Uncertainties in future ecosystem services under land and climate scenarios: The case of erosion in the Alps

• Probabilistic mapping Framework : Introduces a novel probabilistic method for integrating multiple sources of uncertainty—climate models, socioeconomic scenarios, and model parameterization—into spatially explicit ecosystem service assessments. • Key drivers of future Erosion : Demonstrates that land use and land cover (LULC) changes are the dominant drivers of future erosion in the Maurienne Valley, outweighing the generally reducing effects of climate change on erosion rates. • Distinct contributions of uncertainty Sources : Reveals that model parameterization drives the magnitude of erosion changes, while uncertainties in climate models and scenarios primarily influence the direction of future changes. How ecosystems will provide ecosystem services in the future given uncertain changes in climate and land use is an open question that challenges decision-making on adaptation to climate change. Prospective assessments of ecosystem services should carefully include and communicate the sources of uncertainties that affect the predictions. We used the ecosystem service of soil protection against erosion in the Maurienne Valley (French Alps) as a case study to illustrate how several sources of uncertainties can be integrated into an assessment of future ecosystem service supply. We modeled future erosion rates in the Maurienne Valley for years 2020 and 2085 using the Revised Universal Soil Loss Equation (RUSLE) and six climatic and socioeconomic scenarios. We quantified how the ecosystem service supply will be likely affected by climate and land-use change, separately and jointly. We assessed the effects of different sources of uncertainty on projected erosion rates: scenarios, climate models choice, and methods to parametrize the ecosystem service model. Land-use change increased erosion (+ 3.3 ton.ha-1.yr-1 on average, with significant increases in 81 % of the study site), while climate change contributed to a slight reduction (-0.21 ton.ha-1.yr-1 on average with significant decrease 20 % of the study site). The uncertainty of the ecosystem service model parameterization explained 93 % of the variance in erosion values. Furthermore, uncertainty linked to climate models and future scenarios contributed almost equally to the variability in the direction (positive or negative) of erosion change (41 % and 38 % respectively). The uncertainties surrounding the direction of future changes in ecosystem services come mainly from uncertainties in climate models and future scenarios rather than from uncertainties in the ecosystem service model parameters. Assessing the likelihood of future changes in ecosystem services helps prioritize locations where adaptation solutions are likely to be needed.

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Publication Details

Journal
Ecological Modelling
Published
2025-02-16
DOI
https://doi.org/10.1016/j.ecolmodel.2025.111041
Citations
4
Primary Topic
Soil erosion and sediment transport
Type
article
Field-Weighted Citation Impact
4.74

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article

Uncertainties in future ecosystem services under land and climate scenarios: The case of erosion in the Alps

Bruno Locatelli, David Makowski, Améline Vallet, Jérôme Poulenard et al.
4 citations
Ecological Modelling
Soil erosion and sediment transport
4.74
article

Uncertainties in future ecosystem services under land and climate scenarios: The case of erosion in the Alps

Bruno Locatelli, David Makowski, Améline Vallet, Jérôme Poulenard, Nicolas Elleaume, Johan Oszwald, Sandra Lavorel
article en
4 citations

Abstract

• Probabilistic mapping Framework : Introduces a novel probabilistic method for integrating multiple sources of uncertainty—climate models, socioeconomic scenarios, and model parameterization—into spatially explicit ecosystem service assessments. • Key drivers of future Erosion : Demonstrates that land use and land cover (LULC) changes are the dominant drivers of future erosion in the Maurienne Valley, outweighing the generally reducing effects of climate change on erosion rates. • Distinct contributions of uncertainty Sources : Reveals that model parameterization drives the magnitude of erosion changes, while uncertainties in climate models and scenarios primarily influence the direction of future changes. How ecosystems will provide ecosystem services in the future given uncertain changes in climate and land use is an open question that challenges decision-making on adaptation to climate change. Prospective assessments of ecosystem services should carefully include and communicate the sources of uncertainties that affect the predictions. We used the ecosystem service of soil protection against erosion in the Maurienne Valley (French Alps) as a case study to illustrate how several sources of uncertainties can be integrated into an assessment of future ecosystem service supply. We modeled future erosion rates in the Maurienne Valley for years 2020 and 2085 using the Revised Universal Soil Loss Equation (RUSLE) and six climatic and socioeconomic scenarios. We quantified how the ecosystem service supply will be likely affected by climate and land-use change, separately and jointly. We assessed the effects of different sources of uncertainty on projected erosion rates: scenarios, climate models choice, and methods to parametrize the ecosystem service model. Land-use change increased erosion (+ 3.3 ton.ha-1.yr-1 on average, with significant increases in 81 % of the study site), while climate change contributed to a slight reduction (-0.21 ton.ha-1.yr-1 on average with significant decrease 20 % of the study site). The uncertainty of the ecosystem service model parameterization explained 93 % of the variance in erosion values. Furthermore, uncertainty linked to climate models and future scenarios contributed almost equally to the variability in the direction (positive or negative) of erosion change (41 % and 38 % respectively). The uncertainties surrounding the direction of future changes in ecosystem services come mainly from uncertainties in climate models and future scenarios rather than from uncertainties in the ecosystem service model parameters. Assessing the likelihood of future changes in ecosystem services helps prioritize locations where adaptation solutions are likely to be needed.

Ecological ModellingVol. 502
Université Paris-Sud (FR), Centre National de la Recherche Scientifique (FR), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR), École nationale des ponts et chaussées (FR), Université de Montpellier (FR), AgroParisTech (FR), Université Paris-Saclay (FR), Université Rennes 2 (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Ecologie, Société, Evolution (FR), Département mathématiques, informatique, sciences de la donnée et technologies du numérique (FR), Laboratoire d'Écologie Alpine (FR), Mathématiques et Informatique Appliquées, Littoral, Environnement, Télédétection, Géomatique (FR), Université Savoie Mont Blanc (FR), Université Grenoble Alpes (FR)
Agence Nationale de la Recherche
Climate action
Openalex Percentile: Top 6%
Soil erosion and sediment transport
4.74
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