Research Database
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An empirical machine learning method for predicting potential fire control locations for pre-fire planning and operational fire management
Year: 2017
During active fire incidents, decisions regarding where and how to safely and effectively deploy resources to meet management objectives are often made under rapidly evolving conditions, with limited time to assess management strategies or for development of backup plans if initial efforts prove unsuccessful. Under all but the most extreme fire weather conditions, topography and fuels are significant factors affecting potential fire spread and burn severity. We leverage these relationships to quantify the effects of topography, fuel characteristics, road networks and fire suppression effort…
Publication Type: Journal Article
Projected range shifting by montane mammals under climate change: implications for Cascadia's National Parks
Year: 2012
We examined potential impacts of climate change over the next century on eight mammal species of conservation concern in western Washington State, under four warming scenarios. Using two species distribution models, including a logistic regression-based model and the "maximum entropy" (MaxEnt) model, we predicted the location and extent of the potential current and future range of each species based on a suite of environmental and geographical variables. Both models projected significant losses in range size within the focal area over the next century across all warming scenarios. Projections…
Publication Type: Journal Article