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Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019)

Metadata Updated: October 29, 2023

The dataset provides a spatially explicit estimate of 2019 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The estimate is based on the mean output of two regression-tree models. For one model, we include, as an independent variable amongst other independent variables, a dataset that is the mean of 17-years of annual herbaceous percent cover (https://doi.org/10.5066/F71J98QK). This model's test mean error rate (n = 1670), based on nine different randomizations, equals 4.9% with a standard deviation of +/- 0.15. A second model was developed that did not include the mean of 17-years of annual herbaceous percent cover, and this model's test mean error rate (n = 1670), based on nine different randomizations, equals 5.0% with a standard deviation of +/- 0.11. The mean value for each pixel represents the May 2019 early estimate of annual herbaceous percent cover. The pixel values for the merged 2019 dataset range from 0 to100 percent cover with an overall mean value of 11.20 and a standard deviation of +/-9.77. This dataset is generated by integrating ground-truth measurements of annual herbaceous percent cover with 250-m spatial resolution eMODIS NDVI satellite derived data and geophysical variables into regression-tree software. The geographic coverage includes the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied a mask to areas above 2250-m elevation because annual grasses are unlikely to exist at substantial cover above this threshold. To target likely sagebrush ecosystems, the mask also hid pixels classified as something other than shrub or grassland/herbaceous by the 2011 National Land Cover Dataset (NLCD). Cheatgrass (Bromus tectorum) is the most common annual grass in the study area. It grows from seed, usually in spring, matures quickly, produces seed, and dies. After dying, cheatgrass contributes fine fuels that facilitate fire ignition and spread throughout sagebrush ecosystems. These fires remove sagebrush stands. Increasing fire frequencies, land management practices, and development have all contributed to the fragmentation of the once expansive sagebrush ecosystems. These ecosystems are critical for water quality, reduced fire threats, and the survival of sagebrush-dependent wildlife.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date June 1, 2023
Metadata Updated Date October 29, 2023

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date October 29, 2023
Publisher U.S. Geological Survey
Maintainer
@Id http://datainventory.doi.gov/id/dataset/f3821c9966ca46cbcaac0adab7a48891
Identifier USGS:5ce98fefe4b033153c93e3d1
Data Last Modified 20200818
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 5709faf9-49c8-4cfe-856e-ee06615d3c9b
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -122.26389227,36.102421558,-103.120223973,46.32235274
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash 46c7e91e03e57e699f82b5233ec26e626613694aea98d3d7d10e7661bff3a7e3
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -122.26389227, 36.102421558, -122.26389227, 46.32235274, -103.120223973, 46.32235274, -103.120223973, 36.102421558, -122.26389227, 36.102421558}

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