Find research datasets worth reusing

Pinon-Juniper (Core Site) Seasonal Biomass and Seasonal and Annual NPP Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New Mexico

This dataset contains pinon-juniper woodland biomass data and is part of a long-term study at the Sevilleta LTER measuring net primary production (NPP) across four distinct ecosystems: creosote-dominant shrubland (Site C, est. winter 1999), black grama-dominant grassland (Site G, est. winter 1999), blue grama-dominant grassland (Site B, est. winter 2002), and pinon-juniper woodland (Site P, est. winter 2003). Net primary production is a fundamental ecological variable that quantifies rates of carbon consumption and fixation. Estimates of NPP are important in understanding energy flow at a community level as well as spatial and temporal responses to a range of ecological processes. Above-ground net primary production is the change in plant biomass, represented by stems, flowers, fruit and and foliage, over time and incoporates growth as well as loss to death and decomposition. To measure this change the vegetation variables in this dataset, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at permanent 1m x 1m plots within each site. A third sampling at Site C is performed in the winter. Volumetric measurements are made using vegetation data from permanent plots (SEV278, "Pinon-Juniper (Core Site) Quadrat Data for the Net Primary Production Study") and regressions correlating species biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."

Biome Transition Along Elevational Gradients in New Mexico (SEON) Study: Flux Tower Seasonal Biomass and Seasonal and Annual NPP Data at the Sevilleta National Wildlife Refuge, New Mexico

The varied topography and large elevation gradients that characterize the arid and semi-arid Southwest create a wide range of climatic conditions - and associated biomes - within relatively short distances. This creates an ideal experimental system in which to study the effects of climate on ecosystems. Such studies are critical given that the Southwestern U.S. has already experienced changes in climate that have altered precipitation patterns (Mote et al. 2005), and stands to experience dramatic climate change in the coming decades (Seager et al. 2007; Ting et al. 2007). Climate models currently predict an imminent transition to a warmer, more arid climate in the Southwest (Seager et al. 2007; Ting et al. 2007). Thus, high elevation ecosystems, which currently experience relatively cool and mesic climates, will likely resemble their lower elevation counterparts, which experience a hotter and drier climate. In order to predict regional changes in carbon storage, hydrologic partitioning and water resources in response to these potential shifts, it is critical to understand how both temperature and soil moisture affect processes such as evapotranspiration (ET), total carbon uptake through gross primary production (GPP), ecosystem respiration (Reco), and net ecosystem exchange of carbon, water and energy across elevational gradients. We are using a sequence of six widespread biomes along an elevational gradient in New Mexico -- ranging from hot, arid ecosystems at low elevations to cool, mesic ecosystems at high elevation to test specific hypotheses related to how climatic controls over ecosystem processes change across this gradient. We have an eddy covariance tower and associated meteorological instruments in each biome which we are using to directly measure the exchange of carbon, water and energy between the ecosystem and the atmosphere. This gradient offers us a unique opportunity to test the interactive effects of temperature and soil moisture on ecosystem proces

Effects of Multiple Resource Additions on Community and Ecosystem Processes: NutNet Seasonal Biomass and Seasonal and Annual NPP Data at the Sevilleta National Wildlife Refuge, New Mexico

Two of the most pervasive human impacts on ecosystems are alteration of global nutrient budgets and changes in the abundance and identity of consumers. Fossil fuel combustion and agricultural fertilization have doubled and quintupled, respectively, global pools of nitrogen and phosphorus relative to pre-industrial levels. In spite of the global impacts of these human activities, there have been no globally coordinated experiments to quantify the general impacts on ecological systems. This experiment seeks to determine how nutrient availability controls plant biomass, diversity, and species composition in a desert grassland. This has important implications for understanding how future atmospheric deposition of nutrients (N, S, Ca, K) might affect community and ecosystem-level responses. This study is part of a larger coordinated research network that includes more than 40 grassland sites around the world. By using a standardized experimental setup that is consistent across all study sites, we are addressing the questions of whether diversity and productivity are co-limited by multiple nutrients and if so, whether these trends are predictable on a global scale. Above-ground net primary production is the change in plant biomass, represented by stems, flowers, fruit and and foliage, over time and incoporates growth as well as loss to death and decomposition. To measure this change the vegetation variables, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at permanent 1m x 1m plots within each site. Volumetric measurements are made using vegetation data from permanent plots (SEV231, "Effects of Multiple Resource Additions on Community and Ecosystem Processes: NutNet NPP Quadrat Sampling") and regressions correlating species biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."

