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60 results for “Dominance Analysis”
Seasonal Soil Sampling of Grass-dominated, Mesquite-dominated, and Ecotone Sites at the Jornada Basin LTER site for the Analysis of Microbial Community Variance, 2022-2023
Fungal and bacterial soil communities were analyzed to assess the influence of woody shrub encroachment on soil microbial communities. Three study sites in the Jornada Long Term Ecological Research Site were selected to represent a grass-dominated site, a woody shrub dominated site, and an ecotone of woody shrubs and grass. The field sampling began in October 2022 and concluded in July 2023 with five sampling periods that aimed to capture seasonal variation: October 2022, January 2023, March 2023, May 2023, and July 2023. This dataset includes data pertaining to the soil microbial composition, environmental characteristics, microbial sequence processing, and documentation of the code utilized for data processing and statistical analyses. Data on soil microbial composition was collected from Phospholipid Fatty-Acid composition data from soil samples. Data on environmental characteristics were collected from on-site temperature probes, laboratory assessments of soil properties, and Jornada meteorological stations. Information pertaining to microbial sequence processing is included in the documented code as well as in the record of the primers utilized.
Рис. 5. АналиЗ линейной коррелЯции параметров макробентоса от доминируюЩей фракции в пробе грунта (А, Б) и глубины (В, Г). Fig. 5. Analysis of the linear correlation of macrobenthos parameters with the dominant fraction in the bottom sample (А, Б) and depth (В, Г). in Species composition and distribution of bivalve mollusks in plankton and benthos in Nevelsky Strait in summer
Рис. 5. АналиЗ линейной коррелЯции параметров макробентоса от доминируюЩей фракции в пробе грунта (А, Б) и глубины (В, Г). Fig. 5. Analysis of the linear correlation of macrobenthos parameters with the dominant fraction in the bottom sample (А, Б) and depth (В, Г).
Fig. 5 in Comparative movement analysis for a sympatric dhole and golden jackal in a human-dominated landscape
Fig. 5. Dhole (column A) and jackal (column B) step length and turning angle distributions of encamped (black) and exploratory (grey) behavioral states. Turning angles (in degrees) for both the encamped and exploratory states are plotted on the same polar plot for each species.
Fig. 4 in Comparative movement analysis for a sympatric dhole and golden jackal in a human-dominated landscape
Fig. 4. Comparison of both species' daily activity patterns. Smoothing was achieved by averaging over 4 hour time intervals. The 95% confidence intervals were estimated from the standard error of the mean step length.
Fig. 3 in Comparative movement analysis for a sympatric dhole and golden jackal in a human-dominated landscape
Fig. 3. Autocorrelation function (ACF) of: A, the dhole; and B, the jackal step length. Data points above the dotted line are classified as autocorrelated.
Fig. 2 in Comparative movement analysis for a sympatric dhole and golden jackal in a human-dominated landscape
Fig. 2. Decile-shaded isopleths of convex hull home ranges for the dhole and jackal in Khao Ang Rue Nai Wildlife Sanctuary, Thailand.
Fig. 1 in Comparative movement analysis for a sympatric dhole and golden jackal in a human-dominated landscape
Fig. 1. Dhole and jackal relocations overlaid on a land cover map of Khao Ang Rue Nai Wildlife Sanctuary, Thailand.
Fig. 6. A in Comparative movement analysis for a sympatric dhole and golden jackal in a human-dominated landscape
Fig. 6. A, Semi-variance comparison of dhole and jackal positions. Since the dhole was monitored for a shorter time than the jackal (due to collar malfunctions), we present comparative data for this shorter time period. B, The complete jackal semi-variogram. Both semi-variograms are limited in scope to the first two thirds of the data, since estimates in the last third of the semi-variogram has very large confidence intervals. Semi-variance and 95% confidence intervals (CI) estimated from the standard error of the mean semivariance, were smoothed using a moving average over 20 lags.
FIG. 11. — Russula shoreae D.Chakr., A.Ghosh, K in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 11. — Russula shoreae D.Chakr., A.Ghosh, K.Das & Buyck, sp. nov. (from holotype): A-C, fresh and dissected basidiomata in the field and basecamp; D, E, transverse section through pileipellis showing elements; F, transverse section through lamellae showing basidia; G, H, transverse section through lamellae showing hymenial cystidia near the lamellae edges; I-M, transverse section through lamellae showing hymenial cystidia near the lamellae sides. Scale bars: A, B, 20 mm; D, 20 μm; E-M, 10 μm.
FIG. 9. — Russula pseudoflavida A in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 9. — Russula pseudoflavida A.Ghosh, Hembrom, I.Bera & Buyck, sp. nov. (from holotype): A, basidiospore; B, basidia; C, hymenial gloeocystidia near the lamellae edges; D, hymenial gloeocystidia near the lamellae sides; E, marginal cells; F, elements of the pileipellis near the pileus margin: hyphal terminations; G, elements of the pileipellis near the pileus centre: hyphal terminations; H, doubtfull primordial hyphae. Scale bars: 10 µm.
