Accounting for spatial interactions in the upscaling of ecosystem services

Abstract Maps of ecosystem service (ES) supply are frequently used to guide spatial planning, policymaking and ecosystem management. However, these are typically based upon coarse land‐cover proxies. This approach lacks a strong mechanistic basis and neglects spatial biodiversity dynamics and interactions among landscape properties that can modify ES provision. We present an analytical framework for ES upscaling that incorporates spatial interactions between landscape properties, which determine ES supply. The resulting models can be viewed as a spatially informed ES production function. Key aspects of our synthetic framework include (i) the systematic assessment of multiple drivers across many levels of abiotic and biotic organization to formulate the statistical ES production function, (ii) the inclusion of spatial interactions with the surrounding environment into the ES production function and (iii) the use of expert input to inform ES production functions. We demonstrate the approach using two example ES from German grasslands: biodiversity conservation and water supply. We show that the inclusion of spatial interactions in the upscaling model improved model predictions by 15%–33%, depending on the ES evaluated. In addition, inclusion of spatial interactions led to reduced error associated with the upscaled estimates. By overcoming several shortcomings of existing upscaling approaches, we generate maps of ES supply that can more reliably inform spatial planning. Further, the underlying models allow for simulation of changes in the drivers of ES supply and estimation of respective outcomes. These advantages have the potential to better link detailed local‐scale ecological understanding and land management with large‐scale ES supply mapping, and thus better inform decision making.

Authors

Institutions

Publication Details

Journal
Methods in Ecology and Evolution
Published
2026-03-17
DOI
https://doi.org/10.1111/2041-210x.70281
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accounting for spatial interactions in the upscaling of ecosystem services

Steffen Boch, Sophia Leimer, Maximilian Lange, Valentin H. Klaus et al.
Methods in Ecology and Evolution
Land Use and Ecosystem Services
article

Accounting for spatial interactions in the upscaling of ecosystem services

Steffen Boch, Sophia Leimer, Maximilian Lange, Valentin H. Klaus, Ralph Bolliger, Till Kleinebecker, Manuel Fischer, Gaëtane Le Provost, Kirsten Jung, Ute Hamer, Wolfgang Wilcke, Margot Neyret, Swen C. Renner, Paul Magdon, Javier Muro, Jörg Müller, Andrea Larissa Boesing, Peter Manning, Olena Dubovyk, Anja Linstädter
article en

Abstract

Abstract Maps of ecosystem service (ES) supply are frequently used to guide spatial planning, policymaking and ecosystem management. However, these are typically based upon coarse land‐cover proxies. This approach lacks a strong mechanistic basis and neglects spatial biodiversity dynamics and interactions among landscape properties that can modify ES provision. We present an analytical framework for ES upscaling that incorporates spatial interactions between landscape properties, which determine ES supply. The resulting models can be viewed as a spatially informed ES production function. Key aspects of our synthetic framework include (i) the systematic assessment of multiple drivers across many levels of abiotic and biotic organization to formulate the statistical ES production function, (ii) the inclusion of spatial interactions with the surrounding environment into the ES production function and (iii) the use of expert input to inform ES production functions. We demonstrate the approach using two example ES from German grasslands: biodiversity conservation and water supply. We show that the inclusion of spatial interactions in the upscaling model improved model predictions by 15%–33%, depending on the ES evaluated. In addition, inclusion of spatial interactions led to reduced error associated with the upscaled estimates. By overcoming several shortcomings of existing upscaling approaches, we generate maps of ES supply that can more reliably inform spatial planning. Further, the underlying models allow for simulation of changes in the drivers of ES supply and estimation of respective outcomes. These advantages have the potential to better link detailed local‐scale ecological understanding and land management with large‐scale ES supply mapping, and thus better inform decision making.

Methods in Ecology and Evolution
Karlsruhe Institute of Technology (DE), University of Bern (CH), Natural History Museum Vienna (AT), Centre National de la Recherche Scientifique (FR), Helmholtz Centre for Environmental Research (DE), Universität Hamburg (DE), University of Potsdam (DE), Justus-Liebig-Universität Gießen (DE), University of Münster (DE), Swiss Federal Institute for Forest, Snow and Landscape Research (CH), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Johann Heinrich von Thünen-Institut (DE), Santé et Agroécologie du Vignoble (FR), Senckenberg Biodiversity and Climate Research Centre (DE), Laboratoire d'Écologie Alpine (FR), Agroscope (CH), Heinz Nixdorf Stiftung (DE), Technische Hochschule Ulm (DE), University of Bergen (NO), HAW Hamburg (DE), Université Savoie Mont Blanc (FR), Université Grenoble Alpes (FR), Ruhr University Bochum (DE)
Life in Land
Openalex Percentile: Top 18%
Land Use and Ecosystem Services
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.