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1,042 results for “model species”
Shear strength characterization and statistical modelling of 12 hardwood timber species from the Congo Basin
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Data from: Too much of a good thing? Supplementing current species observations with fossil data to assess climate change vulnerability via ecological niche models
<p>Ecological niche models (ENMs) are a powerful tool in ecological research and conservation planning. Since ENMs provide probability maps of suitable areas under environmental change, they may assist in designing conservation actions and addressing conservation priorities. However, ENMs are usually implemented by learning the species climatic preferences from their current geographic distribution, which leaves them vulnerable to the issue of niche truncation issues, as if comes with non-climatic limits to the current species distribution posed by e.g. anthropic activities and settlements, and is bound to assume that species are at equilibrium with their environments. These problems might be alleviated by the inclusion of fossil occurrences, which refer to moments during species evolution when such limits were absent, and a larger fraction of the species fundamental niche was probably explored. Here, we combined current and fossil occurrence data for 38 medium-large mammal species of conservation concern to assess the influence of the fossil record on ENM predictions under future climate change scenarios. We found that ignoring or including fossil data yields consistent trends in terms of predicted range increase/decrease. Yet, although adding fossil data invariably results in increased niche width, estimates of range change magnitude improved for just one half only of the species. These results suggest that most species might be in non-equilibrium with their environment, and that the inclusion of fossil data may be crucial to the better understanding of species climatic requirements, hence for designing effective conservation strategies. </p>
3D model of a small piece of Baltic amber (KM 8) containing four different ant species.
<p>Video S1 of 3D model of a small piece of Baltic amber (KM 8) containing four different ant species. S<span><span><span>pecimen is kept in the collection </span></span><span><span>of the Kaliningrad Amber Museum, Kaliningrad, Russia</span></span></span></p>
Data from: Climatically robust multi-scale species distribution models to support pronghorn recovery in California
<p>We combined two climate-based distribution models with three finer-scale suitability models to identify habitat for pronghorn recovery in California now and into the future.</p> <p>Location: California, United States </p> <p>Methods: We used a consensus approach to identify areas of suitable climate now (1980-2010) and future (2031-2060) for pronghorn in California. We compared the results of models from two separate hypotheses about their historical ecology in the state, specifically the migration hypothesis and the niche reduction hypothesis. We combined occurrences from GPS collars distributed across three populations of pronghorn in the state to create three distinct habitat models: (1) an ensemble model using Random Forests, Maxent, Classification and Regression Trees, and a Generalized Linear Model; (2) a step selection function; and (3) an expert-driven model. We evaluated consensus among both the climate models and the suitability models to prioritize areas for, and evaluate the prospects of, pronghorn recovery. </p> <p>Results: Climate suitability for pronghorn in the future depends heavily on model assumptions. Under the migration hypothesis, our model predicted that there will be on suitable climate in California in the future. Under the niche reduction hypothesis, by contrast, suitable climate will expand. Habitat also depended on the methods used, but areas of consensus among all three exist in large patches throughout the state.</p> <p>Main Conclusions: Identifying habitat for a species which has undergone extreme range collapse, and which has very fine scale habitat needs, presents novel challenges for spatial ecologists. Our multi-method, multi-hypothesis approach can allow habitat modelers to identify areas of consensus and, perhaps more importantly, critical knowledge gaps that could resolve disagreements among the models. For pronghorn, a better understanding of their upper thermal tolerances and whether historical populations migrated will be crucial to their potential recovery in California and throughout the arid Southwest.</p>
Mapping shallow groundwater solute footprints in arid regions using a hydrologically enhanced species distribution model
<p>The topography-only SDM of shallow groundwater and deep groundwater, the final models-SDM maps of shallow groundwater, their improvements, the original dataset of water chemistry, and the related R script in the study are available here</p>
Fig. 2 in Phylogeography and potential glacial refugia of terrestrial gastropod Faustina faustina (Rossmässler, 1835) (Gastropoda: Eupulmonata: Helicidae) inferred from molecular data and species distribution models
Fig. 2 Haplotype distribution for nuclear markers: ITS-2 (left) and 28S rRNA (right)
Physiological parameters for four fish species (rainbow trout, zebra fish, fathead minnow and three-spined stickleback) as the basis for the development of generic physiologically-based kinetic models
<p>This excel file (DOI: 10.5281/zenodo.1414332) provides physiological parameters and their inter-individual variability (mean, coefficient of variation, sample size) for four fish species: rainbow trout (<em>Onchorhynchus mykiss</em>), zebrafish (<em>Danio rerio</em>), fathead minnow (<em>Pimephales promelas</em>), and three-spined stickleback (<em>Gasterosteus aculeatus</em>). These physiological parameters were estimated based on the results of extensive literature searches and specific experimental data described in Grech et al., (2018). </p> <p>This file is associated with R codes (DOI: 10.5281/zenodo.1414332) for generic PB-K models, partition coefficient Quantitative Structure Activity Relationship (QSAR) models for each fish species and parameterisation of model for males and females of each species separately.</p> <p>The full data collection and implementation of the models using case studies are described in Grech et al., 2018 (<a href="https://doi.org/10.1016/j.scitotenv.2018.09.163">https://doi.org/10.1016/j.scitotenv.2018.09.163</a>)</p>
New Zealand native forest plant cover data for Popovic et al. MEE (2019), Untangling direct species associations from indirect mediator species effects with graphical models.
