Increasing decision relevance of ecosystem service science

Lisa Mandle, Analisa Shields-Estrada, Rebecca Chaplin-Kramer, Matthew G.E. Mitchell, Leah L. Bremer, Jesse D. Gourevitch, Peter Hawthorne, Justin A. Johnson, Brian E. Robinson, Jeffrey R. Smith, Laura J. Sonter, Gregory M. Verutes, Adrian L. Vogl, Gretchen C. Daily, Taylor H. Ricketts

Research output: Contribution to journalArticlepeer-review

107 Scopus citations

Abstract

The ecosystem service (ES) community aspires to illuminate how nature contributes to human well-being, and thereby elevate consideration of nature in decision making. So far, however, policy impact of ES research has been limited. To understand why, we identify five key elements of ES research that help inform decisions by connecting the supply of ES to those who benefit from them. Our structured review of the ES literature reveals that only 13% of assessments included the full ES chain from place to value. Only 7% of assessments considered the distribution of ES benefits explicitly across demographic or other beneficiary groups (for example, private landowners versus the broader public), although disaggregation across regions or spatial units was more common (44%). Finally, crucial mediating factors that affect who benefits and how (for example, the vulnerability of beneficiaries or the availability of substitutes for ES) were considered in only 35% of assessments. Our results suggest that increasing the decision relevance of ES research requires more effectively predicting the impacts of specific decisions on the value and distribution of ES across beneficiary groups. Such efforts will need to integrate ecological models with socioeconomic and cultural dimensions of ES more closely than does the current ES literature.

Original languageEnglish (US)
Pages (from-to)161-169
Number of pages9
JournalNature Sustainability
Volume4
Issue number2
DOIs
StatePublished - Oct 12 2020

Bibliographical note

Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature Limited.

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