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8,119 results for “species distribution”
Spatial distribution and its limiting environmental factors of native orchid species diversity in the Beipan River Basin of Guizhou Province, China
<p>Understanding the distribution of biodiversity and its determinants, particularly that of ecologically sensitive ones, has long been intriguing to the science community and will help formulate conservation strategies under future climate changes. To this end, we conducted extensive field surveys on the distribution of orchid flora in the Beipan River Basin in Guizhou Province, which is one of the biodiversity conservation priorities in China. The data we acquired, together with those published previously, were converted into orchid species richness for each of the 3km × 3km grid cells covering the study region. Redundancy analysis (RDA) and Geographically Weighted Regression (GWR) were then applied to determine which of the 30 environmental factors are potentially critical for the spatial distribution of orchid flora we have observed. Despite a moderate spatial extent, we found that the Beipan River Basin harbors about 249 native orchid species belonging to 74 genera, equivalent to 14.5% of orchid flora of China. Orchid species richness in this area follows a descending gradient from the southeast to the northwest, 70.41% of its variation among grid cells can be explained by environmental factors and spatial variables, and spatial variables accounted for 63.90% of the spatial variation of orchid distribution, indicating that spatial variables played a dominant role in the distribution of wild orchidaceae species richness. In addition, the main environmental driver is the mean temperature of the wettest quarter. Our study provides a good example for revealing the main drivers of orchid distribution characteristics, and has a certain reference value for the development of orchid conservation strategies.</p>
Bayesian species distribution models integrate presence-only and presence-absence data to predict deer distribution and relative abundance
<p>Using geospatial data of wildlife presence to predict a species distribution across a geographic area is among the most common tools in management and conservation. The collection of high-quality presence-absence data through structured surveys is, however, expensive, and managers usually have access to larger amounts of low-quality presence-only data collected by citizen scientists, opportunistic observations, and culling returns for game species. Integrated Species Distribution Models (ISDMs) have been developed to make the most of the data available by combining the higher-quality, but usually scarcer and more spatially restricted presence-absence data, with the lower quality, unstructured, but usually more extensive presence-only datasets. Joint-likelihood ISDMs can be run in a Bayesian context using INLA (Integrated Nested Laplace Approximation) methods that allow the addition of a spatially structured random effect to account for data spatial autocorrelation. Here, we apply this innovative approach to fit ISDMs to empirical data, using presence-absence and presence-only data for the three prevalent deer species in Ireland: red, fallow and sika deer. We collated all deer data available for the past 15 years and fitted models predicting distribution and relative abundance at a 25 km<sup>2</sup> resolution across the island. Models' predictions were associated to spatial estimates of uncertainty, allowing us to assess the quality of the model and the effect that data scarcity has on the certainty of predictions. Furthermore, we checked the performance of the three species-specific models using two datasets, independent deer hunting returns and deer densities based on faecal pellet counts. Our work clearly demonstrates the applicability of spatially-explicit ISDMs to empirical data in a Bayesian context, providing a blueprint for managers to exploit unexplored and seemingly unusable data that can, when modelled with the proper tools, serve to inform management and conservation policies.</p>
Data and code for: Functional traits mediate individualistic species-environment distributions at broad spatial scales while fine-scale species' associations remain unpredictable
<p>Ecological communities are structured by a diverse set of processes acting at different spatial scales. In plant communities, assembly processes like ecological sorting, limiting similarity, and stochastic events are all expected to influence plant distributions and co-occurrence patterns. We assembled a data set describing the distribution of 139 herbaceous plant species within and among 257 forest stands in Wisconsin (USA) to elucidate the spatial scales at which these assembly processes operate. Analyses of these data in conjunction with detailed information about environmental conditions, plant functional traits, and phylogenetic relationships provided new insights into the scale-dependent drivers of plant community assembly in temperate forest understories. Traits like leaf height, specific leaf area, and seed mass all influenced individualistic plant distributions along landscape-scale gradients in soil texture, soil fertility, light availability, and climate while phylogenetic relationships did not predict species-environment relationships. These findings point to the importance of trait-mediated ecological sorting in shaping individualistic plant distributions at broad spatial scales. Contrary to our expectations about the importance of limiting similarity at local scales, neither functionally similar nor phylogenetically related herbs segregated among microsites within forest stands. We hypothesize strong ecological sorting among forest stands coupled with stochastic fine-scale interactions among species appear deterministic, niche-based assembly processes at local scales.</p>
FIG. 84. Distribution maps, A. mariae species group. A. A. incurva. B. A in Revision Of The Nearctic Species Of The Genus Amiota Loew (Diptera: Drosophilidae)
FIG. 84. Distribution maps, A. mariae species group. A. A. incurva. B. A. mariae Máca. C. A. texas.
