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РИС. 4. ROC-кривые и плоЩадь под ROC-кривой (AUC) для раЗных моделей. А. РеЗультаты для Xeropicta derbentina. B. РеЗультаты для Brephulopsis cylindrica. Красная кривая иллюстрирует покаЗатели модели для обучаюЩего набора, бледно-голубые линии — для тестовых наборов и отдельных моделей, толстая синяя линия — обЩие покаЗатели всех моделей. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 4. ROC-кривые и плоЩадь под ROC-кривой (AUC) для раЗных моделей. А. РеЗультаты для Xeropicta derbentina. B. РеЗультаты для Brephulopsis cylindrica. Красная кривая иллюстрирует покаЗатели модели для обучаюЩего набора, бледно-голубые линии — для тестовых наборов и отдельных моделей, толстая синяя линия — обЩие покаЗатели всех моделей.
FIG. 3 in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
FIG. 3. Principal component analysis (PCA). The dimensionality reduction technique represents multivariate data on the 2D plane thus showing their structure. Datapoint colors are the same as in Fig. 2.
РИС. 1. Точки находок видов на исследуемой территории. БаЗовая карта: береговая линия, речная сеть – Natural Earth @ naturalearthdata.com; рельеф – Terrain Tiles @ registry.opendata.aws/terrain-tiles; Экорегионы по Dinerstein E. et al. [2017]. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 1. Точки находок видов на исследуемой территории. БаЗовая карта: береговая линия, речная сеть – Natural Earth @ naturalearthdata.com; рельеф – Terrain Tiles @ registry.opendata.aws/terrain-tiles; Экорегионы по Dinerstein E. et al. [2017].
Figure. The phylogenetic tree showing the relationship among Brevibacillus parabrevis strains SA2.2 and TJ2.3, Bacillus licheniformis MG4.2, and their phylogenetically closest type strains. The GenBank accession numbers of the type strains and studied strains are shown following species names. Distance matrix was calculated by Kimura's 2-parameter model. The scale bar indicates 0.02 substitutions per nucleotide position. Alicyclobacillus pohliae AJ564766 served as an out-group. in Distribution of extracellular enzyme-producing bacteria in the digestive tracts of 4 brackish water fish species
Figure. The phylogenetic tree showing the relationship among Brevibacillus parabrevis strains SA2.2 and TJ2.3, Bacillus licheniformis MG4.2, and their phylogenetically closest type strains. The GenBank accession numbers of the type strains and studied strains are shown following species names. Distance matrix was calculated by Kimura's 2-parameter model. The scale bar indicates 0.02 substitutions per nucleotide position. Alicyclobacillus pohliae AJ564766 served as an out-group.
Fig. 2 in Parasite species co-occurrence patterns on Peromyscus: Joint species distribution modelling
Fig. 2. Results of variance partitioning for variation in ectoparasite prevalence explained by fixed and random effects for each ectoparasite species (columns). Explained variance presented for the constrained model for deer mice (n = 229 individuals). DM, deer mice; RBV, southern red-backed vole; WJM, woodland jumping mouse; PA, population abundance. Population abundance of small mammal species measured as captures per 100 trap nights. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Data from: Strategies of resource sharing in clonal plants: A conceptual model and an example of contrasting strategies in two closely related species
<p>These experimental data were collected to quantify amount of C and N translocated between mother and daughter ramets of two stoloniferous species. Data includes concentrations of 13-C and 15-N in plants samples originating from pulse-chase labelling, absolute amounts of the labels present, as well as dry mass of the samples. Details are described in the relevant paper.</p> <p> </p>
Linked collectors and determiners for: Taxonomic utility of niche models in validating species concepts: A case study in Anthophora (Heliophila) (Hymenoptera: Apidae).
Natural history specimen data linked to collectors and determiners held within, "Taxonomic utility of niche models in validating species concepts: A case study in Anthophora (Heliophila) (Hymenoptera: Apidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/1363c785-b3e0-4322-9283-a6d272748735">https://bionomia.net/dataset/1363c785-b3e0-4322-9283-a6d272748735</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/1363c785-b3e0-4322-9283-a6d272748735">https://gbif.org/dataset/1363c785-b3e0-4322-9283-a6d272748735</a>. Formatted as a Frictionless Data package.
