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Figure 4 from: Degtjarenko P, Jüriado I, Mandel T, Tõrra T, Saag A, Scheidegger C, Randlane T (2019) Microsatellite based genetic diversity of the widespread epiphytic lichen Usnea subfloridana (Parmeliaceae, Ascomycota) in Estonia: comparison of populations from the mainland and an island. MycoKeys 58: 27-45. https://doi.org/10.3897/mycokeys.58.36557
Figure 4 Usnea subfloridana multilocus genotypes (Us02, Us03, Us04, Us05, Us06, Us08, Us09) and explanatory variables mean annual air temperature ('Temp') and the presence of thamnolic acid ('Tham') in a lichen sample in the bi-plot of the redundancy analysis (RDA) of the first and second axes.
Figure 5 from: Degtjarenko P, Jüriado I, Mandel T, Tõrra T, Saag A, Scheidegger C, Randlane T (2019) Microsatellite based genetic diversity of the widespread epiphytic lichen Usnea subfloridana (Parmeliaceae, Ascomycota) in Estonia: comparison of populations from the mainland and an island. MycoKeys 58: 27-45. https://doi.org/10.3897/mycokeys.58.36557
Figure 5 Sample populations of Usnea subfloridana and explanatory variables mean annual air temperature ('Temp') and geographical longitude of populations ('Long') in the bi-plot of the redundancy analysis (RDA) of the first and second axes. The shape of symbols indicates the geographical location of studied populations (square – south-eastern region of mainland, circle - western island and diamond – north-eastern region) and the size of symbols indicates the number of different alleles found in the studied populations.
Figure 3 in Characterization of a Small Population of the Orangeblack Hawaiian Damselfly (Megalagrion xanthomelas) in Anchialine Pools at Kaloko-Honokōhau National Historical Park, Hawai'i Island
Figure 3. Mean number of male and female Megalagrion xanthomelas observed at the seven core pools (A–G) and at all core pools combined (H) during June 2016–August 2017.
Figure 4 in Trapping Records of Fruit Fly Pest Species (Diptera: Tephritidae) on Oahu (Hawaiian Islands): Analysis of Spatial Population Trends
Figure 4. Mean captures per trap per day of C. capitata in trimedlure traps (2006–2008) at each trapping site on Oahu.
Figure 3 in Trapping Records of Fruit Fly Pest Species (Diptera: Tephritidae) on Oahu (Hawaiian Islands): Analysis of Spatial Population Trends
Figure 3. Mean captures per trap per day of B. dorsalis in methyl eugenol traps (2006–2008) at each trapping site on Oahu.
Figure 2 in Trapping Records of Fruit Fly Pest Species (Diptera: Tephritidae) on Oahu (Hawaiian Islands): Analysis of Spatial Population Trends
Figure 2. Mean captures per trap per day of B. cucurbitae in cue-lure traps (2006–2008) at each trapping site on Oahu.
Figure 1 in Population status and distribution assessment of Nicobar Long-Tailed Macaque Macaca Fascicularis Umbrosus (Miller, 1902) in Nicobar Group of Islands
Figure 1. Forest cover map of study area. Showing the different forest types across the Nicobar group of Islands. Forest cover map has been classified in to open-forest, moderate-dense forest, very dense forest, Scrubland, no forest and water bodies.
Figure 2 in Population status and distribution assessment of Nicobar Long-Tailed Macaque Macaca Fascicularis Umbrosus (Miller, 1902) in Nicobar Group of Islands
Figure 2. Elevation map of study area. SRTM 1-Arc Sec. Global data sets depicting elevation profiles across the Nicobar group of Islands. The colour ramp signifies the ranging from high to low elevation across the landscape, where red colour indicates the high elevation ranges and green showing the lower elevation ranges.
Evolutionary effects of geographic and climatic isolation between Rhododendron tsusiophyllum populations on the Izu Islands and mainland Honshu of Japan
<p>Geographic and environmental isolations of islands and the mainland offer excellent opportunity to investigate colonization and survival dynamics of island populations. We inferred and compared evolutionary processes and the demographic history of <i>Rhododendron tsusiophyllum</i>, in the Izu Islands and the much larger island Honshu, treated here as the mainland, using thousands of nuclear SNPs obtained by ddRAD-seq from eight populations of <i>R. tsusiophyllum</i> and three populations of <i>R. tschonoskii</i> as an outgroup. Phylogenetic relationships and their habitats suggest that <i>R. tsusiophyllum</i> had evolved and migrated from cold north to warm south regions. We detected clear genetic divergence among populations in three regions of Honshu and the Izu Islands, suggesting restricted migration between them due to isolated habitats on mountains even in the mainland. The three regions have different changes in effective population size, especially, genetic diversity and population size of the Izu Islands are small compared to the others. Further, habitats of populations in the Izu Islands are warmer than those in Honshu, suggesting that they have undergone adaptive evolution. Our study provides evidences of montane rather than insular isolation on genetic divergence, survival of populations and significance of adaptive evolution for island populations with small population size and low genetic diversity, despite close proximity to mainland populations.</p>
Figure 5 in Population dynamics and reproduction of the hermit crab Calcinus gaimardii (Anomura: Diogenidae) at Inhaca Island, southern Mozambique
Figure 5. Calcinus gaimardii (H. Milne Edwards, 1848). Relationship between egg number (EN) and female size (SL).