FIG. 87. Distribution maps, A. avipes species group. A. A. avipes. B. A. biacuminis. C. A in Revision Of The Nearctic Species Of The Genus Amiota Loew (Diptera: Drosophilidae)
FIG. 87. Distribution maps, A. avipes species group. A. A. avipes. B. A. biacuminis. C. A. forceps.
Data from: Wallace 2: A shiny app for modeling species niches and distributions redesigned to facilitate expansion via module contributions
<p>These are the occurrence locality datasets used in the example provided in "<em>wallace</em> 2: a <em>shiny</em> app for modeling species niches and distributions redesigned to facilitate expansion via module contributions" published in Ecography (DOI: 10.1111/ecog.06547). The analysis workflow is displayed in the Supporting information of the paper (Fig. S1), and these data are also used in the <em>wallace</em> 2 vignette (<a href="https://wallaceecomod.github.io/wallace/articles/tutorial-v2.html">https://wallaceecomod.github.io/wallace/articles/tutorial-v2.html</a>).</p>
Fig. ². Geographical distribution of 7KRWWHD EHXQJRQWDQRHK Mustaqim (.)NJ in Thottea beungongtanoeh (Aristolochiaceae), a new species Irom Aceh, northern Sumatra
Fig. ². Geographical distribution of 7KRWWHD EHXQJRQWDQRHK Mustaqim (.)NJ
Data and R scripts for: Ant invasions is associated with lower root density and different root distribution of a foundational savanna tree species
<p>Some invasive ants have worldwide distributions and impose substantial impacts on human society and native biodiversity. Yet we know little about how ants impact soil ecosystems in general, much less how soil ecosystems shift when invasive ants move in. We excavated the coarse roots of a monodominant savanna tree in invaded and uninvaded areas to test the hypothesis that the presence of invasive ants would be associated with changes in root distribution and biomass across the landscape. We found that in the presence of invasive ants, trees had a shifted distribution of lateral coarse roots, with proportionally less root biomass near the surface and far from tree stems. In addition, the density of lateral coarse-root biomass was ~20% lower for trees within invaded landscapes. Our results suggest that soil-nesting invasive ants can drive important changes in rooting strategy for a tree species that serves a foundational role in the biogeochemical cycles of vertisol savannas.</p>
Botanic records from the forest reserves of south west Ghana: Plant species distribution data with checklist and conservation assessments from 114 vegetation plots
<p>South west Ghana is a biodiversity hotspot within the western African lowland tropical rainforest region, supporting many endemic and restricted range plant species. This dataset comprises botanic records from five forest reserves of south west Ghana (Ankasa, Boi Tano, Tano Nimri, Jema Assemkron, Nini Suhein). Vascular plant species distribution data (12,232 records) from 114 vegetation plot samples are presented, surveyed between 1981 and 2015. A plant species checklist including conservation assessments for each species is included. Nomenclature is current as of 2016. The dataset is linked to the publication Marshall et al, 2023, Implications for conservation assessment from flux in the botanical record over 20 years in south west Ghana, Ecology and Evolution <a href="https://doi.org/10.1002/ece3.9775">https://doi.org/10.1002/ece3.9775</a>. The dataset is also used in Marshall et al, 2022, Predictors of plant endemism in two west African forest hotspots, Frontiers in Ecology and Evolution 10:980660 <a href="https://doi.org/10.3389/fevo.2022.980660">https://doi.org/10.3389/fevo.2022.980660</a>.</p>
Dataset for the manuscript: "Three-dimensional species distribution modeling reveals the realized spatial niche for coral recruitment on contemporary Caribbean reefs"
<p>Whether the three-dimensional (3D) structure of habitats influences and partition recruitment niches of corals is unknown. We developed a new method that combined Species Distribution Modeling and Structure from Motion to characterize and map the three-dimensional recruitment niches of two ecosystem engineers on Caribbean coral reefs, scleractinian corals and octocorals. </p> <p>In this repository, we include 48 3D models of small areas of the reef (i.e., within ~ 0.25 m<sup>2</sup> quadrats) reconstructed with Structure-from-Motion, as well as the geospatial data used to characterize and map the realized recruitment niche for scleractinian corals and octocorals on Caribbean coral reefs. We conducted the study at two shallow, fringing reefs off the south shore of St. John, US Virgin Islands, named Grootpan and Europa Bays (18° 18.360’N, 64° 43.140’W, and 18° 19.016’N, 64° 43.798’W, respectively). Within each 0.25 m<sup>2</sup> quadrat, we counted and marked all recruits (octocorals ≤ 5 cm height, and scleractinians ≤ 4 cm wide).</p> <p><em>DATASET DESCRIPTIONS:</em></p> <ul> <li><strong>"Quadname_data.zip":</strong> In each of this folders we included all the data calculated within a quadrat: <ul> <li>ASCII files (.txt).</li> <li>The annotated dense point cloud (.las) for each quadrat.</li> <li>The quadrat 3D model texture (.jpg).</li> <li>The quadrat 3D polygon mesh (.ply).