Find research datasets worth reusing

openCC (other)Dec 2023View details →

Long-term (1935-2019) tree population data from remeasurements of a large network of permanent study plots in old-growth forest, Dukes Research Natural Area, Marquette Co., MI, USA

The Dukes Research Natural Area (Hiawatha National Forest, Marquette Co., MI) amounts to ca. 100 ha of minimally disturbed original forests, including a mix of mesic 'hemlock-northern hardwood' types and peaty wetlands dominated by several species of swamp conifers and black ash (Fraxinus nigra). The RNA hosts a regular grid of 250 0.2-acre (~0.08 ha) permanent monitoring (CFI) plots. This package includes tree censuses for subsets of CFI plots conducted in 1935, 1948, and 1974-1980, and repeated censuses with mapped stems from 1989 to 2019. This 84-year record constitutes one of the longest repeated-measurement, permanent-plot data-sets for old-growth temperate forest.

openCC (other)Jun 2025View details →

Data associated with the 2019 Freshwater Oil Spill Remediation Study (FOReSt) assessing the use of enhanced Monitored Natural Recovery (eMNR) and shoreline washing agent (SWA) of diluted bitumen spills conducted in shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2019 to 2020

The following package includes data from the 2019 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) and shoreline washing agent (SWA) as a secondary remediation method for diluted bitumen spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry, and tritium chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. Data included in this package was first collected and used in the paper by Palace et al., titled Polycyclic aromatic compounds in freshwater ecosystems following non-invasive remediation of controlled diluted bitumen spills: The Freshwater Oil Spill Remediation Study (FOReSt) at the Experimental Lakes Area, Canada.

openCC (other)Jan 2026View details →

The 2021 Freshwater Oil Spill Remediation Study (FOReSt), assessing the use of enhanced Monitored Natural Recovery (eMNR) of conventional heavy crude oil spills conducted in freshwater shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2021 to 2022.

The following package includes data from the 2021 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) as a secondary remediation method for conventional heavy crude oil spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. As well as tables detailing enclosure metrics (depth), tritium chemistry, and a treatment key. Data included in this package was first collected and used in the paper by Stanley et al., titled Rapid Chemical Remediation of Freshwater Enclosures Treated with Conventional Heavy Crude Oil Spills Followed by Enhanced Monitored Natural Recovery

openCC0Aug 2023View details →

Land use and land cover (LULC) classification of the CAP LTER study area (central Arizona, USA) using Landsat imagery: 2015 and 2020

## overview The project extends the long-term, LULC datasets to facilitate environmental change monitoring and social-ecological studies regarding urban sprawl and dynamics, urban heat islands, and outdoor water consumption, among others. Six land-use/land-cover (LULC) maps at 30 m resolution were previously created from 1985 to 2010 at five-year intervals (Zhang and Li 2017). This project updates that suite with maps for 2015 and 2020. As with the prior set, systematic object-based classification was utilized to ensure map consistency and direct comparison capability over time. The maps comprise 11 land-use/land-cover classes with an overall accuracy of 89.1% for 2015 and 89.6% for 2020. ## literature cited - Zhang, Y. and X. Li. 2017. Land cover classification of the CAP LTER study area at five-year intervals from 1985 to 2010 using Landsat imagery ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/dab4db27974f6c8d5b91a91d30c7781d (Accessed 2022-07-13).

zenodo48/100

Data and Models from the study entitled, "Large-area automatic detection of shoreline stranded marine debris using deep learning"

This repository contains data and models used in the study entitled, "Large-area automatic detection of shoreline stranded marine debris using deep learning". This study can be accessed as an open access publication at the following location: https://doi.org/10.1016/j.jag.2023.103515. The data set is comprised of 1,587 images (512 pixels x 512 pixels) which contains 10,703 individual bounding box labels of marine debris objects. The imagery was collected over the State of Hawai'i in 2015 at 2 centimeter resolution (ground spacing distance). The classification scheme consists of 8 labeled classes: unidentified object, processed wood, metal, vessel, net/cloth, buoy, tire, and line fragments.

