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In this study, we develop urban ecosystem accounts in the U.S., using the System of Environmental-Economic Accounting Experimental Ecosystem Accounting (SEEA EEA) framework. Most ecosystem accounts focus on regional and national scales, which are appropriate for many ecosystem services. However, ecosystems provide substantial services in cities, improving quality of life and contributing to resiliency for substantial parts of the population. Our models estimate energy savings for indoor cooling resulting from heat mitigated by trees and rainfall intercepted by trees. Both models cover major cities in the contiguous U.S. and report the results through physical supply and use tables for multiple accounting periods...
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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This data release supports interpretations of field-observed root distributions within a shallow landslide headscarp (CB1) located below Mettman Ridge within the Oregon Coast Range, approximately 15 km northeast of Coos Bay, Oregon, USA. (Schmidt_2021_CB1_topo_far.png and Schmidt_2021_CB1_topo_close.png). Root species, diameter (greater than or equal to 1 mm), general orientation relative to the slide scarp, and depth below ground surface were characterized immediately following landsliding in response to large-magnitude precipitation in November 1996 which triggered thousands of landslides within the area (Montgomery and others, 2009). The enclosed data includes: (1) tests of root-thread failure as a function of...
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This dataset contains field measurements of vegetation from the (1) Adirondack Sugar Maple Project (ASM), and (2) Buck Creek North and Buck Creek South Watersheds. The ASM data, collected in 2009 in 20 Adirondack watersheds (2 or 3 0.10 ha plots per watershed), are comprised of general plot characteristics, tree species identification and diameter at breast height (DBH) for all trees greater than 10 cm DBH, canopy position and health ratings, common and scientific names, and species identification and counts for saplings and seedlings. In Buck Creek North Tributary Watershed and Buck Creek South Tributary Watershed, near Inlet, New York, all trees greater than 5 cm DBH were identified in 15 circular plots (245 square...
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Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the central Cascade Mountain area, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest patches identified in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras...
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Plot-level field data were collected in the summer of 2014 to estimate aboveground and belowground biomass in the Great Dismal Swamp National Wildlife Refuge and Dismal Swamp State Park in North Carolina and Virginia. Data were collected at 85 plots. The location of the center of each plot was recorded with a Trimble ProXH global positioning system (GPS) and differentially corrected. Data files included 1: GDS_plots.csv, 2. GDS_FWD.csv, 3. GDS_LWD.csv, 4. GDS_Shrubs.csv, 5. GDS_Trees.csv, and 6. GDS_plot_summaries.csv. The data contained in GDS_plot_summaries.csv were calculated from the GDS_plots.csv, GDS_FWD.csv, GDS_LWD.csv, GDS_Shrubs.csv, GDS_Trees.csv files using the R statistical software environment (R Core...
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This dataset contains data pertaining to ground surface cover in 30 meter plots around a random selection of points within chaparral from Santa Barbara county south to San Diego County in southern California, USA. These data were obtained from historical aerial imagery from 1943 to 1959 and current imagery from 2016 to 2018 and they were compared to quantify changes in cover type over time. These data support the following publication: Syphard, A.D., Brennan, T.J., Rustigian‐Romsos, H. and Keeley, J.E., 2022. Fire‐driven vegetation type conversion in southern California. Ecological Applications, p.e2626. https://doi.org/10.1002/eap.2626.
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The U.S. Geological Survey (USGS) computed rasters of pre-solved values for the watersheds draining to the pixel delineation point representing the watershed's percent forested land cover from the National Land Cover Dataset (NLCD) 2016 data (land cover values 41-43). These values, which cover the conterminous United States at a scale of 30m pixel size, will be served in the National StreamStats Fire-Hydrology application to describe delineated watersheds ( https://streamstats.usgs.gov/ ). The StreamStats application provides access to spatial analysis tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate...
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the regeneration of floodplain forest. This dataset uses lidar derivatives to identify forest canopy gaps along select portions of the Mississippi River and Illinois River. USACE will use this dataset to select field sites to collect data in forest canopy gaps. This will also serve as the baseline for long-term forest canopy gap study.
