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作 者:段亚锋[1,2,3] 王克林 冯达[5] 吴敏[2,4] 张伟[2,4] 陈洪松[2,4] DUAN Yafeng1,2,4, WANG Kelin2,3 , FENG Da5, WU Min2,3, ZHANG Wei2,3 , CHEN Hongsong2,3(1 Hunan Agriculture University, Changsha 410125, China 2 Key Laboratory of Subtropical Agriculture Ecology, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China 3 Huanfiang Research and Observation Station for Karst Ecosystmes, Huanjiang 547100, China 4 Environmental Monitoring Stations of Changsha, Changsha 410000, China 5 The Surveying and Mapping Research Bureau, Changsha 410007, Chin)
机构地区:[1]湖南农业大学,长沙410125 [2]中国科学院亚热带农业生态研究所亚热带农业生态过程重点实验室,长沙410125 [3]长沙市环境监测中心站,长沙410000 [4]中国科学院环江喀斯特生态系统观测研究站,环江547100 [5]湖南省测绘科技研究所,长沙410007
出 处:《生态学报》2018年第5期1560-1568,共9页Acta Ecologica Sinica
基 金: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)
摘 要:基于定点回顾实验设计,通过对比分析2005年初(退耕还林还草初期)和2014年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;2005年和2014年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。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 spatia
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