Decision analysis for species preservation under sea-level rise

Anna C. Linhoss, Gregory A. Kiker, Matthew E. Aiello-Lammens, Ma. Librada Chu-Agor, Matteo Convertino, Rafael Muñoz-Carpena, Richard Fischer and Igor Linkov

Ecological Modelling, 2013, vol. 263, issue C, 264-272

Abstract: Sea-level rise is expected to dramatically alter low-lying coastal and intertidal areas, which provide important habitat for shoreline-dependent species. The Snowy Plover (Charadrius alexandrinus) is a threatened shorebird that relies on Florida Gulf Coast sandy beaches for nesting and breeding. Selecting a management strategy for the conservation of this species under sea-level rise is a complex task that entails the consideration of multiple streams of information, stakeholder preferences, value judgments, and uncertainty. We use a spatially explicit linked modeling process that incorporates geomorphological (SLAMM), habitat (MaxEnt), and metapopulation (RAMAS GIS) models to simulate the effect of sea-level rise on Snowy Plover populations. We then apply multi-criteria decision analysis to identify preferred management strategies for the conservation of the species. Results show that nest exclosures are the most promising conservation strategy followed by predator management, species focused beach nourishment, and no action. Uncertainty in these results remains an important concern, and a better understanding of decision-maker preferences and the Snowy Plover's life history would improve the reliability of the results. This is an innovative method for planning for sea-level rise through pairing a linked modeling system with decision analysis to provide management focused results under an inherently uncertain future.

Keywords: Multi-criteria decision analysis; Snowy Plover; Ecological modeling; Sea-level rise; Scenario planning (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:263:y:2013:i:c:p:264-272

DOI: 10.1016/j.ecolmodel.2013.05.014

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