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5,805 results for “Data model”
Data from: A hierarchical model of whole assemblage island biogeography
Island systems have long played a central role in the development of ecology and evolutionary biology. However, while many empirical studies suggest species differ in vital biogeographic rates, such as dispersal abilities, quantitative methods have had difficulty incorporating such differences into analyses of whole-assemblages. In particular, differences in dispersal abilities among species can cause variation in the spatial clustering and localization of species distributions. Here, we develop a single, hierarchical Bayes, assemblage-wide model of 252 bird species distributions on the islands of Northern Melanesia and use it to investigate a) whether dispersal limitation structures bird assemblages across the archipelago, b) whether species differ in dispersal ability, and c) test the hypothesis that wing aspect ratio, a trait linked to flight efficiency, predicts differences inferred by the model. Consistent with island biogeographic theory, we found that individual species were more likely to occur on islands with greater area, and on islands near to other islands where the species also occurred. However, species showed wide variation in the importance and spatial scale of these clustering effects. The importance of clustering in distributions was greater for species with low wing aspect ratios, and the spatial scale of clustering was also smaller for low aspect ratio species. These findings suggest that the spatial configuration of islands interacts with species dispersal ability to affect contemporary distributions, and that these species differences are detectable in occurrence patterns. More generally, our study demonstrates a quantitative, hierarchical approach that can be used to model the influence of dispersal heterogeneity in diverse assemblages and test hypotheses for how traits drive dispersal differences, providing a framework for deconstructing ecological assemblages and their drivers.
Data from: Landscape models for nuclear genetic diversity and genetic structure in white-footed mice (Peromyscus leucopus)
Dramatic changes in the North American landscape over the last 12 000 years have shaped the genomes of the small mammals, such as the white-footed mouse (Peromyscus leucopus), which currently inhabit the region. However, very recent interactions of populations with each other and the environment are expected to leave the most pronounced signature on rapidly evolving nuclear microsatellite loci. We analyzed landscape characteristics and microsatellite markers of P. leucopus populations along a transect from southern Ohio to northern Michigan, in order to evaluate hypotheses about the spatial distribution of genetic heterogeneity. Genetic diversity increased to the north and was best approximated by a single-variable model based on habitat availability within a 0.5-km radius of trapping sites. Interpopulation differentiation measured by clustering analysis was highly variable and not significantly related to latitude or habitat availability. Interpopulation differentiation measured as FST values and chord distance was correlated with the proportion of habitat intervening, but was best explained by agricultural distance and by latitude. The observed gradients in diversity and interpopulation differentiation were consistent with recent habitat availability being the major constraint on effective population size in this system, and contradicted the predictions of both the postglacial expansion and core-periphery hypotheses.
Data from: State-space modelling of the flight behaviour of a soaring bird provides new insights to migratory strategies
1. Characterizing the spatiotemporal variation of animal behaviour can elucidate the way individuals interact with their environment and allocate energy. Increasing sophistication of tracking technologies paired with novel analytical approaches allows the characterisation of movement dynamics even when an individual is not directly observable. 2. In this study, high-resolution movement data collected via global positioning system (GPS) tracking in three dimensions were paired with topographical information and used in a Bayesian state-space model to describe the flight modes of migrating golden eagles (Aquila chrysaetos) in eastern North America. 3. Our model identified five functional behavioural states, two of which were previously undescribed variations on thermal soaring. The other states comprised gliding, perching and orographic soaring. States were discriminated by movement features in the horizontal (step length and turning angle) and vertical (change in altitude) planes, and by the association with ridgelines promoting wind deflection. Tracked eagles spent 2%, 31%, 38%, 9% and 20% of their day time in directed thermal soaring, gliding, convoluted thermal soaring, perching and orographic soaring, respectively. The analysis of the relative occurrence of these flight modes highlighted yearly, seasonal, age, individual and sex differences in flight strategy and performance. Particularly, less energy-efficient orographic soaring was more frequent in autumn, when thermals were less available. Adult birds were also better at optimising energy efficiency than sub-adults. 4. Our approach represents the first example of a state-space model for bird flight mode using altitude data in conjunction with horizontal locations, and is applicable to other flying organisms where similar data are available. The ability to describe animal movements in a three-dimensional habitat is critical to advance our understanding of the functional processes driving animals' decisions.
