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230 results for “biogeographic patterns”
Figure 1 in Biogeographic patterns of tenebrionid beetles (Coleoptera, Tenebrionidae) on four island groups in the south Aegean Sea
Figure 1. Map of the island group of Santorini, its relative position in the Aegean and the sampling stations (crosses5pitfall trapping stations).
Figure 6 in Biogeographic patterns of tenebrionid beetles (Coleoptera, Tenebrionidae) on four island groups in the south Aegean Sea
Figure 6. The UPGMA tree based on the results of Cosine coefficient applied on the transformed, non-binary data matrix. The prefixes SA, AS, KA and NI on the names of the islands, indicate the island group they belong (SA, Santorini group; AS, Astypalaia group; KA, Kalymnos group; NI: Nisyros group). The underlined names represent the main islands in each group.
Figure 5 in Biogeographic patterns of tenebrionid beetles (Coleoptera, Tenebrionidae) on four island groups in the south Aegean Sea
Figure 5. The UPGMA tree based on the results of Pearson's Φ coefficient applied on binary data. The prefixes SA, AS, KA and NI on the names of the islands, indicate the island group they belong (SA, Santorini group; AS, Astypalaia group; KA, Kalymnos group; NI: Nisyros group). The underlined names represent the main islands in each group.
Figure 4. A in Small islands and large biogeographic barriers have driven contrasting speciation patterns in Indo-Pacific sunbirds (Aves: Nectariniidae)
Figure 4. A, geographic distribution of Leptocoma aspasia haplotypes in Wallacea and the Sahul Shelf. Each circle represents an island and the fractions within the circle the haplotypes found on that island, proportioned to represent the frequency of each haplotype. The haplotypes are named according to the species-level divisions suggested by ABGD and coloured to represent the clades supported by our phylogenetic analyses. B, TCS haplotype network of Leptocoma haplotypes. Each circle represents a unique ND2–ND3 haplotype, sized to represent how many birds carried that haplotype. The hatch marks represent mutations between haplotypes, also given as numbers in brackets for the wider divergences. The unfilled, white nodes represent hypothetical ancestral states. C, Bayesian consensus tree of Leptocoma haplotypes. Nodes are labelled with Bayesian probabilities.
Figure 1. A in Small islands and large biogeographic barriers have driven contrasting speciation patterns in Indo-Pacific sunbirds (Aves: Nectariniidae)
Figure 1. A, map of the Indo-Pacific region with study regions marked inside boxes. The range of the olive-backed sunbird is shaded horizontally in yellow, the range of the black sunbird vertically in purple, both according to BirdLife International. Seas deeper than 200 m are represented by a darker blue. Biogeographic barriers (Wallace, 1863; Lydekker, 1896) are represented with red lines. B, map of south-east Sulawesi and the Wakatobi Islands in Wallacea, with olive-backed sunbird sampling sites marked with yellow downward-pointing triangles, black sunbird sampling sites with purple upward-pointing triangles. C, map of Australia and New Guinea on the Sahul Shelf, with olive-backed sunbird sampling sites marked with yellow downward-pointing triangles, black sunbird sampling sites with purple upward-pointing triangles. D, map of the Bismarck Archipelago with the sampling site of the B10K black sunbird marked with a purple triangle.
Figure 2 in Small islands and large biogeographic barriers have driven contrasting speciation patterns in Indo-Pacific sunbirds (Aves: Nectariniidae)
Figure 2. Simplified version of a combined maximum likelihood (ML) and Bayesian phylogenetic tree of Cinnyris and Leptocoma species sampled in Wallacea and the Sahul Shelf. In this figure, the outgroup is omitted and each major clade in the data is collapsed into a single branch. Tips representing focal populations are marked with coloured circles. Nodes are labelled with Bayesian probability/ ML bootstraps. Full versions of the ML and Bayesian trees, including all outgroup taxa, are provided in the Supporting Information (Figs S7, S8).
Figure 3. A in Small islands and large biogeographic barriers have driven contrasting speciation patterns in Indo-Pacific sunbirds (Aves: Nectariniidae)
Figure 3. A, geographic distribution of Cinnyris jugularis (sensu Gill et al., 2022) haplotypes in Wallacea and the Sahul Shelf. Each circle represents an island and the fractions within the circle the haplotypes found on that island, proportioned to represent the frequency of each haplotype. The haplotypes are named according to the species-level divisions suggested by ABGD and coloured to represent the clades supported by our phylogenetic analyses. B, TCS haplotype network of Cinnyris haplotypes. Each circle represents a unique ND2–ND3 haplotype, sized to represent how many birds carried that haplotype. The hatch marks represent mutations between haplotypes, also given as numbers in brackets for the wider divergences. The unfilled, white nodes represent hypothetical ancestral states. C, Bayesian consensus tree of Cinnyris haplotypes. Nodes are labelled with Bayesian probabilities.
Figure 5. A in Small islands and large biogeographic barriers have driven contrasting speciation patterns in Indo-Pacific sunbirds (Aves: Nectariniidae)
Figure 5. A, map of the Indo-Pacific with the range of the olive-backed sunbird shaded, as currently recognized by BirdLife International. Sampling sites of the birds included in our 697 bp partial ND2 analysis are marked with different triangles, according to the species they were assigned to by ABGD. Currently recognized subspecies are labelled (Gill et al., 2022). B, mean genetic distance (uncorrected p-distance) between each of the species recognized by ABGD, based on a 697 bp partial ND2 alignment. C, simplified version of a combined maximum likelihood (ML) and Bayesian phylogenetic tree of 697 bp of olive-backed sunbird ND2. In this figure the outgroup is omitted and each of the ABGD species is collapsed into a single branch. Nodes are labelled with Bayesian probability/ ML bootstraps.
Data from: Crossing the uncrossable: novel trans-valley biogeographic patterns revealed in the genetic history of low dispersal mygalomorph spiders (Antrodiaetidae, Antrodiaetus) from California
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Data from: Genome-wide markers untangle the green-lizard radiation in the Aegean Sea and support a rare biogeographical pattern
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Data from: Global biogeographic patterns in bipolar moss species
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Data from: The world’s biogeographical regions revisited: global patterns of endemism in Tipulidae (Diptera)
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Regional and local environment drive biogeographic patterns in intertidal microorganisms
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Data from: Pleistocene extinctions as drivers of biogeographical patterns on the easternmost Canary Islands
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Data from: Contrasting microbial biogeographical patterns between anthropogenic subalpine grasslands and natural alpine grasslands
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Data from: Biogeographic patterns of Iranian Lepidoptera: A framework for conservation
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Data from: Exploring patterns of beta-diversity to test the consistency of biogeographical boundaries: a case study across forest plant communities of Italy
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Data from: Elucidating biogeographical patterns in Australian native canids using genome wide SNPs
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Data from: Metagenetic community analysis of microbial eukaryotes illuminates biogeographic patterns in deep-sea and shallow water sediments
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The preservation potential of terrestrial biogeographic patterns
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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.