures describing the state of the system between programs. As one example of this concept, an integrated meta-model of wildlife disease and population biology is described. A goal of this effort is to improve science-based capabilities for decision making by scientists, natural resource managers, and policy makers addressing environmental problems in general, and focusing on biodiversity risk assessment in particular.

Conservation biology for suites of species: Demographic modeling for Pacific island kingfishers

Science.gov (United States)

Kesler, D.C.; Haig, S.M.

2007-01-01

Conservation practitioners frequently extrapolate data from single-species investigations when managing critically endangered populations. However, few researchers initiate work with the intent of making findings useful to conservation efforts for other species. We presented and explored the concept of conducting conservation-oriented research for suites of geographically separated populations with similar natural histories, resource needs, and extinction threats. An example was provided in the form of an investigation into the population demography of endangered Micronesian kingfishers (Todiramphus cinnamominus). We provided the first demographic parameter estimates for any of the 12 endangered Pacific Todiramphus species, and used results to develop a population projection matrix model for management throughout the insular Pacific. Further, we used the model for elasticity and simulation analyses with demographic values that randomly varied across ranges that might characterize congener populations. Results from elasticity and simulation analyses indicated that changes in breeding adult survival exerted the greatest magnitude of influence on population dynamics. However, changes in nestling survival were more consistently correlated with population dynamics as demographic rates were randomly altered. We concluded that conservation practitioners working with endangered Pacific kingfishers should primarily focus efforts on factors affecting nestling and breeder survival, and secondarily address fledgling juveniles and helpers. Further, we described how the generalized base model might be changed to focus on individual populations and discussed the potential application of multi-species models to other conservation situations. ?? 2007 Elsevier Ltd. All rights reserved.

A real-time PCR assay with improved specificity for detection and discrimination of all clinically relevant Bordetella species by the presence and distribution of three Insertion Sequence elements

Directory of Open Access Journals (Sweden)

Ossewaarde Jacobus M

2011-01-01

Full Text Available Abstract Background In Dutch laboratories molecular detection of B. pertussis and B. parapertussis is commonly based on insertion sequences IS481 and IS1001, respectively. Both IS elements are more widely spread among Bordetella species. Both Bordetella holmesii, and B. bronchiseptica can harbour IS481. Also, IS1001 is found among B. bronchiseptica. IS481, and IS1001 based PCR thus lacks specificity when used for detection of specific Bordetella spp. Findings We designed a PCR based on IS1002, another IS element that is present among Bordetella species, and exploited it as a template in combination with PCR for IS481, and IS1001. In combining the PCRs for IS481, IS1001, and IS1002, and including an inhibition control, we were able to detect and discriminate all clinically relevant Bordetella species. Conclusions We developed an improved PCR method for specific detection of B. pertussis, B. parapertussis, B. holmesii, and B. bronchiseptica.

Cross-species comparison of biological themes and underlying genes on a global gene expression scale in a mouse model of colorectal liver metastasis and in clinical specimens

Directory of Open Access Journals (Sweden)

Schirmacher Peter

2008-09-01

Full Text Available Abstract Background Invasion-related genes over-expressed by tumor cells as well as by reacting host cells represent promising drug targets for anti-cancer therapy. Such candidate genes need to be validated in appropriate animal models. Results This study examined the suitability of a murine model (CT26/Balb/C of colorectal liver metastasis to represent clinical liver metastasis specimens using a global gene expression approach. Cross-species similarity was examined between pure liver, liver invasion, tumor invasion and pure tumor compartments through overlap of up-regulated genes and gene ontology (GO-based biological themes on the level of single GO-terms and of condensed GO-term families. Three out of four GO-term families were conserved in a compartment-specific way between the species: secondary metabolism (liver, invasion (invasion front, and immune response (invasion front and liver. Among the individual GO-terms over-represented in the invasion compartments in both species were "extracellular matrix", "cell motility", "cell adhesion" and "antigen presentation" indicating that typical invasion related processes are operating in both species. This was reflected on the single gene level as well, as cross-species overlap of potential target genes over-expressed in the combined invasion front compartments reached up to 36.5%. Generally, histopathology and gene expression correlated well as the highest single gene overlap was found to be 44% in syn-compartmental comparisons (liver versus liver whereas cross-compartmental overlaps were much lower (e.g. liver versus tumor: 9.7%. However, single gene overlap was surprisingly high in some cross-compartmental comparisons (e.g. human liver invasion compartment and murine tumor invasion compartment: 9.0% despite little histolopathologic similarity indicating that invasion relevant genes are not necessarily confined to histologically defined compartments. Conclusion In summary, cross-species

Species Distribution modeling as a tool to unravel determinants of palm distribution in Thailand

DEFF Research Database (Denmark)

Tovaranonte, Jantrararuk; Barfod, Anders S.; Balslev, Henrik

2011-01-01

As a consequence of the decimation of the forest cover in Thailand from 50% to ca. 20 % since the 1950ies, it is difficult to gain insight in the drivers behind past, present and future distribution ranges of plant species. Species distribution modeling allows visualization of potential species...... distribution under specific sets of assumptions. In this study we used maximum entropy to map potential distributions of 103 species of palms for which more than 5 herbarium records exist. Palms constitute key-stone plant group from both an ecological, economical and conservation perspective. The models were......) and the Area Under the Curve (AUC). All models performed well with AUC scores above 0.95. The predicted distribution ranges showed high suitability for palms in the southern region of Thailand. It also shows that spatial predictor variables are important in cases where historical processes may explain extant...

Ice age distriutions of European small mammals: insights from species distribution modelling

DEFF Research Database (Denmark)

Fløjgaard, Camilla; Normand, Signe; Skov, Flemming

2009-01-01

limits corresponding to the limits of temperate or boreal forest or arctic tundra were used in the analysis. We developed predictive distribution models based on the species present-day European distributions and validated these against their present-day Siberian ranges. The models with the best...... lemmus and Microtus oeconomus), suitable climate was predicted from the Atlantic coast eastward across central Europe and into Russia. Main conclusions. Our results support the idea of more northerly refuge areas in Europe, indicating that boreal species would have found suitable living conditions over...

Estimating Effects of Species Interactions on Populations of Endangered Species.

Science.gov (United States)

Roth, Tobias; Bühler, Christoph; Amrhein, Valentin

2016-04-01

Global change causes community composition to change considerably through time, with ever-new combinations of interacting species. To study the consequences of newly established species interactions, one available source of data could be observational surveys from biodiversity monitoring. However, approaches using observational data would need to account for niche differences between species and for imperfect detection of individuals. To estimate population sizes of interacting species, we extended N-mixture models that were developed to estimate true population sizes in single species. Simulations revealed that our model is able to disentangle direct effects of dominant on subordinate species from indirect effects of dominant species on detection probability of subordinate species. For illustration, we applied our model to data from a Swiss amphibian monitoring program and showed that sizes of expanding water frog populations were negatively related to population sizes of endangered yellow-bellied toads and common midwife toads and partly of natterjack toads. Unlike other studies that analyzed presence and absence of species, our model suggests that the spread of water frogs in Central Europe is one of the reasons for the decline of endangered toad species. Thus, studying population impacts of dominant species on population sizes of endangered species using data from biodiversity monitoring programs should help to inform conservation policy and to decide whether competing species should be subject to population management.

Water-soluble triazabutadienes that release diazonium species upon protonation under physiologically relevant conditions.

Science.gov (United States)

Kimani, Flora W; Jewett, John C

2015-03-23

Triazabutadienes are an understudied structural motif that have remarkable reactivity once rendered water-soluble. It is shown that these molecules readily release diazonium species in a pH-dependent manner in a series of buffer solutions with pH ranges similar to those found in cells. Upon further development, we expect that this process will be well suited to cargo-release strategies and organelle-specific bioconjugation reactions. These compounds offer one of the mildest ways of generating diazonium species in aqueous solutions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Decision-relevant evaluation of climate models: A case study of chill hours in California

Science.gov (United States)

Jagannathan, K. A.; Jones, A. D.; Kerr, A. C.