Data from: Tropical tree height and crown allometries for the Barro Colorado Nature Monument, Panama: a comparison of alternative hierarchical models incorporating interspecific variation in relation to life history traits
Tree allometric relationships are widely employed for estimating forest biomass and production and are basic building blocks of dynamic vegetation models. In tropical forests, allometric relationships are often modeled by fitting scale-invariant power functions to pooled data from multiple species, an approach that fails to capture changes in scaling during ontogeny and physical limits to maximum tree size and that ignores interspecific differences in allometry. Here, we analyzed allometric relationships of tree height (9884 individuals) and crown area (2425) with trunk diameter for 162 species from the Barro Colorado Nature Monument, Panama. We fit nonlinear, hierarchical models informed by species traits – wood density, mean sapling growth, or sapling mortality – and assessed the performance of three alternative functional forms: the scale-invariant power function and the saturating Weibull and generalized Michaelis–Menten (gMM) functions. The relationship of tree height with trunk diameter was best fit by a saturating gMM model in which variation in allometric parameters was related to interspecific differences in sapling growth rates, a measure of regeneration light demand. Light-demanding species attained taller heights at comparatively smaller diameters as juveniles and had shorter asymptotic heights at larger diameters as adults. The relationship of crown area with trunk diameter was best fit by a power function model incorporating a weak positive relationship between crown area and species-specific wood density. The use of saturating functional forms and the incorporation of functional traits in tree allometric models is a promising approach for improving estimates of forest biomass and productivity. Our results provide an improved basis for parameterizing tropical plant functional types in vegetation models.
Data from: Modeling effects of environmental change on wolf population dynamics, trait evolution, and life history
Environmental change has been observed to generate simultaneous responses in population dynamics, life history, gene frequencies, and morphology in a number of species. But how common are such eco-evolutionary responses to environmental change likely to be? Are they inevitable, or do they require a specific type of change? Can we accurately predict eco-evolutionary responses? We address these questions using theory and data from the study of Yellowstone wolves. We show that environmental change is expected to generate eco-evolutionary change, that changes in the average environment will affect wolves to a greater extent than changes in how variable it is, and that accurate prediction of the consequences of environmental change will probably prove elusive.
Data from: Use of auto-germ to model germination timing in the Sagebrush-steppe
Germination timing has a strong influence on direct seeding efforts, and therefore is a closely tracked demographic stage in a wide variety of wildland and agricultural settings. Predictive seed germination models, based on soil moisture and temperature data in the seed zone are an efficient method of estimating germination timing. We utilized Visual Basic for Applications (VBA) to create Auto-Germ, which is an Excel workbook that allows a user to estimate field germination timing based on wet-thermal accumulation models and field temperature and soil moisture data. To demonstrate the capabilities of Auto-Germ, we calculated various germination indices and modeled germination timing for 11 different species, across 6 years, and 10 Artemisia-steppe sites in the Great Basin of North America to identify the planting date required for 50% or more of the simulated population to germinate in spring (1 March or later), which is when conditions are predicted to be more conducive for plant establishment. Both between and within the species, germination models indicated that there was high temporal and spatial variability in the planting date required for spring germination to occur. However, some general trends were identified, with species falling roughly into three categories, where seeds could be planted on average in either fall (Artemisia tridentata ssp. wyomingensis and Leymus cinereus), early winter (Festuca idahoensis, Poa secunda, Elymus lanceolatus, Elymus elymoides, and Linum lewisii), or mid-winter (Achillea millefolium, Elymus wawawaiensis , and Pseudoroegneria spicata) and still not run the risk of germination during winter. These predictions made through Auto-Germ demonstrate that fall may not be an optimal time period for sowing seeds for most non-dormant species if the desired goal is to have seeds germinate in spring.
