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104 results for “habitat characteristics”
Fig. 3 in A new species of Anobothrus (Polychaeta, Ampharetidae) from the Weddell Sea (Antarctica), with notes on habitat characteristics and an updated key to the genus
Fig. 3. Anobothrus konstantini Säring & Bick sp. nov. Micrographs of ShirlastainA staining pattern. A. Complete specimen, lateral view with one outermost branchia, additional material (ZSRO-P2657). B. Notochaetae on segment 11 (TC 10), paratype (ZSRO-P2662). C. Modified notochaetae on segment 12 (TC 11, TC 7), paratype (ZSRO-P2660). D. Dorsal view of anterior end, arrow: glandular circular band on segment 6 (TC 5, TU 1), paratype (ZSRO-P2662). E. Lateral view, arrow: reduced neuropodium on segment 5 (TC 4), without uncini, paratype (ZSRO-P2662). F. Lateral view of anterior end, paratype (ZSRO-P2662). G. Lateral view of three thoracic segments, arrow: modified notopodium with dorsal ridge on segment 12 (TC 11, TU 7), paratype (ZSRO-P2662). Scale bars: A = 500 µm; B = 50 µm, C = 20 µm; D–E = 100 µm; F–G = 200 µm.
Fig. 1 in A new species of Anobothrus (Polychaeta, Ampharetidae) from the Weddell Sea (Antarctica), with notes on habitat characteristics and an updated key to the genus
Fig. 1. Schematic lateral view of Anobothrus konstantini Säring & Bick sp. nov. Abbreviations: see Material and methods. Vertical dotted line in TS6 represents circular glandular band. Vertical lines in TS12 represent elongated ridge between notopodia.
Fig. 2 in A new species of Anobothrus (Polychaeta, Ampharetidae) from the Weddell Sea (Antarctica), with notes on habitat characteristics and an updated key to the genus
Fig. 2. Sampling stations in the vicinity of the Antarctic Peninsula during RV Polarstern expedition PS 81 (Drake Passage, Bransfield Strait, North-Western Weddell Sea, green frame) and the South-Eastern Weddell Sea during PS 96 (North Filchner Trough, South Filchner Trough, blue frame). Stations without Anobothrus konstantini Säring & Bick sp. nov. labeled with a cross. Information about sampled stations and number of individuals of A. konstantini Säring & Bick sp. nov. are given in Table 1.
Dataset for 'Different in the dark: The effect of habitat characteristics on community composition and beta diversity in bromeliad microfauna'
<p>The file contains counting data for bromeliad-inhabiting microfauna (including, heterotrophic nanoflagellates, ciliates, amoeba and rotifers) from samples taken on Ilha do Cardoso, Brazil.</p> <p>Also included are additional Information on abiotic and biotic factors measured (e.g. pH, dissolved oxygen concentration etc.).</p>
Figure 2 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 2. Maxent predictions of suitable zebra mussel (Dreissena polymorpha) habitat in Texas. Shading indicates the logistic output of the Maxent model. Polygons represent state and national borders as well as major river basins within Texas.
Figure 1 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 1. Physicochemical data survey lakes. Sites categorized by TPWD (at the time of this study in 2016) as "infested" (the water body has an established, reproducing population) or "positive" (zebra mussels or their larvae have been detected on more than one occasion despite lack of evidence of a fully established, reproducing population) are indicated by red triangles and included: Lakes Austin, Belton, Bridgeport, Dean Gilbert, Lavon, Lewisville, Ray Roberts, Stillhouse Hollow, Texoma, Travis, and Waco. Sites categorized by TPWD as zebra mussel "negative" are indicated by green circles and included: Lakes Aquilla, Buchanan, Georgetown, Granbury, Granger, Hubbard Creek, Inks, Lady Bird, LBJ, Limestone, Marble Falls, Palo Pinto, Pflugerville, Possum Kingdom, Proctor, and Whitney.
