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Knowledge about the condition of vegetation cover and composition is critical for assessing the structure and function of ecosystems. To effectively quantify the impacts of a rapidly changing environment, methods to track long-term trends of vegetation must be precise, repeatable, and time- and cost-efficient. Measuring vegetation cover and composition in arid and semiarid regions is especially challenging because vegetation is typically sparse, discontinuous, and individual plants are widely spaced. To meet the goal of long-term vegetation monitoring in the Sonoran Desert and other arid and semiarid regions, we determined how estimates of plant species, total vegetation, and soil cover obtained using a widely-implemented...
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These data were collected by the Grand Canyon Monitoring and Research Center (GCMRC) to support riparian vegetation monitoring along the Colorado River between Glen Canyon Dam and the full pool level of Lake Mead. The objectives of the GCMRC riparian vegetation monitoring program are to annually measure and summarize the status (composition and cover) of native and non-native vascular plant species within the riparian zone of the Colorado River between Glen Canyon Dam and Lake Mead, assess change in the vegetation composition and cover in the riparian zone, as related to geomorphic setting and dam operations, particularly flow regime, and collect data in a manner that can be used by multiple stakeholders and is...
Tags: Arizona, Botany, Colorado River, Ecology, Geography, All tags...
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This raster data depicts the modeled distribution of three grassland states: Biocrust, Grass-bare, and Annualized-bare. We developed models of bare ground, total vegetation, exotic grasses and biological soil crust using spectral data from three year composites of growing season (March-October) Landsat data in Google Earth Engine and field data that were collected over the same period at monitoring sites. The resulting regression models were used to characterize the spatial distribution of putative grassland ecological states across our 251,430 ha study area in and around Canyonlands National Park, UT. This model illustrates how a remote sensing approach to land-cover change can be implemented to guide dryland ecosystem...


    map background search result map search result map Grassland State and Transition Map of Canyonlands National Park Needles District and Indian Creek Grazing Allotment Riparian vegetation data downstream of Glen Canyon Dam in Glen Canyon National Recreation Area and Grand Canyon National Park, AZ from 2014 to 2019 Grassland State and Transition Map of Canyonlands National Park Needles District and Indian Creek Grazing Allotment Riparian vegetation data downstream of Glen Canyon Dam in Glen Canyon National Recreation Area and Grand Canyon National Park, AZ from 2014 to 2019