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3,105 results for “Vegetation”
Comparing the impacts of patch-burn grazing on vegetation in two northern tallgrass prairies
The management practice of patch-burn grazing varies grazing pressure across a site by rotating burn locations, thereby creating spatial heterogeneity in vegetation height and density (structure). Patch-burn grazing increases the range of habitats available for different wildlife species, but it may also unintentionally affect plant invasion and plant biodiversity. We evaluated the effects of patch-burn grazing on plant communities in two northern tallgrass prairies. Both dry-mesic prairie sites were in Minnesota, USA, on similar soils and undergoing invasion by the non-native, cool-season grass smooth brome (Bromus inermis). The sites had different cattle stocking rates and burning practices (3 or 5 burn units). We established 15-20 pairs of plots per site with a fence around one member of each pair. We measured vegetation structure, native and non-native plant richness, smooth brome frequency, and frequency-weighted mean coefficients of conservatism (mean C) over 5-6 years across two treatments: patch-burn grazing and burning-without-grazing. At the site with a lower stocking rate and more burn units, grazing promoted spatial heterogeneity by reducing vegetation structure 18-65 percentage points in some units and some years. In both treatments, native richness increased 15% over 6 years, but smooth brome frequency increased over 200%, suggesting that adjustments in management are needed to suppress smooth brome. At the site with a higher stocking rate and fewer burn units, grazing reduced vegetation structure 37-78 percentage points in all units and all years, but native richness was maintained over time. Grazing also increased non-native richness 38 percentage points and reduced mean C by 6 percentage points over 2 years. Smooth brome frequency increased 2% over 2 years in both treatments. Patch-burn grazing at this site may have increased richness of annual or biennial non-native plant species. At both sites, long-lived perennials may drive the resilience of nat
Repeated vegetation monitoring for riparian forest restoration project, Santa Clara River, CA, 2015-2023.
We implemented a spatially-patterned methodology to restore 87 ha of riparian forest habitat, selectively applying multiple restoration approaches based on localized differences in degradation severity throughout the project area. This work was conducted as part of a large, collaborative effort to control invasive Arundo donax and reestablish contiguous natural habitat throughout the Santa Clara River floodplain in southern California.
SGS-LTER Long-Term Monitoring Project: Vegetation Cover on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1999 -2006, ARS Study Number 118 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/140/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83458. The abundance and diversity of small mammals in shortgrass steppe is strongly influenced by the structure and composition of vegetation. Vegetation structure provides cover from predators and harsh abiotic conditions. Plant species composition affects the types of seeds and herbaceous material available to granivores and herbivores, and influences arthropod populations, which are important prey for the omnivorous species that dominate in shortgrass steppe. Both vegetation structure and plant community composition are sensitive to the availability of precipitation as well as the activity of large mammalian herbivores. In 1999, we began measuring vegetation structure and plant community composition on the three grassland and three shrubland trapping webs where we live-trap small mammals
[DEPRECATED] Vegetation Plots of the Bonanza Creek LTER Control Plots: Species Count (1975 - 2004) (Reformatted to ecocomDP Design Pattern)
This ecocomDP data package has been deprecated due to issues in the L0 source dataset that prohibits the creation of an L1 ecocomDP dataset. This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project see https://github.com/EDIorg/ecocomDP/tree/master, or contact EDI https://environmentaldatainitiative.org. This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bnz&identifier=175&revision=20 The abstract below was extracted from the Level 0 data package and is included for context: These data are the vegetation datasets for 27 LTER sites in Bonanza Creek Experimental Forest. The 27 sites are divided into three replicates for six primary successional stages on the floodplains (3 replicates X 6 successional stages = 18 sites) and three replicates for three secondary successional stages in the uplands (3 replicates X 3 successional stages = 9 sites). Data include: 1) Visual estimates of percent cover, 2) Stem counts (the number of individuals/species), and 3) Heights (cm) for "tall shrub species" in twenty 4 m2 plots. Shrubs are considered "Tall shrubs" if they are Salix sp., Alnus sp., Rosa acicularis, Viburnum edule, Betula nana, Betula glandulosa, or Rubus idaeus. Initial colonziations plots (FP0s, SL1s, HR1A) were remeasured every year. Early successional plots were remeasured every 2-4 years. Later succesional plots were remeasured approximately every five years. For a detail schedule of plot measurements please see the file: Vegetation Monitoring Schedule.xls Although most sites were established in 1988 some sites have vegetation plots that have been sampled periodically since 1965. In 2006 shrub data collection was changed to a transect method of sampling. These data can be found in the file: <a href="http://www.lte
Vegetation indices calculated from canopy reflectance spectra at four sites along Imnavait Creek, AK during the 2008-2010 growing seasons.
