Megan C. Milligan , Peter S. Coates , Shawn T. O'Neil , Brianne E. Brussee , Michael P. Chenaille , Derek A. Friend , Kathleen Steele , Justin R. Small , Timothy S. Bowden , Arlene D. Kosic , Katherine Miller , Michael L. Casazza
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引用次数: 0
Abstract
Robust science is needed to inform natural resource management and policy decisions. Predictive species habitat maps are frequently employed in conservation decision-making but are often based on a single metric representing habitat quality. We outlined a framework that combines multiple spatially explicit indices of potential habitat quality that could be used to identify and prioritize habitat management areas, using the greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) as an example species. Due to large-scale changes in sagebrush ecosystems, sage-grouse have suffered significant population declines in recent decades and have become key to land management plans throughout the western United States, where comprehensive habitat maps are crucial to effective conservation efforts. We evaluated habitat selection and survival patterns of sage-grouse across six distinct annual life stages and seasons to generate predictive habitat map surfaces, mapped the distribution of current occupancy, and combined maps of potential selection and survival patterns with space use and occupancy indices to delineate example habitat management categories. Our approach facilitates identification of priority areas to target for habitat preservation and areas where anthropogenic impacts could occur with likely minimal impact to the species. Overall, by combining indices representing selection, survival, and current occupancy, we provide a framework to allow for a flexible and targeted management approach that could be adapted to a wide variety of species.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.