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

Unpacking ecosystem service bundles: towards predictive mapping of synergies and trade-offs between ecosystem services
Unpacking ecosystem service bundles: towards predictive mapping of synergies and trade-offs between ecosystem services
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.
0959-3780
37-50
Spake, Rebecca
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Lasseur, Remy
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Crouzat, Emilie
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Bullock, James M.
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Lavorel, Sandra
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Parks, Katherine E.
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Schaafsma, Marije
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Bennett, Elena M.
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Maes, Joachim
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Mulligan, Mark
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Mouchet, Maud
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Peterson, Garry D.
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Schulp, Catharina J.E.
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Thuiller, Wilfried
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Turner, Monica G.
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Verburg, Peter H.
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Eigenbrod, Felix
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Spake, Rebecca
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Lasseur, Remy
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Crouzat, Emilie
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Bullock, James M.
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Lavorel, Sandra
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Parks, Katherine E.
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Schaafsma, Marije
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Bennett, Elena M.
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Maes, Joachim
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Mulligan, Mark
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Mouchet, Maud
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Peterson, Garry D.
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Schulp, Catharina J.E.
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Thuiller, Wilfried
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Turner, Monica G.
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Verburg, Peter H.
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Eigenbrod, Felix
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Spake, Rebecca, Lasseur, Remy, Crouzat, Emilie, Bullock, James M., Lavorel, Sandra, Parks, Katherine E., Schaafsma, Marije, Bennett, Elena M., Maes, Joachim, Mulligan, Mark, Mouchet, Maud, Peterson, Garry D., Schulp, Catharina J.E., Thuiller, Wilfried, Turner, Monica G., Verburg, Peter H. and Eigenbrod, Felix (2017) Unpacking ecosystem service bundles: towards predictive mapping of synergies and trade-offs between ecosystem services. Global Environmental Change, 47, 37-50. (doi:10.1016/j.gloenvcha.2017.08.004).

Record type: Article

Abstract

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.

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Spake et alUnpacking ecosystem service bundles_acceptedMS - Accepted Manuscript
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Accepted/In Press date: 7 August 2017
e-pub ahead of print date: 4 October 2017
Published date: November 2017

Identifiers

Local EPrints ID: 413028
URI: http://eprints.soton.ac.uk/id/eprint/413028
ISSN: 0959-3780
PURE UUID: 59f2a0c5-4ffc-4ed2-8a08-77a1fef9bf69
ORCID for Marije Schaafsma: ORCID iD orcid.org/0000-0003-0878-069X
ORCID for Felix Eigenbrod: ORCID iD orcid.org/0000-0001-8982-824X

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Date deposited: 14 Aug 2017 16:30
Last modified: 20 Feb 2021 05:02

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Contributors

Author: Rebecca Spake
Author: Remy Lasseur
Author: Emilie Crouzat
Author: James M. Bullock
Author: Sandra Lavorel
Author: Elena M. Bennett
Author: Joachim Maes
Author: Mark Mulligan
Author: Maud Mouchet
Author: Garry D. Peterson
Author: Catharina J.E. Schulp
Author: Wilfried Thuiller
Author: Monica G. Turner
Author: Peter H. Verburg
Author: Felix Eigenbrod ORCID iD

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