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95 results for “vegetation type”
FIG. 3 in Lichen community assemblages and functional traits as indicators of vegetation types in central Mexico, based on herbarium specimens
FIG. 3. — Ordination and clustering of lichen communities from the different vegetation types: A, non-parametric multidimensional scaling (NDMS); B, cluster analysis dendrogram. The sites Cerro el Capulín and Cerro Juan el Grande show different affinities in both analyses (part of the xerophytic shrubland in the NDMS, but more similar to the Quercus L. forest in the dendrogram, labeled as the Xerophytic-Quercus group in the latter).
FIG. 5 in Lichen community assemblages and functional traits as indicators of vegetation types in central Mexico, based on herbarium specimens
FIG. 5. — Non-metric Multidimensional Scaling analysis of lichen community functional traits and environmental variables in three vegetation types. * (p <0.05) and ** (p <0.005) represent the significance of functional traits related to the Xerophytic shrubland (X), Subtropical shrubland (S), and Quercus L. forest (Q).
FIG. 1 in Lichen community assemblages and functional traits as indicators of vegetation types in central Mexico, based on herbarium specimens
FIG. 1. — Amplitude and mean values of alpha diversity (species richness) per vegetation type. Symbols: black dot, outlier; white dots, mean values.
FIG. 6 in Lichen community assemblages and functional traits as indicators of vegetation types in central Mexico, based on herbarium specimens
FIG. 6. — Correlation of lichen community functional traits and environmental variables in three vegetation types.
FIG. 2 in Lichen community assemblages and functional traits as indicators of vegetation types in central Mexico, based on herbarium specimens
FIG. 2. — Beta diversity and shared species per vegetation type: A, pairwise comparisons of the different elements of beta diversity (Xerophytic, xerophytic shrubland; Quercus, Quercus forest; Subtropical, subtropical shrubland); B, Venn diagram showing exclusive and shared species among the vegetation types included in this study.
Camera trap data suggest uneven predation risk across vegetation types in a mixed farmland landscape
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LT-Brazil: A database of leaf traits across biomes and vegetation types in Brazil
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Vegetation structure and fuel dynamics in fire-prone, Mediterranean-type Banksia woodlands
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Biomass from six vegetation types along a toposequence on a floodplain terrace of the Sagavanirktok River, Alaswka,1988, Arctic LTER.
Biomass was harvested from six vegetation types along a toposequence on a floodplain terrace of the Sagavanirktok River in the northern foothills of the Brooks Range , Alaska (68degrees 46' N, 148 degrees 51' W 50m). The vegetation sites are; upland tussock tundra, "hilltop heath", a "hillslope shrub-lupine", a "footslope Equisetum", a wet sedge tundra, and a "riverside willow".
Carbon, nitrogen and phosphorus content in the seasonally thawed soils are described for four arctic tundra vegetation types located near the Toolik Field Station, Arctic LTER 1993.
Carbon, nitrogen and phosphorus content in thawed soils are described for four arctic tundra vegetation types located near the Toolik Field Station.
Data from: Defining a spectrum of integrative trait-based vegetation canopy structural types
Vegetation canopy structure is a fundamental characteristic of terrestrial ecosystems that defines vegetation types and drives ecosystem functioning. We use the multivariate structural trait composition of vegetation canopies to classify ecosystems within a global canopy structure spectrum. Across the temperate forest subset of this spectrum we assess gradients in canopy structural traits, characterize canopy structural types (CST), and evaluate drivers and functional consequences of canopy structural variation. We derive CSTs from multivariate canopy structure data, illustrating variation along three primary structural axes and resolution into six largely distinct and functionally relevant CSTs. Our results illustrate that within-ecosystem successional processes and disturbance legacies can produce variation in canopy structure similar to that associated with sub-continental variation in forest types and ecoclimatic zones. The potential to classify ecosystems into CSTs based on suites of structural traits represents an important advance in understanding and modeling structure-function relationships in vegetated ecosystems.
