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332 results for “Ecological niches”
Figure 2 in Remote sensing and citizen science to characterize the ecological niche of an endemic and endangered Costa Rican poison frog
Figure 2. Land cover classification of the study area in the South Pacific of Costa Rica for 2019 using Sentinel-2 spatial data.
Figure 1 in Remote sensing and citizen science to characterize the ecological niche of an endemic and endangered Costa Rican poison frog
Figure 1. Map of the study area in the South Pacific of Costa Rica (1:1,250,000 scale and Coordinate Reference System (CRS) WGS84) for the analysis of the ecological niche of P. vittatus using data generated during 2020. Main towns are shown. Large protected areas are represented by their management category: 1: Corcovado National Park; 2: Piedras Blancas National Park; 3: Golfo Dulce Forest Reserve; 4: Paso de la Danta Biological Corridor. Sources: Costa Rica Atlas 2014, Costa Rica Conservation Areas National System (SINAC) 2016 and 2020. Photograph of Phyllobates vittatus by Marina Garrido-Priego.
Figure 3 in Remote sensing and citizen science to characterize the ecological niche of an endemic and endangered Costa Rican poison frog
Figure 3. Relative niche suitability for Phyllobates vittatus across its distribution in the South Pacific of Costa Rica. The suitability map was generated during 2020 through the combination of eleven different environmental predictors, with elevation, forest percentage, distance to lakes and distance to ASADAS explaining the greatest proportion of the variance. The legend shows niche suitability ranging from low suitability (0; white) to high suitability (1; dark green). We represent in white high-altitude areas (>1500 m) and large plantations identified during the classification of the land cover, which were not included in the model. This prediction was made with a model built using a 5 km buffer area around the known occurrence points. Large protected areas are represented by their management category: 1: Corcovado National Park; 2: Piedras Blancas National Park; 3: Golfo Dulce Forest Reserve; 4: Paso de la Danta Biological Corridor. Sources: Costa Rica Atlas 2014, Costa Rica Conservation Areas National System (SINAC) 2016 and 2020. This map is at a 1:1,150,000 scale and CRS WGS84.
Data for "Completing the speciation cycle: Ecological niches and traits predict local species coexistence in birds across the globe"
<p>These are files to replicate all analyses in our article:</p> <p>A data file in xlsx format.</p> <p>A phylogeny in nexus format.</p> <p>An R code for analyses.</p>
Data from: Do ecological niche models accurately identify climatic determinants of species ranges?
Defining species' niches is central to understanding their distributions and is thus fundamental to basic ecology and climate change projections. Ecological niche models (ENMs) are a key component of making accurate projections and include descriptions of the niche in terms of both response curves and rankings of variable importance. In this study, we evaluate Maxent's ranking of environmental variables based on their importance in delimiting species' range boundaries by asking whether these same variables also govern annual recruitment based on long-term demographic studies. We found that Maxent-based assessments of variable importance in setting range boundaries in the California tiger salamander (Ambystoma californiense; CTS) correlate very well with how important those variables are in governing ongoing recruitment of CTS at the population level. This strong correlation suggests that Maxent's ranking of variable importance captures biologically realistic assessments of factors governing population persistence. However, this result holds only when Maxent models are built using best-practice procedures and variables are ranked based on permutation importance. Our study highlights the need for building high-quality niche models and provides encouraging evidence that when such models are built, they can reflect important aspects of a species' ecology.
Figure 1 in Distribution of the meadow lizard in Europe and its realized ecological niche model
Figure 1. Distribution map of the meadow lizard (Darevskia praticola) in south-eastern Europe given on an MGRS UTM 10 × 10 km grid scale. A small overview map shows the study region and the two separate parts of the meadow lizard distribution – separate geographic units and evolutionary lineages of the species (modified from Agasyan et al. 2009). Letters on the distribution map refer to the names of larger (100 × 100 km) MGRS squares. Occurrence records were compiled from a large literature survey and our own data (see Supplemental material 1) and classified on the map according to the time frame of the findings.
Figure 2 in Distribution of the meadow lizard in Europe and its realized ecological niche model
Figure 2. Habitat suitability maps for the meadow lizard (Darevskia praticola) in south-eastern Europe given separately for the low resolution (a) and the high resolution ecological niche model (b). Training points used for fitting the ecological niche models are represented with white dots, while the discarded occurrences are shown as '×' signs and placed for the overall visual representation of the model accuracy.
Figure 3 in Distribution of the meadow lizard in Europe and its realized ecological niche model
Figure 3. Examples showing details from the forest cover (Vegetation Continuous Fields layer) and the Maxent's habitat suitability map for the meadow lizard (Darevskia praticola). The maps show two localities: (a) a part of a fragmented forest area in southern Romania where the species occurs, and (b) an area near the Danube River along the border between Serbia and Romania, which is one of the places of greater habitat suitability for this species. The maps also show the difference between the low (upper images) and high (lower images) resolution of both the VCF layer and the habitat suitability.