Extreme Drought in Grassland Ecosystems (EDGE) Seasonal Biomass and Seasonal and Annual NPP Data at the Sevilleta National Wildlife Refuge, New Mexico

Net primary production is a fundamental ecological variable that quantifies rates of carbon consumption and fixation. Estimates of NPP are important in understanding energy flow at a community level as well as spatial and temporal responses to a range of ecological processes. While measures of both below- and above-ground biomass are important in estimating total NPP, this study focuses on above-ground net primary production (ANPP). Above-ground net primary production is the change in plant biomass, including loss to death and decomposition, over a given period of time. Volumetric measurements are made using vegetation data from permanent plots collected in SEV297, "Extreme Drought in Grassland Ecosystems (EDGE) Net Primary Production Quadrat Data" and regressions correlating biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."

opencc-by-4.0Aug 2024View details →

US Atlantic and Gulf Coast Annual Wetland Land Cover and Change Maps, 1985 to 2022

<h3>This dataset is associated with the following article published in Remote Sensing Applications: Society and Environment, which can be accessed here: https://doi.org/10.1016/j.rsase.2024.101392</h3> Shortly after publishing version 2, errors in the map projections were identified and corrected. Please use version 3 instead of version 2. Updates to version 2 were as follows: <ul> <li>Includes watersheds in Texas that were not included in Version 1.</li> <li>A color map (using ArcPro) was added for improved interpretation.</li> <li>A sub-pixel scale offset in the change type map, related to map projection errors, was corrected.</li> </ul> <h2>Mapping Coastal Wetland Changes from 1985 to 2022 in the US Atlantic and Gulf Coasts using Landsat Time Series and National Wetland Inventories</h2> Courtney A. Di Vittorio1, Melita Wiles2, Yasin W. Rabby2, Saeed Movahedi2, Jacob Louie1, Lily Hezrony1, Esteban Coyoy Cifuentes1, Wes Hinchman1, Alex Schluter1 1Department of Engineering, Wake Forest University, Winston-Salem, North Carolina, USA. 2Department of Statistics, Wake Forest University, Winston-Salem, North Carolina, USA. <h3>Abstract</h3> The areal extent of coastal wetlands is declining rapidly worldwide, and scientists and land managers need land cover maps that show the magnitude and severity of changes over time to assess impacts and develop effective conservation strategies. Within the United States (US), the widely-used, continental-scale wetland land cover data products are either static in time (The National Wetlands Inventory) or have a course temporal resolution, and do not distinguish between different types of change (the NOAA Coastal Change Analysis Program, C-CAP). This study presents a new coastal wetland geospatial data product that leverages the Landsat database and maps annual land cover across the US Atlantic and Gulf Coasts from 1985 to 2022. The algorithm was trained on the existing US wetland inventories to make the final maps compatible with products that are used in operational management. A multi-stage classification approach was designed that uses Google Earth Engine and the Continuous Change Detection and Classification (CCDC) algorithm to characterize time series of remote sensing imagery with fitted harmonic functions and identify when changes likely occurred. The fitted time series models are then input into a random forest classifier to make a class prediction. An annual-scale random forest classification is performed in parallel, and results from both algorithms are combined and analysed to detect both gradual and abrupt changes and to identify transitional time series segments. A time series smoothing procedure is subsequently applied to ensure class transitions are logical and consistent and extract a summative change characterization map that shows the severity and spatial density of change. The final maps distinguish between four homogenous classes and six mixed classes, representing areas that are transitioning between classes and where the boundaries between classes are unstable. The average overall accuracy of the algorithm is 93.7%, and the average class omission and commission errors are 6.7% and 6.4%, respectively. A variety of change detection comparisons were performed, using the existing wetland inventory that employed a fundamentally different change detection approach, and a more comparable annual-scale, Landsat-derived product that estimated changes across the Northeastern Atlantic Coast. These comparisons show that the magnitude of severe changes matches that of the existing inventory and the magnitude of the moderate changes matches that of the more comparable product. The 2019 Wetland Status and Trends Report estimated that net loss rates in emergent wetlands from 2010 to 2019 amount to 1.7%, and the new maps show an equivalent loss rate of 1.6%, again showing close agreement.