opencc-by-4.0Sep 2023View details →

edi48/100

Sherbo et al. 2023 Data Package. Data associated with study assessing effects of dissolved organic matter on phytoplankton productivity in boreal lakes. The majority of data was collected in 2018 at the IISD Experimental Lakes Area in Northwestern Ontario

Allochthonous dissolved organic matter (DOM) structures many physical, chemical, and biological properties of lakes, including key variables that control productivity at the base of freshwater food webs. We examined phytoplankton biomass and productivity and their drivers, across eight pristine boreal lakes with DOM ranging from 3.5 to 9.5 mg DOC L-1. Increases in DOM were associated with significant increases in epilimnetic nitrogen, phosphorus and chlorophyll a (Chl a) concentrations suggesting that nutrients associated with DOM stimulate phytoplankton biomass and productivity. Such results were misleading; there was no significant relationship between Chl a and phytoplankton biomass measured via microscopy, and results did not incorporate the effects of DOM on thermocline and euphotic depth. Chl a:biomass and Chl a: carbon ratios indicated that increases in Chl a with DOM were driven by photo-acclimation to declining light availability. Increases. Further, increases in DOM led to large declines in thermocline (~50 %) and euphotic (~75 %) depths, and depth-integrated phytoplankton biomass and primary production (~70 %).

openCC (other)Oct 2023View details →

edi48/100

SGS-LTER Ecosystem Stress Area - long-term density dataset following nutrient enrichment stress on the Central Plains Experimental Range in Nunn, Colorado, USA 1975-2011, ARS Study Number 3 (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/520/8. 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. Water, nitrogen, and water-plus-nitrogen at levels beyond the range normally experience by shortgrass steppe communities were applied from 1971 through 1975, plant densities were sampled through 1977, and then sampling resumed in 1982, with sampling frequencies changing from annually to every other year. The initial sampling from 1970 to 1974 showed that the water and water plus nitrogen treatments had the strongest effect on plant community structure, both treatments increased biomass, and exotic weed species were noted on the water plus nitrogen treatment. Later sampling from 1982 to 1991 showed a ten-fold increase in exotic weed species on the water plus nitrogen plots as compared to the controls (Milchunas and Lauenroth 1995), a community change that has persisted on this site due to a chronic elevation of soil nitrogen caused by a plant tissue/soil organic matter feedback mec

edi48/100

SGS-LTER Ecosystem Stress Area - long-term point-frame (percent basal cover) dataset following nutrient enrichment stress on the Central Plains Experimental Range in Nunn, Colorado, USA 1982-2011, ARS Study Number 3 (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/521/7. 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. Water, nitrogen, and water-plus-nitrogen at levels beyond the range normally experience by shortgrass steppe communities were applied from 1971 through 1975, plant densities were sampled through 1977, and then sampling resumed in 1982, with sampling frequencies changing from annually to every other year. The initial sampling from 1970 to 1974 showed that the water and water plus nitrogen treatments had the strongest effect on plant community structure, both treatments increased biomass, and exotic weed species were noted on the water plus nitrogen treatment. Later sampling from 1982 to 1991 showed a ten-fold increase in exotic weed species on the water plus nitrogen plots as compared to the controls (Milchunas and Lauenroth 1995), a community change that has persisted on this site due to a chronic elevation of soil nitrogen caused by a plant tissue/soil organic matter feedback mec

opencc-zeroApr 2024View details →

Shorelines, elevation transects and environmental data for Drew Point, Ak study area, 2019-2022

