Model Ensembles of Ecosystem Services Fill Global Certainty and Capacity Gaps

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

Fersiynau electronig

Dangosydd eitem ddigidol (DOI)

  • Simon Willcock
  • Danny Hooftman
    Centre for Ecology and Hydrology, Wallingford, UK
  • Rachel Neugarten
    Cornell University
  • Rebecca Chaplin-Kramer
    Stanford University
  • Jose Barredo
    European Commission, Joint Research Centre (JRC), Ispra, Italy
  • Thomas Hickler
    Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Germany
  • Georg Kindermann
    International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
  • Amy Lewis
  • Mats Lindeskog
    Lund University
  • Javier Martinez-Lopez
    University of Granada, Granada, Spain
  • James Bullock
    Centre for Ecology and Hydrology, Wallingford, UK

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.

Allweddeiriau

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CyfnodolynScience Advances
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Dyddiad ar-lein cynnar7 Ebr 2023
Dynodwyr Gwrthrych Digidol (DOIs)
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