长江流域资源与环境 >> 2023, Vol. 32 >> Issue (4): 751-763.doi: 10.11870/cjlyzyyhj202304007

• 自然资源 • 上一篇    下一篇

基于GWR模型的秭归县柑橘园土壤有机碳空间异质性分析

王  娜1,李  乐2,勾蒙蒙1,胡建文1,喇蕗梦1,肖文发1,3,刘常富1,3*   

  1. (1. 中国林业科学研究院森林生态环境与自然保护研究所,国家林业和草原局森林生态环境重点实验室,北京100091;2. 中国林业科学研究院热带林业研究所,广东 广州 510520;3. 南京林业大学南方现代林业协同创新中心,江苏 南京 210037)
  • 出版日期:2023-04-20 发布日期:2023-04-27

Spatial Heterogeneity Analysis of Soil Organic Carbon in Citrus Orchards in Zigui County Based on  GWR Model

WANG Na1, LI Le2, GOU Meng-meng1, HU Jian-wen1, LA Lu-meng1, XIAO Wen-fa1,3, LIU Chang-fu1,3   

  1. (1. Key Laboratory of Forest Ecology and Environment, National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China; 2. Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou 510520, China; 3. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China)
  • Online:2023-04-20 Published:2023-04-27

摘要: 研究柑橘园土壤有机碳空间异质性及其与土壤理化性质、地形特征和气候变量之间的关系,为提升经济林生态系统服务提供科学依据。在秭归县柑橘分布区内进行野外采样,基于随机森林和地理加权回归模型并结合8个地形因子、2个气候因子和13个土壤变量,建模分析了土壤有机碳的主要影响因素,并进行了土壤有机碳含量的空间分布预测。结果表明:研究区0~20 cm(表层)和20~40 cm(下层)土壤有机碳含量平均值分别为11.95和9.01 g·kg-1,长江北岸(9.24和7.56 g·kg-1)土壤有机碳含量低于长江南岸(14.48和10.36 g·kg-1),但长江北岸(0.53和0.66)变异系数高于长江南岸(0.45和0.58)。影响因素对土壤有机碳含量空间分布的相对贡献在土层间存在差异,表层为全氮(53.0%)>全钾(11.9%)>碱解氮(11.4%)>年均降水量(7.6%)>土壤含水量(7.3%)>年均温度(5.1%)>海拔(3.7%),下层为全氮(69.7%)>碱解氮(14.2%)>容重(7.5%)>平面曲率(4.3%)>全钾(3.8%)>细砂(0.6%)。地理加权回归模型预测柑橘园表层和下层土壤有机碳含量分别为6.92~16.85和5.76~13.75 g·kg-1,土壤有机碳含量空间分布局部决定系数在0.662~0.692和0.596~0.642之间,表现为表层北高南低、下层东高西低的特征。秭归县柑橘园实测和预测的土壤有机碳含量均存在明显的空间分异特征:长江南岸高于长江北岸,表层高于下层。土壤理化性质对区域有机碳含量空间分布的影响高于地形和气候因子,土壤全氮的相对贡献最大。因此,通过调控经济林土壤氮素等土壤理化性质有利于提高土壤有机碳储量。

Abstract:  In this study, the spatial heterogeneity of soil organic carbon content in citrus orchards was studied. The relationship between organic carbon content and other soil physicochemical properties, topographic characteristics and climate variables was discussed. This will provide a scientific basis for improving economic forest ecosystem services. Field soil sampling was carried out in the citrus distribution area of Zigui County. The main influencing factors of soil organic carbon were simulated and the spatial distribution of soil organic carbon content was predicted based on the random forest algorithm and geographically weighted regression model in combination with eight topographic variables, two climate variables and thirteen soil variables. The results show that the average contents of soil organic carbon in 0-20 cm (topsoil) and 20-40 cm (subsoil) in the study area were 11.95 and 9.01 g·kg-1, respectively. The soil organic carbon content on the northern bank of the Yangtze River (9.24 and 7.56 g·kg-1) was lower than that on the southern bank of the Yangtze River (14.48 and 10.36 g·kg-1), while the coefficient of variation on the northern bank (0.53 and 0.66) was higher than that on the southern bank (0.45 and 0.58). The relative contribution of influencing factors to the spatial distribution of soil organic carbon content was different among soil layers. The relative contributions were in descending order: total nitrogen (53.0%) > total potassium (11.9%) > available nitrogen (11.4%) > mean annual precipitation (7.6%) > soil moisture content (7.3%) > mean annual temperature (5.1%) > elevation (3.7%) in topsoil; total nitrogen (69.7%) > available nitrogen (14.2%) > bulk density (7.5%) > plane curvature (4.3%) > total potassium (3.8%) > fine sand (0.6%) in subsoil. Based on the geographically weighted regression model, the predicted values of soil organic carbon content in topsoil and subsoil were obtained, i.e., 6.92-16.85 and 5.76-13.75 g·kg-1, respectively. The local coefficients of determination of soil organic carbon content were 0.662-0.692 and 0.596-0.642, respectively. The soil organic carbon content also exhibited the characteristic of “high in the north and low in the south in topsoil, and high in the east and low in the west in subsoil”. The measured and predicted soil organic carbon contents of citrus orchards in Zigui County showed obvious spatial differentiation characteristics: the southern bank > the northern bank and the topsoil > the subsoil. The influence of soil physicochemical properties on the spatial distribution of regional organic carbon content was higher than that of topographic and climate factors. Particularly, total nitrogen had the largest relative contribution. Therefore, regulating soil physicochemical properties such as soil nitrogen in economic forests is beneficial to increasing soil organic carbon storage.

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