Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
299
datasets available to search
ShareScore release 0.9.0
Dataset results
299 results for “niche models”
Data from: Occurrence-habitat mismatching and niche truncation when modelling distributions affected by anthropogenic range contractions
Open the record for dataset details and reuse information.
Global climate model comparisons of niche evolution in Turritelline gastropods across the end-Cretaceous mass extinction
Open the record for dataset details and reuse information.
Data from: Postglacial recolonization of North America by spadefoot toads: integrating niche and corridor modeling to study species' range dynamics over geologic time
<p>Understanding the factors that shape species' distributions is a key topic in biogeography. As climates change, species can either cope with these changes through evolution, plasticity or by shifting their ranges to track the optimal climatic conditions. Ecological niche modeling (ENM) is a widespread technique in biogeography that estimates the niche of the organism by using occurrences and environmental data to estimate species' potential distributions. ENMs are often criticized for failing to take species' dispersal abilities into consideration. Here, we attempt to fill this gap by combining ENMs with dispersal and corridor modeling to study the range dynamics of North American spadefoot toads (Scaphiopodidae) over the Holocene. We first estimated the current and past distributions of spadefoot toads and then estimated their past distributions from the Last Glacial Maximum (LGM) to the present day. Then, we estimated how each taxon recolonized North American by using dispersal and corridor modeling. By combining these two modeling approaches we were able to 1) estimate the LGM refugia used by the North American spadefoot toads, 2) further refine these projections by estimating which of the putative LGM refugia contributed to the recolonization of North America via dispersal, and 3) estimate the relative influence of each LGM refugium to the current species' distributions. The models were tested using previously published phylogeographic data, revealing a high degree of congruence between our models and the genetic data. These results suggest that combining ENMs and dispersal modeling over time is a promising approach to investigate both historical and future species' range dynamics.</p>
Genetic data improves niche model discrimination and alters the direction and magnitude of climate change forecasts
<p>Ecological niche models (ENMs) have classically operated under the simplifying assumptions that there are no barriers to gene flow, species are genetically homogeneous (i.e., no population-specific local adaptation), and all individuals share the same niche. Yet, these assumptions are violated for most broadly distributed species. Here we incorporate genetic data from the widespread riparian tree species narrowleaf cottonwood (<i>Populus angustifolia</i>) to examine whether including intraspecific genetic variation can alter model performance and predictions of climate change impacts. We found that (1) <i>P. angustifolia</i> is differentiated into six genetic groups across its range from México to Canada, and (2) different populations occupy distinct climate niches representing unique ecotypes. Comparing model discriminatory power, (3) all genetically-informed ecological niche models (gENMs) outperformed the standard species-level ENM (3-14% increase in AUC; 1-23% increase in pROC). Furthermore, (4) gENMs predicted large differences among ecotypes in both the direction and magnitude of responses to climate change, and (5) revealed evidence of niche divergence, particularly for the Eastern Rocky Mountain ecotype. (6) Models also predicted progressively increasing fragmentation and decreasing overlap between ecotypes. Contact zones are often hotspots of diversity that are critical for supporting species' capacity to respond to present and future climate change, thus predicted reductions in connectivity among ecotypes is of conservation concern. We further examined the generality of our findings by comparing our model developed for a higher elevation Rocky Mountain species with a related desert riparian cottonwood, <i>P. fremontii</i>. Together our results suggest that incorporating intraspecific genetic information can improve model performance by addressing this important source of variance. gENMs bring an evolutionary perspective to niche modeling and provide a truly "adaptive management" approach to support conservation genetic management of species facing global change.</p>
Integrating univariate niche dynamics in species distribution models: a step forward for marine research on biological invasions
<p>Aim The development of approaches to predict the distribution and potential expansion of invasive species is still an open challenge. Here our goal is to improve the modelling procedure for marine invaders by coupling Species Distribution Models (SDMs) with an analysis of their univariate niche dynamics. In particular, we tested for the first time whether choosing model predictors among the stable niche dimensions was effective in improving predictions of invasive species expansion.<br> Location Mediterranean Sea<br> Taxon Dusky spinefoot, Siganus luridus.<br> Methods We analysed the univariate niche dynamics for S. luridus across its native and invaded ranges, by applying a standardized framework that allowed the identification of cases of niche stability or shift. We compared inter-range transferability of SDMs fitted with different combinations of labile or stable predictors. Finally, we evaluated interactions in SDM settings (calibration area, model technique and predictors set) on models' predictive ability, using independent data from the most recent phase of invasion.