Model ensembles of ecosystem services fill global certainty and capacity gaps

Willcock, Simon; Hooftman, Danny A.P. ORCID: https://orcid.org/0000-0001-9835-6897; Neugarten, Rachel A.; Chaplin-Kramer, Rebecca; Barredo, José I.; Hickler, Thomas; Kindermann, Georg; Lewis, Amy R.; Lindeskog, Mats; Martínez-López, Javier; Bullock, James M. ORCID: https://orcid.org/0000-0003-0529-4020. 2023 Model ensembles of ecosystem services fill global certainty and capacity gaps. Science Advances, 9 (14), eadf5492. 15, pp. https://doi.org/10.1126/sciadv.adf5492

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Official URL: http://dx.doi.org/10.1126/sciadv.adf5492

Abstract/Summary

Sustaining ecosystem services (ES) critical to human well-being is hindered by many practitioners lacking access to ES models (“the capacity gap”) or knowledge of the accuracy of available models (“the certainty gap”), especially in the world’s poorer regions. We developed ensembles of multiple models at an unprecedented global scale for five ES of high policy relevance. Ensembles were 2 to 14% more accurate than individual models. Ensemble accuracy was not correlated with proxies for research capacity, indicating that accuracy is distributed equitably across the globe and that countries less able to research ES suffer no accuracy penalty. By making these ES ensembles and associated accuracy estimates freely available, we provide globally consistent ES information that can support policy and decision-making in regions with low data availability or low capacity for implementing complex ES models. Thus, we hope to reduce the capacity and certainty gaps impeding local- to global-scale movement toward ES sustainability.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1126/sciadv.adf5492
UKCEH and CEH Sections/Science Areas:	Biodiversity (Science Area 2017-) UKCEH Fellows
ISSN:	2375-2548
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
NORA Subject Terms:	Ecology and Environment Data and Information
Related URLs:	Dataset Dataset
Date made live:	07 Nov 2023 11:09 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/535561

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1126/sciadv.adf5492

UKCEH and CEH Sections/Science Areas:

Biodiversity (Science Area 2017-)
UKCEH Fellows

ISSN:

2375-2548

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

NORA Subject Terms:

Ecology and Environment
Data and Information