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As part of Upper Mississippi River Restoration (UMRR), the U.S. Army Corps of Engineers (USACE) is conducting a study to understand what environmental factors are contributing to the failure of floodplain forests to regenerate. This dataset uses lidar derivatives to identify broken forest canopy along the Mississippi River and Illinois River. A broken forest refers to an area that has a canopy height of greater than or equal to 10 meters. From this layer, forest canopy gaps can be identified by locating areas within the broken forest that have at least a 9.144 meter radius, or a 1-tree gap.
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This data release contains three 10-meter resolution GeoTIFFs representing 10-meter (35-foot), 30-meter (100-foot) and 90-meter (300-foot) riparian buffer zones along shorelines, rivers, streams, and other lotic (flowing) water features. The layers are binary, where the value of each cell represents the presence or absence of the buffer zone. In addition, the data release contains shapefile layers that document the extent of corrections that were made to the data to address errors in the stream network (see processing steps section for more details). The methodology combines various fine-scale input layers, including a 1:24k stream network and Chesapeake Bay 1-meter resolution Land Use/Land Cover to approximate...
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This dataset is comprised of water quality data and benthic macroinvertebrate data collected from basins in Colorado, USA, and Finland. The data includes ancillary water quality characteristics but also a suite of trace metals observed at each site. Also included are modeled outputs that characterize the bioavailability of each trace metal to a biotic ligand. These data were used to explore the importance of metal toxicity and pH as stressors on benthic macroinvertebrates characterized as the number of unique Ephemeroptera + Plecoptera + Trichoptera genera observed at each site. An interpretive summary of the work follows. One of the primary goals of biological assessment of rivers is to identify whether contaminants...
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This data release contains data discussed in its larger work citation (Symstad et al., 2017, Climate Risk Management 17:78-91, Associated Item at right). "ClimateComparisonData.csv" contains summary metrics of six climate projections used as climate input for quantitative simulations of hydrologic and ecological responses to climate change at Wind Cave National Park (WCNP) and the same summary metrics for 38 other climate projections available at the time that these simulations were done. "HydroData.csv" contains mean annual streamflow of a stream in WCNP and mean annual hydraulic head of a subterranean lake in Wind Cave as simulated by the rainfall-response aquifer and watershed flow (RRAWFLOW) model for two climate...
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These data were compiled for the creation of a continuous, transboundary land cover map of Bird Conservation Region 33, Sonoran and Mojave Deserts (BCR 33). Objective(s) of our study were to, 1) develop a machine learning (ML) algorithm trained to classify vegetation land cover using remote sensing spectral data and phenology metrics from 2013-2020, over a large subregion of the Sonoran and Mojave Deserts BCR, 2) Calibrate, validate, and refine the final ML-derived vegetation map using a collection of openly sourced remote sensing and ground-based ancillary data, images, and limited fieldwork, and 3) Harmonize a new transboundary classification system by expanding existing land cover mapping resources from the United...
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The U.S. Geological Survey provides a wide range of scientific information to an even wider group of stakeholders. Understanding what capacities are needed and if and or where these capacities exist across the USGS landscape is critical in moving science to the next level of use, implementation, and visualization. The concept behind the groups organized to conduct and interpret the survey that collected these data took advantage of the USGS’s position as a science organization with expertise spanning a wide range of science disciplines, stakeholders, and responsibilities. A survey was conducted of USGS employees (Sep 20-Nov 20) to get a current sample of the capacities that exist across the USGS.
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***This data set is superseded by Welty, J.L., and Jeffries, M.I., 2021, Combined wildland fire datasets for the United States and certain territories, 1800s-Present: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZXGFY3.*** This dataset is comprised of four different zip files. Zip File 1: A combined wildfire polygon dataset ranging in years from 1878-2019 (142 years) that was created by merging and dissolving fire information from 12 different original wildfire datasets to create one of the most comprehensive wildfire datasets available. Attributes describing fires that were reported in the various source data, including fire name, fire code, ignition date, controlled date, containment date, and...