This record consists of the shorelines and their derived products, elevation transects and environmental data used for the Cryosphere preprint: Multiple modes of shoreline change along the Alaskan Beaufort Sea observed using ICESat-2 altimetry and satellite imagery. There are three primary datasets: ERA-5 contains hourly output ERA5 reanalysis dataset (Hersbach et al., 2020, https://doi.org/10.24381/cds.adbb2d47) from a single pixel (-153.83, 70.87) from May 1st through November 30th for 2019, 2020, 2021, and 2022. It also contians a list of derived open water days for each year. ICESat-2  contains the subsetted ATL03 photons (Neuman et. al, 2023, https://doi.org/10.5067/ATLAS/ATL03.006) for RGT 137 ground tracks 1r, 2r and 3r on 07 April 2019,  04 January 2020, 02 July 2021, and 31 December 2021, elevation profiles derived from SlideRule (Shean et al., 2023), and shoreline boundaries picked from the elevation profiles and Planet imagery. It also includes cross-shore transects used to project ICESat-2-derived changes into the local shoreline-perpindicular direction. Planet_shorelines contains shorelines drived from 3m multispectral imagery from Planet Labs (Planet Team, 2024) as well as their derivatiev products. This included shorelines used for year-to-year change (annual_coastlines) and for uncertainty analysis (uncertainty_coastlines). It also includes the derived year-to year-change (shoreline_change), the baseline and cross-shore transects used to derived these change estiamtes, and a table with our derived annual shoreline change estimates compared with previously published estimates in this region. More detailed information on each datasets can be found in each folder's README file.

opencc-by-4.0Jun 2024View details →

Edge length of land use classes aggregated from Corine 2012 in 100 - 5000 meter radius areas around Landklif study plots

Based on CORINE land cover data 2012, we aggregated the original land use classes into 8 classes: urban, agriculture, grassland, broad-leaved forest, coniferous forest, mixed forest, natural/seminatural vegetation, and water (see clc_legend.txt). Based on this new land use classification, we calculated the edge length of landuse patches (total length of edges between different habitat in meter) for 100 - 5000 meters (100-1000 meters with 100 meter interval, 1000 - 5000 meter with 500 meter interval) buffer area around LandKlif plots. LandKlif is funded by the Bavarian State Ministry of Science and the Arts within the Bavarian Climate Research Network (bayklif).  Within the five year funding period of bayklif, five interdisciplinary senior research associations and five junior research groups are be financed with a total sum of 18 million Euro. LandKliF, as one of the five interdisciplinary senior research associations, addresses the effects of climate change on biodiversity and ecosystem services in semi-natural, agricultural and urban landscapes.

opencc-by-4.0Jun 2024View details →

Edge length of land use classes aggregated from Corine 2018 in 100 - 5000 meter radius areas around Landklif study plots

Based on CORINE land cover data 2018, we aggregated the original land use classes into 8 classes: urban, agriculture, grassland, broad-leaved forest, coniferous forest, mixed forest, natural/seminatural vegetation, and water (see clc_legend.txt). Based on this new land use classification, we calculated the edge length of landuse patches (total length of edges between different habitat in meter) for 100 - 5000 meters (100-1000 meters with 100 meter interval, 1000 - 5000 meter with 500 meter interval) buffer area around LandKlif plots. LandKlif is funded by the Bavarian State Ministry of Science and the Arts within the Bavarian Climate Research Network (bayklif).  Within the five year funding period of bayklif, five interdisciplinary senior research associations and five junior research groups are be financed with a total sum of 18 million Euro. LandKliF, as one of the five interdisciplinary senior research associations, addresses the effects of climate change on biodiversity and ecosystem services in semi-natural, agricultural and urban landscapes.

opencc-by-4.0Jun 2024View details →

Landscape composition and shannon diversity of landuse classes aggregated from corine 2018 in 100 - 5000 meter radius areas around Landklif study plots

Based on CORINE land cover data from 2018, we aggregated the original land use classes into 8 classes: urban, agriculture, grassland, Broad-leaved forest, Coniferous forest, Mixed forest, natural/seminatural vegetation, and water (see clc_legend.txt). We calculated the landscape composition (percentage of each land use type according to corine land type) for 100 - 5000 meters (100-1000 meter with 100 meter intervals, 1000 - 5000 meter with 500 meter interval) buffer area around landklif plots. LandKlif is funded by the Bavarian State Ministry of Science and the Arts within the Bavarian Climate Research Network (bayklif).  Within the five year funding period of bayklif, five interdisciplinary senior research associations and five junior research groups are be financed with a total sum of 18 million Euro. LandKliF, as one of the five interdisciplinary senior research associations, addresses the effects of climate change on biodiversity and ecosystem services in semi-natural, agricultural and urban landscapes.