2017-12-01

The past decade has seen a proliferation of different climate datasets with over 60 climate models currently in use. Comparative evaluation and validation of models can assist practitioners chose the most appropriate models for adaptation planning. However, such assessments are usually conducted for `climate metrics' such as seasonal temperature, while sectoral decisions are often based on `decision-relevant outcome metrics' such as growing degree days or chill hours. Since climate models predict different metrics with varying skill, the goal of this research is to conduct a bottom-up evaluation of model skill for `outcome-based' metrics. Using chill hours (number of hours in winter months where temperature is lesser than 45 deg F) in Fresno, CA as a case, we assess how well different GCMs predict the historical mean and slope of chill hours, and whether and to what extent projections differ based on model selection. We then compare our results with other climate-based evaluations of the region, to identify similarities and differences. For the model skill evaluation, historically observed chill hours were compared with simulations from 27 GCMs (and multiple ensembles). Model skill scores were generated based on a statistical hypothesis test of the comparative assessment. Future projections from RCP 8.5 runs were evaluated, and a simple bias correction was also conducted. Our analysis indicates that model skill in predicting chill hour slope is dependent on its skill in predicting mean chill hours, which results from the non-linear nature of the chill metric. However, there was no clear relationship between the models that performed well for the chill hour metric and those that performed well in other temperature-based evaluations (such winter minimum temperature or diurnal temperature range). Further, contrary to conclusions from other studies, we also found that the multi-model mean or large ensemble mean results may not always be most appropriate for this

Two species of vortices in massive gauged non-linear sigma models

International Nuclear Information System (INIS)

Alonso-Izquierdo, A.; Fuertes, W. García; Guilarte, J. Mateos

2015-01-01

Non-linear sigma models with scalar fields taking values on ℂℙ"n complex manifolds are addressed. In the simplest n=1 case, where the target manifold is the S"2 sphere, we describe the scalar fields by means of stereographic maps. In this case when the U(1) symmetry is gauged and Maxwell and mass terms are allowed, the model accommodates stable self-dual vortices of two kinds with different energies per unit length and where the Higgs field winds at the cores around the two opposite poles of the sphere. Allowing for dielectric functions in the magnetic field, similar and richer self-dual vortices of different species in the south and north charts can be found by slightly modifying the potential. Two different situations are envisaged: either the vacuum orbit lies on a parallel in the sphere, or one pole and the same parallel form the vacuum orbit. Besides the self-dual vortices of two species, there exist BPS domain walls in the second case. Replacing the Maxwell contribution of the gauge field to the action by the second Chern-Simons secondary class, only possible in (2+1)-dimensional Minkowski space-time, new BPS topological defects of two species appear. Namely, both BPS vortices and domain ribbons in the south and the north charts exist because the vacuum orbit consits of the two poles and one parallel. Formulation of the gauged ℂℙ"2 model in a reference chart shows a self-dual structure such that BPS semi-local vortices exist. The transition functions to the second or third charts break the U(1)×SU(2) semi-local symmetry, but there is still room for standard self-dual vortices of the second species. The same structures encompassing N complex scalar fields are easily generalized to gauged ℂℙ"N models.

Two species of vortices in massive gauged non-linear sigma models

Energy Technology Data Exchange (ETDEWEB)

Alonso-Izquierdo, A. [Departamento de Matemática Aplicada, Universidad de Salamanca,Facultad de Ciencias Agrarias y Ambientales, Av. Filiberto Villalobos 119, E-37008 Salamanca (Spain); Fuertes, W. García [Departamento de Física, Universidad de Oviedo, Facultad de Ciencias, Calle Calvo Sotelo s/n, E-33007 Oviedo (Spain); Guilarte, J. Mateos [Departamento de Física Fundamental, Universidad de Salamanca, Facultad de Ciencias, Plaza de la Merced, E-37008 Salamanca (Spain)

2015-02-23

Non-linear sigma models with scalar fields taking values on ℂℙ{sup n} complex manifolds are addressed. In the simplest n=1 case, where the target manifold is the S{sup 2} sphere, we describe the scalar fields by means of stereographic maps. In this case when the U(1) symmetry is gauged and Maxwell and mass terms are allowed, the model accommodates stable self-dual vortices of two kinds with different energies per unit length and where the Higgs field winds at the cores around the two opposite poles of the sphere. Allowing for dielectric functions in the magnetic field, similar and richer self-dual vortices of different species in the south and north charts can be found by slightly modifying the potential. Two different situations are envisaged: either the vacuum orbit lies on a parallel in the sphere, or one pole and the same parallel form the vacuum orbit. Besides the self-dual vortices of two species, there exist BPS domain walls in the second case. Replacing the Maxwell contribution of the gauge field to the action by the second Chern-Simons secondary class, only possible in (2+1)-dimensional Minkowski space-time, new BPS topological defects of two species appear. Namely, both BPS vortices and domain ribbons in the south and the north charts exist because the vacuum orbit consits of the two poles and one parallel. Formulation of the gauged ℂℙ{sup 2} model in a reference chart shows a self-dual structure such that BPS semi-local vortices exist. The transition functions to the second or third charts break the U(1)×SU(2) semi-local symmetry, but there is still room for standard self-dual vortices of the second species. The same structures encompassing N complex scalar fields are easily generalized to gauged ℂℙ{sup N} models.

Reactive species output of a plasma jet with a shielding gas device—combination of FTIR absorption spectroscopy and gas phase modelling

International Nuclear Information System (INIS)

Schmidt-Bleker, A; Winter, J; Iseni, S; Dünnbier, M; Reuter, S; Weltmann, K-D

2014-01-01

In this work, a simple modelling approach combined with absorption spectroscopy of long living species generated by a cold atmospheric plasma jet yields insight into relevant gas phase chemistry. The reactive species output of the plasma jet is controlled using a shielding gas device. The shielding gas is varied using mixtures of oxygen and nitrogen at various humidity levels. Through the combination of Fourier transform infrared (FTIR) spectroscopy, computational fluid dynamics (CFD) simulations and zero dimensional kinetic modelling of the gas phase chemistry, insight into the underlying reaction mechanisms is gained. While the FTIR measurements yield absolute densities of ozone and nitrogen dioxide in the far field of the jet, the kinetic simulations give additional information on reaction pathways. The simulation is fitted to the experimentally obtained data, using the CFD simulations of the experimental setup to estimate the correct evaluation time for the kinetic simulation. It is shown that the ozone production of the plasma jet continuously rises with the oxygen content in the shielding gas, while it significantly drops as humidity is increased. The production of nitrogen dioxide reaches its maximum at about 30% oxygen content in the shielding gas. The underlying mechanisms are discussed based on the simulation results. (paper)

Choice of baseline climate data impacts projected species' responses to climate change.

Science.gov (United States)

Baker, David J; Hartley, Andrew J; Butchart, Stuart H M; Willis, Stephen G

2016-07-01

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species-climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040-2069, 2070-2099), using downscaled climate projections, and calculated species turnover and changes in species-specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species-specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site-level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses. © 2016 John Wiley

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...

The true meaning of 'exotic species' as a model for genetically engineered organisms.

