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538 results for “population distribution”
Fig. 1 in Analysis of the spatial distribution patterns of the land snail populations: a geostatistic method approach
Fig. 1. Diagram of the abundance distribution of the land snail B. cylindrica: A – site 1, 2010; B – site 2, 2011; C – site 4, 2012; D – site 5, 2012 (Х and Y axes presented in meters; abundance proportional to sphere sizes).
23E. Rhinella margaritifera. Male.Triunfo, Bolivar.This population could represent R in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
23E. Rhinella margaritifera. Male.Triunfo, Bolivar.This population could represent R. martyi. Photo: César Barrio-Amorós.
Fig. 1 in On the Critically Endangered Cofre de Perote Salamander (Isthmura naucampatepetl): discovery of a new population in Puebla, Mexico, and update of its known distribution
Fig. 1. Distribution maps of Isthmura naucampatepetl. Black circles represent published records, star represents the new population in the Municipality of Chignautla, Puebla, Mexico. The photograph shows the habitat at the new population. Photo by L. Fernández-Badillo.
Fig. 2 in On the Critically Endangered Cofre de Perote Salamander (Isthmura naucampatepetl): discovery of a new population in Puebla, Mexico, and update of its known distribution
Fig. 2. Color patterns of each captured Isthmura naucampatepetl individual. Photo numbers correspond to the specimen numbers given in Table 1. Photo 27 is a ventral view of the chins of an adult female (left) and an adult male (right), showing the male mentonian gland. Photos by L. Fernández-Badillo.
Рис. 1. Диаграммы распределениЯ обилиЯ наЗемного моллюска B. cylindrica: A – участок № 1, 2010 г.; B – участок № 2, 2011 г.; C – участок № 4, 2012 г.; D – участок № 5, 2012 г. (единицы иЗмерениЯ осей Х и Y даны в метрах; численность особей пропорциональна раЗмерам Шариков). in Analysis of the spatial distribution patterns of the land snail populations: a geostatistic method approach
Рис. 1. Диаграммы распределениЯ обилиЯ наЗемного моллюска B. cylindrica: A – участок № 1, 2010 г.; B – участок № 2, 2011 г.; C – участок № 4, 2012 г.; D – участок № 5, 2012 г. (единицы иЗмерениЯ осей Х и Y даны в метрах; численность особей пропорциональна раЗмерам Шариков).
Figure 2 in Indotyphlops braminus (Daudin, 1803): distribution and oldest record of collection dates in Oceania, with report of a newly established population in French Polynesia (Tahiti Island, Society Archipelago)
Figure 2. Anterior ventral area of Indotyphlops braminus MNHN-RA 2015.0057 showing the whitish gular coloration. Picture: I. Ineich.
Figure 1 in Indotyphlops braminus (Daudin, 1803): distribution and oldest record of collection dates in Oceania, with report of a newly established population in French Polynesia (Tahiti Island, Society Archipelago)
Figure 1. Two introduced specimens of Indotyphlops braminus from Tahiti Island in French Polynesia. MNHN-RA 2015.0058 above and MNHN-RA 2015.0057 below. Scale bar: 1cm. Picture: I. Ineich.
Data from: Forecasting animal distribution through individual habitat selection: Insights for population inference and transferable predictions
<p>Habitat selection models frequently use data collected from a small geographic area over a short window of time to extrapolate patterns of relative abundance to unobserved areas or periods of time. However, these types of models often poorly predict how animals will use habitat beyond the place and time of data collection because space-use behaviors vary between individuals and are context-dependent. Here, we present a modelling workflow to advance predictive distribution performance by explicitly accounting for individual variability in habitat selection behavior and dependence on environmental context. Using global positioning system (GPS) data collected from 238 individual pronghorn, (<em>Antilocapra americana</em>), across 3 years in Utah, we combine individual-year-season-specific exponential habitat-selection models with weighted mixed-effects regressions to both draw inference about the drivers of habitat selection and predict space-use in areas/times where/when pronghorn were not monitored. We found a tremendous amount of variation in both the magnitude and direction of habitat selection behavior across seasons, but also across individuals, geographic regions, and years. We were able to attribute portions of this variation to season, movement strategy, sex, and regional variability in resources, conditions, and risks. We were also able to partition residual variation into inter- and intra-individual components. We then used the results to predict population-level, spatially and temporally dynamic, habitat-selection coefficients across Utah, resulting in a temporally dynamic map of pronghorn distribution at a 30x30m resolution but an extent of 220,000km2. We believe our transferable workflow can provide managers and researchers alike a way to turn limitations of traditional habitat selection models - variability in habitat selection - into a tool to understand and predict species-habitat associations across space and time.</p>
Figure 4 in Within-plant distribution and rapid assessment of sugarcane rust mite population on sugarcane canopy
Figure 4 Relationship between sugarcane rust mite density and counting speed of the imprinting technique.
Figure 3 in Within-plant distribution and rapid assessment of sugarcane rust mite population on sugarcane canopy
Figure 3 Within-plant distribution of sugarcane rust mite population based on the imprinting tech- nique (mean ± SEM). The numbers within brackets are the proportions of mite populations within plants. Means across leaves with the same capital letters are not significantly different and means with the same lower letters on a given leaf position are not significantly different (Tukey,P <0.05).
Figure 5 in Within-plant distribution and rapid assessment of sugarcane rust mite population on sugarcane canopy
Figure 5 Physiological parameters of sugarcane canopy (mean±SEM).A=photosynthetic rate, gsw =stomatal conductance,Ci =intercellular CO2, E=transpiration, WUE=water use efficiency.
