Identifying the optimal landscape configuration for landscape multifunctionality
2024
Boesing, Andrea Larissa | Klaus, Valentin, H | Neyret, Margot | Le Provost, Gaëtane | Peter, Sophie | Fischer, Markus | Manning, Peter | Senckenberg Biodiversity and Climate Research Centre (SBiK-F) ; Goethe University Frankfurt = Goethe-Universität Frankfurt am Main-Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung ; Leibniz Association-Leibniz Association | Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich) | Laboratoire d'Ecologie Alpine (LECA) ; Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (Fédération OSUG)-Université Grenoble Alpes (UGA) | Santé et agroécologie du vignoble (UMR SAVE) ; Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Institute for Social-Ecological Research (ISOE) | Universität Bern = University of Bern = Université de Berne (UNIBE) | University of Bergen (UiB)
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Show more [+] Less [-]English. Increased pressure on land resources to provide multiple benefits calls for landscape strategies that optimize the supply of multiple ecosystem services (ES). Previous research into the drivers of landscape multifunctionality have focused on land use composition changes, but the spatial configuration of different land use types also drives ES supply. While the impact of landscape configuration on individual ES is well understood, the net outcome of these influences when considering many ES is not. Here we present the net-balance spatial interactions hypothesis, which posits that the strength and direction of local and surrounding landscape influences on the local supply of an individual ES will drive its optimal landscape configuration. Accordingly, the net balance of these influences across multiple prioritized ES will determine the optimal configuration for landscape multifunctionality. Further, ES that share the same optimal configuration strategy form a bundle that can be managed together. Using data from German grasslands we demonstrate that the net-balance spatial interactions hypothesis is applicable to land-use planning scenarios that aim to maximize multiple ES. It allows general rules to be applied when local, detailed ES data is not available, and can help identify the best option to minimize trade-offs in the face of multiple competing land-use objectives.
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