A modeling framework for the establishment and spread of invasive species in heterogeneous environments.

PubMed

Lustig, Audrey; Worner, Susan P; Pitt, Joel P W; Doscher, Crile; Stouffer, Daniel B; Senay, Senait D

2017-10-01

Natural and human-induced events are continuously altering the structure of our landscapes and as a result impacting the spatial relationships between individual landscape elements and the species living in the area. Yet, only recently has the influence of the surrounding landscape on invasive species spread started to be considered. The scientific community increasingly recognizes the need for broader modeling framework that focuses on cross-study comparisons at different spatiotemporal scales. Using two illustrative examples, we introduce a general modeling framework that allows for a systematic investigation of the effect of habitat change on invasive species establishment and spread. The essential parts of the framework are (i) a mechanistic spatially explicit model (a modular dispersal framework-MDIG) that allows population dynamics and dispersal to be modeled in a geographical information system (GIS), (ii) a landscape generator that allows replicated landscape patterns with partially controllable spatial properties to be generated, and (iii) landscape metrics that depict the essential aspects of landscape with which dispersal and demographic processes interact. The modeling framework provides functionality for a wide variety of applications ranging from predictions of the spatiotemporal spread of real species and comparison of potential management strategies, to theoretical investigation of the effect of habitat change on population dynamics. Such a framework allows to quantify how small-grain landscape characteristics, such as habitat size and habitat connectivity, interact with life-history traits to determine the dynamics of invasive species spread in fragmented landscape. As such, it will give deeper insights into species traits and landscape features that lead to establishment and spread success and may be key to preventing new incursions and the development of efficient monitoring, surveillance, control or eradication programs.

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

NASA Astrophysics Data System (ADS)

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

Global attractivity of an almost periodic N-species nonlinear ecological competitive model

NASA Astrophysics Data System (ADS)

Xia, Yonghui; Han, Maoan; Huang, Zhenkun

2008-01-01

By using comparison theorem and constructing suitable Lyapunov functional, we study the following almost periodic nonlinear N-species competitive Lotka-Volterra model: A set of sufficient conditions is obtained for the existence and global attractivity of a unique positive almost periodic solution of the above model. As applications, some special competition models are studied again, our new results improve and generalize former results. Examples and their simulations show the feasibility of our main results.

Two-species occupancy modeling accounting for species misidentification and nondetection

USGS Publications Warehouse

Chambert, Thierry; Grant, Evan H. Campbell; Miller, David A. W.; Nichols, James; Mulder, Kevin P.; Brand, Adrianne B,

2018-01-01

In occupancy studies, species misidentification can lead to false‐positive detections, which can cause severe estimator biases. Currently, all models that account for false‐positive errors only consider omnibus sources of false detections and are limited to single‐species occupancy.However, false detections for a given species often occur because of the misidentification with another, closely related species. To exploit this explicit source of false‐positive detection error, we develop a two‐species occupancy model that accounts for misidentifications between two species of interest. As with other false‐positive models, identifiability is greatly improved by the availability of unambiguous detections at a subset of site x occasions. Here, we consider the case where some of the field observations can be confirmed using laboratory or other independent identification methods (“confirmatory data”).We performed three simulation studies to (1) assess the model's performance under various realistic scenarios, (2) investigate the influence of the proportion of confirmatory data on estimator accuracy and (3) compare the performance of this two‐species model with that of the single‐species false‐positive model. The model shows good performance under all scenarios, even when only small proportions of detections are confirmed (e.g. 5%). It also clearly outperforms the single‐species model.We illustrate application of this model using a 4‐year dataset on two sympatric species of lungless salamanders: the US federally endangered Shenandoah salamander Plethodon shenandoah, and its presumed competitor, the red‐backed salamander Plethodon cinereus. Occupancy of red‐backed salamanders appeared very stable across the 4 years of study, whereas the Shenandoah salamander displayed substantial turnover in occupancy of forest habitats among years.Given the extent of species misidentification issues in occupancy studies, this modelling approach should help

Some considerations on the use of ecological models to predict species' geographic distributions

USGS Publications Warehouse

Peterjohn, B.G.

2001-01-01

Peterson (2001) used Genetic Algorithm for Rule-set Prediction (GARP) models to predict distribution patterns from Breeding Bird Survey (BBS) data. Evaluations of these models should consider inherent limitations of BBS data: (1) BBS methods may not sample species and habitats equally; (2) using BBS data for both model development and testing may overlook poor fit of some models; and (3) BBS data may not provide the desired spatial resolution or capture temporal changes in species distributions. The predictive value of GARP models requires additional study, especially comparisons with distribution patterns from independent data sets. When employed at appropriate temporal and geographic scales, GARP models show considerable promise for conservation biology applications but provide limited inferences concerning processes responsible for the observed patterns.

Comparing niche- and process-based models to reduce prediction uncertainty in species range shifts under climate change.

PubMed

Morin, Xavier; Thuiller, Wilfried

2009-05-01

Obtaining reliable predictions of species range shifts under climate change is a crucial challenge for ecologists and stakeholders. At the continental scale, niche-based models have been widely used in the last 10 years to predict the potential impacts of climate change on species distributions all over the world, although these models do not include any mechanistic relationships. In contrast, species-specific, process-based predictions remain scarce at the continental scale. This is regrettable because to secure relevant and accurate predictions it is always desirable to compare predictions derived from different kinds of models applied independently to the same set of species and using the same raw data. Here we compare predictions of range shifts under climate change scenarios for 2100 derived from niche-based models with those of a process-based model for 15 North American boreal and temperate tree species. A general pattern emerged from our comparisons: niche-based models tend to predict a stronger level of extinction and a greater proportion of colonization than the process-based model. This result likely arises because niche-based models do not take phenotypic plasticity and local adaptation into account. Nevertheless, as the two kinds of models rely on different assumptions, their complementarity is revealed by common findings. Both modeling approaches highlight a major potential limitation on species tracking their climatic niche because of migration constraints and identify similar zones where species extirpation is likely. Such convergent predictions from models built on very different principles provide a useful way to offset uncertainties at the continental scale. This study shows that the use in concert of both approaches with their own caveats and advantages is crucial to obtain more robust results and that comparisons among models are needed in the near future to gain accuracy regarding predictions of range shifts under climate change.

Hierarchical species distribution models

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

Modeling species-abundance relationships in multi-species collections

USGS Publications Warehouse

Peng, S.; Yin, Z.; Ren, H.; Guo, Q.

2003-01-01

Species-abundance relationship is one of the most fundamental aspects of community ecology. Since Motomura first developed the geometric series model to describe the feature of community structure, ecologists have developed many other models to fit the species-abundance data in communities. These models can be classified into empirical and theoretical ones, including (1) statistical models, i.e., negative binomial distribution (and its extension), log-series distribution (and its extension), geometric distribution, lognormal distribution, Poisson-lognormal distribution, (2) niche models, i.e., geometric series, broken stick, overlapping niche, particulate niche, random assortment, dominance pre-emption, dominance decay, random fraction, weighted random fraction, composite niche, Zipf or Zipf-Mandelbrot model, and (3) dynamic models describing community dynamics and restrictive function of environment on community. These models have different characteristics and fit species-abundance data in various communities or collections. Among them, log-series distribution, lognormal distribution, geometric series, and broken stick model have been most widely used.

Model for Predicting Passage of Invasive Fish Species Through Culverts

NASA Astrophysics Data System (ADS)

Neary, V.

2010-12-01

Conservation efforts to promote or inhibit fish passage include the application of simple fish passage models to determine whether an open channel flow allows passage of a given fish species. Derivations of simple fish passage models for uniform and nonuniform flow conditions are presented. For uniform flow conditions, a model equation is developed that predicts the mean-current velocity threshold in a fishway, or velocity barrier, which causes exhaustion at a given maximum distance of ascent. The derivation of a simple expression for this exhaustion-threshold (ET) passage model is presented using kinematic principles coupled with fatigue curves for threatened and endangered fish species. Mean current velocities at or above the threshold predict failure to pass. Mean current velocities below the threshold predict successful passage. The model is therefore intuitive and easily applied to predict passage or exclusion. The ET model’s simplicity comes with limitations, however, including its application only to uniform flow, which is rarely found in the field. This limitation is addressed by deriving a model that accounts for nonuniform conditions, including backwater profiles and drawdown curves. Comparison of these models with experimental data from volitional swimming studies of fish indicates reasonable performance, but limitations are still present due to the difficulty in predicting fish behavior and passage strategies that can vary among individuals and different fish species.

Addressing potential local adaptation in species distribution models: implications for conservation under climate change

USGS Publications Warehouse

Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.

2016-01-01

Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

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

USGS Publications Warehouse

Edwards, T.C.; Cutler, D.R.; Zimmermann, N.E.; Geiser, L.; Moisen, Gretchen G.

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 resubstitution rates were similar for each lichen species irrespective of the underlying sample survey form. Cross-validation estimates of prediction accuracies were lower than resubstitution accuracies for all species and both design types, and in all cases were closer to the true prediction accuracies based on the EVALUATION data set. We argue that greater emphasis should be placed on calculating and reporting cross-validation accuracy rates rather than simple resubstitution accuracy rates. Evaluation of the DESIGN and PURPOSIVE tree models on the EVALUATION data set shows significantly lower prediction accuracy for the PURPOSIVE tree models relative to the DESIGN models, indicating that non-probabilistic sample surveys may generate models with limited predictive capability. These differences were consistent across all four lichen species, with 11 of the 12 possible species and sample survey type comparisons having significantly lower accuracy rates. Some differences in accuracy were as large as 50%. The classification tree structures also differed considerably both among and within the modelled species, depending on the sample survey form. Overlap in the predictor variables selected by the DESIGN and PURPOSIVE tree models ranged from only 20% to 38%, indicating the classification trees fit the two evaluated survey forms on different sets of predictor variables. The magnitude of these differences in predictor variables throws doubt on ecological interpretation derived from prediction models based on non-probabilistic sample surveys. ?? 2006 Elsevier B.V. All rights reserved.

Bounding species distribution models

USGS Publications Warehouse

Stohlgren, T.J.; Jarnevich, C.S.; Esaias, W.E.; Morisette, J.T.

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. ?? 2011 Current Zoology.

Comparisons of Air Radiation Model with Shock Tube Measurements

NASA Technical Reports Server (NTRS)

Bose, Deepak; McCorkle, Evan; Bogdanoff, David W.; Allen, Gary A., Jr.

2009-01-01

This paper presents an assessment of the predictive capability of shock layer radiation model appropriate for NASA s Orion Crew Exploration Vehicle lunar return entry. A detailed set of spectrally resolved radiation intensity comparisons are made with recently conducted tests in the Electric Arc Shock Tube (EAST) facility at NASA Ames Research Center. The spectral range spanned from vacuum ultraviolet wavelength of 115 nm to infrared wavelength of 1400 nm. The analysis is done for 9.5-10.5 km/s shock passing through room temperature synthetic air at 0.2, 0.3 and 0.7 Torr. The comparisons between model and measurements show discrepancies in the level of background continuum radiation and intensities of atomic lines. Impurities in the EAST facility in the form of carbon bearing species are also modeled to estimate the level of contaminants and their impact on the comparisons. The discrepancies, although large is some cases, exhibit order and consistency. A set of tests and analyses improvements are proposed as forward work plan in order to confirm or reject various proposed reasons for the observed discrepancies.

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

PubMed

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

2018-03-15

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 >20μm 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 Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction

PubMed Central

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

Caveats for correlative species distribution modeling

USGS Publications Warehouse

Jarnevich, Catherine S.; Stohlgren, Thomas J.; Kumar, Sunil; Morisette, Jeffrey T.; Holcombe, Tracy R.

2015-01-01

Correlative species distribution models are becoming commonplace in the scientific literature and public outreach products, displaying locations, abundance, or suitable environmental conditions for harmful invasive species, threatened and endangered species, or species of special concern. Accurate species distribution models are useful for efficient and adaptive management and conservation, research, and ecological forecasting. Yet, these models are often presented without fully examining or explaining the caveats for their proper use and interpretation and are often implemented without understanding the limitations and assumptions of the model being used. We describe common pitfalls, assumptions, and caveats of correlative species distribution models to help novice users and end users better interpret these models. Four primary caveats corresponding to different phases of the modeling process, each with supporting documentation and examples, include: (1) all sampling data are incomplete and potentially biased; (2) predictor variables must capture distribution constraints; (3) no single model works best for all species, in all areas, at all spatial scales, and over time; and (4) the results of species distribution models should be treated like a hypothesis to be tested and validated with additional sampling and modeling in an iterative process.

Bounding Species Distribution Models

NASA Technical Reports Server (NTRS)

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].

Target Scattering Metrics: Model-Model and Model-Data Comparisons

DTIC Science & Technology

2017-12-13

measured synthetic aperture sonar (SAS) data or from numerical models is investigated. Metrics are needed for quantitative comparisons for signals...candidate metrics for model-model comparisons are examined here with a goal to consider raw data prior to its reduction to data products, which may...be suitable for input to classification schemes. The investigated metrics are then applied to model-data comparisons. INTRODUCTION Metrics for

Target Scattering Metrics: Model-Model and Model Data comparisons

DTIC Science & Technology

2017-12-13

measured synthetic aperture sonar (SAS) data or from numerical models is investigated. Metrics are needed for quantitative comparisons for signals...candidate metrics for model-model comparisons are examined here with a goal to consider raw data prior to its reduction to data products, which may...be suitable for input to classification schemes. The investigated metrics are then applied to model-data comparisons. INTRODUCTION Metrics for

Incorporating Context Dependency of Species Interactions in Species Distribution Models.

PubMed

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

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

NASA Astrophysics Data System (ADS)

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.

Comparison of model results transporting the odd nitrogen family with results transporting separate odd nitrogen species

NASA Technical Reports Server (NTRS)

Douglass, Anne R.; Jackman, Charles H.; Stolarski, Richard S.

1989-01-01

A fast two-dimensional residual circulation stratospheric family transport model, designed to minimize computer requirements, is developed. The model was used to calculate the ambient and perturbed atmospheres in which odd nitrogen species are transported as a family, and the results were compared with calculations in which HNO3, N2O5, ClONO2, and HO2NO2 are transported separately. It was found that ozone distributions computed by the two models for a present-day atmosphere are nearly identical. Good agreement was also found between calculated species concentrations and the ozone response, indicating the general applicability of the odd-nitrogen family approximations.

Estimating species richness and accumulation by modeling species occurrence and detectability

USGS Publications Warehouse

Dorazio, R.M.; Royle, J. Andrew; Soderstrom, B.; Glimskarc, A.

2006-01-01

A statistical model is developed for estimating species richness and accumulation by formulating these community-level attributes as functions of model-based estimators of species occurrence while accounting for imperfect detection of individual species. The model requires a sampling protocol wherein repeated observations are made at a collection of sample locations selected to be representative of the community. This temporal replication provides the data needed to resolve the ambiguity between species absence and nondetection when species are unobserved at sample locations. Estimates of species richness and accumulation are computed for two communities, an avian community and a butterfly community. Our model-based estimates suggest that detection failures in many bird species were attributed to low rates of occurrence, as opposed to simply low rates of detection. We estimate that the avian community contains a substantial number of uncommon species and that species richness greatly exceeds the number of species actually observed in the sample. In fact, predictions of species accumulation suggest that even doubling the number of sample locations would not have revealed all of the species in the community. In contrast, our analysis of the butterfly community suggests that many species are relatively common and that the estimated richness of species in the community is nearly equal to the number of species actually detected in the sample. Our predictions of species accumulation suggest that the number of sample locations actually used in the butterfly survey could have been cut in half and the asymptotic richness of species still would have been attained. Our approach of developing occurrence-based summaries of communities while allowing for imperfect detection of species is broadly applicable and should prove useful in the design and analysis of surveys of biodiversity.

Species distribution modelling for plant communities: Stacked single species or multivariate modelling approaches?

Treesearch

Emilie B. Henderson; Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Harold S.J. Zald

2014-01-01

Landscape management and conservation planning require maps of vegetation composition and structure over large regions. Species distribution models (SDMs) are often used for individual species, but projects mapping multiple species are rarer. We compare maps of plant community composition assembled by stacking results from many SDMs with multivariate maps constructed...

Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models

PubMed Central

de la Estrella, Manuel; Mateo, Rubén G.; Wieringa, Jan J.; Mackinder, Barbara; Muñoz, Jesús

2012-01-01

Objectives Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning. Methodology Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types. Results/Conclusions Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall

Identification of four Aconitum species used as "Caowu" in herbal markets by 3D reconstruction and microstructural comparison.

PubMed

Liu, Chan-Chan; Cheng, Ming-En; Peng, Huasheng; Duan, Hai-Yan; Huang, Luqi

2015-05-01

Authentication is the first priority when evaluating the quality of Chinese herbal medicines, particularly highly toxic medicines. The most commonly used authentication methods are morphological identification and microscopic identification. Unfortunately, these methods could not effectively evaluate some herbs with complex interior structures, such as root of Aconitum species with a circular conical shape and an interior structure with successive changes. Defining the part that should be selected as the standard plays an essential role in accurate microscopic identification. In this study, we first present a visual 3D model of Aconitum carmichaeli Debx. constructed obtained from microscopic analysis of serial sections. Based on this model, we concluded that the point of largest root diameter should be used as the standard for comparison and identification. The interior structure at this point is reproducible and its shape and appearance can easily be used to distinguish among species. We also report details of the interior structures of parts not shown in the 3D model, such as stone cells and cortical thickness. To demonstrate the usefulness of the results from the 3D model, we have distinguished the microscopic structures, at their largest segments, of the other three Aconitum species used for local habitat species of Caowu. This work provides the basis for resolution of some debate regarding the microstructural differences among these species. Thus, we conclude that the 3D model composed of serial sections has enabled the selection of a standard cross-section that will enable the accurate identification of Aconitum species in Chinese medicine. © 2015 Wiley Periodicals, Inc.

Trapped Radiation Model Uncertainties: Model-Data and Model-Model Comparisons

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.

2000-01-01

The standard AP8 and AE8 models for predicting trapped proton and electron environments have been compared with several sets of flight data to evaluate model uncertainties. Model comparisons are made with flux and dose measurements made on various U.S. low-Earth orbit satellites (APEX, CRRES, DMSP, LDEF, NOAA) and Space Shuttle flights, on Russian satellites (Photon-8, Cosmos-1887, Cosmos-2044), and on the Russian Mir Space Station. This report gives the details of the model-data comparisons-summary results in terms of empirical model uncertainty factors that can be applied for spacecraft design applications are given in a combination report. The results of model-model comparisons are also presented from standard AP8 and AE8 model predictions compared with the European Space Agency versions of AP8 and AE8 and with Russian-trapped radiation models.

Trapped Radiation Model Uncertainties: Model-Data and Model-Model Comparisons

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.

2000-01-01

The standard AP8 and AE8 models for predicting trapped proton and electron environments have been compared with several sets of flight data to evaluate model uncertainties. Model comparisons are made with flux and dose measurements made on various U.S. low-Earth orbit satellites (APEX, CRRES, DMSP. LDEF, NOAA) and Space Shuttle flights, on Russian satellites (Photon-8, Cosmos-1887, Cosmos-2044), and on the Russian Mir space station. This report gives the details of the model-data comparisons -- summary results in terms of empirical model uncertainty factors that can be applied for spacecraft design applications are given in a companion report. The results of model-model comparisons are also presented from standard AP8 and AE8 model predictions compared with the European Space Agency versions of AP8 and AE8 and with Russian trapped radiation models.

Inter-species variation in yolk steroid levels and a cowbird-host comparison

USGS Publications Warehouse

Hahn, D. Caldwell; Hatfield, Jeffrey S.; Abdelnabi, Mahmoud A.; Wu, Julie M.; Igl, Lawrence D.; Ottinger, Mary A.

2005-01-01

We examined variability in yolk hormone levels among songbird species and the role of yolk steroids as a mechanism for enhanced exploitation of hosts by the parasitic Brown-headed Cowbird Molothrus ater. Within-clutch variation in yolk steroids has been found in several avian species in single species studies, but few comparisons have been made among species. We found a large range of differences in yolk testosterone among the seven passerine species examined, with significant differences between those at the high end (Song Sparrow Melospiza melodia , Red-winged Blackbird Agelaius phoeniceus, and House Sparrow, Passer domesticus ) and those at the low end (Eastern Phoebe Sayornis phoebe, and House Finch Carpodacus mexicanus ). We also found that the testosterone level in cowbird eggs was intermediate in relation to host species levels and was significantly lower than that in three common cowbird hosts (Song Sparrow, Red-winged Blackbird, and House Sparrow), but not significantly different from three others. Geographical comparisons of yolk testosterone levels in all cowbird subspecies and populations from several regions showed no significant differences, though a trend that deserves further exploration was the pattern of lowest level in the ancestral population of cowbirds in the central prairies and of highest level in the northwestern population where range invasion occurred approximately 40 years ago. The levels of 17 betaestradiol were similar in the seven songbird species examined, which is consistent with current hypotheses that this hormone plays a role in embryonic sexual differentiation. Further investigation is needed to determine whether the large differences observed among species in absolute level of yolk testosterone are the relevant focal point or whether target tissue sensitivity differences mediate the effects of this yolk steroid, particularly between parasitic and non-parasitic species.

Tropospheric OH and HO2 radicals: field measurements and model comparisons.

PubMed

Stone, Daniel; Whalley, Lisa K; Heard, Dwayne E

2012-10-07

The hydroxyl radical, OH, initiates the removal of the majority of trace gases in the atmosphere, and together with the closely coupled species, the hydroperoxy radical, HO(2), is intimately involved in the oxidation chemistry of the atmosphere. This critical review discusses field measurements of local concentrations of OH and HO(2) radicals in the troposphere, and in particular the comparisons that have been made with numerical model calculations containing a detailed chemical mechanism. The level of agreement between field measurements of OH and HO(2) concentrations and model calculations for a given location provides an indication of the degree of understanding of the underlying oxidation chemistry. We review the measurement-model comparisons for a range of different environments sampled from the ground and from aircraft, including the marine boundary layer, continental low-NO(x) regions influenced by biogenic emissions, the polluted urban boundary layer, and polar regions. Although good agreement is found for some environments, there are significant discrepancies which remain unexplained, a notable example being unpolluted, forested regions. OH and HO(2) radicals are difficult species to measure in the troposphere, and we also review changes in detection methodology, quality assurance procedures such as instrument intercomparisons, and potential interferences.

Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction

USGS Publications Warehouse

Jones-Farrand, D. Todd; Fearer, Todd M.; Thogmartin, Wayne E.; Thompson, Frank R.; Nelson, Mark D.; Tirpak, John M.

2011-01-01

Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (P , 0.05). Red-headed Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region. We assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk. Based on our results, models developed independently for the same purpose

Phenotypic and genomic comparison of Mycobacterium aurum and surrogate model species to Mycobacterium tuberculosis: implications for drug discovery.

PubMed

Namouchi, Amine; Cimino, Mena; Favre-Rochex, Sandrine; Charles, Patricia; Gicquel, Brigitte

2017-07-13

Tuberculosis (TB) is caused by Mycobacterium tuberculosis and represents one of the major challenges facing drug discovery initiatives worldwide. The considerable rise in bacterial drug resistance in recent years has led to the need of new drugs and drug regimens. Model systems are regularly used to speed-up the drug discovery process and circumvent biosafety issues associated with manipulating M. tuberculosis. These include the use of strains such as Mycobacterium smegmatis and Mycobacterium marinum that can be handled in biosafety level 2 facilities, making high-throughput screening feasible. However, each of these model species have their own limitations. We report and describe the first complete genome sequence of Mycobacterium aurum ATCC23366, an environmental mycobacterium that can also grow in the gut of humans and animals as part of the microbiota. This species shows a comparable resistance profile to that of M. tuberculosis for several anti-TB drugs. The aims of this study were to (i) determine the drug resistance profile of a recently proposed model species, Mycobacterium aurum, strain ATCC23366, for anti-TB drug discovery as well as Mycobacterium smegmatis and Mycobacterium marinum (ii) sequence and annotate the complete genome sequence of this species obtained using Pacific Bioscience technology (iii) perform comparative genomics analyses of the various surrogate strains with M. tuberculosis (iv) discuss how the choice of the surrogate model used for drug screening can affect the drug discovery process. We describe the complete genome sequence of M. aurum, a surrogate model for anti-tuberculosis drug discovery. Most of the genes already reported to be associated with drug resistance are shared between all the surrogate strains and M. tuberculosis. We consider that M. aurum might be used in high-throughput screening for tuberculosis drug discovery. We also highly recommend the use of different model species during the drug discovery screening process.

One-dimensional turbulence modeling of a turbulent counterflow flame with comparison to DNS

DOE PAGES

Jozefik, Zoltan; Kerstein, Alan R.; Schmidt, Heiko; ...

2015-06-01

The one-dimensional turbulence (ODT) model is applied to a reactant-to-product counterflow configuration and results are compared with DNS data. The model employed herein solves conservation equations for momentum, energy, and species on a one dimensional (1D) domain corresponding to the line spanning the domain between nozzle orifice centers. The effects of turbulent mixing are modeled via a stochastic process, while the Kolmogorov and reactive length and time scales are explicitly resolved and a detailed chemical kinetic mechanism is used. Comparisons between model and DNS results for spatial mean and root-mean-square (RMS) velocity, temperature, and major and minor species profiles aremore » shown. The ODT approach shows qualitatively and quantitatively reasonable agreement with the DNS data. Scatter plots and statistics conditioned on temperature are also compared for heat release rate and all species. ODT is able to capture the range of results depicted by DNS. As a result, conditional statistics show signs of underignition.« less

Modeling phytoplankton community in reservoirs. A comparison between taxonomic and functional groups-based models.

PubMed

Di Maggio, Jimena; Fernández, Carolina; Parodi, Elisa R; Diaz, M Soledad; Estrada, Vanina

2016-01-01

In this paper we address the formulation of two mechanistic water quality models that differ in the way the phytoplankton community is described. We carry out parameter estimation subject to differential-algebraic constraints and validation for each model and comparison between models performance. The first approach aggregates phytoplankton species based on their phylogenetic characteristics (Taxonomic group model) and the second one, on their morpho-functional properties following Reynolds' classification (Functional group model). The latter approach takes into account tolerance and sensitivity to environmental conditions. The constrained parameter estimation problems are formulated within an equation oriented framework, with a maximum likelihood objective function. The study site is Paso de las Piedras Reservoir (Argentina), which supplies water for consumption for 450,000 population. Numerical results show that phytoplankton morpho-functional groups more closely represent each species growth requirements within the group. Each model performance is quantitatively assessed by three diagnostic measures. Parameter estimation results for seasonal dynamics of the phytoplankton community and main biogeochemical variables for a one-year time horizon are presented and compared for both models, showing the functional group model enhanced performance. Finally, we explore increasing nutrient loading scenarios and predict their effect on phytoplankton dynamics throughout a one-year time horizon. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

Treesearch

Louis R. Iverson; Frank R. Thompson; Stephen Matthews; Matthew Peters; Anantha Prasad; William D. Dijak; Jacob Fraser; Wen J. Wang; Brice Hanberry; Hong He; Maria Janowiak; Patricia Butler; Leslie Brandt; Chris Swanston

2016-01-01

Context. Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process...

Stochastic species abundance models involving special copulas

NASA Astrophysics Data System (ADS)

Huillet, Thierry E.

2018-01-01

Copulas offer a very general tool to describe the dependence structure of random variables supported by the hypercube. Inspired by problems of species abundances in Biology, we study three distinct toy models where copulas play a key role. In a first one, a Marshall-Olkin copula arises in a species extinction model with catastrophe. In a second one, a quasi-copula problem arises in a flagged species abundance model. In a third model, we study completely random species abundance models in the hypercube as those, not of product type, with uniform margins and singular. These can be understood from a singular copula supported by an inflated simplex. An exchangeable singular Dirichlet copula is also introduced, together with its induced completely random species abundance vector.

Modeling of inhomogeneous mixing of plasma species in argon-steam arc discharge

NASA Astrophysics Data System (ADS)

Jeništa, J.; Takana, H.; Uehara, S.; Nishiyama, H.; Bartlová, M.; Aubrecht, V.; Murphy, A. B.

2018-01-01

This paper presents numerical simulation of mixing of argon- and water-plasma species in an argon-steam arc discharge generated in a thermal plasma generator with the combined stabilization of arc by axial gas flow (argon) and water vortex. The diffusion of plasma species itself is described by the combined diffusion coefficients method in which the coefficients describe the diffusion of argon ‘gas,’ with respect to water vapor ‘gas.’ Diffusion processes due to the gradients of mass density, temperature, pressure, and an electric field have been considered in the model. Calculations for currents 150-400 A with 15-22.5 standard liters per minute (slm) of argon reveal inhomogeneous mixing of argon and oxygen-hydrogen species with the argon species prevailing near the arc axis. All the combined diffusion coefficients exhibit highly nonlinear distribution of their values within the discharge, depending on the temperature, pressure, and argon mass fraction of the plasma. The argon diffusion mass flux is driven mainly by the concentration and temperature space gradients. Diffusions due to pressure gradients and due to the electric field are of about 1 order lower. Comparison with our former calculations based on the homogeneous mixing assumption shows differences in temperature, enthalpy, radiation losses, arc efficiency, and velocity at 400 A. Comparison with available experiments exhibits very good qualitative and quantitative agreement for the radial temperature and velocity profiles 2 mm downstream of the exit nozzle.

New trends in species distribution modelling

USGS Publications Warehouse

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.

Ecophysiology of wetland plant roots: A modelling comparison of aeration in relation to species distribution

USGS Publications Warehouse

Sorrell, B.K.; Mendelssohn, I.A.; McKee, K.L.; Woods, R.A.

2000-01-01

This study examined the potential for inter-specific differences in root aeration to determine wetland plant distribution in nature. We compared aeration in species that differ in the type of sediment and depth of water they colonize. Differences in root anatomy, structure and physiology were applied to aeration models that predicted the maximum possible aerobic lengths and development of anoxic zones in primary adventitious roots. Differences in anatomy and metabolism that provided higher axial fluxes of oxygen allowed deeper root growth in species that favour more reducing sediments and deeper water. Modelling identified factors that affected growth in anoxic soils through their effects on aeration. These included lateral root formation, which occurred at the expense of extension of the primary root because of the additional respiratory demand they imposed, reducing oxygen fluxes to the tip and stele, and the development of stelar anoxia. However, changes in sediment oxygen demand had little detectable effect on aeration in the primary roots due to their low wall permeability and high surface impedance, but appeared to reduce internal oxygen availability by accelerating loss from laterals. The development of pressurized convective gas flow in shoots and rhizomes was also found to be important in assisting root aeration, as it maintained higher basal oxygen concentrations at the rhizome-root junctions in species growing into deep water. (C) 2000 Annals of Botany Company.

Richards-like two species population dynamics model.

PubMed

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.

Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula

PubMed Central

Schorr, G; Holstein, N; Pearman, P B; Guisan, A; Kadereit, J W

2012-01-01

The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data. PMID:22833799

Species diversity and predation strategies in a multiple species predator-prey model

NASA Astrophysics Data System (ADS)

Mullan, Rory; Glass, David H.; McCartney, Mark

2015-08-01

A single predator, single prey ecological model, in which the behaviour of the populations relies upon two control parameters has been expanded to allow for multiple predators and prey to occupy the ecosystem. The diversity of the ecosystem that develops as the model runs is analysed by assessing how many predator or prey species survive. Predation strategies that dictate how the predators distribute their efforts across the prey are introduced in this multiple species model. The paper analyses various predation strategies and highlights their effect on the survival of the predators and prey species.

Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods

USGS Publications Warehouse

Moisen, Gretchen G.; Freeman, E.A.; Blackard, J.A.; Frescino, T.S.; Zimmermann, N.E.; Edwards, T.C.

2006-01-01

Many efforts are underway to produce broad-scale forest attribute maps by modelling forest class and structure variables collected in forest inventories as functions of satellite-based and biophysical information. Typically, variants of classification and regression trees implemented in Rulequest's?? See5 and Cubist (for binary and continuous responses, respectively) are the tools of choice in many of these applications. These tools are widely used in large remote sensing applications, but are not easily interpretable, do not have ties with survey estimation methods, and use proprietary unpublished algorithms. Consequently, three alternative modelling techniques were compared for mapping presence and basal area of 13 species located in the mountain ranges of Utah, USA. The modelling techniques compared included the widely used See5/Cubist, generalized additive models (GAMs), and stochastic gradient boosting (SGB). Model performance was evaluated using independent test data sets. Evaluation criteria for mapping species presence included specificity, sensitivity, Kappa, and area under the curve (AUC). Evaluation criteria for the continuous basal area variables included correlation and relative mean squared error. For predicting species presence (setting thresholds to maximize Kappa), SGB had higher values for the majority of the species for specificity and Kappa, while GAMs had higher values for the majority of the species for sensitivity. In evaluating resultant AUC values, GAM and/or SGB models had significantly better results than the See5 models where significant differences could be detected between models. For nine out of 13 species, basal area prediction results for all modelling techniques were poor (correlations less than 0.5 and relative mean squared errors greater than 0.8), but SGB provided the most stable predictions in these instances. SGB and Cubist performed equally well for modelling basal area for three species with moderate prediction success

MANTIS: a phylogenetic framework for multi-species genome comparisons.

