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    基于GWR和RF模型的泸江流域土壤有机碳空间分布特征

    Spatial distribution characteristics of soil organic carbon in Lujiang River Basin based on GWR and RF model

    • 摘要: 研究喀斯特石漠化区土壤有机碳空间分异与其土壤理化性质、环境因子变量之间的关系,可为增加土壤碳汇和提高土壤质量提供科学依据。在喀斯特石漠化区泸江流域进行野外采样,基于地理加权回归(GWR)模型和随机森林(RF)模型对土壤变量因子、地形因子和气候因子进行建模空间分布预测,并分析土壤有机碳的影响因素。结果表明:1)GWR模型预测泸江流域土壤有机碳上层(0~20 cm)和下层(20~40 cm)的质量浓度局部决定系数(Local R2)在0.42~0.65和0.48~0.62之间,各解释因子具有较强的空间异质性特征;2)上层和下层土壤有机碳质量浓度预测精度分别为82.3%和83.4%,范围分别为0.90~11.25 kg/m2和0.85~5.49 kg/m2,上层土壤最大值、最小值和平均值均高于下层;3)土壤有机碳的空间分布是上层高值区出现在泸江流域的东西2翼,下层的是泸江流域西部和东北部的土壤有机碳质量浓度高; 4)基于RF影响因素分析,上层土壤最大影响的因子为碱解氮(72.73%),下层土壤最大的影响因子为年平均气温(39.39%),上层和下层均受到碱解氮和总氮的影响较大,土壤内部理化性质相较于外部自然环境因子,对区域土壤有机碳空间分布影响更显著。研究结果可为泸江流域促进土壤有机碳循环、提高土壤肥力提供理论支撑。

       

      Abstract:
      Background Soil organic carbon is an important component of carbon storage in terrestrial ecosystems, due to severe soil erosion in karst rocky desertification areas, soil fertility has decreased and soil organic carbon has been lost, causing significant impacts on the ecological environment of the watershed. In this study, the spatial heterogeneity of soil organic carbon content in karst rocky desertification areas was studied.The relationship between organic carbon content and other soil physicochemical properties, Environmental factor variables was discussed. This will provide a scientific basis for increasing soil carbon sink and improving soil quality.
      Methods We collected soil samples from 0–20 cm and 20–40 cm, air dried them naturally and took an appropriate amount of sample to grind and sieve, and measured soil physical and chemical indicators. Firstly, based on soil carbon content data, we calculated the single point soil organic carbon density. Secondly, field soil sampling was carried out in the karst rocky desertification area of Lujiang River Basin. The spatial distribution of soil organic carbon content was predicted based on geographically weighted regression (GWR) model and the random forest (RF) algorithm in combination with topographic variables, climate variables and soil variables.
      Results 1) GWR model predicted that the local determination coefficients for the average contents of soil organic carbon in topsoil (0–20 cm) and subsoil (20–40 cm) in the study area were between 0.42–0.65 and 0.48–0.62, and the explanatory factors had strong spatial heterogeneity. 2) The prediction accuracy of soil organic carbon content in topsoil and subsoil was 82.3% and 83.4%, respectively, based on the GWR model, the predicted values of soil organic carbon mass concentration in topsoil and subsoil were obtained 0.90–11.25 kg/m2 and 0.85–5.49 kg/m2 respectively, the maximum, minimum and average values of the topsoil were higher than those of the subsoil. 3) The spatial distribution of soil organic carbon contents was that the high values appeared in topsoil in the east and west wings of the Lujiang River Basin, while in subsoil in the west and northeast of the Lujiang River Basin. 4) Based on the analysis of influencing factors via RF algorithms, the most influential factor of the topsoil was alkali-hydrolyzed nitrogen (72.73%) and the most influential factor of subsoil was annual mean temperature (39.39%), both the upper and lower layers were significantly affected by ammonium nitrogen and total nitrogen. The effect of soil physicochemical properties on the spatial distribution of regional organic carbon content was remarkable than that of external natural environmental factors.
      Conclusions This study reveals the spatial differentiation characteristics of soil organic carbon in the Lujiang River Basin and analyzes various indicator factors that affect the spatial distribution of soil organic carbon, which may provide a theoretical support for promoting soil organic carbon cycle, reducing soil erosion and improving soil fertility in Lujiang River Basin.

       

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