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896 results for “distributional ranges”
A meta-analysis of butterfly structural colors: their color range, distribution, and biological production
<p><span>Butterfly scales are among the richest natural sources of optical nanostructures, which produce structural color and iridescence. Several recurring nanostructure types have been described, such as ridge multilayers, gyroids, and lower lamina thin films. While the optical mechanisms of these nanostructure classes are known, their phylogenetic distributions and functional ranges have not been described in detail. In this Review, we examine a century of research on the biological production of structural colors, including their evolution, development, and genetic regulation. We also create a database of more than 300 optical nanostructures in butterflies and conduct a meta-analysis of the color range, abundance, and phylogenetic distribution of each nanostructure class. Butterfly structural colors are ubiquitous in short wavelengths but extremely rare in long wavelengths, especially red. In particular, blue wavelengths (around 450 nm) occur in more clades and are produced by more kinds of nanostructures than other hues. Nanostructure categories differ in prevalence, phylogenetic distribution, color range, and brightness. For example, lamina thin films are the least bright; perforated lumen multilayers occur most often but are almost entirely restricted to the family Lycaenidae; and 3D photonic crystals, including gyroids, have the narrowest wavelength range (from about 450 to 550 nm). We discuss the implications of these patterns in terms of nanostructure evolution, physical constraint, and relationships to pigmentary color. Finally, we highlight opportunities for future research, such as analyses of subadult and Hesperid structural colors and the identification of genes that directly build the nanostructures, with relevance for biomimetic engineering.</span></p>
Transitions between colour mechanisms affect speciation dynamics and range distributions of birds
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Data from: Mapping coastal redwoods (<em>Sequoia sempervirens</em>) across their natural range: An updateable and field-validated distribution map using Sentinel satellite data and cloud computing
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Combining camera trap surveys and IUCN range maps to improve knowledge of species distributions
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Data from: The importance of biotic interactions in distribution models of wild bees depends on the type of ecological relations, spatial scale and range
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Data from: Integrated species distribution models to account for sampling biases and improve range wide occurrence predictions
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Resources for: Spatio-temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts
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Data from: Species distribution models of the Spotted Wing Drosophila (Drosophila suzukii, Diptera: Drosophilidae) in its native and invasive range reveal an ecological niche shift
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A meta-analysis of butterfly structural colors: their color range, distribution, and biological production
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Data from: Is there a disease-free halo at species range limits? The co-distribution of anther-smut disease and its host species
1. While disease is widely recognized as affecting host population size, it has rarely been considered to play a role in determining host range limits. Many diseases may not be able to persist near the range limit if host population density falls below the critical threshold level for pathogen invasion. However, in vector- and sexually-transmitted diseases, pathogen transmission may be largely independent of host density and theory demonstrates that diseases with frequency-dependent transmission may persist in small populations near the range limit. 2. Empirical studies of disease at species range limits have lagged behind the theory, and to date, no previous study has tested the hypothesis that vector or sexually transmitted diseases can be maintained at host range limits. 3. We studied the distribution of anther-smut disease, a sterilizing pollinator-transmitted disease, on four alpine plant species to determine whether disease was present at the host range limits. 4. We found that host abundance declined towards the elevational range limits, and disease extended to the most extreme elevational range limits in three of the four host species. Maximum likelihood estimation of the magnitude of the disease-free halo showed that it was small or non-existent for all host species. Moreover, disease prevalence within populations was often higher nearer the host's range limit than in the range center and was independent of host density. 5. Synthesis: Our results show that diseases where transmission is frequency-dependent have the potential to affect host distributions not just in theory, but also in real world populations.
Fig. 2 in Distributional Range Extension and Live Coloration of the Indo-Pacific Deepwater Cardinalfish Ostorhinchus cheni (Perciformes: Apogonidae)
Fig. 2. Preserved specimen of Ostorhinchus cheni. USNM 212791, 104.5 mm SL, Sri Lanka.