PubMed

Tzika, Athanasia C; Helaers, Raphaël; Van de Peer, Yves; Milinkovitch, Michel C

2008-01-15

Practitioners of comparative genomics face huge analytical challenges as whole genome sequences and functional/expression data accumulate. Furthermore, the field would greatly benefit from a better integration of this wealth of data with evolutionary concepts. Here, we present MANTIS, a relational database for the analysis of (i) gains and losses of genes on specific branches of the metazoan phylogeny, (ii) reconstructed genome content of ancestral species and (iii) over- or under-representation of functions/processes and tissue specificity of gained, duplicated and lost genes. MANTIS estimates the most likely positions of gene losses on the true phylogeny using a maximum-likelihood function. A user-friendly interface and an extensive query system allow to investigate questions pertaining to gene identity, phylogenetic mapping and function/expression parameters. MANTIS is freely available at http://www.mantisdb.org and constitutes the missing link between multi-species genome comparisons and functional analyses.

Delineating generalized species boundaries from species distribution data and a species distribution model

Treesearch

Matthew P. Peters; Stephen N. Matthews; Louis R. Iverson; Anantha M. Prasad

2013-01-01

Species distribution models (SDM) are commonly used to provide information about species ranges or extents, and often are intended to represent the entire area of potential occupancy or suitable habitat in which individuals occur. While SDMs can provide results over various geographic extents, they normally operate within a grid and cannot delimit distinct, smooth...

Combined field/modelling approaches to represent the air-vegetation distribution of benzo[a]pyrene using different vegetation species

NASA Astrophysics Data System (ADS)

Ratola, Nuno; Jiménez-Guerrero, Pedro

2015-04-01

A strategy designed to combine the features of field-based experiments and modelling approaches is presented in this work to assess air-vegetation distribution of benzo(a)pyrene (BaP) in the Iberian Peninsula (IP). Given the lack of simultaneous data in both environmental matrices, a methodology with two main steps was employed. First, evaluating the simulations with the chemistry transport model (CTM) WRF (Weather Research and Forecasting) + CHIMERE data against the European Monitoring and Evaluation Programme (EMEP) network, to test the aptitude of the CTM to replicate the respective atmospheric levels. Then, using modelled concentrations and a method to estimate air levels of BaP from biomonitoring data to compare the performance of different pine species (Pinus pinea, Pinus pinaster, Pinus nigra and Pinus halepensis) to describe the atmospheric evidences. The comparison of modelling vs. biomonitoring has a higher dependence on the location of the sampling points, rather than on the pine species, as some tend to overestimate and others to underestimate BaP concentrations, in most cases regardless of the season. The climatology of the canopy levels of BaP was successfully validated with the concentrations in pine needles (most biases below 26%), however, the model was unable to distinguish between species. This should be taken into consideration in future studies, as biases can rise up to 48%, especially in summer and autumn, the. The comparison with biomonitoring data showed a similar pattern, but with the best results in the warmer months.

Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models

ERIC Educational Resources Information Center

Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum

2011-01-01

Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…

A cross-species analysis method to analyze animal models' similarity to human's disease state

PubMed Central

2012-01-01

Background Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. Results We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. Conclusions We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for

A cross-species analysis method to analyze animal models' similarity to human's disease state.

PubMed

Yu, Shuhao; Zheng, Lulu; Li, Yun; Li, Chunyan; Ma, Chenchen; Li, Yixue; Li, Xuan; Hao, Pei

2012-01-01

Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as

Hindlimb muscle architecture in non-human great apes and a comparison of methods for analysing inter-species variation

PubMed Central

Myatt, Julia P; Crompton, Robin H; Thorpe, Susannah K S

2011-01-01

By relating an animal's morphology to its functional role and the behaviours performed, we can further develop our understanding of the selective factors and constraints acting on the adaptations of great apes. Comparison of muscle architecture between different ape species, however, is difficult because only small sample sizes are ever available. Further, such samples are often comprised of different age–sex classes, so studies have to rely on scaling techniques to remove body mass differences. However, the reliability of such scaling techniques has been questioned. As datasets increase in size, more reliable statistical analysis may eventually become possible. Here we employ geometric and allometric scaling techniques, and ancovas (a form of general linear model, GLM) to highlight and explore the different methods available for comparing functional morphology in the non-human great apes. Our results underline the importance of regressing data against a suitable body size variable to ascertain the relationship (geometric or allometric) and of choosing appropriate exponents by which to scale data. ancova models, while likely to be more robust than scaling for species comparisons when sample sizes are high, suffer from reduced power when sample sizes are low. Therefore, until sample sizes are radically increased it is preferable to include scaling analyses along with ancovas in data exploration. Overall, the results obtained from the different methods show little significant variation, whether in muscle belly mass, fascicle length or physiological cross-sectional area between the different species. This may reflect relatively close evolutionary relationships of the non-human great apes; a universal influence on morphology of generalised orthograde locomotor behaviours or, quite likely, both. PMID:21507000

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

PubMed

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

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

PubMed

Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

2003-05-01

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

Adaptive invasive species distribution models: A framework for modeling incipient invasions

USGS Publications Warehouse

Uden, Daniel R.; Allen, Craig R.; Angeler, David G.; Corral, Lucia; Fricke, Kent A.

2015-01-01

The utilization of species distribution model(s) (SDM) for approximating, explaining, and predicting changes in species’ geographic locations is increasingly promoted for proactive ecological management. Although frameworks for modeling non-invasive species distributions are relatively well developed, their counterparts for invasive species—which may not be at equilibrium within recipient environments and often exhibit rapid transformations—are lacking. Additionally, adaptive ecological management strategies address the causes and effects of biological invasions and other complex issues in social-ecological systems. We conducted a review of biological invasions, species distribution models, and adaptive practices in ecological management, and developed a framework for adaptive, niche-based, invasive species distribution model (iSDM) development and utilization. This iterative, 10-step framework promotes consistency and transparency in iSDM development, allows for changes in invasive drivers and filters, integrates mechanistic and correlative modeling techniques, balances the avoidance of type 1 and type 2 errors in predictions, encourages the linking of monitoring and management actions, and facilitates incremental improvements in models and management across space, time, and institutional boundaries. These improvements are useful for advancing coordinated invasive species modeling, management and monitoring from local scales to the regional, continental and global scales at which biological invasions occur and harm native ecosystems and economies, as well as for anticipating and responding to biological invasions under continuing global change.

Occupancy modeling and estimation of the holiday darter species complex within the Etowah River system

USGS Publications Warehouse

Anderson, Gregory B.; Freeman, Mary C.; Hagler, Megan M.; Freeman, Byron J.

2012-01-01

Documenting the status of rare fishes is a crucial step in effectively managing populations and implementing regulatory mechanisms of protection. In recent years, site occupancy has become an increasingly popular metric for assessing populations, but species distribution models that do not account for imperfect detection can underestimate the proportion of sites occupied and the strength of the relationship with a hypothesized covariate. However, valid detection requires temporal or spatial replication, which is often not feasible due to logistical or budget constraints. In this study, we used a method that allowed for spatial replication during a single visit to evaluate the current status of the holiday darter species complex, Etheostoma sp. cf. E. brevirostrum, within the Etowah River system. Moreover, the modeling approach used in this study facilitated comparisons of factors influencing stream occupancy as well as species detection within sites. The results suggest that there is less habitat available for the Etowah holiday darter form (Etheostoma sp. cf. E. brevirostrum B) than for the Amicalola holiday darter form (Etheostoma sp. cf. E. brevirostrum A). Additionally, occupancy models suggest that even small decreases in forest cover within these headwater systems adversely affect holiday darter populations.

Nyala and Bushbuck I: A Competing Species Model.

ERIC Educational Resources Information Center

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

NASA Technical Reports Server (NTRS)

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

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

PubMed

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.

Task-Driven Comparison of Topic Models.

PubMed

Alexander, Eric; Gleicher, Michael

2016-01-01

Topic modeling, a method of statistically extracting thematic content from a large collection of texts, is used for a wide variety of tasks within text analysis. Though there are a growing number of tools and techniques for exploring single models, comparisons between models are generally reduced to a small set of numerical metrics. These metrics may or may not reflect a model's performance on the analyst's intended task, and can therefore be insufficient to diagnose what causes differences between models. In this paper, we explore task-centric topic model comparison, considering how we can both provide detail for a more nuanced understanding of differences and address the wealth of tasks for which topic models are used. We derive comparison tasks from single-model uses of topic models, which predominantly fall into the categories of understanding topics, understanding similarity, and understanding change. Finally, we provide several visualization techniques that facilitate these tasks, including buddy plots, which combine color and position encodings to allow analysts to readily view changes in document similarity.

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

USGS Publications Warehouse

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

Considerations for building climate-based species distribution models

USGS Publications Warehouse

Bucklin, David N.; Basille, Mathieu; Romañach, Stephanie; Brandt, Laura A.; Mazzotti, Frank J.; Watling, James I.

2016-01-01

Climate plays an important role in the distribution of species. A given species may adjust to new conditions in-place, move to new areas with suitable climates, or go extinct. Scientists and conservation practitioners use mathematical models to predict the effects of future climate change on wildlife and plan for a biodiverse future. This 8-page fact sheet written by David N. Bucklin, Mathieu Basille, Stephanie S. Romañach, Laura A. Brandt, Frank J. Mazzotti, and James I. Watling and published by the Department of Wildlife Ecology and Conservation explains how, with a better understanding of species distribution models, we can predict how species may respond to climate change. The models alone cannot tell us how a certain species will actually respond to changes in climate, but they can inform conservation planning that aims to allow species to both adapt in place and (for those that are able to) move to newly suitable areas. Such planning will likely minimize loss of biodiversity due to climate change.

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

PubMed

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.

A Rapid Approach to Modeling Species-Habitat Relationships

NASA Technical Reports Server (NTRS)

Carter, Geoffrey M.; Breinger, David R.; Stolen, Eric D.

2005-01-01

A growing number of species require conservation or management efforts. Success of these activities requires knowledge of the species' occurrence pattern. Species-habitat models developed from GIS data sources are commonly used to predict species occurrence but commonly used data sources are often developed for purposes other than predicting species occurrence and are of inappropriate scale and the techniques used to extract predictor variables are often time consuming and cannot be repeated easily and thus cannot efficiently reflect changing conditions. We used digital orthophotographs and a grid cell classification scheme to develop an efficient technique to extract predictor variables. We combined our classification scheme with a priori hypothesis development using expert knowledge and a previously published habitat suitability index and used an objective model selection procedure to choose candidate models. We were able to classify a large area (57,000 ha) in a fraction of the time that would be required to map vegetation and were able to test models at varying scales using a windowing process. Interpretation of the selected models confirmed existing knowledge of factors important to Florida scrub-jay habitat occupancy. The potential uses and advantages of using a grid cell classification scheme in conjunction with expert knowledge or an habitat suitability index (HSI) and an objective model selection procedure are discussed.

Species comparison of the physical properties of loblolly and slash pine wood and bark

Treesearch

Thomas L. Eberhardt; Joseph Dahlen; Laurence Schimleck

2017-01-01

Composition of the southern pine forest is now predominated by two species, loblolly pine (Pinus taeda L.) and slash pine (Pinus elliottii Engelm.), owing to fire suppression activities, natural regeneration on abandoned agricultural lands, and extensive planting. Comparison of the wood and bark physical properties of these...

SPECIES - EVALUATING THERMODYNAMIC PROPERTIES, TRANSPORT PROPERTIES & EQUILIBRIUM CONSTANTS OF AN 11-SPECIES AIR MODEL

NASA Technical Reports Server (NTRS)

Thompson, R. A.

1994-01-01

Accurate numerical prediction of high-temperature, chemically reacting flowfields requires a knowledge of the physical properties and reaction kinetics for the species involved in the reacting gas mixture. Assuming an 11-species air model at temperatures below 30,000 degrees Kelvin, SPECIES (Computer Codes for the Evaluation of Thermodynamic Properties, Transport Properties, and Equilibrium Constants of an 11-Species Air Model) computes values for the species thermodynamic and transport properties, diffusion coefficients and collision cross sections for any combination of the eleven species, and reaction rates for the twenty reactions normally occurring. The species represented in the model are diatomic nitrogen, diatomic oxygen, atomic nitrogen, atomic oxygen, nitric oxide, ionized nitric oxide, the free electron, ionized atomic nitrogen, ionized atomic oxygen, ionized diatomic nitrogen, and ionized diatomic oxygen. Sixteen subroutines compute the following properties for both a single species, interaction pair, or reaction, and an array of all species, pairs, or reactions: species specific heat and static enthalpy, species viscosity, species frozen thermal conductivity, diffusion coefficient, collision cross section (OMEGA 1,1), collision cross section (OMEGA 2,2), collision cross section ratio, and equilibrium constant. The program uses least squares polynomial curve-fits of the most accurate data believed available to provide the requested values more quickly than is possible with table look-up methods. The subroutines for computing transport coefficients and collision cross sections use additional code to correct for any electron pressure when working with ionic species. SPECIES was developed on a SUN 3/280 computer running the SunOS 3.5 operating system. It is written in standard FORTRAN 77 for use on any machine, and requires roughly 92K memory. The standard distribution medium for SPECIES is a 5.25 inch 360K MS-DOS format diskette. The contents of the

Comparison of Two Freshwater Turtle Species as Monitors of Environmental Contamination

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meyers-Schone, L.

1990-01-01

Two species of turtles that occupy different ecological niches were compared for their usefulness as monitors of contamination in freshwater ecosystems. Trachemvs scrinta (Agassiz) (yellow-bellied slider) and Chelvdra sernentina (Linnaeus) (common snapping turtle) were selected for comparison based on species abundance and differences in food habits and sediment contact. A review of the literature on contaminants in turtles and results of preliminary surveys conducted at the field sites, which are included in this study, were used to direct and focus this research project. White Oak Lake, a settling basin for low-level radioactive and nonradioactive contaminants, and Bearden Creek Embayment, anmore » uncontaminated reference site upriver, were used as study sites in the investigation of turtles as indicators of chemical contamination. Turtles were analyzed for concentrations of strontium-go, cesium-137, cobalt 60, and mercury in specific target tissues, and for single-stranded DNA breaks, a non-specific indicator of possible exposure to genotoxic agents in the environment. Significantly higher concentrations of {sup 90}Sr, {sup 137}Cs, {sup 60}Co, and mercury were detected in turtles from White Oak Lake than in turtles from the reference site. In addition, turtles from White Oak Lake contained a significantly greater amount of DNA damage than those from the reference site. Although this suggests greater exposure of White Oak Lake turtles to genotoxic agents, further studies are needed to establish the cause of the enhanced amount of single-stranded breaks. Interspecific comparisons of the turtles from White Oak Lake indicated that diet may play a significant role in the exposure of turtles to certain contaminants. No difference was detected between the concentrations of {sup 90}Sr, {sup 137}Cs, {sup 60}Co between the two species.« less

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

PubMed

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

Species Tree Inference Using a Mixture Model.

PubMed

Ullah, Ikram; Parviainen, Pekka; Lagergren, Jens

2015-09-01

Species tree reconstruction has been a subject of substantial research due to its central role across biology and medicine. A species tree is often reconstructed using a set of gene trees or by directly using sequence data. In either of these cases, one of the main confounding phenomena is the discordance between a species tree and a gene tree due to evolutionary events such as duplications and losses. Probabilistic methods can resolve the discordance by coestimating gene trees and the species tree but this approach poses a scalability problem for larger data sets. We present MixTreEM-DLRS: A two-phase approach for reconstructing a species tree in the presence of gene duplications and losses. In the first phase, MixTreEM, a novel structural expectation maximization algorithm based on a mixture model is used to reconstruct a set of candidate species trees, given sequence data for monocopy gene families from the genomes under study. In the second phase, PrIME-DLRS, a method based on the DLRS model (Åkerborg O, Sennblad B, Arvestad L, Lagergren J. 2009. Simultaneous Bayesian gene tree reconstruction and reconciliation analysis. Proc Natl Acad Sci U S A. 106(14):5714-5719), is used for selecting the best species tree. PrIME-DLRS can handle multicopy gene families since DLRS, apart from modeling sequence evolution, models gene duplication and loss using a gene evolution model (Arvestad L, Lagergren J, Sennblad B. 2009. The gene evolution model and computing its associated probabilities. J ACM. 56(2):1-44). We evaluate MixTreEM-DLRS using synthetic and biological data, and compare its performance with a recent genome-scale species tree reconstruction method PHYLDOG (Boussau B, Szöllősi GJ, Duret L, Gouy M, Tannier E, Daubin V. 2013. Genome-scale coestimation of species and gene trees. Genome Res. 23(2):323-330) as well as with a fast parsimony-based algorithm Duptree (Wehe A, Bansal MS, Burleigh JG, Eulenstein O. 2008. Duptree: a program for large-scale phylogenetic

Can species distribution models really predict the expansion of invasive species?

PubMed

Barbet-Massin, Morgane; Rome, Quentin; Villemant, Claire; Courchamp, Franck

2018-01-01

Predictive studies are of paramount importance for biological invasions, one of the biggest threats for biodiversity. To help and better prioritize management strategies, species distribution models (SDMs) are often used to predict the potential invasive range of introduced species. Yet, SDMs have been regularly criticized, due to several strong limitations, such as violating the equilibrium assumption during the invasion process. Unfortunately, validation studies-with independent data-are too scarce to assess the predictive accuracy of SDMs in invasion biology. Yet, biological invasions allow to test SDMs usefulness, by retrospectively assessing whether they would have accurately predicted the latest ranges of invasion. Here, we assess the predictive accuracy of SDMs in predicting the expansion of invasive species. We used temporal occurrence data for the Asian hornet Vespa velutina nigrithorax, a species native to China that is invading Europe with a very fast rate. Specifically, we compared occurrence data from the last stage of invasion (independent validation points) to the climate suitability distribution predicted from models calibrated with data from the early stage of invasion. Despite the invasive species not being at equilibrium yet, the predicted climate suitability of validation points was high. SDMs can thus adequately predict the spread of V. v. nigrithorax, which appears to be-at least partially-climatically driven. In the case of V. v. nigrithorax, SDMs predictive accuracy was slightly but significantly better when models were calibrated with invasive data only, excluding native data. Although more validation studies for other invasion cases are needed to generalize our results, our findings are an important step towards validating the use of SDMs in invasion biology.

Can species distribution models really predict the expansion of invasive species?

PubMed Central

Rome, Quentin; Villemant, Claire; Courchamp, Franck

2018-01-01

Predictive studies are of paramount importance for biological invasions, one of the biggest threats for biodiversity. To help and better prioritize management strategies, species distribution models (SDMs) are often used to predict the potential invasive range of introduced species. Yet, SDMs have been regularly criticized, due to several strong limitations, such as violating the equilibrium assumption during the invasion process. Unfortunately, validation studies–with independent data–are too scarce to assess the predictive accuracy of SDMs in invasion biology. Yet, biological invasions allow to test SDMs usefulness, by retrospectively assessing whether they would have accurately predicted the latest ranges of invasion. Here, we assess the predictive accuracy of SDMs in predicting the expansion of invasive species. We used temporal occurrence data for the Asian hornet Vespa velutina nigrithorax, a species native to China that is invading Europe with a very fast rate. Specifically, we compared occurrence data from the last stage of invasion (independent validation points) to the climate suitability distribution predicted from models calibrated with data from the early stage of invasion. Despite the invasive species not being at equilibrium yet, the predicted climate suitability of validation points was high. SDMs can thus adequately predict the spread of V. v. nigrithorax, which appears to be—at least partially–climatically driven. In the case of V. v. nigrithorax, SDMs predictive accuracy was slightly but significantly better when models were calibrated with invasive data only, excluding native data. Although more validation studies for other invasion cases are needed to generalize our results, our findings are an important step towards validating the use of SDMs in invasion biology. PMID:29509789

Poised to prosper? A cross-system comparison of climate change effects on native and non-native species performance

USDA-ARS?s Scientific Manuscript database

Climate change and biological invasions are primary threats to global biodiversity that may operate synergistically in the future. To date, the hypothesis that climate change will favor non-native species has been examined though local comparisons of single or few species. We took a meta-analytical ...

Integrating occupancy models and structural equation models to understand species occurrence

PubMed Central

Joseph, Maxwell B.; Preston, Daniel L.; Johnson, Pieter T. J.

2016-01-01

Understanding the drivers of species occurrence is a fundamental goal in basic and applied ecology. Occupancy models have emerged as a popular approach for inferring species occurrence because they account for problems associated with imperfect detection in field surveys. Current models, however, are limited because they assume covariates are independent (i.e., indirect effects do not occur). Here, we combined structural equation and occupancy models to investigate complex influences on species occurrence while accounting for imperfect detection. These two methods are inherently compatible because they both provide means to make inference on latent or unobserved quantities based on observed data. Our models evaluated the direct and indirect roles of cattle grazing, water chemistry, vegetation, nonnative fishes, and pond permanence on the occurrence of six pond-breeding amphibians, two of which are threatened: the California tiger salamander (Ambystoma californiense), and the California red-legged frog (Rana draytonii). While cattle had strong effects on pond vegetation and water chemistry, their overall effects on amphibian occurrence were small compared to the consistently negative effects of nonnative fish. Fish strongly reduced occurrence probabilities for four of five native amphibians, including both species of conservation concern. These results could help to identify drivers of amphibian declines and to prioritize strategies for amphibian conservation. More generally, this approach facilitates a more mechanistic representation of ideas about the causes of species distributions in space and time. As shown here, occupancy modeling and structural equation modeling are readily combined, and bring rich sets of techniques that may provide unique theoretical and applied insights into basic ecological questions. PMID:27197402

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

USGS Publications Warehouse

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

EPA Science Inventory

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. ...

Shaken but not stirred: Multiscale habitat suitability modeling of sympatric marten species (Martes martes and Martes foina) in the northern Iberian Peninsula

Treesearch

Maria Vergara; Samuel A. Cushman; Fermin Urra; Aritz Ruiz-Gonzalez

2016-01-01

Multispecies and multiscale habitat suitability models (HSM) are important to identify the environmental variables and scales influencing habitat selection and facilitate the comparison of closely related species with different ecological requirements. Objectives This study explores the multiscale relationships of habitat suitability for the pine (Martes...

Modelling invasion for a habitat generalist and a specialist plant species

USGS Publications Warehouse

Evangelista, P.H.; Kumar, S.; Stohlgren, T.J.; Jarnevich, C.S.; Crall, A.W.; Norman, J. B.; Barnett, D.T.

2008-01-01

Predicting suitable habitat and the potential distribution of invasive species is a high priority for resource managers and systems ecologists. Most models are designed to identify habitat characteristics that define the ecological niche of a species with little consideration to individual species' traits. We tested five commonly used modelling methods on two invasive plant species, the habitat generalist Bromus tectorum and habitat specialist Tamarix chinensis, to compare model performances, evaluate predictability, and relate results to distribution traits associated with each species. Most of the tested models performed similarly for each species; however, the generalist species proved to be more difficult to predict than the specialist species. The highest area under the receiver-operating characteristic curve values with independent validation data sets of B. tectorum and T. chinensis was 0.503 and 0.885, respectively. Similarly, a confusion matrix for B. tectorum had the highest overall accuracy of 55%, while the overall accuracy for T. chinensis was 85%. Models for the generalist species had varying performances, poor evaluations, and inconsistent results. This may be a result of a generalist's capability to persist in a wide range of environmental conditions that are not easily defined by the data, independent variables or model design. Models for the specialist species had consistently strong performances, high evaluations, and similar results among different model applications. This is likely a consequence of the specialist's requirement for explicit environmental resources and ecological barriers that are easily defined by predictive models. Although defining new invaders as generalist or specialist species can be challenging, model performances and evaluations may provide valuable information on a species' potential invasiveness.

Predicting species distributions from checklist data using site-occupancy models

USGS Publications Warehouse

Kery, M.; Gardner, B.; Monnerat, C.

2010-01-01

Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent

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

NASA Astrophysics Data System (ADS)

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.

Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions

USGS Publications Warehouse

Royle, J. Andrew; Chandler, Richard B.; Yackulic, Charles; Nichols, James D.

2012-01-01

1. Understanding the factors affecting species occurrence is a pre-eminent focus of applied ecological research. However, direct information about species occurrence is lacking for many species. Instead, researchers sometimes have to rely on so-called presence-only data (i.e. when no direct information about absences is available), which often results from opportunistic, unstructured sampling. MAXENT is a widely used software program designed to model and map species distribution using presence-only data. 2. We provide a critical review of MAXENT as applied to species distribution modelling and discuss how it can lead to inferential errors. A chief concern is that MAXENT produces a number of poorly defined indices that are not directly related to the actual parameter of interest – the probability of occurrence (ψ). This focus on an index was motivated by the belief that it is not possible to estimate ψ from presence-only data; however, we demonstrate that ψ is identifiable using conventional likelihood methods under the assumptions of random sampling and constant probability of species detection. 3. The model is implemented in a convenient r package which we use to apply the model to simulated data and data from the North American Breeding Bird Survey. We demonstrate that MAXENT produces extreme under-predictions when compared to estimates produced by logistic regression which uses the full (presence/absence) data set. We note that MAXENT predictions are extremely sensitive to specification of the background prevalence, which is not objectively estimated using the MAXENT method. 4. As with MAXENT, formal model-based inference requires a random sample of presence locations. Many presence-only data sets, such as those based on museum records and herbarium collections, may not satisfy this assumption. However, when sampling is random, we believe that inference should be based on formal methods that facilitate inference about interpretable ecological quantities

Scale dependence in species turnover reflects variance in species occupancy.

PubMed

McGlinn, Daniel J; Hurlbert, Allen H

2012-02-01

Patterns of species turnover may reflect the processes driving community dynamics across scales. While the majority of studies on species turnover have examined pairwise comparison metrics (e.g., the average Jaccard dissimilarity), it has been proposed that the species-area relationship (SAR) also offers insight into patterns of species turnover because these two patterns may be analytically linked. However, these previous links only apply in a special case where turnover is scale invariant, and we demonstrate across three different plant communities that over 90% of the pairwise turnover values are larger than expected based on scale-invariant predictions from the SAR. Furthermore, the degree of scale dependence in turnover was negatively related to the degree of variance in the occupancy frequency distribution (OFD). These findings suggest that species turnover diverges from scale invariance, and as such pairwise turnover and the slope of the SAR are not redundant. Furthermore, models developed to explain the OFD should be linked with those developed to explain species turnover to achieve a more unified understanding of community structure.

CO2 exposure as translational cross-species experimental model for panic.

PubMed

Leibold, N K; van den Hove, D L A; Viechtbauer, W; Buchanan, G F; Goossens, L; Lange, I; Knuts, I; Lesch, K P; Steinbusch, H W M; Schruers, K R J

2016-09-06

The current diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders are being challenged by the heterogeneity and the symptom overlap of psychiatric disorders. Therefore, a framework toward a more etiology-based classification has been initiated by the US National Institute of Mental Health, the research domain criteria project. The basic neurobiology of human psychiatric disorders is often studied in rodent models. However, the differences in outcome measurements hamper the translation of knowledge. Here, we aimed to present a translational panic model by using the same stimulus and by quantitatively comparing the same outcome measurements in rodents, healthy human subjects and panic disorder patients within one large project. We measured the behavioral-emotional and bodily response to CO2 exposure in all three samples, allowing for a reliable cross-species comparison. We show that CO2 exposure causes a robust fear response in terms of behavior in mice and panic symptom ratings in healthy volunteers and panic disorder patients. To improve comparability, we next assessed the respiratory and cardiovascular response to CO2, demonstrating corresponding respiratory and cardiovascular effects across both species. This project bridges the gap between basic and human research to improve the translation of knowledge between these disciplines. This will allow significant progress in unraveling the etiological basis of panic disorder and will be highly beneficial for refining the diagnostic categories as well as treatment strategies.

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

PubMed

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

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

PubMed Central

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

2013-01-01

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 km2 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

Modelling survival: exposure pattern, species sensitivity and uncertainty.

PubMed

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.

Modelling survival: exposure pattern, species sensitivity and uncertainty

PubMed Central

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.

2016-01-01

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. PMID:27381500

Modelling survival: exposure pattern, species sensitivity and uncertainty

NASA Astrophysics Data System (ADS)

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.

2016-07-01

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.

Multispecies diffusion models: A study of uranyl species diffusion

NASA Astrophysics Data System (ADS)

Liu, Chongxuan; Shang, Jianying; Zachara, John M.

2011-12-01

Rigorous numerical description of multispecies diffusion requires coupling of species, charge, and aqueous and surface complexation reactions that collectively affect diffusive fluxes. The applicability of a fully coupled diffusion model is, however, often constrained by the availability of species self-diffusion coefficients, as well as by computational complication in imposing charge conservation. In this study, several diffusion models with variable complexity in charge and species coupling were formulated and compared to describe reactive multispecies diffusion in groundwater. Diffusion of uranyl [U(VI)] species was used as an example in demonstrating the effectiveness of the models in describing multispecies diffusion. Numerical simulations found that a diffusion model with a single, common diffusion coefficient for all species was sufficient to describe multispecies U(VI) diffusion under a steady state condition of major chemical composition, but not under transient chemical conditions. Simulations revealed that for multispecies U(VI) diffusion under transient chemical conditions, a fully coupled diffusion model could be well approximated by a component-based diffusion model when the diffusion coefficient for each chemical component was properly selected. The component-based diffusion model considers the difference in diffusion coefficients between chemical components, but not between the species within each chemical component. This treatment significantly enhanced computational efficiency at the expense of minor charge conservation. The charge balance in the component-based diffusion model can be enforced, if necessary, by adding a secondary migration term resulting from model simplification. The effect of ion activity coefficient gradients on multispecies diffusion is also discussed. The diffusion models were applied to describe U(VI) diffusive mass transfer in intragranular domains in two sediments collected from U.S. Department of Energy's Hanford 300A

An exactly solvable coarse-grained model for species diversity

NASA Astrophysics Data System (ADS)

Suweis, Samir; Rinaldo, Andrea; Maritan, Amos

2012-07-01

We present novel analytical results concerning ecosystem species diversity that stem from a proposed coarse-grained neutral model based on birth-death processes. The relevance of the problem lies in the urgency for understanding and synthesizing both theoretical results from ecological neutral theory and empirical evidence on species diversity preservation. The neutral model of biodiversity deals with ecosystems at the same trophic level, where per capita vital rates are assumed to be species independent. Closed-form analytical solutions for the neutral theory are obtained within a coarse-grained model, where the only input is the species persistence time distribution. Our results pertain to: the probability distribution function of the number of species in the ecosystem, both in transient and in stationary states; the n-point connected time correlation function; and the survival probability, defined as the distribution of time spans to local extinction for a species randomly sampled from the community. Analytical predictions are also tested on empirical data from an estuarine fish ecosystem. We find that emerging properties of the ecosystem are very robust and do not depend on specific details of the model, with implications for biodiversity and conservation biology.

Comparison of two freshwater turtle species as monitors of environmental contamination

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meyers-Schoene, L.; Walton, B.T.

1990-04-01

Two species of turtles that occupy different ecological niches were compared for their usefulness as monitors of contamination in freshwater ecosystems. Trachemys scripta (Agassiz) and Chelydra serpentina (Linnaeus) were selected for comparison based on species abundance and differences in food habits and sediment contact. A review of the literature on contaminants in turtles and results of preliminary surveys conducted at the field sites, which are included in this study, were used to direct and focus this research project. White Oak Lake, a settling basin for low-level radioactive and nonradioactive contaminants, and Bearden Creek Embayment, an uncontaminated reference site upriver, weremore » used as study sites in the investigation of turtles as indicators of chemical contamination. Turtles were analyzed for concentrations of strontium-90, cesium-137, cobalt 60, and mercury in specific target tissues, and for single-stranded DNA breaks, a non-specific indicator of possible exposure to genotoxic agents in the environment. 133 refs., 2 figs., 15 tabs.« less

On the dangers of model complexity without ecological justification in species distribution modeling

Treesearch

David M. Bell; Daniel R. Schlaepfer

2016-01-01

Although biogeographic patterns are the product of complex ecological processes, the increasing com-plexity of correlative species distribution models (SDMs) is not always motivated by ecological theory,but by model fit. The validity of model projections, such as shifts in a species’ climatic niche, becomesquestionable particularly during extrapolations, such as for...

