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638 results for “biomes”
A Registry Study of Biomarkers in Progression of Acute Heart Failure(BIOMS-POAHF)
ClinicalTrials.gov study NCT04108182. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: The evolution of sexual and parthenogenetic Warramaba: a window onto Plio-Pleistocene diversification processes in an arid biome
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Data from: Defining functional biomes and monitoring their change globally
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Data from: Speciation with gene flow in whiptail lizards from a Neotropical xeric biome
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Data from: Identification of habitat-specific biomes of aquatic fungal communities using a comprehensive nearly full-length 18S rRNA dataset enriched with contextual data
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Data sets used in the manuscript titled "Ecosystem-level energy and water budgets are resilient to canopy mortality in sparse semi-arid biomes"
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Data from: Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area
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Data from: Cross-biome metagenomic analyses of soil microbial communities and their functional attributes
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Data from: The global distribution of grass functional traits within grassy biomes
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Variation among biomes in temporal dynamics of aboveground primary production, from 1975 to 1998, LTER
This data package consists of Annual net primary production (ANPP) and annual precipitation data from 11 Long Term Ecological Research (LTER) sites across North America. Data were compiled for analyses summarized in a study published in Science (2001, 291:481-484 DOI: 10.1126/science.291.5503.481). These data were obtained online or received directly form site investigators. For those sites with multiple communities sampled, only a single, representative community type was selected from each site. Each LTER site included in this dataset used unique methods for estimating ANPP (see individual web pages at http://sites.lternet.edu/for details).
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).
NPP Multi-Biome: TEM Calibration Data, 1992, R1
This data set contains one data file (.csv format) that is known as the Terrestrial Ecosystem Model (TEM) data set. The data provide pool sizes and fluxes of carbon (C) and nitrogen (N) for 16 globally distributed field sites that represent a wide range of terrestrial biomes, tundra to tropical forest, but exclude wetlands. The net primary productivity (NPP) data were extracted from the literature. They were not previously widely available to the ecosystem modeling community in electronic form until this data set and additional NPP data sets were published by the ORNL DAAC. The data were used to calibrate the ecosystem process-based TEM. The TEM was developed by staff at the Ecosystem Center, Marine Biological Laboratory, Woods Hole, Massachusetts, USA, to estimate the spatial and temporal distribution of major carbon (C) and nitrogen (N) fluxes and pool sizes at continental to global scales (resolution: 0.5 degrees latitude x 0.5 degrees longitude). Eight of the TEM calibration sites are also included in the ORNL DAAC NPP data collection as individual site NPP data sets. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1999.
NPP Multi-Biome: PIK Data for Northern Eurasia, 1940-1988 (Based on Bazilevich), R1
There is one comma-separated (.csv) data file and one text (.txt) file (bibliographic information) with this data set. This data set provides above-ground net primary production (ANPP) and total net primary producitivity (NPP) [expressed in grams of carbon per square meter per year (gC/m2/year)], and the C fraction used to convert dry biomass weight to carbon content, for 127 unique study sites in northern Eurasia. The sites are classified by ecozone (i.e., tundra, forest-tundra, taiga, mixed forest, broadleaf forest, small-leaved secondary forests, forest bogs, meadows, steppe, semi-desert, and polar desert) and plant community (phytocoenosis). Each study location is georeferenced (latitude/longitude) with elevation and zonal/interzonal information. References to original author, year of publication, and table/record in Bazilevich (1993) are also included. The data set also provides a bibliography of 274 original-source references (in Russian) to accompany the 127 data records on NPP from Bazilevich (1993). The data are a subset of data adapted from Bazilevich, N.I. 1993. Biological Productivity of Ecosystems of Northern Eurasia. Nauka Publishers, Moscow. 293 pp. (in Russian). The data set originated from field measurements of primary productivity collected between 1940 and 1988 for most of the terrestrial vegetation types in northern Eurasia. The NPP data collection contains field measurements of biomass, estimated NPP, and climate data for terrestrial grassland, tropical forest, temperate forest, boreal forest, and tundra sites worldwide. Data were compiled from the published literature for intensively studied and well-documented individual field sites and from a number of previously compiled multi-site, multi-biome data sets of georeferenced NPP estimates. The principal compilation effort (Olson et al., 2001) was sponsored by the NASA Terrestrial Ecology Program. For more information, please visit the NPP web site at http://daac.ornl.gov/NPP/npp_home.html.