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We developed a LiDAR-based habitat model for the threatened Marbled Murrelet (MAMU) in the Siuslaw National Forest, Oregon, using a two-step approach. First, we tested the applicability of the LiDAR-based model developed for the Coos Bay District of the Bureau of Land Management (BLM) to the Siuslaw N.F. In the second step, we tested alternative habitat models developed with forest structural data and Murrelet survey data from the Siuslaw N.F. We compared the performance of each model to provide forest managers with the best predictive tool to guide habitat management for the Marbled Murrelet. This shapefile contains the probability of Marbled Murrelet occupancy values of each model for vegetation polygons defined...
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Note: this dataset has been superseded by this new data product: Simpson, A., Turner, R., Blake, R., Liebhold, A., and Dorado, M., 2021, United States Register of Introduced and Invasive Species: U.S. Geological Survey data release, https://doi.org/10.5066/P95XL09Q. Invasive species are a subset of non-native (or nonindigenous) species, and knowing what species are non-native to a region is a first step to managing invasive species. This is the second update to the dataset "First comprehensive list of non-native species established in three major regions of the United States" supporting a USGS Open File Report by the same name published on 2018-10-17. Version 3.0 of the non-native species list, as of 2020-09-15,...
map background search result map search result map Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity: data sets Adirondack New York vegetation data, 2000-2015 Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA Data from simulations of ecological and hydrologic response to climate change scenarios at Wind Cave National Park, South Dakota, 1901-2050 Estimated Probabilities from Lidar Models for Marbled Murrelet (Brachyramphus marmoratus) Occupancy in Forest Vegetation Stands in the Siuslaw National Forest, Oregon A comprehensive list of non-native species established in three major regions of the United States: Version 3.0 Great Dismal Swamp field measurements for aboveground and belowground biomass Combined wildfire datasets for the United States and certain territories, 1878-2019 Forest Canopy Gaps Identified by Lidar for Navigational Pool 8 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 13 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 13 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 21 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 24 of the Mississippi River Data release for Piloting Urban Ecosystem Accounting for the United States USGS Earthmap Capacity Assessment Dataset Precomputed Percent Forested-Area Rasters Derived from NLCD 2016 in Support of the StreamStats Fire-Hydrology Application, Conterminous United States Root thread strength, landslide headscarp geometry, and observed root characteristics at the monitored CB1 landslide, Oregon, USA Vegetation Type Conversion in Southern California Between 1943 and 2018 Random forest classification data developed from multitemporal Landsat 8 spectral data and phenology metrics for a subregion in Sonoran and Mojave Deserts, April 2013 – December 2020 Chesapeake Bay Watershed 1:24k 10, 30 and 90-meter Riparian Buffer Zones Root thread strength, landslide headscarp geometry, and observed root characteristics at the monitored CB1 landslide, Oregon, USA Data from simulations of ecological and hydrologic response to climate change scenarios at Wind Cave National Park, South Dakota, 1901-2050 Broken Forest Canopy Identified by Lidar for the Navigational Pool 21 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 8 of the Mississippi River Great Dismal Swamp field measurements for aboveground and belowground biomass Broken Forest Canopy Identified by Lidar for the Navigational Pool 24 of the Mississippi River Forest Canopy Gaps Identified by Lidar for Navigational Pool 13 of the Mississippi River Broken Forest Canopy Identified by Lidar for the Navigational Pool 13 of the Mississippi River Adirondack New York vegetation data, 2000-2015 Estimated Probabilities from Lidar Models for Marbled Murrelet (Brachyramphus marmoratus) Occupancy in Forest Vegetation Stands in the Siuslaw National Forest, Oregon Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA Vegetation Type Conversion in Southern California Between 1943 and 2018 Random forest classification data developed from multitemporal Landsat 8 spectral data and phenology metrics for a subregion in Sonoran and Mojave Deserts, April 2013 – December 2020 Chesapeake Bay Watershed 1:24k 10, 30 and 90-meter Riparian Buffer Zones Precomputed Percent Forested-Area Rasters Derived from NLCD 2016 in Support of the StreamStats Fire-Hydrology Application, Conterminous United States Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity: data sets A comprehensive list of non-native species established in three major regions of the United States: Version 3.0 Data release for Piloting Urban Ecosystem Accounting for the United States Combined wildfire datasets for the United States and certain territories, 1878-2019 USGS Earthmap Capacity Assessment Dataset