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Found 509 dataset(s) matching "FRAGMENT".
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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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...
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This dataset provides a near-real-time estimate of 2019 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatgrass percent cover in the Northern...
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Sample Analyses: Four samples of silica sinter from Giant and Castle Geysers compo sedof opal-A or opal-A/C were analyzed for U-Th isotopes at USGS laboratories in Denver, CO...
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This dataset contains whole major element geochemical data used to calculate values of the chemical alteration index (CIA), data for Nd, Sm, Y, and total REE and expected ranges for total REEY...
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The Long Term Resource Monitoring (LTRM) program employs a destructive harvest method for sampling aquatic vegetation whereby a rake is dragged ~1.5 m over the substrate and plant materials are...
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The Mesa mule deer population is part of the larger Sublette herd that winters in the north-central portion of the Green River Basin, east of the Green River and west of U.S. Highway 191 (fig....
