Data coverage
This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported. The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available. These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one .csv file. LeafCarbonNutrients1106 This data set provides carbon (C), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) concentrations in green and senesced leaves. Vegetation characteristics reported include species growth habit, leaf area, mass, and mass loss with senescence. The data were compiled from 86 selected studies in 31 countries, and resulted in approximately 1,000 data points for both green and senesced leaves from woody and non-woody vegetation as described in Vergutz et al (2012). The studies were conducted from 1970-2009. There are two comma-delimited data files with this data set. LAIWoodyPlants1231 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. GlobalLitterCarbonNutrients1244 Measurement data of aboveground litterfall and littermass and litter carbon, nitrogen, and nutrient concentrations were extracted from 685 original literature sources and compiled into a comprehensive database to support the analysis of global patterns of carbon and nutrients in litterfall and litter pools. Data are included from sources dating from 1827 to 1997. The reported data include the literature reference, general site information (description, latitude, longitude, and elevation), site climate data (mean annual temperature and precipitation), site vegetation characteristics (management, stand age, ecosystem and vegetation-type codes), annual quantities of litterfall (by class, kg m-2 yr-1), litter pool mass (by class and litter layer, kg m-2), and concentrations of nitrogen (N), phosphorus (P), and base cations for the litterfall (g m-2 yr-1) and litter pool components (g m-2). The investigators intent was to compile a comprehensive data set of individual direct field measurements as reported by researchers. While the primary emphasis was on acquiring C data, measurements of N, P, and base cations were also obtained, although the database is sparse for elements other than C and N. Each of the 1,497 records in the database represents a measurement site. Replicate measurements were averaged according to conventions described in Section 5 and recorded for each site in the database. The sites were at 575 different locations. AmazonForestStructureLIDAR2412 This dataset provides initial condition files for initializing the Ecosystem Demography Model (ED2). This dataset holds regional forest structure characteristics across the Brazilian Amazon that were derived from 545 airborne lidar transects (300 x 12500 m each) acquired during the Amazon Biomass Estimation Project (EBA2016) campaign in 2016. These data contain vertical distributions of stem density, carbon storage, and other vegetation traits for over 1,300,000 columns (50 x 50 m each) that were aggregated into 288 grid cells (1 x 1 degree). This dataset also contains soil edaphic characteristics obtained from existing datasets and carbon stored in litter and soil layers estimated from the land use history and limited measurements in different land use types. Three types of files are provided: Site files (.sss) hold soil and terrain characteristics. Patch files (.sss) hold patch location, area, disturbance type, stem density, stem basal area, leaf area index (LAI), aboveground biomass (AGB), along with carbon and nitrogen density in several categories for patches within sites. Cohort files (.css) hold diameter at breast height, plant height, stem density, mass of living and dead biomass, LAI, AGB), and plant functional type for cohorts of stems within patches and sites. The data are provided in text format compatible with the ED2 model. Non-ForestTreesSaharaSahel1832 This dataset provides georeferenced polygon vectors of individual tree canopy geometries for dryland areas in West African Sahara and Sahel that were derived using deep learning applied to 50-cm resolution satellite imagery. More than 1.8 billion non-forest trees (i.e., woody plants with a crown size over 3 m2) over about 1.3 million km2 were identified from panchromatic and pansharpened normalized difference vegetation index (NDVI) images at 0.5-m spatial resolution using an automatic tree detection framework based on supervised deep-learning techniques. Combined with existing and future fieldwork, these data lay the foundation for a comprehensive database that contains information on all individual trees outside of forests and could provide accurate estimates of woody carbon in arid and semi-arid areas throughout the Earth for the first time. LULCNigeriaEthiopiaSAfrica2367 This dataset provides a two-tier annual Land Use (LU) and Urban Land Cover (LC) product suite over three African countries, Ethiopia, Nigeria, and South Africa, across a 5-year period of 2016-2020. Remote sensing data sources were used to create 30-m resolution LU maps (Tier-1), which were then utilized to delineate urban boundaries for 10-m resolution LC classes (Tier-2). Random Forest machine learning classifier models were trained on reference data for each tier and country (but one model was trained across all years); models were validated using a separate reference data set for each tier and country. Tier-1 LU maps were based on the 30-m Landsat time series, and Tier-2 urban LC maps were based on the 10-m Sentinel-2 time series. Additional data sources included climate, topography, night-time light, and soils. The overall map accuracy was 65-80% for Tier-1 maps and 60-80% for Tier-2 maps, depending on the year and country. The data are provided in cloud optimized GeoTIFF (COG) format. BASINTCP963 This data set reports stable isotope ratio data of CO2 (13C/12C and 18O/16O) associated with photosynthetic and respiratory exchanges across the biosphere-atmosphere boundary. Measurements were made at selected AmeriFlux sites including Harvard Forest, Howland Fore
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