opencc-by-4.0Jan 2022View details →

Global annual soil respiration from 2000 to 2020

This dataset contains a product of annual global soil respiration from 2000 to 2020 at 1 km×1 km spatial resolution. It is an updated dataset and the previous dataset includes a product of annual global soil respiration from 2000 to 2014 (<a href="https://doi.org/10.5061/dryad.w3r2280nq">https://doi.org/10.5061/dryad.w3r2280nq</a>). More details on this dataset are presented in the paper titled “Spatial and temporal variations in global soil respiration and their relationships with climate and land cover”. This dataset was derived using satellite remote sensing data, biome-specific statistical models, and 1,292 site years of globally-distributed in-situ soil respiration measurements. All data processing and statistical analyses were conducted using Matlab (The MathWorks, Natick, MA).

opencc-by-4.0Sep 2022View details →

Annual Article Processing Charges (APCs) and number of gold and hybrid open access articles in Web of Science indexed journals published by Elsevier, Sage, Springer-Nature, Taylor & Francis and Wiley 2015-2018

Dataset of annual Article Processing Charges (APCs) for 6,252 journals from 2015 to 2018. The dataset contains annual APCs for journals indexed in the Web of Science (WoS) and published by the oligopoly of academic publishers (Elsevier, Sage, Springer-Nature, Taylor & Francis, Wiley). It also includes an estimate of the total APCs paid by the academic community based on the number of gold and hybrid articles published between 2015 and 2018. The dataset was created using publication data from WoS, OA status from Unpaywall and annual APC prices from open datasets (<a href="https://doi.org/10.5281/ZENODO.3841568">Matthias, 2020</a>; <a href="https://doi.org/10.5683/SP2/84PNSG">Morrison, 2021</a>) and historical fees retrieved via the Internet Archive Wayback Machine.  Detailed methods and findings are reported in the following journal article Butler, L.-A., Matthias, L., Simard, M.-A., Mongeon, P., & Haustein, S. (2023). The Oligopoly's Shift to Open Access. How the Big Five Academic Publishers Profit from Article Processing Charges. Quantitative Science Studies. Preprint: <a href="https://doi.org/10.5281/zenodo.8322555">https://doi.org/10.5281/zenodo.8322555</a> Description of included files (v1): APCs.csv: contains the annual APCs for gold and hybrid OA journals indexed in Web of Science published by the oligopoly of academic publishers (Elsevier, Sage, Springer-Nature, Taylor & Francis, Wiley) between 2015 and 2018 including the total estimate of APCs paid per journal per year. It contains APC data for 18,846 journal-year-OA status combinations. countries.csv: contains the fractionalized number of annual gold and hybrid OA articles by oligopoly publishers between 2015 and 2018 and the total estimate of fractionalized APCs paid per country per journal per year. oecd.csv: contains the fractionalized number of annual gold and hybrid OA articles by oligopoly publishers between 2015 and 2018 and the total estimate of fractionalized APCs per discipline per journal per year. ReadMe.csv: contains a description of the variables used in APCs.csv, countries.csv and oecd.csv.

opencc-by-4.0Apr 2024View details →

2010_2023_ERA5_Precipitation_Daily_Dekadal_Monthly_Annual_5k_ER

Precipitation from the ERA5 reanalysis archive supplied by the European Centre of Medium Range Weather Forecasting for 2010 - 2023. Abstract: Precipitation from the ERA5 reanalysis archive supplied by the European Centre for Medium Range Weather Forecasting . for 2010 - 2023 . The original data is at 0.25 degree resolution and was downloaded and scaled by ERA extraction algroithms. The daily data have been aggregated into dekadal, monthly, and annual datasets to match the outputs produced by NASA from the MODIS imagery temperature and vegetation Index datasets. The resolution was also chosen to match these MODIS datasets. This dataset was windowed for E4warning project to Europe and North Africa.

opencc-by-4.0Mar 2018View details →

Annual and 33-year water body frequency maps of the contiguous US from 1984 to 2016