A spectrophotometer was used to scan the canopy vegetation at four sites along Imnavait Creek in the Kuparuk Watershed near Toolik Lake LTER, Alaska. The resulting reflectance spectra were used to calculate average vegetation indices for each site and collection day.
Tree regeneration after fire: Wickersham Dome long-term vegetation study, birch height data
These data represent the most recent set of observations (made in 2002 by J. Johnstone) for several long-term vegetation monitoring plots near Wickersham Dome that were set up by Les Viereck and Joan Foote following the 1971 wildfire and 1978 experimental burns. Earlier records are available in the BNZ long-term vegetation database. This dataset documents tree seedling/sapling and shrub measurements made in 2002. Lists heights of all individual paper birch (Betula papyrifera) present in a plot.
Tree regeneration after fire: Wickersham Dome long-term vegetation study, bl. spruce height data
These data represent the most recent set of observations (made in 2002 by J. Johnstone) for several long-term vegetation monitoring plots near Wickersham Dome that were set up by Les Viereck and Joan Foote following the 1971 wildfire and 1978 experimental burns. Earlier records are available in the BNZ long-term vegetation database. This dataset documents tree seedling/sapling and shrub measurements made in 2002. Lists heights of all individual black spruce (Picea mariana) present in a plot.
Tree regeneration after fire: Wickersham Dome long-term vegetation study, aspen height data
These data represent the most recent set of observations (made in 2002 by J. Johnstone) for several long-term vegetation monitoring plots near Wickersham Dome that were set up by Les Viereck and Joan Foote following the 1971 wildfire and 1978 experimental burns. Earlier records are available in the BNZ long-term vegetation database. This dataset documents tree seedling/sapling and shrub measurements made in 2002. Lists heights of all individual trembling aspen (Populus tremuloides) present in a plot.
Tree regeneration after fire: Effects of burn severity, CPCRW vegetative cover analysis
This study examines the effects of burn severity on patterns of post-fire tree establishment in the boreal forest. We collected data from 5 separate field experiments examining seedling establishment across different severity levels in 4 burns in central Yukon Territory, Canada, and interior Alaska, USA. The experimental studies focus on the germination, survival, and growth responses of four common tree species, trembling aspen (Populus tremuloides), lodgepole pine (Pinus contorta), white spruce (Picea glauca) and black spruce (Picea mariana). Data on the soil organic layer (depth, moisture, bulk density, pH) were also collected at each site. This file contains visual cover estimates, by species, for 2000-2002 at the CPCRW site. Sample dates are: 4 August 2000 25 July 2001 16 July 2002. Values are percent cover in a 1x1m quadrat, where T=trace (less than 0.5%), out=outside quadrat but inside experimental plot. An additional line is included which give the full species names associated with the 6-letter codes used as column headers.
Tree regeneration after fire: Effects of burn severity, Delta vegetative cover analysis
This study examines the effects of burn severity on patterns of post-fire tree establishment in the boreal forest. We collected data from 5 separate field experiments examining seedling establishment across different severity levels in 4 burns in central Yukon Territory, Canada, and interior Alaska, USA. The experimental studies focus on the germination, survival, and growth responses of four common tree species, trembling aspen (Populus tremuloides), lodgepole pine (Pinus contorta), white spruce (Picea glauca) and black spruce (Picea mariana). Data on the soil organic layer (depth, moisture, bulk density, pH) were also collected at each site. This file contains visual cover estimates, by species, for 2000-2002 at the Delta site. Data for severity and warming treatments are included. Sample dates are: 31 July 2000 18 July 2001 13 July 2002. Values are percent cover in a 1x1m quadrat, where T=trace (less than 0.5%), out=outside quadrat but inside experimental plot. An additional line is included which give the full species names associated with the 6-letter codes used as column headers.