Comparison of reference doses (RfDs) developed for the protection of wildlife species in contrast to humans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valoppi, L.; Carlisle, J.; Polisini, J.

1995-12-31

A component of both human health and ecological risk assessments is the evaluation of toxicity values. A comparison between the methodology for the development of Reference Doses (RfDs) to be protective of humans, and that developed for vertebrate wildlife species is presented. For all species, a chronic No Observable Adverse Effect Level (NOAEL) is developed by applying uncertainty factors (UFs) to literature-based toxicity values. Uncertainty factors are used to compensate for the length of exposure, sensitivity of endpoints, and cross-species extrapolations between the test species and the species being assessed. Differences between human and wildlife species could include the toxicologicalmore » endpoint, the critical study, and the magnitude of the cross-species extrapolation factor. Case studies for select chemicals are presented which contrast RfDs developed for humans and those developed for avian and mammalian wildlife.« less

A new Notomastus (Annelida, Capitellidae) species from Korean waters, with genetic comparison based on three gene markers.

PubMed

Jeong, Man-Ki; Soh, Ho Young; Wi, Jin Hee; Suh, Hae-Lip

2018-01-01

Notomastus koreanus sp. n. , collected from the sublittoral muddy bottom of Korean waters, is described as a new species. The Korean new species closely resembles N. torquatus Hutchings & Rainer, 1979 in the chaetal arrangement and the details of abdominal segments, but differs in the position of genital pores and the absence of eyes. DNA sequences (mtCOI, 16S rRNA, and histone H3) of the new species were compared with all the available sequences of Notomastus species in the GenBank database. Three genes showed significant genetic differences between the new species and its congeners (COI: 51.2%, 16S: 38.1-47.3%, H3: 3.7-9.3%). This study also includes a comprehensive comparison of the new Korean Notomastus species with its most closely similar species, based on the morphological and genetic results.

Analytically tractable model for community ecology with many species

NASA Astrophysics Data System (ADS)

Dickens, Benjamin; Fisher, Charles K.; Mehta, Pankaj

2016-08-01

A fundamental problem in community ecology is understanding how ecological processes such as selection, drift, and immigration give rise to observed patterns in species composition and diversity. Here, we analyze a recently introduced, analytically tractable, presence-absence (PA) model for community assembly, and we use it to ask how ecological traits such as the strength of competition, the amount of diversity, and demographic and environmental stochasticity affect species composition in a community. In the PA model, species are treated 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. Building upon previous work, we show that, despite its simplicity, the PA model reproduces the qualitative features of more complicated models of community assembly. In agreement with recent studies of 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. These results suggest that the concepts of ecological "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.

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

PubMed

Rougier, Thibaud; Lassalle, Géraldine; Drouineau, Hilaire; Dumoulin, Nicolas; Faure, Thierry; Deffuant, Guillaume; Rochard, Eric; Lambert, Patrick

2015-01-01

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 adaptations to cold

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

PubMed Central

Rougier, Thibaud; Lassalle, Géraldine; Drouineau, Hilaire; Dumoulin, Nicolas; Faure, Thierry; Deffuant, Guillaume; Rochard, Eric; Lambert, Patrick

2015-01-01

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 adaptations to cold

An inter-comparison of PM10 source apportionment using PCA and PMF receptor models in three European sites.

PubMed

Cesari, Daniela; Amato, F; Pandolfi, M; Alastuey, A; Querol, X; Contini, D

2016-08-01

Source apportionment of aerosol is an important approach to investigate aerosol formation and transformation processes as well as to assess appropriate mitigation strategies and to investigate causes of non-compliance with air quality standards (Directive 2008/50/CE). Receptor models (RMs) based on chemical composition of aerosol measured at specific sites are a useful, and widely used, tool to perform source apportionment. However, an analysis of available studies in the scientific literature reveals heterogeneities in the approaches used, in terms of "working variables" such as the number of samples in the dataset and the number of chemical species used as well as in the modeling tools used. In this work, an inter-comparison of PM10 source apportionment results obtained at three European measurement sites is presented, using two receptor models: principal component analysis coupled with multi-linear regression analysis (PCA-MLRA) and positive matrix factorization (PMF). The inter-comparison focuses on source identification, quantification of source contribution to PM10, robustness of the results, and how these are influenced by the number of chemical species available in the datasets. Results show very similar component/factor profiles identified by PCA and PMF, with some discrepancies in the number of factors. The PMF model appears to be more suitable to separate secondary sulfate and secondary nitrate with respect to PCA at least in the datasets analyzed. Further, some difficulties have been observed with PCA in separating industrial and heavy oil combustion contributions. Commonly at all sites, the crustal contributions found with PCA were larger than those found with PMF, and the secondary inorganic aerosol contributions found by PCA were lower than those found by PMF. Site-dependent differences were also observed for traffic and marine contributions. The inter-comparison of source apportionment performed on complete datasets (using the full range of

Transferability of species distribution models for the detection of an invasive alien bryophyte using imaging spectroscopy data

NASA Astrophysics Data System (ADS)

Skowronek, Sandra; Van De Kerchove, Ruben; Rombouts, Bjorn; Aerts, Raf; Ewald, Michael; Warrie, Jens; Schiefer, Felix; Garzon-Lopez, Carol; Hattab, Tarek; Honnay, Olivier; Lenoir, Jonathan; Rocchini, Duccio; Schmidtlein, Sebastian; Somers, Ben; Feilhauer, Hannes

2018-06-01

Remote sensing is a promising tool for detecting invasive alien plant species. Mapping and monitoring those species requires accurate detection. So far, most studies relied on models that are locally calibrated and validated against available field data. Consequently, detecting invasive alien species at new study areas requires the acquisition of additional field data which can be expensive and time-consuming. Model transfer might thus provide a viable alternative. Here, we mapped the distribution of the invasive alien bryophyte Campylopus introflexus to i) assess the feasibility of spatially transferring locally calibrated models for species detection between four different heathland areas in Germany and Belgium and ii) test the potential of combining calibration data from different sites in one species distribution model (SDM). In a first step, four different SDMs were locally calibrated and validated by combining field data and airborne imaging spectroscopy data with a spatial resolution ranging from 1.8 m to 4 m and a spectral resolution of about 10 nm (244 bands). A one-class classifier, Maxent, which is based on the comparison of probability densities, was used to generate all SDMs. In a second step, each model was transferred to the three other study areas and the performance of the models for predicting C. introflexus occurrences was assessed. Finally, models combining calibration data from three study areas were built and tested on the remaining fourth site. In this step, different combinations of Maxent modelling parameters were tested. For the local models, the area under the curve for a test dataset (test AUC) was between 0.57-0.78, while the test AUC for the single transfer models ranged between 0.45-0.89. For the combined models the test AUC was between 0.54-0.9. The success of transferring models calibrated in one site to another site highly depended on the respective study site; the combined models provided higher test AUC values than the locally

Using habitat suitability models to target invasive plant species surveys.

PubMed

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 < 0.01), and targeted sampling did detect more species than nontargeted sampling with less

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

PubMed

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.

A comparison of regional and national values for recovering threatened and endangered marine species in the United States.

PubMed

Wallmo, Kristy; Lew, Daniel K

2016-09-01

It is generally acknowledged that willingness-to-pay (WTP) estimates for environmental goods exhibit some degree of spatial variation. In a policy context, spatial variation in threatened and endangered species values is important to understand, as the benefit stream from policies affecting threatened and endangered species may vary locally, regionally, or among certain population segments. In this paper we present WTP estimates for eight different threatened and endangered marine species estimated from a stated preference choice experiment. WTP is estimated at two different spatial scales: (a) a random sample of over 5000 U.S. households and (b) geographically embedded samples (relative to the U.S. household sample) of nine U.S. Census regions. We conduct region-to-region and region-to-nation statistical comparisons to determine whether species values differ among regions and between each region and the entire U.S. Our results show limited spatial variation between national values and values estimated from regionally embedded samples, and differences are only found for three of the eight species. More variation exists between regions, and for all species there is a significant difference in at least one region-to-region comparison. Given that policy analyses involving threatened and endangered marine species can often be regional in scope (e.g., ecosystem management) or may disparately affect different regions, our results should be of high interest to the marine management community. Published by Elsevier Ltd.

Depressive-like behavioral profiles in captive-bred single- and socially-housed rhesus and cynomolgus macaques: a species comparison

PubMed Central

Camus, Sandrine M. J.; Rochais, Céline; Blois-Heulin, Catherine; Li, Qin; Hausberger, Martine; Bezard, Erwan

2014-01-01

Background: To unravel the causes of major depressive disorder (MDD), the third leading cause of disease burden around the world, ethological animal models have recently been proposed. Our previous studies highlighted a depressive-like profile among single- and socially-housed farm-bred cynomolgus macaques. Although phylogenetically close, cynomolgus and rhesus macaques, the two most commonly used macaque species in biomedical research, differ on several levels such as patterns of aggression, reconciliation, temperament, or dominance styles. The question of whether one captive macaque species was more vulnerable than another in the development of a pathological profile reminiscent of MDD symptoms was explored. Methods: Behavioral data (including body postures, orientations, gaze directions, inter-individual distances, and locations in the cage) were collected in farming conditions. Using an unbiased validated ethological scan-sampling method, followed by multiple correspondence and hierarchical clustering analyses, 40 single- and 35 socially-housed rhesus macaques were assessed. Independently, for each housing condition, inter-species comparisons were made with previously acquired data on farm-bred cynomolgus monkeys. Results: Consistent with our previous studies, we found depressive-like characteristics (e.g., inactivity, low level of investigation and maintenance, long time spent inactive while facing the wall) among single- and socially-housed rhesus macaques. Species-specificities were reported in non-depressive time budgets and in the prevalence of the pathological profiles. Conclusions: Our results suggest that rhesus may be more vulnerable to developing a despair-like state than cynomolgus macaques, both in single- and in social-housing conditions. Therefore, rhesus macaques are more suitable for use as a “spontaneous” model of depressive disorders. PMID:24600363

Using habitat suitability models to target invasive plant species surveys

USGS Publications Warehouse

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 2) = 47.42, P < 0.01). From these findings, we conclude that habitat suitability models can be

The Cryosphere Model Comparison Tool (CmCt): Ice Sheet Model Validation and Comparison Tool for Greenland and Antarctica

NASA Astrophysics Data System (ADS)

Simon, E.; Nowicki, S.; Neumann, T.; Tyahla, L.; Saba, J. L.; Guerber, J. R.; Bonin, J. A.; DiMarzio, J. P.

2017-12-01

The Cryosphere model Comparison tool (CmCt) is a web based ice sheet model validation tool that is being developed by NASA to facilitate direct comparison between observational data and various ice sheet models. The CmCt allows the user to take advantage of several decades worth of observations from Greenland and Antarctica. Currently, the CmCt can be used to compare ice sheet models provided by the user with remotely sensed satellite data from ICESat (Ice, Cloud, and land Elevation Satellite) laser altimetry, GRACE (Gravity Recovery and Climate Experiment) satellite, and radar altimetry (ERS-1, ERS-2, and Envisat). One or more models can be uploaded through the CmCt website and compared with observational data, or compared to each other or other models. The CmCt calculates statistics on the differences between the model and observations, and other quantitative and qualitative metrics, which can be used to evaluate the different model simulations against the observations. The qualitative metrics consist of a range of visual outputs and the quantitative metrics consist of several whole-ice-sheet scalar values that can be used to assign an overall score to a particular simulation. The comparison results from CmCt are useful in quantifying improvements within a specific model (or within a class of models) as a result of differences in model dynamics (e.g., shallow vs. higher-order dynamics approximations), model physics (e.g., representations of ice sheet rheological or basal processes), or model resolution (mesh resolution and/or changes in the spatial resolution of input datasets). The framework and metrics could also be used for use as a model-to-model intercomparison tool, simply by swapping outputs from another model as the observational datasets. Future versions of the tool will include comparisons with other datasets that are of interest to the modeling community, such as ice velocity, ice thickness, and surface mass balance.

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

PubMed

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.

Modeled Impacts of Anthropogenic Stressors on Listed Species in Southern California

NASA Astrophysics Data System (ADS)

Bell, M. D.; Hulton, H. L.; Allen, M. F.

2013-12-01

Based on data from the 2010 U.S. Census, Riverside County was the fastest growing county in California over the last decade. Urbanization has contributed to the disruption of the wildlands through fragmentation, changes in fire regimes, increased nitrogen deposition, and invasion of exotic plant species. These anthropogenic disturbances act independently and additively to disrupt environmental processes and community interactions even within protected wildlands. Here we incorporate these environmental stressors into Mahalanobis D2 species distribution models to measure the impact of multiple anthropogenic stressors on potential species distributions in Western Riverside County, with an emphasis on threatened species and species of concern. Species occurrence data from 1990 to 2010 of 6 rare and threatened species (2 bird, 2 mammal, and 2 plant) were used as inputs to develop a Habitat Suitability Index (HSI) for each species; potential species distributions were then modeled at a scale of a 250 m2 grid using terrain, climate, and vegetation community indices. We modeled the changing patterns of HSI across a landscape when anthropogenic stressors were added, individually and in combination. The changes in HSI of the rare and threatened species were compared to a common species from each group. Model outputs for endangered and threatened mammal and bird species show that there is a consistent decline in the HSI in cells with high nitrogen deposition and cells near urban development. The spatial shift in habitat suitability moved away from the environmental stressors, and there was also a reduction in area of patches modeled as high suitable habitat in all threatened species suggesting that the minimum habitat requirements for the species are reduced. There were not large changes in species distributions for the common species modeled. As rare species are often difficult to observe during surveys, monitoring the change of an easily measurable metric such a nitrogen

ClusCo: clustering and comparison of protein models.

PubMed

Jamroz, Michal; Kolinski, Andrzej

2013-02-22

The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the one of the bottlenecks in the protein modeling pipeline. Clusco is fast and easy-to-use software for high-throughput comparison of protein models with different similarity measures (cRMSD, dRMSD, GDT_TS, TM-Score, MaxSub, Contact Map Overlap) and clustering of the comparison results with standard methods: K-means Clustering or Hierarchical Agglomerative Clustering. The application was highly optimized and written in C/C++, including the code for parallel execution on CPU and GPU, which resulted in a significant speedup over similar clustering and scoring computation programs.

Comparisons and Evaluation of Hall Thruster Models

DTIC Science & Technology

2002-03-20

COVERED (FROM - TO) 20-04-2001 to 20-04-2002 4. TITLE AND SUBTITLE comparisons and Evaluation of Hall Thruster Models Unclassified 5a. CONTRACT NUMBER...TITLE AND SUBTITLE Comparisons and Evaluation of Hall Thruster Models 5c. PROGRAM ELEMENT NUMBER 5d. PROJECT NUMBER 5d. TASK NUMBER 6. AUTHOR(S...evaluation of Hall thruster models G. J. M. Hagelaar, J. Bareilles, L. Garrigues, and J.-P. Boeuf CPAT, Bâtiment 3R2, Université Paul Sabatier 118 Route

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

PubMed Central

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

2016-01-01

Summary 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. PMID:27840673

Incorporating uncertainty in predictive species distribution modelling.

PubMed

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).

PubMed

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.

CO2 exposure as translational cross-species experimental model for panic

PubMed Central

Leibold, N K; van den Hove, D L A; Viechtbauer, W; Buchanan, G F; Goossens, L; Lange, I; Knuts, I; Lesch, K P; Steinbusch, H W M; Schruers, K R J

2016-01-01

The current diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders are being challenged by the heterogeneity and the symptom overlap of psychiatric disorders. Therefore, a framework toward a more etiology-based classification has been initiated by the US National Institute of Mental Health, the research domain criteria project. The basic neurobiology of human psychiatric disorders is often studied in rodent models. However, the differences in outcome measurements hamper the translation of knowledge. Here, we aimed to present a translational panic model by using the same stimulus and by quantitatively comparing the same outcome measurements in rodents, healthy human subjects and panic disorder patients within one large project. We measured the behavioral–emotional and bodily response to CO2 exposure in all three samples, allowing for a reliable cross-species comparison. We show that CO2 exposure causes a robust fear response in terms of behavior in mice and panic symptom ratings in healthy volunteers and panic disorder patients. To improve comparability, we next assessed the respiratory and cardiovascular response to CO2, demonstrating corresponding respiratory and cardiovascular effects across both species. This project bridges the gap between basic and human research to improve the translation of knowledge between these disciplines. This will allow significant progress in unraveling the etiological basis of panic disorder and will be highly beneficial for refining the diagnostic categories as well as treatment strategies. PMID:27598969

Using cross-species comparisons and a neurobiological framework to understand early social deprivation effects on behavioral development.

PubMed

Brett, Zoë H; Humphreys, Kathryn L; Fleming, Alison S; Kraemer, Gary W; Drury, Stacy S

2015-05-01

Building upon the transactional model of brain development, we explore the impact of early maternal deprivation on neural development and plasticity in three neural systems: hyperactivity/impulsivity, executive function, and hypothalamic-pituitary-adrenal axis functioning across rodent, nonhuman primate, and human studies. Recognizing the complexity of early maternal-infant interactions, we limit our cross-species comparisons to data from rodent models of artificial rearing, nonhuman primate studies of peer rearing, and the relations between these two experimental approaches and human studies of children exposed to the early severe psychosocial deprivation associated with institutional care. In addition to discussing the strengths and limitations of these paradigms, we present the current state of research on the neurobiological impact of early maternal deprivation and the evidence of sensitive periods, noting methodological challenges. Integrating data across preclinical animal models and human studies, we speculate about the underlying biological mechanisms; the differential impact of deprivation due to temporal factors including onset, offset, and duration of the exposure; and the possibility and consequences of reopening of sensitive periods during adolescence.

Using cross-species comparisons and a neurobiological framework to understand early social deprivation effects on behavioral development

PubMed Central

BRETT, ZOË H.; HUMPHREYS, KATHRYN L.; FLEMING, ALISON S.; KRAEMER, GARY W.; DRURY, STACY S.

2017-01-01

Building upon the transactional model of brain development, we explore the impact of early maternal deprivation on neural development and plasticity in three neural systems: hyperactivity/impulsivity, executive function, and hypothalamic–pituitary–adrenal axis functioning across rodent, nonhuman primate, and human studies. Recognizing the complexity of early maternal–infant interactions, we limit our cross-species comparisons to data from rodent models of artificial rearing, nonhuman primate studies of peer rearing, and the relations between these two experimental approaches and human studies of children exposed to the early severe psychosocial deprivation associated with institutional care. In addition to discussing the strengths and limitations of these paradigms, we present the current state of research on the neurobiological impact of early maternal deprivation and the evidence of sensitive periods, noting methodological challenges. Integrating data across preclinical animal models and human studies, we speculate about the underlying biological mechanisms; the differential impact of deprivation due to temporal factors including onset, offset, and duration of the exposure; and the possibility and consequences of reopening of sensitive periods during adolescence. PMID:25997759

Engineering Large Animal Species to Model Human Diseases.

PubMed

Rogers, Christopher S

2016-07-01

Animal models are an important resource for studying human diseases. Genetically engineered mice are the most commonly used species and have made significant contributions to our understanding of basic biology, disease mechanisms, and drug development. However, they often fail to recreate important aspects of human diseases and thus can have limited utility as translational research tools. Developing disease models in species more similar to humans may provide a better setting in which to study disease pathogenesis and test new treatments. This unit provides an overview of the history of genetically engineered large animals and the techniques that have made their development possible. Factors to consider when planning a large animal model, including choice of species, type of modification and methodology, characterization, production methods, and regulatory compliance, are also covered. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Wildlife species richness in shelterbelts: test of a habitat model

USGS Publications Warehouse

Schroeder, Richard L.; Cable, Ted T.; Haire, Sandra L.

1992-01-01

Shelterbelts are human-made habitats consisting of rows of shrubs and trees planted either in fields or on the windward side of farmstead dwellings. Shelterbelts provide wooded habitat for a large variety of birds and other wildlife. A model to predict wildlife species richness in shelterbelts (Schroeder 1986) was published as part of the U.S. Fish and Wildlife Service Habitat Suitability Index (HSI) model series (Schamberger et al. 1982). HSI models have been used extensively by wildlife managers and land use planners to assess habitat quality. Several HSI models have become the focus of a test program that includes analysis of field data for corroboration, refutation, or modification of model hypotheses. Previous tests of HSI models focused either on single species (e.g., Cook and Irwin 1985, Morton et al. 1989, Schroeder 1990) or examined portions of HSI models, such as the relationship between cavity abundance and tree diameter (Allen and Corn 1990). The shelterbelt model, however, assesses habitat value at the community level. The effects of habitat characteristics, area, and perimeter on diversity and abundance of bird and mammal species in shelterbelts were first studied by Yahner (1983a, b). Johnson and Beck (1988) confirmed the importance of shelterbelts to wildlife and identified area, perimeter, and diversity and complexity of vegetation as key measurements of habitat quality. The shelterbelt model incorporates both specific habitat variables and larger scale parameters, such as area and configuration, to predict wildlife species richness. This shift in perspective comes at a time of increasing interest in conservation and planning beyond the species levels (e.g., Graul and Miller 1984, Hutto et al. 1987, Schroeder 1987: 26).We report results of a 3-year study of spatial and vegetative parameters and their relationship to breeding bird species richness (BSR) in 34 Kansas shelterbelts. Our objectives were to test the hypothesis presented in the original

Acorn Production Prediction Models for Five Common Oak Species of the Eastern United States

Treesearch

Anita K. Rose; Cathryn H. Greenberg; Todd M. Fearer

2011-01-01

Acorn production varies considerably among oak (Quercus) species, individual trees, years, and locations, which directly affects oak regeneration and populations of wildlife species that depend on acorns for food. Hard mast indices provide a relative ranking and basis for comparison of within- and between-year acorn crop size at a broad scale, but do...

An analytically tractable model for community ecology with many species

NASA Astrophysics Data System (ADS)

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.

A Review and Comparison of Mouse and Rat Responses to Micro Gravity, Hyper Gravity and Simulated Models of Partial Gravity; Species Differences, Gaps in the Available Data, and Consideration of the Advantages and Caveats of Each Model for Spaceflight

NASA Technical Reports Server (NTRS)

Donovan, F. M.; Gresser, A. L.; Sato, Kevin Y.; Taylor, Elizabeth M.

2018-01-01

Laboratory strains of mice and rat are widely used to study mammalian responses to stimulus, and both have been studied under a variety of gravity conditions, including space flight. We compared results obtained from exposure to spaceflight and microgravity, hyper gravity via centrifugation, earth gravity, and models of simulated partial gravity (hind-limb unloading and partial weight bearing treatments). We examined the reported changes in survival, body mass, circadian rhythm (body temperature and activity levels), behavior, bone, muscle, immune, cardio-vasculature, vestibular, reproduction and neonate survival, microbiome, and the visual system. Not all categories have published data for both species, some have limited data, and there are variations in experiment design that allow for only relative comparisons to be considered. The data reveal species differences in both the level of gravity required to obtain a response, degree of response, and in temporal expression of responses. Examination of the data across the gravity levels allows consideration of the hypothesis that gravitational responses follow a continuum, and organ specific differences are noted. In summary, we present advantages and caveats of each model system as pertains to gravitational biology research and identify gaps in our knowledge of how these mammals respond to gravity.

Comparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States

USGS Publications Warehouse

Magarey, Roger; Newton, Leslie; Hong, Seung C.; Takeuchi, Yu; Christie, Dave; Jarnevich, Catherine S.; Kohl, Lisa; Damus, Martin; Higgins, Steven I.; Miller, Leah; Castro, Karen; West, Amanda; Hastings, John; Cook, Gericke; Kartesz, John; Koop, Anthony

2018-01-01

This study compares four models for predicting the potential distribution of non-indigenous weed species in the conterminous U.S. The comparison focused on evaluating modeling tools and protocols as currently used for weed risk assessment or for predicting the potential distribution of invasive weeds. We used six weed species (three highly invasive and three less invasive non-indigenous species) that have been established in the U.S. for more than 75 years. The experiment involved providing non-U. S. location data to users familiar with one of the four evaluated techniques, who then developed predictive models that were applied to the United States without knowing the identity of the species or its U.S. distribution. We compared a simple GIS climate matching technique known as Proto3, a simple climate matching tool CLIMEX Match Climates, the correlative model MaxEnt, and a process model known as the Thornley Transport Resistance (TTR) model. Two experienced users ran each modeling tool except TTR, which had one user. Models were trained with global species distribution data excluding any U.S. data, and then were evaluated using the current known U.S. distribution. The influence of weed species identity and modeling tool on prevalence and sensitivity effects was compared using a generalized linear mixed model. Each modeling tool itself had a low statistical significance, while weed species alone accounted for 69.1 and 48.5% of the variance for prevalence and sensitivity, respectively. These results suggest that simple modeling tools might perform as well as complex ones in the case of predicting potential distribution for a weed not yet present in the United States. Considerations of model accuracy should also be balanced with those of reproducibility and ease of use. More important than the choice of modeling tool is the construction of robust protocols and testing both new and experienced users under blind test conditions that approximate operational conditions.

Dispersal kernel estimation: A comparison of empirical and modelled particle dispersion in a coastal marine system

NASA Astrophysics Data System (ADS)

Hrycik, Janelle M.; Chassé, Joël; Ruddick, Barry R.; Taggart, Christopher T.

2013-11-01

Early life-stage dispersal influences recruitment and is of significance in explaining the distribution and connectivity of marine species. Motivations for quantifying dispersal range from biodiversity conservation to the design of marine reserves and the mitigation of species invasions. Here we compare estimates of real particle dispersion in a coastal marine environment with similar estimates provided by hydrodynamic modelling. We do so by using a system of magnetically attractive particles (MAPs) and a magnetic-collector array that provides measures of Lagrangian dispersion based on the time-integration of MAPs dispersing through the array. MAPs released as a point source in a coastal marine location dispersed through the collector array over a 5-7 d period. A virtual release and observed (real-time) environmental conditions were used in a high-resolution three-dimensional hydrodynamic model to estimate the dispersal of virtual particles (VPs). The number of MAPs captured throughout the collector array and the number of VPs that passed through each corresponding model location were enumerated and compared. Although VP dispersal reflected several aspects of the observed MAP dispersal, the comparisons demonstrated model sensitivity to the small-scale (random-walk) particle diffusivity parameter (Kp). The one-dimensional dispersal kernel for the MAPs had an e-folding scale estimate in the range of 5.19-11.44 km, while those from the model simulations were comparable at 1.89-6.52 km, and also demonstrated sensitivity to Kp. Variations among comparisons are related to the value of Kp used in modelling and are postulated to be related to MAP losses from the water column and (or) shear dispersion acting on the MAPs; a process that is constrained in the model. Our demonstration indicates a promising new way of 1) quantitatively and empirically estimating the dispersal kernel in aquatic systems, and 2) quantitatively assessing and (or) improving regional hydrodynamic

Comparison of different artificial neural network architectures in modeling of Chlorella sp. flocculation.

PubMed

Zenooz, Alireza Moosavi; Ashtiani, Farzin Zokaee; Ranjbar, Reza; Nikbakht, Fatemeh; Bolouri, Oberon

2017-07-03

Biodiesel production from microalgae feedstock should be performed after growth and harvesting of the cells, and the most feasible method for harvesting and dewatering of microalgae is flocculation. Flocculation modeling can be used for evaluation and prediction of its performance under different affective parameters. However, the modeling of flocculation in microalgae is not simple and has not performed yet, under all experimental conditions, mostly due to different behaviors of microalgae cells during the process under different flocculation conditions. In the current study, the modeling of microalgae flocculation is studied with different neural network architectures. Microalgae species, Chlorella sp., was flocculated with ferric chloride under different conditions and then the experimental data modeled using artificial neural network. Neural network architectures of multilayer perceptron (MLP) and radial basis function architectures, failed to predict the targets successfully, though, modeling was effective with ensemble architecture of MLP networks. Comparison between the performances of the ensemble and each individual network explains the ability of the ensemble architecture in microalgae flocculation modeling.

Improving environmental assessments by integrating Species Sensitivity Distributions into environmental modeling: examples with two hypothetical oil spills.

PubMed

Bejarano, Adriana C; Mearns, Alan J

2015-04-15

A three dimensional (3D) trajectory model was used to simulate oil mass balance and environmental concentrations of two 795,000 L hypothetical oil spills modeled under physical and chemical dispersion scenarios. Species Sensitivity Distributions (SSD) for Total Hydrocarbon Concentrations (THCs) were developed, and Hazard Concentrations (HC) used as levels of concern. Potential consequences to entrained water column organisms were characterized by comparing model outputs with SSDs, and obtaining the proportion of species affected (PSA) and areas with oil concentrations exceeding HC5s (Area ⩾ HC5). Under the physically-dispersed oil scenario ⩽ 77% of the oil remains on the water surface and strands on shorelines, while with the chemically-dispersed oil scenario ⩽ 67% of the oil is entrained in the water column. For every 10% increase in chemical dispersion effectiveness, the average PSA and Area ⩾ HC5 increases (range: 0.01-0.06 and 0.50-2.9 km(2), respectively), while shoreline oiling decreases (⩽ 2919 L/km). Integrating SSDs into modeling may improve understanding of scales of potential impacts to water column organisms, while providing net environmental benefit comparison of oil spill response options. Copyright © 2015 Elsevier Ltd. All rights reserved.

New approaches for sampling and modeling native and exotic plant species richness

USGS Publications Warehouse

Chong, G.W.; Reich, R.M.; Kalkhan, M.A.; Stohlgren, T.J.

2001-01-01

We demonstrate new multi-phase, multi-scale approaches for sampling and modeling native and exotic plant species to predict the spread of invasive species and aid in control efforts. Our test site is a 54,000-ha portion of Rocky Mountain National Park, Colorado, USA. This work is based on previous research wherein we developed vegetation sampling techniques to identify hot spots of diversity, important rare habitats, and locations of invasive plant species. Here we demonstrate statistical modeling tools to rapidly assess current patterns of native and exotic plant species to determine which habitats are most vulnerable to invasion by exotic species. We use stepwise multiple regression and modified residual kriging to estimate numbers of native species and exotic species, as well as probability of observing an exotic species in 30 × 30-m cells. Final models accounted for 62% of the variability observed in number of native species, 51% of the variability observed in number of exotic species, and 47% of the variability associated with observing an exotic species. Important independent variables used in developing the models include geographical location, elevation, slope, aspect, and Landsat TM bands 1-7. These models can direct resource managers to areas in need of further inventory, monitoring, and exotic species control efforts.

Item Response Modeling of Paired Comparison and Ranking Data

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto; Brown, Anna

2010-01-01

The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…

Occupancy Estimation and Modeling : Inferring Patterns and Dynamics of Species Occurrence

USGS Publications Warehouse

MacKenzie, D.I.; Nichols, J.D.; Royle, J. Andrew; Pollock, K.H.; Bailey, L.L.; Hines, J.E.

2006-01-01

This is the first book to examine the latest methods in analyzing presence/absence data surveys. Using four classes of models (single-species, single-season; single-species, multiple season; multiple-species, single-season; and multiple-species, multiple-season), the authors discuss the practical sampling situation, present a likelihood-based model enabling direct estimation of the occupancy-related parameters while allowing for imperfect detectability, and make recommendations for designing studies using these models. It provides authoritative insights into the latest in estimation modeling; discusses multiple models which lay the groundwork for future study designs; addresses critical issues of imperfect detectibility and its effects on estimation; and explores the role of probability in estimating in detail.

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species.

PubMed

Wang, Yi; Coleman-Derr, Devin; Chen, Guoping; Gu, Yong Q

2015-07-01

Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that is useful for genome wide comparisons and visualization of orthologous clusters. OrthoVenn provides coverage of vertebrates, metazoa, protists, fungi, plants and bacteria for the comparison of orthologous clusters and also supports uploading of customized protein sequences from user-defined species. An interactive Venn diagram, summary counts, and functional summaries of the disjunction and intersection of clusters shared between species are displayed as part of the OrthoVenn result. OrthoVenn also includes in-depth views of the clusters using various sequence analysis tools. Furthermore, OrthoVenn identifies orthologous clusters of single copy genes and allows for a customized search of clusters of specific genes through key words or BLAST. OrthoVenn is an efficient and user-friendly web server freely accessible at http://probes.pw.usda.gov/OrthoVenn or http://aegilops.wheat.ucdavis.edu/OrthoVenn. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparison of debris flux models

NASA Astrophysics Data System (ADS)

Sdunnus, H.; Beltrami, P.; Klinkrad, H.; Matney, M.; Nazarenko, A.; Wegener, P.

