Meeting species persistence targets under climate change: A spatially explicit conservation planning model

Diogo Alagador, Jorge Orestes Cerdeira

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Aim: Climate change threatens the effectiveness of existing protected areas, pivotal, yet static, instruments to promote the persistence of biodiversity. The identification of the areas more likely to be used by multiple species to track their most suitable changing climates is therefore an important step in conservation planning. Species persistence targets and budget limitation are two critical ingredients constraining target-based conservation area selection. However, defining adequate persistence targets under budget constraints is far from intuitive. Location: Unspecific. Methods: We propose a two-staged mixed-integer linear programming model to determine optimized persistence targets for several species, for a given time horizon and climate change scenarios, under budgetary limitation. The first stage tunes pre-established targets for each species with a bound on the size of the area to select. The second stage identifies a set of areas of minimum cost that allows the persistence levels optimized in the first stage to be achieved. We apply a heuristic to test whether small deviations from optimal persistence settings (i.e., targets for multiple species) do influence cost-effectiveness of final solutions. Analyses were undertaken using a synthetic data set replicating changes of environmental suitability for several simulated species using several experimental designs. Results: Our results showed that minor differences to the optimal persistence scores can result in large contraction of cost-effectiveness in final solutions. Main conclusions: Persistence targets should be carefully assessed case by case, and alternative species persistence settings should be considered, as they potentially result in important reductions of cost-effectiveness. Our model along with the respective heuristic can be used as a tool to efficiently promote species persistence under climate change.

Original languageEnglish
Pages (from-to)703-713
Number of pages11
JournalDiversity and Distributions
Volume23
Issue number6
DOIs
Publication statusPublished - 1 Jun 2017

Keywords

  • biogeography conservation
  • decision support tools
  • mixed-integer programming
  • reserve design
  • risk analysis
  • spatial optimization

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