Interactions among ecosystem services across Europe: Bagplots and cumulative correlation coefficients reveal synergies, trade-offs, and regional patterns. (February 2015)

• Record Type: Journal Article
• Authors: Jopke, Cornelius; Kreyling, Juergen; Maes, Joachim; Koellner, Thomas
• Is Part Of: Ecological indicators. Volume 49(2015)
• Page Start: 46
• Page End: 52
• Publication Date: 2015-02
• Subjects: Nonparametric statistics -- Cumulative correlation coefficient -- Trade-offs -- Synergies -- Ecosystem services -- European union; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2014.09.037
• Languages: English
• ISSNs: 1470-160X

Abstract

Abstract: Understanding interactions of ecosystem service pairs and bundles is vital for making reasonable decisions in ecosystem management. Often, interaction analyses use linear correlation coefficients in order to identify trade-offs and synergies. Due to non-linear relations between ecosystem services in many cases, only weak interdependencies are revealed by this approach. For this reason we adopted nonparametric statistics, specifically bagplots (bivariate boxplots), for analyzing ecosystem service interactions. We demonstrate that bagplots complement correlation coefficients in assessing ecosystem services at NUTS 3 level across Europe and use them for mapping geographical patterns. In addition we suggest a new measure, which is the cumulative correlation coefficient R to rank the ecosystem services based on their synergies and trade-offs. We found that crop capacity is clearly the most conflicting ecosystem service, and carbon storage the one with the highest synergistic value. We conclude that bagplots allow insights into the relationships between ecosystems services beyond the highly aggregated correlation coefficients. In addition the new standardized measure – cumulative R – could support monitoring of trade-offs and synergies in time for a given study region or comparing study regions with respect to their frictions in ecosystem services supply.