The availability of models to estimate the impact risk from the man-made space debris and the natural meteoroid environment is essential for both, manned and unmanned satellite missions. Various independent tools based on different approaches have been developed in the past years. Due to an increased knowledge of the debris environment and its sources e.g. from improved measurement capabilities, these models could be updated regularly, providing more detailed and more reliable simulations. This paper addresses an in-depth, quantitative comparison of widely distributed debris flux models which were recently updated, namely ESA's MASTER 2001 model, NASA's ORDEM 2000 and the Russian SDPA 2000 model. The comparison was performed in the frame of the work of the 20t h Interagency Debris Coordination (IADC) meeting held in Surrey, UK. ORDEM 2000ORDEM 2000 uses careful empirical estimates of the orbit populations based onthree primary data sources - the US Space Command Catalog, the H ystackaRadar, and the Long Duration Exposure Facility spacecraft returned surfaces.Further data (e.g. HAX and Goldstone radars, impacts on Shuttle windows andradiators, and others) were used to adjust these populations for regions in time,size, and space not covered by the primary data sets. Some interpolation andextrapolation to regions with no data (such as projections into the future) wasprovided by the EVOLVE model. MASTER 2001The ESA MASTER model offers a full three dimensional description of theterrestrial debris distribution reaching from LEO up to the GEO region. Fluxresults relative to an orbiting target or to an inertial volume can be resolved intosource terms, impactor characteristics and orbit, as well as impact velocity anddirection. All relevant debris source terms are considered by the MASTERmodel. For each simulated source, a corresponding debris generation model interms of mass/diameter distribution, additional velocities, and directionalspreading has been developed. A

Benchmarking novel approaches for modelling species range dynamics.

PubMed

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

Mammalian pre-implantation chromosomal instability: species comparison, evolutionary considerations, and pathological correlations.

PubMed

Carbone, Lucia; Chavez, Shawn L

2015-01-01

Pre-implantation embryo development in mammals begins at fertilization with the migration and fusion of the maternal and paternal pro-nuclei, followed by the degradation of inherited factors involved in germ cell specification and the activation of embryonic genes required for subsequent cell divisions, compaction, and blastulation. The majority of studies on early embryogenesis have been conducted in the mouse or non-mammalian species, often requiring extrapolation of the findings to human development. Given both conserved similarities and species-specific differences, however, even comparison between closely related mammalian species may be challenging as certain aspects, including susceptibility to chromosomal aberrations, varies considerably across mammals. Moreover, most human embryo studies are limited to patient samples obtained from in vitro fertilization (IVF) clinics and donated for research, which are generally of poorer quality and produced with germ cells that may be sub-optimal. Recent technical advances in genetic, epigenetic, chromosomal, and time-lapse imaging analyses of high quality whole human embryos have greatly improved our understanding of early human embryogenesis, particularly at the single embryo and cell level. This review summarizes the major characteristics of mammalian pre-implantation development from a chromosomal perspective, in addition to discussing the technological achievements that have recently been developed to obtain this data. We also discuss potential translation to clinical applications in reproductive medicine and conclude by examining the broader implications of these findings for the evolution of mammalian species and cancer pathology in somatic cells.

Unified phenology model with Bayesian calibration for several European species in Belgium

NASA Astrophysics Data System (ADS)

Fu, Y. S. H.; Demarée, G.; Hamdi, R.; Deckmyn, A.; Deckmyn, G.; Janssens, I. A.

2009-04-01

Plant phenology is a good bio-indicator for climate change, and this has brought a significant increase of interest. Many kinds of phenology models have been developed to analyze and predict the phenological response to climate change, and those models have been summarized into one kind of unified model, which could be applied to different species and environments. In our study, we selected seven European woody plant species (Betula verrucosa, Quercus robur pedunculata, Fagus sylvatica, Fraxinus excelsior, Symphoricarpus racemosus, Aesculus hippocastanum, Robinia pseudoacacia) occurring in five sites distributed across Belgium. For those sites and tree species, phenological observations such as bud burst were available for the period 1956 - 2002. We also obtained regional downscaled climatic data for each of these sites, and combined both data sets to test the unified model. We used a Bayesian approach to generate distributions of model parameters from the observation data. In this poster presentation, we compare parameter distributions between different species and between different sites for individual species. The results of the unified model show a good agreement with the observations, except for Fagus sylvatica. The failure to reproduce the bud burst data for Fagus sylvatica suggest that the other factors not included in the unified model affect the phenology of this species. The parameter series show differences among species as we expected. However, they also differed strongly for the same species among sites.Further work should elucidate the mechanism that explains why model parameters differ among species and sites.

Hierarchical modeling of population stability and species group attributes from survey data

USGS Publications Warehouse

Sauer, J.R.; Link, W.A.

2002-01-01

Many ecological studies require analysis of collections of estimates. For example, population change is routinely estimated for many species from surveys such as the North American Breeding Bird Survey (BBS), and the species are grouped and used in comparative analyses. We developed a hierarchical model for estimation of group attributes from a collection of estimates of population trend. The model uses information from predefined groups of species to provide a context and to supplement data for individual species; summaries of group attributes are improved by statistical methods that simultaneously analyze collections of trend estimates. The model is Bayesian; trends are treated as random variables rather than fixed parameters. We use Markov Chain Monte Carlo (MCMC) methods to fit the model. Standard assessments of population stability cannot distinguish magnitude of trend and statistical significance of trend estimates, but the hierarchical model allows us to legitimately describe the probability that a trend is within given bounds. Thus we define population stability in terms of the probability that the magnitude of population change for a species is less than or equal to a predefined threshold. We applied the model to estimates of trend for 399 species from the BBS to estimate the proportion of species with increasing populations and to identify species with unstable populations. Analyses are presented for the collection of all species and for 12 species groups commonly used in BBS summaries. Overall, we estimated that 49% of species in the BBS have positive trends and 33 species have unstable populations. However, the proportion of species with increasing trends differs among habitat groups, with grassland birds having only 19% of species with positive trend estimates and wetland birds having 68% of species with positive trend estimates.

Exploration of an urban lake management model to simulate chlorine interference based on the ecological relationships among aquatic species.

PubMed

Yan, Zhiqiang; Wang, Yafei; Wu, Di; Xia, Beicheng

2018-05-29

In eutrophic lakes, algae are known to be sensitive to chlorine, but the impact of chlorine on the wider ecosystem has not been investigated. To quantitatively investigate the effects of chlorine on the urban lake ecosystem and analyze the changes in the aquatic ecosystem structure, a dynamic response model of aquatic species to chlorine was constructed based on the biomass density dynamics of aquatic species of submerged macrophytes, phytoplankton, zooplankton, periphyton, and benthos. The parameters were calibrated using data from the literature and two simulative experiments. The model was then validated using field data from an urban lake with a surface area of approximately 8000 m 2 located in the downtown area of Guangzhou, South China. The correlation coefficient (R), root mean square error-observations standard deviation ratio (RSR) and index of agreement (IOA) were used to evaluate the accuracy and reliability of the model and the results were consistent with the observations (0.446 R < 0.985, RSR < 0.7, IOA > 0.6). Comparisons between the simulated and observed trends confirmed the feasibility of using this model to investigate the dynamics of aquatic species under chlorine interference. The model can help managers apply a modest amount of chlorine to control eutrophication and provides scientific support for the management of urban lakes.

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

PubMed

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.

Centrifuge Rotor Models: A Comparison of the Euler-Lagrange and the Bond Graph Modeling Approach

NASA Technical Reports Server (NTRS)

Granda, Jose J.; Ramakrishnan, Jayant; Nguyen, Louis H.

2006-01-01

A viewgraph presentation on centrifuge rotor models with a comparison using Euler-Lagrange and bond graph methods is shown. The topics include: 1) Objectives; 2) MOdeling Approach Comparisons; 3) Model Structures; and 4) Application.

Impacts of forest fragmentation on species richness: a hierarchical approach to community modelling

USGS Publications Warehouse

Zipkin, Elise F.; DeWan, Amielle; Royle, J. Andrew

2009-01-01

1. Species richness is often used as a tool for prioritizing conservation action. One method for predicting richness and other summaries of community structure is to develop species-specific models of occurrence probability based on habitat or landscape characteristics. However, this approach can be challenging for rare or elusive species for which survey data are often sparse. 2. Recent developments have allowed for improved inference about community structure based on species-specific models of occurrence probability, integrated within a hierarchical modelling framework. This framework offers advantages to inference about species richness over typical approaches by accounting for both species-level effects and the aggregated effects of landscape composition on a community as a whole, thus leading to increased precision in estimates of species richness by improving occupancy estimates for all species, including those that were observed infrequently. 3. We developed a hierarchical model to assess the community response of breeding birds in the Hudson River Valley, New York, to habitat fragmentation and analysed the model using a Bayesian approach. 4. The model was designed to estimate species-specific occurrence and the effects of fragment area and edge (as measured through the perimeter and the perimeter/area ratio, P/A), while accounting for imperfect detection of species. 5. We used the fitted model to make predictions of species richness within forest fragments of variable morphology. The model revealed that species richness of the observed bird community was maximized in small forest fragments with a high P/A. However, the number of forest interior species, a subset of the community with high conservation value, was maximized in large fragments with low P/A. 6. Synthesis and applications. Our results demonstrate the importance of understanding the responses of both individual, and groups of species, to environmental heterogeneity while illustrating the utility

HABITAT DISTRIBUTION MODELS FOR 37 VERTEBRATE SPECIES ADDRESSED BY THE MULTI-SPECIES HABITAT CONSERVATION PLAN OF CLARK COUNTY, NEVADA

EPA Science Inventory

Thirty-seven species identified in the Clark County Multi-Species Habitat Conservation Plan were

previously modeled through the Southwest Regional Gap Analysis Project. Existing SWReGAP habitat

models and modeling databases were used to facilitate the revision of mo...

Cross-species pharmacological characterization of the allylglycine seizure model in mice and larval zebrafish.

PubMed

Leclercq, Karine; Afrikanova, Tatiana; Langlois, Melanie; De Prins, An; Buenafe, Olivia E; Rospo, Chiara C; Van Eeckhaut, Ann; de Witte, Peter A M; Crawford, Alexander D; Smolders, Ilse; Esguerra, Camila V; Kaminski, Rafal M

2015-04-01

Treatment-resistant seizures affect about a third of patients suffering from epilepsy. To fulfill the need for new medications targeting treatment-resistant seizures, a number of rodent models offer the opportunity to assess a variety of potential treatment approaches. The use of such models, however, has proven to be time-consuming and labor-intensive. In this study, we performed pharmacological characterization of the allylglycine (AG) seizure model, a simple in vivo model for which we demonstrated a high level of treatment resistance. (d,l)-Allylglycine inhibits glutamic acid decarboxylase (GAD) - the key enzyme in γ-aminobutyric acid (GABA) biosynthesis - leading to GABA depletion, seizures, and neuronal damage. We performed a side-by-side comparison of mouse and zebrafish acute AG treatments including biochemical, electrographic, and behavioral assessments. Interestingly, seizure progression rate and GABA depletion kinetics were comparable in both species. Five mechanistically diverse antiepileptic drugs (AEDs) were used. Three out of the five AEDs (levetiracetam, phenytoin, and topiramate) showed only a limited protective effect (mainly mortality delay) at doses close to the TD50 (dose inducing motor impairment in 50% of animals) in mice. The two remaining AEDs (diazepam and sodium valproate) displayed protective activity against AG-induced seizures. Experiments performed in zebrafish larvae revealed behavioral AED activity profiles highly analogous to those obtained in mice. Having demonstrated cross-species similarities and limited efficacy of tested AEDs, we propose the use of AG in zebrafish as a convenient and high-throughput model of treatment-resistant seizures. Copyright © 2015 Elsevier Inc. All rights reserved.

How many sightings to model rare marine species distributions

PubMed Central

Authier, Matthieu; Monestiez, Pascal; Ridoux, Vincent

2018-01-01

Despite large efforts, datasets with few sightings are often available for rare species of marine megafauna that typically live at low densities. This paucity of data makes modelling the habitat of these taxa particularly challenging. We tested the predictive performance of different types of species distribution models fitted to decreasing numbers of sightings. Generalised additive models (GAMs) with three different residual distributions and the presence only model MaxEnt were tested on two megafauna case studies differing in both the number of sightings and ecological niches. From a dolphin (277 sightings) and an auk (1,455 sightings) datasets, we simulated rarity with a sighting thinning protocol by random sampling (without replacement) of a decreasing fraction of sightings. Better prediction of the distribution of a rarely sighted species occupying a narrow habitat (auk dataset) was expected compared to the distribution of a rarely sighted species occupying a broad habitat (dolphin dataset). We used the original datasets to set up a baseline model and fitted additional models on fewer sightings but keeping effort constant. Model predictive performance was assessed with mean squared error and area under the curve. Predictions provided by the models fitted to the thinned-out datasets were better than a homogeneous spatial distribution down to a threshold of approximately 30 sightings for a GAM with a Tweedie distribution and approximately 130 sightings for the other models. Thinning the sighting data for the taxon with narrower habitats seemed to be less detrimental to model predictive performance than for the broader habitat taxon. To generate reliable habitat modelling predictions for rarely sighted marine predators, our results suggest (1) using GAMs with a Tweedie distribution with presence-absence data and (2) implementing, as a conservative empirical measure, at least 50 sightings in the models. PMID:29529097

GCSS Idealized Cirrus Model Comparison Project

NASA Technical Reports Server (NTRS)

Starr, David OC.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric; Khvorostyanov, Vitaly;

Updating Known Distribution Models for Forecasting Climate Change Impact on Endangered Species

PubMed Central

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. PMID:23840330

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

PubMed

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.

Comparison of some secondary metabolite content in the seventeen species of the Boraginaceae family.

PubMed

Dresler, Sławomir; Szymczak, Grażyna; Wójcik, Małgorzata

2017-12-01

The Boraginaceae family comprises plants that have important therapeutic and cosmetic applications. Their pharmacological effect is related to the presence of naphthaquinones, flavonoids, terpenoids, phenols, or purine derivative - allantoin. In the present study, comparison of some secondary metabolite content and phytochemical relationship between 17 species of the Boraginaceae family were analyzed. High performance capillary electrophoresis (HPCE) was used to perform a chemometric analysis in the following Boraginaceae species: Anchusa azurea Mill., Anchusa undulata L., Borago officinalis L., Buglossoides purpurocaerulea (L.) I.M. Johnst., Cerinthe minor L., Cynoglossum creticum Mill, Echium italicum L., Echium russicum J.F. Gmel., Echium vulgare L., Lindelofia macrostyla (Bunge) Popov (syn. Lindelofia anchusoides (Lindl.) Lehm.), Lithospermum officinale L., Nonea lutea (Desr.) DC., Omphalodes verna Moench (syn. Cynoglossum omphaloides L.), Pulmonaria mollis Wulfen ex Hornem., Pulmonaria obscura Dumort., Symphytum cordatum Waldst. & Kit ex Willd., and Symphytum officinale L. Six active compounds in shoot extracts (allantoin, p-hydroxybenzoic acid, rutin, hydrocaffeic acid, rosmarinic acid, and chlorogenic acid) and four compounds in root extracts (allantoin, hydrocaffeic acid, rosmarinic acid, and shikonin) were identified. The presence and abundance of these compounds were used for the characterization of the species and for revealing their phytochemical similarity and differentiation. The present study provides the first comprehensive report of the extraction and quantification of several compounds in Boraginaceae species (some of them for the first time). Among the 17 species studied, species with potentially high pharmacological activity were recognized.

Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution

PubMed Central

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. PMID:23861828

Neurobehavioral Integrity of Chimpanzee Newborns: Comparisons across groups and across species reveal gene-environment interaction effects

PubMed Central

Bard, Kim A.; Brent, Linda; Lester, Barry; Worobey, John; Suomi, Stephen J.

2014-01-01

The aims of this article are to describe the neurobehavioral integrity of chimpanzee newborns, to investigate how early experiences affect the neurobehavioral organization of chimpanzees, and to explore species differences by comparing chimpanzee newborns to a group of typically developing human newborns. Neurobehavioral integrity related to orientation, motor performance, arousal, and state regulation of 55 chimpanzee (raised in four different settings) and 42 human newborns was measured with the Neonatal Behavioral Assessment Scale (NBAS) a semi-structured 25-minute interactive assessment. Thirty-eight chimpanzees were tested every other day from birth, and analyses revealed significant developmental changes in 19 of 27 NBAS scores. The cross-group and cross-species comparisons were conducted at 2 and 30 days of age. Among the 4 chimpanzee groups, significant differences were found in 23 of 24 NBAS scores. Surprisingly, the cross-species comparisons revealed that the human group was distinct in only 1 of 25 NBAS scores (the human group had significantly less muscle tone than all the chimpanzee groups). The human group was indistinguishable from at least one of the chimpanzee groups in the remaining 24 of 25 NBAS scores. The results of this study support the conclusion that the interplay between genes and environment, rather than genes alone or environment alone, accounts for phenotypic expressions of newborn neurobehavioral integrity in hominids. PMID:25110465

A comparison of self-oscillating phonation models

NASA Astrophysics Data System (ADS)

McPhail, Michael; Campo, Elizabeth; Walters, Gage; Krane, Michael

2017-11-01

This talk presents a comparison of self-oscillating models of phonation. The goal is to assess how well synthetic rubber vocal folds reproduce the gross behavior of phonation. Data from molded rubber folds and a variety of excised mammalian larynges were collected from the literature and from the authors' physical model. Gross trends are discussed and a simple scaling is presented that appears to collapse these data. Finally, comparisons between molded rubber folds and excised larynges are highlighted. Acknowledge support from NIH DC R01005642-11.

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

PubMed

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

2017-01-01

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. 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. 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. 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 variation, choosing the appropriate statistics

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

PubMed Central

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 comparison of spontaneous problem-solving abilities in three estrildid finch (Taeniopygia guttata, Lonchura striata var. domestica, Stagonopleura guttata) species.

PubMed

Schmelz, Martin; Krüger, Oliver; Call, Josep; Krause, E Tobias

2015-11-01

Cognition has been extensively studied in primates while other, more distantly related taxa have been neglected for a long time. More recently, there has been an increased interest in avian cognition, with the focus mostly on big-brained species like parrots and corvids. However, the majority of bird species has never systematically been studied in diverse cognitive tasks other than memory and learning tasks, so not much can yet be concluded about the relevant factors for the evolution of cognition. Here we examined 3 species of the estrildid finch family in problem-solving tasks. These granivorous, non-tool-using birds are distributed across 3 continents and are not known for high levels of innovation or spontaneous problem solving in the wild. In this study, our aim was to find such abilities in these species, assess what role domestication might play with a comparison of 4 genetically separated zebra finch strains, and to look for between-species differences between zebra finches, Bengalese finches, and diamond firetails. Furthermore, we established a 3-step spontaneous problem-solving procedure with increasing levels of complexity. Results showed that some estrildid finches were generally capable of spontaneously solving problems of variable complexity to obtain food. We found striking differences in these abilities between species, but not between strains within species, and offer a discussion of potential reasons. Our established methodology can now be applied to a larger number of bird species for phylogenetic comparisons on the behavioral level to get a deeper understanding of the evolution of cognitive abilities. (c) 2015 APA, all rights reserved).

Nitrogen Species in the Post-Pinatubo Stratosphere: Model Analysis Utilizing UARS Measurements

NASA Technical Reports Server (NTRS)

Danilin, M. Y.; Rodriguez, J. M.; Hu, W.; Ko, M. K. W.; Weisenstein, D. K.; Kumer, J. B.; Mergenthaler, J. L.; Russell, J. M., III; Koike, M.; Yue, G. K.

1998-01-01

We present an analysis of the impact of heterogeneous chemistry on the partitioning of nitrogen species measured by the Upper Atmosphere Research Satellite (UARS) instruments. The UARS measurements utilized include: N2O, HNO3 and ClONO2 (Cryogen Limb Array Etalon Spectrometer (CLAES), version 7), temperature, methane, ozone, H2O, HCI, NO and NO2 (HALogen Occultation Experiment (HALOE), version 18). The analysis is carried out for the data from January 1992 to September 1994 in the 100-1 mbar (approximately 17-47 km) altitude range and over 10 degree latitude bins from 70 deg S to 70 deg N. Temporal-spatial evolution of aerosol surface area density (SAD) is adopted according to the Stratospheric Aerosol and Gas Experiment (SAGE) II data. A diurnal steady-state photochemical box model, constrained by the temperature, ozone, H2O, CH4, aerosol SAD and columns of O2 and O3 above the point of interest, has been used as the main tool to analyze these data. Total inorganic nitrogen (NOy) is obtained by three different methods: (1) as a sum of the UARS measured NO, NO2, HNO3, and CIONO2; (2) from the N2O-NOy correlation, (3) from the CH4-NOy correlation. To validate our current understanding of stratospheric heterogeneous chemistry for post-Pinatubo conditions, the model-calculated NOx/NOy ratios and the NO, NO2, and HNO3 profiles are compared to the UARS-derived data. In general, the UARS-constrained box model captures the main features of nitrogen species partitioning in the post-Pinatubo years. However, the model underestimates the NO2 content, particularly, in the 30-7 mbar (approximately 23-32 km) range. Comparisons of the calculated temporal behavior of the partial columns of NO2 and HNO3 and ground based measurements at 45 deg S and 45 deg N are also presented. Our analysis indicates that ground-based and HALOE v.18 measurements of the NO2 vertical columns are consistent within the range of their uncertainties and are systematically higher (up to 50%) than the model

Nitrogen Species in the Post-Pinatubo Stratosphere: Model Analysis Utilizing UARS Measurements

NASA Technical Reports Server (NTRS)

Danilin, M. Y.; Rodriquez, J. M.; Hu, W.; Ko, M. K. W.; Weisenstein, D. K.; Mergenthaler, J. L.; Russell, J. M., III; Koike, M.; Yue, G. K.

1998-01-01

We present an analysis of the impact of heterogeneous chemistry on the partitioning of nitrogen species measured by the Upper Atmosphere Research Satellite (UARS) instruments. The UARS measurements utilized include: N2O, HNO3 and ClONO2 (Cryogen Limb Array Etalon Spectrometer (CLAES), version 7), temperature, methane, ozone, H2O, HCl, NO and NO2 (HALogen Occultation Experiment (HALOE), version 18). The analysis is carried out for the data from January 1992 to September 1994 in the 100-1 mbar (approx.17-47 km) altitude range and over 10 degree latitude bins from 70degS to 70degN. Temporal-spatial evolution of aerosol surface area density (SAD) is adopted according to the Stratospheric Aerosol and Gas Experiment (SAGE) 11 data. A diurnal steady-state photochemical box model, constrained by the temperature, ozone, H2O, CH4, aerosol SAD and columns of O2 and O3 above the point of interest, has been used as the main tool to analyze these data. Total inorganic nitrogen (NO(y)) is obtained by three different methods: (1) as a sum of the UARS measured NO, NO2, HNO3, and ClONO2; (2) from the N2O-NO(y) correlation, and (3) from the CH4-NO(y) correlation. To validate our current understanding of stratospheric heterogeneous chemistry for post-Pinatubo conditions, the model-calculated NO(x)/NO(y) ratios and the NO, NO2, and HNO3 profiles are compared to the UARS-derived data. In general, the UARS-constrained box model captures the main features of nitrogen species partitioning in the post-Pinatubo years. However, the model underestimates the NO2 content, particularly, in the 30-7 mbar (approx. 23-32 km) range. Comparisons of the calculated temporal behavior of the partial columns of NO2 and HNO3 and ground based measurements at 45degS and 45degN are also presented. Our analysis indicates that ground-based and HALOE v. 18 measurements of the NO2 vertical columns are consistent within the range of their uncertainties and are systematically higher (up to 50%) than the model

Nitrogen Species in the Post-Pinatubo Stratosphere: Model Analysis Utilizing UARS Measurements

NASA Technical Reports Server (NTRS)

Danilin, Michael Y.; Rodriguez, Jose M.; Hu, Wen-Jie; Ko, Malcolm K. W.; Weisenstein, Debra K.; Kumer, John B.; Mergenthaler, John L.; Russel, James M., III; Koike, Makoto; Yue, Glenn K.

1999-01-01

We present an analysis of the impact of heterogeneous chemistry on the partitioning of nitrogen species measured by the Upper Atmosphere Research Satellite (UARS) instruments. The UARS measurements utilized include N2O, HNO3, and ClONO2 from the cryogenic limb array etalon spectrometer (CLAES), version 7 (v.7), and temperature, methane, ozone, H2O, HCl, NO and NO2 from the halogen occultation experiment (HALOE), version 18. The analysis is carried out for the UARS data obtained between January 1992 and September 1994 in the 100-to 1-mbar (approx. 17-47 km) altitude range and over 10 degrees latitude bins from 70 S to 70 N. The spatiotemporal evolution of aerosol surface area density (SAD) is adopted from analysis of the Stratospheric Aerosol and Gas Experiment (SAGE) II data. A diurnal steady state photochemical box model, constrained by the temperature, ozone, H2O, CH4, aerosol SAD, and columns of O2 and O3 above the point of interest, has been used as the main tool to analyze these data. Total inorganic nitrogen (NOy) is obtained by three different methods: (1) as a sum of the UARS-measured NO, NO2, HNO3, and ClONO2; (2) from the N2O-NOy correlation, and (3) from the CH4-NOy correlation. To validate our current understanding of stratospheric heterogeneous chemistry for post-Pinatubo conditions, the model-calculated monthly averaged NOx/NOy ratios and the NO, NO2, and HNO3 profiles are compared with the UARS-derived data. In general, the UARS-constrained box model captures the main features of nitrogen species partitioning in the post-Pinatubo years, such as recovery of NOx after the eruption, their seasonal variability and vertical profiles. However, the model underestimates the NO2 content, particularly in the 30- to 7-mbar (approx.23-32 km) range. Comparisons of the calculated temporal behavior of the partial columns of NO2 and HNO3 and ground-based measurements at 45 S and 45 N are also presented. Our analysis indicates that ground-based and HALOE v.18

How to resolve the SLOSS debate: lessons from species-diversity models.

PubMed

Tjørve, Even

2010-05-21

The SLOSS debate--whether a single large reserve will conserve more species than several small--of the 1970s and 1980s never came to a resolution. The first rule of reserve design states that one large reserve will conserve the most species, a rule which has been heavily contested. Empirical data seem to undermine the reliance on general rules, indicating that the best strategy varies from case to case. Modeling has also been deployed in this debate. We may divide the modeling approaches to the SLOSS enigma into dynamic and static approaches. Dynamic approaches, covered by the fields of island equilibrium theory of island biogeography and metapopulation theory, look at immigration, emigration, and extinction. Static approaches, such as the one in this paper, illustrate how several factors affect the number of reserves that will save the most species. This article approaches the effect of different factors by the application of species-diversity models. These models combine species-area curves for two or more reserves, correcting for the species overlap between them. Such models generate several predictions on how different factors affect the optimal number of reserves. The main predictions are: Fewer and larger reserves are favored by increased species overlap between reserves, by faster growth in number of species with reserve area increase, by higher minimum-area requirements, by spatial aggregation and by uneven species abundances. The effect of increased distance between smaller reserves depends on the two counteracting factors: decreased species density caused by isolation (which enhances minimum-area effect) and decreased overlap between isolates. The first decreases the optimal number of reserves; the second increases the optimal number. The effect of total reserve-system area depends both on the shape of the species-area curve and on whether overlap between reserves changes with scale. The approach to modeling presented here has several implications for

Model Comparison of Nonlinear Structural Equation Models with Fixed Covariates.

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan

2003-01-01

Proposed a new nonlinear structural equation model with fixed covariates to deal with some complicated substantive theory and developed a Bayesian path sampling procedure for model comparison. Illustrated the approach with an illustrative example using data from an international study. (SLD)

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

PubMed

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

NASA Astrophysics Data System (ADS)

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

Comparison of NGA-West2 directivity models

USGS Publications Warehouse

Spudich, Paul A.; Rowshandel, Badie; Shahi, Shrey; Baker, Jack W.; Chiou, Brian S-J

2014-01-01

Five directivity models have been developed based on data from the NGA-West2 database and based on numerical simulations of large strike-slip and reverse-slip earthquakes. All models avoid the use of normalized rupture dimension, enabling them to scale up to the largest earthquakes in a physically reasonable way. Four of the five models are explicitly “narrow-band” (in which the effect of directivity is maximum at a specific period that is a function of earthquake magnitude). Several strategies for determining the zero-level for directivity have been developed. We show comparisons of maps of the directivity amplification. This comparison suggests that the predicted geographic distributions of directivity amplification are dominated by effects of the models' assumptions, and more than one model should be used for ruptures dipping less than about 65 degrees.

Acute Toxicity Prediction to Threatened and Endangered Species Using Interspecies Correlation Estimation (ICE) Models.

PubMed

Willming, Morgan M; Lilavois, Crystal R; Barron, Mace G; Raimondo, Sandy

2016-10-04

Evaluating contaminant sensitivity of threatened and endangered (listed) species and protectiveness of chemical regulations often depends on toxicity data for commonly tested surrogate species. The U.S. EPA's Internet application Web-ICE is a suite of Interspecies Correlation Estimation (ICE) models that can extrapolate species sensitivity to listed taxa using least-squares regressions of the sensitivity of a surrogate species and a predicted taxon (species, genus, or family). Web-ICE was expanded with new models that can predict toxicity to over 250 listed species. A case study was used to assess protectiveness of genus and family model estimates derived from either geometric mean or minimum taxa toxicity values for listed species. Models developed from the most sensitive value for each chemical were generally protective of the most sensitive species within predicted taxa, including listed species, and were more protective than geometric means models. ICE model estimates were compared to HC5 values derived from Species Sensitivity Distributions for the case study chemicals to assess protectiveness of the two approaches. ICE models provide robust toxicity predictions and can generate protective toxicity estimates for assessing contaminant risk to listed species.

Modeling Emergent Macrophyte Distributions: Including Sub-dominant Species

EPA Science Inventory

Mixed stands of emergent vegetation are often present following drawdowns but models of wetland plant distributions fail to include subdominant species when predicting distributions. Three variations of a spatial plant distribution cellular automaton model were developed to explo...

Modeling spatially-varying landscape change points in species occurrence thresholds

USGS Publications Warehouse

Wagner, Tyler; Midway, Stephen R.

2014-01-01

Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover

The Origin of Species by Means of Mathematical Modelling.

PubMed

Bessonov, Nikolai; Reinberg, Natalia; Banerjee, Malay; Volpert, Vitaly

2018-04-30

Darwin described biological species as groups of morphologically similar individuals. These groups of individuals can split into several subgroups due to natural selection, resulting in the emergence of new species. Some species can stay stable without the appearance of a new species, some others can disappear or evolve. Some of these evolutionary patterns were described in our previous works independently of each other. In this work we have developed a single model which allows us to reproduce the principal patterns in Darwin's diagram. Some more complex evolutionary patterns are also observed. The relation between Darwin's definition of species, stated above, and Mayr's definition of species (group of individuals that can reproduce) is also discussed.

Comparison of natural and nonnative two-species communities of Anolis lizards.

PubMed

Poe, Steven

2014-07-01

Human-mediated colonizations present an informative model system for understanding assembly of organismal communities. However, it is unclear whether communities including naturalized species are accurate analogs of natural communities or unique combinations not present in nature. I compared morphology and phylogenetic structure of natural and naturalized two-species communities of Anolis lizards. Natural communities are phylogenetically clustered, whereas naturalized communities show no significant phylogenetic structure. This result likely reflects differences in colonization pools for these communities-that is, invasion from anywhere for naturalized communities but from proximal and thus phylogenetically close lineages in natural communities. Both natural and naturalized communities each include pairs of species that are significantly similar to each other in morphology, and both sets of communities are composed of species that possess traits of good colonizers. These similarities suggest that the formation of natural and naturalized communities may be at least partially governed by similar processes. Human-mediated invasions may be credibly viewed as modern incarnations of natural colonizations in this case.

Species Distribution Model using Hyperspectral Data Application in Peatland, Central Kalimantan

NASA Astrophysics Data System (ADS)

Dayuf Jusuf, Muhammad

2016-11-01

Tumih / Parepat (Combretocarpus-rotundatus Mig. Dencer) of the family Anisophylleaceae and Meranti (Shorea Belangerang, ShoreaTeysmanniana Dyer ex. Brandis) of Dipterocarpaceae are groups of species of vegetation that is modeled for the designation of its spread. Pioneer species are predicted as an indicator of ecosystem restoration succession of wet tropical peatland characteristic (unique) and very susceptible (fragile) in an endemic Sundaland hotspot. Projected climate change and conservation planning a topic of heated discussion. the analysis of alternative approaches and the development of a combination of search algorithm projection models within the fabric of the diffusion of the species to attain this through a geospatial information system technology. Model approach used to work out problems in research on this vegetation species level based machine learning is a method (hybrid). which is a combination of wavelet and neural network. Often the approach to field data into general use in the management of natural resources and biodiversity assessment. Expression of the hybrid models provides encouraging results. to decide the classification of the species Tumih / Parepat and Meranti through mapping of vegetation species that are backed up by the pattern of the spectral curve of the field spectrometer.