Figure 7 in Talitrid amphipods (Crustacea: Amphipoda: Talitridae) and the driftwood ecological niche: a morphological and molecular study
Figure 7. Scattergram and fitted linear regressions as in Figure 4. Pl3 ExL, third pleopod exopod length in mm.
Figure 4 in Talitrid amphipods (Crustacea: Amphipoda: Talitridae) and the driftwood ecological niche: a morphological and molecular study
Figure 4. Scattergram and fitted linear regressions of Macarorchestia remyi from Principina a Mare, Italy (filled diamonds) and Macarorchestia roffensis (open squares) from the Medway estuary, UK. TBL, total body length in mm; ED, eye diameter in mm.
Figure 3 in Talitrid amphipods (Crustacea: Amphipoda: Talitridae) and the driftwood ecological niche: a morphological and molecular study
Figure 3. Non-metric multidimensional scaling plot of Bray–Curtis similarity indices based on Kimura two-parameter (K2P) distances between all talitrids considered in the study. The distance between symbols is proportional to the similarity between samples. (A) Values based on the 500-bp alignment; (B) values based on the 84-bp long alignment. Macarorchestia spp. (MMA, MRL, MRU, MRV, MRW) are marked in light grey. The putative new species (NTW) is marked in dark grey.
Figure 2 in Talitrid amphipods (Crustacea: Amphipoda: Talitridae) and the driftwood ecological niche: a morphological and molecular study
Figure 2. Frequency distribution of mitochondrial DNA for cytochrome oxidase I (mt-COI) Kimura two-parameter (K2P) distances for pairwise comparisons within the family Talitridae (black) and the genera Macarorchestia (white) and Orchestia (grey). Values are reported for: (A) 500-bp long alignment (data include only M. remyi for the genus Macarorchestia); (B) 84-bp long alignment (data include all three Macarorchestia species).
Figure 6 in Talitrid amphipods (Crustacea: Amphipoda: Talitridae) and the driftwood ecological niche: a morphological and molecular study
Figure 6. Scattergram and fitted linear regressions as in Figure 4. A2 FA, second antenna flagellum article count.
Figure 5 in Talitrid amphipods (Crustacea: Amphipoda: Talitridae) and the driftwood ecological niche: a morphological and molecular study
Figure 5. Scattergram and fitted linear regressions as in Figure 4. Pl3 BA, third pleopod basis length in mm.
Figure 8 in Talitrid amphipods (Crustacea: Amphipoda: Talitridae) and the driftwood ecological niche: a morphological and molecular study
Figure 8. Scattergram of eye diameter in mm (ED) on total body length in mm (TBL) in for Macarorchestia martini (filled triangles) and an unknown species (open circles). The fitted regression line is for the unknown species only.
Figure 6. Identity test between L. laeta and L in Ecological niche divergence between the brown recluse spiders Loxosceles laeta and L. surca (Sicariidae) in Chile
Figure 6. Identity test between L. laeta and L. surca in Chile. The expected niche area is significantly out of the observed niche between them.
Figure 4 in Ecological niche divergence between the brown recluse spiders Loxosceles laeta and L. surca (Sicariidae) in Chile
Figure 4. Environmental suitability map for Loxosceles surca and Loxosceles laeta under Maxent algorithm. Colours represent different ranges of probabilities of presence (high probability: 0.75– 1.0). (a) Potential distribution of Loxosceles surca. (b) Potential distribution of Loxosceles laeta.
Figure 5 in Ecological niche divergence between the brown recluse spiders Loxosceles laeta and L. surca (Sicariidae) in Chile
Figure 5. Precipitations and annual mean temperatures both Loxosceles laeta and Loxosceles surca records. (a) Histogram of the frequency of precipitation of warmest quarter period, constructed from the known distribution of both species. (b) Histogram of the frequency of annual mean temperature, constructed from the known distribution of both species.
Figure 1 in Ecological niche divergence between the brown recluse spiders Loxosceles laeta and L. surca (Sicariidae) in Chile
Figure 1. Location records for two species of Loxosceles showing the range overlap in northern of Chile; L. laeta (blue circles) and L. surca (red triangles).
Figure 2 in Ecological niche divergence between the brown recluse spiders Loxosceles laeta and L. surca (Sicariidae) in Chile
Figure 2. Loxosceles surca in northern of Chile. (a) Habitat where the spiders were found. (b) Live female specimen of the Loxosceles surca, Altos de Pica, Chile. (Photography: William H. Piel).
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.