The 18 benefits of using ecosystem services classification systems
John Finisdore,
Charles Rhodes,
Roy Haines-Young,
Simone Maynard,
Jeffrey Wielgus,
Anthony Dvarskas,
Joel Houdet,
Fabien Quétier,
Karl A. Lamothe,
Helen Ding,
François Soulard,
George Van Houtven and
Petrina Rowcroft
Ecosystem Services, 2020, vol. 45, issue C
Abstract:
Ecosystem services (ES) practitioners (e.g., researchers, policy makers) have been working to better define, measure, and value the ways that nature contributes to society. Because measurement techniques follow the labeling or identification of ES, precise identification is critical. This article reviews literature and consults experts in classification science and ES to determine the expected benefits of using ES classification knowledge (classification knowledge); ecosystem services classification systems (ES-CS) and their principles. An informal analysis of the costs of transitioning from the current ad-hoc approach—based on various ES lists—to using classification knowledge was conducted. 18 benefits of using classification knowledge were found, including allowing ES to be defined more easily and precisely, easing the transfer of knowledge among studies, and avoiding the need to recreate ES identification systems. Collectively, these 18 benefits should allow for more accurate and consistent definition of ES, thereby serving to improve communication and measurement of ES. Moreover, the expected benefits of using ES-CS outweigh expected costs of the transition. Practitioners can use ES-CS in whole, or in parts, as their research or their institutions warrant. Finally, a case study was conducted that shows how ES measures can be organized using ES-CS, delivering benefits to practitioners.
Keywords: Ecosystem services; Final ecosystem services; Classification systems; NESCS; CICES; Ecosystem services metrics (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecoser:v:45:y:2020:i:c:s2212041620301029
DOI: 10.1016/j.ecoser.2020.101160
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