To what extent can ecosystem services motivate protecting biodiversity?

Laura E. Dee, Michel De Lara, Christopher Costello, Steven D. Gaines

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Society increasingly focuses on managing nature for the services it provides people rather than for the existence of particular species. How much biodiversity protection would result from this modified focus? Although biodiversity contributes to ecosystem services, the details of which species are critical, and whether they will go functionally extinct in the future, are fraught with uncertainty. Explicitly considering this uncertainty, we develop an analytical framework to determine how much biodiversity protection would arise solely from optimising net value from an ecosystem service. Using stochastic dynamic programming, we find that protecting a threshold number of species is optimal, and uncertainty surrounding how biodiversity produces services makes it optimal to protect more species than are presumed critical. We define conditions under which the economically optimal protection strategy is to protect all species, no species, and cases in between. We show how the optimal number of species to protect depends upon different relationships between species and services, including considering multiple services. Our analysis provides simple criteria to evaluate when managing for particular ecosystem services could warrant protecting all species, given uncertainty. Evaluating this criterion with empirical estimates from different ecosystems suggests that optimising some services will be more likely to protect most species than others.

Original languageEnglish (US)
Pages (from-to)935-946
Number of pages12
JournalEcology letters
Volume20
Issue number8
DOIs
StatePublished - Aug 2017

Bibliographical note

Publisher Copyright:
© 2017 John Wiley & Sons Ltd/CNRS

Keywords

  • Biodiversity conservation
  • biodiversity-ecosystem services
  • conservation decisions
  • ecosystem services
  • stochastic optimal control
  • uncertainty

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