The causes of spatial variability of surface soil organic matter in different forests in depressions between karst hills

基于动态监测样地(200 m × 40 m)的网格(10 m × 10 m)取样,以农作区为对照,用地统计学方法研究了喀斯特峰丛洼地人工林、次生林和原生林3类典型森林生态系统表层土壤(0-15 cm)有机质的空间变异,通过主成分分析和相关分析,探讨了其生态学过程和机制。结果表明:喀斯特峰丛洼地土壤有机质很高,沿着农作区-人工林-次生林-原生林的恢复梯度,土壤有机质显著提高,变异系数逐步增大;农作区和3类森林土壤表层有机质均具有良好的空间自相关性;农作区试验半变异函数C₀/(C₀+C)值为26.5%,呈中等程度的空间相关性;3类森林的C₀/(C₀+C)值为9.0%-22.6%,呈强烈的空间相关性;农作区和人工林土壤有机质呈单峰分布,次生林呈凹型分布,原生林呈凸型分布;不同森林的主导因子不同,农作区的主导因子为主要土壤养分,人工林为地形和物种多样性,次生林为森林结构和物种多样性,原生林为地形和物种多样性,且同一因子在不同森林与土壤表层有机质的正负作用关系和相关程度也不同。因此,农作区和3类森林应根据其土壤表层有机质的空间变异及主要影响因子制定相应的固碳措施。;The spatial variability of surface soil (0-15 cm) organic matter in plantation, secondary forest, and primary forest in depressions between hills in a karst region was examined using farmland as a control. The ecological processes and mechanisms behind this variability were also discussed. Eighty sample plots of 10 m × 10 m were established in 200 m × 40 m farmland, plantation, secondary fores, and primary forest plots in depressions between karst hills. Geostatistics was used to analyze the spatial pattern of surface soil organic matter in the plots and principal component analysis and correlation analysis were used to analyze the relationships with other factors. The soil organic matter content in the depressions between karst hills was high. Along the restoration gradient from farmland > plantation > secondary forest > primary forest, the surface soil organic matter content significantly increased and the coefficients of variation also increased. The vegetation in primary forest was well preserved and soil organic matter was up to 118 g/kg, 3.76 times that of farmland. The coefficients of variation of soil organic matter in the farmland and three forest types were 19.4%-48.5%. There was a fine spatial autocorrelation in the surface soil organic matter in the farmland and the three forest types. The farmland and plantation forest were strongly influenced by humans and therefore more balanced. This meant the correlogram range was large and the maximum correlogram coefficient Moran's I was 0.460 in the farmland and 0.780 in the plantation. The natural restoration time of the secondary forest was 22 years. Here there were more, but unevenly distributed, vegetation types meaning the correlogram range was smaller and Moran's I coefficients fluctuated considerably. In the primary forest, however, the disturbance was low and vegetation intact. This meant the correlation was mainly affected by the topography. The best fitting models for semi-variation of secondary forest soil organic matter function in Karst peak-cluster depressions are the exponential model and the Gaussian model. The resulting R² values of 0.926-0.971 demonstrate how well they reflected the soil organic matter spatial structure characteristics. The value of C₀/(C₀+C) of the surface soil organic matter in farmland was 26.5%, indicating a medium spatial correlation. The values of C₀/(C₀+C) in the three forest types ranged from 9.0% to 22.6%, suggesting strong spatial correlations. The spatial pattern of surface soil organic matter in farmland and plantation presented a unimodal distribution: in secondary forest it had a concave distribution and in primary forest it had a convex distribution. Soil nutrient content was the largest influencing factor on the variation in the farmland, topography and species diversity were the largest influencing factors in the plantation and primary forest, and forest structure and species diversity were the largest influencing factors in the secondary forest. Even when considering the same factor in the three forest types, the functions and correlations differed. Therefore, the corresponding strategies of fixing carbon should take the spatial variability of surface soil organic matter and its largest influencing factors in farmland and the three forest types into account.