Fig. 1 in Distribution and Occurrence of the Neogregarine Pathogen, Ophryocystis anatoliensis (Apicomplexa) in Populations of Chrysomela populi L. (Coleoptera: Chrysomelidae)
Fig. 1. Infected (bold) and non-infected localities where Crysomela populi adults and larvae were collected in Turkey.
Fig. 2 in Distribution and Occurrence of the Neogregarine Pathogen, Ophryocystis anatoliensis (Apicomplexa) in Populations of Chrysomela populi L. (Coleoptera: Chrysomelidae)
Fig. 2. Ophryocystis anatoliensis infection levels in C. populi populations in Turkey during the three years.
Рис. 3. РаспреΑеΛение чайковых птиц (А — тихоокеанская чайка, Б — восточносибирская чайка, В — бургомистр, Г — моевка) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/ км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 3. Distribution of larids — (А) slaty-backed gull, (Б) Vega gull, (В) glaucous gull, (Г) blacklegged kittiwake — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects, dotted line indicates a 200 m isobath in Population of seabirds in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan during the winter-spring period of 2020
Рис. 3. РаспреΑеΛение чайковых птиц (А — тихоокеанская чайка, Б — восточносибирская чайка, В — бургомистр, Г — моевка) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/ км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 3. Distribution of larids — (А) slaty-backed gull, (Б) Vega gull, (В) glaucous gull, (Г) blacklegged kittiwake — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects, dotted line indicates a 200 m isobath
Рис. 2. РаспреΑеΛение трубконосых птиц (А — темноспинный аΛьбатрос, Б — гΛупыш, В — тонкокΛювый буревестник, Г — сизая качурка) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 2. Distribution of tubenoses — (А) Laysan albatross, (Б) Northern fulmar, (В) shorttailed shearwater, (Г) fork-tailed storm-petrel — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects; dotted line indicates a 200 m isobath in Population of seabirds in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan during the winter-spring period of 2020
Рис. 2. РаспреΑеΛение трубконосых птиц (А — темноспинный аΛьбатрос, Б — гΛупыш, В — тонкокΛювый буревестник, Г — сизая качурка) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 2. Distribution of tubenoses — (А) Laysan albatross, (Б) Northern fulmar, (В) shorttailed shearwater, (Г) fork-tailed storm-petrel — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects; dotted line indicates a 200 m isobath
Рис. 4. РаспреΑеΛение чистиковых птиц (А — тонкокΛювая и тоΛстокΛювая кайры, Б — боΛьшая конюга, В — конюга-крошка, Г — топорок) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 4. Distribution of alcids — (А) common and thick-billed murres, (Б) crested auklet, (В) least auklet, (Г) tufted puffin — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects, dotted line indicates a 200 m isobath in Population of seabirds in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan during the winter-spring period of 2020
Рис. 4. РаспреΑеΛение чистиковых птиц (А — тонкокΛювая и тоΛстокΛювая кайры, Б — боΛьшая конюга, В — конюга-крошка, Г — топорок) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 4. Distribution of alcids — (А) common and thick-billed murres, (Б) crested auklet, (В) least auklet, (Г) tufted puffin — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects, dotted line indicates a 200 m isobath
Figure 3 in Phylogeographic affinities, distribution and population status of the non-native Asian pond mussels Sinanodonta lauta and S. woodiana in Kazakhstan
Figure 3. Shells of Sinanodonta lauta and the temperate invasive lineage of S. woodiana from Kazakhstan. A-C) S. lauta, irrigation channel of the Ili River near Topar settlement [specimens RMBH biv764_7, RMBH biv763_1, and RMBH biv763_5, respectively]. D-F) Temperate invasive lineage of S. woodiana, Kapchagay Reservoir [specimens RMBH biv762_3, RMBH biv762_5, and RMBH biv762_2, respectively]. Scale bar = 20 mm. (Photo: Ekaterina Konopleva).
Figure 4 in Phylogeographic affinities, distribution and population status of the non-native Asian pond mussels Sinanodonta lauta and S. woodiana in Kazakhstan
Figure 4. Shell morphometry and age of Sinanodonta lauta (N = 20) and the temperate invasive lineage of S. woodiana (N = 10) from Kazakhstan. A) Shell length vs shell height scatterplot. B) Shell length vs shell width scatterplot. C) Shell length vs age scatterplot. D) Shell elongation index vs shell convexity index scatterplot.
Figure 2 in Phylogeographic affinities, distribution and population status of the non-native Asian pond mussels Sinanodonta lauta and S. woodiana in Kazakhstan
Figure 2. Habitat of a viable population of Sinanodonta lauta in Kazakhstan: irrigation channel of the Ili River near Topar settlement. (Photo: Ilya Vikhrev).
Figure 1 in Phylogeographic affinities, distribution and population status of the non-native Asian pond mussels Sinanodonta lauta and S. woodiana in Kazakhstan
Figure 1. Ranges and population status of Sinanodonta lauta and the temperate invasive lineage of S. woodiana in Middle Asia. The circles indicate recent well-established populations, and the squares indicate old unconfirmed records of S. lauta (green) and S. woodiana (red). The green star indicates the site of putative initial introduction of S. lauta to Kazakhstan between 1961 and 1971. The color filling indicates freshwater basins, in which non-native populations of S. lauta and S. woodiana (light green) and S. woodiana (pink) were established. The species occurrence data are presented in Table 1.
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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.