APEX beta vegetation surveys from both the permafrost plateau area and the active thaw margin, from 2017 to present
This dataset contains the vegetation survey data for the bog and permafrost plateau sites at the Alaskan Peatland Experiment (APEX) from 2018 to 2024. Each year of surveys is recorded in a separate subsheet.
Numerical summaries of vegetation indices and land surface temperature derived from remotely sensed imagery in Phoenix Area Social Survey (PASS) neighborhoods of central Arizona
This project calculates two vegetation indices: Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI), and land surface temperature (LST) from remotely sensed imagery. NDVI and SAVI are calculated from the 2010, 2013, 2015, and 2017 NAIP imagery (1m resolution). LST is calculated from Landsat 5 and 8 imagery (30m resolution) from summer months in 1985, 1990, 1995, 2000, 2005, 2010, and 2015. Summary values are calculated for each of the aforementioned data resources for 2011 and 2017 Phoenix Area Social Survey (PASS) study area boundaries. Tabular summaries of the mean, median, minimum, maximum, and standard deviation of the NDVI, SAVI, and LST values for the 2011 and 2017 Phoenix Area Social Survey boundaries (45 and 12 neighborhoods, respectively) are provided. Javascript code used to process NDVI, SAVI, and LST imagery, and R code used to calculate numerical summaries of NDVI, SAVI, and LST in PASS neighborhoods are included with this dataset. Locations and areas of PASS study neighborhood boundaries and source imagery used to calculate these summaries are available through the Environmental Data Initiative - see resouce listing in the methods of this data set.
Normalized Difference Vegetation Index (NDVI) derived from 2010 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates the Normalized Difference Vegetation Index (NDVI) from 2010 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as fifteen individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf, png, and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_NDVI_CAP2010-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf, png, and kml index map). Javascript code used to process NDVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.
Normalized Difference Vegetation Index (NDVI) derived from 2013 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates the Normalized Difference Vegetation Index (NDVI) from 2013 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as fifteen individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf, png, and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_NDVI_CAP2013-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf, png, and kml index map). Javascript code used to process NDVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.
Normalized Difference Vegetation Index (NDVI) derived from 2015 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates the Normalized Difference Vegetation Index (NDVI) from 2015 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as fifteen individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf, png, and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_NDVI_CAP2015-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf, png, and kml index map). Javascript code used to process NDVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.
Normalized Difference Vegetation Index (NDVI) derived from 2017 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates the Normalized Difference Vegetation Index (NDVI) from 2017 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as fifteen individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf, png, and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_NDVI_CAP2017-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf, png, and kml index map). Javascript code used to process NDVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.
Soil-Adjusted Vegetation Index (SAVI) derived from 2010 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates the Soil-adjusted Vegetation Index (SAVI) from 2010 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as multiple individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_SAVI_CAP2010-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf and kml index maps). Javascript code used to process SAVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.
Soil-Adjusted Vegetation Index (SAVI) derived from 2013 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates the Soil-adjusted Vegetation Index (SAVI) from 2013 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as multiple individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_SAVI_CAP2013-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf and kml index maps). Javascript code used to process SAVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.
Soil-Adjusted Vegetation Index (SAVI) derived from 2015 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates the Soil-adjusted Vegetation Index (SAVI) from 2015 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as multiple individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_SAVI_CAP2015-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf and kml index maps). Javascript code used to process SAVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.
Soil-Adjusted Vegetation Index (SAVI) derived from 2017 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates the Soil-adjusted Vegetation Index (SAVI) from 2017 National Agriculture Imagery Program (NAIP) imagery (1-meter resolution) for the central Arizona region. Because of their large size, data (as GeoTIFF files) for each survey year are provided as multiple individual tiles each comprising a portion of the overall coverage area. An index of the relative position of each tile in the coverage area is provided as a pdf and kml where the tile index contains a portion of the GeoTIFF file name (e.g., the relative position of the data file NAIP_SAVI_CAP2017-0000000000-0000000000.tif to the overall coverage area is identified by the index id 0000000000-0000000000 in the pdf and kml index maps). Javascript code used to process SAVI values is included with this dataset. This data set is one in a series of NDVI and SAVI (Soil Adjusted Vegetation Index) data sets for the central Arizona region spanning multiple years (2010-2017). Related data are available through the Environmental Data Initiative - see resouce listing in the methods of this data set for references.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.