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286 results for “Forest composition”
Figure 1 in Composition and spatio-temporal dynamics of aquatic bird community in humid areas of Alto Parana Atlantic Forest
Figure 1. Map of the RPPN Foz do Rio Aguapeí and location of the six studied areas in the RPPN Foz do Rio Aguapeí. Legend: (1) Lagoa São Gabriel; (2) Lagoa das Piranhas; (3) Lagoa dos Porcos; (4) Constructed wetland; (5) Aguapei river –; and (6) Lagoa da sede. Sources: CESP (2013) and Google Earth (2021).
Figure 2 in Composition and spatio-temporal dynamics of aquatic bird community in humid areas of Alto Parana Atlantic Forest
Figure 2. Cumulative curve of the 52 waterfowl bird species in the RPPN Foz do Rio Aguapeí showing stability from sample 27 to 31.
Figure 3 in Composition and spatio-temporal dynamics of aquatic bird community in humid areas of Alto Parana Atlantic Forest
Figure 3. NMDS (stress of 0.097) of the spatial distribution of the aquatic bird community recorded by the transect method in the lagoons of the RPPN Foz do Aguapeí, during the dry (rounded symbols) and rainy seasons (square symbols). Legend: LS = Lagoa da Sede; LSG = Lagoa São Gabriel; LP = Lagoa da Piranha and LPO = Lagoa dos Porcos.
Fig. 3 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 3 | Response of tree species to climate change across biomes. The median absolute latitude and median elevation shift among species, fraction of lost and gained species, and change in taxonomic and phylogenetic composition under climate change were computed for each forest ecoregion. The boxplots show statistics for n = 239 ecoregions for Tropical Moist Broadleaf Forests, n = 14 ecoregions for Tropical Coniferous Forests, n = 55 ecoregions for Tropical Dry Broadleaf Forests, n = 26 ecoregions for Boreal Forests, n = 91 ecoregions for Temperate Broadleaf Forests, n = 49 ecoregions for Temperate Conifer Forests and n = 61 ecoregions for Mediterranean Forests. The center line of the boxplots shows the median, the box limits the quartiles, the whiskers 1.5 times the interquartile range, and the points the outliers.Changes are computed between predicted distributions with climate variables for 1981-2010 and climate projections for 2071-2100 under climate change scenario SSP 5.85. Changes in composition are computed as the Euclidean distance between scaled NMDS and evoPCA values computed at the ecoregion level. Source data are provided as a Source Data file.
Fig. 2 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 2 | Species occupancy range distribution and loss. a Distributions of species occupancy range sizes globally (gray) and constrained to forests (at least 10% tree cover, color) for species in each forest biome. b Boxplot of relative range reduction across species in each forest biome with the center line showing the median, the box limits the quartiles, the whiskers 1.5 times the interquartile range, and the points the outliers. The distributions and boxplots are computed for n = 6810 species for Tropical Moist Broadleaf Forests, n = 588 species for Tropical Coniferous Forests, n = 1101 species for Tropical Dry Broadleaf Forests, n = 54 species for Boreal Forests, n = 1744 species for Temperate Broadleaf Forests, n = 178 species for Temperate Conifer Forests and n = 580 species for Mediterranean Forests. c Global map of median species range size constrained to forests, created with QGIS110. The gray base map corresponds to all areas for which model predictors were available. d Plot of species' median latitude against range size constrained to forests, colored by point density, where red indicates the highest density. Source data are provided as a Source Data file.
Fig. 1 in Regional uniqueness of tree species composition and response to forest loss and climate change
Fig. 1 | Gradients in taxonomic and phylogenetic composition show a near- a, c. Scatter plot of taxonomic and phylogenetic ordinations in environmental unique biodiversity signature of every single location on the planet. Taxonomic space, a 2-dimensional space made up of the 2 first axes of a PCA of the environcomposition is represented by a 3-axis non-metric dimensional scaling (NMDS) and mental variables used for species distribution modeling: mean annual temperature phylogenetic beta-diversity is represented by the 3 first axes of a phylogenetic (MAT), temperature seasonality (T season), annual precipitation (Annual P), preordination (evoPCA). Both the taxonomic and phylogenetic ordinations are com- cipitation seasonality (P season), growing season length (GSL), net primary proputed on the global community matrix derived from the modeled distributions of ductivity (NPP),silt content (Silt),coarse fragments (CF),and soil pH (pH).b, d. Map n = 10,590 tree species sampled at a resolution of 100 km, resulting in n = 12,548 of taxonomic and phylogenetic ordinations in geographical space. Source data are sites. The 3 axes of each ordination are mapped to red, green, and blue with provided as a Source Data file. The maps were created with QGIS110 and the gray minimum and maximum values corresponding to the 10th and 90th percentiles. base map corresponds to all areas for which model predictors were available.
Figure 4 in Composition and spatio-temporal dynamics of aquatic bird community in humid areas of Alto Parana Atlantic Forest
Figure 4. NMDS (stress of 0.001) of the spatial distribution of the aquatic bird community recorded by the transect method in the lotic environments of the RPPN Foz do Aguapeí, during the dry (rounded symbols) and rainy seasons (square symbols). Legend: AR = Aguapeí River and CW = Constructed wetland.