Science.gov (United States)

Regal, P J

1993-03-15

The exotic or non-indigenous species model for deliberately introduced genetically engineered organisms (GEOs) has often been misunderstood or misrepresented. Yet proper comparisons of of ecologically competent GEOs to the patterns of adaptation of introduced species have been highly useful among scientists in attempting to determine how to apply biological theory to specific GEO risk issues, and in attempting to define the probabilities and scale of ecological risks with GEOs. In truth, the model predicts that most projects may be environmentally safe, but a significant minority may be very risky. The model includes a history of institutional follies that also should remind workers of the danger of oversimplifying biological issues, and warn against repeating the sorts of professional misjudgements that have too often been made in introducing organisms to new settings. We once expected that the non-indigenous species model would be refined by more analysis of species eruptions, ecological genetics, and the biology of select GEOs themselves, as outlined. But there has been political resistance to the effective regulation of GEOs, and a bureaucratic tendency to focus research agendas on narrow data collection. Thus there has been too little promotion by responsible agencies of studies to provide the broad conceptual base for truly science-based regulation. In its presently unrefined state, the non-indigenous species comparison would overestimate the risks of GEOs if it were (mis)applied to genetically disrupted, ecologically crippled GEOs, but in some cases of wild-type organisms with novel engineered traits, it could greatly underestimate the risks. Further analysis is urgently needed.

Citizen Science and Open Data: a Model for Invasive Alien Plant Species in Kenya's Northern Rangelands

Science.gov (United States)

Amirazodi, S.; Griffin, R.; Flores Cordova, A. I.; Ouko, E.; Omondi, S.; Mugo, R. M.; Farah, H.; Flores Cordova, A. I.; Adams, E. C.

2017-12-01

Invasive species in African savannas pose great threat to the native biodiversity and changes ecosystem functioning. In the forest sector, for instance Acacia species are important sources of fuel-wood, yet at the same time they have increased strain on water resources and shrunken forage spaces for both livestock and wildlife. In recently infested regions, invasive species can progress through the stages of introduction, establishment and dispersal to a full range. Currently there is much worldwide interest in predicting distributions of invasive species, and several organizations are faced with questions of whether and how to tackle such environmental challenges, or how to interpret predictions from the science community. Conservation practioners require mapped estimates of where species could persist in a given region, and this is associated to information about the biotope - i.e. the geographic location of the species' niche. The process of collecting species distribution data for identifying the potential distribution of the invasive species in the invaded ranges has become a challenge both in terms of resource and time allocation. This study highlights innovative approaches in crowdsourcing validation data in mapping and modelling invasive species (Acacia reficiens and Cactus) through involvement of the local communities. The general approach was to model the distribution of A. reficiens and Cactus (Opuntia Spp) using occurrence records from native range, then project the model into new regions to assess susceptibility to invasion using climatic and topographic environmental variables. The models performed better than random prediction (P 0.75.

Relevance of the ICRP biokinetic model for dietary organically bound tritium

International Nuclear Information System (INIS)

Trivedi, A.

1999-10-01

Ingested dietary tritium can participate in metabolic processes, and become synthesized into organically bound tritium in the tissues and organs. The distribution and retention of the organically bound tritium throughout the body are much different than tritium in the body water. The International Commission on Radiological Protection (ICRP) Publication 56 (1989) has a biokinetic model to calculate dose from the ingestion of organically bound dietary tritium. The model predicts that the dose from the ingestion of organically bound dietary tritium is about 2.3 times higher than from the ingestion of the same activity of tritiated water. Under steady-state conditions, the calculated dose rate (using the first principle approach) from the ingestion of dietary organically bound tritium can be twice that from the ingestion of tritiated water. For an adult, the upper-bound dose estimate for the ingestion of dietary organically bound tritium is estimated to be close to 2.3 times higher than that of tritiated water. Therefore, given the uncertainty in the dose calculation with respect to the actual relevant dose, the ICRP biokinetic model for organically bound tritium is sufficient for dosimetry for adults. (author)

Relevance in the science classroom: A multidimensional analysis

Science.gov (United States)

Hartwell, Matthew F.

While perceived relevance is considered a fundamental component of adaptive learning, the experience of relevance and its conceptual definition have not been well described. The mixed-methods research presented in this dissertation aimed to clarify the conceptual meaning of relevance by focusing on its phenomenological experience from the students' perspective. Following a critical literature review, I propose an identity-based model of perceived relevance that includes three components: a contextual target, an identity target, and a connection type, or lens. An empirical investigation of this model that consisted of two general phases was implemented in four 9th grade-biology classrooms. Participants in Phase 1 (N = 118) completed a series of four open-ended writing activities focused on eliciting perceived personal connections to academic content. Exploratory qualitative content analysis of a 25% random sample of the student responses was used to identify the main meaning-units of the proposed model as well as different dimensions of student relevance perceptions. These meaning-units and dimensions provided the basis for the construction of a conceptual mapping sentence capturing students' perceived relevance, which was then applied in a confirmatory analysis to all other student responses. Participants in Phase 2 (N = 139) completed a closed survey designed based on the mapping sentence to assess their perceived relevance of a biology unit. The survey also included scales assessing other domain-level motivational processes. Exploratory factor analysis and non-metric multidimensional scaling indicated a coherent conceptual structure, which included a primary interpretive relevance dimension. Comparison of the conceptual structure across various groups (randomly-split sample, gender, academic level, domain-general motivational profiles) provided support for its ubiquity and insight into variation in the experience of perceived relevance among students of different

On the well posedness and further regularity of a diffusive three species aquatic model

KAUST Repository

Parshad, R.D.

2012-01-01

We consider Upadhay\\'s three species aquatic food chain model, with the inclusion of spatial spread. This is a well established food chain model for the interaction of three given aquatic species. It exhibits rich dynamical behavior, including chaos. We prove the existence of a global weak solution to the diffusive system, followed by existence of local mild and strong solution.

Why relevance theory is relevant for lexicography

DEFF Research Database (Denmark)

Bothma, Theo; Tarp, Sven

2014-01-01

This article starts by providing a brief summary of relevance theory in information science in relation to the function theory of lexicography, explaining the different types of relevance, viz. objective system relevance and the subjective types of relevance, i.e. topical, cognitive, situational...... that is very important for lexicography as well as for information science, viz. functional relevance. Since all lexicographic work is ultimately aimed at satisfying users’ information needs, the article then discusses why the lexicographer should take note of all these types of relevance when planning a new...... dictionary project, identifying new tasks and responsibilities of the modern lexicographer. The article furthermore discusses how relevance theory impacts on teaching dictionary culture and reference skills. By integrating insights from lexicography and information science, the article contributes to new...

A nonlocal and periodic reaction-diffusion-advection model of a single phytoplankton species.

Science.gov (United States)

Peng, Rui; Zhao, Xiao-Qiang

2016-02-01

In this article, we are concerned with a nonlocal reaction-diffusion-advection model which describes the evolution of a single phytoplankton species in a eutrophic vertical water column where the species relies solely on light for its metabolism. The new feature of our modeling equation lies in that the incident light intensity and the death rate are assumed to be time periodic with a common period. We first establish a threshold type result on the global dynamics of this model in terms of the basic reproduction number R0. Then we derive various characterizations of R0 with respect to the vertical turbulent diffusion rate, the sinking or buoyant rate and the water column depth, respectively, which in turn give rather precise conditions to determine whether the phytoplankton persist or become extinct. Our theoretical results not only extend the existing ones for the time-independent case, but also reveal new interesting effects of the modeling parameters and the time-periodic heterogeneous environment on persistence and extinction of the phytoplankton species, and thereby suggest important implications for phytoplankton growth control.

Quantitative thermodynamic predication of interactions between nucleic acid and non-nucleic acid species using Microsoft excel.