opencc-by-4.0May 2023View details →

Arctic shoreline displacement and validation data for two pilot study areas

Arctic shoreline displacement data for two pilot study areas are supporting information for the paper Nylén, Calle-Navarro and Gonzales-Inca: Arctic shoreline displacement with open satellite imagery and data fusion – Pilot study 1984–2022. The two study areas are: <ul> <li>Tanafjorden: a low-arctic meso-tidal fjord coast in mainland Norway</li> <li>Ny-Ålesund: a high-arctic micro-tidal glaciated coast in north-western Svalbard</li> </ul> The study areas are 2500 km² each. The dataset includes following files: <ul> <li>Calculating_coastal_landcover_timeseries_summaries.R: code for summarizing the coastal land cover time-series in the R software.</li> <li>Calculating_shoreline_timeseries.R: code for calculating the shoreline by fitting and smoothing a polyline to the land cover raster in the R software.</li> <li>X_timeseries.tif: a multiband GeoTIFF raster file, with each band describing coastal land cover during one of the eight time-steps (1984–1988, 1989–1993, 1994–1998, 1999–2003, 2004–2008, 2009–2013, 2014–2018 and 2019–2022).</li> <li>X_summary.tif: a multiband GeoTIFF raster file, with bands that summarize the time-series from different viewpoints. These summary variables are: probability of belonging to the land class, long-term trend (between 1984-2003 and 2004-2022), change intensity, first time-step in water class, last time-step in water class, first time-step in land class and last time-step in land class.</li> <li>X_shoreline.geojson: a GeoJSON vector file, consisting of polylines for the shoreline during each time-step. The attributes of the polyline layer describe the time-step and the total length of the shoreline.</li> <li>NyAlesund_timeseries_REDUCED.tif: a reduced time-series for the Ny-Ålesund study area, including only the time-steps with adequate number of observations (i.e., excluding 1984–1988, 1994–1998 and 2004–2008).</li> <li>X_reference_shoreline.geojson: a GeoJSON vector file including the manually digitized (scale 1/5000) reference shoreline corresponding to the time-step 2019–2022.</li> <li>X_validationpoints.geojson: a GeoJSON vector file including 2000 random points (within 2 km from the reference shoreline) that have been manually classified into water and land. The classification corresponds to the time-step 2019–2022.</li> </ul>

openCC (other)Nov 2024View details →

Higgins et al. 2024 study on dissolved organic matter controls and effects at the IISD Experimental Lakes Area, Northwestern Ontario, Canada, 1970-2019

This dataset represents long-term ecological reserch data collected at the IISD Experimental Lakes Area, Northwestern Ontario, Canada (1970 - 2019) used to support a research study reported in (Higgins et al. 2024). The study examines the relationships between long-term changes in precipitation, dissolved organic matter (DOM) loading and lake concentrations, and various physical, chemical and biological indicators.

openCC (other)Feb 2025View details →

Data associated with a study on freshwater phenanthrene removal by three emergent wetland plants conducted in a microcosm experiment at the IISD Experimental Lakes Area, ON, Canada, in 2022.

The following package includes data from a study that evaluated the efficacy of three common wetland plants, Typha sp. (cattail), Carex utriculata (sedge a), and C. lasiocarpa (sedge b) in enhancing removal of phenanthrene (1 mg/L) from freshwater in a microcosm experiment conducted at the IISD Experimental Lakes Area, northwestern Ontario, Canada, in 2022. Over 21 days, microcosms were monitored for phenanthrene chemistry, basic water quality, plant growth metrics (height and final biomass), and root biofilm oxygen consumption (respirometry) and adenosine triphosphate (ATP). Data included in this package was first collected and used in the paper by Stanley et al., titled Freshwater Phenanthrene Removal by three Emergent Wetland Plants.

