This data set contains moisture content measurements for fuel sticks located in the forest understory of the rainfall exclusion experimental site, Tapajos National Forest, Para, Brazil. The mean and standard errors are reported for control and treatment plot measurements. The measurements were taken on various dates and times of day between 1998 and 2000 during the dry season.The rainfall exclusion treatment began in late January 2000 and continued through December 2004. About 60% of throughfall (equivalent to approximately half the rainfall) was diverted from a 1-hectare plot (i.e., dry) using plastic panels installed in the understory. The comparable 1-hectare control plot (i.e., wet) was unaltered. The goal of this experiment was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad et al., 2002). There is one comma-separated (.csv) data file with this data set.

This data set contains estimates of understory fuel loads (forest litter) at six locations near Paragominas in Northeastern Amazonia. Samples were collected from three different forest conditions: primary forest, logged forest, and burned forest. Volumes and weights are provided by size and condition class based on the planar transect method of estimating understory fuel loads (Brown 1971). Means and standard errors are reported from 3 transects in each forest x condition class. There is one comma-delimited data file (.csv) with this data set.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products.

This data set contains information that can be used to examine water fluxes in soils beneath tree crops in an Amazonian agroforest. The data consists of repeated measurements of soil matrix pressure and soil moisture content at several depths. The study was carried out at the Empresa Brasileira de Pesquisa Agropecuaria (Embrapa)-Amazonia Ocidental, 29 km North of Manaus, Brazil (3d 8m S, 59d 52m W, 40 - 50 m above sea level), in 1998 and 1999.Microaggregated tropical soils have shown high water conductivity even under unsaturated conditions in laboratory experiments. It is not clear, however, what depth the infiltrating soil water reaches during storm events under humid tropical conditions. Dynamics and fluxes of water were determined with high temporal resolution to a depth of 5 m in a Xanthic Hapludox of central Amazonia, Brazil. The soil water percolated to a depth of 0.9 m within 2 h of a rainfall event of 48 mm. Water fluxes were significantly slower below 0.9 m (17% of infiltration at 0 - 0.9 m) due to higher bulk densities. Percolation not only started rapidly after a rainfall event when soil water suction reached a certain threshold (ca. 20 - 30 hPa) but was also reduced to background levels less than 1 h after the rain had ended. The demonstrated extremely short-term dynamics of water fluxes have implications for measurement design of water availability and solute leaching in microaggregated tropical soil that require correct time integrals of solution concentrations and soil water dynamics. Measurement intervals of 30 min or less were necessary in our study. Rapid water flows may explain the observed high nutrient losses from the topsoil of microaggregated tropical soil and the large accumulation of nutrients in the deep soil (> 5 m).

Tree and liana (vine) measurements were collected in a logging concession at the Fazenda Rohsamar in the municipality of Jurena in northwestern Mato Grosso. Tree identification and diameter measurements were collected between July 31, 2003 and October 14, 2003 on 10-m x 1000-m transects and the liana measurements were collected between August 5, 2003 and October 14, 2003 on 10 2-m x 1000-m transects within a 1400 ha logging block ( Feldpauschh et al. 2006). Liana transects were nested within tree census transects to relate total species data to the tree inventory. The biomass of lianas was calculated using two different allometric equations derived for lianas in Amazonian forests ( Gerwing and Farias, 2000; Gerwing et al. 2004). Comma-separated data files of measurements of (1) tree species (diameter >10 cm), and forest characteristics, (2) measurements of liana diameter, forest characteristics, and calculated biomass, and (3) georeference points for the liana sampling transects are provided.Selective logging has become a dominant land-use in Brazilian Amazonia. Published data on forest biomass in southern Amazonia is sparse. As part of a larger study to evaluate the effect of reduced impact logging on carbon dynamics and nutrient stocks, forest structure, and forest regeneration potential, we conducted a pre-harvest campaign to estimate tree and liana biomass in a parcel of managed forest in northwestern Mato Grosso. Prior to logging in 2003, a scientific inventory was conducted in Block 5 of the logging concession(Figure 1). Tree characteristics for all trees and palms > 10 cm DBH was measured by stratified sampling across the block to account for differences in tree densities (trees/ha). Transects were located using a commercial timber inventory to identify tree trunks approximately 10 cm DBH, lower and upper canopy height, species, and location of all individuals to the nearest 10 cm on an x-y grid. Diameter of all liana stems were included if their ultimate rooting point before ascending into the canopy fell within the transect. Lianas that had been cut due to reduced impact logging practices were also measured. Distance along the transect was recorded for each stem.

