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55 results for “vegetation monitoring”
Monthly Vegetation and Invertebrate Population Monitoring near the Georgia Coastal Ecosystems LTER Flux Tower
Permanent study plots were established in a Spartina alterniflora-dominated marsh in the vicinity of the Georgia Coastal Ecosystems LTER Flux Tower to provide measurements of plant biomass and invertebrate population density over time for comparison with marsh-atmospheric CO2 exchange. Six replicate plots were randomly placed within each of three height zones of Spartina alterniflora (i.e. short, medium and tall Spartina). Beginning in June 2013, surveys were conducted approximately monthly to determine abundance of Littoraria irrorata, Prokelisia marginata, and grasshoppers in each plot. Plant species, stem density, height, and flowering status were also measured in each of the plots, and biomass was calculated using allometric relationships between plant height, flowering status and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 2 per zone - additional cores collected some months in 2014 and 2016) to measure above and below ground biomass for each Spartina zone. Beginning in February 2016, chlorophyll measurements were taken in the proximity of the plots in each Spartina zone (n = 15 per zone).
Soil salinity and organic content at GCE-LTER vegetation monitoring plots in October 2020
Soil samples were collected in conjunction with Fall 2020 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water. Organic content was measured gravimetrically by comparing ash-free dry weight and total weight of soil samples.
Soil salinity at GCE-LTER vegetation monitoring plots in October 2021
Soil samples were collected in conjunction with Fall 2021 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.
Soil salinity at GCE-LTER vegetation monitoring plots in October 2022
Soil samples were collected in conjunction with Fall 2022 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.
Soil salinity at GCE-LTER vegetation monitoring plots in October 2023
Soil samples were collected in conjunction with Fall 2023 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.
Towers Forestry Plot, Long-term Vegetation Monitoring in a 1-ha old-growth Rainforest, La Selva Research Station, OTS, Sarapiquí, Heredia, Costa Rica, 2010–2020
The Towers Plot is a 1-hectare permanent vegetation plot established in 2010 under the canopy towers at La Selva Research Station, Sarapiquí, Heredia, Costa Rica. The plot was created by the Organization for Tropical Studies (OTS) to monitor long-term changes in forest structure, composition, and dynamics in an old-growth tropical rainforest. All woody stems with a diameter at breast height (DBH) of 10 cm or greater—including trees, palms, and lianas—were tagged, mapped, and measured following standardized procedures. Censuses were conducted between 2010 and 2020 to document growth, mortality, and recruitment. The dataset includes taxonomic identifications, stem diameter measurements, spatial coordinates within the plot, and metadata describing field methods and species composition. The plot was established beneath three canopy towers that had been previously constructed through the NSF-funded Major Research Instrumentation (MRI) project, NSF 0722741, which provided key infrastructure for canopy and environmental research at La Selva. This proximity created a valuable opportunity to integrate vegetation monitoring with existing environmental instrumentation. Johana Hurtado, coordinator of the Tropical Ecology, Assessment and Monitoring (TEAM) project at La Selva, collaborated with OTS staff in the establishment of the plot, ensuring methodological consistency with other tropical forest monitoring sites. This dataset provides a comprehensive record of woody plant diversity and forest structure in a lowland old-growth Neotropical rainforest. It supports research on forest dynamics, carbon storage, and ecosystem change. The overall monitoring project is ongoing; this data package contains observations from 2010 through 2020.
H2Ohio Wetland Monitoring Program Vegetation Community Composition, Biomass, and Nutrient Content across Ohio, USA (2021-2022)
This data package includes vegetation community composition, percent cover, biomass, and nutrient concentration data from wetland projects across Ohio, USA, monitored by the H2Ohio Wetland Monitoring Program. Monitoring began in July 2021 and is ongoing, with annual updates planned. While data collection varies by site, most wetlands are surveyed to characterize vegetation and estimate nutrient stocks through community composition assessments and biomass sampling. Sampling points are randomly generated within and up to 5 meters outside the approximated wetland boundary. Surveys are conducted at points where wetland species (FAC–OBL) are present using a 1×1 meter quadrat to record species composition and percent cover. At approximately half of these locations, a 0.25×0.25 meter quadrat is placed outside the northeast corner to collect vegetation samples for nutrient analysis. In these smaller quadrats, community composition and percent cover are recorded prior to sampling aboveground biomass and, at approximately one third of those sites, belowground biomass. Datasets collected by the H2Ohio Wetland Monitoring Program containing surface water and soil nutrient concentration from samples collected at Ohio wetlands during the 2021–2022 sampling period can be found in an accompanying data package (edi.2087) at https://doi.org/10.6073/pasta/297bd6d93b4fcc8416e4225834db380e.
