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555 results for “Woody”
Data from: Decay classes of coarse woody debris in a lowland Dipterocarp forest: implications for volume, density and carbon estimates
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Data from: N/P imbalance as a key driver for the invasion of oligothrophic dune systems by a woody legume
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Shade is the most important factor limiting growth of a woody range expander
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Data from: Spring predictability explains different leaf-out strategies in the woody floras of North America, Europe and East Asia
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Data from: Shifts in woody plant defense syndromes during leaf development
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Data from: Identification of putative orthologous genes for the phylogenetic reconstruction of temperate woody bamboos (Poaceae: Bambusoideae)
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Temporal and palaeoclimatic context of the evolution of insular woodiness in the Canary Islands: Supplementary tables and figures
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Data from: Relationships between resprouting ability, species traits, and resource allocation patterns in woody species in a temperate forest
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Data from: How much of the world is woody?
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Data from: Geographical patterns in phylogenetic diversity of Chinese woody plants and its application for conservation planning
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Data from: Factors explaining variability in woody above-ground biomass accumulation in restored tropical forest
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Characteristics of African Savanna Biomes for Determining Woody Cover
This data set includes the soil and vegetation characteristics, herbivore estimates, and precipitation measurement data for the 854 sites described and analyzed in Sankaran et al., 2005. Savannas are globally important ecosystems of great significance to human economies. In these biomes, which are characterized by the co-dominance of trees and grasses, woody cover is a chief determinant of ecosystem properties. The availability of resources (water, nutrients) and disturbance regimes (fire, herbivory) are thought to be important in regulating woody cover but perceptions differ on which of these are the primary drivers of savanna structure. Analyses of data from 854 sites across Africa (Figure 1) showed that maximum woody cover in savannas receiving a mean annual precipitation (MAP) of less than approximately 650 mm is constrained by, and increases linearly with, MAP. These arid and semi-arid savannas may be considered stable systems in which water constrains woody cover and permits grasses to coexist, while fire, herbivory and soil properties interact to reduce woody cover below the MAP-controlled upper bound. Above a MAP of approximately 650 mm, savannas are unstable systems in which MAP is sufficient for woody canopy closure, and disturbances (fire, herbivory) are required for the coexistence of trees and grass. These results provide insights into the nature of African savannas and suggest that future changes in precipitation may considerably affect their distribution and dynamics (Sankaran et al., 2005).This data set includes the site characteristics and measurement data for the 854 sites described and analyzed in Sankaran et al., 2005. The data are provided in two formats, *.xls and *.csv. See the data format section below for more information. A companion document composed of the supplemental documentation and figures provided with Sankaran et al., 2005 is also included (ftp://daac.ornl.gov/data/global_vegetation/savanna_woody_cover/comp/Woody_Cover.pdf).
LBA-ECO CD-10 Coarse Woody Debris Data at km 67 Tower Site, Tapajos National Forest
This data sets reports properties of fallen course woody debris in an old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from April 2001 through July 2001.Standing and Fallen coarse woody debris (CWD), or necromass were measured in a series of ecological plots at the km 67 eddy flux tower site in the Tapajos National Forest (Figure 2). The data set includes different size classes of debris measured in different plot sizes. Size classes were: 2-10cm (in 64 m2 subplots) , 10-30cm (in 1600 m2 subplots), 30cm (in 38400 m2 subplots), standing (in entire 50m by 1000m transects).
SAFARI 2000 Woody Vegetation Characteristics of Kalahari and Skukuza Sites
This data set contains species composition, basal area, height, and crown cover of all woody plants at six sites along the Kalahari Transect visited in February-March of 2000 as part of SAFARI 2000. Similar measurements on woody and herbaceous vegetation at the Skukuza Flux Tower site in Kruger National Park, South Africa, were made in June of 2000. Leaf area index was derived from measurements made using PAR sensors at each site.Sampling protocol was the same at each site, with a slight variation at Skukuza. A grid of 42 points, 6 rows of 7 columns, each 50 m apart, was laid down in an area 300 m x 350 m for the Kalahari Transect sites. At Skukuza, the grid was 7x7, or 350 m x 350 m, centered on the tower site, yielding 49 points. At each grid point, all woody plants within a circular plot of a fixed radius were identified and measured. Stem circumference was measured on all stems and basal area per stem was derived. Basal area for the circular plots, per species, was calculated and extrapolated to hectares. Tree and stem densities were determined from the number of trees and stems in subplots and extrapolated to hectares. Woody plant height and canopy cover were determined, and aboveground woody biomass and peak leaf area index were estimated. The files are in comma-delimited ASCII format, with the first line listing the data set, author, and date, followed by the data records.
