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A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

Journal

ECOLOGICAL INDICATORS
Volume 69, Issue -, Pages 792-802

Publisher

ELSEVIER
DOI: 10.1016/j.ecolind.2016.05.027

Keywords

Spatially structured populations; Decision theory; Graph theory; Occupancy; Metapopulations; Perturbation analysis

Funding

  1. National Institute for Mathematical and Biological Synthesis working group on Habitat for Migratory Species - National Science Foundation through NSF [DBI-1300426]
  2. Div Of Biological Infrastructure
  3. Direct For Biological Sciences [1300426] Funding Source: National Science Foundation

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Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and Synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources. (C) 2016 Elsevier Ltd. All rights reserved.

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