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Bruce K Wylie

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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of their availability. Utilizing a previously developed crop classification model (CCM), which was used to generate historical annual crop cover maps (classifying nine major crops: corn, cotton, sorghum, soybeans, spring wheat, winter wheat, alfalfa, other hay/non alfalfa, fallow/idle cropland, and ‘other’ as one class for remaining crops), we hypothesized that such crop cover maps could be generated in near real time (NRT). The CCM was trained on 14 temporal and 15 static geospatial datasets, known as predictor variables, and...
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Switchgrass (Panicum virgatum L.), a highly productive perennial grass, has been recommended as one potential source for cellulosic biofuel feedstocks. Previous studies indicate that planting perennial grasses (e.g., switchgrass) in high topographic relief cropland waterway buffers can improve local environmental conditions and sustainability. The main advantages of this land management practice include (1) reducing soil erosion and improving water quality because switchgrass requires less tillage, fertilizers, and pesticides; and (2) improving regional ecosystem services (e.g., improving water infiltration, minimizing drought and flood impacts on production, and serving as carbon sinks). In this study, we mapped...
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Cheatgrass began invading the Great Basin about 100 years ago, changing large parts of the landscape from a rich, diverse ecosystem to one where a single invasive species dominates. Cheatgrass dominated areas experience more fires that burn more land than in native ecosystems, resulting in economic and resource losses. Therefore, the reduced production, or absence, of cheatgrass in previously invaded areas during years of adequate precipitation could be seen as a windfall. However, this cheatgrass dieoff phenomenon creates other problems for land managers like accelerated soil erosion, loss of early spring food supply for livestock and wildlife, and unknown recovery pathways. We used satellite data and scientific...
Exotic annual grasses [EAG] are one of the most damaging biological stressors in western North America. Despite numerous environmental and societal impacts associated with EAG there remains a need to enhance regional monitoring capabilities to better guide management and conservation efforts. Here we provide estimates of historic and potential future trends in EAG abundance that were developed using linear trend analysis and machine learning techniques at a 30-m spatial resolution. Specifically, these data represent historic (1985 to 2019) and potential future (2025-2040) rates of exotic annual grass change as estimated using Theil-Sen regression and a process-constrained, random forest model assuming only changes...
Exotic annual grasses are one of the most damaging biological stressors in western North America and increase the susceptibility of landscapes to wildfire occurrence. Here we couple estimates of long-term rangeland component fractions (e.g. exotic annual grasses) with remote sensing, climate data, and machine learning techniques to estimate the long-term (1985 to 2019) probability of wildfire occurrence (30-m spatial resolution) in sagebrush-dominated landscapes of the western United States.
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