</li> <li>The quadrat 2.5D Digital Elevation Model (i.e., DEM; .tif).</li> <li>Shape files with recruits local coordinates within each quadrat (.dbf, .prj, .shp, .shx).</li> </ul> </li> <li><strong>"datawide.rds": </strong>This is the file needed to run the analyses performed in Martínez-Quintana et al., 2023. This file is obtained after processing all the raw data calculated within each quadrat. All code associated with the workflow used to obtain the datawide.rds file and run the analyses performed in Martínez-Quintana et al., 2023 is available at <a href="https://github.com/AdamWilsonLab/meshSDM">github.com/AdamWilsonLab/meshSDM</a>.</li> </ul> <p><strong>IMPORTANT NOTES: </strong></p> <ul> <li>Quadrat names starting with the letters “eu” indicate the data were collected at Europa Bay, whereas those starting with the letters “ec” indicate that data were collected at Grootpan Bay (commonly named East Cabritte).</li> <li>Each ASCII file (quadname_ASCII_subsampled_X.txt) contains the slope and roughness of the quadrat calculated on the point cloud at 5, 10, 20, and 100 mm scales, and the smooth point cloud used to calculate the topographic exposure index (TEI) described in Martínez-Quintana et al., 2023. Calculations were performed and ASCII files were created with CloudCompare.</li> <li>Each dense point cloud, mesh, texture, and DEM were calculated with Agisoft Metashape.</li> <li>Agisoft Metashape allows the user to classify and annotate groups of points in the dense point cloud. However, the list of classes provided by the software corresponds to the standard list used for terrestrial LiDAR data; these classes cannot be renamed within the software. Thus, for the present study, we coded the automatic semantic classifications available in Metashape as follows: <ul> <li>Ground = Calcareous rock.</li> <li>Building = Igneous rock.</li> <li>High noise = Sand.</li> <li>Low vegetation = Adult Scleractinian corals.</li> <li>Medium vegetation = Adult Octocoral base.</li> <li>High vegetation = Sponge.</li> <li>Water = Octocoral recruit (named also ocr).</li> <li>Road Surface = Scleractinian recruit (named also scr).</li> <li>Unclassified = created points but never classified (excluded from the analyses).</li> <li>Low Point = noise (unreliable points).</li> <li>Transmission tower and Rail = Points outside the quadrat and excluded from the analysis.</li> </ul> </li> </ul>
Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation study
<p>Data and R codes necessary to replicate the analyses presented in the paper entitled "Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation study", published in Peer Community in Ecology (<a href="https://doi.org/10.24072/pcjournal.263">10.24072/pcjournal.263</a>).</p>
Distribution patterns and drivers of non-endemic and endemic glires species in China
<p><span>Spatial patterns and determinants of species richness in complex geographical regions are important subjects of current biogeography and biodiversity conservation research. Glires are small herbivorous mammal species with limited migratory ability that may serve as an indicator of biodiversity and ecosystems. Herein, we aimed to evaluate how multiple ecological hypotheses could explain the species richness patterns of glires in China. Initially, we constructed a mapping grid of 80 </span>×<span> 80 km<sup>2</sup> squares which covered China's land mass and mapped the distribution ranges of the 237 glires species that had recorded. The glires taxa were separated into three response variables based on their distribution: (a) all species, (b) non-endemic species, and (c) endemic species. The species richness patterns of the response variables were evaluated using four predictor sets: (a) hydrothermal characteristics, (b) climatic seasonality, (c) habitat heterogeneity, and (d) human factors. We performed regression tree analysis, multiple linear regression analysis, and variation partitioning analyses to determine the effects of predictors on spatial species patterns. The results showed that the distribution pattern of species richness was the highest in the Hengduan Mountains and surrounding areas in southwest China. However, only a few endemic species adapted to high-latitude environments. It was found that there are differences in the determinants between non-endemic and endemic species. Habitat heterogeneity was the most influential determinant for the distribution patterns of non-endemic species richness. Climatic seasonality was the best predictor to determine the richness distribution pattern of endemic species, whereas this was least affected by human factors. Furthermore, it should be noted, that hydrothermal characteristics were not strong predictors of richness patterns for all or non-endemic species, which may be due to the fact that there are also more species in some areas with less precipitation or energy. Therefore, glires are likely to persist in areas with characteristics of high habitat heterogeneity and stable climate.</span></p>
Figure 11 in New distributional records for Mexican Cleridae (Coleoptera) with the description of three new species
Figure 11. Croton cf. guatemalensis Lotsy at type locality of Enoclerus sepultura.