NACP Biome-BGC Modeled Ecosystem Carbon Balance, Pacific Northwest, USA, 1986-2010
This data set provides Biome-BGC modeled estimates of carbon stocks and fluxes in the U.S. Pacific Northwest for the years 1986-2010. Fluxes include net ecosystem production (NEP), and net aboveground wood growth. Stocks include aboveground wood mass. Also present are mapped distributions of associated forest disturbances, distinguished by disturbance type (harvest, fire, pest/pathogen). The data are presented in a mapped form as well as in tabular summaries broken out by ownership and ecoregion. Maps of annual precipitation and temperature data are included for the years 1980-2010.
Biome-BGC: Modeling Effects of Disturbance and Climate (Thornton et al. 2002)
This archived model product contains the directions, executables, and procedures for running Biome-BGC, Version 4.1.1, to recreate the results of: Thornton, P.E., Law, B.E., Gholz, H.L., Clark, K.L., Falge, E., Ellsworth, D.S., Goldstein, A.H., Monson, R.K., Hollinger, D., Falk, M., Chen, J. and Sparks, J.P. 2002. Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests. Agricultural and Forest Meteorology 113:185-222.Thornton et al., 2002 excerpt: AbstractThe effects of disturbance history, climate, and changes in atmospheric carbon dioxide (CO2) concentration and nitrogen deposition (Ndep) on carbon and water fluxes in seven North American evergreen forests are assessed using a coupled water, carbon, nitrogen model, canopy-scale flux observations, and descriptions of the vegetation type, management practices, and disturbance histories at each site. The effects of interannual climate variability, disturbance history, and vegetation ecophysiology on carbon and water fluxes and storage are integrated by the ecosystem process model Biome-BGC, with results compared to site biometric analyses and eddy covariance observations aggregated by month and year. The model produced good estimates of between-site variation in leaf area index, with mixed performance for between- and within-site variation in evapotranspiration. There is a model bias toward smaller annual carbon sinks at five sites, with a seasonal model bias toward smaller warm-season sink strength at all sites.
Literature-Derived Parameters for the BIOME-BGC Terrestrial Ecosystem Model
Ecosystem simulation models use descriptive input parameters to establish the physiology, biochemistry, structure, and allocation patterns of vegetation functional types, or biomes. For single-stand simulations, it is possible to measure required data, but as spatial resolution increases, data availability decreases. Generalized biome parameterizations are then required. Undocumented parameter selection and unknown model sensitivity to parameter variation for larger-resolution simulations are currently the major limitations to global and regional modeling. We present documented input parameters for process-based ecosystem simulation models (specifically for the BIOME-BGC) for major natural temperate biomes. Parameter groups include the following: turnover and mortality; allocation; carbon to nitrogen ratios (C:N); the percent of plant material in labile, cellulose, and lignin pools; leaf morphology; leaf conductance rates and limitations; canopy water interception and light extinction; and the percent of leaf nitrogen in Rubisco (i.e., ribulose bisphosphate-1,5-carboxylase/oxygenase). Input parameters may also be used for other ecosystem models.
Biome-BGC: Terrestrial Ecosystem Process Model, Version 4.1.1
Biome-BGC is a computer program that estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. The primary model purpose is to study global and regional interactions between climate, disturbance, and biogeochemical cycles.Biome-BGC represents physical and biological processes that control fluxes of energy and mass. These processes include: New leaf growth and old leaf litterfall Sunlight interception by leaves and penetration to the ground Precipitation routing to leaves and soil Snow accumulation and melting Drainage and runoff of soil water Evaporation of water from soil and wet leaves Transpiration of soil water through leaf stomata Photosynthetic fixation of carbon from CO2 in the air Uptake of nitrogen from the soil Distribution of carbon and nitrogen to growing plant parts Decomposition of fresh plant litter and old soil organic matter Plant mortality Fire The model uses a daily time-step. This means that each flux is estimated for a one-day period. Between days, the program updates its memory of the mass stored in different components of the vegetation, litter, and soil. Weather is the most important control on vegetation processes. Flux estimates in Biome-BGC depend strongly on daily weather conditions. Model behavior over time depends on climate--the history of these weather conditions.A companion file with more information about Biome-BGC and its components is available at ftp://daac.ornl.gov/data/model_archive/BIOME_BGC/biome_bgc_4.1.1/comp/BiomeBGC_v411_release.pdf .Biome-BGC, Version 4.1.1 was developed and is maintained by the Numerical Terradynamic Simulation Group, School of Forestry, The University of Montana, Missoula, Montana, USA. Additional information can be found on there web site at: http://www.ntsg.umt.edu/.