Infusing considerations of trophic dependencies into species distribution modelling.

PubMed

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.

Guidelines for a priori grouping of species in hierarchical community models

USGS Publications Warehouse

Pacifici, Krishna; Zipkin, Elise; Collazo, Jaime; Irizarry, Julissa I.; DeWan, Amielle A.

2014-01-01

Recent methodological advances permit the estimation of species richness and occurrences for rare species by linking species-level occurrence models at the community level. The value of such methods is underscored by the ability to examine the influence of landscape heterogeneity on species assemblages at large spatial scales. A salient advantage of community-level approaches is that parameter estimates for data-poor species are more precise as the estimation process borrows from data-rich species. However, this analytical benefit raises a question about the degree to which inferences are dependent on the implicit assumption of relatedness among species. Here, we assess the sensitivity of community/group-level metrics, and individual-level species inferences given various classification schemes for grouping species assemblages using multispecies occurrence models. We explore the implications of these groupings on parameter estimates for avian communities in two ecosystems: tropical forests in Puerto Rico and temperate forests in northeastern United States. We report on the classification performance and extent of variability in occurrence probabilities and species richness estimates that can be observed depending on the classification scheme used. We found estimates of species richness to be most precise and to have the best predictive performance when all of the data were grouped at a single community level. Community/group-level parameters appear to be heavily influenced by the grouping criteria, but were not driven strictly by total number of detections for species. We found different grouping schemes can provide an opportunity to identify unique assemblage responses that would not have been found if all of the species were analyzed together. We suggest three guidelines: (1) classification schemes should be determined based on study objectives; (2) model selection should be used to quantitatively compare different classification approaches; and (3) sensitivity

Climate suitability for European ticks: assessing species distribution models against null models and projection under AR5 climate.

PubMed

Williams, Hefin Wyn; Cross, Dónall Eoin; Crump, Heather Louise; Drost, Cornelis Jan; Thomas, Christopher James

2015-08-28

There is increasing evidence that the geographic distribution of tick species is changing. Whilst correlative Species Distribution Models (SDMs) have been used to predict areas that are potentially suitable for ticks, models have often been assessed without due consideration for spatial patterns in the data that may inflate the influence of predictor variables on species distributions. This study used null models to rigorously evaluate the role of climate and the potential for climate change to affect future climate suitability for eight European tick species, including several important disease vectors. We undertook a comparative assessment of the performance of Maxent and Mahalanobis Distance SDMs based on observed data against those of null models based on null species distributions or null climate data. This enabled the identification of species whose distributions demonstrate a significant association with climate variables. Latest generation (AR5) climate projections were subsequently used to project future climate suitability under four Representative Concentration Pathways (RCPs). Seven out of eight tick species exhibited strong climatic signals within their observed distributions. Future projections intimate varying degrees of northward shift in climate suitability for these tick species, with the greatest shifts forecasted under the most extreme RCPs. Despite the high performance measure obtained for the observed model of Hyalomma lusitanicum, it did not perform significantly better than null models; this may result from the effects of non-climatic factors on its distribution. By comparing observed SDMs with null models, our results allow confidence that we have identified climate signals in tick distributions that are not simply a consequence of spatial patterns in the data. Observed climate-driven SDMs for seven out of eight species performed significantly better than null models, demonstrating the vulnerability of these tick species to the effects of

Further Development of the PCRTM Model and RT Model Inter Comparison

NASA Technical Reports Server (NTRS)

Yang, Qiguang; Liu, Xu; Wu, Wan; Kizer, Susan

2015-01-01

New results for the development of the PCRTM model will be presented. The new results were used for IASI retrieval validation inter comparison and better results were obtained compare to other fast radiative transfer models.

Comparison of two wild rodent species as sentinels of environmental contamination by mine tailings.

PubMed

Tovar-Sánchez, E; Cervantes, L T; Martínez, C; Rojas, E; Valverde, M; Ortiz-Hernández, M L; Mussali-Galante, P

2012-06-01

Contamination with heavy metals is among the most hazardous environmental concerns caused by mining activity. A valuable tool for monitoring these effects is the use of sentinel organisms. Particularly, small mammals living inside mine tailings are an excellent study system because their analysis represents a realistic approach of mixtures and concentrations of metal exposure. We analyzed metal tissue concentrations and DNA damage levels for comparison between genders of a sentinel (Peromyscus melanophrys) and a nonsentinel (Baiomys musculus) species. Also, the relationship between DNA damage and the distance from the contamination source was evaluated. This study was conducted in an abandoned mine tailing at Morelos, Mexico. Thirty-six individuals from both species at the exposed and reference sites were sampled. Metal concentrations in bone and liver of both species were analyzed by atomic absorption spectrophotometry, and DNA damage levels were assayed using the alkaline comet assay. In general, concentrations of zinc, nickel, iron, and manganese were statistically higher in exposed individuals. A significant effect of the organ and the site on all metal tissue concentrations was detected. Significant DNA damage levels were registered in the exposed group, being higher in B. musculus. Females registered higher DNA damage levels than males. A negative relationship between distance from the mine tailing and DNA damage in B. musculus was observed. We consider that B. musculus is a suitable species to assess environmental quality, especially for bioaccumulable pollutants--such as metals--and recommend that it may be considered as a sentinel species.

Inference about species richness and community structure using species-specific occupancy models in the National Swiss Breeding Bird Survey MUB

USGS Publications Warehouse

Kery, M.; Royle, J. Andrew; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Species richness is the most widely used biodiversity measure. Virtually always, it cannot be observed but needs to be estimated because some species may be present but remain undetected. This fact is commonly ignored in ecology and management, although it will bias estimates of species richness and related parameters such as occupancy, turnover or extinction rates. We describe a species community modeling strategy based on species-specific models of occurrence, from which estimates of important summaries of community structure, e.g., species richness, occupancy, or measures of similarity among species or sites, are derived by aggregating indicators of occurrence for all species observed in the sample, and for the estimated complement of unobserved species. We use data augmentation for an efficient Bayesian approach to estimation and prediction under this model based on MCMC in WinBUGS. For illustration, we use the Swiss breeding bird survey (MHB) that conducts 2?3 territory-mapping surveys in a systematic sample of 267 1 km2 units on quadrat-specific routes averaging 5.1 km to obtain species-specific estimates of occupancy, and estimates of species richness of all diurnal species free of distorting effects of imperfect detectability. We introduce into our model species-specific covariates relevant to occupancy (elevation, forest cover, route length) and sampling (season, effort). From 1995 to 2004, 185 diurnal breeding bird species were known in Switzerland, and an additional 13 bred 1?3 times since 1900. 134 species were observed during MHB surveys in 254 quadrats surveyed in 2001, and our estimate of 169.9 (95% CI 151?195) therefore appeared sensible. The observed number of species ranged from 4 to 58 (mean 32.8), but with an estimated 0.7?11.2 (mean 2.6) further, unobserved species, the estimated proportion of detected species was 0.48?0.98 (mean 0.91). As is well known, species richness declined at higher elevation and fell above the timberline, and most

Data for Room Fire Model Comparisons

PubMed Central

Peacock, Richard D.; Davis, Sanford; Babrauskas, Vytenis

1991-01-01

With the development of models to predict fire growth and spread in buildings, there has been a concomitant evolution in the measurement and analysis of experimental data in real-scale fires. This report presents the types of analyses that can be used to examine large-scale room fire test data to prepare the data for comparison with zone-based fire models. Five sets of experimental data which can be used to test the limits of a typical two-zone fire model are detailed. A standard set of nomenclature describing the geometry of the building and the quantities measured in each experiment is presented. Availability of ancillary data (such as smaller-scale test results) is included. These descriptions, along with the data (available in computer-readable form) should allow comparisons between the experiment and model predictions. The base of experimental data ranges in complexity from one room tests with individual furniture items to a series of tests conducted in a multiple story hotel equipped with a zoned smoke control system. PMID:28184121

Data for Room Fire Model Comparisons.

PubMed

Peacock, Richard D; Davis, Sanford; Babrauskas, Vytenis

1991-01-01

With the development of models to predict fire growth and spread in buildings, there has been a concomitant evolution in the measurement and analysis of experimental data in real-scale fires. This report presents the types of analyses that can be used to examine large-scale room fire test data to prepare the data for comparison with zone-based fire models. Five sets of experimental data which can be used to test the limits of a typical two-zone fire model are detailed. A standard set of nomenclature describing the geometry of the building and the quantities measured in each experiment is presented. Availability of ancillary data (such as smaller-scale test results) is included. These descriptions, along with the data (available in computer-readable form) should allow comparisons between the experiment and model predictions. The base of experimental data ranges in complexity from one room tests with individual furniture items to a series of tests conducted in a multiple story hotel equipped with a zoned smoke control system.

Mitochondrial Genome Analysis of Wild Rice (Oryza minuta) and Its Comparison with Other Related Species.

PubMed

Asaf, Sajjad; Khan, Abdul Latif; Khan, Abdur Rahim; Waqas, Muhammad; Kang, Sang-Mo; Khan, Muhammad Aaqil; Shahzad, Raheem; Seo, Chang-Woo; Shin, Jae-Ho; Lee, In-Jung

2016-01-01

Oryza minuta (Poaceae family) is a tetraploid wild relative of cultivated rice with a BBCC genome. O. minuta has the potential to resist against various pathogenic diseases such as bacterial blight (BB), white backed planthopper (WBPH) and brown plant hopper (BPH). Here, we sequenced and annotated the complete mitochondrial genome of O. minuta. The mtDNA genome is 515,022 bp, containing 60 protein coding genes, 31 tRNA genes and two rRNA genes. The mitochondrial genome organization and the gene content at the nucleotide level are highly similar (89%) to that of O. rufipogon. Comparison with other related species revealed that most of the genes with known function are conserved among the Poaceae members. Similarly, O. minuta mt genome shared 24 protein-coding genes, 15 tRNA genes and 1 ribosomal RNA gene with other rice species (indica and japonica). The evolutionary relationship and phylogenetic analysis revealed that O. minuta is more closely related to O. rufipogon than to any other related species. Such studies are essential to understand the evolutionary divergence among species and analyze common gene pools to combat risks in the current scenario of a changing environment.

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

PubMed

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.

Breakdown of Phylogenetic Signal: A Survey of Microsatellite Densities in 454 Shotgun Sequences from 154 Non Model Eukaryote Species

PubMed Central

Meglécz, Emese; Nève, Gabriel; Biffin, Ed; Gardner, Michael G.

2012-01-01

Microsatellites are ubiquitous in Eukaryotic genomes. A more complete understanding of their origin and spread can be gained from a comparison of their distribution within a phylogenetic context. Although information for model species is accumulating rapidly, it is insufficient due to a lack of species depth, thus intragroup variation is necessarily ignored. As such, apparent differences between groups may be overinflated and generalizations cannot be inferred until an analysis of the variation that exists within groups has been conducted. In this study, we examined microsatellite coverage and motif patterns from 454 shotgun sequences of 154 Eukaryote species from eight distantly related phyla (Cnidaria, Arthropoda, Onychophora, Bryozoa, Mollusca, Echinodermata, Chordata and Streptophyta) to test if a consistent phylogenetic pattern emerges from the microsatellite composition of these species. It is clear from our results that data from model species provide incomplete information regarding the existing microsatellite variability within the Eukaryotes. A very strong heterogeneity of microsatellite composition was found within most phyla, classes and even orders. Autocorrelation analyses indicated that while microsatellite contents of species within clades more recent than 200 Mya tend to be similar, the autocorrelation breaks down and becomes negative or non-significant with increasing divergence time. Therefore, the age of the taxon seems to be a primary factor in degrading the phylogenetic pattern present among related groups. The most recent classes or orders of Chordates still retain the pattern of their common ancestor. However, within older groups, such as classes of Arthropods, the phylogenetic pattern has been scrambled by the long independent evolution of the lineages. PMID:22815847

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

Treesearch

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...

Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.

PubMed

Renner, Ian W; Warton, David I

2013-03-01

Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature. Copyright © 2013, The International Biometric Society.

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

PubMed

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

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

USGS Publications Warehouse

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

Comparing species interaction networks along environmental gradients.

PubMed

Pellissier, Loïc; Albouy, Camille; Bascompte, Jordi; Farwig, Nina; Graham, Catherine; Loreau, Michel; Maglianesi, Maria Alejandra; Melián, Carlos J; Pitteloud, Camille; Roslin, Tomas; Rohr, Rudolf; Saavedra, Serguei; Thuiller, Wilfried; Woodward, Guy; Zimmermann, Niklaus E; Gravel, Dominique

2018-05-01

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis

Radicals and Reservoirs in the GMI Chemistry and Transport Model: Comparison to Measurements

NASA Technical Reports Server (NTRS)

Douglass, Anne R.; Stolarski, Richard S.; Strahan, Susan E.; Connell, Peter S.

2004-01-01

We have used a three-dimensional chemistry and transport model (CTM), developed under the Global Modeling Initiative (GMI), to carry out two simulations of the composition of the stratosphere under changing halogen loading for 1995 through 2030. The two simulations differ only in that one uses meteorological fields from a general circulation model while the other uses meteorological fields from a data assimilation system. A single year's winds and temperatures are repeated for each 36-year simulation. We compare results from these two simulations with an extensive collection of data from satellite and ground-based measurements for 1993-2000. Comparisons of simulated fields with observations of radical and reservoir species for some of the major ozone-destroying compounds are of similar quality for both simulations. Differences in the upper stratosphere, caused by transport of total reactive nitrogen and methane, impact the balance among the ozone loss processes and the sensitivity of the two simulations to the change in composition.

Preclinical QT safety assessment: cross-species comparisons and human translation from an industry consortium.

PubMed

Holzgrefe, Henry; Ferber, Georg; Champeroux, Pascal; Gill, Michael; Honda, Masaki; Greiter-Wilke, Andrea; Baird, Theodore; Meyer, Olivier; Saulnier, Muriel

2014-01-01

In vivo models have been required to demonstrate relative cardiac safety, but model sensitivity has not been systematically investigated. Cross-species and human translation of repolarization delay, assessed as QT/QTc prolongation, has not been compared employing common methodologies across multiple species and sites. Therefore, the accurate translation of repolarization results within and between preclinical species, and to man, remains problematic. Six pharmaceutical companies entered into an informal consortium designed to collect high-resolution telemetered data in multiple species (dog; n=34, cynomolgus; n=37, minipig; n=12, marmoset; n=14, guinea pig; n=5, and man; n=57). All animals received vehicle and varying doses of moxifloxacin (3-100 mg/kg, p.o.) with telemetered ECGs (≥500 Hz) obtained for 20-24h post-dose. Individual probabilistic QT-RR relationships were derived for each subject. The rate-correction efficacies of the individual (QTca) and generic correction formulae (Bazett, Fridericia, and Van de Water) were objectively assessed as the mean squared slopes of the QTc-RR relationships. Normalized moxifloxacin QTca responses (Veh Δ%/μM) were derived for 1h centered on the moxifloxacin Tmax. All QT-RR ranges demonstrated probabilistic uncertainty; slopes varied distinctly by species where dog and human exhibited the lowest QT rate-dependence, which was much steeper in the cynomolgus and guinea pig. Incorporating probabilistic uncertainty, the normalized QTca-moxifloxacin responses were similarly conserved across all species, including man. The current results provide the first unambiguous evidence that all preclinical in vivo repolarization assays, when accurately modeled and evaluated, yield results that are consistent with the conservation of moxifloxacin-induced QT prolongation across all common preclinical species. Furthermore, these outcomes are directly transferable across all species including man. The consortium results indicate that the

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

USGS Publications Warehouse

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

Data-Model and Inter-Model Comparisons of the GEM Outflow Events Using the Space Weather Modeling Framework

NASA Astrophysics Data System (ADS)

Welling, D. T.; Eccles, J. V.; Barakat, A. R.; Kistler, L. M.; Haaland, S.; Schunk, R. W.; Chappell, C. R.

2015-12-01

Two storm periods were selected by the Geospace Environment Modeling Ionospheric Outflow focus group for community collaborative study because of its high magnetospheric activity and extensive data coverage: the September 27 - October 4, 2002 corotating interaction region event and the October 22 - 29 coronal mass ejection event. During both events, the FAST, Polar, Cluster, and other missions made key observations, creating prime periods for data-model comparison. The GEM community has come together to simulate this period using many different methods in order to evaluate models, compare results, and expand our knowledge of ionospheric outflow and its effects on global dynamics. This paper presents Space Weather Modeling Framework (SWMF) simulations of these important periods compared against observations from the Polar TIDE, Cluster CODIF and EFW instruments. Emphasis will be given to the second event. Density and velocity of oxygen and hydrogen throughout the lobes, plasma sheet, and inner magnetosphere will be the focus of these comparisons. For these simulations, the SWMF couples the multifluid version of BATS-R-US MHD to a variety of ionospheric outflow models of varying complexity. The simplest is outflow arising from constant MHD inner boundary conditions. Two first-principles-based models are also leveraged: the Polar Wind Outflow Model (PWOM), a fluid treatment of outflow dynamics, and the Generalized Polar Wind (GPW) model, which combines fluid and particle-in-cell approaches. Each model is capable of capturing a different set of energization mechanisms, yielding different outflow results. The data-model comparisons will illustrate how well each approach captures reality and which energization mechanisms are most important. Inter-model comparisons will illustrate how the different outflow specifications affect the magnetosphere. Specifically, it is found that the GPW provides increased heavy ion outflow over a broader spatial range than the alternative

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

NASA Astrophysics Data System (ADS)

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 (p<0.05) higher than those for Bioclim and Domain based models, but insignificantly different from those for Mahal-based models (p=0.955); while R for the Maxent-based models were significantly higher than those for all the other three types of models (p<0.05). Thus, we concluded that the Maxent-based models had the best performance. High AUC and R also indicated that Maxent

Estimating the efficiency of fish cross-species cDNA microarray hybridization.

PubMed

Cohen, Raphael; Chalifa-Caspi, Vered; Williams, Timothy D; Auslander, Meirav; George, Stephen G; Chipman, James K; Tom, Moshe

2007-01-01

Using an available cross-species cDNA microarray is advantageous for examining multigene expression patterns in non-model organisms, saving the need for construction of species-specific arrays. The aim of the present study was to estimate relative efficiency of cross-species hybridizations across bony fishes, using bioinformatics tools. The methodology may serve also as a model for similar evaluations in other taxa. The theoretical evaluation was done by substituting comparative whole-transcriptome sequence similarity information into the thermodynamic hybridization equation. Complementary DNA sequence assemblages of nine fish species belonging to common families or suborders and distributed across the bony fish taxonomic branch were selected for transcriptome-wise comparisons. Actual cross-species hybridizations among fish of different taxonomic distances were used to validate and eventually to calibrate the theoretically computed relative efficiencies.

Use of cccupancy models to evaluate expert knowledge-based species-habitat relationships

USGS Publications Warehouse

Iglecia, Monica N.; Collazo, Jaime A.; McKerrow, Alexa

2012-01-01

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.

A new mathematical model of bacterial interactions in two-species oral biofilms

PubMed Central

Martin, Bénédicte; Tamanai-Shacoori, Zohreh; Bronsard, Julie; Ginguené, Franck; Meuric, Vincent

2017-01-01

Periodontitis are bacterial inflammatory diseases, where the bacterial biofilms present on the tooth-supporting tissues switch from a healthy state towards a pathogenic state. Among bacterial species involved in the disease, Porphyromonas gingivalis has been shown to induce dysbiosis, and to induce virulence of otherwise healthy bacteria like Streptococcus gordonii. During biofilm development, primary colonizers such as S. gordonii first attach to the surface and allow the subsequent adhesion of periodontal pathogens such as P. gingivalis. Interactions between those two bacteria have been extensively studied during the adhesion step of the biofilm. The aim of the study was to understand interactions of both species during the growing phase of the biofilm, for which little knowledge is available, using a mathematical model. This two-species biofilm model was based on a substrate-dependent growth, implemented with damage parameters, and validated thanks to data obtained on experimental biofilms. Three different hypothesis of interactions were proposed and assayed using this model: independence, competition between both bacteria species, or induction of toxicity by one species for the other species. Adequacy between experimental and simulated biofilms were found with the last hypothetic mathematical model. This new mathematical model of two species bacteria biofilms, dependent on different substrates for growing, can be applied to any bacteria species, environmental conditions, or steps of biofilm development. It will be of great interest for exploring bacterial interactions in biofilm conditions. PMID:28253369

Factorial Comparison of Working Memory Models

PubMed Central

van den Berg, Ronald; Awh, Edward; Ma, Wei Ji

2014-01-01

Three questions have been prominent in the study of visual working memory limitations: (a) What is the nature of mnemonic precision (e.g., quantized or continuous)? (b) How many items are remembered? (c) To what extent do spatial binding errors account for working memory failures? Modeling studies have typically focused on comparing possible answers to a single one of these questions, even though the result of such a comparison might depend on the assumed answers to both others. Here, we consider every possible combination of previously proposed answers to the individual questions. Each model is then a point in a 3-factor model space containing a total of 32 models, of which only 6 have been tested previously. We compare all models on data from 10 delayed-estimation experiments from 6 laboratories (for a total of 164 subjects and 131,452 trials). Consistently across experiments, we find that (a) mnemonic precision is not quantized but continuous and not equal but variable across items and trials; (b) the number of remembered items is likely to be variable across trials, with a mean of 6.4 in the best model (median across subjects); (c) spatial binding errors occur but explain only a small fraction of responses (16.5% at set size 8 in the best model). We find strong evidence against all 6 documented models. Our results demonstrate the value of factorial model comparison in working memory. PMID:24490791

Model-simulated and Satellite-derived Leaf Area Index (LAI) Comparisons Across Multiple Spatial Scales

NASA Astrophysics Data System (ADS)

Iiames, J. S., Jr.; Cooter, E. J.

2016-12-01

Leaf Area Index (LAI) is an important parameter in assessing vegetation structure for characterizing forest canopies over large areas at broad spatial scales using satellite remote sensing data. However, satellite-derived LAI products can be limited by obstructed atmospheric conditions yielding sub-optimal values, or complete non-returns. The United States Environmental Protection Agency's Exposure Methods and Measurements and Computational Exposure Divisions are investigating the viability of supplemental modelled LAI inputs into satellite-derived data streams to support various regional and local scale air quality models for retrospective and future climate assessments. In this present study, one-year (2002) of plot level stand characteristics at four study sites located in Virginia and North Carolina (USA) are used to calibrate species-specific plant parameters in a semi-empirical biogeochemical model. The Environmental Policy Integrated Climate (EPIC) model was designed primarily for managed agricultural field crop ecosystems, but also includes managed woody species that span both xeric and mesic sites (e.g., mesquite, pine, oak, etc.). LAI was simulated using EPIC at a 4 km2 and 12 km2 grid coincident with the regional Community Multiscale Air Quality Model (CMAQ) grid. LAI comparisons were made between model-simulated and MODIS-derived LAI. Field/satellite-upscaled LAI was also compared to the corresponding MODIS LAI value. Preliminary results show field/satellite-upscaled LAI (1 km2) was 1.5 to 3 times smaller than that with the corresponding 1 km2 MODIS LAI for all four sites across all dates, with the largest discrepancies occurring at leaf-out and leaf senescence periods. Simulated LAI/MODIS LAI comparison results will be presented at the conference. Disclaimer: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S. Environmental Protection Agency funded and conducted the research described in this paper. Although

Effectiveness of Reptile Species Identification--A Comparison of a Dichotomous Key with an Identification Book

ERIC Educational Resources Information Center

Randler, Christoph; Zehender, Irene

2006-01-01

Species identification tasks are a prerequisite for an understanding of biodiversity. Here, we focused on different educational materials to foster the identification of six European reptile species. Our educational training unit was based on natural plastic models of six species and pupils either used an illustrated identification book or a…

The scaling of geographic ranges: implications for species distribution models

USGS Publications Warehouse

Yackulic, Charles B.; Ginsberg, Joshua R.

2016-01-01

There is a need for timely science to inform policy and management decisions; however, we must also strive to provide predictions that best reflect our understanding of ecological systems. Species distributions evolve through time and reflect responses to environmental conditions that are mediated through individual and population processes. Species distribution models that reflect this understanding, and explicitly model dynamics, are likely to give more accurate predictions.

Comparison of sterols and fatty acids in two species of Ganoderma

PubMed Central

2012-01-01

Background Two species of Ganoderma, G. sinense and G. lucidum, are used as Lingzhi in China. Howerver, the content of triterpenoids and polysaccharides, main actives compounds, are significant different, though the extracts of both G. lucidum and G. sinense have antitumoral proliferation effect. It is suspected that other compounds contribute to their antitumoral activity. Sterols and fatty acids have obvious bioactivity. Therefore, determination and comparison of sterols and fatty acids is helpful to elucidate the active components of Lingzhi. Results Ergosterol, a specific component of fungal cell membrane, was rich in G. lucidum and G. sinense. But its content in G. lucidum (median content 705.0 μg·g-1, range 189.1-1453.3 μg·g-1, n = 19) was much higher than that in G. sinense (median content 80.1 μg·g-1, range 16.0-409.8 μg·g-1, n = 13). Hierarchical clustering analysis based on the content of ergosterol showed that 32 tested samples of Ganoderma were grouped into two main clusters, G. lucidum and G. sinense. Hierarchical clustering analysis based on the contents of ten fatty acids showed that two species of Ganoderma had no significant difference though two groups were also obtained. The similarity of two species of Ganoderma in fatty acids may be related to their antitumoral proliferation effect. Conclusions The content of ergosterol is much higher in G. lucidum than in G. sinense. Palmitic acid, linoleic acid, oleic acid, stearic acid are main fatty acids in Ganoderma and their content had no significant difference between G. lucidum and G. sinense, which may contribute to their antitumoral proliferation effect. PMID:22293530

Factors affecting species distribution predictions: A simulation modeling experiment

Treesearch

Gordon C. Reese; Kenneth R. Wilson; Jennifer A. Hoeting; Curtis H. Flather

2005-01-01

Geospatial species sample data (e.g., records with location information from natural history museums or annual surveys) are rarely collected optimally, yet are increasingly used for decisions concerning our biological heritage. Using computer simulations, we examined factors that could affect the performance of autologistic regression (ALR) models that predict species...

Autoregressive modelling of species richness in the Brazilian Cerrado.

PubMed

Vieira, C M; Blamires, D; Diniz-Filho, J A F; Bini, L M; Rangel, T F L V B

2008-05-01

Spatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R(2) values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.

Provisional Models for Endangered Species Pesticide Assessments

EPA Pesticide Factsheets

The tools and models on this web page were developed for use in the Steps 1 and 2 analyses of national level assessments of the risks of chlorpyrifos, diazinon and malathion to endangered and threatened species and designated critical habitat.

Supervised DNA Barcodes species classification: analysis, comparisons and results

PubMed Central

2014-01-01

Background Specific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms. Methods In this work the efficacy of supervised machine learning methods to classify species with DNA Barcode sequences is shown. The Weka software suite, which includes a collection of supervised classification methods, is adopted to address the task of DNA Barcode analysis. Classifier families are tested on synthetic and empirical datasets belonging to the animal, fungus, and plant kingdoms. In particular, the function-based method Support Vector Machines (SVM), the rule-based RIPPER, the decision tree C4.5, and the Naïve Bayes method are considered. Additionally, the classification results are compared with respect to ad-hoc and well-established DNA Barcode classification methods. Results A software that converts the DNA Barcode FASTA sequences to the Weka format is released, to adapt different input formats and to allow the execution of the classification procedure. The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model. Rule-based methods have slightly inferior classification performances, but deliver the species specific positions and nucleotide assignments. On synthetic data the supervised machine learning methods obtain superior classification performances with respect to the traditional DNA Barcode

ESTIMATION OF CHEMICAL TOXICITY TO WILDLIFE SPECIES USING INTERSPECIES CORRELATION MODELS

EPA Science Inventory

Ecological risks to wildlife are typically assessed using toxicity data for relataively few species and with limited understanding of differences in species sensitivity to contaminants. Empirical interspecies correlation models were derived from LD50 values for 49 wildlife speci...

The Influences of Airmass Histories on Radical Species During POLARIS

NASA Technical Reports Server (NTRS)

Pierson, James M.; Kawa, S. R.

1998-01-01

The POLARIS mission focused on understanding the processes associated with the decrease of polar stratospheric ozone from spring to fall at high latitudes. This decrease is linked primarily to in situ photochemical destruction by reactive nitrogen species, NO and NO2, which also control other catalytic loss cycles. Steady state models have been used to test photochemistry and radical behavior but are not always adequate in simulating radical species observations. In some cases, air mass history can be important and trajectory models give an improved simulation of the radical species. Trajectory chemistry models, however, still consistently underestimate NO and NO2 abundances compared to measurements along the ER-2 flight track. The Goddard chemistry on trajectory model has been used to test updated rate constants for NO2 + OH, NO2 + O and OH + HNO3, key reactions that affect NO and NO2 abundances. We present comparisons between the modified Goddard chemistry on trajectory model, the JPL steady state model and observations from selected flights.

Mapping, Monitoring and Modeling Submersed Aquatic Vegetation Species and Communities

NASA Astrophysics Data System (ADS)

Hartis, Brett Michael

Aquatic macrophyte communities are critically important habitat species in aquatic systems worldwide. None are more important than those found beneath the water's surface, commonly referred to as submersed aquatic vegetation (SAV). Although vital to such systems, many native submersed plants have shown near irreversible declines in recent decades as water quality impairment, habitat destruction, and encroachment by invasive species have increased. In the past, aquatic plant science has emphasized the restoration and protection of native species and the management of invasive species. Comparatively little emphasis has been directed toward adequately mapping and monitoring these resources to track their viability over time. Modeling the potential intrusion of certain invasive plant species has also been given little attention, likely because aquatic systems in general can be difficult to assess. In recent years, scientists and resource managers alike have begun paying more attention to mapping SAV communities and to address the spread of invasive species across various regions. This research attempts to provide new, cutting-edge techniques to improve SAV mapping and monitoring efforts in coastal regions, at both community and individual species levels, while also providing insights about the establishment potential of Hydrilla verticillata, a noxious, highly invasive submersed plant. Technological advances in satellite remote sensing, interpolation and spatial analysis in geographic information systems, and state-of-the-art climate envelope modeling techniques were used to further assess the dynamic nature of SAV on various scales. This work contributes to the growing science of mapping, monitoring, and modeling of SAV

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

PubMed

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

2016-07-01

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 to a

Establishing endangered species recovery criteria using predictive simulation modeling

USGS Publications Warehouse

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.

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

USGS Publications Warehouse

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

Beyond the zebrafish: diverse fish species for modeling human disease

PubMed Central

Schartl, Manfred

2014-01-01

ABSTRACT In recent years, zebrafish, and to a lesser extent medaka, have become widely used small animal models for human diseases. These organisms have convincingly demonstrated the usefulness of fish for improving our understanding of the molecular and cellular mechanisms leading to pathological conditions, and for the development of new diagnostic and therapeutic tools. Despite the usefulness of zebrafish and medaka in the investigation of a wide spectrum of traits, there is evidence to suggest that other fish species could be better suited for more targeted questions. With the emergence of new, improved sequencing technologies that enable genomic resources to be generated with increasing efficiency and speed, the potential of non-mainstream fish species as disease models can now be explored. A key feature of these fish species is that the pathological condition that they model is often related to specific evolutionary adaptations. By exploring these adaptations, new disease-causing and disease-modifier genes might be identified; thus, diverse fish species could be exploited to better understand the complexity of disease processes. In addition, non-mainstream fish models could allow us to study the impact of environmental factors, as well as genetic variation, on complex disease phenotypes. This Review will discuss the opportunities that such fish models offer for current and future biomedical research. PMID:24271780

Performance metrics and variance partitioning reveal sources of uncertainty in species distribution models

USGS Publications Warehouse

Watling, James I.; Brandt, Laura A.; Bucklin, David N.; Fujisaki, Ikuko; Mazzotti, Frank J.; Romañach, Stephanie; Speroterra, Carolina

2015-01-01

Species distribution models (SDMs) are widely used in basic and applied ecology, making it important to understand sources and magnitudes of uncertainty in SDM performance and predictions. We analyzed SDM performance and partitioned variance among prediction maps for 15 rare vertebrate species in the southeastern USA using all possible combinations of seven potential sources of uncertainty in SDMs: algorithms, climate datasets, model domain, species presences, variable collinearity, CO2 emissions scenarios, and general circulation models. The choice of modeling algorithm was the greatest source of uncertainty in SDM performance and prediction maps, with some additional variation in performance associated with the comprehensiveness of the species presences used for modeling. Other sources of uncertainty that have received attention in the SDM literature such as variable collinearity and model domain contributed little to differences in SDM performance or predictions in this study. Predictions from different algorithms tended to be more variable at northern range margins for species with more northern distributions, which may complicate conservation planning at the leading edge of species' geographic ranges. The clear message emerging from this work is that researchers should use multiple algorithms for modeling rather than relying on predictions from a single algorithm, invest resources in compiling a comprehensive set of species presences, and explicitly evaluate uncertainty in SDM predictions at leading range margins.

