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Natasha B Carr

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This data set includes the relative production scenarios for eight (8) grass species based on linear models from Epstein, et al. (1998). We selected two indicator species for each community: shortgrass prairie: blue grama (Bouteloua gracilis; BOGR) and buffalo grass (Bouteloua dactyloides; BODA); mixedgrass prairie: sideoats grama (Bouteloua curtipendula; BOCU) and little bluestem (Schizachyrium scoparium; SCSC); tallgrass prairie: big bluestem (Andropogon gerardii; ANGE) and Indiangrass (Sorghastrum nutans; SONU); and semiarid grasslands: black grama (Bouteloua eriopoda; BOER) and tobosagrass (Pleuraphis mutica; PLMU). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided...
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The surface disturbance footprint raster data set quantifies the percent surface disturbance from development at a 90-meter resolution. The surface disturbance footprint is used to compute a multiscale index of landscape intactness for the Bureau of Land Management’s (BLM) landscape approach. The surface disturbance footprint is mapped for the western United States (17 states), by compiling and combining spatial data for four development disturbance variable classes. Development classes include urban land cover (impervious surface), agriculture (cropland), energy and mineral extraction and transport (oil and gas wells, solar arrays, wind turbines, surface mines, pipelines, and transmission lines), and transportation...
This data set includes the relative production scenarios for bufflaograss [0.72(Temp) - 0.12(Precip) - 0.04(Sand) + 3.08]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier...
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Federal land managers need an adaptive management framework to accommodate changing conditions and that allows them to effectively link the appropriate science to natural resource management decision-making across jurisdictional boundaries. FRAME-SIMPPLLE is a collaborative modeling process designed to accomplish this goal by coupling the adaptive capabilities of the SIMPPLLE modeling system with accepted principles of collaboration. The two essential components of the process are FRAME (Framing Research in support of the Adaptive Management of Ecosystems), which creates a collaborative problem-solving environment, and SIMPPLLE (SIMulating Patterns and Processes at Landscape Scales), which is a vegetation dynamics...
Scenario planning is a useful tool for identifying key vulnerabilities of ecological systems to changing climates, informed by the potential outcomes for a set of divergent, plausible, and relevant climate scenarios. We evaluated potential vulnerabilities of grassland communities to changing climate in the Southern Great Plains (SGP) and the Landscape Conservation Design pilot area (LCD) for the U.S. Fish and Wildlife Service, Science Applications Program, Great Plains Landscape Conservation Cooperative. Four climate scenarios (warm-dry, warm-wet, hot-dry, and hot-wet) from atmospheric-ocean general circulation models were selected to represent a suite of plausible future climatic conditions. For each scenario,...
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