<br> Results We detected a pattern of niche stability for several variables, especially salinity and bathymetry, which positively influenced model inter-ranges transferability: when the models calibrated in the native range include only stable niche axes, predictive ability is improved. We also identified a shift toward lower surface temperatures in the introduced range, which were almost never experienced by the species before invasion. The model calibrated within the combined ranges was the most ecologically congruent. Also, models calibrated in the invaded range allowed a correct prediction of range expansion, with the predicted suitable areas only slightly underestimated.<br> Main conclusions We provide the first evidence that using conserved predictors in SDMs improves inter-range projections of expanding invasive species. Variable selection, calibration area and modelling technique all matter when modelling invasive species, with important interaction effects. We provide guidelines on how to improve SDMs applications in biological invasion research.</p>
Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect
<p>Aim</p> <p>Correlative Species Distribution Models (SDMs) are subject to substantial spatio-temporal limitations when historical occurrence records of data-poor species provide incomplete and outdated information for niche modelling. Complementary mechanistic modelling techniques can, therefore, offer a valuable contribution to underpin more physiologically-informed predictions of biological invasions, the risk of which is often exacerbated by climate change. In this study we integrate physiological and human pressure data to address the uncertainties and limitations of correlative SDMs and to better understand, predict, and manage biological invasions.</p> <p>Location</p> <p>Western archipelagos of the Southern Ocean and martime Antarctica</p> <p>Taxon</p> <p>Eretmoptera murphyi (Chironomidae), invertebrates.</p> <p>Methods</p> <p>Mahalanobis Distances were used for correlative SDM construction for a species with few records. A mechanistic SDM was built around different fitness components (larval survival and life stage progression) as a function of temperature. SDM predictions were combined with human activity levels in Antarctica to generate a site vulnerability index to the colonization of E. murphyi. Future scenarios of ecophysiological suitability were built around the warming trends in the region.<br> Results Both SDMs converge to predict high environmental suitability in the species' native and introduced ranges. However, the mechanistic model indicates a slightly larger invasive potential based on larval performance at different temperatures. Human activity levels across the Antarctic Peninsula play a key role in discerning site vulnerabilities. Niche suitability in Antarctica grows considerably under long-term climate scenarios, leading to a substantially higher invasive threat to the Antarctic ecosystems. In turn changing conditions result on growing physiological mismatches with the environment in the native range on South Georgia.</p> <p>Main conclusions</p> <p>Long-term studies of invasion potential under climate benefit from integrating correlative predictions with physiological experiments, as the invasion potential varies depending on the area and the timescale examined. This study also highlights a conservation paradox whereby the accidental introduction of an insect represents a threat to the Antarctic ecoystems that contrasts with its endangered status at the native range.</p>
Supplementary material 1 from: Bustamante RO, Alves L, Goncalves E, Duarte M, Herrera I (2020) A classification system for predicting invasiveness using climatic niche traits and global distribution models: application to alien plant species in Chile. NeoBiota 63: 127-146. https://doi.org/10.3897/neobiota.63.50049
Table S1. Exotic species located in Quadrant 1 (see Figure 3) and impacts on biodiversity, agriculture and cattle raisng
Temporal variability is key to modelling the climatic niche
<p><strong>Aim</strong><i>:</i> Niche-based species distribution models (SDMs) have become a ubiquitous tool in ecology and biogeography. These models relate species occurrences with the environmental conditions found at these sites. Climatic variables are the most commonly used environmental data, and are usually included in SDMs as averages of a reference period (30-50 years). In this study we analyze the impact of including inter-annual climatic variability on the estimation of species niches and predicted distributions when assessing plant demographic response to extreme climatic episodes.</p> <p><strong>Location</strong><i>:</i> Mediterranean basin, SE Iberian Peninsula.</p> <p><strong>Methods</strong><i>:</i> We first characterized species niches with inter-annual and average climate in the same environmental space. We then compare the respective capacities of climatic suitability obtained from averaged climate-based and from inter-annual variability-based niches to explain population demographic responses to extreme drought. Furthermore, we assessed the relative increase in niche size when including climatic variability for a set of Mediterranean species exhibiting a wide range of distribution areas.