NPP Multi-Biome: Global Primary Production Data Initiative Products, R2
Net primary productivity (NPP) estimates were compiled by the Global Primary Production Data Initiative (GPPDI). The database covers 2,523 individual sites and 5,164 half-degree grid cells and underwent extensive review under the Ecosystem Model-Data Intercomparison (EMDI) process. The GPPDI database includes NPP measurements that were collected over a long time period by many investigators using a variety of methods. The measurements are categorized as either Class A, from intensively studied sites; Class B, from extensive sites; or reported as Class C, 0.5 latitude-longitude grid cells. The data set contains six comma-separated files (.csv format). There are two files for each class. One file for each class contains site locations, elevation, NPP estimates, climate data, biome and dominant species information, and references. The other file for each class contains model validation outlier flags derived from site-specific reviews. This document and a companion file (Olson et al., 2001) describe the compilation of NPP estimates under the GPPDI. The results of the EMDI review and outlier analysis produced a refined set of NPP estimates and model driver data (the EMDI database; Olson et al., 2001; 2013). Another ORNL DAAC data set (Zheng et al., 2013) contributed to the compilation of GPPDI. Revision Notes: This data set has been revised to correct previously reported ANPP, BNPP, and TNPP estimates for three OTTER Transect sites, USA, in the Class A NPP data file and BNPP, and TNPP estimates for Vindhyan, India, in the Class B NPP data file. Please see the Data Set Revisions section of this document for detailed information.
Biome-BGC: Modeling Carbon Dynamics in Ponderosa Pine Stands (Law et al. 2003)
This archived model product contains the directions, executables, and procedures for running Biome-BGC, Version 4.1.2, to recreate the results of Law BE, Sun OJ, Campbell J, Van Tuyl S, Thornton PE, 2003. Changes in carbon storage and fluxes in a chronosequence of ponderosa pine. Global Change Biology, 9(4), 510-514.Law et al. 2003 excerpt: Abstract Forest development following stand-replacing disturbance influences a variety of ecosystem processes including carbon exchange with the atmosphere. On a series of ponderosa pine (Pinius ponderosa var. Laws.) stands ranging from 9 to > 300 years in central Oregon, USA, we used biological measurements to estimate carbon storage in vegetation and soil pools, net primary productivity (NPP) and net ecosystem productivity (NEP) to examine variation with stand age. Measurements were made in 2000 on a chronosequence of 12 ponderosa pine stands. Total ecosystem carbon storage and the fraction of ecosystem carbon in aboveground wood mass increased rapidly until 150-200 years, and did not decline in older stands. Forest inventory data on 950 ponderosa pine plots in Oregon show that the greatest proportion of plots exist in stands ~ 100 years old, indicating that a majority of stands are approaching maximum carbon storage and net carbon uptake. Our data suggests that NEP averages ~ 70 g C m-2 year-1 for ponderosa pine forests in Oregon. About 85% of the total carbon storage in biomass on the survey plots exists in stands greater than 100 years, which has implications for managing forests for carbon sequestration. To investigate variation in carbon storage and fluxes with disturbance, simulation with process models requires a dynamic parameterization for biomass allocation that depends on stand age, and should include a representation of competition between multiple plant functional types for space, water, and nutrients.
Carbon Monitoring System Carbon Flux from the Net Biome Exchange L4 V2 (CMSFluxNBE) at GES DISC
This dataset provides the Carbon Flux from the Net Biome Exchange.The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.