Data from: Effects of input data sources on species distribution model predictions across species with different distributional ranges
<p>Species distribution models (SDMs) are a popular tool in theoretical and quantitative ecology, and constitute the most widely used modelling framework in global change science and biodiversity conservation. As main data sources, SDMs require georeferenced biodiversity observations as a response or dependent variable (e.g. species occurrence, species richness, etc) and geographic layers of environmental information as predictors or independent variables (e.g. climate, land cover, vegetation indices derived from remote sensing, etc). However, although SDMs have become one of the most important quantitative tools for addressing regular and timely biodiversity assessments worldwide, these techniques are still subject to different sources of uncertainty that have been unequally assessed. Thus, despite uncertainty related to niche-based or distribution-based models has been addressed at different stages in the modelling process, an analysis of the effect of uncertainty coming from alternative data sources on the predictive ability of SDMs is still limited.</p> <p>Citizen-collected species occurrence data (e.g. eBird) are often used for fitting SDMs when data from standardized and expert-supported surveys (e.g. Atlases) are unavailable. On the other hand, macroclimate variables are much more commonly used as predictors in SDMs than other sources of information coming from remote sensing data. We assessed the effects of using different data sources (in both response and predictor variables) on SDM performance across a wide range of bird species with contrasting distributional ranges in the Iberian Peninsula (Portugal and Spain). To do that, a SDM ensemble-forecasting approach was implemented by using bird data from two different data sources: the semi-structured eBird project and standardized Atlases. We fitted SDMs with three predictor types: macroclimate, remotely sensed ecosystem functional attributes (EFAs) from vegetation indices, and their combination. Species were grouped in four range size classes. We also used different evaluation metrics to better assess the uncertainty of model predictions. We then applied generalized linear mixed-effects models to test the effect on model performance of input data source across distributional range sizes while accounting for different accuracy metrics. Pairwise comparisons between range projections were used to assess their spatial similarity.</p> <p>Our models demonstrated the usefulness and complementarity of different input data sources when modelling species distribution across different distributional ranges. Citizen science and remote sensing data contribute to update the knowledge of the distribution of the most threatened bird species by increasing the model accuracy. These findings highlight the need to integrate different data sources to improve the model predictions at regional scale. Our framework also underlines that model uncertainty should be examined more exhaustively at early stages of the modelling process.</p> <p>To perfom and replicate this study, this dataset provides all needed files (as tables) to fit SDMs: i) the Iberian bird species occurrences at 10km UTM square as a response or dependent variable; ii) the geographic layers of environmental information at 10km UTM square for the Iberian Peninsula as predictors or independent variables, such as climate data, ecosystem functioning attributes (EFAs) and the combined climate and EFA data. The dataset is provided by four <em>*.csv</em> files named as:</p> <p><em>1) The_Iberian_bird_species_occurrences_dataset_10km.csv</em></p> <p><em>2) CHELSA_bioclimate_variables_IP10km.csv</em></p> <p><em>3) MODIS_EVI-based_EFAs_IP10km.csv</em></p> <p><em>4) Combined_bioclimate_EFA_dataset_IP10km.csv</em></p> <p>For a more detailed description of the main dataset and each of these subdatasets, please refer to the attached README file.</p> <p><strong>Keywords:</strong> bird atlas, eBird data, ecosystem functional attributes (EFAs), Iberian Peninsula, IUCN categories, Model accuracy, MODIS EVI, narrow-ranged species, remote sensing, species distribution models (SDMs), widespread species</p>
Fig. 2 in Interspecific Interactions as a Factor of Limitation of Geographical Distribution: Evidence Obtained by Modeling Home Ranges of Vole Twin Species Microtus Arvalis – M. Levis (Rodentia, Microtidae)
Fig. 2. Potential distribution of the East European vole (Microtus levis). Captions as in fig.1.
Data from: Demographic and ecogeographic factors limit wild grapevine spread at the southern edge of its distribution range - wild grapevine sampling locations, Maxent input files, morphological and microsatellite data
<p><span>This dataset contains raw data described in the paper: "Rahimi O., Ohana-Levi N., Brauner H., Inbar N., Hübner S. and Drori E. (2021) "Demographic and ecogeographic factors limit wild grapevine spread at the southern edge of its distribution range", accepted for publication in "Ecology and Evolution".</span></p> <p><span>The spatial distribution of plants is constrained by demographic and eco-geographic factors that determine the range and abundance of the species. In this study, we performed genetic and morphological analyzes based on SSR and OIV datasets. In addition, according to the spatial distribution model performed by Maxent software we found that distance to water sources, Normalized difference vegetation index, and precipitation are the main environmental factors constraining <i>V.v. sylvestris</i> distribution at its southern distribution range. All raw data used for this study can be found in this deposit which contains a table with grapevine locations, Maxent input files, morphological and microsatellite data. </span></p>
Publication release: How well do species distribution models predict occurrences in exotic ranges?