Data from: Reproductive tradeoffs and phenotypic selection change with body condition, but not with predation regime, across island lizard populations
<p>Tradeoffs between reproduction and survival are central to life-history theory and are expected to shape patterns of phenotypic selection, but the ecological factors structuring these tradeoffs and resultuant patterns of selection are generally unknown. We manipulated reproductive investment and predation regime in island populations of brown anole lizards (<em>Anolis sagrei</em>) to test (1) whether previously documented increases in the survival of experimentally non-reproductive females (OVX = ovariectomy) reflect the greater susceptibility of reproductive females (SHAM = control) to predation, and (2) whether phenotypic selection differs as a function of reproductive investment and predation regime. OVX females exceeded SHAM controls in growth, mass gain, and body condition, indicating pronounced energetic costs of reproduction. Although mortality was greatest in the presence of bird and snake predators, differences in survival between OVX and SHAM were unrealted to predation regime, as were patterns of natural selection on body size. Instead, we found that body condition at the conclusion of the experiment differed significantly across populations, suggesting that local environments varied in their ability to support mass gain and positive energy balance. As mean body condition improved across populations, the magnitude of the survival cost of reproduction increased, linear selection on body size shifted from positive to negative, and quadratic selection shifted from stabilizing to weakly disruptive. Our results suggest that reproductive tradeoffs and patterns of phenotypic selection in female brown anoles are more sensitive to inferred variation in environmental quality than to experimentally induced variation in predation.</p>
Figure 3 from: Ober K, Matthews B, Ferrieri A, Kuhn S (2011) The evolution and age of populations of Scaphinotus petersi Roeschke on Arizona Sky Islands (Coleoptera, Carabidae, Cychrini). ZooKeys 147: 183-197. https://doi.org/10.3897/zookeys.147.2024
Figure 3 - Phylogeny of Scaphinotus petersi dated using a Bayesian relaxed molecular clock in BEAST. Outgroups are removed to show greater detail. Specimen numbers are removed, but the mountain range from which they were collected is indicated. Branches are proportional to time in thousands of years. Shading indicates the two most recent glacial maxima. 95% confidence intervals for the ages of major clades in the tree are indicated with blue bars. The capital letters indicate population fragmentation between mountain ranges (see Table 3).
Figure 1 from: Ober K, Matthews B, Ferrieri A, Kuhn S (2011) The evolution and age of populations of Scaphinotus petersi Roeschke on Arizona Sky Islands (Coleoptera, Carabidae, Cychrini). ZooKeys 147: 183-197. https://doi.org/10.3897/zookeys.147.2024
Figure 1 - Study location A Scaphinotus petersi distribution is circled area. Habitat above 1830m is shown in black and between 1500 and 1830m is shown in grey B Shaded relief map of study area. Black dots denote sampling localities of Scaphinotus petersi used in this study (see Table 1) abbreviated as follows: P, Pinal Mountains; SC, Santa Catalina Mountains; PN, Pinaleño Mountains; and H, Huachuca Mountains. Figure courtesy of Sara Mitchell.
Figure 2 from: Ober K, Matthews B, Ferrieri A, Kuhn S (2011) The evolution and age of populations of Scaphinotus petersi Roeschke on Arizona Sky Islands (Coleoptera, Carabidae, Cychrini). ZooKeys 147: 183-197. https://doi.org/10.3897/zookeys.147.2024
Figure 2 - Maximum likelihood tree of Scaphinotus petersi populations from combined COI and ND1 data. Outgroups are removed to show greater detail. Specimen numbers are removed, but the mountain range from which they were collected is indicated. Support for branches is indicated by Bayesian Posterior Probability/Maximum Likelihood bootstrap values. Scale bar units are substitutions per site.
Figure 2 from: Colombo Ferreguetti Á, Pereira BC, Bergallo HG (2018) Assessing the population density of the spotted paca, Cuniculus paca, (Rodentia: Cuniculidae) on an Atlantic Forest island, southeastern Brazil. Zoologia 35: 1-5. https://doi.org/10.3897/zoologia.35.e23133
Figure 2 Plot of the detection function for spotted pacas based on the AIC selected Conventional Distance Sampling (CDS) model. Histogram represents the probability of detection for each distance interval. The curved line is the detection function, showing the probability that a spotted paca is observed as a function of distance from the transect line.
Figure 1 from: Colombo Ferreguetti Á, Pereira BC, Bergallo HG (2018) Assessing the population density of the spotted paca, Cuniculus paca, (Rodentia: Cuniculidae) on an Atlantic Forest island, southeastern Brazil. Zoologia 35: 1-5. https://doi.org/10.3897/zoologia.35.e23133
Figure 1 Ilha Grande in the state of Rio de Janeiro, Brazil and location of the transects. Black triangle representing the Abraão village.
Data from: Population genomic analysis uncovers African and European admixture in Drosophila melanogaster populations from the southeastern United States and Caribbean Islands
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Data from: High genetic diversity in the offshore island populations of the tephritid fruit fly Bactrocera dorsalis
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Data from: Measuring population differentiation using GST or D? A simulation study with microsatellite DNA markers under a finite island model and nonequilibrium conditions
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Evolutionary effects of geographic and climatic isolation between Rhododendron tsusiophyllum populations on the Izu Islands and mainland Honshu of Japan
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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.