There are 50 5-by-5 degree tiles covering the entire CONUS. In each zipped tile folder, there are 33 annual water body frequency images (e.g. freq_2016_-070_040.tif), one 33-year water body frequency image (e.g. 33YearFreq_1984_2016_-070_040.tif), and one 33-year good observation image (e.g. 33YearGoodObs_1984_2016_-070_040.tif).  The annual and 33-year water body frequency are defined as the ratio of water observations to total good observations in a year and in 1984-2016, respectively. The frequency stored in these image is compressed in 8 bits (1-255). To get the frequency in floating point (0-1.0), use the equation: f = (F-1)/254.0, where F is in 8 bits while f is in floating point.  For each Landsat image, the CFmask band was used as a quality control band to remove the cloud, cloud shadow, and snow pixels. The solar azimuth and zenith angles of each image were used along with the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) to simulate terrain shadows and remove them. The remaining pixels were considered as good observations that can be used for water body detection. The total good observation number during 1984-2016 is stored in the 33-year good observation images. Projection is WGS84, while spatial resolution is 0.000269494585236. For additional details, please go to our lab server (http://mangrove.rccc.ou.edu/eomfftp/conus_water_dataset/). To use this data, please cite our articles:  Zou, Z., Xiao, X., Dong, J., Qin, Y., Doughty, R.B., Menarguez, M.A., Zhang, G., Wang, J. Divergent Trends of Open Surface Water Body Area in the Contiguous United States from 1984 to 2016, PNAS, doi: 10.1073/pnas.1719275115 Zou, Z., J. Dong, M. A. Menarguez, X. Xiao, Y. Qin, R. B. Doughty, K. V. Hooker, and K. David Hambright (2017), Continued decrease of open surface water body area in Oklahoma during 1984-2015, Sci Total Environ, 595, 451-460, doi: 10.1016/j.scitotenv.2017.03.259.

opencc-by-4.0Aug 2022View details →

Annual tropical forest loss during 2001-2021 in the Congo Basin

The loaded dataset in Zenodo includes the following parts: (1) Shp file of the Congo Basin; (2) GeoTIFF image of the evergreen forest cover map in the Congo Basin (file name 'Congo_EvergreenForest2000_TCC70_Height5_Clip'); (3) GeoTIFF image of the annual forest loss map produced by us (file name 'Congo_log2001_2021_L78S2_w300_cb300_theta0p2_clean120_5_new'); (4) GeoTIFF image of the post-forest loss recovery index map produced by us (file name 'Congo_RI_Log2001_2021_L78S2_w300_cb300_400_theta0p2_clean120_5_new.tif'), and it is noted that the industrial plantation map (file name 'JRC_TMF_plantations_2022.tif') should be used to exclude any plantations in our post-forest loss recovery index map, as industrial plantations is not regarded as forest recovery.

opencc-by-4.0Jul 2021View details →

Indicative distribution map for Ecosystem Functional Group T7.1 Annual croplands

This archive contains indicative distribution maps and profiles for T7.1 Annual croplands, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith et al. (2020) for details. The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).

openCC (other)Sep 2025View details →

City of Seattle, Seattle Public Utilities, Annual Bull Trout Redd Surveys in Tributaries to Chester Morse Lake 1996-current, Cedar River Municipal Watershed, King County, WA

These data were collected during weekly annual redd surveys conducted by Seattle Public Utilities (SPU) in the Cedar River Municipal Watershed (CRMW), 1996 - current. Annual weekly bull trout redd surveys funded through the CRMW Habitat Conservation Plan (HCP) began in 2000 and ended in 2011 spawning year. To reinstate a monitoring program for the population, redd surveys in the most heavily used habitats by bull trout (termed the Core Zone), were opportunistically conducted in 2018. Weekly annual surveys in most of the Core Zone were reinstated in 2019. Approximately 77% of all redds observed 2000 - 2011 would have been observed during those years using the 2019 - 2022 spatial survey extent (SPU data on file). In 2023, the spatial and temporal coverage of surveys were on par with historical coverage, i.e., approximately 100% of all redds observed 2000 - 2011 would have been observed using the 2023 spatial survey extent. Information on redd location is used primarily to enable derivation of redd elevations. Redd elevation is required to estimate potential impacts to the spawning population and incubating embryos caused by reservoir inundation of stream spawning habitat after the spawning period during fall through spring. Redd weekly timing information is critical to accurately represent whether embryos remain in the gravel and are vulnerable to impacts of reservoir inundation as the reservoir is refilled starting in early spring. It is also vitally important that SPU understand timing and abundance of redds beyond the inundation zone to enable understanding of the overall impact to the population.

openCC (other)Oct 2021View details →

SBC LTER: Reef: Annual time series of biomass for kelp forest species, ongoing since 2000 (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/281/3, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sbc/50/10. The abstract below was extracted from the Level 0 data package and is included for context: These data are annual estimates of biomass of approximately 225 taxa of reef algae, invertebrates and fish in permanent transects at 11 kelp forest sites in the Santa Barbara Channel (2-8 transects per site). Abundance is measured annually (as percent cover or density, by size) and converted to biomass (i.e., wet mass, dry mass, decalcified dry mass, ash free dry mass) using published taxon-specific algorithms. Data collection began in summer 2000 and continues annually in summer to provide information on community structure, population dynamics and species change. The time period of data collection varied among the 11 kelp forest sites. Sampling at BULL, CARP, and NAPL began in 2000, sampling at the other 6 mainland sites (AHND, AQUE, IVEE, GOLB, ABUR, MOHK) began in 2001 (transects 3, 5, 6, 7, 8 at IVEE were added in 2011). Data collection at the two Santa Cruz Island sites (SCTW and SCDI) began in 2004. See Methods for more information. See Methods for more information. The primary research objective of the Santa Barbara Coastal LTER is to investigate the importance of land and ocean processes in structuring giant kelp (Macrocystis pyrifera ) forest ecosystems. As in many temperate regions, the shallow rocky reefs in the Santa Barbara Channel, California, are dominated by giant kelp forests. Because of their close proximity to shore, kelp forests are influenced by physical and biological processes occurring on land as well as in the open ocean. SBC LTER research

