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

IF 3.2 3区 环境科学与生态学 Q2 ECOLOGY Ecological Modelling Pub Date : 2025-03-01 Epub Date: 2025-02-16 DOI:10.1016/j.ecolmodel.2025.111041
Nicolas Elleaume , Bruno Locatelli , David Makowski , Améline Vallet , Jérôme Poulenard , Johan Oszwald , Sandra Lavorel
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Abstract

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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土地和气候情景下未来生态系统服务的不确定性:以阿尔卑斯山的侵蚀为例
在气候和土地利用变化不确定的情况下,生态系统将如何在未来提供生态系统服务是一个悬而未决的问题,对适应气候变化的决策提出了挑战。对生态系统服务的前瞻性评估应仔细地包括并通报影响预测的不确定因素的来源。我们以Maurienne山谷(法国阿尔卑斯山脉)的土壤保护生态系统服务为例,说明了如何将几个不确定性来源整合到未来生态系统服务供应的评估中。我们使用修订通用土壤流失方程(RUSLE)和6种气候和社会经济情景模拟了2020年和2085年毛里安河谷未来的侵蚀率。我们量化了气候和土地利用变化分别和共同影响生态系统服务供应的可能方式。我们评估了不同不确定性来源对预估侵蚀率的影响:情景、气候模式选择和生态系统服务模式参数化方法。土地利用变化增加侵蚀(+ 3.3 t .ha-1)。年-1平均,81%的研究地点显著增加),而气候变化略微减少(-0.21吨-公顷)。年-1平均显著下降20%的研究地点)。生态系统服务模式参数化的不确定性解释了侵蚀值变化的93%。此外,与气候模式和未来情景相关的不确定性对侵蚀变化方向(正或负)变率的贡献几乎相等(分别为41%和38%)。围绕未来生态系统服务变化方向的不确定性主要来自气候模式和未来情景的不确定性,而不是生态系统服务模式参数的不确定性。评估生态系统服务未来变化的可能性有助于优先考虑可能需要适应解决方案的地点。
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来源期刊
Ecological Modelling
Ecological Modelling 环境科学-生态学
CiteScore
5.60
自引率
6.50%
发文量
259
审稿时长
69 days
期刊介绍: The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).
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