鄱阳湖季节性淹水湿地土壤有机碳动态模拟与预测

该文以鄱阳湖国家级湿地自然保护区的泗洲头、常湖池以及蚌湖季节性淹水湿地为研究对象,选择典型湿地植被芦苇(Phragmites australis)、苔草(Carex spp)和南荻(Triarrhena lutarioriparia),基于DNDC模型模拟和预测不同湿地植被下表层(0～20 cm)土壤有机碳含量(m_SOC)动态变化,估算土壤碳储量和CO₂的年排放量.结果表明:DNDC模型能够准确模拟研究区不同典型植被下的m_SOC动态变化,δ_RSME<30%,R²>0.9.敏感性分析显示:影响m_SOC动态变化的敏感因素是初始土壤有机碳和黏粒含量.常湖池、蚌湖和泗洲头土壤平均有机碳密度分别为36.71、17.12和11.47 t·hm^-2,土壤碳储量分别为8 738、66 090和21 174 t,常湖池具有较大的碳储量.苔草、南荻和芦苇平均土壤碳密度分别为21.96、21.86、15.98 t·hm^-2,土壤碳储量分别为933 928、62 933、166 458 t,苔草固碳能力巨大.基于DNDC模型模拟预测表明:在未来120年内研究区不同植被类型土壤有机碳含量将呈稳定下降趋势.

The Dynamic Simulation and Prediction of Soil Organic Carbon in Seasonally Flooded Wetlands in Poyang Lake

Taking the seasonally flooded wetlands of Sizhoutou,Changhuchi and Banghu in Poyang Lake National Wetland Nature Reserve as the research objects,the typical wetland vegetation Phragmites australis,Carex spp and Triarrhena lutarioriparia are selected.Based on the DNDC model, the dynamic changs of soil organic carbon(m_SOC)under the different wetland vegetation(0—20 cm)are simulated and predicted,and the soil carbon storage and annual CO₂ emissions are estimated.The results show that the DNDC model can accurately simulate the dynamic changes of m_SOC under different typical vegetation in the study area,with δ_RMSE<30% and R²>0.9. Sensitivity analysis shows that the sensitive factors affecting the dynamic change of m_SOC are the initial soil organic carbon and clay content of the topsoil.The average soil organic carbon density of Changhuchi,Banghu and Sizhoutou are 36.71,17.12 and 11.47 t·hm^-2,respectively,and the soil carbon storage are 8 738,66 090 and 21 174 t,respectively.Changhuchi has a larger carbon storage.The average soil carbon densities of C. spp,T. lutarioriparia and P. australis are 21.96,21.86 and 15.98 t·hm^-2,respectively,and the soil carbon storage are 933 928,62 933 and 166 458 t,respectively.C. spp has a huge carbon sequestration capacity.Based on the DNDC model simulation prediction,it is found that the soil organic carbon content of different vegetation types in the study area will show a steady downward trend in the next 120 years.