Midpoint attractor models resolve the mid-elevation peak in Himalayan plant species richness
<p>The midpoint attractor models (MPA) of species richness integrate a unimodal environmental favourability gradient and neutral effects forced by geometric constraints and thus extend ecologically neutral mid-domain model. However, both alternative MPA algorithms assume that underlying environmental favourability peaks within the modeling domain. Here, we used elevational distribution data for 1054 plant species occurring in NW Himalaya to explore species richness gradients and MPA performance in species groups defined by biogeography, taxonomy and life form. MPA models achieved an excellent fit, but the two MPA algorithms produced contrasting estimates of midpoint attractor location, especially for species groups with richness originating in lowlands. Therefore, we propose a modification of the MPA model accounting for the environmental favourability peak outside the study domain to reflect these situations. Biogeographic origin was more decisive for midpoint attractor location than taxonomic or life-form classification, indicating relatively low climatic niche conservatism in plants.</p>
Figure S1 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figure S1. Bayesian consensus tree of the Mesobuthus caucasicus complex reconstructed from mitochondrial DNA sequences.
Figure 9 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figure 9. Phylogeny the Mesobuthus caucasicus complex reconstructed using mitochondrial DNA sequences. The Przewalski's scorpion (M. przewalskii) is deeply diverged from other species and the Chinese scorpion (M. martensii) belongs to the species complex. Node supports are shown by bootstrapping probabilities from 1000 replicates and Bayesian posterior probabilities.
Figures 1–8 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figures 1–8. Mesobuthus przewalskii stat. nov., from Qiemo, Xinjiang. 1. Male, dorsal view. 2. Male, ventral view. 3. Female, dorsal view. 4. Female, ventral view. 5. Male, dentition of pedipalp chela movable finger. 6. Male, dentition of pedipalp chela fixed finger. 7. Male, ventral aspect of genital operculum and pectines. 8. Female, ventral aspect of genital operculum and pectines. Scale bars: 1–4 = 5.0 mm; 5–8 = 2.0 mm.
Figure 11 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figure 11. Ecological niche models of Mesobuthus scorpions. Potential distribution areas for the Przewalski's scorpion M. przewalsii (purple) is shown together with the Chinese scorpion M. martensii (green) and other species of the M. caucasicus complex (yellow). The entire Tarim Basin and adjacent Gobi region are suitable for survival of M. przewalskii. No area to the west of the Tianshan Mountains and the Pamir Plateau is suitable for M. przewalskii, and similarly no area to the east of the Tianshan Mountains and the Pamir Plateau is suitable for other species of the M. caucasicus complex. There are overlaps in predicted suitable distribution areas between M. przewalskii and M. martensii along the northeast edge of the Qinghai-Tibet Plateau. The suitable areas in the Junggar Basin and to the north of the Tianshan Mountains are likely due to over prediction of the model, because M. przewalskii does not occur in these regions. Ecological niche model for M. martensii was adopted from Shi et al. 2007.
Figure 10 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figure 10. Phylogenetic network for the Mesobuthus caucasicus species complex. Although the interrelationships between species is poorly resolved, no reticulations have occurred in the most recent common ancestors for each species. The Przewalski's scorpion M. przewalskii is clearly diverged from other member of the species complex and warrants a species rank. The divergence of the Chinese scorpion M. martensii is comparable to the divergences among the members of the species complex.
Figure 3 in The emerging vertebrate model species for neurophysiological studies is Danionella cerebrum, new species (Teleostei: Cyprinidae)
Figure 3. RaxmltreeforthecoxIgeneofthefivespeciesof Danionella (upperlef) fromdifferentsampling locations (data set 1) and map (upper right) showing type localities (large circles) and locations of additional samples (small circles). Note that both species, D. cerebrum and D. translucida, co-occur at each other's type locality. Roadside canal at Hmawbi (lower lef), type locality of D. cerebrum, and Daikme Chaung (lower right), type locality of D. translucida, illustrating the typical turbid streams in which these two species occur. Map created with QGIS version 3.8.3-Zanzibar (http://www.qgis.org).