Data from: Comparing the impact of future cropland expansion on global biodiversity and carbon storage across models and scenarios
<p>Land-use change is a direct driver of biodiversity and carbon storage loss. Projections of future land-use often include notable expansion of cropland areas in response to changes in climate and food demand, although there are large uncertainties in results between models and scenarios. This study examines these uncertainties by comparing three different socio-economic scenarios (SSP1-3) across three models (IMAGE, GLOBIOM and PLUMv2). It assesses the impacts on biodiversity metrics and direct carbon loss from biomass and soil as a direct consequence of cropland expansion. Results show substantial variation between models and scenarios, with little overlap across all nine projections. Although SSP1 projects the least impact, there are still significant impacts projected. IMAGE and GLOBIOM project the greatest impact across carbon storage and biodiversity metrics due to both extent and location of cropland expansion. Furthermore, for all the biodiversity and carbon metrics used, there is a greater proportion of variance explained by model used. This demonstrates the importance of improving the accuracy of land-based models. Incorporating effects of land-use change in biodiversity impact assessments would also help better prioritise future protection of biodiverse and carbon-rich areas.</p>
Data from: Point process models for presence-only analysis
1. Presence-only data are widely used for species distribution modelling, and point process regression models are a exible tool that has considerable potential for this problem, when data arise as point events. 2. In this paper we review point process models, some of their advantages, and some common methods of fitting them to presence-only data. 3. Advantages include (and are not limited to): clarification of what the response variable is that is modelled; a framework for choosing the number and location of quadrature points (commonly referred to as pseudoabsences or \background points") objectively; clarity of model assumptions and tools for checking them; models to handle spatial dependence between points when it is present; ways forward regarding difficult issues such as accounting for sampling bias. 4. Point process models are related to some common approaches to presenceonly species distribution modelling, which means that a variety of different software tools can be used to fit these models, including MAXENT or generalised linear modelling software.
Data from: Using survival models to estimate invertebrate prey identification times in a generalist stream fish
Estimates of predator feeding rates are important for understanding trophic dynamics. One common method for quantifying feeding rates in fishes combine mass-based diet data with gastric evacuation times to estimate prey mass consumed per predator. An alternative approach is to estimate rates of prey individuals consumed using prey identification times − the time period over which prey remain identifiable in a predator's stomach. One challenge with the analysis of prey identification times, however, is that the response variable is likely to be censored because the 'true' prey identification time cannot be observed directly. Here, we applied survival analysis that can incorporate censored data to estimate the effects of predator body size, water temperature, and prey characteristics (type, count and body size) on identification times in reticulate sculpin (Cottus perplexus). We focused on seven types of prey that are common in this generalist predator's diet: mayflies (Ephemeroptera), caddisflies (Trichoptera), stoneflies (Plecoptera), flies (Diptera), beetles (Coleoptera), worms (Annelida), and sculpin eggs. An information-theoretic model comparison approach indicated that an accelerated failure-time Weibull model with all five covariates provided the best relative fit to the full dataset. Prey type had a strong effect on prey identification times, with annelid worms having the shortest times (< 1 hr) and caddisflies having the longest times (> 15 hrs). Water temperature decreased prey identification times (7.5% per 1°C increase), whereas prey count (i.e. meal size) increased prey identification times (15.5% per additional prey item). Sculpin body size had a weak negative effect on prey identification times (0.04% per 1 mm increase). Body sizes of some taxa, including mayflies, caddisflies, and stoneflies, increased prey identification times, leading to an interaction between prey type and prey size. Our study highlights the utility of survival analysis to quantify variation in prey identification times in the diets of generalist predators.
Data from: Spatial scaling of environmental variables improves species-habitat models of fishes in a small, sand-bed lowland river
Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species' presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the importance of considering habitat at spatial scales larger than the sampling site, and (iii) that the importance of (river morphological) habitat characteristics differs depending on the spatial scale.
Data from: Gene trees, species trees and Earth history combine to shed light on the evolution of migration in a model avian system
The evolution of migration in birds has fascinated biologists for centuries. In this study, we performed phylogenetic-based analyses of Catharus thrushes, a model genus in the study of avian migration, and their close relatives. For these analyses, we used both mitochondrial and nuclear genes, and the resulting phylogenies were used to trace migratory traits and biogeographic patterns. Our results provide the first robust assessment of relationships within Catharus and relatives and indicate that both mitochondrial and autosomal genes contribute to overall support of the phylogeny. Measures of phylogenetic informativeness indicated that mitochondrial genes provided more signal within Catharus than did nuclear genes, whereas nuclear loci provided more signal for relationships between Catharus and close relatives than did mitochondrial genes. Insertion and deletion events also contributed important support across the phylogeny. Across all taxa included in the study, and for Catharus, possession of long-distance migration is reconstructed as the ancestral condition, and a North American (north of Mexico) ancestral area is inferred. Within Catharus, sedentary behaviour evolved after the first speciation event in the genus and is geographically and temporally correlated with Central American distributions and the final closure of the Central American Seaway. Migratory behaviour subsequently evolved twice in Catharus and is geographically and temporally correlated with a recolonization of North America in the late Pleistocene. By temporally linking speciation events with changes in migratory condition and events in Earth history, we are able to show support for several competing hypotheses relating to the geographic origin of migration.