</p> <p><strong>Results</strong><i>:</i> We found that climatic suitability obtained from inter-annual variability-based niches showed higher explanatory capacity than average climate-based suitability, especially for populations living in climatically marginal conditions, although both niches quantifications significantly explained species demographic responses. In addition, species with restricted distribution ranges increased relatively more their niche space when considering climatic variability, probably because in widely distributed species spatial variability compensates for temporal variability.</p> <p><strong>Main Conclusions</strong><i>:</i> The common use of climatic averages when characterizing species niches could lead to underestimations of species distribution and misunderstanding of demographic behavior, with implications for conservation plans derived from SDMs, e.g. overestimations of species extinction risk under climate change, or underestimations of alien species invasion' risk. We highlight that including climatic variability in niche modelling can be particularly important when dealing with species with restricted distribution and populations at the margin of their species niche.</p>
Data from: Is there a correlation between abundance and environmental suitability derived from ecological niche modelling? A meta-analysis
It is thought that species abundance is correlated with environmental suitability and that environmental variables, scale, and type of model fitting can confound this relationship. We performed a meta-analysis to (i) test whether species abundance is positively correlated with environmental suitability derived from correlative ecological niche models (ENM), (ii) test whether studies encompassing large areas within a species range (>50%) exhibited higher AS correlations than studies encompassing small areas within a species range (<50%), (iii) assess which modelling method provided higher AS correlation, and (iv) compare strength of the AS relationship between studies using only climatic variables and those that used both climatic and other environmental variables to derive suitability. We used correlation coefficients to measure the relationship between abundance and environmental suitability derived from ENM. Each correlation coefficient was considered an effect size in a random-effects multivariate meta-analysis. In all cases we found a significantly positive relationship between abundance and suitability. This relationship was consistent regardless of scale of study, ENM method, or set of variables used to derive suitability. There was no difference in strength of correlation between studies focusing on large or small areas within a species' range or among ENM methods. Studies using other variables in combination with climate exhibited higher AS correlations than studies using only climatic variables. We conclude that occurrence data can be a reasonable proxy for abundance, especially for vertebrates, and the use of local variables increases the strength of the AS relationship. Use of ENMs can significantly decrease survey costs and allow the study of large-scale abundance patterns using less information. Including only climatic variables in ENM may confound the relationship between abundance and suitability when compared to studies including variables taken locally. However, modelers and conservationists must be aware that high environmental suitability does not always indicate high abundance.
Community science validates climate suitability projections from ecological niche modeling
<p><span>Climate change poses an intensifying threat to many bird species, and projections of future climate suitability provide insight into how species may shift their distributions in response. Climate suitability is characterized using ecological niche models (ENMs), which correlate species occurrence data with current environmental covariates and project future distributions using the modeled relationships together with climate predictions. Despite their widespread adoption, ENMs rely on several assumptions that are rarely validated <i>in situ </i>and can be highly sensitive to modeling decisions, precluding their reliability in conservation decision-making. Using data from a novel, large-scale community science program, we developed dynamic occupancy models to validate near-term climate suitability projections for bluebirds and nuthatches in summer and winter. We estimated occupancy, colonization, and extinction dynamics across species' ranges in the United States in relation to projected climate suitability in the 2020s, and used a Gibbs variable selection approach to quantify evidence of species-climate relationships. We also included a Bird Conservation Region strata-level random effect to examine among-strata variation in occupancy that may be attributable to land-use and ecoregional differences. Across species and seasons, we found strong evidence that initial occupancy and colonization were positively related to 2020 climate suitability, illustrating an independent validation of projections from ENMs across a large geographic area. </span><span>Random strata effects revealed that occupancy probabilities were generally higher than average in core areas and lower than average in peripheral areas of species' ranges, and served as a first step in identifying spatial patterns of occupancy from these community science data. </span><span>Our findings lend much-needed support to the use of ENM projections for addressing questions about potential climate-induced changes in species' occupancy dynamics. More broadly, </span>our work highlights the value of community scientist observations for ground-truthing projections from statistical models and for refining our understanding of the processes shaping species' distributions under a changing climate.</p>
Data from: Intraspecific niche models for ponderosa pine (Pinus ponderosa) suggest potential variability in population-level response to climate change.
Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine (Pinus ponderosa), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently-available, geographically-widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently-devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype-climate relationship using a niche-overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.
Data from: Ecological niche modeling as a tool for prediction of the potential geographic distribution of Bacillus anthracis spores in Tanzania
Introduction: Anthrax is caused by the spore-forming, Gram-positive bacterium Bacillus anthracis. The aim of this study was to predict the potential distribution of B. anthracis in Tanzania and produce epidemiological evidence for the management of anthrax outbreaks in the country. Methods: The Maxent algorithm was used to predict areas at risk of anthrax outbreaks based on the occurrence and environmental data in Arusha and Kilimanjaro regions; the model was later transferred to predict the entire country. Seventy percent of the occurrence data were used to train the model, while 30% were used for model evaluation. Results: Four regions of northern Tanzania are predicted to have a high risk for anthrax outbreaks, while the southern and western regions had low-risk areas. Soil type (56.5%), soil pH (23.7%), and isothermally (10.4%) were the most important variables for the model prediction, and the most significant soil types were solonetz, fluvisols, and lithosols. Conclusions: A strong risk level across districts of the Tanzania mainland was identified in this study. A total of 18 districts in Tanzania Mainland are predicted to be at very high risk of an anthrax outbreak occurrence. These findings are important for policymakers to effectively mount targeted control measures for anthrax outbreaks in Tanzania.
Data from: An Appalachian population of neochoristoderes (Diapsida: Choristodera) elucidated through fossil evidence and ecological niche modeling
<p>Four neochoristoderan vertebral centra are described from the latest Cretaceous of New Jersey. One specimen was recovered from the basal transgressive lag of the Navesink Formation in the area of Holmdel Park, New Jersey, and two others were recovered nearby and likely were derived from the same horizon. The fourth was recovered from the Marshalltown sequence in the vicinity of the Ellisdale Dinosaur Site. These vertebrae expand the geographic range of Late Cretaceous neochoristoderes in North America by over 2000 km further east, and represent the first neochoristoderan remains from the Atlantic coastal plain. To discern whether neochoristodere remains are to be expected in New Jersey, and elucidate why neochoristoderes are apparently so rare in Appalachia, we implemented ecological niche modeling to predict the range of suitable habitat for <i>Champsosaurus</i>, the only known genus of Late Cretaceous neochoristoderes. We found that in Appalachia, the ideal habitat of <i>Champsosaurus</i> likely existed slightly further north and west than the Atlantic coastal plain, and New Jersey is likely on or near the margin of this suitable habitat space. These results suggest that the occurrence of neochoristoderes in New Jersey is consistent with the habitat requirements of known Late Cretaceous neochoristoderes. These vertebrae therefore may represent the southern margin of a population of neochoristoderes that lived further inland, where latest Cretaceous sediments are not preserved. The continued recovery of material from Late Cretaceous deposits along the Atlantic coast, and review of existing collections, is encouraged to clarify the true distribution of neochoristoderes in Appalachia.</p>
Data from: Phylogeography and niche modelling of the relict plant Amborella trichopoda (Amborellaceae) reveal multiple Pleistocene refugia in New Caledonia
Amborella trichopoda Baill. (Amborellaceae, Amborellales), the sole living member of the sister group to all other extant Angiosperms, is endemic to New Caledonia. We addressed the intraspecific phylogeography of Amborella by investigating whether its present population genetic structure could be related to its current and past habitats. We found moderate range-wide genetic diversity based on nuclear microsatellite data, and detected four well-differentiated, geographically distinct genetic groups using Bayesian clustering analyses. We modeled the ecological niche of Amborella based on current climatic and environmental conditions. The predictive ability of the model was very good throughout the Central East mainland zone, but Amborella was predicted in the northern part of the island where this plant has not been reported. Furthermore, no significant barrier was detected based on habitat suitability that could explain the genetic differentiation across the area. Conversely, we found that the main genetic clusters could be related to the distribution of suitable habitat at the last glacial maximum (LGM, ca. 21 000 years BP), when Amborella experienced a dramatic 96.5% reduction in suitable area. At least two lineages survived in distinct putative refugia located in the Massif des Lèvres and in the vicinity of Mount Aoupinié. Our findings finally confirmed the importance of LGM rainforest refugia in shaping the current intra- and inter-specific diversity in New Caledonian plants, and revealed the possibility of an as-yet unreported refugium. The combination of niche modelling and population genetics thereby offered novel insight into the biogeographic history of an emblematic taxon.