Science.gov (United States)

Zou, Jiaqi; Li, Na

2013-09-01

Proper design of nucleic acid sequences is crucial for many applications. We have previously established a thermodynamics-based quantitative model to help design aptamer-based nucleic acid probes by predicting equilibrium concentrations of all interacting species. To facilitate customization of this thermodynamic model for different applications, here we present a generic and easy-to-use platform to implement the algorithm of the model with Microsoft(®) Excel formulas and VBA (Visual Basic for Applications) macros. Two Excel spreadsheets have been developed: one for the applications involving only nucleic acid species, the other for the applications involving both nucleic acid and non-nucleic acid species. The spreadsheets take the nucleic acid sequences and the initial concentrations of all species as input, guide the user to retrieve the necessary thermodynamic constants, and finally calculate equilibrium concentrations for all species in various bound and unbound conformations. The validity of both spreadsheets has been verified by comparing the modeling results with the experimental results on nucleic acid sequences reported in the literature. This Excel-based platform described here will allow biomedical researchers to rationalize the sequence design of nucleic acid probes using the thermodynamics-based modeling even without relevant theoretical and computational skills. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

GRIZZLY Model of Multi-Reactive Species Diffusion, Moisture/Heat Transfer and Alkali-Silica Reaction for Simulating Concrete Aging and Degradation

Energy Technology Data Exchange (ETDEWEB)

Huang, Hai [Idaho National Lab. (INL), Idaho Falls, ID (United States); Spencer, Benjamin W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Cai, Guowei [Vanderbilt Univ., Nashville, TN (United States)

2015-09-01

Concrete is widely used in the construction of nuclear facilities because of its structural strength and its ability to shield radiation. The use of concrete in nuclear power plants for containment and shielding of radiation and radioactive materials has made its performance crucial for the safe operation of the facility. As such, when life extension is considered for nuclear power plants, it is critical to have accurate and reliable predictive tools to address concerns related to various aging processes of concrete structures and the capacity of structures subjected to age-related degradation. The goal of this report is to document the progress of the development and implementation of a fully coupled thermo-hydro-mechanical-chemical model in GRIZZLY code with the ultimate goal to reliably simulate and predict long-term performance and response of aged NPP concrete structures subjected to a number of aging mechanisms including external chemical attacks and volume-changing chemical reactions within concrete structures induced by alkali-silica reactions and long-term exposure to irradiation. Based on a number of survey reports of concrete aging mechanisms relevant to nuclear power plants and recommendations from researchers in concrete community, we’ve implemented three modules during FY15 in GRIZZLY code, (1) multi-species reactive diffusion model within cement materials; (2) coupled moisture and heat transfer model in concrete; and (3) anisotropic, stress-dependent, alkali-silica reaction induced swelling model. The multi-species reactive diffusion model was implemented with the objective to model aging of concrete structures subjected to aggressive external chemical attacks (e.g., chloride attack, sulfate attack, etc.). It considers multiple processes relevant to external chemical attacks such as diffusion of ions in aqueous phase within pore spaces, equilibrium chemical speciation reactions and kinetic mineral dissolution/precipitation. The moisture

On the ""early-time"" evolution of variables relevant to turbulence models for Rayleigh-Taylor instability

Energy Technology Data Exchange (ETDEWEB)

Rollin, Bertrand [Los Alamos National Laboratory; Andrews, Malcolm J [Los Alamos National Laboratory

2010-01-01

We present our progress toward setting initial conditions in variable density turbulence models. In particular, we concentrate our efforts on the BHR turbulence model for turbulent Rayleigh-Taylor instability. Our approach is to predict profiles of relevant parameters before the fully turbulent regime and use them as initial conditions for the turbulence model. We use an idealized model of the mixing between two interpenetrating fluids to define the initial profiles for the turbulence model parameters. Velocities and volume fractions used in the idealized mixing model are obtained respectively from a set of ordinary differential equations modeling the growth of the Rayleigh-Taylor instability and from an idealization of the density profile in the mixing layer. A comparison between predicted initial profiles for the turbulence model parameters and initial profiles of the parameters obtained from low Atwood number three dimensional simulations show reasonable agreement.

Software Helps Retrieve Information Relevant to the User

Science.gov (United States)

Mathe, Natalie; Chen, James

2003-01-01

The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.

Molecular Diagnosis of Pathogenic Sporothrix Species.

Directory of Open Access Journals (Sweden)

Anderson Messias Rodrigues

2015-12-01

Full Text Available Sporotrichosis is a chronic (subcutaneous infection caused by thermodimorphic fungi in the order, Ophiostomatales. These fungi are characterized by major differences in routes of transmission, host predilections, species virulence, and susceptibilities to antifungals. Sporothrix species emerge in the form of outbreaks. Large zoonoses and sapronoses are ongoing in Brazil and China, respectively. Current diagnostic methods based on morphology and physiology are inaccurate due to closely related phenotypes with overlapping components between pathogenic and non-pathogenic Sporothrix. There is a critical need for new diagnostic tools that are specific, sensitive, and cost-effective.We developed a panel of novel markers, based on calmodulin (CAL gene sequences, for the large-scale diagnosis and epidemiology of clinically relevant members of the Sporothrix genus, and its relative, Ophiostoma. We identified specific PCR-based markers for S. brasiliensis, S. schenckii, S. globosa, S. mexicana, S. pallida, and O. stenoceras. We employed a murine model of disseminated sporotrichosis to optimize a PCR assay for detecting Sporothrix in clinical specimens.Primer-BLAST searches revealed candidate sequences that were conserved within a single species. Species-specific primers showed no significant homology with human, mouse, or microorganisms outside the Sporothrix genus. The detection limit was 10-100 fg of DNA in a single round of PCR for identifying S. brasiliensis, S. schenckii, S. globosa, S. mexicana, and S. pallida. A simple, direct PCR assay, with conidia as a source of DNA, was effective for rapid, low-cost genotyping. Samples from a murine model of disseminated sporotrichosis confirmed the feasibility of detecting S. brasiliensis and S. schenckii DNA in spleen, liver, lungs, heart, brain, kidney, tail, and feces of infected animals.This PCR-based method could successfully detect and identify a single species in samples from cultures and from clinical

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

From models to crop species: caveats and solutions for translational metabolomics

Directory of Open Access Journals (Sweden)

Takayuki eTohge

2011-10-01

Full Text Available Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer of between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. LC-MS-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns and ion detection, a very wide range of metabolites can be analysed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation and analytic errors due to ion-suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum and Oryza sativa that illustrate how such dangers can be detected and circumvented.

Effects of sample survey design on the accuracy of classification tree models in species distribution models

Science.gov (United States)

Thomas C. Edwards; D. Richard Cutler; Niklaus E. Zimmermann; Linda Geiser; Gretchen G. Moisen

2006-01-01

We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by...

Perspectives on creating clinically relevant blast models for mild traumatic brain injury and post traumatic stress disorder symptoms

Directory of Open Access Journals (Sweden)

Lisa eBrenner

2012-03-01

Full Text Available Military personnel are returning from Iraq and Afghanistan and reporting non-specific physical (somatic, behavioral, psychological, and cognitive symptoms. Many of these symptoms are frequently associated with mild traumatic brain injury (mTBI and/or post traumatic stress disorder (PTSD. Despite significant attention and advances in assessment and intervention for these two conditions, challenges persist. To address this, clinically relevant blast models are essential in the full characterization of this type of injury, as well as in the testing and identification of potential treatment strategies. In this publication, existing diagnostic challenges and current treatment practices for mTBI and/or PTSD will be summarized, along with suggestions regarding how what has been learned from existing models of PTSD and traditional mechanism (e.g., non-blast TBI can be used to facilitate the development of clinically relevant blast models.