Woody and Herbaceous Vegetation Change across the Savannas of West Africa, 1982-2013
The WAVeTrends dataset is a 0.05 degree (5.55 km) vegetation change product, spanning the West African Sudano-Sahel region. It provides pixel-wise information on concurrent woody and herbaceous vegetation trends over a 32-year period (1982-2013). Change in woody vegetation was derived using long-term rain use efficiency (RUE) sensitivity, i.e., the per-pixel comparison of the difference of mean RUE between the first and last decades of the 32-year time series. Herbaceous vegetation change was defined by short-term RUE sensitivity, i.e., comparing the slope of the RUE relationship (productivity vs. precipitation) between both decades using per-pixel Analysis of Covariance (ANCOVA). Categorical vegetation change was then determined for each pixel using the direction of the change and a significance level of p<0.05. The use of RUE (the amount of biomass produced per unit of precipitation) for vegetation trend analysis in savanna regions relies on the assumption that rainfall is a significant positive driver of net production in drylands. Testing of this long-term productivity-rainfall relationship revealed that the assumption was not always met, therefore, validity flags are included for each pixel location.
LBA-ECO ND-02 Secondary Forest Small Stem, Non-Woody Biomass, Para, Brazil: 1999-2005
This data set reports biomass from small stems and non-woody vegetation measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment. The study location was Fazenda Vitoria, 6.5-km northwest of the town of Paragominas, Para, Brazil, in a 6-year old secondary-growth forest. Vegetation life-forms with diameters less than or equal to 2 cm (grasses, herbs, vines and dead material) were destructively sampled in November 1999, June 2000, June 2001, July 2003, July 2004, and July 2005. All data are provided in a single comma-separated file. The site was divided into three blocks with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea), three were fertilized with phosphorus (50 kg P/ha as superphosphate), three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control.
A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011
This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources.
Woody Biomass for Eastern U.S. Forests, 1983-1996
Estimates of the woody biomass density and pools were derived at the county scale of resolution of all forests of the eastern United States using new approaches for converting inventoried wood volume to estimates of above and belowground biomass. Biomass density and pools were estimated from the US Department of Agriculture Forest Service, Forest Inventory and Analysis database on growing stock volume by forest type and stand size-class. Estimates were compiled for 2,009 counties in the 33 Eastern states based on state-based inventories conducted between 1983 and 1996 (see Brown and Schroeder 1999). Stand volume was converted to aboveground biomass with regression equations for biomass expansion factors (BEF; ratio of aboveground biomass density of all living trees to merchantable volume). Belowground biomass was estimated as a function of aboveground biomass with regression equations. Biomass pools were calculated as the product of biomass density and forest area, summed by stand-size class. Forest area was defined by the Forest Service as land producing or capable of producing in excess of 20 cubic feet per acre per year of industrial roundwood products. Statistics were presented for hardwood and softwood (pine plus spruce-fir) forest categories. The approach accounted for commercial and non commercial tree species with diameters greater than 2.5 cm and included noncommercial tree components (branches, twigs, and leaves). Belowground components include both fine and coarse roots.The estimation methods were based on work by Schroeder et al. 1997 and were also used to estimate aboveground woody production (Brown and Schroeder 1999).Based on the analysis of the biomass data (Brown et al. 1999), total biomass density for hardwood forests ranged from 36 to 344 Mg ha-1, with an area-weighted mean of 159 Mg ha-1. About 50% of all counties had hardwood forests with biomass densities between 125 and 175 Mg ha-1. For softwood forests, biomass density ranged from 2 to 346 Mg ha-1, with an area-weighted mean of 110 Mg ha-1. Biomass densities were generally lower for softwoods than for hardwoods; ca. 40% of all counties had softwood forests with biomass densities between 75 and 125 Mg ha-1. Highest amounts of forest biomass were located in the Northern Lake states, mountain areas of the Mid-Atlantic states, and parts of New England, and lowest amounts in the Midwest states. The total biomass for all eastern forests for the late 1980s was estimated at 20.5 Pg, 80% of which was in hardwood forests. Maps (Brown et al. 1999) provided a visual representation of the pattern of forest biomass densities and pools over space that are useful for forest managers and decision makers, and for verification of vegetation models.
Gridded Estimates of Woody Cover and Biomass across Sub-Saharan Africa, 2000-2004
This dataset provides maps of woody (tree and shrub) cover and biomass across Sub-Saharan Africa at a resolution of 1 km for the period 2000-2004. Canopy cover observations and remote-sensing data related to woody vegetation were used to predict woody cover across Africa. Predicted woody cover, canopy height, and tree allometry were used to estimate woody biomass for Sub-Saharan Africa. Canopy cover observations were assembled from field measurements and Google Earth imagery collected from 2000-2004. Remote-sensing data related to the structural attributes of woody vegetation were derived from MODIS optical data and Q-SCAT (Quick Scatterometer) microwave measurements. Canopy height estimates were derived from spaceborne lidar and tree allometry equations were retrieved from GlobAllomeTree.
MODIS-derived Aggregate, Woody and Herbaceous Leaf Area Index for Africa, 2002-2022
This dataset provides leaf area index (LAI) estimates for Sub-Saharan Africa for woody, herbaceous, and aggregate vegetation types. The estimates were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Level 4 and the native MODIS LAI product (MCD15A2H Version 6.1), which provides LAI measurements every 8 days at 500-m pixel size. Data from the MCD15A2H product were processed further to generate three layers including: a smoothed and gap filled LAI layer referred to as aggregate leaf area index and two additional layers processed to separate woody LAI (tree and shrubs) and herbaceous LAI (grass and forbs). The data include 31 MODIS 10-degree tiles and cover 2002 to 2022. The data are provided in NetCDF format.
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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.