Figure 1 in The emerging vertebrate model species for neurophysiological studies is Danionella cerebrum, new species (Teleostei: Cyprinidae)
Figure 1. Danionellacerebrum. (a) male (ca. 10 mmSL) and (b) female (ca. 12 mmSL) inlife, notpreserved; note yellowish chromatophores dorsally on head, melanophores scattered in rows on body in both sexes, and eggs covered by large melanophores in female; (c) MTD 39985, paratype, 10.4 mm SL, male and (d) BMNH 2021.8.30.1, holotype, 12.6 mm SL, female (below), white arrows mark position of vent, which is shifed anteriorly to the pelvic fins in males; (e) Weberian apparatus in male, MTD 39992, paratype, 11.7 mm SL and (f) female, MTD 39992, paratype, 11.8 mm SL, in lateral view; the same in male (g) and female (h) in frontal view; (e) and (g) black arrowhead marks connection between lateral process and outer arm of os suspensorium, star marks connecting flanges between inner and outer arms of os suspensorium and red arrow marks posterior extension of inner arm of os suspensorium covering swimbladder dorsally. Abbreviations: cl, claustrum; dc, drumming cartilage; ios, inner arm of os suspensorium; nc, neural complex; oos, outer arm of os suspensorium; r, rib; sc, scaphium; sw, swimbladder.
Figure 4. Timetreeofthefivespeciesof Danionella illustratingrelationshipsof D in The emerging vertebrate model species for neurophysiological studies is Danionella cerebrum, new species (Teleostei: Cyprinidae)
Figure 4. Timetreeofthefivespeciesof Danionella illustratingrelationshipsof D. cerebrum (lef), differencesin external appearance of preserved specimens (middle), and sexual dimorphisms in the skeleton of the Weberian apparatus (right, double column) in cleared and double stained specimens. Preserved specimens (middle) from top: Danionelladracula, BMNH 2008.1.1.1, male, holotype, BMNH.1.1.2–99, female, paratype, D. priapus, BMNH 2009.9.9.1, male, holotype, BMNH 2009.9.9.2–37, paratype, female; D. translucida NRM 32235, male and female paratypes; D. mirifica, USNM 372848, male and female paratypes; D. cerebrum, MTD 39985, male, paratype, BMNH 2021.8.30.1, female, holotype. Cleared and stained specimens (scale bar 0.1 mm), males, lef column from top: D. dracula, BMNH 2008.1.1.100–119, 16.2 mm; D. priapus, BMNH 2009.9.9.38–43, 16.5 mm; D. translucida, MTD 39992, 9.8 mm; D. mirifica, USNM 372848, 13.2 mm; D. cerebrum, MTD 39986, 11.7 mm; black arrowheads mark connection between lateral process and outer arm of os suspensorium, black stars mark connecting flanges between inner and outer arms of os suspensorium, and red arrows marks posterior extension of inner arm of os suspensorium covering swimbladder dorsally. Females, right column from top: D. dracula, BMNH 2008.1.1.100–119, 14.7 mm; D. priapus, BMNH 2009.9.9.38–43, 14.8 mm; D. translucida, MTD 39992, 11.2 mm; D. mirifica, USNM 372848, 13.2 mm, D. cerebrum, MTD 39986, 11.7 mm.
Data for: Combining environmental niche models, multi-grain analyses, and species traits identifies pervasive effects of land use on butterfly biodiversity across Italy
<p><span>Understanding how species respond to human activities is paramount to ecology and conservation science, one outstanding question being how large-scale patterns in land use affect biodiversity. To facilitate answering this question, we propose a novel analytical framework that combines Environmental Niche Models, multi-grain analyses, and species traits. We illustrate the framework capitalizing on the most extensive dataset compiled to date for the butterflies of Italy (106,514 observations for 288 species), assessing how agriculture and urbanization have affected biodiversity of these taxa from landscape to regional scales (3–48 km grains) across the country while accounting for its steep climatic gradients.</span></p> <p><span>Multiple lines of evidence suggest pervasive and scale-dependent effects of land use on butterflies in Italy. While land use explained patterns in species richness primarily at grains ≤ 12 km, idiosyncratic responses in species highlighted "winners" and "losers" across human-dominated regions. Detrimental effects of agriculture and urbanization emerged from landscape (3-km grain) to regional (48-km grain) scales, disproportionally affecting small butterflies and butterflies with a short flight curve. Human activities have therefore reorganized the biogeography of Italian butterflies, filtering out species with poor dispersal capacity and narrow niche breadth not only from local assemblages but also from regional species pools. </span></p> <p><span>These results suggest that global conservation efforts neglecting large-scale patterns in land use risk falling short of their goals, even for taxa typically assumed to persist in small natural areas (e.g., invertebrates). Our study also confirms that consideration of spatial scales will be crucial to implementing effective conservation actions in the Post-2020 Global Biodiversity Framework. In this context, applications of the proposed analytical framework have broad potential to identify which mechanisms underlie biodiversity change at different spatial scales. </span></p> <p><span><em>Funding statement: </em>FR is supported by the PROBAE project "Protect butterflies across Europe through climate refugia" funded by the European Commission through Horizon 2020, Marie Skłodowska-Curie Actions (MSCA) individual fellowship, reintegration panel (Grant agreement ID: 101024579). Open Access Funding provided by Universita degli Studi di Torino within the CRUI-CARE Agreement.</span></p>
MetaTransformer trained species model
<p>Trained models of our MetaTransformer with size 13 k-mer embedding trained on species microbial data. </p>
Species distribution and abundance modelling with dynamicSDM: a case study analysis of the red-billed quelea (Quelea quelea).