<div class="record-description"> <p>Species distribution models (SDMs) are widely used predictive tools to forecast potential biological invasions. However, the reliability of SDMs extrapolated to exotic ranges remains understudied, with most analyses restricted to few species and equivocal results. We examined the spatial transferability of SDMs for 647 non-indigenous species extrapolated across 1,867 invaded ranges, and identify what factors may help differentiate predictive success from failure. We performed a large-scale assessment of the transferability of SDMs using two modelling approaches: generalized additive models (GAMs) and MaxEnt. We fitted SDMs on the native ranges of species and extrapolated them to exotic ranges. We examined the influence of general factors and factors related to biological invasions on spatial transferability.</p> <p>Here, we provide the code and data for publication in Global Ecology and Biogeography as part of Nguyen and Leung 2022 "How well do species distribution models predict occurrences in exotic ranges?". Provided are the files and scripts necessary to fit and validate the SDMs using distirbutional data from their native and exotic ranges, respectively, formulated as generalized additive models (GAMs) or MaxEnt models. Additionally, provided is a script to validate the SDMs on their native fitting range using 10-fold cross-validation, and to fit the transferability model, as a linear mixed model (LMM), with a provided cleaned data.frame. The dataset provided includes a full species list with GBIF occurrence records, target-group background (TGB) records to use with model fitting and validation, as well as environmental data associated with the sightings.</p> </div>
Evolution in response to climate in the native and introduced ranges of a globally distributed plant
<p><span>The extent to which species can adapt to spatiotemporal climatic variation in their native and introduced ranges remains unresolved. To address this, we examined how clines in cyanogenesis (HCN production—an antiherbivore defense associated with decreased tolerance to freezing) have shifted in response to climatic variation in space and time over a 60-year period in both the native and introduced ranges of <em>Trifolium repens</em>. HCN production is a polymorphic trait controlled by variation at two Mendelian loci (<em>Ac</em> and <em>Li</em>). Using phenotypic assays, we estimated within-population frequencies of HCN production and dominant alleles at both loci (i.e., <em>Ac</em> and <em>Li</em>) from 10,575 plants sampled from 131 populations on 5 continents, and then compared these frequencies to those from historical data collected in the 1950s. There were no clear relationships between changes in the frequency of HCN production, <em>Ac</em>, or <em>Li</em> and changes in temperature between contemporary and historical samples. We did detect evidence of continued evolution to temperature gradients in the introduced range, whereby the slope of contemporary clines for HCN and <em>Ac</em> in relation to winter temperature became steeper than historical clines and more similar to native clines. These results suggest that cyanogenesis clines show no clear changes through time in response to global warming, but introduced populations continue to adapt to their contemporary environments.</span></p>
Data from: Lineage-specific trait variations and plasticity of obligate parthenogenetic animals following the expansion of distribution range to a continental archipelago.
