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This data set was collected as part of a structured decision-making workshop designed to identify sources of uncertainty and articulate alternative hypotheses about prescribed fire in high marshes of the Gulf of Mexico. Workshop participants independently scored alternative hypotheses based on a standard rubric using an online system. Following the workshop, we used the scores to compute QVoI for each participant. We used QVoI to prioritize the sources of uncertainty based on their magnitude of uncertainty, relevance for decision making, and reducibility.
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U.S. Geological Survey and partners are testing the effects of prescribed fire on Black Rails, Yellow Rails, and Mottled Ducks in the high marsh habitats of the northern Gulf of Mexico region. The study is conducted in cooperation with Mississippi State University, Illinois Natural History Survey, U.S. Fish and Wildlife Service, state agencies, universities, and non-governmental organizations. The objectives of this project are to develop an adaptive management framework that allows land managers to reduce our uncertainty about the effects of prescribed fire on these species and the habitats on which they depend, and give managers tools and information that will help them determine the best management actions to...
Categories: Data Release - In Progress;
Tags: Bayesian decision model,
Ecology,
Gulf of Mexico,
USGS Science Data Catalog (SDC),
Wildlife Biology, All tags...
adaptive management,
biota,
decision analysis,
management experiment,
marsh birds,
prescribed fire,
salt marsh,
structured decision making,
threatened species,
value of information,
waterfowl, Fewer tags
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