Comparing species distribution models constructed with different subsets of environmental predictors

USGS Publications Warehouse

Bucklin, David N.; Basille, Mathieu; Benscoter, Allison M.; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.; Speroterra, Carolina; Watling, James I.

2014-01-01

Our results indicate that additional predictors have relatively minor effects on the accuracy of climate-based species distribution models and minor to moderate effects on spatial predictions. We suggest that implementing species distribution models with only climate predictors may provide an effective and efficient approach for initial assessments of environmental suitability.

Arima model and exponential smoothing method: A comparison

NASA Astrophysics Data System (ADS)

Wan Ahmad, Wan Kamarul Ariffin; Ahmad, Sabri

2013-04-01

This study shows the comparison between Autoregressive Moving Average (ARIMA) model and Exponential Smoothing Method in making a prediction. The comparison is focused on the ability of both methods in making the forecasts with the different number of data sources and the different length of forecasting period. For this purpose, the data from The Price of Crude Palm Oil (RM/tonne), Exchange Rates of Ringgit Malaysia (RM) in comparison to Great Britain Pound (GBP) and also The Price of SMR 20 Rubber Type (cents/kg) with three different time series are used in the comparison process. Then, forecasting accuracy of each model is measured by examinethe prediction error that producedby using Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute deviation (MAD). The study shows that the ARIMA model can produce a better prediction for the long-term forecasting with limited data sources, butcannot produce a better prediction for time series with a narrow range of one point to another as in the time series for Exchange Rates. On the contrary, Exponential Smoothing Method can produce a better forecasting for Exchange Rates that has a narrow range of one point to another for its time series, while itcannot produce a better prediction for a longer forecasting period.

Comparison of on-line and off-line methods to quantify reactive oxygen species (ROS) in atmospheric aerosols

NASA Astrophysics Data System (ADS)

Fuller, S. J.; Wragg, F. P. H.; Nutter, J.; Kalberer, M.

2014-08-01

Atmospheric aerosol particle concentrations have been linked with a wide range of pulmonary and cardio-vascular diseases but the particle properties responsible for these negative health effects are largely unknown. It is often speculated that reactive oxygen species (ROS) present in atmospheric particles lead to oxidative stress in, and ultimately disease of, the human lung. The quantification of ROS is highly challenging because some ROS components such as radicals are highly reactive and therefore short-lived. Thus, fast analysis methods are likely advantageous over methods with a long delay between aerosol sampling and ROS analysis. We present for the first time a detailed comparison of conventional off-line and fast on-line methods to quantify ROS in organic aerosols. For this comparison a new and fast on-line instrument was built and characterized to quantify ROS in aerosol particles with high sensitivity and a limit of detection of 4 nmol H2O2 equivalents per m3 air. ROS concentrations are measured with a time resolution of approximately 15 min, which allows the tracking of fast changing atmospheric conditions. The comparison of the off-line and on-line method shows that, in oxidized organic model aerosol particles, the majority of ROS have a very short lifetime of a few minutes whereas a small fraction is stable for a day or longer. This indicates that off-line techniques, where there is often a delay of hours to days between particle collection and ROS analysis, may severely underestimate true ROS concentrations and that fast on-line techniques are necessary for a reliable ROS quantification in atmospheric aerosol particles and a meaningful correlation with health outcomes.

Using the Maxent program for species distribution modelling to assess invasion risk

USGS Publications Warehouse

Jarnevich, Catherine S.; Young, Nicholas E.; Venette, R.C

2015-01-01

MAXENT is a software package used to relate known species occurrences to information describing the environment, such as climate, topography, anthropogenic features or soil data, and forecast the presence or absence of a species at unsampled locations. This particular method is one of the most popular species distribution modelling techniques because of its consistent strong predictive performance and its ease to implement. This chapter discusses the decisions and techniques needed to prepare a correlative climate matching model for the native range of an invasive alien species and use this model to predict the potential distribution of this species in a potentially invaded range (i.e. a novel environment) by using MAXENT for the Burmese python (Python molurus bivittatus) as a case study. The chapter discusses and demonstrates the challenges that are associated with this approach and examines the inherent limitations that come with using MAXENT to forecast distributions of invasive alien species.

Validity and sensitivity of a model for assessment of impacts of river floodplain reconstruction on protected and endangered species

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nooij, R.J.W. de; Lotterman, K.M.; Sande, P.H.J. van de

Environmental Impact Assessment (EIA) must account for legally protected and endangered species. Uncertainties relating to the validity and sensitivity of EIA arise from predictions and valuation of effects on these species. This paper presents a validity and sensitivity analysis of a model (BIO-SAFE) for assessment of impacts of land use changes and physical reconstruction measures on legally protected and endangered river species. The assessment is based on links between species (higher plants, birds, mammals, reptiles and amphibians, butterflies and dragon- and damselflies) and ecotopes (landscape ecological units, e.g., river dune, soft wood alluvial forests), and on value assignment to protectedmore » and endangered species using different valuation criteria (i.e., EU Habitats and Birds directive, Conventions of Bern and Bonn and Red Lists). The validity of BIO-SAFE has been tested by comparing predicted effects of landscape changes on the diversity of protected and endangered species with observed changes in biodiversity in five reconstructed floodplains. The sensitivity of BIO-SAFE to value assignment has been analysed using data of a Strategic Environmental Assessment concerning the Spatial Planning Key Decision for reconstruction of the Dutch floodplains of the river Rhine, aimed at flood defence and ecological rehabilitation. The weights given to the valuation criteria for protected and endangered species were varied and the effects on ranking of alternatives were quantified. A statistically significant correlation (p < 0.01) between predicted and observed values for protected and endangered species was found. The sensitivity of the model to value assignment proved to be low. Comparison of five realistic valuation options showed that different rankings of scenarios predominantly occur when valuation criteria are left out of the assessment. Based on these results we conclude that linking species to ecotopes can be used for adequate impact assessments

VisTrails SAHM: visualization and workflow management for species habitat modeling

USGS Publications Warehouse

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.

IsoPlot: a database for comparison of mRNA isoforms in fruit fly and mosquitoes

PubMed Central

Ng, I-Man; Tsai, Shang-Chi

2017-01-01

Abstract Alternative splicing (AS), a mechanism by which different forms of mature messenger RNAs (mRNAs) are generated from the same gene, widely occurs in the metazoan genomes. Knowledge about isoform variants and abundance is crucial for understanding the functional context in the molecular diversity of the species. With increasing transcriptome data of model and non-model species, a database for visualization and comparison of AS events with up-to-date information is needed for further research. IsoPlot is a publicly available database with visualization tools for exploration of AS events, including three major species of mosquitoes, Aedes aegypti, Anopheles gambiae, and Culex quinquefasciatus, and fruit fly Drosophila melanogaster, the model insect species. IsoPlot includes not only 88,663 annotated transcripts but also 17,037 newly predicted transcripts from massive transcriptome data at different developmental stages of mosquitoes. The web interface enables users to explore the patterns and abundance of isoforms in different experimental conditions as well as cross-species sequence comparison of orthologous transcripts. IsoPlot provides a platform for researchers to access comprehensive information about AS events in mosquitoes and fruit fly. Our database is available on the web via an interactive user interface with an intuitive graphical design, which is applicable for the comparison of complex isoforms within or between species. Database URL: http://isoplot.iis.sinica.edu.tw/ PMID:29220459

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

USGS Publications Warehouse

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

Limits to randomness in paleobiologic models: the case of Phanerozoic species diversity

NASA Technical Reports Server (NTRS)

Sepkoski, J. J. Jr; Sepkoski JJ, J. r. (Principal Investigator)

1994-01-01

The question of how random, or unconstrained, paleobiologic models should be is examined with a case study: Signor's (1982, 1985) inverse calculation of levels of marine species diversity through the Phanerozoic. His calculation involved an ingenious model that estimated species numbers and species abundances in the world oceans of the past by correcting known numbers of fossil species for variations in sedimentary rocks available for sampling and in effort paleontologists might devote to sampling. The model proves robust to changes in possible shapes of species-abundance distributions, but it is sensitive to alterations in the assumption that paleontologists collect fossils at random. If it is assumed that ease of collecting varies with age of sediment (with the Cenozoic offering easy sampling) or that paleontologists tend to seek out rarer fossils, results of the inverse calculation change. In particular, the magnitude of the calculated Cenozoic diversity increase always declines from the factor of about seven as originally reported to something considerably smaller. This leaves open the problem of the magnitude of Cenozoic increase in marine species diversity, awaiting better empirical data and, perhaps, more exacting models, random or otherwise.

GIS-based niche modeling for mapping species' habitats

USGS Publications Warehouse

Rotenberry, J.T.; Preston, K.L.; Knick, S.

2006-01-01

Ecological a??niche modelinga?? using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.

The Distribution and Abundance of Bird Species: Towards a Satellite, Data Driven Avian Energetics and Species Richness Model

NASA Technical Reports Server (NTRS)

Smith, James A.

2003-01-01

This paper addresses the fundamental question of why birds occur where and when they do, i.e., what are the causative factors that determine the spatio-temporal distributions, abundance, or richness of bird species? In this paper we outline the first steps toward building a satellite, data-driven model of avian energetics and species richness based on individual bird physiology, morphology, and interaction with the spatio-temporal habitat. To evaluate our model, we will use the North American Breeding Bird Survey and Christmas Bird Count data for species richness, wintering and breeding range. Long term and current satellite data series include AVHRR, Landsat, and MODIS.

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

NASA Astrophysics Data System (ADS)

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.

Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints.

PubMed

Colwell, Robert K; Gotelli, Nicholas J; Ashton, Louise A; Beck, Jan; Brehm, Gunnar; Fayle, Tom M; Fiedler, Konrad; Forister, Matthew L; Kessler, Michael; Kitching, Roger L; Klimes, Petr; Kluge, Jürgen; Longino, John T; Maunsell, Sarah C; McCain, Christy M; Moses, Jimmy; Noben, Sarah; Sam, Katerina; Sam, Legi; Shapiro, Arthur M; Wang, Xiangping; Novotny, Vojtech

2016-09-01

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness. © 2016 John Wiley & Sons Ltd/CNRS.

AmphiBase: A new genomic resource for non-model amphibian species.

PubMed

Kwon, Taejoon

2017-01-01

More than five thousand genes annotated in the recently published Xenopus laevis and Xenopus tropicalis genomes do not have a candidate orthologous counterpart in other vertebrate species. To determine whether these sequences represent genuine amphibian-specific genes or annotation errors, it is necessary to analyze them alongside sequences from other amphibian species. However, due to large genome sizes and an abundance of repeat sequences, there are limited numbers of gene sequences available from amphibian species other than Xenopus. AmphiBase is a new genomic resource covering non-model amphibian species, based on public domain transcriptome data and computational methods developed during the X. laevis genome project. Here, I review the current status of AmphiBase, including amphibian species with available transcriptome data or biological samples, and describe the challenges of building a comprehensive amphibian genomic resource in the absence of genomes. This mini-review will be informative for researchers interested in functional genomic experiments using amphibian model organisms, such as Xenopus and axolotl, and will assist in interpretation of results implicating "orphan genes." Additionally, this study highlights an opportunity for researchers working on non-model amphibian species to collaborate in their future efforts and develop amphibian genomic resources as a community. © 2017 Wiley Periodicals, Inc.

Psychological effect on single-species population models in a polluted environment.

PubMed

Wei, Fengying; Chen, Lihong

2017-08-01

We formulate and investigate the psychological effect of single-species population models in a polluted environment in this paper. For the deterministic single-species population model, the conditions that guarantee the local extinction and persistence in the mean are derived firstly. We then show that, around the pollution-free equilibrium, the stochastic single-species population is weakly persistent in the mean, and is stochastically permanent under some conditions. As a consequence, some numerical simulations demonstrate the efficiency of the main results. Copyright © 2017 Elsevier Inc. All rights reserved.

Investigation of the DSMC Approach for Ion/neutral Species in Modeling Low Pressure Plasma Reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deng Hao; Li, Z.; Levin, D.

2011-05-20

Low pressure plasma reactors are important tools for ionized metal physical vapor deposition (IMPVD), a semiconductor plasma processing technology that is increasingly being applied to deposit Cu seed layers on semiconductor surfaces of trenches and vias with the high aspect ratio (e.g., >5:1). A large fraction of ionized atoms produced by the IMPVD process leads to an anisotropic deposition flux towards the substrate, a feature which is critical for attaining a void-free and uniform fill. Modeling such devices is challenging due to their high plasma density, reactive environment, but low gas pressure. A modular code developed by the Computational Opticalmore » and Discharge Physics Group, the Hybrid Plasma Equipment Model (HPEM), has been successfully applied to the numerical investigations of IMPVD by modeling a hollow cathode magnetron (HCM) device. However, as the development of semiconductor devices progresses towards the lower pressure regime (e.g., <5 mTorr), the breakdown of the continuum assumption limits the application of the fluid model in HPEM and suggests the incorporation of the kinetic method, such as the direct simulation Monte Carlo (DSMC), in the plasma simulation.The DSMC method, which solves the Boltzmann equation of transport, has been successfully applied in modeling micro-fluidic flows in MEMS devices with low Reynolds numbers, a feature shared with the HCM. Modeling of the basic physical and chemical processes for ion/neutral species in plasma have been developed and implemented in DSMC, which include ion particle motion due to the Lorentz force, electron impact reactions, charge exchange reactions, and charge recombination at the surface. The heating of neutrals due to collisions with ions and the heating of ions due to the electrostatic field will be shown to be captured by the DSMC simulations. In this work, DSMC calculations were coupled with the modules from HPEM so that the plasma can be self-consistently solved. Differences in the

Implications of movement for species distribution models - Rethinking environmental data tools.

PubMed

Bruneel, Stijn; Gobeyn, Sacha; Verhelst, Pieterjan; Reubens, Jan; Moens, Tom; Goethals, Peter

2018-07-01

Movement is considered an essential process in shaping the distributions of species. Nevertheless, most species distribution models (SDMs) still focus solely on environment-species relationships to predict the occurrence of species. Furthermore, the currently used indirect estimates of movement allow to assess habitat accessibility, but do not provide an accurate description of movement. Better proxies of movement are needed to assess the dispersal potential of individual species and to gain a more practical insight in the interconnectivity of communities. Telemetry techniques are rapidly evolving and highly capable to provide explicit descriptions of movement, but their usefulness for SDMs will mainly depend on the ability of these models to deal with hitherto unconsidered ecological processes. More specifically, the integration of movement is likely to affect the environmental data requirements as the connection between environmental and biological data is crucial to provide reliable results. Mobility implies the occupancy of a continuum of space, hence an adequate representation of both geographical and environmental space is paramount to study mobile species distributions. In this context, environmental models, remote sensing techniques and animal-borne environmental sensors are discussed as potential techniques to obtain suitable environmental data. In order to provide an in-depth review of the aforementioned methods, we have chosen to use the modelling of fish distributions as a case study. The high mobility of fish and the often highly variable nature of the aquatic environment generally complicate model development, making it an adequate subject for research. Furthermore, insight into the distribution of fish is of great interest for fish stock assessments and water management worldwide, underlining its practical relevance. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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.

Intercomparisons of Aura MLS, ACE, and HALOE Observations of Long-Lived Trace Species Using the Langley Lagrangian Chemistry and Transport Model

NASA Technical Reports Server (NTRS)

Considine, David B.; Natarajan, Murali; Fairlie, T. D.; Lingenfelser, Gretchen S.; Bernath, Peter

2007-01-01

We use the LaRC Lagrangian Chemistry and Transport Model (LCTM) [Considine et al., 2007; Pierce et al., 2003] to intercompare ACE, Aura, and HALOE observations of long-lived trace species. The LCTM calculates the transport, mixing, and photochemical evolution of an ensemble of parcels that have been initialized from ACE-FTS measurements. Here we focus on late November, 2004 comparisons, due to the previous 3-week period of continuous HALOE observations and MLS v2.2 data on November 29, 2004.

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

NASA Astrophysics Data System (ADS)

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.

Mechanistic species distribution modeling reveals a niche shift during invasion.

PubMed

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

Information-theoretic model comparison unifies saliency metrics

PubMed Central

Kümmerer, Matthias; Wallis, Thomas S. A.; Bethge, Matthias

2015-01-01

Learning the properties of an image associated with human gaze placement is important both for understanding how biological systems explore the environment and for computer vision applications. There is a large literature on quantitative eye movement models that seeks to predict fixations from images (sometimes termed “saliency” prediction). A major problem known to the field is that existing model comparison metrics give inconsistent results, causing confusion. We argue that the primary reason for these inconsistencies is because different metrics and models use different definitions of what a “saliency map” entails. For example, some metrics expect a model to account for image-independent central fixation bias whereas others will penalize a model that does. Here we bring saliency evaluation into the domain of information by framing fixation prediction models probabilistically and calculating information gain. We jointly optimize the scale, the center bias, and spatial blurring of all models within this framework. Evaluating existing metrics on these rephrased models produces almost perfect agreement in model rankings across the metrics. Model performance is separated from center bias and spatial blurring, avoiding the confounding of these factors in model comparison. We additionally provide a method to show where and how models fail to capture information in the fixations on the pixel level. These methods are readily extended to spatiotemporal models of fixation scanpaths, and we provide a software package to facilitate their use. PMID:26655340

Post-discharge evolution of reactive species in the water activated by a surface air plasma: a modeling study

NASA Astrophysics Data System (ADS)

Liu, Z. C.; Liu, D. X.; Chen, C.; Liu, Z. J.; Yang, A. J.; Rong, M. Z.; Chen, H. L.; Kong, M. G.

2018-05-01

Plasma-activated water (PAW) has been reported to sustain a bactericidal ability for months. However, many reactive species regarded as the main antibacterial agents in PAW have short lifetimes of less than one second. In order to explain the prolonged antibacterial ability of PAW and predict how to extend its effective time, we studied the post-discharge evolution of reactive species in PAW based on a system-level model reported previously. Three common storage conditions for PAW were considered within the post-discharge time of 14 d: (I) leaving the residual gas and PAW in the sealed reactor; (II) leaving PAW in the open air; (III) sealing the container of PAW. In comparison, storage condition III was the best condition to preserve the long-lived species including H2O2 and HNO2/, whereas storage condition I was the best method to preserve the short-lived species including OH, HO2 and ONOOH/ONOO‑. It suggests that the gas–liquid mass transfer plays an important role in the evolution of reactive species. We also found that O2NOOH/O2NOO‑ had an almost one order of magnitude higher concentration and a longer residue time than those of ONOOH/ONOO‑. This distinction suggests that the biological effect of O2NOOH/O2NOO‑ may be important.

Comparison of Brassicaceae species for phytotoxicity testing

EPA Science Inventory

We compared four Brassicaceae species for potential use as test species in the EPAs Series 850 vegetative vigor test and other phytotoxicity tests to determine effects of chemicals on non-target plants. Arabidopsis thaliana var. Columbia is commonly used in plant molecular and p...

Using multi-species occupancy models in structured decision making on managed lands

USGS Publications Warehouse

Sauer, John R.; Blank, Peter J.; Zipkin, Elise F.; Fallon, Jane E.; Fallon, Frederick W.

2013-01-01

Land managers must balance the needs of a variety of species when manipulating habitats. Structured decision making provides a systematic means of defining choices and choosing among alternative management options; implementation of a structured decision requires quantitative approaches to predicting consequences of management on the relevant species. Multi-species occupancy models provide a convenient framework for making structured decisions when the management objective is focused on a collection of species. These models use replicate survey data that are often collected on managed lands. Occupancy can be modeled for each species as a function of habitat and other environmental features, and Bayesian methods allow for estimation and prediction of collective responses of groups of species to alternative scenarios of habitat management. We provide an example of this approach using data from breeding bird surveys conducted in 2008 at the Patuxent Research Refuge in Laurel, Maryland, evaluating the effects of eliminating meadow and wetland habitats on scrub-successional and woodland-breeding bird species using summed total occupancy of species as an objective function. Removal of meadows and wetlands decreased value of an objective function based on scrub-successional species by 23.3% (95% CI: 20.3–26.5), but caused only a 2% (0.5, 3.5) increase in value of an objective function based on woodland species, documenting differential effects of elimination of meadows and wetlands on these groups of breeding birds. This approach provides a useful quantitative tool for managers interested in structured decision making.

Predicting herbicide mixture effects on multiple algal species using mixture toxicity models.

PubMed

Nagai, Takashi

2017-10-01

The validity of the application of mixture toxicity models, concentration addition and independent action, to a species sensitivity distribution (SSD) for calculation of a multisubstance potentially affected fraction was examined in laboratory experiments. Toxicity assays of herbicide mixtures using 5 species of periphytic algae were conducted. Two mixture experiments were designed: a mixture of 5 herbicides with similar modes of action and a mixture of 5 herbicides with dissimilar modes of action, corresponding to the assumptions of the concentration addition and independent action models, respectively. Experimentally obtained mixture effects on 5 algal species were converted to the fraction of affected (>50% effect on growth rate) species. The predictive ability of the concentration addition and independent action models with direct application to SSD depended on the mode of action of chemicals. That is, prediction was better for the concentration addition model than the independent action model for the mixture of herbicides with similar modes of action. In contrast, prediction was better for the independent action model than the concentration addition model for the mixture of herbicides with dissimilar modes of action. Thus, the concentration addition and independent action models could be applied to SSD in the same manner as for a single-species effect. The present study to validate the application of the concentration addition and independent action models to SSD supports the usefulness of the multisubstance potentially affected fraction as the index of ecological risk. Environ Toxicol Chem 2017;36:2624-2630. © 2017 SETAC. © 2017 SETAC.

Model of Peatland Vegetation Species using HyMap Image and Machine Learning

NASA Astrophysics Data System (ADS)

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

PubMed Central

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

Quantitative comparisons of three modeling approaches for characterizing drought response of a highly variable, widely grown crop species

NASA Astrophysics Data System (ADS)

Pleban, J. R.; Mackay, D. S.; Aston, T.; Ewers, B. E.; Wienig, C.

2013-12-01

Quantifying the drought tolerance of crop species and genotypes is essential in order to predict how water stress may impact agricultural productivity. As climate models predict an increase in both frequency and severity of drought corresponding plant hydraulic and biochemical models are needed to accurately predict crop drought tolerance. Drought can result in cavitation of xylem conduits and related loss of plant hydraulic conductivity. This study tested the hypothesis that a model incorporating a plants vulnerability to cavitation would best assess drought tolerance in Brassica rapa. Four Brassica genotypes were subjected to drought conditions at a field site in Laramie, WY. Concurrent leaf gas exchange, volumetric soil moisture content and xylem pressure measurements were made during the drought period. Three models were used to access genotype specific drought tolerance. All 3 models rely on the Farquhar biochemical/biophysical model of leaf level photosynthesis, which is integrated into the Terrestrial Regional Ecosystem Exchange Simulator (TREES). The models differ in how TREES applies the environmental driving data and plant physiological mechanisms; specifically how water availability at the site of photosynthesis is derived. Model 1 established leaf water availability from a modeled soil moisture content; Model 2 input soil moisture measurements directly to establish leaf water availability; Model 3 incorporated the Sperry soil-plant transport model, which calculates flows and pressure along the soil-plant water transport pathway to establish leaf water availability. This third model incorporated measured xylem pressures thus constraining leaf water availability via genotype specific vulnerability curves. A multi-model intercomparison was made using a Bayesian approach, which assessed the interaction between uncertainty in model results and data. The three models were further evaluated by assessing model accuracy and complexity via deviance information

Comparison of dark energy models after Planck 2015

NASA Astrophysics Data System (ADS)

Xu, Yue-Yao; Zhang, Xin

2016-11-01

We make a comparison for ten typical, popular dark energy models according to their capabilities of fitting the current observational data. The observational data we use in this work include the JLA sample of type Ia supernovae observation, the Planck 2015 distance priors of cosmic microwave background observation, the baryon acoustic oscillations measurements, and the direct measurement of the Hubble constant. Since the models have different numbers of parameters, in order to make a fair comparison, we employ the Akaike and Bayesian information criteria to assess the worth of the models. The analysis results show that, according to the capability of explaining observations, the cosmological constant model is still the best one among all the dark energy models. The generalized Chaplygin gas model, the constant w model, and the α dark energy model are worse than the cosmological constant model, but still are good models compared to others. The holographic dark energy model, the new generalized Chaplygin gas model, and the Chevalliear-Polarski-Linder model can still fit the current observations well, but from an economically feasible perspective, they are not so good. The new agegraphic dark energy model, the Dvali-Gabadadze-Porrati model, and the Ricci dark energy model are excluded by the current observations.

Modeling metapopulation dynamics for single species of seabirds

USGS Publications Warehouse

Buckley, P.A.; Downer, R.; McCullough, D.R.; Barrett, R.H.

1992-01-01

Seabirds share many characteristics setting them apart from other birds. Importantly, they breed more or less obligatorily in local clusters of colonies that can move regularly from site to site, and they routinely exchange breeders. The properties of such metapopulations have only recently begun to be examined, often with models that are occupancy-based (using only colony presence or absence data) and deterministic (using single, empirically determined values for each of several population biology parameters). Some recent models are now frequency-based (using actual population sizes at each site), as well as stochastic (randomly varying critical parameters between biologically realistic limits), yielding better estimates of the behavior of future populations. Using two such models designed to quantify relative risks of population changes under different future scenarios (RAMAS/stage and RAMAS/space), we have examined probable future populations dynamics for three hypothetical seabirds -- an albatross, a cormorant, and a tern. With real parameters and ranges of values we alternatively modelled each species with and without density dependence, as well as with their numbers in a single, large colony, or in many smaller ones, distributed evenly or lognormally. We produced a series of species-typical lines for different population risks over the 50 years we simulated. We call these curves Instantaneous Threat Assessments (ITAs), and their shapes mirror the varying life history characteristics of our three species. We also demonstrated (by a process known as sensitivity analysis) that the most important parameters determining future population fates of all three species were correlation of mean growth rate among colonies; dispersal rate of present and future breeders; subadult survivorship; and the number of subpopulations (=colonies) - in roughly that descending order of importance. In addition, density dependence was found to markedly alter ITA line shape and position

Assessing the relative importance of environmental effects, carry-over effects and species differences in thermal stress resistance: a comparison of Drosophilids across field and laboratory generations.

PubMed

Schiffer, Michele; Hangartner, Sandra; Hoffmann, Ary A

2013-10-15

There is increasing interest in comparing species of related organisms for their susceptibility to thermal extremes in order to evaluate potential vulnerability to climate change. Comparisons are typically undertaken on individuals collected from the field with or without a period of acclimation. However, this approach does not allow the potential contributions of environmental and carry-over effects across generations to be separated from inherent species differences in susceptibility. To assess the importance of these different sources of variation, we here considered heat and cold resistance in Drosophilid species from tropical and temperate sites in the field and across two laboratory generations. Resistance in field-collected individuals tended to be lower when compared with F1 and F2 laboratory generations, and species differences in field flies were only weakly correlated to differences established under controlled rearing conditions, unlike in F1-F2 comparisons. This reflected large environmental effects on resistance associated with different sites and conditions experienced within sites. For the 8 h cold recovery assay there was no strong evidence of carry-over effects, whereas for the heat knockdown and 2 h cold recovery assays there was some evidence for such effects. However, for heat these were species specific in direction. Variance components for inherent species differences were substantial for resistance to heat and 8 h cold stress, but small for 2 h cold stress, though this may be a reflection of the species being considered in the comparisons. These findings highlight that inherent differences among species are difficult to characterise accurately without controlling for environmental sources of variation and carry-over effects. Moreover, they also emphasise the complex nature of carry-over effects that vary depending on the nature of stress traits and the species being evaluated.

Engelmann Spruce Site Index Models: A Comparison of Model Functions and Parameterizations

PubMed Central

Nigh, Gordon

2015-01-01

Engelmann spruce (Picea engelmannii Parry ex Engelm.) is a high-elevation species found in western Canada and western USA. As this species becomes increasingly targeted for harvesting, better height growth information is required for good management of this species. This project was initiated to fill this need. The objective of the project was threefold: develop a site index model for Engelmann spruce; compare the fits and modelling and application issues between three model formulations and four parameterizations; and more closely examine the grounded-Generalized Algebraic Difference Approach (g-GADA) model parameterization. The model fitting data consisted of 84 stem analyzed Engelmann spruce site trees sampled across the Engelmann Spruce – Subalpine Fir biogeoclimatic zone. The fitted models were based on the Chapman-Richards function, a modified Hossfeld IV function, and the Schumacher function. The model parameterizations that were tested are indicator variables, mixed-effects, GADA, and g-GADA. Model evaluation was based on the finite-sample corrected version of Akaike’s Information Criteria and the estimated variance. Model parameterization had more of an influence on the fit than did model formulation, with the indicator variable method providing the best fit, followed by the mixed-effects modelling (9% increase in the variance for the Chapman-Richards and Schumacher formulations over the indicator variable parameterization), g-GADA (optimal approach) (335% increase in the variance), and the GADA/g-GADA (with the GADA parameterization) (346% increase in the variance). Factors related to the application of the model must be considered when selecting the model for use as the best fitting methods have the most barriers in their application in terms of data and software requirements. PMID:25853472

Challenges in Species Tree Estimation Under the Multispecies Coalescent Model

PubMed Central

Xu, Bo; Yang, Ziheng

2016-01-01

The multispecies coalescent (MSC) model has emerged as a powerful framework for inferring species phylogenies while accounting for ancestral polymorphism and gene tree-species tree conflict. A number of methods have been developed in the past few years to estimate the species tree under the MSC. The full likelihood methods (including maximum likelihood and Bayesian inference) average over the unknown gene trees and accommodate their uncertainties properly but involve intensive computation. The approximate or summary coalescent methods are computationally fast and are applicable to genomic datasets with thousands of loci, but do not make an efficient use of information in the multilocus data. Most of them take the two-step approach of reconstructing the gene trees for multiple loci by phylogenetic methods and then treating the estimated gene trees as observed data, without accounting for their uncertainties appropriately. In this article we review the statistical nature of the species tree estimation problem under the MSC, and explore the conceptual issues and challenges of species tree estimation by focusing mainly on simple cases of three or four closely related species. We use mathematical analysis and computer simulation to demonstrate that large differences in statistical performance may exist between the two classes of methods. We illustrate that several counterintuitive behaviors may occur with the summary methods but they are due to inefficient use of information in the data by summary methods and vanish when the data are analyzed using full-likelihood methods. These include (i) unidentifiability of parameters in the model, (ii) inconsistency in the so-called anomaly zone, (iii) singularity on the likelihood surface, and (iv) deterioration of performance upon addition of more data. We discuss the challenges and strategies of species tree inference for distantly related species when the molecular clock is violated, and highlight the need for improving the

The Complete Chloroplast Genome of Wild Rice (Oryza minuta) and Its Comparison to Related Species.

PubMed

Asaf, Sajjad; Waqas, Muhammad; Khan, Abdul L; Khan, Muhammad A; Kang, Sang-Mo; Imran, Qari M; Shahzad, Raheem; Bilal, Saqib; Yun, Byung-Wook; Lee, In-Jung

2017-01-01

Oryza minuta , a tetraploid wild relative of cultivated rice (family Poaceae), possesses a BBCC genome and contains genes that confer resistance to bacterial blight (BB) and white-backed (WBPH) and brown (BPH) plant hoppers. Based on the importance of this wild species, this study aimed to understand the phylogenetic relationships of O. minuta with other Oryza species through an in-depth analysis of the composition and diversity of the chloroplast (cp) genome. The analysis revealed a cp genome size of 135,094 bp with a typical quadripartite structure and consisting of a pair of inverted repeats separated by small and large single copies, 139 representative genes, and 419 randomly distributed microsatellites. The genomic organization, gene order, GC content and codon usage are similar to those of typical angiosperm cp genomes. Approximately 30 forward, 28 tandem and 20 palindromic repeats were detected in the O . minuta cp genome. Comparison of the complete O. minuta cp genome with another eleven Oryza species showed a high degree of sequence similarity and relatively high divergence of intergenic spacers. Phylogenetic analyses were conducted based on the complete genome sequence, 65 shared genes and matK gene showed same topologies and O. minuta forms a single clade with parental O. punctata . Thus, the complete O . minuta cp genome provides interesting insights and valuable information that can be used to identify related species and reconstruct its phylogeny.

