Impacts of agricultural intensity on soil organic carbon pools in a main vegetable cultivation region of China

被引:10
|
作者
Liu, Yang [1 ,2 ]
Yu, Dongsheng [1 ,2 ]
Wang, Ning [1 ]
Shi, Xuezheng [1 ,2 ]
Warner, Eric D. [3 ]
Zhang, Haidong [1 ,2 ]
Qin, Falv [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Penn State Univ, Off Remote Sensing & Spatial Informat Resources, University Pk, PA 16802 USA
来源
SOIL & TILLAGE RESEARCH | 2013年 / 134卷
关键词
Soil organic carbon; Vegetable cultivation; Intensive use of agricultural soil; Agricultural intensity index; LAND-USE CHANGE; NITROGEN; FERTILIZER; TILLAGE; STORAGE;
D O I
10.1016/j.still.2013.07.003
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Agricultural intensity, a function of agricultural input and output, impacts agricultural soil organic carbon (SOC) pools. Investigating the agricultural intensity and SOC density relationship supports understanding of anthropogenic activities on SOC pools in agricultural regions. Cangshan County, one of the most important vegetable cultivation counties in China, was selected as the study area for this investigation. By using soil survey data compiled in 1980 and 2008, 21 towns in Cangshan County were used as study units to investigate the relationship between agricultural intensity indicators and index, with SOC density. Results demonstrate that single agricultural intensity indicators could not reflect SOC densities changes well. Conversely the agricultural intensity index, a composite measure of agricultural input, output and input-output indicators (AI(1), AI(2) and AI(3), respectively), was a more reliable measure reflecting SOC density variability. An S-curve model, SOCd (t ha(-1)) = exp (alpha-beta/AI(i)), was the best fit for the plot of SOC densities with the agricultural intensity index. Relationships between AI(3) and SOC density were statistically significant for 1980, 2008 and their variation during 2008-1980 (p < 0.05), indicating that AI(3) had a more robust relationship with SOC density compared with AI(1) and AI(2). Though the relationships have low precision (R-2 = 0.24-0.40) for not including the natural factors and more indictors relative to variation of SOC density should be selected to improve the interpretability, it is still valuable to introduce the agricultural intensity index when detecting dynamics of SOC pools at a large regional scale. (C) 2013 Elsevier B.V. All rights reserved.
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页码:25 / 32
页数:8
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