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段亚锋,王克林,冯达,吴敏,张伟,陈洪松.典型喀斯特小流域土壤有机碳和全氮空间格局变化及其对退耕还林还草的响应.生态学报,2018,(5).http://dx.doi.org/10.5846/stxb201701220184  
典型喀斯特小流域土壤有机碳和全氮空间格局变化及其对退耕还林还草的响应
Response of the spatial pattern of soil organic carbon and total nitrogen to vegetation restoration in a typical small karst catchment
投稿时间:2017-01-22  修订日期:2017-10-19
DOI: 10.5846/stxb201701220184
关键词喀斯特  土壤有机碳  土壤全氮  空间格局  退耕还林还草
Key WordsKarst  Soil organic carbon  Soil nitrogen  Spatial heterogeneity  Vegetation restoration
基金项目国家重点研发计划项目(2016YFC0502400);973 计划项目课题(2015CB452703);国家自然科学基金项目(31270555,41471445)
作者单位E-mail
段亚锋 湖南农业大学 206511@qq.com 
王克林 中国科学院亚热带农业生态研究所 kelin@isa.ac.cn 
冯达 湖南省测绘科技研究所  
吴敏 中国科学院亚热带农业生态研究所  
张伟 中国科学院亚热带农业生态研究所  
陈洪松 中国科学院亚热带农业生态研究所  
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摘要:
基于定点回顾实验设计,通过对比分析2005a初(退耕还林还草初期)和2014a底典型喀斯特峰丛洼地小流域土壤碳氮格局变化,探讨石漠化治理工程实施后,植被恢复对土壤碳氮积累和碳氮空间格局的影响。研究结果发现:退耕还林还草10a后,示范区土壤有机碳(SOC)含量显著增加1.3g/kg,但土壤全氮含量无显著变化;就空间格局而言,退耕还林还草初期土壤碳氮高值聚类区主要分布在坡脚旱地和荒地(荒草)类型区,退耕还林还草10a后其高值聚类区主要分布在荒地(灌丛和荒草)类型区,而10a前后土壤碳氮的低值聚类区始终分布在洼地旱地类型区;2005a和2014a土壤有机碳半变异函数的拟合模型相同,均为球状模型,在退耕还林还草10a后空间异质性增强,土壤有机碳的空间格局受土壤母质和植被结构的影响增强;而土壤全氮半变异函数的拟合模型不同,由指数模型变为球状模型,在退耕还林还草10a后空间异质性减弱,土壤全氮的空间格局受随机因素影响增强。研究结果对石漠化区域土地利用结构的优化调整具有重要的科学参考和实践指导意义。
Abstract:
The spatial patterns of soil organic carbon (SOC) and total nitrogen (TN) are the important components of the co-evolution mechanisms of vegetation and soil nutrient. However, the changes occurring in these spatial patterns during the process of vegetation restoration are poorly documented, especially in southwest China, a region suffering from severe land degradation. Based on soil sampling at the fixed points, we compared the spatial pattern changes of SOC and TN from 2005 (in initial stages of restoration) to 2014 in a typical small karst catchment undergoing rock desertification control for 10 years. The spatial pattern was analyzed using the grid sampling method (20m×20m space) with which we collected 528 and 504 samples in 2005 and 2014, respectively. The one-way analysis of variance (ANOVA) comparison showed that the average SOC values in 2014 (18.6g/kg) were significantly higher than those in 2005 (16.5g/kg), but the average TN values showed no significant change after 10 years. The cluster analysis suggested that the high-value clustering points of SOC and TN were changed from the dry land at the toe of slope and abandoned land in 2005 to abandoned land in 2014. Conversely, the low-value clustering points were always located on the dry land at the center of depression in the past decade. The estimation of the spatial pattern of the studied SOC and TN were performed by the geostatistical analyses using semivariograms to determine the average variance between the samples collected (semivariance) at increasing distances from one another. The results showed the semivariograms of SOC were both fitted to a spherical model between 2005 and 2014. However, the exponential model of TN turned into the spherical model following the vegetation restoration after 10 years. The sill and range values of the semivariogram functions for SOC were greater in 2014 than those in 2005, but shorter for TN. We found that the process of vegetation restoration could lead to an increase in the spatial heterogeneity and patches for SOC, but a decrease in the spatial heterogeneity and patches for TN. This indicated that the influence of parent material and the pattern of vegetation on SOC and random factors on TN were growing increasingly during vegetation restoration in the typical karst catchment. We conclude that afforestation increased both the SOC content and its spatial heterogeneity, but slightly changed the TN content and decreased its spatial heterogeneity after ecosystem restoration for 10 years in the karst areas of southwest China. Moreover, the native vegetation and the cultivated land transformed to native vegetation were the high-value clustering points at the study catchment during 2005–2014. In addition, the human disturbance intensity is an important factor controlling the low-value clustering points in the past decade. Our findings could provide the scientific basis for determining the optimal land use structure and sustainable restoration of ecosystem.
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