Quantifying source and sink habitats and pathways in spatially structured populations: A generalized modelling approach

Christine Sample, Joanna A. Bieri, Benjamin Allen, Yulia Dementieva, Alyssa Carson, Connor Higgins, Sadie Piatt, Shirley Qiu, Summer Stafford, Brady J. Mattsson, Darius J. Semmens, Wayne E. Thogmartin and Jay E. Diffendorfer

Ecological Modelling, 2019, vol. 407, issue C, -

Abstract: The ability to classify habitats and movement pathways as sources or sinks is an important part of the decision making process for the conservation of spatially structured populations. Diverse approaches have been used to quantify the importance of habitats and pathways in a spatial network; however, these approaches have been limited by a lack of general applicability across life histories and movement strategies. In this paper, we develop a generalized per-capita contribution metric, the C-metric, for quantifying habitat and pathway quality. This metric is novel in that it can be applied broadly to both metapopulations and migratory species. It allows for any number of age and sex classes, unlimited number of seasons or time intervals within the annual cycle, and for density-dependent parameters. We demonstrate the flexibility of the metric with four case studies: a hypothetical metapopulation, elk of the Greater Yellowstone Ecosystem, northern pintail ducks in North America, and the eastern population of the monarch butterfly. General computer code to calculate the per-capita contribution metric is provided. We demonstrate that the C-metric is useful for identifying source and sink habitats in a network and suggest that the C-metric could be supplemented by some measure of network structure for a more robust description of habitat or pathway importance.

Keywords: Migration; Network model; Habitat quality; Spatial ecology; Metric; Ecological traps (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:407:y:2019:i:c:9

DOI: 10.1016/j.ecolmodel.2019.06.003

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