SGS-LTER Ecosystem Stress Area - long-term density dataset following nutrient enrichment stress on the Central Plains Experimental Range in Nunn, Colorado, USA 1975-2011, ARS Study Number 3 (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/330/3, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/520/8. 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. Water, nitrogen, and water-plus-nitrogen at levels beyond the range normally experience by shortgrass steppe communities were applied from 1971 through 1975, plant densities were sampled through 1977, and then sampling resumed in 1982, with sampling frequencies changing from annually to every other year. The initial sampling from 1970 to 1974 showed that the water and water plus nitrogen treatments had the strongest effect on plant community structure, both treatments increased biomass, and exotic weed species were noted on the water plus nitrogen treatment. Later sampling from 1982 to 1991 showed a ten-fold increase in exotic weed species on the water plus nitrogen plots as compared to the controls (Milchunas and Lauenroth 1995), a community change that has persiste

SGS-LTER Ecosystem Stress Area - long-term point-frame (percent basal cover) dataset following nutrient enrichment stress on the Central Plains Experimental Range in Nunn, Colorado, USA 1982-2011, ARS Study Number 3 (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/331/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/521/7. 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. Water, nitrogen, and water-plus-nitrogen at levels beyond the range normally experience by shortgrass steppe communities were applied from 1971 through 1975, plant densities were sampled through 1977, and then sampling resumed in 1982, with sampling frequencies changing from annually to every other year. The initial sampling from 1970 to 1974 showed that the water and water plus nitrogen treatments had the strongest effect on plant community structure, both treatments increased biomass, and exotic weed species were noted on the water plus nitrogen treatment. Later sampling from 1982 to 1991 showed a ten-fold increase in exotic weed species on the water plus nitrogen plots as compared to the controls (Milchunas and Lauenroth 1995), a community change that has persiste

openCustomNov 2013View details →

LiDAR data (August 2008) for the Andrews Experimental Forest and Willamette National Forest study areas

Watershed Sciences, Inc. collected Light Detection and Ranging (LiDAR) data from HJ Andrews and the Willamette National Forest (WNF) on August 10-11, 2008. Total area of the study are is 17,705 acres. The total area of delivered LiDAR including 100 m buffer is 19,493 acres. This data set includes the base products delivered by Watershed Sciences, and derived products (hill shades, slope and aspect grids, and contours). The base products include the point cloud data (LAS format), and the derived bare-earth and highest-hits digital elevation models (DEM). The DEMs are at 1 meter cell size resolution. The bare-earth DEM is a representation of the topography of the area, with all the vegetation removed. The highest-hit DEM is a representation of the first object the LiDAR system struck during data capture. This includes the bare-earth topography with vegetation and structures. The vegetation DEM is the result of subtracting the bare-earth DEM from the highest-hit DEM. The elevations are the heights of the vegetation. The final products are in ESRI GRID digital format, with a 1 meter cell size resolution. Each cell in the GRID has a value that represents the modeled elevation (either total elevation or vegetation height) at that location. The resulting DEM's were used to create slope, aspect, hill shade, and contour data for the area.

openOpenDec 2008View details →

Pond Area Estimates: Nine Study Regions in Alaska for 3 time periods (1950s, 1978-1982, 1999-2001) using remotely sensed images

The data are ArcGIS shapefiles by USGS quadrangle within 9 study regions: Arctic Coastal Plain, Stevens Village area, Yukon Flats, Minto Flats, Denali Flats, Talkeetna, Innoko Flats, Tetlin Flats, and Copper River Basin. Each shapefile polygon represents the shoreline of a pond as visually interpreted from each georectified remotely sensed image. All images were rectified based on at least 25 control points from 1:63 360 USGS digital raster graphics topographic maps using a second-order polynomial with a RMS error of less than one satellite image pixel (30 meters). All closed-basin ponds greater than 0.2 hectares were visually delineated and manually traced as polygons using ArcGIS. Each pond polygon has an ID and Hectares field representing the pond ID and area in hectares for the time period of the remotely sensed image.