A maximum pseudo-likelihood approach for estimating species trees under the coalescent model

Directory of Open Access Journals (Sweden)

Edwards Scott V

2010-10-01

Full Text Available Abstract Background Several phylogenetic approaches have been developed to estimate species trees from collections of gene trees. However, maximum likelihood approaches for estimating species trees under the coalescent model are limited. Although the likelihood of a species tree under the multispecies coalescent model has already been derived by Rannala and Yang, it can be shown that the maximum likelihood estimate (MLE of the species tree (topology, branch lengths, and population sizes from gene trees under this formula does not exist. In this paper, we develop a pseudo-likelihood function of the species tree to obtain maximum pseudo-likelihood estimates (MPE of species trees, with branch lengths of the species tree in coalescent units. Results We show that the MPE of the species tree is statistically consistent as the number M of genes goes to infinity. In addition, the probability that the MPE of the species tree matches the true species tree converges to 1 at rate O(M -1. The simulation results confirm that the maximum pseudo-likelihood approach is statistically consistent even when the species tree is in the anomaly zone. We applied our method, Maximum Pseudo-likelihood for Estimating Species Trees (MP-EST to a mammal dataset. The four major clades found in the MP-EST tree are consistent with those in the Bayesian concatenation tree. The bootstrap supports for the species tree estimated by the MP-EST method are more reasonable than the posterior probability supports given by the Bayesian concatenation method in reflecting the level of uncertainty in gene trees and controversies over the relationship of four major groups of placental mammals. Conclusions MP-EST can consistently estimate the topology and branch lengths (in coalescent units of the species tree. Although the pseudo-likelihood is derived from coalescent theory, and assumes no gene flow or horizontal gene transfer (HGT, the MP-EST method is robust to a small amount of HGT in the

Species distribution models for a migratory bird based on citizen science and satellite tracking data

Directory of Open Access Journals (Sweden)

Christopher L. Coxen

2017-07-01

Full Text Available Species distribution models can provide critical baseline distribution information for the conservation of poorly understood species. Here, we compared the performance of band-tailed pigeon (Patagioenas fasciata species distribution models created using Maxent and derived from two separate presence-only occurrence data sources in New Mexico: 1 satellite tracked birds and 2 observations reported in eBird basic data set. Both models had good accuracy (test AUC > 0.8 and True Skill Statistic > 0.4, and high overlap between suitability scores (I statistic 0.786 and suitable habitat patches (relative rank 0.639. Our results suggest that, at the state-wide level, eBird occurrence data can effectively model similar species distributions as satellite tracking data. Climate change models for the band-tailed pigeon predict a 35% loss in area of suitable climate by 2070 if CO2 emissions drop to 1990 levels by 2100, and a 45% loss by 2070 if we continue current CO2 emission levels through the end of the century. These numbers may be conservative given the predicted increase in drought, wildfire, and forest pest impacts to the coniferous forests the species inhabits in New Mexico. The northern portion of the species’ range in New Mexico is predicted to be the most viable through time.

Species distribution models for a migratory bird based on citizen science and satellite tracking data

Science.gov (United States)

Coxen, Christopher L.; Frey, Jennifer K.; Carleton, Scott A.; Collins, Daniel P.

2017-01-01

Species distribution models can provide critical baseline distribution information for the conservation of poorly understood species. Here, we compared the performance of band-tailed pigeon (Patagioenas fasciata) species distribution models created using Maxent and derived from two separate presence-only occurrence data sources in New Mexico: 1) satellite tracked birds and 2) observations reported in eBird basic data set. Both models had good accuracy (test AUC > 0.8 and True Skill Statistic > 0.4), and high overlap between suitability scores (I statistic 0.786) and suitable habitat patches (relative rank 0.639). Our results suggest that, at the state-wide level, eBird occurrence data can effectively model similar species distributions as satellite tracking data. Climate change models for the band-tailed pigeon predict a 35% loss in area of suitable climate by 2070 if CO2 emissions drop to 1990 levels by 2100, and a 45% loss by 2070 if we continue current CO2 emission levels through the end of the century. These numbers may be conservative given the predicted increase in drought, wildfire, and forest pest impacts to the coniferous forests the species inhabits in New Mexico. The northern portion of the species’ range in New Mexico is predicted to be the most viable through time.

Is the climate right for pleistocene rewilding? Using species distribution models to extrapolate climatic suitability for mammals across continents.

Directory of Open Access Journals (Sweden)

Orien M W Richmond

Full Text Available Species distribution models (SDMs are increasingly used for extrapolation, or predicting suitable regions for species under new geographic or temporal scenarios. However, SDM predictions may be prone to errors if species are not at equilibrium with climatic conditions in the current range and if training samples are not representative. Here the controversial "Pleistocene rewilding" proposal was used as a novel example to address some of the challenges of extrapolating modeled species-climate relationships outside of current ranges. Climatic suitability for three proposed proxy species (Asian elephant, African cheetah and African lion was extrapolated to the American southwest and Great Plains using Maxent, a machine-learning species distribution model. Similar models were fit for Oryx gazella, a species native to Africa that has naturalized in North America, to test model predictions. To overcome biases introduced by contracted modern ranges and limited occurrence data, random pseudo-presence points generated from modern and historical ranges were used for model training. For all species except the oryx, models of climatic suitability fit to training data from historical ranges produced larger areas of predicted suitability in North America than models fit to training data from modern ranges. Four naturalized oryx populations in the American southwest were correctly predicted with a generous model threshold, but none of these locations were predicted with a more stringent threshold. In general, the northern Great Plains had low climatic suitability for all focal species and scenarios considered, while portions of the southern Great Plains and American southwest had low to intermediate suitability for some species in some scenarios. The results suggest that the use of historical, in addition to modern, range information and randomly sampled pseudo-presence points may improve model accuracy. This has implications for modeling range shifts of

Fidelity in Animal Modeling: Prerequisite for a Mechanistic Research Front Relevant to the Inflammatory Incompetence of Acute Pediatric Malnutrition

Science.gov (United States)

Woodward, Bill

2016-01-01

Inflammatory incompetence is characteristic of acute pediatric protein-energy malnutrition, but its underlying mechanisms remain obscure. Perhaps substantially because the research front lacks the driving force of a scholarly unifying hypothesis, it is adrift and research activity is declining. A body of animal-based research points to a unifying paradigm, the Tolerance Model, with some potential to offer coherence and a mechanistic impetus to the field. However, reasonable skepticism prevails regarding the relevance of animal models of acute pediatric malnutrition; consequently, the fundamental contributions of the animal-based component of this research front are largely overlooked. Design-related modifications to improve the relevance of animal modeling in this research front include, most notably, prioritizing essential features of pediatric malnutrition pathology rather than dietary minutiae specific to infants and children, selecting windows of experimental animal development that correspond to targeted stages of pediatric immunological ontogeny, and controlling for ontogeny-related confounders. In addition, important opportunities are presented by newer tools including the immunologically humanized mouse and outbred stocks exhibiting a magnitude of genetic heterogeneity comparable to that of human populations. Sound animal modeling is within our grasp to stimulate and support a mechanistic research front relevant to the immunological problems that accompany acute pediatric malnutrition. PMID:27077845

Fidelity in Animal Modeling: Prerequisite for a Mechanistic Research Front Relevant to the Inflammatory Incompetence of Acute Pediatric Malnutrition.

Science.gov (United States)

Woodward, Bill

2016-04-11

Inflammatory incompetence is characteristic of acute pediatric protein-energy malnutrition, but its underlying mechanisms remain obscure. Perhaps substantially because the research front lacks the driving force of a scholarly unifying hypothesis, it is adrift and research activity is declining. A body of animal-based research points to a unifying paradigm, the Tolerance Model, with some potential to offer coherence and a mechanistic impetus to the field. However, reasonable skepticism prevails regarding the relevance of animal models of acute pediatric malnutrition; consequently, the fundamental contributions of the animal-based component of this research front are largely overlooked. Design-related modifications to improve the relevance of animal modeling in this research front include, most notably, prioritizing essential features of pediatric malnutrition pathology rather than dietary minutiae specific to infants and children, selecting windows of experimental animal development that correspond to targeted stages of pediatric immunological ontogeny, and controlling for ontogeny-related confounders. In addition, important opportunities are presented by newer tools including the immunologically humanized mouse and outbred stocks exhibiting a magnitude of genetic heterogeneity comparable to that of human populations. Sound animal modeling is within our grasp to stimulate and support a mechanistic research front relevant to the immunological problems that accompany acute pediatric malnutrition.