FIG. 4 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 4. — Phylogram generated by Maximum Likelihood analysis based on nrITS sequence data of Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov. and allied species. Maximum Likelihood bootstrap support values (MLbs) ≥ 70% are shown on the left of "/" and Bayesian Posterior Probabilities (BPP) ≥ 0.95 are shown on the right above or below the branches at nodes. Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov. is placed in red font to highlight its phylogenetic position in the tree.
FIG. 2 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 2. — SEM micrographs of basidiospores: A, B, Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov.; C, D, R. pseudoflavida A.Ghosh, Hembrom, I.Bera & Buyck, sp. nov.; E, F, R. shoreae D.Chakr., A.Ghosh, K.Das & Buyck, sp. nov. Scale bars: A-C, E, F, 2 μm; D, 1 μm.
FIG. 6 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 6. — Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov. (from holotype): A, basidiospore; B, hymenial gloeocystidia near the lamellae edges; C, elements of the pileipellis near the pileus centre: hyphal terminations; D, basidia; E, hymenial gloeocystidia near the lamellae sides; F, elements of the pileipellis near the pileus margin: hyphal terminations. Scale bars: 10 µm.
FIG. 8. — Russula pseudoflavida A in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 8. — Russula pseudoflavida A.Ghosh, Hembrom, I.Bera & Buyck, sp. nov. (from holotype): A-C, fresh and dissected basidiomata in the field and basecamp; D-F, transverse section through pileipellis showing elements; G, primordial hyphae in carbolfuchsine; H-J, transverse section through lamellae showing hymenial gloeocystidia near the lamellae sides; K, transverse section through lamellae showing hymenial gloeocystidia near the lamellae edges. Scale bars: A, B, 20 mm; D, E, G, 20 μm; F, H-K, 10 μm.
FIG. 10 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 10. — Phylogram generated by Maximum Likelihood analysis based on nrITS sequence data of Russula shorae D.Chakr., A.Ghosh, K.Das & Buyck, sp. nov. and their allied species. Maximum Likelihood bootstrap support values (MLbs) ≥ 70% are shown on the left of "/" and Bayesian Posterior Probabilities (BPP) ≥ 0.95 are shown on the right above or below the branches at nodes. Russula shorae D.Chakr., A.Ghosh, K.Das & Buyck, sp. nov. is placed in red font to highlight their phylogenetic positions in the tree.
FIG. 1 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 1. — Distributional map and habitat of Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov., R. pseudoflavida A.Ghosh, Hembrom, I.Bera & Buyck, sp. nov. and R. shoreae D.Chakr., A.Ghosh, K.Das & Buyck, sp. nov. in India.
FIG. 7 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 7. — Phylogram generated by Maximum Likelihood analysis based on nrITS sequence data of Russula pseudoflavida A.Ghosh, Hembrom, I.Bera & Buyck, sp. nov. and allied species. Maximum Likelihood bootstrap support values (MLbs) ≥ 70% are shown on the left of "/" and Bayesian Posterior Probabilities (BPP) ≥ 0.95 are shown on the right above or below the branches at nodes. Russula pseudoflavida A.Ghosh, Hembrom, I.Bera & Buyck, sp. nov. is placed in red font to highlight its phylogenetic position in the tree.
FIG. 12. — Russula shoreae D.Chakr., A.Ghosh, K in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 12. — Russula shoreae D.Chakr., A.Ghosh, K.Das & Buyck, sp. nov. (from holotype): A, basidiospore; B, elements of the pileipellis near the pileus margin: hyphal terminations and pileocystidia; C, hymenial cystidia near the lamellae sides; D, basidia; E, hymenial cystidia near the lamellae edges; F, elements of the pileipellis near the pileus centre: hyphal terminations and pileocystidia. Scale bars: 10 µm.
FIG. 3 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 3. — Phylogram generated by Maximum Likelihood analysis based on combined sequence data of nrLSU, mtSSU and rpb2 for Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov., R. pseudoflavida A.Ghosh, Hembrom, I.Bera & Buyck, sp. nov. and R. shoreae D.Chakr., A.Ghosh, K.Das & Buyck, sp. nov. and their allied species. Maximum Likelihood bootstrap support values (MLbs) ≥ 70% are shown on the left of "/" and Bayesian Posterior Probabilities (BPP) ≥ 0.95 are shown on the right above or below the branches at nodes. The new species are placed in red font to highlight their phylogenetic positions in the tree.
FIG. 5 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 5. — Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov. (from holotype): A-D, fresh and dissected basidiomata in the field and basecamp; E, F, transverse section through pileipellis showing elements; G, transverse section through lamellae showing hymenial gloeocystidia near the lamellae edges; H, I, transverse section through lamellae showing hymenial gloeocystidia near the lamellae sides; J, transverse section through lamellae showing basidia. Scale bars: A, 40 mm; E, 100 μm; F-J, 10 μm.
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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.