<p>Forest cover measurements were collected at 1246 native forest sites that form part of a network of permanent 20 x 20 m plots spread throughout New Zealand. A total of 1831 plant species were present in these plots, with the most common being herbs, graminoids, ferns, shrubs and trees. Plant cover (in ordinal categories) was assessed for each species in several tiers at different heights. The cover data we analysed (<em>NZ_native_forest_cover.csv) </em>were the maximum cover recorded over all the tiers at the 964 sites identified as native forests, containing 1311 species with at least one presence. <em>NZ_native_forest_species.csv</em> contains species data including species name, exotic/native, and plant type (tree, shrub, etc.), corresponding to the plant species in the columns of <em>NZ_native_forest_cover.csv</em>.</p> <p>We acknowledge the use of data drawn from the Natural Forest plot data collected between January 2002 and March 2007 by the LUCAS programme for the Ministry for the Environment, New Zealand.</p> <p> </p>
Datasets associated with: Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography
<p>Data associated with the paper 'Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography' by Lembrechts JJ et al., published in Global Ecology and Biogeography.</p> <p>Contains a dataset containing all extracted and measured temperature variables for all 106 measurement plots (climatedata), as well as the climate and species data used in the Species Distribution Models (SDMs). </p> <p>For details on the content of the table, see the readme-file, for details on methodology, see the original paper. </p>
РИС. 10. Относительная ваЖность предикторов для моделей распространения Brephulopsis.cylindrica. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 10. Относительная ваЖность предикторов для моделей распространения Brephulopsis.cylindrica.
РИС. 7. Пригодность местообитаний для Xeropicta derbentina согласно ансамблевой модели. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 7. Пригодность местообитаний для Xeropicta derbentina согласно ансамблевой модели.
Species functional data and species distribution model projections for future land-use and fire management scenarios in the Transboundary Biosphere Reserve Gerês-Xurés
<p>The data includes nine functional traits and species distribution model projections for 102 species of vertebrates (amphibians, birds, and reptiles) in the Transboundary Biosphere Reserve Gerês-Xurés. The model projections are available for 2050 under six different land-use and fire management scenarios, namely two land-use scenarios of “business-as-usual” (BAU; ongoing trends of land abandonment) and “High Nature Value farmlands” (HNV), each under three fire management scenarios (low suppression - LS, current fire suppression - CS, and high fire suppression - HS). The species distribution projections for each scenario are presented as matrices of species presences/absences, obtained after reclassifying consensus predictions of species distribution models.</p>
Data from: Resolving relationships and phylogeographic history of the Nyssa sylvatica complex using data from RAD-seq and species distribution modeling
Nyssa sylvatica complex consists of several woody taxa occurring in eastern North America. These taxa were recognized as two or three species including three or four varieties by different authors. Due to high morphological similarities and complexity of morphological variation, classification and delineation of taxa in the group have been difficult and controversial. Here we employ data from RAD-seq to elucidate the genetic structure and phylogenetic relationships within the group. Using the genetic evidence, we evaluate previous classifications and delineate species. We also employ Species Distribution Modeling (SDM) to evaluate impacts of climatic changes on the ranges of the taxa and to gain insights into the relevant refugia in eastern North America. Results from Molecular Variance Analysis (AMOVA), STRUCTURE, phylogenetic analyses using Maximum likelihood, Bayesian Inference, and Splittree methods of RAD-seq data strongly support a two-clade pattern, largely separating samples of N. sylvatica from those of N. biflora-N. ursina mix. Divergence time analysis with BEAST suggests the two clades diverged in the mid Miocene. The ancestor of the present trees of N. sylvatica was suggested to be in the Pliocene and that of N. biflora-N. ursina mix in the end of the Miocene. Results from SDM predicted a smaller range in the southern part of the species present range of each clade during the Last Glacial Maximum (LGM). A northward expansion of the ranges during interglacial period and a northward shift of the ranges in the future under a model of global warming were also predicted. Our results support the recognition of two species in the complex, N. sylvatica and N. biflora, following the phylogenetic species concept. We found no genetic evidence supporting recognitions of intraspecific taxa. However, we propose subsp. ursina and subsp. biflora within N. biflora due to their distinction in habits, distributions, and habitats. Our results further support movements of trees in eastern North America in response to climatic changes. Finally, our study demonstrates that RAD-seq data and a combination of population genomics and SDM are valuable in resolving relationship and biogeographic history of closely related species that are taxonomically difficult.