<p><span>Two asexual lineages, JPN1 and JPN2, of panarctic <em>Daphnia pulex</em> expanded the distribution range to Japan from North America, independent of each other. According to the mutation rates within these lineages, JPN1 lineage colonized Japan earlier than JPN2 lineage. Moreover, the ratio of nonsynonymous to synonymous mutation rates (dN/dS) was lower in JPN1 than in JPN2 lineage.</span></p> <p><span>Accordingly, it is hypothesized that variations of phenotypic traits differ between these two lineages. In addition, since they are obligate parthenogenetic animals, the lineage occupying a larger distribution range should have a larger phenotypic plasticity. To test these hypotheses, we experimentally examined the phenotypic variations of fitness-related traits, including digestive, life history and morphological traits, among several genotypes of these lineages.</span></p> <p><span>We found that within-lineage variations of most traits were smaller in JPN1 than in JPN2. In addition, the overall phenotypic variations were also smaller within the JPN1 lineage than within the JPN2 lineage. These results support the idea that the JPN1 lineage has been more efficiently subjected to negative selection, as expected from the lower dN/dS ratio.</span></p> <p><span>However, the magnitude of the phenotypic plasticity to changing food levels was at the same level for both the JPN1 and JPN2 lineages, while variations found in the phenotypic plasticity were smaller in the JPN1 lineage. The difference in the variations of the phenotypic traits and plasticity between the two lineages suggests that these two lineages have evolved under somewhat different environmental conditions and that genotypes of the JPN2 lineage may have exploited niches that differed somewhat from that of the JPN1 genotypes.</span></p>
Data from: Occurrence-habitat mismatching and niche truncation when modelling distributions affected by anthropogenic range contractions
<p><strong>Aims: </strong>Human-induced pressures such as deforestation cause anthropogenic range contractions (ARCs). Such contractions present dynamic distributions that may engender data misrepresentations within species distribution models. The temporal bias of occurrence data—where occurrences represent distributions before (past bias) or after (recent bias) ARCs—underpins these data misrepresentations. Occurrence-habitat mismatching results when occurrences sampled before contractions are modelled with contemporary anthropogenic variables; niche truncation results when occurrences sampled after contractions are modelled without anthropogenic variables. Our understanding of their independent and interactive effects on model performance remains incomplete but is vital for developing good modelling protocols. Through a virtual ecologist approach, we demonstrate how these data misrepresentations manifest and investigate their effects on model performance.</p> <p><strong>Location:</strong> Virtual Southeast Asia</p> <p><strong>Methods:</strong> Using 100 virtual species, we simulated ARCs with 100-year land-use data and generated temporally biased (past, recent) occurrence datasets. We modelled datasets with and without a contemporary land-use variable (conventional modelling protocols) and with a temporally dynamic land-use variable. We evaluated each model's ability to predict historical and contemporary distributions.</p> <p><strong>Results:</strong> Greater ARC resulted in greater occurrence-habitat mismatching for datasets with past bias and greater niche truncation for datasets with recent bias. Occurrence-habitat mismatching prevented models with the contemporary land-use variable from predicting anthropogenic-related absences, causing overpredictions of contemporary distributions. Although niche truncation caused underpredictions of historical distributions (environmentally suitable habitats), incorporating the contemporary land-use variable resolved these underpredictions, even when mismatching occurred. Models with the temporally dynamic land-use variable consistently outperformed models without.</p> <p><strong>Main conclusions:</strong> We showed how these data misrepresentations can degrade model performance, undermining their use for empirical research and conservation science. Given the ubiquity of anthropogenic range contractions, these data misrepresentations are likely inherent to most datasets. Therefore, we present a three-step strategy for handling data misrepresentations: maximise the temporal range of anthropogenic predictors, exclude mismatched occurrences, and test for residual data misrepresentations.</p>
Population expansion, divergence, and persistence in western fence lizards (Sceloporus occidentalis) at the northern extreme of their distributional range
<p>Population dynamics within species at the edge of their distributional range, including the formation of genetic structure during range expansion, are difficult to study when they have had limited time to evolve. Western Fence Lizards (<em>Sceloporus occidentalis</em>) have a patchy distribution at the northern edge of their range around the Puget Sound, Washington, where they almost exclusively occur on imperiled coastal habitats. The entire region was covered by Pleistocene glaciation as recently as 16,000 years ago, suggesting that populations must have colonized these habitats relatively recently. We tested for population differentiation across this landscape using genome-wide SNPs and morphological data. A time-calibrated species tree supports the hypothesis of a post-glacial establishment and subsequent population expansion into the region. Despite a strong signal for fine-scale population genetic structure across the Puget Sound with as many as 8–10 distinct subpopulations supported by the SNP data, there is minimal evidence for morphological differentiation at this same spatiotemporal scale. Historical demographic analyses suggest that populations expanded and diverged across the region as the Cordilleran Ice Sheet receded. Population isolation, lack of dispersal corridors, and strict habitat requirements are the key drivers of population divergence in this system. These same factors may prove detrimental to the future persistence of populations as they cope with increasing shoreline development associated with urbanization.</p>
data sets from "Updated trends of the stratospheric ozone vertical distribution in the 60S–60N latitude range based on the LOTUS regression model"
<p>Monthly means data sets from satellite, ground-based and model records used in the article entitled: "Updated trends of the stratospheric ozone vertical distribution in the 60 S–60 N latitude range based on the LOTUS regression model"</p> <p> </p>
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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.