Data from: Phylogeography in continuous space: coupling species distribution models and circuit theory to assess the effect of contiguous migration at different climatic periods on genetic differentiation in Busseola fusca (Lepidoptera: Noctuidae)
Current population genetic models fail to cope with genetic differentiation for species with large, contiguous and heterogeneous distribution. We show that in such a case, genetic differentiation can be predicted at equilibrium by circuit theory, where conductance corresponds to abundance in species distribution models (SDM). Circuit-SDM approach was used for the phylogeographic study of the lepidopteran cereal stemborer Busseola fusca Füller (Noctuidae) across sub-Saharan Africa. Species abundance was surveyed across its distribution range. SDM models were optimized and selected by cross validation. Relationship between observed matrices of genetic differentiation between individuals, and matrices of resistance distance was assessed through Mantel tests and redundancy discriminant analyses (RDA). A total of 628 individuals from 130 localities in 17 countries were genotyped at 7 microsatellite loci. Six population clusters were found based on a Bayesian analysis. The eastern margin of Dahomey Gap between East and West Africa was the main factor of genetic differentiation. The SDM projections at present, last interglacial and last glacial maximum periods were used for estimation of circuit resistance between locations of genotyped individuals. For all periods of time, when using either all individuals or only East-African individuals, partial Mantel r and RDA analyses conditioning on geographic distance were found significant. Under future projections (year 2080), partial r and RDA significance were different. From this study, it is concluded that analytical solutions provided by circuit theory are useful for the evolutionary management of populations and for phylogeographic analysis when coalescence times are not accessible by approximate Bayesian simulations.
Data from: Utility of pooled sequencing for association mapping in non-model organisms
High density genome-wide sequencing increases the likelihood of discovering genes of major effect and genomic structural variation in organisms. While there is an increasing availability of reference genomes across broad taxa, the greatest limitation to whole-genome sequencing of multiple individuals continues to be the costs associated with sequencing. To alleviate excessive costs, pooling multiple individuals with similar phenotypes and sequencing the homogenized DNA (Pool-Seq) can achieve high genome coverage, but at the loss of individual genotypes. Although Pool-Seq has been an effective method for association mapping in model organisms, it has not been frequently utilized in natural populations. To extend bioinformatic tools for rapid implementation of Pool-Seq data in non-model organisms, we developed a pipeline called PoolParty and illustrate its effectiveness in genetic association mapping. Alignment expectations based on five pooled Chinook salmon (Oncorhynchus tshawytscha) libraries showed that approximately 48% genome coverage per library could be achieved with reasonable sequencing effort. We additionally examined male and female O. tshawytscha libraries to illustrate how Pool-Seq techniques can successfully map known genes associated with functional differences among sexes such as growth hormone 2. Finally, we compared pools of individuals of different spawning ages for each sex to discover novel genes involved with age at maturity in O. tshawytscha such as opsin4 and transmembrane protein19. While not appropriate for every system, Pool-Seq data processed by the PoolParty pipeline is a practical method for identifying genes of major effect in non-model organisms when high genome coverage is necessary and cost is a limiting factor.
Data from: Tests of species-specific models reveal the importance of drought in postglacial range shifts of a Mediterranean-climate tree: insights from integrative distributional, demographic and coalescent modelling and ABC model selection
Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species-specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade-offs in functional traits, and local-scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade-off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common.
