Unpacking ecosystem service bundles: Towards predictive mapping of synergies and trade-offs between ecosystem services

Rebecca Spake, Rémy Lasseur, Emilie Crouzat, James M. Bullock, Sandra Lavorel, Katherine E. Parks, Marije Schaafsma, Elena M. Bennett, Joachim Maes, Mark Mulligan, Maud Mouchet, Garry D. Peterson, Catharina J.E. Schulp, Wilfried Thuiller, Monica G. Turner, Peter H. Verburg, Felix Eigenbrod*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Multiple ecosystem services (ES) can respond similarly to social and ecological factors to form bundles. Identifying key social-ecological variables and understanding how they co-vary to produce these consistent sets of ES may ultimately allow the prediction and modelling of ES bundles, and thus, help us understand critical synergies and trade-offs across landscapes. Such an understanding is essential for informing better management of multi-functional landscapes and minimising costly trade-offs. However, the relative importance of different social and biophysical drivers of ES bundles in different types of social-ecological systems remains unclear. As such, a bottom-up understanding of the determinants of ES bundles is a critical research gap in ES and sustainability science. Here, we evaluate the current methods used in ES bundle science and synthesize these into four steps that capture the plurality of methods used to examine predictors of ES bundles. We then apply these four steps to a cross-study comparison (North and South French Alps) of relationships between social-ecological variables and ES bundles, as it is widely advocated that cross-study comparisons are necessary for achieving a general understanding of predictors of ES associations. We use the results of this case study to assess the strengths and limitations of current approaches for understanding distributions of ES bundles. We conclude that inconsistency of spatial scale remains the primary barrier for understanding and predicting ES bundles. We suggest a hypothesis-driven approach is required to predict relationships between ES, and we outline the research required for such an understanding to emerge.

Original languageEnglish
Pages (from-to)37-50
Number of pages14
JournalGlobal Environmental Change
Early online date4 Oct 2017
Publication statusPublished - Nov 2017


A University of Southampton IfLS Research Stimulus Fund to RS, MS, KP, JMB and FE supported RS. RS, RL and FE received support from ERC Starting Grant ‘SCALEFORES’ (Grant number 680176 ). RS and JMB were funded by CEH project NEC05264 . RL, EC and SL received funding from OPERAs (grant number FP7-ENV-2012-two-stage-308393 ). MS received funding from an ESPA Early Career Fellowship Grant (grant number FELL-2014-104 ) with support from the Ecosystem Services for Poverty Alleviation (ESPA) programme. The ESPA programme is funded by the Department for International Development (DFID), the Economic and Social Research Council (ESRC) and the Natural Environment Research Council (NERC). PV received support from ERC Grant ‘GLOLAND’ (grant number 311819). Funding for MGT was provided by the US National Science Foundation (grant numbers DEB-1038759 , DEB-1440297 , and DEB-1440485 ). EB received funding from Natural Sciences and Engineering Research Council of Canada (grant number RGPIN 327077-2013 ) and NSERC EWR Steacie Fellowship. GDP was funded by Social-ecological dynamics of ecosystem services in the Norrström basin (SEEN) project, financed by the Swedish Research Council Formas (grant number 2012-1058 ) and Swedish Research Council MISTRA (through a core grant to the Stockholm Resilience Centre). We are grateful for constructive feedback from two anonymous reviewers.

FundersFunder number
Ecosystem Services for Poverty Alleviation
Stockholm Resilience Centre
Swedish Research Council MISTRA
National Science FoundationDEB-1440297, DEB-1440485, DEB-1038759
Horizon 2020 Framework Programme680176
Natural Sciences and Engineering Research Council of CanadaRGPIN 327077-2013
Economic and Social Research Council
Natural Environment Research Council311819
Department for International Development, UK Government
European Research Council
Svenska Forskningsrådet Formas2012-1058
Centre for Ecology and HydrologyFELL-2014-104, NEC05264, FP7-ENV-2012-two-stage-308393


    • Biodiversity
    • Cross-study comparison
    • Ecosystem services
    • French Alps
    • Land use
    • Natural capital
    • Social-ecological systems
    • Trade-off


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