Figure 4 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 4. Biplot of components 1 and 2 (top) and 1 and 3 (bottom) from Principal Component Analysis of water quality variables in 27 study lakes. Variables that predominated in each component (|factor loading| ≥ 0.50) are shown on the appropriate axes. Individual lake data are represented by symbols, with open circles representing lakes without previously reported incidences of zebra mussels (absent, 16 lakes), and solid circles those known to harbor the invasive species (present, 11 lakes) at the time of sampling (October 2016). No separation between the two lake groups is evident in either of the biplots. Ca, calcium, N, nitrogen; P, phosphorous.
Figure 3 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 3. Maxent predictions of suitable quagga mussel (Dreissena bugensis) habitat in Texas. Shading indicates the logistic output of the Maxent model. Polygons represent state and national borders as well as major river basins within Texas.
Fig. 2 in Habitat characteristics and environmental parameters influencing fish assemblages of karstic pools in southern Mexico
Fig. 2. Biplot of the scores for the environmental variables (36 pools) using canonical variate analysis (CVA) based by Euclidean distance (Hill's scaling option). Environmental vector showed the direction along which each variable changes most: temperature (T), dissolved oxygen (DO), conductivity (Cond), pH, nitrates (NO 3), ammonium (NH 4), and potassium (K). Polygons: group locations (pools) with similar hydrological characteristics (Table 1). Group A: pools characterized by high ammonium concentration, B: pools with high electrical conductivity, and C: pools with high phosphorous concentrations.
Fig. 3 in Habitat characteristics and environmental parameters influencing fish assemblages of karstic pools in southern Mexico
Fig. 3. Non-metric multi-dimensional scaling ordination of fish assemblage structure in karstic pools from Calakmul Biosphere Reserve. Habitat type obtained by CVA analysis s specified for the exclusive species.
Fig. 1 in Habitat characteristics and environmental parameters influencing fish assemblages of karstic pools in southern Mexico
Fig. 1. Calakmul Biosphere Reserve in southern Mexico, showing the borderline of the core area, and buffer zone indicated by shaded polygons. The white circles denoted pools located in habitat A, black circles are pools in habitat B, and black squares in habitat C. Pool identification numbers are specified in Table 3.
Fig. 4 in Habitat characteristics and environmental parameters influencing fish assemblages of karstic pools in southern Mexico
Fig. 4. CCA ordination diagram based on species abundances (closed circles), with habitat quality variables designed by a star: G = grass, T= ephemeral, P = perennial, WV = without vegetation, AR = arboreal cover, AV = aquatic vegetation, HU = human use, TF = tilapia farming. Environmental parameters represented by vectors: O2 = dissolved oxygen, Cond. = conductivity, pH, NO3 = nitrates, NH4 = ammonium, and K = potassium. See Table 2 for species abbreviations. The first canonical axes: (F = 6.09, P = 0.026) and for all canonical axes (F = 1.879, P = 0.040).
Рис. 1. ЭкоΛого-географическая характеристика зоопΛанктона гиΔротермаΛьной зоны оз. Кенон в июΛе 2019 г.: А — зоогеография, Б — местообитание, В — способ переΔвижения, Г — способ питания Fig. 1. Ecological and geographic characteristics of zooplankton in the hydrothermal zone of Lake Kenon in July 2019: А — zoogeography, Б — habitat, В — type of locomotion, Г — type of feeding in Zooplankton Structure And Distribution In The Hydrothermal Zone Of Cooling Reservoirs (Trans-Baikal Territory)
Рис. 1. ЭкоΛого-географическая характеристика зоопΛанктона гиΔротермаΛьной зоны оз. Кенон в июΛе 2019 г.: А — зоогеография, Б — местообитание, В — способ переΔвижения, Г — способ питания Fig. 1. Ecological and geographic characteristics of zooplankton in the hydrothermal zone of Lake Kenon in July 2019: А — zoogeography, Б — habitat, В — type of locomotion, Г — type of feeding
Figs. 2–4 in Myrmecofauna (Hymenoptera: Formicidae) response to habitat characteristics of tropical montane cloud forests in central Veracruz, Mexico
Figs. 2–4. Species richness, diversity profiles, and rank–abundance curves. Fig. 2. Comparison of the richness of woody plants at a sampling coverage of 90% and of ants at 85% coverage, among 5 fragments of tropical montane cloud forest in central Veracruz, Mexico. Statistical differences are considered when 95% confidence intervals do not overlap, whereas no differences are assumed when they do overlap, with an α = 0.05. Fig. 3. Diversity profiles of the ant assemblages of F1–F5 based on the equivalent species number. Statistical differences are considered when 95% confidence intervals do not overlap, whereas no differences are assumed when they do overlap, with an α = 0.05. Fig. 4. Rank–abundance curves of the ant assemblages of F1–F5. Total number of ant incidences in each fragment is 60 traps. Only those species with a relative abundance equal to or higher than 10% in a given fragment are shown. Ant species are numbered in accordance with Table 2.