Size-selective exclusion of mammals and invertebrates differently affects grassland plant communities depending on vegetation type
<p>Human-caused loss of vertebrate and invertebrate animals, defaunation, is increasing, and potentially affects plant community structure of diverse grassland ecosystems worldwide. We experimentally simulated defaunation using size-selective fences to progressively exclude large-, medium- and small-sized mammals, and invertebrates from two subalpine vegetation types in the Swiss National Park (SNP): intensively grazed short-grass and moderately grazed tall-grass vegetation. We assessed plant community properties yearly from 2009 to 2013, and examined treatment effects on plant community structure in the two grassland types. In the short-grass vegetation, the exclusion of large mammals increased total plant biomass, while the exclusion of large and medium-sized mammals increased total, grass and forb biomass compared to when all animals had access. These increases became stronger when also invertebrates were excluded. The exclusion of all mammals and invertebrates increased biomass of grasses by 205%, forbs by 100% and total plant biomass by 118% compared to when all animals had access, hence enhancing relative biomass of grasses from 43.6% to 60%, changing plant species composition and lowering richness of forbs by 16%, the number of plant families by 13% and family-level Shannon diversity by 23%. In contrast to these significant community-level responses found in the short-grass vegetation, there was no evidence that the size-selective exclusion of animals altered the plant community structure of the tall-grass vegetation. The contrasting results were due to the difference in plant community composition prior to our experiment, which were related to differences in quantity and quality of forage and in grazing intensities of herbivores between the two grassland types. Synthesis. Our results showed that different-sized animals, in particular large mammals and invertebrates, contributed to maintain the plant community structure in the short-grass vegetation, highlighting the importance of multiple, functionally different animal groups for ecosystem functioning and stability. In contrast to the short-grass vegetation, we could not detect such a top-down control by animals in the tall-grass vegetation. Our results suggest that potential defaunation effects on grassland plant community structure depend on the degree of grazing pressure release and grassland vegetation type.</p>
After the 'Black Summer' fires: faunal responses to megafire depend on fire severity, proportional area burnt, and vegetation type
<ol> <li>Climate change and human activities have disrupted historical fire regimes, leading to complex and far-reaching impacts on global ecosystems. Despite extensive research in fire ecology, studies exploring vertebrate responses to megafires, and to nuanced fire characteristics, remain limited.</li> <li>We collected camera trap data 3–27 months following Australia's 2019–20 'Black Summer' megafires from 30 burnt sites and 10 unburnt sites. Our data included 14 animal species/groups, encompassing mammalian predators, small and medium-sized mammals, large herbivores, and birds. We used generalised additive mixed models to assess the influence of time-since-the-fires, burn status, fire severity, proportional area burnt, and vegetation type on species' activity.</li> <li>Models that included fire variables were well-supported for all species. The proportional cover of low-moderate or high-extreme severity fire had substantial support for five species, particularly herbivores, which generally showed a preference for burnt sites but at differing fire severities. The proportional area burnt, disregarding severity, was well supported for four species. At highly burned sites, fox activity peaked shortly after the fires, while small to medium-sized mammal activity increased more gradually. Vegetation type strongly influenced the response of four species to fire; in particular, wet forest birds preferred unburnt areas.</li> <li> <em>Policy implications</em>. We document variable short- to medium-term responses of a range of species to fire which could help guide management interventions. We demonstrate that animal species' responses to fire are diverse and better captured using broader landscape-scale fire variables. We found that species were strongly influenced by proportional area burnt, fire severity, and vegetation type. Introduced foxes were attracted to recently burnt areas, so timely predator control may benefit vulnerable prey species. Wet forest species were sensitive to fires and could benefit from preservation and restoration of these habitats. Some species exploited low-moderate severity burnt areas, while others preferred high-severity burns. This suggests that species will face diverse challenges and opportunities in future extreme fire events. We emphasise the importance of using multi-faceted approaches to account for the complex responses of co-occurring species to fire events.</li> </ol>
A 10 m resolution land cover map of the Tibetan Plateau with detailed vegetation types
<p>A 10 m resolution land cover map of the Tibetan Plateau with 12 vegetation types and 3 non-vegetation types for the year 2022 (TP_LC10-2022) by leveraging state-of-the-art remote sensing approaches including the Sentinel-1 and Sentinel-2 imagery, environmental and topographic datasets, and Random Forest model using Google Earth Engine platform.</p>
Diel greenhouse gas emissions demonstrate a strong response to vegetation patch types in a freshwater wetland
<p>Data supporting submitted research paper. "All_flux_variables.csv" includes all plot data and is organized by the date/time of sample, campaign number, and sample location in rows and data collected as headers in the columns. "Flux_tower_data.csv" are meterological variables include in data analysis collected by a flux tower on sight. All other files are time series data for water pH (n = 2), water temperature (n = 3-5). Refer to the "metadata.csv" for units and descriptions of data in files. </p>
New vegetation type map of India prepared using satellite remote sensing: Comparison with global vegetation maps and utilities
<p>The dataset is the vegetation type map for India as per <a href="https://www.sciencedirect.com/science/article/pii/S0303243415000574?via%3Dihub">Roy et 2015 "<span>New vegetation type map of India prepared using satellite remote sensing: Comparison with global vegetation maps and utilities". </span></a></p> <p><span>The dataset consistes of two files- (1) a raster GIS file at 60m spatial resolution (EPSG 32643 WGS 84/ UTM Zone 34) in which each pixel value means a vegetation class as defined and mapped in Roy et al., 2015 and (2) a csv file which contains information matching the pixel value with the vegetation type. <br><br>For all additional information, please refer to the pper reviewed publication. </span></p>
Fig. 6 in The Impact Of Forest Harvesting Machines On Understorey Vegetation In Hylocomiosa Forest Type In Zemgale, Latvia
Fig. 6. The proportion of evergreen and summer green plant species in the herbaceous' layer.
Fig. 4 in The Impact Of Forest Harvesting Machines On Understorey Vegetation In Hylocomiosa Forest Type In Zemgale, Latvia
Fig. 4. The projective coverage of herbaceous' and moss' layers (mean values are shown ± SE).
Fig. 3 in The Impact Of Forest Harvesting Machines On Understorey Vegetation In Hylocomiosa Forest Type In Zemgale, Latvia
Fig. 3. The number of species of herbaceous and moss layers (mean values are shown ± SE).
Figure 2 in Bird communities of different woody vegetation types from the Niraj Valley, Romania
Figure 2. PCoA of the bird communities from the woody vegetation based on the Bray–Curtis index.
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.