Figures 6–7. Enoclerus primulus. 6 in New distributional records for Mexican Cleridae (Coleoptera) with the description of three new species
Figures 6–7. Enoclerus primulus. 6) Habitus. 7) Lateral aspect.
Figures 8–10. Enoclerus sepultura. 8 in New distributional records for Mexican Cleridae (Coleoptera) with the description of three new species
Figures 8–10. Enoclerus sepultura. 8) Habitus. 9) Lateral aspect. 10) Holotype in life.
Figure 5 in New distributional records for Mexican Cleridae (Coleoptera) with the description of three new species
Figure 5. Habitat at the type locality of Cymatodera bezarki; Oaxacan assistant for scale.
Data sources and code for: "Species-specific acclimation capacity of key traits explains global vertical distributions of seagrass species"
<p>Minguito-Frutos_etal_2023_Data1.xlsx contains the data for analyzing the relationship between plant size and seagrass growth reproductive strategy and the species-specific vertical distribution of seagrasses. </p> <p>Minguito-Frutos_etal_2023_Data2.xlsx contains the data for the meta-analityc approach studying the relationship between the vertical distribution of seagrass species and the plasticity of their traits (physiological, morphological, structural and growth). </p> <p>Scripts_Minguito_Frutos_etal_2023_GEB_Ref.GEB-2022-0592.R contains the R reproducible code to run all the analyses carried out in this study. </p>
Fig. 10 in On the genus Ammonius Thorell, 1899 (Mygalomorphae, Barychelidae): description of the female of A. pupulus, a new species and new distribution records
Fig. 10. Distribution map of the presently known species of the genus Ammonius Thorell, 1899.
Species distribution data and distribution of private and public protected areas in Cerrado, Brazil
<p>Here we present the models of 103 threatened vertebrates (Anphibia, Reptile, Birds and Mammals) from the Cerrado in Brazil and all information about spatial distribution of private and public conservation protected areas that is a part of an article about the value of private areas to conservation.</p>
Local habitat type influences bumble bee pathogen loads and bee species distribution
<p>Bumble bees (<em>Bombus </em>spp.) perform important ecological services in both managed and natural ecosystems. Anthropogenically-induced change, however, has altered the availability of floral resources, climatic suitability, and exposure to insecticides, factors that impact overall health and disease levels in these bees. Habitat management presents a solution for improving bee health and biodiversity, but this requires better understanding of how different pathogens and bee species respond to habitat conditions. Herein, we take advantage of the washboard of repeated ridges (forested) and valleys (mostly unforested and developed) in central Pennsylvania to examine whether local variation in habitat type and other landscape factors influence bumble bee community composition and the levels of four leading pathogens in the common eastern bumble bee, <em>Bombus impatiens</em>. Loads of viral pathogens (deformed wing virus and black queen cell virus) were found to be lowest in forest habitats, whereas loads of a gut parasite, <em>Crithidia bombi</em>, were highest in forests. Ridgetop forests hosted the most diverse bumble bee communities, including several habitat specialists. <em>B. impatiens</em> was most abundant in valleys, and showed higher incidence in areas of greater disturbance, including more developed, unforested, and lower floral resource sites, a pattern that mirrors its success in the face of anthropogenic change. Additionally, DNA barcoding revealed that <em>B. sandersoni</em> is much more common than is apparent from databases, likely due to misidentification as mimics <em>B. perplexus</em> and <em>B. vagans</em>. Our results provide evidence that habitat type can play a large role in pathogen load dynamics, but in ways that differ by pathogen type, and point to a need for consideration of habitat at both macro-ecological and local spatial scale</p>
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.