Improving the Use of Species Distribution Models in Conservation Planning and Management under Climate Change

PubMed Central

Porfirio, Luciana L.; Harris, Rebecca M. B.; Lefroy, Edward C.; Hugh, Sonia; Gould, Susan F.; Lee, Greg; Bindoff, Nathaniel L.; Mackey, Brendan

2014-01-01

Choice of variables, climate models and emissions scenarios all influence the results of species distribution models under future climatic conditions. However, an overview of applied studies suggests that the uncertainty associated with these factors is not always appropriately incorporated or even considered. We examine the effects of choice of variables, climate models and emissions scenarios can have on future species distribution models using two endangered species: one a short-lived invertebrate species (Ptunarra Brown Butterfly), and the other a long-lived paleo-endemic tree species (King Billy Pine). We show the range in projected distributions that result from different variable selection, climate models and emissions scenarios. The extent to which results are affected by these choices depends on the characteristics of the species modelled, but they all have the potential to substantially alter conclusions about the impacts of climate change. We discuss implications for conservation planning and management, and provide recommendations to conservation practitioners on variable selection and accommodating uncertainty when using future climate projections in species distribution models. PMID:25420020

Comparison of Cultivars and Seasonal Variation in Blueberry (Vaccinium Species) Leaf Extract on Adult T-Cell Leukemia Cell Line Growth Suppression.

PubMed

Kai, Hisahiro; Fuse, Takuichi; Kunitake, Hisato; Morishita, Kazuhiro; Matsuno, Koji

2014-06-30

The inhibitory effects of blueberry leaves on the proliferation of adult T-cell leukemia (ATL) cell lines have previously been reported. A comparison of blueberry leaf extracts from different cultivars and seasonal variation were investigated regarding their effects on ATL cell line proliferation. The inhibitory effects of 80% ethanol leaf extracts from different blueberry cultivars collected from April to December in 2006 or 2008 were evaluated using two ATL cell lines. The bioactivities of leaf extracts of rabbit-eye blueberry ( Vaccinium virgatum Aiton; RB species), southern highbush blueberry ( V. spp.; SB species), northern highbush blueberry ( V. corymbosum L.; NB species), and wild blueberry ( V. bracteatum Thunb.; WB species) were compared. Of these, leaves of the RB species collected in December showed a significantly stronger inhibitory effect in both cell lines than the SB, NB, or WB species. These results suggest elevated biosynthesis of ATL-preventative bioactive compounds in the leaves of the RB species before the defoliation season.

Comparison of Cultivars and Seasonal Variation in Blueberry (Vaccinium Species) Leaf Extract on Adult T-Cell Leukemia Cell Line Growth Suppression

PubMed Central

Kai, Hisahiro; Fuse, Takuichi; Kunitake, Hisato; Morishita, Kazuhiro; Matsuno, Koji

2014-01-01

The inhibitory effects of blueberry leaves on the proliferation of adult T-cell leukemia (ATL) cell lines have previously been reported. A comparison of blueberry leaf extracts from different cultivars and seasonal variation were investigated regarding their effects on ATL cell line proliferation. The inhibitory effects of 80% ethanol leaf extracts from different blueberry cultivars collected from April to December in 2006 or 2008 were evaluated using two ATL cell lines. The bioactivities of leaf extracts of rabbit-eye blueberry (Vaccinium virgatum Aiton; RB species), southern highbush blueberry (V. spp.; SB species), northern highbush blueberry (V. corymbosum L.; NB species), and wild blueberry (V. bracteatum Thunb.; WB species) were compared. Of these, leaves of the RB species collected in December showed a significantly stronger inhibitory effect in both cell lines than the SB, NB, or WB species. These results suggest elevated biosynthesis of ATL-preventative bioactive compounds in the leaves of the RB species before the defoliation season. PMID:28933373

Comparison of pathogenicity of Alternaria pellucida and Curvularia lunata on weed Echinochloa species.

PubMed

Reza, Mohammad; Motlagh, Safari

2015-07-01

Echinochloa spp. are the most important weeds in rice fields. In this research Curvularia lunata and Alternaria pellucida were isolated from these weeds and their pathogenicity effects were compared on these weeds and five rice cultivars in a completely random design with three replications in greenhouse conditions. Fungi were inoculated on weeds and rice cultivars, using spore suspension consisting of 10' spore ml(-1) of distilled water. Results indicated significant effect of Curvularia lunata and Alternaria pellucida on Echinochloa oryzicola and E. crus-galli. In the present study, effect of C. lunata on fresh weight, dry weight and height of Echinochloa species based on variance analysis table, a significant reaction was observed for height and fresh weight, but for dry weight reaction was not significant. The effect of A. pellucida on fresh weight, dry weight and height of Echinochloa species based on variance analysis table, a significant reaction was observed for all the three traits. Also, rice cultivars did not show any significant reaction to C. lunata and A. pellucida. The results showed that in comparison between effect of Curvularia lunata and Alternaria pellucida on Echinochloa spp., disease rating caused by A. pellucida on E. oryzicola and E. crusalli was more than disease rating caused by C. lunata and these species of weed were more susceptible to A. pellucida. However, A. alternata can be considered as a better promising bioherbicide to control Echinochloa spp.

Detecting temporal trends in species assemblages with bootstrapping procedures and hierarchical models

USGS Publications Warehouse

Gotelli, Nicholas J.; Dorazio, Robert M.; Ellison, Aaron M.; Grossman, Gary D.

2010-01-01

Quantifying patterns of temporal trends in species assemblages is an important analytical challenge in community ecology. We describe methods of analysis that can be applied to a matrix of counts of individuals that is organized by species (rows) and time-ordered sampling periods (columns). We first developed a bootstrapping procedure to test the null hypothesis of random sampling from a stationary species abundance distribution with temporally varying sampling probabilities. This procedure can be modified to account for undetected species. We next developed a hierarchical model to estimate species-specific trends in abundance while accounting for species-specific probabilities of detection. We analysed two long-term datasets on stream fishes and grassland insects to demonstrate these methods. For both assemblages, the bootstrap test indicated that temporal trends in abundance were more heterogeneous than expected under the null model. We used the hierarchical model to estimate trends in abundance and identified sets of species in each assemblage that were steadily increasing, decreasing or remaining constant in abundance over more than a decade of standardized annual surveys. Our methods of analysis are broadly applicable to other ecological datasets, and they represent an advance over most existing procedures, which do not incorporate effects of incomplete sampling and imperfect detection.

Species data: National inventory of range maps and distribution models

USGS Publications Warehouse

Gergely, Kevin J.; McKerrow, Alexa

2013-01-01

The Gap Analysis Program (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP species data includes vertebrate range maps and distribution models for the continental United States, as well as Alaska, Hawaii, Puerto Rico, and U.S. Virgin Islands. The vertebrate species include amphibians, birds, mammals, and reptiles. Furthermore, data used to create the distribution models (for example, percent canopy cover, elevation, and so forth) also are available.

Synteny of Prunus and other model plant species

PubMed Central

Jung, Sook; Jiwan, Derick; Cho, Ilhyung; Lee, Taein; Abbott, Albert; Sosinski, Bryon; Main, Dorrie

2009-01-01

Background Fragmentary conservation of synteny has been reported between map-anchored Prunus sequences and Arabidopsis. With the availability of genome sequence for fellow rosid I members Populus and Medicago, we analyzed the synteny between Prunus and the three model genomes. Eight Prunus BAC sequences and map-anchored Prunus sequences were used in the comparison. Results We found a well conserved synteny across the Prunus species – peach, plum, and apricot – and Populus using a set of homologous Prunus BACs. Conversely, we could not detect any synteny with Arabidopsis in this region. Other peach BACs also showed extensive synteny with Populus. The syntenic regions detected were up to 477 kb in Populus. Two syntenic regions between Arabidopsis and these BACs were much shorter, around 10 kb. We also found syntenic regions that are conserved between the Prunus BACs and Medicago. The array of synteny corresponded with the proposed whole genome duplication events in Populus and Medicago. Using map-anchored Prunus sequences, we detected many syntenic blocks with several gene pairs between Prunus and Populus or Arabidopsis. We observed a more complex network of synteny between Prunus-Arabidopsis, indicative of multiple genome duplication and subsequence gene loss in Arabidopsis. Conclusion Our result shows the striking microsynteny between the Prunus BACs and the genome of Populus and Medicago. In macrosynteny analysis, more distinct Prunus regions were syntenic to Populus than to Arabidopsis. PMID:19208249

Multi-species occurrence models to evaluate the effects of conservation and management actions

USGS Publications Warehouse

Zipkin, E.F.; Andrew, Royle J.; Dawson, D.K.; Bates, S.

2010-01-01

Conservation and management actions often have direct and indirect effects on a wide range of species. As such, it is important to evaluate the impacts that such actions may have on both target and non-target species within a region. Understanding how species richness and composition differ as a result of management treatments can help determine potential ecological consequences. Yet it is difficult to estimate richness because traditional sampling approaches detect species at variable rates and some species are never observed. We present a framework for assessing management actions on biodiversity using a multi-species hierarchical model that estimates individual species occurrences, while accounting for imperfect detection of species. Our model incorporates species-specific responses to management treatments and local vegetation characteristics and a hierarchical component that links species at a community-level. This allows for comprehensive inferences on the whole community or on assemblages of interest. Compared to traditional species models, occurrence estimates are improved for all species, even for those that are rarely observed, resulting in more precise estimates of species richness (including species that were unobserved during sampling). We demonstrate the utility of this approach for conservation through an analysis comparing bird communities in two geographically similar study areas: one in which white-tailed deer (Odocoileus virginianus) densities have been regulated through hunting and one in which deer densities have gone unregulated. Although our results indicate that species and assemblage richness were similar in the two study areas, point-level richness was significantly influenced by local vegetation characteristics, a result that would have been underestimated had we not accounted for variability in species detection.

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

PubMed

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

Controlling species richness in spin-glass model ecosystems

NASA Astrophysics Data System (ADS)

Poderoso, Fábio C.; Fontanari, José F.

2006-11-01

Within the framework of the random replicator model of ecosystems, we use equilibrium statistical mechanics tools to study the effect of manipulating the ecosystem so as to guarantee that a fixed fraction of the surviving species at equilibrium display a predefined set of characters (e.g., characters of economic value). Provided that the intraspecies competition is not too weak, we find that the consequence of such intervention on the ecosystem composition is a significant increase on the number of species that become extinct, and so the impoverishment of the ecosystem.

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

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.

2016-01-01

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 emphasise 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

Comparison of Themodynamic and Transport Property Models for Computing Equilibrium High Enthalpy Flows

NASA Astrophysics Data System (ADS)

Ramasahayam, Veda Krishna Vyas; Diwakar, Anant; Bodi, Kowsik

2017-11-01

To study the flow of high temperature air in vibrational and chemical equilibrium, accurate models for thermodynamic state and transport phenomena are required. In the present work, the performance of a state equation model and two mixing rules for determining equilibrium air thermodynamic and transport properties are compared with that of curve fits. The thermodynamic state model considers 11 species which computes flow chemistry by an iterative process and the mixing rules considered for viscosity are Wilke and Armaly-Sutton. The curve fits of Srinivasan, which are based on Grabau type transition functions, are chosen for comparison. A two-dimensional Navier-Stokes solver is developed to simulate high enthalpy flows with numerical fluxes computed by AUSM+-up. The accuracy of state equation model and curve fits for thermodynamic properties is determined using hypersonic inviscid flow over a circular cylinder. The performance of mixing rules and curve fits for viscosity are compared using hypersonic laminar boundary layer prediction on a flat plate. It is observed that steady state solutions from state equation model and curve fits match with each other. Though curve fits are significantly faster the state equation model is more general and can be adapted to any flow composition.

Bringing modeling to the masses: A web based system to predict potential species distributions

USGS Publications Warehouse

Graham, Jim; Newman, Greg; Kumar, Sunil; Jarnevich, Catherine S.; Young, Nick; Crall, Alycia W.; Stohlgren, Thomas J.; Evangelista, Paul

2010-01-01

Predicting current and potential species distributions and abundance is critical for managing invasive species, preserving threatened and endangered species, and conserving native species and habitats. Accurate predictive models are needed at local, regional, and national scales to guide field surveys, improve monitoring, and set priorities for conservation and restoration. Modeling capabilities, however, are often limited by access to software and environmental data required for predictions. To address these needs, we built a comprehensive web-based system that: (1) maintains a large database of field data; (2) provides access to field data and a wealth of environmental data; (3) accesses values in rasters representing environmental characteristics; (4) runs statistical spatial models; and (5) creates maps that predict the potential species distribution. The system is available online at www.niiss.org, and provides web-based tools for stakeholders to create potential species distribution models and maps under current and future climate scenarios.

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

PubMed

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

Distribution models and species discovery: the story of a new Solanum species from the Peruvian Andes

PubMed Central

Särkinen, Tiina; Gonzáles, Paúl; Knapp, Sandra

2013-01-01

Abstract A new species of Solanum sect. Solanum from Peru is described here. Solanum pseudoamericanum Särkinen, Gonzáles & S.Knapp sp. nov. is a member of the Morelloid clade of Solanum, and is characterized by the combination of mostly forked inflorescences, flowers with small stamens 2.5 mm long including the filament, and strongly exerted styles with capitate stigmas. The species was first thought to be restricted to the seasonally dry tropical forests of southern Peru along the dry valleys of Río Pampas and Río Apurímac. Results from species distribution modelling (SDM) analysis with climatic predictors identified further potential suitable habitat areas in northern and central Peru. These areas were visited during field work in 2013. A total of 17 new populations across the predicted distribution were discovered using the model-based sampling method, and five further collections were identified amongst herbarium loans. Although still endemic to Peru, Solanum pseudoamericanum is now known from across northern, central and southern Peru. Our study demonstrates the usefulness of SDM for predicting new occurrences of rare plants, especially in the Andes where collection densities are still low in many areas and where many new species remain to be discovered. PMID:24399901

Distribution models and species discovery: the story of a new Solanum species from the Peruvian Andes.

PubMed

Särkinen, Tiina; Gonzáles, Paúl; Knapp, Sandra

2013-01-01

A new species of Solanum sect. Solanum from Peru is described here. Solanum pseudoamericanum Särkinen, Gonzáles & S.Knapp sp. nov. is a member of the Morelloid clade of Solanum, and is characterized by the combination of mostly forked inflorescences, flowers with small stamens 2.5 mm long including the filament, and strongly exerted styles with capitate stigmas. The species was first thought to be restricted to the seasonally dry tropical forests of southern Peru along the dry valleys of Río Pampas and Río Apurímac. Results from species distribution modelling (SDM) analysis with climatic predictors identified further potential suitable habitat areas in northern and central Peru. These areas were visited during field work in 2013. A total of 17 new populations across the predicted distribution were discovered using the model-based sampling method, and five further collections were identified amongst herbarium loans. Although still endemic to Peru, Solanum pseudoamericanum is now known from across northern, central and southern Peru. Our study demonstrates the usefulness of SDM for predicting new occurrences of rare plants, especially in the Andes where collection densities are still low in many areas and where many new species remain to be discovered.

The Sim-SEQ Project: Comparison of Selected Flow Models for the S-3 Site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukhopadhyay, Sumit; Doughty, Christine A.; Bacon, Diana H.

Sim-SEQ is an international initiative on model comparison for geologic carbon sequestration, with an objective to understand and, if possible, quantify model uncertainties. Model comparison efforts in Sim-SEQ are at present focusing on one specific field test site, hereafter referred to as the Sim-SEQ Study site (or S-3 site). Within Sim-SEQ, different modeling teams are developing conceptual models of CO2 injection at the S-3 site. In this paper, we select five flow models of the S-3 site and provide a qualitative comparison of their attributes and predictions. These models are based on five different simulators or modeling approaches: TOUGH2/EOS7C, STOMP-CO2e,more » MoReS, TOUGH2-MP/ECO2N, and VESA. In addition to model-to-model comparison, we perform a limited model-to-data comparison, and illustrate how model choices impact model predictions. We conclude the paper by making recommendations for model refinement that are likely to result in less uncertainty in model predictions.« less

Model Comparison for Electron Thermal Transport

NASA Astrophysics Data System (ADS)

Moses, Gregory; Chenhall, Jeffrey; Cao, Duc; Delettrez, Jacques

2015-11-01

Four electron thermal transport models are compared for their ability to accurately and efficiently model non-local behavior in ICF simulations. Goncharov's transport model has accurately predicted shock timing in implosion simulations but is computationally slow and limited to 1D. The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. uses multigroup diffusion to speed up the calculation. Chenhall has expanded upon the iSNB diffusion model to a higher order simplified P3 approximation and a Monte Carlo transport model, to bridge the gap between the iSNB and Goncharov models while maintaining computational efficiency. Comparisons of the above models for several test problems will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.

Development of aquatic life criteria for triclosan and comparison of the sensitivity between native and non-native species.

PubMed

Wang, Xiao-Nan; Liu, Zheng-Tao; Yan, Zhen-Guang; Zhang, Cong; Wang, Wei-Li; Zhou, Jun-Li; Pei, Shu-Wei

2013-09-15

Triclosan (TCS) is an antimicrobial agent which is used as a broad-spectrum bacteriostatic and found in personal care products, and due to this it is widely spread in the aquatic environment. However, there is no paper dealing with the aquatic life criteria of TCS, mainly result from the shortage of toxicity data of different taxonomic levels. In the present study, toxicity data were obtained from 9 acute toxicity tests and 3 chronic toxicity tests using 9 Chinese native aquatic species from different taxonomic levels, and the aquatic life criteria was derived using 3 methods. Furthermore, differences of species sensitivity distributions (SSD) between native and non-native species were compared. Among the tested species, demersal fish Misgurnus anguillicaudatus was the most sensitive species, and the fishes were more sensitive than the aquatic invertebrates of Annelid and insect, and the insect was the least sensitive species. The comparison showed that there was no significant difference between SSDs constructed from native and non-native taxa. Finally, a criterion maximum concentration of 0.009 mg/L and a criterion continuous concentration of 0.002 mg/L were developed based on different taxa, according to the U.S. Environmental Protection Agency guidelines. Copyright © 2013 Elsevier B.V. All rights reserved.

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

USGS Publications Warehouse

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).

Phylogeny of zebrafish, a "model species," within Danio, a "model genus".

PubMed

McCluskey, Braedan M; Postlethwait, John H

2015-03-01

Zebrafish (Danio rerio) is an important model for vertebrate development, genomics, physiology, behavior, toxicology, and disease. Additionally, work on numerous Danio species is elucidating evolutionary mechanisms for morphological development. Yet, the relationships of zebrafish and its closest relatives remain unclear possibly due to incomplete lineage sorting, speciation with gene flow, and interspecies hybridization. To clarify these relationships, we first constructed phylogenomic data sets from 30,801 restriction-associated DNA (RAD)-tag loci (483,026 variable positions) with clear orthology to a single location in the sequenced zebrafish genome. We then inferred a well-supported species tree for Danio and tested for gene flow during the diversification of the genus. An approach independent of the sequenced zebrafish genome verified all inferred relationships. Although identification of the sister taxon to zebrafish has been contentious, multiple RAD-tag data sets and several analytical methods provided strong evidence for Danio aesculapii as the most closely related extant zebrafish relative studied to date. Data also displayed patterns consistent with gene flow during speciation and postspeciation introgression in the lineage leading to zebrafish. The incorporation of biogeographic data with phylogenomic analyses put these relationships in a phylogeographic context and supplied additional support for D. aesculapii as the sister species to D. rerio. The clear resolution of this study establishes a framework for investigating the evolutionary biology of Danio and the heterogeneity of genome evolution in the recent history of a model organism within an emerging model genus for genetics, development, and evolution. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Quantifying errors in trace species transport modeling.

PubMed

Prather, Michael J; Zhu, Xin; Strahan, Susan E; Steenrod, Stephen D; Rodriguez, Jose M

2008-12-16

One expectation when computationally solving an Earth system model is that a correct answer exists, that with adequate physical approximations and numerical methods our solutions will converge to that single answer. With such hubris, we performed a controlled numerical test of the atmospheric transport of CO(2) using 2 models known for accurate transport of trace species. Resulting differences were unexpectedly large, indicating that in some cases, scientific conclusions may err because of lack of knowledge of the numerical errors in tracer transport models. By doubling the resolution, thereby reducing numerical error, both models show some convergence to the same answer. Now, under realistic conditions, we identify a practical approach for finding the correct answer and thus quantifying the advection error.

Seeing the forest and the trees: multilevel models reveal both species and community patterns

Treesearch

Michelle M. Jackson; Monica G. Turner; Scott M. Pearson; Anthony R. Ives

2012-01-01

Studies designed to understand species distributions and community assemblages typically use separate analytical approaches (e.g., logistic regression and ordination) to model the distribution of individual species and to relate community composition to environmental variation. Multilevel models (MLMs) offer a promising strategy for integrating species and community-...

Modeling potential habitats for alien species Dreissena polymorpha in continental USA

USGS Publications Warehouse

Mingyang, Li; Yunwei, Ju; Kumar, Sunil; Stohlgren, Thomas J.

2008-01-01

The effective measure to minimize the damage of invasive species is to block the potential invasive species to enter into suitable areas. 1864 occurrence points with GPS coordinates and 34 environmental variables from Daymet datasets were gathered, and 4 modeling methods, i.e., Logistic Regression (LR), Classification and Regression Trees (CART), Genetic Algorithm for Rule-Set Prediction (GARP), and maximum entropy method (Maxent), were introduced to generate potential geographic distributions for invasive species Dreissena polymorpha in Continental USA. Then 3 statistical criteria of the area under the Receiver Operating Characteristic curve (AUC), Pearson correlation (COR) and Kappa value were calculated to evaluate the performance of the models, followed by analyses on major contribution variables. Results showed that in terms of the 3 statistical criteria, the prediction results of the 4 ecological niche models were either excellent or outstanding, in which Maxent outperformed the others in 3 aspects of predicting current distribution habitats, selecting major contribution factors, and quantifying the influence of environmental variables on habitats. Distance to water, elevation, frequency of precipitation and solar radiation were 4 environmental forcing factors. The method suggested in the paper can have some reference meaning for modeling habitats of alien species in China and provide a direction to prevent Mytilopsis sallei on the Chinese coast line.

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

USGS Publications Warehouse

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

Food-web models predict species abundances in response to habitat change.

PubMed

Gotelli, Nicholas J; Ellison, Aaron M

2006-10-01

Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss.

Food-Web Models Predict Species Abundances in Response to Habitat Change

PubMed Central

Gotelli, Nicholas J; Ellison, Aaron M

2006-01-01

Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss. PMID:17002518

The importance of considering rainfall partitioning in afforestation initiatives in semiarid climates: A comparison of common planted tree species in Tehran, Iran.

PubMed

Sadeghi, Seyed Mohammad Moein; Attarod, Pedram; Van Stan, John Toland; Pypker, Thomas Grant

2016-10-15

As plantations become increasingly important sources of wood and fiber in arid/semiarid places, they have also become increasingly criticized for their hydrological impacts. An examination and comparison of gross rainfall (GR) partitioning across commonly-planted tree species (Pinus eldarica, Cupressus arizonica, Robinia pseudoacacia, and Fraxinus rotundifolia) in semiarid regions has great value for watershed and forest managers interested in managing canopy hydrological processes for societal benefit. Therefore, we performed a field study examining GR partitioning into throughfall (TF), stemflow (SF), and rainfall interception (I) for these species in the semiarid Chitgar Forest Park, Tehran, Iran. An advantage to our study is that we explore the effects of forest structural differences in plantation forests experiencing similar climatic factors and storm conditions. As such, variability in GR partitioning due to different meteorological conditions is minimized, allowing comparison of structural attributes across plantations. Our results show that commonly-selected afforestation species experiencing the same climate produced differing stand structures that differentially partition GR into TF, SF, and I. P. eldarica might be the best of the four species to plant if the primary goal of afforestation is to limit erosion and stormwater runoff as it intercepted more rainfall than other species. However, the high SF generation from F. rotundifolia, and low GR necessary to initiate SF, could maximize retention of water in the soils since SF has been shown to infiltrate along root pathways and access groundwater. A consideration of GR partitioning should be considered when selecting a species for afforestation/reforestation in water-limited ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

Performance of Candida ID, a New Chromogenic Medium for Presumptive Identification of Candida Species, in Comparison to CHROMagar Candida

PubMed Central

Willinger, Birgit; Hillowoth, Cornelia; Selitsch, Brigitte; Manafi, Mammad

2001-01-01

Candida ID agar allows identification of Candida albicans and differentiation of other Candida species. In comparison with CHROMagar Candida, we evaluated the performance of this medium directly from 596 clinical specimens. In particular, detection of C. albicans after 24 h of incubation was easier on Candida ID (sensitivity, 96.8%) than on CHROMagar (sensitivity, 49.6%). PMID:11574621

Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.

PubMed

Vesely, Stepan; Klöckner, Christian A; Dohnal, Mirko

2016-03-01

In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

Regeneration of three pine species in a Mediterranean forest: A study to test predictions from species distribution models under changing climates.

PubMed

Tíscar, P A; Candel-Pérez, D; Estrany, J; Balandier, P; Gómez, R; Lucas-Borja, M E

2017-04-15

The study tested the hypothesis that future changes in the composition of tree communities, as predicted by species distribution models, could already be apparent in the current regeneration patterns of three pine species (Pinus pinaster, P. nigra and P. sylvestris)inhabiting the central-eastern mountains of Spain. We carried out both an observational study and a seed-sowing experiment to analyze, along an altitudinal and latitudinal gradient, whether recent recruitment patterns indicate an expansion of P. pinaster forests to the detriment of P. nigra ones in the low-altitude southern sites of these mountains; or whether P. sylvestris is being replaced by P. nigra in the high-altitude sites from the same area. The observational study gathered data from 561 plots of the Spanish National Forest Inventory. The seed-sowing experiment tested the effects of irrigation and stand basal area on seedling emergence and survival. Data were analyzed by means of Generalized Linear Models and Generalized Linear Mixed Models. Regeneration of the three pine species responded similarly to the explicative factors studied, but the density of tree seedlings and saplings exhibited a wide spatial heterogeneity. This result suggested that a mosaic of site- and species-specific responses to climate change might mislead model projections on the future forest occupancy of tree species. Yet, we found no indications of neither an expansion nor a contraction of the near future forest occupancy of the tree species studied. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

An overview of methods for developing bioenergetic and life history models for rare and endangered species

USGS Publications Warehouse

Petersen, J.H.; DeAngelis, D.L.; Paukert, C.P.

2008-01-01

Many fish species are at risk to some degree, and conservation efforts are planned or underway to preserve sensitive populations. For many imperiled species, models could serve as useful tools for researchers and managers as they seek to understand individual growth, quantify predator-prey dynamics, and identify critical sources of mortality. Development and application of models for rare species however, has been constrained by small population sizes, difficulty in obtaining sampling permits, limited opportunities for funding, and regulations on how endangered species can be used in laboratory studies. Bioenergetic and life history models should help with endangered species-recovery planning since these types of models have been used successfully in the last 25 years to address management problems for many commercially and recreationally important fish species. In this paper we discuss five approaches to developing models and parameters for rare species. Borrowing model functions and parameters from related species is simple, but uncorroborated results can be misleading. Directly estimating parameters with laboratory studies may be possible for rare species that have locally abundant populations. Monte Carlo filtering can be used to estimate several parameters by means of performing simple laboratory growth experiments to first determine test criteria. Pattern-oriented modeling (POM) is a new and developing field of research that uses field-observed patterns to build, test, and parameterize models. Models developed using the POM approach are closely linked to field data, produce testable hypotheses, and require a close working relationship between modelers and empiricists. Artificial evolution in individual-based models can be used to gain insight into adaptive behaviors for poorly understood species and thus can fill in knowledge gaps. ?? Copyright by the American Fisheries Society 2008.

Estimating near-road pollutant dispersion: a model inter-comparison

EPA Science Inventory

A model inter-comparison study to assess the abilities of steady-state Gaussian dispersion models to capture near-road pollutant dispersion has been carried out with four models (AERMOD, run with both the area-source and volume-source options to represent roadways, CALINE, versio...

SysFinder: A customized platform for search, comparison and assisted design of appropriate animal models based on systematic similarity.

PubMed

Yang, Shuang; Zhang, Guoqing; Liu, Wan; Wang, Zhen; Zhang, Jifeng; Yang, Dongshan; Chen, Y Eugene; Sun, Hong; Li, Yixue

2017-05-20

Animal models are increasingly gaining values by cross-comparisons of response or resistance to clinical agents used for patients. However, many disease mechanisms and drug effects generated from animal models are not transferable to human. To address these issues, we developed SysFinder (http://lifecenter.sgst.cn/SysFinder), a platform for scientists to find appropriate animal models for translational research. SysFinder offers a "topic-centered" approach for systematic comparisons of human genes, whose functions are involved in a specific scientific topic, to the corresponding homologous genes of animal models. Scientific topic can be a certain disease, drug, gene function or biological pathway. SysFinder calculates multi-level similarity indexes to evaluate the similarities between human and animal models in specified scientific topics. Meanwhile, SysFinder offers species-specific information to investigate the differences in molecular mechanisms between humans and animal models. Furthermore, SysFinder provides a user-friendly platform for determination of short guide RNAs (sgRNAs) and homology arms to design a new animal model. Case studies illustrate the ability of SysFinder in helping experimental scientists. SysFinder is a useful platform for experimental scientists to carry out their research in the human molecular mechanisms. Copyright © 2017 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Assessing three fish species ecological status in Colorado River, Grand Canyon based on physical habitat and population models.

PubMed

Yao, Weiwei; Chen, Yuansheng

2018-04-01

Colorado River is a unique ecosystem and provides important ecological services such as habitat for fish species as well as water power energy supplies. River management for this ecosystem requires assessment and decision support tools for fish which involves protecting, restoring as well as forecasting of future conditions. In this paper, a habitat and population model was developed and used to determine the levels of fish habitat suitability and population density in Colorado River between Lees Ferry and Lake Mead. The short term target fish populations are also predicted based on native fish recovery strategy. This model has been developed by combining hydrodynamics, heat transfer and sediment transport models with a habitat suitability index model and then coupling with habitat model into life stage population model. The fish were divided into four life stages according to the fish length. Three most abundant and typical native and non-native fish were selected as target species, which are rainbow trout (Oncorhynchus mykiss), brown trout (Salmo trutta) and flannelmouth sucker (Catostomus latipinnis). Flow velocity, water depth, water temperature and substrates were used as the suitability indicators in habitat model and overall suitability index (OSI) as well as weight usable area (WUA) was used as an indicator in population model. A comparison was made between simulated fish population alteration and surveyed fish number fluctuation during 2000 to 2009. The application of this habitat and population model indicates that this model can be accurate present habitat situation and targets fish population dynamics of in the study areas. The analysis also indicates the flannelmouth sucker population will steadily increase while the rainbow trout will decrease based on the native fish recovery scheme. Copyright © 2018. Published by Elsevier Inc.

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy

PubMed Central

Pottier, Julien; Malenovský, Zbyněk; Psomas, Achilleas; Homolová, Lucie; Schaepman, Michael E.; Choler, Philippe; Thuiller, Wilfried; Guisan, Antoine; Zimmermann, Niklaus E.

2014-01-01

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data. PMID:25079495

Assessment of the hybrid propagation model, Volume 2: Comparison with the Integrated Noise Model

DOT National Transportation Integrated Search

2012-08-31

This is the second of two volumes of the report on the Hybrid Propagation Model (HPM), an advanced prediction model for aviation noise propagation. This volume presents comparisons of the HPM and the Integrated Noise Model (INM) for conditions of une...

Comparison of oligosaccharides in milk specimens from humans and twelve other species.