Non-climatic thermal adaptation: implications for species' responses to climate warming.

Science.gov (United States)

Marshall, David J; McQuaid, Christopher D; Williams, Gray A

2010-10-23

There is considerable interest in understanding how ectothermic animals may physiologically and behaviourally buffer the effects of climate warming. Much less consideration is being given to how organisms might adapt to non-climatic heat sources in ways that could confound predictions for responses of species and communities to climate warming. Although adaptation to non-climatic heat sources (solar and geothermal) seems likely in some marine species, climate warming predictions for marine ectotherms are largely based on adaptation to climatically relevant heat sources (air or surface sea water temperature). Here, we show that non-climatic solar heating underlies thermal resistance adaptation in a rocky-eulittoral-fringe snail. Comparisons of the maximum temperatures of the air, the snail's body and the rock substratum with solar irradiance and physiological performance show that the highest body temperature is primarily controlled by solar heating and re-radiation, and that the snail's upper lethal temperature exceeds the highest climatically relevant regional air temperature by approximately 22°C. Non-climatic thermal adaptation probably features widely among marine and terrestrial ectotherms and because it could enable species to tolerate climatic rises in air temperature, it deserves more consideration in general and for inclusion into climate warming models.

Using maximum topology matching to explore differences in species distribution models

Science.gov (United States)

Poco, Jorge; Doraiswamy, Harish; Talbert, Marian; Morisette, Jeffrey; Silva, Claudio

2015-01-01

Species distribution models (SDM) are used to help understand what drives the distribution of various plant and animal species. These models are typically high dimensional scalar functions, where the dimensions of the domain correspond to predictor variables of the model algorithm. Understanding and exploring the differences between models help ecologists understand areas where their data or understanding of the system is incomplete and will help guide further investigation in these regions. These differences can also indicate an important source of model to model uncertainty. However, it is cumbersome and often impractical to perform this analysis using existing tools, which allows for manual exploration of the models usually as 1-dimensional curves. In this paper, we propose a topology-based framework to help ecologists explore the differences in various SDMs directly in the high dimensional domain. In order to accomplish this, we introduce the concept of maximum topology matching that computes a locality-aware correspondence between similar extrema of two scalar functions. The matching is then used to compute the similarity between two functions. We also design a visualization interface that allows ecologists to explore SDMs using their topological features and to study the differences between pairs of models found using maximum topological matching. We demonstrate the utility of the proposed framework through several use cases using different data sets and report the feedback obtained from ecologists.

Clinical and Neurobiological Relevance of Current Animal Models of Autism Spectrum Disorders

Science.gov (United States)

Kim, Ki Chan; Gonzales, Edson Luck; Lázaro, María T.; Choi, Chang Soon; Bahn, Geon Ho; Yoo, Hee Jeong; Shin, Chan Young

2016-01-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication impairments, as well as repetitive and restrictive behaviors. The phenotypic heterogeneity of ASD has made it overwhelmingly difficult to determine the exact etiology and pathophysiology underlying the core symptoms, which are often accompanied by comorbidities such as hyperactivity, seizures, and sensorimotor abnormalities. To our benefit, the advent of animal models has allowed us to assess and test diverse risk factors of ASD, both genetic and environmental, and measure their contribution to the manifestation of autistic symptoms. At a broader scale, rodent models have helped consolidate molecular pathways and unify the neurophysiological mechanisms underlying each one of the various etiologies. This approach will potentially enable the stratification of ASD into clinical, molecular, and neurophenotypic subgroups, further proving their translational utility. It is henceforth paramount to establish a common ground of mechanistic theories from complementing results in preclinical research. In this review, we cluster the ASD animal models into lesion and genetic models and further classify them based on the corresponding environmental, epigenetic and genetic factors. Finally, we summarize the symptoms and neuropathological highlights for each model and make critical comparisons that elucidate their clinical and neurobiological relevance. PMID:27133257

An object-oriented forest landscape model and its representation of tree species

Science.gov (United States)

Hong S. He; David J. Mladenoff; Joel Boeder

1999-01-01

LANDIS is a forest landscape model that simulates the interaction of large landscape processes and forest successional dynamics at tree species level. We discuss how object-oriented design (OOD) approaches such as modularity, abstraction and encapsulation are integrated into the design of LANDIS. We show that using OOD approaches, model decisions (olden as model...

Predicting what helminth parasites a fish species should have using Parasite Co-occurrence Modeler (PaCo)

Science.gov (United States)

Strona, Giovanni; Lafferty, Kevin D.

2013-01-01

Fish pathologists are often interested in which parasites would likely be present in a particular host. Parasite Co-occurrence Modeler (PaCo) is a tool for identifying a list of parasites known from fish species that are similar ecologically, phylogenetically, and geographically to the host of interest. PaCo uses data from FishBase (maximum length, growth rate, life span, age at maturity, trophic level, phylogeny, and biogeography) to estimate compatibility between a target host and parasite species–genera from the major helminth groups (Acanthocephala, Cestoda, Monogenea, Nematoda, and Trematoda). Users can include any combination of host attributes in a model. These unique features make PaCo an innovative tool for addressing both theoretical and applied questions in parasitology. In addition to predicting the occurrence of parasites, PaCo can be used to investigate how host characteristics shape parasite communities. To test the performance of the PaCo algorithm, we created 12,400 parasite lists by applying any possible combination of model parameters (248) to 50 fish hosts. We then measured the relative importance of each parameter by assessing their frequency in the best models for each host. Host phylogeny and host geography were identified as the most important factors, with both present in 88% of the best models. Habitat (64%) was identified in more than half of the best models. Among ecological parameters, trophic level (41%) was the most relevant while life span (34%), growth rate (32%), maximum length (28%), and age at maturity (20%) were less commonly linked to best models. PaCo is free to use at www.purl.oclc.org/fishpest.

Stochastic resonance and noise delayed extinction in a model of two competing species

Science.gov (United States)

Valenti, D.; Fiasconaro, A.; Spagnolo, B.

2004-01-01

We study the role of the noise in the dynamics of two competing species. We consider generalized Lotka-Volterra equations in the presence of a multiplicative noise, which models the interaction between the species and the environment. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence of a periodic driving term, which accounts for the environment temperature variation. We find noise-induced periodic oscillations of the species concentrations and stochastic resonance phenomenon. We find also a nonmonotonic behavior of the mean extinction time of one of the two competing species as a function of the additive noise intensity.

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM).

Science.gov (United States)

West, Amanda M; Evangelista, Paul H; Jarnevich, Catherine S; Young, Nicholas E; Stohlgren, Thomas J; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

2016-10-11

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Integrating remote sensing with species distribution models; Mapping tamarisk invasions using the Software for Assisted Habitat Modeling (SAHM)

Science.gov (United States)

West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

2016-01-01

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

The dynamic complexity of a three species food chain model

International Nuclear Information System (INIS)

Lv Songjuan; Zhao Min

2008-01-01

In this paper, a three-species food chain model is analytically investigated on theories of ecology and using numerical simulation. Bifurcation diagrams are obtained for biologically feasible parameters. The results show that the system exhibits rich complexity features such as stable, periodic and chaotic dynamics

Species distribution modelling for conservation of an endangered endemic orchid.

