Soils store vast amounts of carbon (C) on land, and increasing soil organic carbon (SOC) stocks in already managed soils such as croplands may be one way to remove C from the atmosphere, thereby limiting subsequent warming. The main objective of this study was to estimate the amount of additional C input needed to annually increase SOC stocks by 4‰ at 16 long-term agricultural experiments in Europe, including exogenous organic matter (EOM) additions. We used an ensemble of six SOC models and ran them under two configurations: (1) with default parametrization and (2) with parameters calibrated site-by-site to fit the evolution of SOC stocks in the control treatments (without EOM). We compared model simulations and analysed the factors generating variability across models. The calibrated ensemble was able to reproduce the SOC stock evolution in the unfertilised control treatments. We found that, on average, the experimental sites needed an additional 1.5 ± 1.2 Mg C ha⁻¹ year⁻¹ to increase SOC stocks by 4‰ per year over 30 years, compared to the C input in the control treatments (multi-model median ± median standard deviation across sites). That is, a 119% increase compared to the control. While mean annual temperature, initial SOC stocks and initial C input had a significant effect on the variability of the predicted C input in the default configuration (i.e., the relative standard deviation of the predicted C input from the mean), only water-related variables (i.e., mean annual precipitation and potential evapotranspiration) explained the divergence between models when calibrated. Our work highlights the challenge of increasing SOC stocks in agriculture and accentuates the need to increasingly lean on multi-model ensembles when predicting SOC stock trends and related processes. To increase the reliability of SOC models under future climate change, we suggest model developers to better constrain the effect of water-related variables on SOC decomposition.

中文翻译：

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多模型预测显示达到 4‰ 目标所需的碳输入变化具有高度不确定性

土壤在陆地上储存了大量的碳 (C)，增加农田等已管理土壤中的土壤有机碳 (SOC) 储量可能是从大气中去除碳的一种方式，从而限制随后的变暖。本研究的主要目的是估算在欧洲进行的 16 项长期农业试验中每年将 SOC 储量增加 4‰ 所需的额外碳输入量，包括外源有机物 (EOM) 添加。我们使用了六个 SOC 模型的集合，并在两种配置下运行它们：(1) 使用默认参数化和 (2) 使用逐个站点校准的参数以适应控制处理（无 EOM）中 SOC 存量的演变。我们比较了模型模拟并分析了产生模型间变异性的因素。校准后的整体能够在未施肥的对照处理中重现 SOC 库的演变。我们发现，平均而言，实验地点需要额外的 1.5 ± 1.2 Mg C ha⁻¹ 年⁻¹与对照处理中的 C 输入相比，在 30 年内每年将 SOC 库存增加 4‰（多模型中值 ± 跨站点的中值标准差）。也就是说，与对照相比增加了 119%。虽然年平均温度、初始 SOC 储量和初始 C 输入对默认配置中预测的 C 输入的可变性（即预测的 C 输入与平均值的相对标准偏差）有显着影响，但只有与水相关的变量（即年平均降水量和潜在蒸散量）解释了校准时模型之间的差异。我们的工作强调了增加农业 SOC 库存的挑战，并强调在预测 SOC 库存趋势和相关过程时越来越依赖多模型集合。