Soils provide services that can increase food security and mitigate global warming. Simulation modelling of biophysical processes is one approach used to estimate values of soil ecosystem services (SES) based on soil properties and climate conditions. The SES are usually investigated using statistical approaches that assume that values of SES are normally distributed. This assumption, however, ignores atypical values of SES, which deviate strongly from average values. Classic approaches have, therefore, failed to identify such atypical values of SES. To address this issue, we applied extreme value theory (EVT) as a statistical tool to identify thresholds above which SES can be considered as ‘extreme’. EVT was applied to a dataset of four SES—climate regulation, groundwater recharge, water-to-plant provision and plant biomass provision—estimated by biophysical soil and crop modelling based on a dataset of 64 cultivated soils located in northwestern France under a single climate observed over 30 years (1988–2018) and a single crop management of a maize and wheat rotation. Extreme values of the SES considered in our study were identified, and soil properties associated with these values were characterised. For instance, soils with extreme minimum values of climate regulation service had the highest pH, clay and organic carbon contents and maximum rooting depth. Applying EVT also enabled identification of the ‘return period’, which is the amount of time after which an extreme value of SES is likely to occur again. For instance, under the maize and wheat rotation simulated and weather conditions equivalent to those from 1988 to 2018, storage of organic carbon in the soil of 1000 kg C ha⁻¹ year⁻¹ is expected to be exceeded by at least one of the 64 of soils once every 2 years. This approach can thus be useful for decision making in natural resource management by identifying atypical values of SES and predicting how frequently they may occur.

中文翻译：

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根据相关土壤特性和天气条件预测的土壤生态系统服务极值分析

土壤提供的服务可以提高粮食安全和减缓全球变暖。生物物理过程的模拟建模是一种用于根据土壤特性和气候条件估算土壤生态系统服务 (SES) 值的方法。SES 通常使用假设 SES 值呈正态分布的统计方法进行研究。然而，这个假设忽略了 SES 的非典型值，它与平均值有很大的偏差。因此，经典方法未能识别 SES 的此类非典型值。为了解决这个问题，我们应用极值理论 (EVT) 作为统计工具来确定 SES 可被视为“极端”的阈值。EVT 应用于四个 SES 的数据集——气候调节、地下水补给、水对植物的供应和植物生物量的供应——通过生物物理土壤和作物模型估算，该模型基于法国西北部 64 种耕作土壤的数据集，在 30 多年（1988-2018 年）观察到的单一气候和单一作物管理的情况下玉米和小麦轮作。确定了我们研究中考虑的 SES 的极值，并描述了与这些值相关的土壤特性。例如，具有气候调节服务极小值的土壤具有最高的 pH 值、粘土和有机碳含量以及最大根深。应用 EVT 还可以识别“重现期”，即 SES 极值可能再次出现之前的时间量。例如，⁻¹ 年⁻¹预计每 2 年一次被 64 种土壤中的至少一种超过。因此，通过识别 SES 的非典型值并预测它们可能出现的频率，这种方法可用于自然资源管理中的决策制定。