This data set reports the results of a study to measure soil emissions of the carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and nitric oxide (NO) throughout an entire cropping cycle in (1) slash-and-burn and (2) chop-and-mulch prepared agricultural fields from 2001-2004. An adjacent 15-year-old fallow field with secondary forest vegetation served as the control. The study site is within the municipality of Igarape Acu, Para, Brazil, at the Experimental Farm of the Federal Rural University of Amazonia. Flux data are reported in one comma-separated file.

Nitrogen is a major nutrient in terrestrial ecosystems and an important catalyst in tropospheric photochemistry. Over the last century human activities have dramatically increased inputs of reactive nitrogen (Nr, the combination of oxidized, reduced and organically bound nitrogen) to the Earth system. Nitrogen cycle perturbations have compromised air quality and human health, acidified ecosystems, and degraded and eutrophied lakes and coastal estuaries [Vitousek et al., 1997a, 1997b; Rabalais, 2002; Howarth et al., 2003; Townsend et al., 2003; Galloway et al., 2004]. To begin to quantify the changes to the global N cycle, we have assembled key flux data and N2O mixing ratios from various sources. The data assembled from different sources includes fertilizer production from 1920-2004; manure production from 1860-2004; crop N fixation estimated for three time points, 1860, 1900, 1995; tropospheric N2O mixing ratios from ice core and firn measurements, and tropospheric concentrations to cover the time period from 1756-2004. The changing N2O concentrations provide an independent index of changes to the global N cycle, in much the same way that changing carbon dioxide concentrations provide an important constraint on the global carbon cycle. The changes to the global N cycle are driven by industrialization, as indicated by fossil fuel NOx emission, and by the intensification of agriculture, as indicted by fertilizer and manure production and crop N2 fixation. The data set and the science it reflects are by nature interdisciplinary. Making the data set available through the ORNL DAAC is an attempt to make the data set available to the considerable interdisciplinary community studying the N cycle.

This data set provides high-resolution surface reflectance, thermal imagery, burn severity metrics, and LiDAR-derived structural measures of forested areas in the Sierra Nevada Mountains, California, USA, collected before and after the August 2013 Rim and September 2014 King mega forest fires. Pre-fire data were paired with post-fire collections to assess pre- and post-fire landscape characteristics and fire severity. Field estimates of fire severity were collected to compare with derived remote sensing indices. Reflectance measurements for the spectroscopic AVIRIS and MASTER sensors are distributed as multi-band geotiffs for each megafire and acquisition date. Derived operational metric products for each sensor are provided in individual GeoTIFFs. GeoTIFFs produced from LiDAR point data depict first order topographic indices and summary statistics of vertical vegetation structure.

This data set contains an inventory of natural and anthropogenic methane emissions for all counties in the six New England states of Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and Maine. The inventory represents a snapshot in time (circa 1990-1994) and provides emission estimates for multiple sources including wetlands, landfills, ruminant animals, residential wood combustion, fossil fuel combustion and use, animal manure, wastewater treatment, and natural gas transmission pipelines. Also included is the uptake or sink of methane in relatively well-drained upland soils.

This data set provides maps produced from model output data from the National Aeronautics and Space Administration-Carnegie Ames Stanford Approach (NASA-CASA) model and other modeling approaches. The maps include estimated annual Net Primary Production (ANPP), leaf (live) biomass carbon, wood (live) biomass carbon, fine root (live) biomass carbon, metabolic leaf litter (dead) carbon, structural leaf litter (dead) carbon, woody detritus (dead) carbon, and slow soil carbon, gridded at half-degree spatial resolution for the years 1982-1998, and 2001 (NPP data) for Brazil. Maps are provided at one-degree resolution for monthly soil emissions and soil uptake of N2O, NO, CO, and CH4. In addition, there are maps in 8-km resolution for soil texture, soil carbon, soil pH, soil maximum plant available water (paw), and net primary productivity (NPP).There are three files with this data set in tar.gz format. The files are in half-degree, one-degree, and 8-km resolution. When expanded, the half degree and one degree files contain 83 map files in GeoTIFF (.tif) format. The third file (8-km resolution) contains the soil and productivity maps. When expanded, this file contains 22 files in GeoTIFF (.tif) format.

This dataset provides annual estimates of tree mortality due to fires and bark beetles from 2003 to 2012 on forestland in the continental western United States. Tree mortality was estimated at 1-km spatial resolution by combining tree aboveground carbon (AGC) and disturbance datasets derived largely from remote sensing. Tree mortality is expressed as the amount of AGC stored in trees killed by disturbance (Mg carbon per km2). The dataset also includes annual uncertainty maps that were generated using a Monte Carlo approach in which tree biomass, biomass carbon content, and disturbance severity were iteratively varied by their uncertainty.