openCC0Mar 2018View details →

Contribution of CO2 and CH4 emissions at ice-melt to annual emissions from 450 and 270 lakes, respectively, 1986 to 2014

The ice-covered period on lakes in the northern hemisphere can be extensive, lasting up to 7 months of the year. During this time, C cycling in lakes is altered affecting CO2 and CH4 dynamics below ice. Lake ice impedes atmospheric exchange, trapping CO2 and CH4 in the lake over winter. As lake ice-melts, CO2 and CH4 that has accumulated over winter is emitted from the into the atmosphere. To investigate the importance of CO2 and CH4 emissions during the ice-melt period, we conducted a literature search for studies that had CO2 and CH4 emission estimates for both the ice-melt and open water period. From these literature values, we could calculate the percent contribution of the ice-melt period to annual CO2 and CH4 emissions. We obtained data for 271 (n= 258) and 447 (n= 689) individual lakes, for CH4 and CO2, respectively.

openCustomAug 2021View details →

Annual heron counts on Chincoteague Island, Virginia 1992-2011 (Reformatted to the ecocomDP Design Pattern)

openOpenAug 2021View details →

SGS-LTER Standard Production Data: 1983-2008 Annual Aboveground Net Primary Production on the Central Plains Experimental Range, Nunn, Colorado, USA 1983-2008, ARS Study Number 6 (Reformatted to the ecocomDP Design Pattern)

This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/700/1. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. The objective of the long-term ANPP study is to monitor long-term net above ground primary production of the shortgrass steppe community by species. There are 6 sites: ridgetop (ridge), midslope (mid), swale, ESA (replicate 1 not 2), Section 25 (SEC 25), and owl-creek (OC). Each site is located in a different landscape position or soil type on the shortgrass steppe and may be grazed or not. Ridgetop, midslope and swale are grazed and are sampled along a catena. Section 25 is grazed and is located in an upload grassland. ESA is an ungrazed upland grassland an is the control from the Ecosystem Stress Area experiment. Owl Creek is ungrazed and is located in the lowland along the owl creek drainage. There are 3 transects with 5 plots in each transect. Plots in the grazed locations are protected by cages. Because this is a monitoring effort, true replicates across the landscape are not

openCustomAug 2021View details →

Annual heron counts on Chincoteague Island, Virginia 1992-2011 (Reformatted to a Darwin Core Archive)

openCC (other)Oct 2019View details →

Annual bedload accumulation from sediment basin surveys in small gauged watersheds in the Andrews Experimental Forest, 1957 to present

Sediment debris basins are established within the Andrews Experimental Forest as part of paired watershed experiments examining differences in streamflow and nutrient chemistry due to timber harvest. Basins are constructed below the stream gaging station in each of five basins, and these basins and the deposits of sediment within them are re-surveyed or emptied annually to measure bedload sediment production. Basins are measured on Watersheds 1, 2 (control) and 3 beginning with wateryear 1957 and on Watersheds 9 (control) and 10 beginning wateryear 1974. Data collection is ongoing at an annual time step. Data provided include the watershed name, wateryear, survey method, watershed area, annual bedload volume and accumulation rate. These data display both the chronic production of sediment, as well as pulsed, episodic bedload from landslides within the contributing basins.

openOpenJul 2008View details →

Kuskokwim River Floodplain: White Spruce (Picea glauca) annual tree-ring width measurements (mm) at breast height from tree-core samples taken above Red Devil on the Kuskokwim River in July, 2007

This dataset contains annual raw ring width measurements in the Tucsan (decadal format) (.rwl file extension) of 14 large white spruce trees growing within 50m of the Kuskokwim River. Ring-widths were measured to 0.001mm on a velmex laser micrometer and accuracy was checked by crossdating using COFECHA. Annual values were measured from 1779-2006.