Figs. 5 and 6. Results from cluster and linkage tree analyses. Fig. 5 in Myrmecofauna (Hymenoptera: Formicidae) response to habitat characteristics of tropical montane cloud forests in central Veracruz, Mexico
Figs. 5 and 6. Results from cluster and linkage tree analyses. Fig. 5. Dendrogram of hierarchical standardized clustering based on the SØrensen similarity index of the studied fragments. The cophenetic correlation coefficient of the cluster is 0.89. The dendrogram displays with continuous lines the divisions for which the SIMPROF test rejects the null hypothesis (where assemblages in that group have no further structure to explore) and with dashed lines the groups of assemblages not separated (at P <0.05) by SIMPROF. Fig. 6. Linkage tree analysis (LINKTREE) showing divisive clustering of fragments (F1–F5) from species compositions constrained by inequalities on one or more environmental variables. Only binary partitions of uncorrelated environmental variables are shown in the cluster. The dendrogram displays with continuous lines the divisions for which the SIMPROF test rejects the null hypothesis (where assemblages in that group have no further structure to explore) and with dashed lines the groups of assemblages not separated (at P <0.05) by SIMPROF.
Fig. 1 in Myrmecofauna (Hymenoptera: Formicidae) response to habitat characteristics of tropical montane cloud forests in central Veracruz, Mexico
Fig. 1. Location of the study area in central Veracruz, Mexico. The black polygons indicate the selected fragments (F1–F5) of tropical montane cloud forest.
Fig. 1 in Sleeping site selection in two Asian viverrids: effects of predation risk, resource access and habitat characteristics
Fig. 1. Home ranges, core areas and sleeping sites of binturongs (Arctictis binturong) and masked palm civets (Paguma larvata). Home ranges (minimum convex polygon [MCP] 95%) and core areas (MCP 50%) with sleeping sites overlaid of (a) three masked palm civets and a female binturong at Tikong, (b) a male binturong at Sesawo, and (c) location of study sites (Sesawo and Tikong) within the study area (Thung Yai Naresuan Wildlife Sanctuary – West). Different gray shades within home ranges represent core areas of each animal.
Fig. 4 in Sleeping site selection in two Asian viverrids: effects of predation risk, resource access and habitat characteristics
Fig. 4. Use and reuse of sleeping sites. Cumulative number of unique sleeping sites in relation to the total number of sites observed for two binturongs (Arctictis binturong) and three masked palm civets (Paguma larvata). Numbers of unique sleeping sites (sites that are not re-used) versus total sleeping sites observed and study areas are indicated in parenthesis.
Fig. 3 in Sleeping site selection in two Asian viverrids: effects of predation risk, resource access and habitat characteristics
Fig. 3. Use of sleeping sites within different forest types. Percentage of different forest types used (denoted as U) for sleeping sites versus forest types available (A) for two binturongs (Arctictis binturong) and three masked palm civets (Paguma larvata). Forest types are: semi-evergreen forest (SEF), mixed deciduous forest (MDF), and dry dipterocarp forest (DDF). Numbers in parenthesis after individual animals represent the number of sleeping sites used in the analysis, excluding reused sites.
Fig. 2 in Sleeping site selection in two Asian viverrids: effects of predation risk, resource access and habitat characteristics
Fig. 2. Use of vertical strata for sleeping sites. Percentage use of different vertical strata of sleeping sites by five radio-collared viverrids (two binturongs Arctictis binturong and three masked palm civets Paguma larvata). Strata are: Above canopy, Canopy, and Sub-canopy. Numbers in parenthesis represent number of sleeping sites where animals were directly observed, excluding reused sites.
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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)
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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.