PubMed

Warren, C D; Chaturvedi, P; Newburg, A R; Oftedal, O T; Tilden, C D; Newburg, D S

2001-01-01

Human milk contains large amounts of many oligosaccharides, most of which are fucosylated; several inhibit pathogenic bacteria, viruses, and toxins that cause disease in humans. Although bovine milk is known to have much less and many fewer types of oligosaccharides, no studies heretofore have indicated whether the amount or complexity of human milk oligosaccharides is unique to our species. Toward this end, a comparison was made of the major individual oligosaccharides in milk specimens from a variety of species, including the great apes. The neutral compounds, which represent the bulk of oligosaccharides in human milk, were isolated, perbenzoylated, resolved by high performance liquid chromatography (HPLC), and detected at 229nm. Ambiguous structures were determined by mass spectrometry. All milk specimens contained lactose, although levels were quite low in bear and kangaroo milk. The types of oligosaccharides in milk specimens from the primates resembled those of human milk, but the amounts, especially of the larger molecules, were markedly lower. The relative amounts of oligosaccharides in the bonobo changed over the course of lactation, as they do in humans. Marine mammals generally had few oligosaccharides in their milk other than 2'-fucosyllactose. Grizzly and black bear milk specimens contained a wide range of oligosaccharides, many of which had novel, fucosylated structures. Milk specimens from humans, bears, and marsupials had the greatest quantity of, and the most complex, neutral oligosaccharides. Although human milk contained more oligosaccharide than did milk specimens from the other species studied, the presence of appreciable amounts of complex oligosaccharides was not unique to humans. This finding suggests that in animal milk specimens, as in human milk, neutral fucosylated oligosaccharides potentially offer protection from pathogens to offspring with immature immune systems.

Of mice and rats: key species variations in the sexual differentiation of brain and behavior.

PubMed

Bonthuis, P J; Cox, K H; Searcy, B T; Kumar, P; Tobet, S; Rissman, E F

2010-07-01

Mice and rats are important mammalian models in biomedical research. In contrast to other biomedical fields, work on sexual differentiation of brain and behavior has traditionally utilized comparative animal models. As mice are gaining in popularity, it is essential to acknowledge the differences between these two rodents. Here we review neural and behavioral sexual dimorphisms in rats and mice, which highlight species differences and experimental gaps in the literature, that are needed for direct species comparisons. Moving forward, investigators must answer fundamental questions about their chosen organism, and attend to both species and strain differences as they select the optimal animal models for their research questions. Copyright 2010 Elsevier Inc. All rights reserved.

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

PubMed

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

Data-Model Comparisons of the October, 2002 Event Using the Space Weather Modeling Framework

NASA Astrophysics Data System (ADS)

Welling, D. T.; Chappell, C. R.; Schunk, R. W.; Barakat, A. R.; Eccles, V.; Glocer, A.; Kistler, L. M.; Haaland, S.; Moore, T. E.

2014-12-01

The September 27 - October 4, 2002 time period has been selected by the Geospace Environment Modeling Ionospheric Outflow focus group for community collaborative study because of its high magnetospheric activity and extensive data coverage. The FAST, Polar, and Cluster missions, as well as others, all made key observations during this period, creating a prime event for data-model comparisons. The GEM community has come together to simulate this period using many different methods in order to evaluate models, compare results, and expand our knowledge of ionospheric outflow and its effects on global dynamics. This paper presents Space Weather Modeling Framework (SWMF) simulations of this important period compared against observations from the Polar TIDE, Cluster CODIF and EFW instruments. Density and velocity of oxygen and hydrogen throughout the lobes, plasmasheet, and inner magnetosphere will be the focus of these comparisons. For these simulations, the SWMF couples the multifluid version of BATS-R-US MHD to a variety of ionospheric outflow models of varying complexity. The simplest is outflow arising from constant MHD inner boundary conditions. Two first-principles-based models are also leveraged: the Polar Wind Outflow Model (PWOM), a fluid treatment of outflow dynamics, and the Generalized Polar Wind (GPW) model, which combines fluid and particle-in-cell approaches. Each model is capable of capturing a different set of energization mechanisms, yielding different outflow results. The data-model comparisons will illustrate how well each approach captures reality and which energization mechanisms are most important. This work will also assess our current capability to reproduce ionosphere-magnetosphere mass coupling.

THE NORTH AMERICAN MERCURY MODEL INTER-COMPARISON STUDY (NAMMIS)

EPA Science Inventory

This paper describes the North American Mercury Model Inter-comparison Study (NAMMIS). The NAMMIS is an effort to apply atmospheric Hg models in a tightly constrained testing environment with a focus on North America. With each model using the same input data sets for initial co...

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

Treesearch

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)...

Nitrogen Species in the Post-Pinatubo Stratosphere: Model Analysis Utilizing UARS Measurements. Appendix F

NASA Technical Reports Server (NTRS)

Danilin, Michael Y.; Rodriguez, Jose M.; Hu, Wenjie; Ko, Malcolm K. W.; Weisenstein, Debra K.; Kumer, John B.; Mergenthaler, John L.; Russell, James M., III; Koike, Makoto; Yue, Glenn K.

1999-01-01

We present an analysis of the impact of heterogeneous chemistry on the partitioning of nitrogen species measured by the Upper Atmosphere Research Satellite (UARS) instruments. The UARS measurements utilized include N2O, HNO3, and ClONO2 from the cryogenic limb array etalon spectrometer (CLAES), version 7 (v.7), and temperature, methane, ozone, H2O, HCl, NO and NO2 from the halogen occultation experiment (HALOE), version 18. The analysis is carried out for the UARS data obtained between January 1992 and September 1994 in the 100- to 1-mbar (approx. 17-47 km) altitude range and over 10 deg latitude bins from 70 deg S to 70 deg N. The spatiotemporal evolution of aerosol surface area density (SAD) is adopted from analysis of the Stratospheric Aerosol and Gas Experiment (SAGE) II data. A diurnal steady state photochemical box model, constrained by the temperature, ozone, H2O, CH4, aerosol SAD, and columns of O2 and O3 above the point of interest, has been used as the main tool to analyze these data. Total inorganic nitrogen (NOY) is obtained by three different methods: (1) as a sum of the UARS-measured NO, NO2, HNO3, and ClONO2; (2) from the N2O-NOY correlation; and (3) from the CH4-NOY correlation. To validate our current understanding of stratospheric heterogeneous chemistry for post-Pinatubo conditions, the model-calculated monthly averaged NO(x)/NO(y) ratios and the NO, NO2, and HNO3 profiles are compared with the UARS-derived data. In general, the UARS-constrained box model captures the main features of nitrogen species partitioning in the post-Pinatubo years, such as recovery of NO(x) after the eruption, their seasonal variability and vertical profiles. However, the model underestimates the NO2 content, particularly in the 30- to 7-mbar (approx. 23-32 km) range. Comparisons of the calculated temporal behavior of the partial columns of NO2 and HNO3 and ground-based measurements at 45 deg S and 45 deg N are also presented. Our analysis indicates that ground

A fully coupled 3D transport model in SPH for multi-species reaction-diffusion systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adami, Stefan; Hu, X. Y.; Adams, N. A.

2011-08-23

Abstract—In this paper we present a fully generalized transport model for multiple species in complex two and threedimensional geometries. Based on previous work [1] we have extended our interfacial reaction-diffusion model to handle arbitrary numbers of species allowing for coupled reaction models. Each species is tracked independently and we consider different physics of a species with respect to the bulk phases in contact. We use our SPH model to simulate the reaction-diffusion problem on a pore-scale level of a solid oxide fuel cell (SOFC) with special emphasize on the effect of surface diffusion.

3D shape decomposition and comparison for gallbladder modeling

NASA Astrophysics Data System (ADS)

Huang, Weimin; Zhou, Jiayin; Liu, Jiang; Zhang, Jing; Yang, Tao; Su, Yi; Law, Gim Han; Chui, Chee Kong; Chang, Stephen

2011-03-01

This paper presents an approach to gallbladder shape comparison by using 3D shape modeling and decomposition. The gallbladder models can be used for shape anomaly analysis and model comparison and selection in image guided robotic surgical training, especially for laparoscopic cholecystectomy simulation. The 3D shape of a gallbladder is first represented as a surface model, reconstructed from the contours segmented in CT data by a scheme of propagation based voxel learning and classification. To better extract the shape feature, the surface mesh is further down-sampled by a decimation filter and smoothed by a Taubin algorithm, followed by applying an advancing front algorithm to further enhance the regularity of the mesh. Multi-scale curvatures are then computed on the regularized mesh for the robust saliency landmark localization on the surface. The shape decomposition is proposed based on the saliency landmarks and the concavity, measured by the distance from the surface point to the convex hull. With a given tolerance the 3D shape can be decomposed and represented as 3D ellipsoids, which reveal the shape topology and anomaly of a gallbladder. The features based on the decomposed shape model are proposed for gallbladder shape comparison, which can be used for new model selection. We have collected 19 sets of abdominal CT scan data with gallbladders, some shown in normal shape and some in abnormal shapes. The experiments have shown that the decomposed shapes reveal important topology features.

Predicting the geographical distribution of two invasive termite species from occurrence data.

PubMed

Tonini, Francesco; Divino, Fabio; Lasinio, Giovanna Jona; Hochmair, Hartwig H; Scheffrahn, Rudolf H

2014-10-01

Predicting the potential habitat of species under both current and future climate change scenarios is crucial for monitoring invasive species and understanding a species' response to different environmental conditions. Frequently, the only data available on a species is the location of its occurrence (presence-only data). Using occurrence records only, two models were used to predict the geographical distribution of two destructive invasive termite species, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki. The first model uses a Bayesian linear logistic regression approach adjusted for presence-only data while the second one is the widely used maximum entropy approach (Maxent). Results show that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development. The impact of future scenarios such as climate warming and population growth on the biotic distribution of both termite species was also assessed. Future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. The Bayesian logistic approach outperformed Maxent consistently in all models according to evaluation criteria such as model sensitivity and ecological realism. The importance of further studies for an explicit treatment of residual spatial autocorrelation and a more comprehensive comparison between both statistical approaches is suggested.

Supporting local diversity of habitats and species on farmland: a comparison of three wildlife-friendly schemes.

PubMed

Hardman, Chloe J; Harrison, Dominic P G; Shaw, Pete J; Nevard, Tim D; Hughes, Brin; Potts, Simon G; Norris, Ken

2016-02-01

Restoration and maintenance of habitat diversity have been suggested as conservation priorities in farmed landscapes, but how this should be achieved and at what scale are unclear. This study makes a novel comparison of the effectiveness of three wildlife-friendly farming schemes for supporting local habitat diversity and species richness on 12 farms in England.The schemes were: (i) Conservation Grade (Conservation Grade: a prescriptive, non-organic, biodiversity-focused scheme), (ii) organic agriculture and (iii) a baseline of Entry Level Stewardship (Entry Level Stewardship: a flexible widespread government scheme). Conservation Grade farms supported a quarter higher habitat diversity at the 100-m radius scale compared to Entry Level Stewardship farms. Conservation Grade and organic farms both supported a fifth higher habitat diversity at the 250-m radius scale compared to Entry Level Stewardship farms. Habitat diversity at the 100-m and 250-m scales significantly predicted species richness of butterflies and plants. Habitat diversity at the 100-m scale also significantly predicted species richness of birds in winter and solitary bees. There were no significant relationships between habitat diversity and species richness for bumblebees or birds in summer.Butterfly species richness was significantly higher on organic farms (50% higher) and marginally higher on Conservation Grade farms (20% higher), compared with farms in Entry Level Stewardship. Organic farms supported significantly more plant species than Entry Level Stewardship farms (70% higher) but Conservation Grade farms did not (10% higher). There were no significant differences between the three schemes for species richness of bumblebees, solitary bees or birds. Policy implications . The wildlife-friendly farming schemes which included compulsory changes in management, Conservation Grade and organic, were more effective at increasing local habitat diversity and species richness compared with the less

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

NASA Astrophysics Data System (ADS)

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).

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

PubMed

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

Treesearch

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...

Comparison between two meshless methods based on collocation technique for the numerical solution of four-species tumor growth model

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Mohammadi, Vahid

2017-03-01

As is said in [27], the tumor-growth model is the incorporation of nutrient within the mixture as opposed to being modeled with an auxiliary reaction-diffusion equation. The formulation involves systems of highly nonlinear partial differential equations of surface effects through diffuse-interface models [27]. Simulations of this practical model using numerical methods can be applied for evaluating it. The present paper investigates the solution of the tumor growth model with meshless techniques. Meshless methods are applied based on the collocation technique which employ multiquadrics (MQ) radial basis function (RBFs) and generalized moving least squares (GMLS) procedures. The main advantages of these choices come back to the natural behavior of meshless approaches. As well as, a method based on meshless approach can be applied easily for finding the solution of partial differential equations in high-dimension using any distributions of points on regular and irregular domains. The present paper involves a time-dependent system of partial differential equations that describes four-species tumor growth model. To overcome the time variable, two procedures will be used. One of them is a semi-implicit finite difference method based on Crank-Nicolson scheme and another one is based on explicit Runge-Kutta time integration. The first case gives a linear system of algebraic equations which will be solved at each time-step. The second case will be efficient but conditionally stable. The obtained numerical results are reported to confirm the ability of these techniques for solving the two and three-dimensional tumor-growth equations.

Cross-species comparison of aCGH data from mouse and human BRCA1- and BRCA2-mutated breast cancers

PubMed Central

2010-01-01

Background Genomic gains and losses are a result of genomic instability in many types of cancers. BRCA1- and BRCA2-mutated breast cancers are associated with increased amounts of chromosomal aberrations, presumably due their functions in genome repair. Some of these genomic aberrations may harbor genes whose absence or overexpression may give rise to cellular growth advantage. So far, it has not been easy to identify the driver genes underlying gains and losses. A powerful approach to identify these driver genes could be a cross-species comparison of array comparative genomic hybridization (aCGH) data from cognate mouse and human tumors. Orthologous regions of mouse and human tumors that are commonly gained or lost might represent essential genomic regions selected for gain or loss during tumor development. Methods To identify genomic regions that are associated with BRCA1- and BRCA2-mutated breast cancers we compared aCGH data from 130 mouse Brca1Δ/Δ;p53Δ/Δ, Brca2Δ/Δ;p53Δ/Δ and p53Δ/Δ mammary tumor groups with 103 human BRCA1-mutated, BRCA2-mutated and non-hereditary breast cancers. Results Our genome-wide cross-species analysis yielded a complete collection of loci and genes that are commonly gained or lost in mouse and human breast cancer. Principal common CNAs were the well known MYC-associated gain and RB1/INTS6-associated loss that occurred in all mouse and human tumor groups, and the AURKA-associated gain occurred in BRCA2-related tumors from both species. However, there were also important differences between tumor profiles of both species, such as the prominent gain on chromosome 10 in mouse Brca2Δ/Δ;p53Δ/Δ tumors and the PIK3CA associated 3q gain in human BRCA1-mutated tumors, which occurred in tumors from one species but not in tumors from the other species. This disparity in recurrent aberrations in mouse and human tumors might be due to differences in tumor cell type or genomic organization between both species. Conclusions The selection

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

PubMed

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

Linking river management to species conservation using dynamic landscape scale models

USGS Publications Warehouse

Freeman, Mary C.; Buell, Gary R.; Hay, Lauren E.; Hughes, W. Brian; Jacobson, Robert B.; Jones, John W.; Jones, S.A.; LaFontaine, Jacob H.; Odom, Kenneth R.; Peterson, James T.; Riley, Jeffrey W.; Schindler, J. Stephen; Shea, C.; Weaver, J.D.

2013-01-01

Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape-scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation.

Comparison of aerosol optical properties above clouds between POLDER and AeroCom models over the South East Atlantic Ocean during the fire season

NASA Astrophysics Data System (ADS)

Peers, F.; Bellouin, N.; Waquet, F.; Ducos, F.; Goloub, P.; Mollard, J.; Myhre, G.; Skeie, R. B.; Takemura, T.; Tanré, D.; Thieuleux, F.; Zhang, K.

2016-04-01

Aerosol properties above clouds have been retrieved over the South East Atlantic Ocean during the fire season 2006 using satellite observations from POLDER (Polarization and Directionality of Earth Reflectances). From June to October, POLDER has observed a mean Above-Cloud Aerosol Optical Thickness (ACAOT) of 0.28 and a mean Above-Clouds Single Scattering Albedo (ACSSA) of 0.87 at 550 nm. These results have been used to evaluate the simulation of aerosols above clouds in five Aerosol Comparisons between Observations and Models (Goddard Chemistry Aerosol Radiation and Transport (GOCART), Hadley Centre Global Environmental Model 3 (HadGEM3), European Centre Hamburg Model 5-Hamburg Aerosol Module 2 (ECHAM5-HAM2), Oslo-Chemical Transport Model 2 (OsloCTM2), and Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS)). Most models do not reproduce the observed large aerosol load episodes. The comparison highlights the importance of the injection height and the vertical transport parameterizations to simulate the large ACAOT observed by POLDER. Furthermore, POLDER ACSSA is best reproduced by models with a high imaginary part of black carbon refractive index, in accordance with recent recommendations.

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

Treesearch

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...

Higher sensitivity and lower specificity in post-fire mortality model validation of 11 western US tree species

USGS Publications Warehouse

Kane, Jeffrey M.; van Mantgem, Phillip J.; Lalemand, Laura; Keifer, MaryBeth

2017-01-01

Managers require accurate models to predict post-fire tree mortality to plan prescribed fire treatments and examine their effectiveness. Here we assess the performance of a common post-fire tree mortality model with an independent dataset of 11 tree species from 13 National Park Service units in the western USA. Overall model discrimination was generally strong, but performance varied considerably among species and sites. The model tended to have higher sensitivity (proportion of correctly classified dead trees) and lower specificity (proportion of correctly classified live trees) for many species, indicating an overestimation of mortality. Variation in model accuracy (percentage of live and dead trees correctly classified) among species was not related to sample size or percentage observed mortality. However, we observed a positive relationship between specificity and a species-specific bark thickness multiplier, indicating that overestimation was more common in thin-barked species. Accuracy was also quite low for thinner bark classes (<1 cm) for many species, leading to poorer model performance. Our results indicate that a common post-fire mortality model generally performs well across a range of species and sites; however, some thin-barked species and size classes would benefit from further refinement to improve model specificity.

Gradient modeling of conifer species using random forests

Treesearch

Jeffrey S. Evans; Samuel A. Cushman

2009-01-01

Landscape ecology often adopts a patch mosaic model of ecological patterns. However, many ecological attributes are inherently continuous and classification of species composition into vegetation communities and discrete patches provides an overly simplistic view of the landscape. If one adopts a nichebased, individualistic concept of biotic communities then it may...

Maximum Likelihood Implementation of an Isolation-with-Migration Model for Three Species.

PubMed

Dalquen, Daniel A; Zhu, Tianqi; Yang, Ziheng

2017-05-01

We develop a maximum likelihood (ML) method for estimating migration rates between species using genomic sequence data. A species tree is used to accommodate the phylogenetic relationships among three species, allowing for migration between the two sister species, while the third species is used as an out-group. A Markov chain characterization of the genealogical process of coalescence and migration is used to integrate out the migration histories at each locus analytically, whereas Gaussian quadrature is used to integrate over the coalescent times on each genealogical tree numerically. This is an extension of our early implementation of the symmetrical isolation-with-migration model for three species to accommodate arbitrary loci with two or three sequences per locus and to allow asymmetrical migration rates. Our implementation can accommodate tens of thousands of loci, making it feasible to analyze genome-scale data sets to test for gene flow. We calculate the posterior probabilities of gene trees at individual loci to identify genomic regions that are likely to have been transferred between species due to gene flow. We conduct a simulation study to examine the statistical properties of the likelihood ratio test for gene flow between the two in-group species and of the ML estimates of model parameters such as the migration rate. Inclusion of data from a third out-group species is found to increase dramatically the power of the test and the precision of parameter estimation. We compiled and analyzed several genomic data sets from the Drosophila fruit flies. Our analyses suggest no migration from D. melanogaster to D. simulans, and a significant amount of gene flow from D. simulans to D. melanogaster, at the rate of ~0.02 migrant individuals per generation. We discuss the utility of the multispecies coalescent model for species tree estimation, accounting for incomplete lineage sorting and migration. © The Author(s) 2016. Published by Oxford University Press, on

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

USGS Publications Warehouse

Zimmermann, N.E.; Edwards, T.C.; Moisen, Gretchen G.; Frescino, T.S.; Blackard, J.A.

2007-01-01

1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

PubMed Central

ZIMMERMANN, N E; EDWARDS, T C; MOISEN, G G; FRESCINO, T S; BLACKARD, J A

2007-01-01

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from

Operational Tree Species Mapping in a Diverse Tropical Forest with Airborne Imaging Spectroscopy.

PubMed

Baldeck, Claire A; Asner, Gregory P; Martin, Robin E; Anderson, Christopher B; Knapp, David E; Kellner, James R; Wright, S Joseph

2015-01-01

Remote identification and mapping of canopy tree species can contribute valuable information towards our understanding of ecosystem biodiversity and function over large spatial scales. However, the extreme challenges posed by highly diverse, closed-canopy tropical forests have prevented automated remote species mapping of non-flowering tree crowns in these ecosystems. We set out to identify individuals of three focal canopy tree species amongst a diverse background of tree and liana species on Barro Colorado Island, Panama, using airborne imaging spectroscopy data. First, we compared two leading single-class classification methods--binary support vector machine (SVM) and biased SVM--for their performance in identifying pixels of a single focal species. From this comparison we determined that biased SVM was more precise and created a multi-species classification model by combining the three biased SVM models. This model was applied to the imagery to identify pixels belonging to the three focal species and the prediction results were then processed to create a map of focal species crown objects. Crown-level cross-validation of the training data indicated that the multi-species classification model had pixel-level producer's accuracies of 94-97% for the three focal species, and field validation of the predicted crown objects indicated that these had user's accuracies of 94-100%. Our results demonstrate the ability of high spatial and spectral resolution remote sensing to accurately detect non-flowering crowns of focal species within a diverse tropical forest. We attribute the success of our model to recent classification and mapping techniques adapted to species detection in diverse closed-canopy forests, which can pave the way for remote species mapping in a wider variety of ecosystems.

No more non-model species: the promise of next generation sequencing for comparative immunology.

PubMed

Dheilly, Nolwenn M; Adema, Coen; Raftos, David A; Gourbal, Benjamin; Grunau, Christoph; Du Pasquier, Louis

2014-07-01

Next generation sequencing (NGS) allows for the rapid, comprehensive and cost effective analysis of entire genomes and transcriptomes. NGS provides approaches for immune response gene discovery, profiling gene expression over the course of parasitosis, studying mechanisms of diversification of immune receptors and investigating the role of epigenetic mechanisms in regulating immune gene expression and/or diversification. NGS will allow meaningful comparisons to be made between organisms from different taxa in an effort to understand the selection of diverse strategies for host defence under different environmental pathogen pressures. At the same time, it will reveal the shared and unique components of the immunological toolkit and basic functional aspects that are essential for immune defence throughout the living world. In this review, we argue that NGS will revolutionize our understanding of immune responses throughout the animal kingdom because the depth of information it provides will circumvent the need to concentrate on a few "model" species. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of methods for determining the numbers and species distribution of coliform bacteria in well water samples.

PubMed

Niemi, R M; Heikkilä, M P; Lahti, K; Kalso, S; Niemelä, S I

2001-06-01

Enumeration of coliform bacteria and Escherichia coli is the most widely used method in the estimation of hygienic quality of drinking water. The yield of target bacteria and the species composition of different populations of coliform bacteria may depend on the method.Three methods were compared. Three membrane filtration methods were used for the enumeration of coliform bacteria in shallow well waters. The yield of confirmed coliform bacteria was highest on Differential Coliform agar, followed by LES Endo agar. Differential Coliform agar had the highest proportion of typical colonies, of which 74% were confirmed as belonging to the Enterobacteriaceae. Of the typical colonies on Lactose Tergitol 7 TTC agar, 75% were confirmed as Enterobacteriaceae, whereas 92% of typical colonies on LES Endo agar belonged to the Enterobacteriaceae. LES Endo agar yielded many Serratia strains, Lactose Tergitol 7 TTC agar yielded numerous strains of Rahnella aquatilis and Enterobacter, whereas Differential Coliform agar yielded the widest range of species. The yield of coliform bacteria varied between methods. Each method compared had a characteristic species distribution of target bacteria and a typical level of interference of non-target bacteria. Identification with routine physiological tests to distinct species was hampered by the slight differences between species. High yield and sufficient selectivity are difficult to achieve simultaneously, especially if the target group is diverse. The results showed that several aspects of method performance should be considered, and that the target group must be distinctly defined to enable method comparisons.

Integrating physiological threshold experiments with climate modeling to project mangrove species' range expansion.

PubMed

Cavanaugh, Kyle C; Parker, John D; Cook-Patton, Susan C; Feller, Ilka C; Williams, A Park; Kellner, James R

2015-05-01

Predictions of climate-related shifts in species ranges have largely been based on correlative models. Due to limitations of these models, there is a need for more integration of experimental approaches when studying impacts of climate change on species distributions. Here, we used controlled experiments to identify physiological thresholds that control poleward range limits of three species of mangroves found in North America. We found that all three species exhibited a threshold response to extreme cold, but freeze tolerance thresholds varied among species. From these experiments, we developed a climate metric, freeze degree days (FDD), which incorporates both the intensity and the frequency of freezes. When included in distribution models, FDD accurately predicted mangrove presence/absence. Using 28 years of satellite imagery, we linked FDD to observed changes in mangrove abundance in Florida, further exemplifying the importance of extreme cold. We then used downscaled climate projections of FDD to project that these range limits will move northward by 2.2-3.2 km yr(-1) over the next 50 years. © 2014 John Wiley & Sons Ltd.

Comparison of Species Sensitivity Distributions Derived from Interspecies Correlation Models to Distributions used to Derive Water Quality Criteria

EPA Science Inventory

Species sensitivity distributions (SSD) require a large number of measured toxicity values to define a chemical’s toxicity to multiple species. This investigation comprehensively evaluated the accuracy of SSDs generated from toxicity values predicted from interspecies correlation...

A Source Area Approach Demonstrates Moderate Predictive Ability but Pronounced Variability of Invasive Species Traits

PubMed Central

Essl, Franz; Dullinger, Stefan

2016-01-01

The search for traits that make alien species invasive has mostly concentrated on comparing successful invaders and different comparison groups with respect to average trait values. By contrast, little attention has been paid to trait variability among invaders. Here, we combine an analysis of trait differences between invasive and non-invasive species with a comparison of multidimensional trait variability within these two species groups. We collected data on biological and distributional traits for 1402 species of the native, non-woody vascular plant flora of Austria. We then compared the subsets of species recorded and not recorded as invasive aliens anywhere in the world, respectively, first, with respect to the sampled traits using univariate and multiple regression models; and, second, with respect to their multidimensional trait diversity by calculating functional richness and dispersion metrics. Attributes related to competitiveness (strategy type, nitrogen indicator value), habitat use (agricultural and ruderal habitats, occurrence under the montane belt), and propagule pressure (frequency) were most closely associated with invasiveness. However, even the best multiple model, including interactions, only explained a moderate fraction of the differences in invasive success. In addition, multidimensional variability in trait space was even larger among invasive than among non-invasive species. This pronounced variability suggests that invasive success has a considerable idiosyncratic component and is probably highly context specific. We conclude that basing risk assessment protocols on species trait profiles will probably face hardly reducible uncertainties. PMID:27187616

A Source Area Approach Demonstrates Moderate Predictive Ability but Pronounced Variability of Invasive Species Traits.

PubMed

Klonner, Günther; Fischer, Stefan; Essl, Franz; Dullinger, Stefan

2016-01-01

The search for traits that make alien species invasive has mostly concentrated on comparing successful invaders and different comparison groups with respect to average trait values. By contrast, little attention has been paid to trait variability among invaders. Here, we combine an analysis of trait differences between invasive and non-invasive species with a comparison of multidimensional trait variability within these two species groups. We collected data on biological and distributional traits for 1402 species of the native, non-woody vascular plant flora of Austria. We then compared the subsets of species recorded and not recorded as invasive aliens anywhere in the world, respectively, first, with respect to the sampled traits using univariate and multiple regression models; and, second, with respect to their multidimensional trait diversity by calculating functional richness and dispersion metrics. Attributes related to competitiveness (strategy type, nitrogen indicator value), habitat use (agricultural and ruderal habitats, occurrence under the montane belt), and propagule pressure (frequency) were most closely associated with invasiveness. However, even the best multiple model, including interactions, only explained a moderate fraction of the differences in invasive success. In addition, multidimensional variability in trait space was even larger among invasive than among non-invasive species. This pronounced variability suggests that invasive success has a considerable idiosyncratic component and is probably highly context specific. We conclude that basing risk assessment protocols on species trait profiles will probably face hardly reducible uncertainties.

Dynamic models for problems of species occurrence with multiple states

USGS Publications Warehouse

MacKenzie, D.I.; Nichols, J.D.; Seamans, M.E.; Gutierrez, R.J.

2009-01-01

Recent extensions of occupancy modeling have focused not only on the distribution of species over space, but also on additional state variables (e.g., reproducing or not, with or without disease organisms, relative abundance categories) that provide extra information about occupied sites. These biologist-driven extensions are characterized by ambiguity in both species presence and correct state classification, caused by imperfect detection. We first show the relationships between independently published approaches to the modeling of multistate occupancy. We then extend the pattern-based modeling to the case of sampling over multiple seasons or years in order to estimate state transition probabilities associated with system dynamics. The methodology and its potential for addressing relevant ecological questions are demonstrated using both maximum likelihood (occupancy and successful reproduction dynamics of California Spotted Owl) and Markov chain Monte Carlo estimation approaches (changes in relative abundance of green frogs in Maryland). Just as multistate capture?recapture modeling has revolutionized the study of individual marked animals, we believe that multistate occupancy modeling will dramatically increase our ability to address interesting questions about ecological processes underlying population-level dynamics.

Computational Software to Fit Seismic Data Using Epidemic-Type Aftershock Sequence Models and Modeling Performance Comparisons

NASA Astrophysics Data System (ADS)

Chu, A.

2016-12-01

Modern earthquake catalogs are often analyzed using spatial-temporal point process models such as the epidemic-type aftershock sequence (ETAS) models of Ogata (1998). My work implements three of the homogeneous ETAS models described in Ogata (1998). With a model's log-likelihood function, my software finds the Maximum-Likelihood Estimates (MLEs) of the model's parameters to estimate the homogeneous background rate and the temporal and spatial parameters that govern triggering effects. EM-algorithm is employed for its advantages of stability and robustness (Veen and Schoenberg, 2008). My work also presents comparisons among the three models in robustness, convergence speed, and implementations from theory to computing practice. Up-to-date regional seismic data of seismic active areas such as Southern California and Japan are used to demonstrate the comparisons. Data analysis has been done using computer languages Java and R. Java has the advantages of being strong-typed and easiness of controlling memory resources, while R has the advantages of having numerous available functions in statistical computing. Comparisons are also made between the two programming languages in convergence and stability, computational speed, and easiness of implementation. Issues that may affect convergence such as spatial shapes are discussed.

INVASIVE SPECIES: PREDICTING GEOGRAPHIC DISTRIBUTIONS USING ECOLOGICAL NICHE MODELING

EPA Science Inventory

Present approaches to species invasions are reactive in nature. This scenario results in management that perpetually lags behind the most recent invasion and makes control much more difficult. In contrast, spatially explicit ecological niche modeling provides an effective solut...

Application of Biotic Ligand and Toxic Unit modeling approaches to predict improvements in zooplankton species richness in smelter-damaged lakes near Sudbury, Ontario.

PubMed

Khan, Farhan R; Keller, W Bill; Yan, Norman D; Welsh, Paul G; Wood, Chris M; McGeer, James C

2012-02-07

Using a 30-year record of biological and water chemistry data collected from seven lakes near smelters in Sudbury (Ontario, Canada) we examined the link between reductions of Cu, Ni, and Zn concentrations and zooplankton species richness. The toxicity of the metal mixtures was assessed using an additive Toxic Unit (TU) approach. Four TU models were developed based on total metal concentrations (TM-TU); free ion concentrations (FI-TU); acute LC50s calculated from the Biotic Ligand Model (BLM-TU); and chronic LC50s (acute LC50s adjusted by metal-specific acute-to-chronic ratios, cBLM-TU). All models significantly correlated reductions in metal concentrations to increased zooplankton species richness over time (p < 0.01) with a rank based on r(2) values of cBLM-TU > BLM-TU = FI-TU > TM-TU. Lake-wise comparisons within each model showed that the BLM-TU and cBLM-TU models provided the best description of recovery across all seven lakes. These two models were used to calculate thresholds for chemical and biological recovery using data from reference lakes in the same region. A threshold value of TU = 1 derived from the cBLM-TU provided the most accurate description of recovery. Overall, BLM-based TU models that integrate site-specific water chemistry-derived estimates of toxicity offer a useful predictor of biological recovery.

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