Data from: Simple measures of climate, soil properties and plant traits predict national scale grassland soil carbon stocks

1. Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. 2. Using data from an extensive national survey of English grasslands we show that surface soil (0–7cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. 3. Soil C stocks in the largest pool, of intermediate particle size (50–250 μm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0.45–50 μm), was explained by soil pH and the community abundance weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N rich vegetation. The C stock in the small active fraction (250–4000 μm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. 4. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. 5. Synthesis and applications. Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1–100 000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

1. 土壤碳（C）储量是一项关键的生态系统服务。土壤碳库在维持土壤肥力与调节气候方面发挥着至关重要的作用，但在区域乃至国家尺度上调控这些碳库的因素仍不明确，尤其是在考虑其组成与稳定性的情况下。当前此类碳库的制图仅能依赖可靠性不足的替代指标，或是耗费人力的直接测量手段。
2. 本研究基于英国全国草地大规模调查数据集，证实可通过植物功能性状（plant traits）以及土壤pH值（soil pH）、气候条件的简易测量指标，在区域与国家尺度上预测不同稳定性粒径组分（size fractions of varying stability）的表层土壤（surface soil，0~7cm）碳储量。
3. 占比最高的中等粒径（50~250 μm）碳库，其土壤碳储量的最优解释变量为年平均温度（mean annual temperature, MAT）、土壤pH值（soil pH）与土壤含水量。第二大碳库为受物理与生化双重保护的高稳定性颗粒（0.45~50 μm），其碳储量可由土壤pH值（soil pH）与群落加权平均（community abundance weighted mean, CWM）叶片氮（N）含量（leaf nitrogen content）解释，且富氮植被下的该碳库储量更高。小型活性组分（active fraction，250~4000 μm）的碳储量则受多类变量影响：年平均温度（mean annual temperature, MAT）、年平均降水量（mean annual precipitation）、平均生长季长度、土壤pH值（soil pH）以及群落加权平均比叶面积（specific leaf area）；在叶片厚实致密的植被下，该组分的碳储量更高。
4. 本研究利用英国另一独立区域的数据集对上述各粒径组分的预测模型进行独立验证，结果显示除活性组分外，其余组分的预测值与实测值呈中等强度相关，且无系统性偏差；活性组分的预测效果欠佳。
5. 综合与应用。验证结果表明，通过易于获取的气候、土壤与植物调查数据，可有效开展局地至景观尺度（1~100 000 km²）的土壤碳储量预测。此类预测是制定保护土壤碳库、提升土壤碳固存（soil C sequestration）能力的高效管理策略的核心组成部分。