Do selfing species have greater niche breadth? Support from ecological niche modeling
<p>We explore the relationship between plant mating system (selfing or outcrossing) and niche breadth to gain new insights into processes that drive species distributions. Using a comparative approach with highly selfing versus highly outcrossing sister species, we test the extent to which: (1) species pairs have evolved significant niche divergence and less niche overlap, (2) selfers have wider niche breadths than outcrossers or vice versa, and (3) niches of selfers and outcrossers are defined by significant differences in environmental variables. We applied predictive ecological niche modeling approaches to estimate and contrast niche divergence, overlap and breadth, and to identify key environmental variables associated with each species' niche for seven sister species with divergent mating systems. Data from 4862 geo-referenced herbarium occurrence records were compiled for 14 species in Collinsia and Tonella (Plantaginaceae) and 19 environmental variables associated with each record. We found sister species display significant niche divergence, though not as a function of divergence time, and overall, selfers have significantly wider niche breadths compared to their outcrossing sisters. Our results suggest that a selfing mating system likely contributes to the greater capacity to reach, reproduce, establish, and adapt to new habitats, which increases niche breadth of selfers.</p>
Data from: Ecological niche modelling for conservation planning of an endemic snail in the verge of becoming a pest in cardamom plantations in the Western Ghats biodiversity hotspot
Conservation managers and policy makers are often confronted with a challenging dilemma of devising suitable strategies to maintain agricultural productivity while conserving endemic species that at the early stages of becoming pests of agricultural crops. Identification of environmental factors conducive to species range expansion for forecasting species distribution patterns will play a central role in devising management strategies to minimize the conflict between the agricultural productivity and biodiversity conservation. Here, we present results of a study that predicts the distribution of Indrella ampulla, a snail endemic to the Western Ghats biodiversity hotspot, which is becoming a pest in cardamom (Ellettaria cardamomum) plantations. We determined the distribution patterns and niche overlap between I. ampulla and Ellettaria cardamomum using maximum entropy (MaxEnt) niche modeling techniques under current and future (2020–2080) climatic scenarios. The results showed that climatic (precipitation of coldest quarter and isothermality) and soil (cation exchange capacity of soil [CEC]) parameters are major factors that determine the distribution of I. ampulla in Western Ghats. The model predicted cardamom cultivation areas in southern Western Ghats are highly sensitive to invasion of I. ampulla under both present and future climatic conditions. While the land area in the central Western Ghats is predicted to become unsuitable for I. ampulla and Ellettaria cardamomum in future, we found 71% of the Western Ghats land area is suitable for Ellettaria cardamomum cultivation and 45% suitable for I. ampulla, with an overlap of 35% between two species. The resulting distribution maps are invaluable for policy makers and conservation managers to design and implement management strategies minimizing the conflicts to sustain agricultural productivity while maintaining biodiversity in the region.
Data from: Correlation between genetic diversity and environmental suitability: taking uncertainty from ecological niche models into account
The hindcast of shifts in the geographical ranges of species as estimated by ecological niche modelling (ENM) has been coupled with phylogeographical patterns, allowing the inference of past processes that drove population differentiation and genetic variability. However, more recently, some studies have suggested that maps of environmental suitability estimated by ENM may be correlated to species' abundance, raising the possibility of using environmental suitability to infer processes related to population demographic dynamics and genetic variability. In both cases, one of the main problems is that there is a wide variation in ENM development methods and climatic models. In this study, we analyse the relationship between heterozygosity (He) and environmental suitability from multiple ENMs for 25 population estimates for Dipteryx alata, a widely distributed, endemic tree species of the Cerrado region of central Brazil. We propose a new approach for generating a statistical distribution of correlations under randomly generated ENM. The confidence intervals from these distributions indicate how model selection with different properties affects the ability to detect a correlation of interest (e.g. the correlation between He and suitability). Additionally, our approach allows us to explore which particular ensemble of ENMs produces the better result for finding an association between environmental suitability and He. Caution is necessary when choosing a method or a climatic data set for modelling geographical distributions, but the new approach proposed here provides a conservative way to evaluate the ability of ensembles to detect patterns of interest.