Science.gov (United States)

Wang, Hsiao-Hsuan; Wonkka, Carissa L; Treglia, Michael L; Grant, William E; Smeins, Fred E; Rogers, William E

2015-04-21

Concerns regarding the long-term viability of threatened and endangered plant species are increasingly warranted given the potential impacts of climate change and habitat fragmentation on unstable and isolated populations. Orchidaceae is the largest and most diverse family of flowering plants, but it is currently facing unprecedented risks of extinction. Despite substantial conservation emphasis on rare orchids, populations continue to decline. Spiranthes parksii (Navasota ladies' tresses) is a federally and state-listed endangered terrestrial orchid endemic to central Texas. Hence, we aimed to identify potential factors influencing the distribution of the species, quantify the relative importance of each factor and determine suitable habitat for future surveys and targeted conservation efforts. We analysed several geo-referenced variables describing climatic conditions and landscape features to identify potential factors influencing the likelihood of occurrence of S. parksii using boosted regression trees. Our model classified 97 % of the cells correctly with regard to species presence and absence, and indicated that probability of existence was correlated with climatic conditions and landscape features. The most influential variables were mean annual precipitation, mean elevation, mean annual minimum temperature and mean annual maximum temperature. The most likely suitable range for S. parksii was the eastern portions of Leon and Madison Counties, the southern portion of Brazos County, a portion of northern Grimes County and along the borders between Burleson and Washington Counties. Our model can assist in the development of an integrated conservation strategy through: (i) focussing future survey and research efforts on areas with a high likelihood of occurrence, (ii) aiding in selection of areas for conservation and restoration and (iii) framing future research questions including those necessary for predicting responses to climate change. Our model could also

A dynamic performance model for redox-flow batteries involving soluble species

International Nuclear Information System (INIS)

Shah, A.A.; Watt-Smith, M.J.; Walsh, F.C.

2008-01-01

A transient modelling framework for a vanadium redox-flow battery (RFB) is developed and experiments covering a range of vanadium concentration and electrolyte flow rate are conducted. The two-dimensional model is based on a comprehensive description of mass, charge and momentum transport and conservation, and is combined with a global kinetic model for reactions involving vanadium species. The model is validated against the experimental data and is used to study the effects of variations in concentration, electrolyte flow rate and electrode porosity. Extensions to the model and future work are suggested

Thinking beyond the Common Candida Species: Need for Species-Level Identification of Candida Due to the Emergence of Multidrug-Resistant Candida auris.

Science.gov (United States)

Lockhart, Shawn R; Jackson, Brendan R; Vallabhaneni, Snigdha; Ostrosky-Zeichner, Luis; Pappas, Peter G; Chiller, Tom

2017-12-01

Candida species are one of the leading causes of nosocomial infections. Because much of the treatment for Candida infections is empirical, some institutions do not identify Candida to species level. With the worldwide emergence of the multidrug-resistant species Candida auris , identification of Candida to species level has new clinical relevance. Species should be identified for invasive candidiasis isolates, and species-level identification can be considered for selected noninvasive isolates to improve detection of C. auris . Copyright © 2017 American Society for Microbiology.

Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling

Directory of Open Access Journals (Sweden)

Yvonne Walz

2015-11-01

Full Text Available Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d’Ivoire using high- and moderateresolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixelbased modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

The non-ideal associated species model applied to the system copper-indium

International Nuclear Information System (INIS)

Kellogg, H.H.

1991-01-01

The liquid copper-indium system displays complex thermochemical behavior. Deviations from Raoult's law change from positive to negative, and the integral heat of mixing also varies from positive to strongly negative and is markedly dependent on temperature. This behavior was successfully modelled, over the entire composition range and for a temperature range of 400 K, using the non-ideal associated-species concept, with InCu 3 as the associated species. Independent evidence exists for association at the composition InCu 3 , from measurements of magnetic susceptibility, electrical resistivity and Hall effect. In this paper, the applicability of the model to other systems is discussed

Environmentally relevant approaches to assess nanoparticles ecotoxicity: A review

Energy Technology Data Exchange (ETDEWEB)

Bour, Agathe; Mouchet, Florence; Silvestre, Jérôme; Gauthier, Laury [Université de Toulouse (France); UPS, INP (France); EcoLab (Laboratoire d’écologie fonctionnelle et environnement) (France); ENSAT, Avenue de l’Agrobiopôle, F-31326 Castanet-Tolosan (France); CNRS (France); EcoLab (Laboratoire d’écologie fonctionnelle et environnement), F-31326 Castanet-Tolosan (France); Pinelli, Eric, E-mail: pinelli@ensat.fr [Université de Toulouse (France); UPS, INP (France); EcoLab (Laboratoire d’écologie fonctionnelle et environnement) (France); ENSAT, Avenue de l’Agrobiopôle, F-31326 Castanet-Tolosan (France); CNRS (France); EcoLab (Laboratoire d’écologie fonctionnelle et environnement), F-31326 Castanet-Tolosan (France)

2015-02-11

Highlights: • Integrated ecotoxicity of NPs from organism to community level is reviewed. • Trophic chains allow determining the implication of trophic route in NP toxicity. • The use of microcosms and mesocosms allows studies at larger scale. • Data concerning NP fate and effects in environmental conditions are lacking. - Abstract: Despite the increasing production and use of nanoparticles (NPs), there is a lack of knowledge about their environmental fate and ecotoxicity. Studies in environmentally relevant conditions are necessary to better assess these parameters, but such studies are rather rare. The present work represents first time that studies on engineered NPs using environmentally relevant exposure methods have been reviewed. These exposure methods differ from standardized protocols and can be classified into three groups: experimental trophic chains that allow study of the trophic route, multi-species exposures under laboratory conditions that allow for complex but controlled exposure and outdoor exposures that are more similar to environmentally realistic conditions. The majority of studies of micro- or mesocosms have focused on NP partitioning and bioaccumulation. The other major parameter that has been studied is NP ecotoxicity, which has been assessed in single species, in single species via the trophic route, and at the community level. The induction of biochemical defense systems, immunomodulation, effects on growth and reproduction, behavioral alterations and mortality have been used as indicators of major toxicity, depending on the species studied. The major effects of NPs on both microbial and algal communities include modifications of community compositions and diversities, decreased biomass and changes in community activities.

Environmentally relevant approaches to assess nanoparticles ecotoxicity: A review

International Nuclear Information System (INIS)

Bour, Agathe; Mouchet, Florence; Silvestre, Jérôme; Gauthier, Laury; Pinelli, Eric

2015-01-01

Highlights: • Integrated ecotoxicity of NPs from organism to community level is reviewed. • Trophic chains allow determining the implication of trophic route in NP toxicity. • The use of microcosms and mesocosms allows studies at larger scale. • Data concerning NP fate and effects in environmental conditions are lacking. - Abstract: Despite the increasing production and use of nanoparticles (NPs), there is a lack of knowledge about their environmental fate and ecotoxicity. Studies in environmentally relevant conditions are necessary to better assess these parameters, but such studies are rather rare. The present work represents first time that studies on engineered NPs using environmentally relevant exposure methods have been reviewed. These exposure methods differ from standardized protocols and can be classified into three groups: experimental trophic chains that allow study of the trophic route, multi-species exposures under laboratory conditions that allow for complex but controlled exposure and outdoor exposures that are more similar to environmentally realistic conditions. The majority of studies of micro- or mesocosms have focused on NP partitioning and bioaccumulation. The other major parameter that has been studied is NP ecotoxicity, which has been assessed in single species, in single species via the trophic route, and at the community level. The induction of biochemical defense systems, immunomodulation, effects on growth and reproduction, behavioral alterations and mortality have been used as indicators of major toxicity, depending on the species studied. The major effects of NPs on both microbial and algal communities include modifications of community compositions and diversities, decreased biomass and changes in community activities

Species Typing in Dermal Leishmaniasis

Science.gov (United States)

