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Do the predicted suitability scores from species distribution models correlate with species performance on-ground?
<p>Species distribution models are a very popular statistical tool for inferring potential distribution range of species across space and time and are thought to be a good predictor for habitat suitability. Some studies have suggested that if these models are reliable, predicted habitat suitability (PHS) should relate to species traits visualization, growth potential, body size, abundance. We validated this hypothesis by estimating association between the PHS and species abundance for 17 avian species endemic to the Western Ghats - Sri Lanka biodiversity hotspot. Additionally, we compared the PHS of sites where species were detected in both seasons (wet and dry) against sites where they were detected in the dry season alone. As a proxy for abundance, we estimated single-season occupancy estimates (ψ) using detection/non-detection data from multiple visits to the survey sites. We report significant and positive PHS-ψ correlation, though the strength of this association varied across species and models. Half of the species showed higher suitability scores for the sites where they were detected year round. The results presented here suggest that the predictive models can be used as a proxy for habitat quality, in addition to inferring the potential distribution.</p>
Figure 7 in Chorion surface ultrastructure of loach Misgurnus anguillicaudatus: adaptation to the environment and correlation with the reproductive strategy
Figure 7. Internal pattern of chorion after water contact. Abbreviation: r, ridge. Magnification, × 1500.
Figure 8 in Chorion surface ultrastructure of loach Misgurnus anguillicaudatus: adaptation to the environment and correlation with the reproductive strategy
Figure 8. Internal characters of egg membrane after stickiness removal. Abbreviation: m, microvilli. Magnification, × 3000.
Figure 5 in Chorion surface ultrastructure of loach Misgurnus anguillicaudatus: adaptation to the environment and correlation with the reproductive strategy
Figure 5. Micropyle at higher magnification. Abbreviations: mc, micropylar canal; sg, sinistral groove. Magnification, × 2500.
Figure 2 in Chorion surface ultrastructure of loach Misgurnus anguillicaudatus: adaptation to the environment and correlation with the reproductive strategy
Figure 2. Chorion outer surface of M. anguillicaudatus egg. Abbreviation: p, pore. Magnification, × 7000.
Figure 4 in Chorion surface ultrastructure of loach Misgurnus anguillicaudatus: adaptation to the environment and correlation with the reproductive strategy
Figure 4. Micropyle at the animal pole. Abbreviations: mp, micropyle; hp, hollow pit. Magnification, × 120.
Figure 3 in Chorion surface ultrastructure of loach Misgurnus anguillicaudatus: adaptation to the environment and correlation with the reproductive strategy
Figure 3. Envelope surface of loach egg after treatment with trypsin solution. Abbreviations: f, bud-like fillings; p, pore. Magnification, × 7500.
Correlated decision making across multiple phases of olfactory guided search in Drosophila
<p>All motile organisms must search for food, often requiring the exploration of heterogeneous environments across a wide range of spatial scales. Recent field and laboratory experiments with the fruit fly, <i>Drosophila</i>, have revealed that they employ different strategies across these regimes, including kilometer scale straight-path flights between resource clusters, zig-zagging trajectories to follow odor plumes, and local search on foot after landing. However, little is known about the extent to which experiences in one regime might influence decisions in another. To determine how a flies' odor plume tracking during flight is related to their behavior after landing, I tracked the behavior of individually labelled fruit flies as they explored an array of three odor emitting, but food-barren, objects. The distance flies travelled on the objects in search of food was correlated with the time elapsed between their visits, suggesting that their in-flight plume tracking and on-foot local search behaviors are interconnected through a lossy memory-like process.</p>
Figure 1 in An overview of female reproductive traits in South American Mabuya (Squamata, Scincidae), with emphasis on brood size and its correlates
Figure 1. Relationship between mean brood size and maximum female size (r = 0.71, p <0.05, n = 10) in South American Mabuya species. SVL, snout–vent length.
Figure 2 in An overview of female reproductive traits in South American Mabuya (Squamata, Scincidae), with emphasis on brood size and its correlates
Figure 2. Relationship between maximum brood size and maximum female size (r = 0.75, p = 0.01, n = 10) in South American Mabuya species. SVL, snout–vent length.
Data from: Timing of spring departure of long distance migrants correlates with previous year's conditions at their breeding site
<p>Precise timing of the migration is crucial for animals targeting seasonal resources at locations encountered across their annual cycle. Upon departure, long distance migrants need to anticipate unknown environmental conditions at their arrival site, and they do zkzdsxso with their internal annual clock. Here, we tested the hypothesis that long distance migrants synchronize their circannual clock according to the phenology of their environment during the breeding season, and therefore adjust their spring departure date according to the conditions encountered at their breeding site the year before. To this end, we used tracking data of Eurasian curlews from different locations and combined movement data with satellite-extracted green-up dates at their breeding site. Spring departure date was better explained by green-up date of the previous year, while arrival date at the breeding site was better explained by latitude and longitude of the breeding site, suggesting that other factors impacted migration timing <i>en route</i>. On a broader temporal scale, our results suggest that long distance migrants may be able to adjust their migration timing to advancing spring dates in the context of climate change. </p>
Figure 15 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 15. Leptus molochinus (C. L. Koch, 1837), larva, scanning electron micrograph. Tarsus II termination.
Figure 13 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 13. Leptus molochinus (C. L. Koch, 1837), larva, scanning electron micrograph. Vestigiala on genu II and solenidion on tibia II.
Figure 12 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 12. Leptus molochinus (C. L. Koch, 1837), larva, scanning electron micrograph. Odontus and palp tarsus.
Figure 11 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 11. Leptus molochinus (C. L. Koch, 1837), larva, scanning electron micrograph. Mouth and terminal segments of palps.
Figure 9 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 9. Leptus molochinus (C. L. Koch, 1837), larva. Ventral side of the body (legs omitted beyond trochanters).
Figure 8 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 8. Leptus molochinus (C. L. Koch, 1837), larva. Dorsal side of the body (legs omitted beyond trochanters).
Figure 6 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 6. Leptus molochinus (C. L. Koch, 1837), adult, female. Setae: (A) dorsal opisthosomal seta; (B–J) normal and specialised setae on legs: (B–F) normal setae; (G) spinala; (H) vestigiala; (I) solenidion; (J) famulus.
Figure 5 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 5. Leptus molochinus (C. L. Koch, 1837), adult, female. Dorsal opisthosomal setae, lateral view.
Figure 3 in Correlation of heteromorphic life instars in terrestrial Parasitengona mites and its impact on taxonomy - the case of Leptus molochinus (C. L. Koch, 1837) and Leptus ignotus (Oudemans, 1903) (Acari: Trombidiformes: Prostigmata: Erythraeidae)
Figure 3. Leptus molochinus (C. L. Koch, 1837), adult, female. Crista metopica and eyes (chaetotaxy beyond crista metopica omitted).
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.