Data from: Ecological niche modeling for a cultivated plant species: a case study on taro (Colocasia esculenta) in Hawai'i
Under the threat of ongoing and projected climate change, communities in the Pacific Islands face challenges of adapting culture and lifestyle to accommodate a changing landscape. Few models can effectively predict how biocultural livelihoods might be impacted. Here, we examine how environmental and anthropogenic factors influence an ecological niche model (ENM) for the realized niche of cultivated taro (Colocasia esculenta) in Hawai'i. We created and tuned two sets of ENMs: one using only environmental variables, and one using both environmental and cultural characteristics of Hawa'i. These models were projected under two different Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) for 2070. Models were selected and evaluated using average omission rate and area under the receiver operating characteristic curve (AUC). We compared optimal model predictions by comparing the percentage of taro plots predicted present and measured ENM overlap using Schoener's D-statistic. The model including only environmental variables consisted of 19 Worldclim bioclimatic variables, in addition to slope, altitude, distance to perennial streams, soil evaporation, and soil moisture. The optimal model with environmental variables plus anthropogenic features also included a road density variable (which we assumed as a proxy for urbanization) and a variable indicating agricultural lands of importance to the State of Hawai'i. The model including anthropogenic features performed better than the environment-only model based on omission rate, AUC, and review of spatial projections. The two models also differed in spatial projections for taro under anticipated future climate change. Our results demonstrate how ENMs including anthropogenic features can predict which areas might be best suited to plant cultivated species in the future, and how these areas could change under various climate projections. These predictions might inform biocultural conservation priorities and initiatives. In addition, we discuss the incongruences that arise when traditional ENM theory is applied to species whose distribution has been significantly impacted by human intervention, particularly at a local scale relevant to biocultural conservation initiatives.
Data from: A test of the central-marginal hypothesis using population genetics and ecological niche modelling in an endemic salamander (Ambystoma barbouri)
The central-marginal hypothesis (CMH) predicts that population size, genetic diversity, and genetic connectivity are highest at the core and decrease near the edges of species' geographic distributions. We provide a test of the CMH using three replicated core-to-edge transects that encompass nearly the entire geographic range of the endemic streamside salamander (Ambystoma barbouri). We confirmed that the mapped core of the distribution was the most suitable habitat using ecological niche modelling (ENM) and via genetic estimates of effective population sizes. As predicted by the CMH, we found statistical support for decreased genetic diversity, effective population size, and genetic connectivity from core to edge in western and northern transects, yet not along a southern transect. Based on our niche model, habitat suitability is lower towards the southern range edge, presumably leading to conflicting core-to-edge genetic patterns. These results suggest that multiple processes may influence a species' distribution based on the heterogeneity of habitat across a species' range and that replicated sampling may be needed to accurately test the CMH. Our work also emphasizes the importance of identifying the geographic range core with methods other than using the Euclidean center on a map, which may help to explain discrepancies among other empirical tests of the CMH. Assessing core to edge population genetic patterns across an entire species' range accompanied with ENM can inform our general understanding of the mechanisms leading to species' geographic range limits.
Data from: Environmental filtering improves ecological niche models across multiple scales
1. A clear challenge for ecological niche modeling is determining how to best mitigate the effects of sampling bias from commonly collected biodiversity data. Recent approaches have focused on filtering occurrences in overrepresented regions based on geographic or environmental proximity. 2. We tested the efficacy of filtering in geographic and environmental space using occurrence data from four species. Our evaluation strategies examined 14 distance measures in geographic and environmental spaces and eight combinations of environmental variables and their ordinations. This resulted in 78 datasets for each species, which we evaluated using area under the curve (AUC), the difference between training and testing AUC, omission rate, the true skill statistic, and Schoener's D to examine the effects of different filtering schemes. 3. The degree of change produced by filtering on predicted suitability and evaluation statistics increased with increasing range size. Environmental filtering resulted in higher model fit at larger extents and retained more occurrences than geographic filtering. 4. Our results indicate that models should be evaluated using multiple evaluation statistics at multiple thresholds. The use of bin sizes when filtering in environmental space allows for simple comparison between species and filter types and makes for an easily reportable and repeatable distance metric. We specifically recommend that ecological niche models using natural history collection data filter in environmental space with variables derived from permutation importance or the first few axes of a principal components ordination.
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.