A greenhouse experiment partially supports inferences of ecogeographic isolation from niche models of Clarkia sister species
<p><b>Premise: </b>Ecogeographic isolation, or geographic isolation caused by ecological divergence, is thought to be of primary importance in speciation, yet is difficult to demonstrate and quantify. To determine whether distributions are limited by divergent adaptation or historical contingency, the gold standard is to reciprocally transplant taxa between their geographic ranges. Alternatively, ecogeographic isolation is inferred from species distribution models and niche divergence tests based on widely available environmental and occurrence data.</p> <p><b>Methods: </b>We test for ecogeographic isolation between two sister species of California annual wildflowers, <i>Clarkia concinna</i> and <i>C. breweri</i>, with a hybrid approach. We use niche models to predict water availability as the major axis of ecological divergence and then test that with a greenhouse experiment. Specifically, we manipulate water availability in field soils for two populations of each species and predict higher fitness in conditions representing home habitats to those representing the environment of each's sister species.</p> <p><b>Key Results: </b>Water availability and soil representing <i>C. concinna</i> generally increased both species' fitness. Thus, water and soil may indeed limit <i>C. concinna</i> from colonizing the range of C. breweri, but not vice versa. We suggest that the competitive environment and pollinator availability, which are not directly captured with either approach, may be key biotic factors correlated with climate that contribute to unexplained ecogeographic isolation for <i>C. breweri</i>.</p> <p><b>Conclusions:</b> Ours is a valuable approach to assessing ecogeographic isolation, in that it balances feasibility with model validation, and our results have implications for species distribution modeling efforts geared towards predicting climate change responses.</p>
Potential distributional shifts in North America of allelopathic invasive plant species under climate change models
<p>Occurrence data for invaive species used in ecological niche modeling for predictive studies. These data are cleaned to removed data with duplicates, incomplete coordinates, unlikely coordinates (e.g., 0,0), or those lacking environmental data were removed using the scrubr v.0.1.1 package in R (Chamberlain, 2016). Points falling outside of the respective training region for each species were also removed. These data represent downloads from iDigBio and GBIF.</p>
Data from: Genomic data and multi-species demographic modelling uncover past hybridization between currently allopatric freshwater species
<p>Evidence for ancient interspecific gene flow through hybridization has been reported in many animal and plant taxa based on genetic markers. The study of genomic patterns of closely related species with allopatric distributions allows the assessment of the relative importance of vicariant isolating events and past gene flow. Here, we investigated the role of gene flow in the evolutionary history of four closely related freshwater fish species with currently allopatric distributions in western Iberian rivers - Squalius carolitertii, S. pyrenaicus, S. torgalensis and S. aradensis - using a population genomics dataset of 23 562 SNPs from 48 individuals, obtained through genotyping by sequencing (GBS). We uncovered a species tree with two well differentiated clades: (i) S. carolitertii and S. pyrenaicus; and (ii) S. torgalensis and S. aradensis. By using D-statistics and demographic modelling based on the site frequency spectrum, comparing alternative demographic scenarios of hybrid origin, secondary contact and isolation, we found that the S. pyrenaicus North lineage is likely the result of an ancient hybridization event between S. carolitertii (contributing ~84%) and S. pyrenaicus South lineage (contributing ~16%), consistent with a hybrid speciation scenario. Furthermore, in the hybrid lineage we identify outlier loci potentially affected by selection favouring genes from each parental lineage at different genomic regions. Our results suggest that ancient hybridization can affect speciation and that freshwater fish species currently in allopatry are useful to study these processes.</p>
STonKGs Species Model
<p>The fine-tuned model trained on species annotations.</p>
Analytic dataset informing modeling of winter species distributions of North American bat species
<p>The fungal pathogen <i>Pseudogymnoascus destructans</i> and resultant white-nose syndrome (WNS) continues to advance across North America, infecting new bat populations, species, and hibernacula. Western North America hosts the highest bat diversity in the U.S. and Canada, yet little is known about hibernacula and hibernation behavior in this region. An improved understanding of where bats hibernate and the conditions that create suitable hibernacula is critical if land managers are to anticipate and address the conservation needs of WNS-susceptible species in regions yet to be infected. We estimated suitability of potential winter hibernaculum sites across the ranges of five bat species occurring in western North America. We estimated winter survival capacity from a mechanistic survivorship model based on bat bioenergetics and climate conditions. Leveraging the Google Earth Engine platform for spatial data processing, we used boosted regression trees to relate these estimates, along with key landscape attributes, to bat occurrence data in a hybrid correlative-mechanistic approach. Winter survival capacity, topography, land cover, and access to caves and