Woody vegetation composition and structure at long-term monitoring plots on the Stevenson-Hamilton Research Supersite, Kruger National Park, South Africa (2012)
This dataset contains measurements of woody vegetation composition and structural attributes collected in 2012 from long-term ecological monitoring plots located on the Stevenson-Hamilton Research Supersite in the Kruger National Park, South Africa. The study region is characterized by granitic soils, broad-leaved savanna vegetation, and a long history of fire, herbivory, and climate-driven ecological dynamics. Vegetation surveys were conducted in sixteen 0.25-ha sampling plots to quantify woody species composition, stem density, and size structure. Additional measurements of vegetation structure were collected, including grass biomass, canopy cover, canopy height, and canopy diversity, providing a broader assessment of both woody and herbaceous layers. These data establish an important baseline for monitoring ecological change, evaluating woody vegetation dynamics under variable fire and herbivore regimes, and supporting ongoing research on savanna ecosystem functioning within the Kruger National Park.
Riparian Woody Vegetation Composition and Structure in Long-Term Monitoring Plots Along the Sabie River, Kruger National Park (2011-2012)
This dataset contains measurements of woody vegetation composition and structural attributes collected in 2009 and 2010 from 15 long-term riparian monitoring plots located along the Sabie River in the southern region of the Kruger National Park, South Africa. The Sabie River is the park’s most perennial river system and supports diverse riparian plant communities influenced by hydrological variability, flooding dynamics, sediment deposition, herbivory, and climate-driven disturbance. Within each monitoring plot, field teams recorded woody species identity, stem density, plant height, and stem diameter. Additional structural and condition indicators were collected, including canopy breakage, evidence of bark stripping, resprouting status, and whether individuals were toppled or alive at the time of sampling. These structural attributes provide detailed assessments of disturbance impacts and vegetation condition within riparian zones. Data collection followed the same standardized protocols as the Southern Granites long-term vegetation monitoring program, allowing for cross-site comparisons between upland savanna and riparian systems. This dataset provides a baseline for evaluating long-term ecological change in riparian woody plant communities and supports ongoing research on the ecological functioning and resilience of river corridors in Kruger National Park.
Marsh to Upland: Vegetation Monitoring in Coastal Virginia, 2018-2022
This dataset includes data from vegetation plots along a marsh to upland gradient in three salt-marshes along the Eastern Shore of Virginia. Coastal wetlands serve as vital habitats and provide various ecosystems services. These ecosystems are experiencing novel abiotic conditions driven by anthropogenic change, including changes in salinity and moisture due to sea level rise. A key component of wetland ecosystems are their vegetation communities, which often show a transition from non-woody marsh plants like grasses and sedges to woody shrubs and larger trees in the upland reaches of the wetland. This dataset was collected from three coastal wetlands: Boxtree Preserve (Boxtree), Cushmans Landing (Cushmans), and Mockhorn Wildlife Management Area GATR Tract (GATR). Measurements of emergent vegetation percent cover and tree and shrub characteristics are taken annually at maximum biomass for the plant community, which occurs in August in this system (Moore 2013). At each site sampling occurs along four transects which run through the low marsh, high marsh, transitional area, lowest elevation upland forest, and slightly higher elevation upland forest. Each transect is segmented into five zones based on these plant communities, which roughly correspond to elevation bins of 1m. Each zone contains one sampling location.
Forest Transition Experiment - Vegetation Monitoring on a Coastal Virginia Forest, 2019-2023
This dataset contains data on vegetation (shrubs, trees, non-woody vegetation, seedlings and Phragmites occurrence in permanent plots at the Brownsville Forest near Nassawadox, VA.