Dujardin, Jean-Claude

2015-01-01

SUMMARY Leishmania is an infectious protozoan parasite related to African and American trypanosomes. All Leishmania species that are pathogenic to humans can cause dermal disease. When one is confronted with cutaneous leishmaniasis, identification of the causative species is relevant in both clinical and epidemiological studies, case management, and control. This review gives an overview of the currently existing and most used assays for species discrimination, with a critical appraisal of the limitations of each technique. The consensus taxonomy for the genus is outlined, including debatable species designations. Finally, a numerical literature analysis is presented that describes which methods are most used in various countries and regions in the world, and for which purposes. PMID:25672782

Filtered selection coupled with support vector machines generate a functionally relevant prediction model for colorectal cancer

Directory of Open Access Journals (Sweden)

Gabere MN

2016-06-01

Full Text Available Musa Nur Gabere,1 Mohamed Aly Hussein,1 Mohammad Azhar Aziz2 1Department of Bioinformatics, King Abdullah International Medical Research Center/King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia; 2Colorectal Cancer Research Program, Department of Medical Genomics, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia Purpose: There has been considerable interest in using whole-genome expression profiles for the classification of colorectal cancer (CRC. The selection of important features is a crucial step before training a classifier.Methods: In this study, we built a model that uses support vector machine (SVM to classify cancer and normal samples using Affymetrix exon microarray data obtained from 90 samples of 48 patients diagnosed with CRC. From the 22,011 genes, we selected the 20, 30, 50, 100, 200, 300, and 500 genes most relevant to CRC using the minimum-redundancy–maximum-relevance (mRMR technique. With these gene sets, an SVM model was designed using four different kernel types (linear, polynomial, radial basis function [RBF], and sigmoid.Results: The best model, which used 30 genes and RBF kernel, outperformed other combinations; it had an accuracy of 84% for both ten fold and leave-one-out cross validations in discriminating the cancer samples from the normal samples. With this 30 genes set from mRMR, six classifiers were trained using random forest (RF, Bayes net (BN, multilayer perceptron (MLP, naïve Bayes (NB, reduced error pruning tree (REPT, and SVM. Two hybrids, mRMR + SVM and mRMR + BN, were the best models when tested on other datasets, and they achieved a prediction accuracy of 95.27% and 91.99%, respectively, compared to other mRMR hybrid models (mRMR + RF, mRMR + NB, mRMR + REPT, and mRMR + MLP. Ingenuity pathway analysis was used to analyze the functions of the 30 genes selected for this model and their potential association with CRC: CDH3, CEACAM7, CLDN1, IL8, IL6R, MMP1

Quantitative RNA-Seq analysis in non-model species: assessing transcriptome assemblies as a scaffold and the utility of evolutionary divergent genomic reference species

Directory of Open Access Journals (Sweden)

Hornett Emily A

2012-08-01

Full Text Available Abstract Background How well does RNA-Seq data perform for quantitative whole gene expression analysis in the absence of a genome? This is one unanswered question facing the rapidly growing number of researchers studying non-model species. Using Homo sapiens data and resources, we compared the direct mapping of sequencing reads to predicted genes from the genome with mapping to de novo transcriptomes assembled from RNA-Seq data. Gene coverage and expression analysis was further investigated in the non-model context by using increasingly divergent genomic reference species to group assembled contigs by unique genes. Results Eight transcriptome sets, composed of varying amounts of Illumina and 454 data, were assembled and assessed. Hybrid 454/Illumina assemblies had the highest transcriptome and individual gene coverage. Quantitative whole gene expression levels were highly similar between using a de novo hybrid assembly and the predicted genes as a scaffold, although mapping to the de novo transcriptome assembly provided data on fewer genes. Using non-target species as reference scaffolds does result in some loss of sequence and expression data, and bias and error increase with evolutionary distance. However, within a 100 million year window these effect sizes are relatively small. Conclusions Predicted gene sets from sequenced genomes of related species can provide a powerful method for grouping RNA-Seq reads and annotating contigs. Gene expression results can be produced that are similar to results obtained using gene models derived from a high quality genome, though biased towards conserved genes. Our results demonstrate the power and limitations of conducting RNA-Seq in non-model species.

Modelling for an improved integrated multi-trophic aquaculture system for the production of highly valued marine species

Directory of Open Access Journals (Sweden)

Luana Granada

2014-05-01

Full Text Available Integrated multi-trophic aquaculture (IMTA is regarded as a suitable approach to limit aquaculture nutrients and organic matter outputs through biomitigation. Here, species from different trophic or nutritional levels are connected through water transfer. The co-cultured species are used as biofilters, and each level has its own independent commercial value, providing both economic and environmental sustainability. In order to better understand and optimize aquaculture production systems, dynamic modelling has been developed towards the use of models for analysis and simulation of aquacultures. Several models available determine the carrying capacity of farms and the environmental effects of bivalve and fish aquaculture. Also, in the last two decades, modelling strategies have been designed in order to predict the dispersion and deposition of organic fish farm waste, usually using the mean settling velocity of faeces and feed pellets. Cultured organisms growth, effects of light and temperature on algae growth, retention of suspended solids, biodegradation of nitrogen and wastewater treatment are examples of other modelled parameters in aquaculture. Most modelling equations have been developed for monocultures, despite the increasing importance of multi-species systems, such as polyculture and IMTA systems. The main reason for the development of multi-species models is to maximize the production and optimize species combinations in order to reduce the environmental impacts of aquaculture. Some multi-species system models are available, including from the polyculture of different species of bivalves with fish to more complex systems with four trophic levels. These can incorporate ecosystem models and use dynamic energy budgets for each trophic group. In the proposed IMTA system, the bioremediation potential of the marine seaweed Gracilaria vermiculophylla (nutrient removal performance and the Mediterranean filter-feeding polychaete Sabella

A content relevance model for social media health information.

Science.gov (United States)

Prybutok, Gayle Linda; Koh, Chang; Prybutok, Victor R

2014-04-01

Consumer health informatics includes the development and implementation of Internet-based systems to deliver health risk management information and health intervention applications to the public. The application of consumer health informatics to educational and interventional efforts such as smoking reduction and cessation has garnered attention from both consumers and health researchers in recent years. Scientists believe that smoking avoidance or cessation before the age of 30 years can prevent more than 90% of smoking-related cancers and that individuals who stop smoking fare as well in preventing cancer as those who never start. The goal of this study was to determine factors that were most highly correlated with content relevance for health information provided on the Internet for a study group of 18- to 30-year-old college students. Data analysis showed that the opportunity for convenient entertainment, social interaction, health information-seeking behavior, time spent surfing on the Internet, the importance of available activities on the Internet (particularly e-mail), and perceived site relevance for Internet-based sources of health information were significantly correlated with content relevance for 18- to 30-year-old college students, an educated subset of this population segment.

The Relevance Voxel Machine (RVoxM): A Self-Tuning Bayesian Model for Informative Image-Based Prediction

DEFF Research Database (Denmark)

Sabuncu, Mert R.; Van Leemput, Koen

2012-01-01

This paper presents the relevance voxel machine (RVoxM), a dedicated Bayesian model for making predictions based on medical imaging data. In contrast to the generic machine learning algorithms that have often been used for this purpose, the method is designed to utilize a small number of spatially...

Remarks on the Species of Gomphrena (Amaranthaceae of Taiwan

Directory of Open Access Journals (Sweden)

Shih-Huei Chen

2012-09-01

Full Text Available Gomphrena serrata, an Amaranthaceous species of tropical origin, was recently found naturalized in disturbed sites of Taiwan. This species has been confused with G. celosioides, widespread on this island. The present study gives a key and useful characters to differentiate the present species from the latter. A taxonomic treatment of the two species in Taiwan, line drawings and other relevant information are provided.