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Cell biology, microbiology, ecology, biodiversity, species data, evolutionary biology
24,625 datasets
Landgate's Woody Change product identifies transitions in perennial woody vegetation cover between 2007 and 2008 using 30-meter Landsat imagery. It classifies pixel-level changes across categories like forest, sparse woody, and non-woody vegetation.
Landgate's annual product identifies transitions in perennial woody vegetation between forest, sparse woody, and non-woody classifications for Western Australia. The data is derived from 30-meter resolution Landsat imagery and tracks six change classes, including forest to non-woody and non-woody to sparse.
Landgate annually produces vegetation change products identifying transitions between forest, sparse woody, and non-woody classifications from Landsat imagery. The dataset includes change classes such as non-woody to forest, forest to non-woody, and sparse to forest.
Landgate's vegetation change product identifies transitions in perennial woody cover between 2013 and 2014 using 30-meter Landsat imagery. The dataset classifies pixel-level changes among forest, sparse woody, and non-woody categories. It includes change classes such as no change, non-woody to forest, and forest to non-woody.
Western Australia vegetation change products identify transitions in perennial woody cover between forest, sparse woody, and non-woody classifications for the 2015-2016 period. The dataset is produced by Landgate using 30-meter resolution Landsat imagery. Change classes include no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody, and forest to sparse.
Landgate's Woody Change product identifies annual changes in perennial woody vegetation from Landsat imagery. It classifies transitions between forest, sparse woody, and non-woody categories for the 2011-2012 period. The dataset includes change classes such as non-woody to forest and forest to non-woody.
Proteomic analysis of canine mammary tissues identified 12 differentially expressed extracellular matrix proteins. The dataset includes eight upregulated proteins (COL12A1, COL4A1, COL4A2, SERPINH1, SERPINF1, HTRA1, TNC, PCOLCE) and four downregulated proteins (MMRN1, ABI3BP, DPT, OGN). Findings were validated against human breast cancer transcriptomic data, highlighting conserved molecular signatures.
Grant UKCCSRC-C2-209 funded a demonstration of calcium looping, a carbon capture technology operating around 650°C. The project poster was presented at a CSLF reception in London on June 27, 2016. The British Geological Survey (BGS) is listed as the organization for this dataset.
2009-2010 annual change products identify locations where perennial woody vegetation changed between forest, sparse woody, and non-woody classifications based on 30-meter Landsat imagery. The dataset, produced by Landgate, includes change classes such as non-woody to forest and forest to non-woody.
District of Columbia's RiverSmart Homes program data details incentives offered to residents for reducing stormwater runoff. The program provides financial and technical assistance for installing rain barrels, rain gardens, native plantings, shade trees, and permeable pavers. It is maintained by the District of Columbia government and was last updated in April 2026.
High-quality digital SLR images are captured at rangeland vegetation plots across Australia using standardized AusPlots methodologies. At each plot, three photopoints are established in an equilateral triangle, with each point capturing a 360° panoramic sequence of up to 40 photographs with a minimum 50% overlap.
Western Australia's Landgate agency provides annual vegetation change products identifying transitions in perennial woody cover. The data classifies changes between forest, sparse woody, and non-woody categories using 30-meter resolution Landsat imagery for the 2017-2018 period.
A 3D Digital Canopy Model representing the altitude of arboreal vegetation for Montreal in 2015. This model corresponds to a 2D canopy dataset from the same year and can be integrated with a 2015 Numerical Surface Model for enhanced coverage.
Great Smoky Mountains National Park hosts field data from 10-20 m2 plots established to monitor the decline of eastern hemlock trees. The dataset likely contains measurements of tree diameters, understory vegetation, soil microbial communities, ant species, and decomposition rates to test predictions about ecosystem changes. Data was collected by a researcher affiliated with the Department of the Interior and last updated in March 2026.
131.5 KB of data on predation by birds, ants, and all predators on caterpillars exposed for 72 hours. The dataset, authored by Katerina Sam and last updated in April 2026, records predation events in canopy and understory layers of forests along a latitudinal gradient.
Vegetation change products identify transitions between forest, sparse woody, and non-woody classifications annually. The data is produced by Landgate using Landsat imagery with a 30-meter ground pixel resolution. Change classes include no change and conversions between the three vegetation states.
Hourly and monthly estimates of Net Ecosystem Exchange (NEE) of CO2 across the conterminous United States at a 50 km resolution from January 2012 to October 2014. The dataset was generated by the Ecosystem Demography Biosphere Model (ED2), uniquely constrained by AirMOSS-derived root zone soil moisture measurements. This model-data fusion approach aims to improve predictions of carbon fluxes by accounting for soil moisture impacts on ecosystem processes.
Annual products identify changes in perennial woody vegetation between forest, sparse woody, and non-woody classifications. The data, created by Landgate, covers the period from 1972 to 1977.
60 vegetation plots across four forest canopy variants reveal that the invasive tree Prunus virginiana imposes stronger habitat effects than its congener P. serotina, reducing light and increasing litter. When both species co-occur, understory structure resembles that under P. serotina, suggesting a weakening of P. virginiana's stronger impacts and contrasting with invasional meltdown predictions. The dataset includes measurements of canopy openness, biomass, soil properties, and taxonomic, functional, and phylogenetic diversity of understory plants.
Vegetation change products identify transitions in perennial woody cover between forest, sparse woody, and non-woody classifications annually. The dataset, produced by Landgate, covers the period 1977-1980 using 30-meter resolution Landsat imagery.