Fig. 2 in Abundance and composition of coprophagous Scarabaeidae (Coleoptera: Scarabaeoidea) in the developmental cycle of pine stands in Człuchów Forest (NW Poland)
Fig. 2. Baited ground trap for collecting Scarabaeidae in pine stands in Człuchów Forest, 1998-1999 (drawing by J. Piętka).
Fig. 9 in Abundance and composition of coprophagous Scarabaeidae (Coleoptera: Scarabaeoidea) in the developmental cycle of pine stands in Człuchów Forest (NW Poland)
Fig. 9. Result of PCA analysis featuring Scarabaeidae communities inhabiting various stages of the pine stand developmental cycle in Człuchów Forest (legend as in Fig. 5; species abbreviations as in Tab. 2)
Fig. 1 in Functional trophic composition of the ichthyofauna of forest streams in eastern Brazilian Amazon
Fig. 1. Location of the 18 sampled streams reaches (enlarged detail) in the northeastern region of Pará. The road network shown on the map relates only to the main roads.
Figure 5 in Composition and structure of plant communities in the Moist Temperate Forest Ecosystem of the Hindukush Mountains, Pakistan
Figure 5. CCA plot Analysis of illustrating the influence of elevation on spreading pattern of plant communities in Lalkoo valley Swat.
Figure 4 in Composition and structure of plant communities in the Moist Temperate Forest Ecosystem of the Hindukush Mountains, Pakistan
Figure 4. Results of CCA joint biplot showing results for eleven plant communities' correlation with environmental variable. BAB-I: Berberis- Abies- Bergenia; PIP-II: Picea-Indigofera- Poa; APP-III: Abies- Parrotiopsis- Poa,QVP-IV:Quercus-Viburnum-Poa,PSP-V:PiceaSalix-Primula,AVP-VI:Abies-Viburnum -Poa; VTP-VII: ViburnumTaxus-Poa; PVL-VIII: Pinus-Viburnum-Lithospermum; ABC-IX: Abies-Berberis-Carex; PVP-X: Pinus-Viburnum-Poa; and PPP-XI: Parrotiopsis-Picea-Poa represents community types.
Figure 2 in Fire effects on Atlantic Forest sites from a composition, structure and functional perspective
Figure 2. Average of species richness (A), basal area (B), Shannon index (C), tree density (D), CWM Height (E), CWM Leaf length (F), CWM wood density (G), CWM Leaf deciduousness (H), CWM dispersal mode (I), CWM shade tolerance (J) for tree species inventoried in burned and unburned sites in Paraíba do Sul river basin, Southeast Atlantic Forest biome, Brazil.Same letters represent no statistical difference.
Fig. 1 in Species composition and distribution of ground beetles (Coleoptera, Carabidae) in the forests of the Kamanos State Strict Reserve (Lithuania)
Fig. 1. Similarity (Ics) between the forest types of the Kamanos State Strict Reserve with respect to species composition of ground beetles according to quantitative data (species similarity) (1 - oxalidosum spruce stand, 2 - myrtillosum pine stand, 3 - myrtillo - oxalidosum spruce stand, 4 - oxalidosum broadleaved birch stand, 5 - calamagrostics birch stand, 6 - caricosum birch stand, 7 - caricoso - ledosum pine stand, 8 - sphagno - ledosum pine stand).
Fig. 5 in Abundance and composition of Geotrupidae (Coleoptera: Scarabaeoidea) in the developmental cycle of pine stands in Człuchów Forest (NW Poland)
Fig. 5. Average annual abundance of A. stercorosus in pine stands in Człuchów Forest, 1998-1999 (explanations as in Fig. 2)
Fig. 10. A in Abundance and composition of Geotrupidae (Coleoptera: Scarabaeoidea) in the developmental cycle of pine stands in Człuchów Forest (NW Poland)
Fig. 10. A diagram of PCA analysis illustrating the dominance structure in Geotrupidae communities inhabiting various phases of the developmental cycle of pine stands in Człuchów Forest, 1998-1999 (explanations as in Fig. 9)
Fig. 2. A in Abundance and composition of Geotrupidae (Coleoptera: Scarabaeoidea) in the developmental cycle of pine stands in Człuchów Forest (NW Poland)
Fig. 2. A baited ground trap for collecting Geotrupidae in pine stands in Człuchów Forest, 1998-1999 (drawing by J. Piętka)
Fig. 6 in Abundance and composition of Geotrupidae (Coleoptera: Scarabaeoidea) in the developmental cycle of pine stands in Człuchów Forest (NW Poland)
Fig. 6. Average annual abundance of T. vernalis in pine stands in Człuchów Forest, 1998-1999 (explanations as in Fig. 2)
Figure 3 in Impact of dike age on biodiversity and functional composition of soil macrofaunal communities in poplar forests in a reclaimed coastal area
Figure 3. PCoA ordinal configuration of soil macrofaunal communities from different habitats by Euclidean distance similarity index. In the code of the samples, the prefix means the code of the habitat, and the suffix means the number of the sample.
Figure 2 in Impact of dike age on biodiversity and functional composition of soil macrofaunal communities in poplar forests in a reclaimed coastal area
Figure 2. One-way ANOVA of taxonomic richness and abundance (A) and Margalef 's richness index R and Shannon– Weaver diversity index H' (B) across different habitats (mean ± SE). Means with different scripts are significantly different by Dunnett's T3 test (A) and LSD test (B), α = 0.05.
ScienceDex guides
Understand access before you commit
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.