Data from: Fencing solves human‐wildlife conflict locally but shifts problems elsewhere: a case study using functional connectivity modelling of the African elephant
1. Fencing is one of the commonest methods for mitigating human-wildlife conflicts. At the same time, fencing is considered to be of one of the most pressing emerging threats to conservation globally. Although fences act as barriers and eventually can cause population isolation and fragmentation, it is challenging to quantitatively predict the possible consequences fences have for wildlife. 2. Here, we model how fencing designed to mitigate human-elephant conflict (HEC) on the Borderlands between Kenya and Tanzania will affect functional connectivity and movement corridors for African elephants. Specifically, we (1) model functional landscape connectivity integrating natural and anthropogenic factors; (2) predict seasonal movement corridors used by elephants in non-protected areas; and (3) evaluate whether fencing in one area can potentially intensify human-wildlife conflicts elsewhere. 3. We used GPS movement and remote sensing data to develop monthly step-selection functions to model functional connectivity. For future scenarios, we used a currently ongoing fencing project designed for human-elephant conflict mitigation within the study area. We modelled movement corridors using least-cost path and circuit theory methods, evaluated their predictive power and quantified connectivity changes resulting from the planned fencing. 4. Our results suggest that fencing will not cause landscape fragmentation and will not change functional landscape connectivity dramatically. However, fencing will lead to a loss of connectivity locally and will increase the potential for HEC in new areas. We estimated that wetlands important for movement corridors will be more intensively used by the elephants, which may also cause problems of overgrazing. Seasonal analysis highlighted an increasing usage of non-protected lands in the dry season and equal importance of the pinch point wetlands for preserving overall function connectivity. 5. Synthesis and applications. Fencing is a solution to small-scale HEC problems, but will not solve the issue at a broader scale. Moreover, our results highlight that it may intensify the conflicts and overuse of habitat patches in other areas, thereby negating any conservation benefits. If fencing is employed on a broader scale, then it is imperative that corridors are integrated within the protected area network to ensure local connectivity of affected species.
Data from: Historical species distribution models predict species limits in western Plethodon salamanders
Allopatry is commonly used to predict boundaries in species delimitation investigations under the assumption that currently allopatric distributions are indicative of reproductive isolation; however, species ranges are known to change over time. Incorporating a temporal perspective of geographic distributions should improve species delimitation; to explore this, we investigate three species of western Plethodon salamanders that have shifted their ranges since the end of the Pleistocene. We generate species distribution models (SDM) of the current range, hindcast these models onto a climatic model 21 Ka, and use three molecular approaches to delimit species in an integrated fashion. In contrast to expectations based on the current distribution, we detect no independent lineages in species with allopatric and patchy distributions (Plethodon vandykei and Plethodon larselli). The SDMs indicate that probable habitat is more expansive than their current range, especially during the last glacial maximum (LGM) (21 Ka). However, with a contiguous distribution, two independent lineages were detected in Plethodon idahoensis, possibly due to isolation in multiple glacial refugia. Results indicate that historical SDMs are a better predictor of species boundaries than current distributions, and strongly imply that researchers should incorporate SDM and hindcasting into their investigations and the development of species hypotheses.
Data from: Applying ecological site concepts and state-and-transition models to a grazed riparian rangeland
Ecological sites and state-and-transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in rangeland systems. These models have been widely implemented in upland rangelands, but comparatively little attention has been given to developing ecological site concepts for rangeland riparian areas, and additional environmental criteria may be necessary to classify riparian ecological sites. Between 2013 and 2016, fifteen study reaches on five creeks were studied at Tejon Ranch in southern California. Data were collected to describe the relationship between riparian vegetation composition, environmental variables, and livestock management; and to explore the utility of ecological sites and state-and-transition models for describing riparian vegetation communities and for creating hypotheses about drivers of vegetation change. Hierarchical cluster analysis was used to classify the environmental and vegetation data (15 stream reaches 4 years) into two ecological sites and eight community phases that comprised three vegetation states. Classification and regression tree (CART) analysis was used to determine the influence of abiotic site variables, annual precipitation, and cattle activity on vegetation clusters. Channel slope explained the greatest amount of variation in vegetation clusters; however, soil texture, geology, watershed size, and elevation were also selected as important predictors of vegetation composition. The classification tree built with this limited set of abiotic predictor variables explained 90% of the observed vegetation clusters. Cattle grazing and annual precipitation were not linked to qualitative differences in vegetation. Abiotic variables explained almost all of the observed riparian vegetation dynamics—and the divisions in the CART analysis corresponded roughly to the ecological sites—suggesting that ecological sites are well-suited for understanding and predicting change in this highly variable system. These findings support continued development of riparian ecological site concepts and state-and-transition models to aid decision making for conservation and management of rangeland riparian areas.