mines were important predictors of winter hibernaculum selection, but the shape and relative importance of these relationships varied among species. This suggests that the occurrence of bat hibernacula can, in part, be predicted from readily mapped above-ground features, and is not only dictated by below-ground characteristics for which spatial data are lacking. Furthermore, our mechanistic estimate of winter survivorship was, on average, the third strongest predictor of winter occurrence probability across focal species. Winter distributions of North American bat species were driven by their physiological capacity to survive winter conditions and duration in a given location, as well as selection for topographic and other landscape features, but in species-specific ways. The influence of winter survivorship on several species' distributions, the underlying influence of climate conditions on winter survivorship, and the anticipated influence of WNS on bats' hibernation physiology and survivorship together suggest that North American bat distributions may undergo future shifts as these species are exposed to not only WNS, but climate change. We anticipate that the models presented here may offer a valuable baseline for assessing the potential species-level impacts of these stressors.</p>
Challenges and opportunities of species distribution modelling of terrestrial arthropod predators
<p>Aim. Species distribution models (SDMs) have emerged as essential tools in the equipment of many ecologists, useful to explore species distributions in space and time and answering an assortment of questions related to biogeography, climate change biology and conservation biology. Historically, most SDM research concentrated on well-known organisms, especially vertebrates. In recent years, these tools are becoming increasingly important for predicting the distribution of understudied invertebrate taxa. Here, we reviewed the literature published on main terrestrial arthropod predators (ants, ground beetles and spiders) to explore some of the challenges and opportunities of species distribution modelling in mega-diverse arthropod groups. Location. Global. Methods. Systematic mapping of the literature and bibliometric analysis. Results. Most SDM studies of animals to date have focused either on broad samples of vertebrates or on arthropod species that are charismatic (e.g. butterflies) or economically important (e.g. vectors of disease, crop pests and pollinators). We show that the use of SDMs to map the geography of terrestrial arthropod predators is a nascent phenomenon, with a near-exponential growth in the number of studies over the past 10 years and still limited collaborative networks among researchers. There is a bias in studies towards charismatic species and geographical areas that hold lower levels of diversity but greater availability of data, such as Europe and North America. Conclusions. Arthropods pose particular modelling challenges that add to the ones already present for vertebrates, but they should also offer opportunities for future SDM research as data and new methods are made available. To overcome data limitations, we illustrate the potential of modern data sources and new modelling approaches. We discuss areas of research where SDMs may be combined with dispersal models and increasingly available phylogenetic and functional data to understand evolutionary changes in ranges and range-limiting traits over past and contemporary time scales.</p>
Bayesian species distribution models integrate presence-only and presence-absence data to predict deer distribution and relative abundance
<p>Using geospatial data of wildlife presence to predict a species distribution across a geographic area is among the most common tools in management and conservation. The collection of high-quality presence-absence data through structured surveys is, however, expensive, and managers usually have access to larger amounts of low-quality presence-only data collected by citizen scientists, opportunistic observations, and culling returns for game species. Integrated Species Distribution Models (ISDMs) have been developed to make the most of the data available by combining the higher-quality, but usually scarcer and more spatially restricted presence-absence data, with the lower quality, unstructured, but usually more extensive presence-only datasets. Joint-likelihood ISDMs can be run in a Bayesian context using INLA (Integrated Nested Laplace Approximation) methods that allow the addition of a spatially structured random effect to account for data spatial autocorrelation. Here, we apply this innovative approach to fit ISDMs to empirical data, using presence-absence and presence-only data for the three prevalent deer species in Ireland: red, fallow and sika deer. We collated all deer data available for the past 15 years and fitted models predicting distribution and relative abundance at a 25 km<sup>2</sup> resolution across the island. Models' predictions were associated to spatial estimates of uncertainty, allowing us to assess the quality of the model and the effect that data scarcity has on the certainty of predictions. Furthermore, we checked the performance of the three species-specific models using two datasets, independent deer hunting returns and deer densities based on faecal pellet counts. Our work clearly demonstrates the applicability of spatially-explicit ISDMs to empirical data in a Bayesian context, providing a blueprint for managers to exploit unexplored and seemingly unusable data that can, when modelled with the proper tools, serve to inform management and conservation policies.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.