长三角典型水稻土有机碳组分构成及其主控因子

准确把握水稻土有机碳组分构成特征及其主控因子,对定量化评价土壤有机碳质量和未来演变趋势具有重要意义。通过室内土壤呼吸培养实验结合有机碳三库一级动力学方程,模拟得到长三角地区典型水稻土剖面(0—100 cm)各土层有机碳组分含量及其分布特征;并利用主成分分析获取主控因子,建立有机碳组分回归预测模型。结果表明:水稻土活性碳、慢性碳和惰性碳含量随剖面深度增加而降低,上层土壤(0—40 cm)有机碳组分含量下降速度明显快于下层土壤(40—100 cm);水稻土活性碳构成比例不超过5.3%,惰性碳构成比例大于活性碳与慢性碳比例之和,达到60%以上,水稻土有机碳总量变异主要取决于慢性碳和惰性碳组分变异。因此,水稻土固碳重点在于慢性和惰性组分。同时,研究还发现水稻土类型和剖面深度主要在表层对有机碳组分含量和比例构成产生显著影响,土壤有机碳量、全氮和pH是影响水稻土有机碳组分含量分异的主控因子,利用主控因子可较好预测水稻土有机碳组分含量。

Characteristics of typical paddy soil organic carbon fractions and their main control factors in the Yangtze River Delta

Paddy soil is a key type of cultivated soil in China. Precisely understanding the characteristics and main control factors of paddy soil organic carbon fractions is critical to quantitatively evaluating soil organic carbon (SOC) quality and monitoring its trends. We collected 65 soil samples from 13 soil profiles associated with three major paddy soil types in the Yangtze River Delta, including 5 hydromorphic paddy soil profiles, 3 percogenic paddy soil profiles, and 5 degleyed paddy soil profiles. Through long-term soil incubation experiments, the SOC decomposition amounts were measured at different times (1, 3, 5, 7, 10, 15, 22, 29, 36, 43, 50, 60, 70, 84, 99 d); the amount of resistant SOC(C_r) was determined by the acid hydrolysis method, and the amount of active SOC(C_a), slow SOC(C_s), and resistant SOC(C_r) were simulated by fitting a three-pool first-order equation to the above data. Distribution characteristics of paddy soil organic fractions in profiles (0-100 cm) were analyzed and illuminated, and main control factors on SOC fractions were obtained through principal component analysis. Finally, a regression model was established to predict SOC fractions from the main control factors. Results showed that the amount of active SOC(C_a), slow SOC(C_s), and resistant SOC(C_r) declined with the increase of soil profile depth, and that the rate of SOC fraction decrease in the upper layer (0-40 cm) was faster than in the subsoil (40-100 cm). The type of paddy soil did not influence the amount of soil organic carbon fractions significantly. The C_a pool comprised less than 5.3% of the total SOC, and the proportion of the C_r pool, which was more than 60% in total SOC, was larger than the combined proportions of the C_a and C_s pools. The amount of SOC fractions was significantly higher in topsoil (0-20 cm) than in other soil horizons. The variation in total SOC was mainly due to the C_s and C_r contributions. Therefore, more attention should be paid to the fractions of C_s and C_r when maximizing carbon sequestration in soils. The type of paddy soil and the depth primarily influenced the organic carbon composition of the topsoil. This research found that total SOC, total nitrogen (TN), and pH were the main control factors influencing the differences in SOC fraction amounts, and they can be used to predict SOC fraction amounts to more comprehensively understand the SOC cycle. Determining the amounts and composition proportions of SOC fractions can contribute significantly to mastering soil organic carbon pool dynamics. Creating a cost effective model to predict SOC fractions is meaningful and urgent. According to our research, SOC fractions can be predicted from the basic physical and chemical properties of soils.