Abstract. Land planning projects aiming to maximise soil organic carbon (SOC) stocks are increasing in number and scope. In response, a rising number of studies assess SOC additional storage capacities over regional to global spatial scales. In order to provide realistic values transferrable beyond the scientific community, SOC storage capacity assessments should consider the timescales over which this capacity might be reached, considering the effects of C inputs, soil type and depth on soil C dynamics. This research was conducted in a 320 km² territory in North-eastern France where eight contrasted soil types have been identified, characterized and mapped thanks to a high density of fully-described soil profiles. Continuous profiles of SOC stocks were interpolated for each soil type and land use (cropland, grassland or forest). Depth-dependent estimates of maximum SOC additional storage capacity using the Hassink equation and a data-driven approach were compared. We used a novel method that uses the data-driven approach to constrain C inputs in a simple model of depth-dependent C dynamics to simulate SOC accrual over 25 years, and mapped the SOC stocks, maximum additional storage capacity and stock evolution. SOC stocks and maximum additional storage capacities are highly heterogenous over the region of study. Median SOC stocks range from 78–333 tC ha^-1. Data-driven maximum SOC additional storage capacities vary from 19 tC ha^-1 in forested Leptosols to 197 tC ha^-1 in grassland Gleysols. Estimations of SOC maximum additional storage capacities based on the Hassink approach led to unrealistic vertical distributions of SOC stock, with particular overestimation in the deeper layers. Crucially, the simulated SOC accrual over 25 years was five times lower than the maximum SOC additional storage capacity (0.57 and 2.5 MgC respectively). Further consideration of depth-dependent SOC dynamics in different soil types is therefore needed to provide targets of SOC storage over timescales relevant to public policies aiming to approach carbon neutrality by 2050.

中文翻译：

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2050年碳中和目标下不同土壤类型土壤有机碳额外储存能力的深度依赖性


摘要。旨在最大限度地提高土壤有机碳（SOC）储量的土地规划项目的数量和范围不断增加。为此，越来越多的研究评估了 SOC 在区域到全球空间尺度上的额外存储容量。为了提供可在科学界之外转移的现实值，SOC 存储容量评估应考虑可能达到该容量的时间尺度，并考虑碳输入、土壤类型和深度对土壤碳动态的影响。这项研究是在法国东北部 320 公里 ² 领土上进行的，由于高密度的全面描述的土壤剖面，已经识别、表征和绘制了八种对比鲜明的土壤类型。针对每种土壤类型和土地利用（农田、草地或森林）对 SOC 储量的连续剖面进行插值。使用 Hassink 方程和数据驱动方法对最大 SOC 附加存储容量的深度相关估计进行了比较。我们使用了一种新颖的方法，该方法使用数据驱动的方法来约束深度相关 C 动态的简单模型中的 C 输入，以模拟 25 年的 SOC 累积，并映射 SOC 库存、最大附加存储容量和库存演变。研究区域内的 SOC 库存和最大附加存储容量高度异质。 SOC 库中值范围为 78–333 tC ha ^-1 。数据驱动的最大 SOC 额外存储容量从森林薄土中的 19 tC ha ^-1 到草地 Gleysols 中的 197 tC ha ^-1 不等。基于 Hassink 方法对 SOC 最大附加存储容量的估计导致 SOC 存量的垂直分布不切实际，尤其是对更深层的估计过高。 至关重要的是，25 年来模拟的 SOC 累积量比最大 SOC 附加存储容量（分别为 0.57 和 2.5 MgC）低五倍。因此，需要进一步考虑不同土壤类型中与深度相关的 SOC 动态，以提供与旨在到 2050 年实现碳中和的公共政策相关的时间尺度上的 SOC 存储目标。