Data from: "Genome-wide microsatellite marker development from next-generation sequencing of two non-model bat species impacted by wind turbine mortality: Lasiurus borealis and L. cinereus (Vespertilionidae)" in Genomic Resources Notes accepted 1 October 2013 to 30 November 2013
Tree-roosting bats in the genus Lasiurus are widespread, migratory species that have not been well characterized for population genetic diversity and structure due to a lack of genetic resources. Generating genetic resources in Lasiurus is made pressing by the need for conservation genetic assessments of demographic trends in this genus, which comprise a large percentage of bat mortalities at wind turbine sites across North America. We report on marker development from whole-genome Illumina sequencing of the red bat (Lasirus borealis) and the hoary bat (L. cinereus). We generated paired-end libraries for a single individual of each species, sequenced on the Illumina HiSeq platform. We mapped a total of 46.6 million reads to the Myotis lucifigus reference genome, and used bioinformatics searches to identify tends of thousands of simple sequence repeats (SSRs) distributed across the bat genome. We selected 48 candidate microsatellite loci to develop cross-species primer sequences for Lasiurus, assembled these into multiplex combinations, and tested for amplification and polymorphism levels in a sample of 23 individuals from each of L. borealis and L. cinereus. In total, we identified 42 highly polymorphic loci that could be robustly amplified and scored, the majority of which (39) were also combinable into highly multiplexed assays of 4-8 loci each. The combination of new genomic sequence assemblies, a large set of highly polymorphic microsatellite loci, and the ability to efficiently multiplex represents a significant contribution to the genetic resources available for population and comparative genetic studies of bats.
Data from: Heterogeneity in genetic diversity among non-coding loci fails to fit neutral coalescent models of population history
Inferring aspects of the population histories of species using coalescent analyses of non-coding nuclear DNA has grown in popularity. These inferences, such as divergence, gene flow, and changes in population size, assume that genetic data reflect simple population histories and neutral evolutionary processes. However, violating model assumptions can result in a poor fit between empirical data and the models. We sampled 22 nuclear intron sequences from at least 19 different chromosomes (a genomic transect) to test for deviations from selective neutrality in the gadwall (Anas strepera), a Holarctic duck. Nucleotide diversity among these loci varied by nearly two orders of magnitude (from 0.0004 to 0.029), and this heterogeneity could not be explained by differences in substitution rates. Using two different coalescent methods to infer models of population history and then simulating neutral genetic diversity under these models, we found that the among-locus heterogeneity in nucleotide diversity was significantly higher than expected for these simple models. Defining more complex models of population history demonstrated that a pre-divergence bottleneck was also unlikely to explain this heterogeneity. However, both selection and interspecific hybridization could account for the heterogeneity observed among loci. Regardless of the cause of the deviation, our results illustrate that violating key assumptions of coalescent models can mislead inferences of population history.
Data from: Development and validation of an expert-based habitat suitability model to support boreal caribou conservation
The long-term persistence of boreal caribou (Rangifer tarandus caribou) is threatened by the negative impacts of human activities, including industrial development. The vast geographical distribution and behavioural variability of caribou warranted the development and validation of an appropriate conservation tool for managers in eastern Canada. We developed a habitat suitability model for boreal caribou in Québec by integrating expert knowledge into a hierarchical analysis. We elicited responses from 14 experts on caribou ecology to determine the best spatiotemporal scales of application, the relative importance of habitat variables, the zone of influence of human infrastructure, and the parameterization of the model. Based on this input, we built the model using 8 habitat categories and 3 human infrastructure variables. Experts identified mature conifer-dominated forests and open lichen woodlands as the most important vegetation categories for boreal caribou, whereas density of and proximity to paved roads, forest roads, and mines decreased habitat quality. We mapped the resulting model over the entire province of Québec (up to the northern forest allocation limit), and validated it using independent GPS telemetry datasets acquired in 3 distinct regions. Our model predicted that habitat suitability was highest in the northeastern part of our study area, where timber harvest activities and roads were virtually absent. Conversely, southern parts of Québec were generally unsuitable for boreal caribou. Our habitat suitability model is among the first tools for boreal caribou conservation available to wildlife and land managers in Québec.
ScienceDex guides
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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.