Seasonal and annual summary statistics of urbanization, vegetation, land surface temperature, and bioclimatic variables derived from remotely-sensed imagery in areas surrounding long-term bird monitoring locations in the greater Phoenix, Arizona, USA metropolitan area (1997-2023)
This data package consists of 26 years (1998-2023) of environmental data and 22 years (2000-2022) years of bioclimatic data associated with CAP-LTER long-term point-count bird censusing sites (https://doi.org/10.6073/pasta/4777d7f0a899f506d6d4f9b5d535ba09), temporally aggregated by year and by four meteorological seasons (Winter, Spring, Summer, Fall). The environmental variables include land surface temperature (LST), three spectral indices of vegetation and water – the normalized difference vegetation index (NDVI), the soil adjusted vegetation index (SAVI), and modified normalized difference water index (MNDWI) – and four spectral indices of impervious surface/urbanization. Impervious surface indices include the normalized difference built-up index (NDBI), the normalized difference impervious surface index (NDISI), the enhanced normalized differences impervious surface index (ENDISI), and the normalized impervious surface index (NISI). LST and all spectral indices were derived from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. The seven bioclimatic variables (e.g., air temperature, precipitation) were sourced from 1-km resolution gridded estimates of daily climatic data from NASA Daymet V4. We created temporally-aggregated Daymet raster images by calculating mean pixel-values for each season and year, as well as seasonally and annually summed precipitation. We summarized the values of each environmental variable by generating variously-sized (100-m, 500-m, 1000-m) buffers around each bird point count location and extracting weighted mean values of each environmental variable, with each pixel's values weighted by the proportion of its area falling within the buffer. All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of s
Soil salinity at GCE-LTER vegetation monitoring plots in October 2015
Soil samples were collected in conjunction with Fall 2015 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.
Soil salinity at GCE-LTER vegetation monitoring plots in October 2016
Soil samples were collected in conjunction with Fall 2016 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.
Soil salinity at GCE-LTER vegetation monitoring plots in October 2017
Soil samples were collected in conjunction with Fall 2017 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.
Soil salinity at GCE-LTER vegetation monitoring plots in October 2018
Soil samples were collected in conjunction with Fall 2018 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.
Soil salinity at GCE-LTER vegetation monitoring plots in October 2019
Soil samples were collected in conjunction with Fall 2019 plant monitoring at half of the permanent vegetation monitoring plots in the creekbank and midmarsh zones at 10 GCE study sites. Pore-water salinity was determined by analysis of supernatant salinity in dried soil samples hydrated with a measured volume of deionized water.
PIE LTER salt marsh vegetation cover data from regularly monitored quadrats along transects in Rowley, MA.
Marsh vegetation cover data from quadrats along transects in salt marsh sites in Rowley, MA. The transects are intended to study long term changes in marsh vegetation. Four sites ((12 transects) were originally set up to study the impact of salt marsh haying. Two of these sites (labeled McH and EPH) were regularly hayed until 2002. The other two (PUH and CC) were reference sites. Two additional sites labeled RM and RR (8 transects) were originally set up to track invasion by Phragmites australis.
PIE LTER salt marsh vegetation frequency of occurrence from regularly monitored transects in Rowley, MA
Marsh vegetation presence-absence data along transects in salt marsh sites in Rowley, MA. The transects are intended to study long term changes in marsh vegetation. Four sites ((12 transects) were originally set up to study the impact of salt marsh haying. Two of these sites (labeled McH and EPH) were regularly hayed until 2002. The other two (PUH and CC) were reference sites. Two additional sites labeled RM and RR (8 transects) were originally set up to track invasion by Phragmites australis.
Remote Sensing Drought Monitoring Dataset based Temperature Vegetation Precipitation Dryness Index (TVPDI) from 2001 to 2020 in China
<p>In this dataset, the MODIS vegetation index and land surface temperature products are processed into NDVI and LST monthly time series with a spatial resolution of 1 km, and the final precipitation data of GPM IMERG are downscaled, unified at a spatial resolution of 1 km. And after a standardization process, using the spatial distance model, a remote sensing drought monitoring dataset in China from 2001 to 2020 was produced based on the Temperature Vegetation Precipitation Dryness Index. For the specific construction process of this data, please refer to https://linkinghub.elsevier.com/retrieve/pii/S0034425720303278</p>
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Allen Brain Atlas
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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.