<p><strong>GBIF_all_aves_2000_2020.csv</strong><br> A dataset containing e-Bird sampling events for all bird species across southern Africa between 2000-2020 (Fink et al., 2021, GBIF, 2021). <br> <br> Fink, D., T. Auer, A. Johnston, M. Strimas-Mackey, O. Robinson, S. Ligocki, W. Hochachka, L. Jaromczyk, C. Wood, I. Davies, M. Iliff, L. Seitz. 2021. eBird Status and Trends, Data Version: 2020; Released: 2021. Cornell Lab of Ornithology, Ithaca, New York. \doi{10.2173/ebirdst.2020}<br> GBIF.org (12 July 2021) GBIF Occurrence Download \doi{10.15468/dl.ppcu6q}</p> <p><strong>RBQ_full_analysis.R</strong></p> <p>An R script for the generation of dynamic species distribution and abundance models for nomadic bird, the red-billed quelea (<em>Quelea quelea</em>) using dynamicSDM package functions. </p> <p><strong>Unfiltered_quelea_occurrence.csv</strong><br> A dataset containing species occurrence and abundance records for the bird species, the red-billed quelea (<em>Quelea quelea</em>) between 1976-2021 (GBIF 2021 & GBIF 2022 & sources listed in Table 1). <br> <br> GBIF.org (12 July 2021) GBIF Occurrence Download \doi{10.15468/dl.ppcu6q}<br> <br> GBIF.org (25 July 2022) GBIF Occurrence Download \doi{10.15468/dl.k2kftv}<br> </p> <p><strong>Table S1. </strong>Red-billed quelea (<em>Quelea quelea</em>) occurrence and abundance data sources.</p> <table align="left"> <tbody> <tr> <td> <p><strong>Data type</strong></p> </td> <td> <p><strong>Sources</strong></p> </td> </tr> <tr> <td> <p><strong>Control operation </strong></p> </td> <td> <ul> <li>Information Core for Southern African Migrant Pests (ICOSAMP, 2001-2005).</li> <li>Centre for Overseas Pest Research (COPR), Natural History Museum, Tring.</li> <li>Botswana Ministries of Agriculture.</li> <li>Mozambique Ministry of Agriculture</li> </ul> </td> </tr> <tr> <td> <p><strong>Citizen science</strong></p> </td> <td> <ul> <li>Global Biodiversity Information Facility, including iNaturalist, eBird, South Africa Bird Atlas Project (SABAP) and South Africa Bird Ringing Unit (SAFRING) sources.</li> </ul> </td> </tr> <tr> <td> <p><strong>Independent research</strong></p> </td> <td> <ul> <li>EXCEL File "NfA-yearposRAC" (unpublished data set complied by R. A. Cheke, 2010).</li> </ul> </td> </tr> </tbody> </table>
Species detection histories used in Killion et al. (2023): Integrating Spaceborne Estimates of Structural Diversity of Habitat into Wildlife Occupancy Models
<p>Camera trap species detection histories used for occupancy models in "Integrating Spaceborne Estimates of Structural Diversity of Habitat into Wildlife Occupancy Models". </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.