TY - JOUR
T1 - Impacts of agricultural intensity on soil organic carbon pools in a main vegetable cultivation region of China
AU - Liu, Yang
AU - Yu, Dongsheng
AU - Wang, Ning
AU - Shi, Xuezheng
AU - Warner, Eric D.
AU - Zhang, Haidong
AU - Qin, Falv
N1 - Funding Information:
This study was supported by the 973 project (2010CB950702), the “Strategic Priority Research Program – Climate Change: Carbon Budget and Related Issues” of the Chinese Academy of Sciences , Grant No. ( XDA05050507 ), and the Knowledge Innovation Program of Chinese Academy of Sciences ( KZCX2-YW-Q1-07 ).
PY - 2013
Y1 - 2013
N2 - 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 (AI1, AI2 and AI3, respectively), was a more reliable measure reflecting SOC density variability. An S-curve model, SOCd (tha-1)=exp (α-β/AIi), was the best fit for the plot of SOC densities with the agricultural intensity index. Relationships between AI3 and SOC density were statistically significant for 1980, 2008 and their variation during 2008-1980 (p<0.05), indicating that AI3 had a more robust relationship with SOC density compared with AI1 and AI2. Though the relationships have low precision (R2=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.
AB - 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 (AI1, AI2 and AI3, respectively), was a more reliable measure reflecting SOC density variability. An S-curve model, SOCd (tha-1)=exp (α-β/AIi), was the best fit for the plot of SOC densities with the agricultural intensity index. Relationships between AI3 and SOC density were statistically significant for 1980, 2008 and their variation during 2008-1980 (p<0.05), indicating that AI3 had a more robust relationship with SOC density compared with AI1 and AI2. Though the relationships have low precision (R2=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.
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U2 - 10.1016/j.still.2013.07.003
DO - 10.1016/j.still.2013.07.003
M3 - Article
AN - SCOPUS:84881250184
SN - 0167-1987
VL - 134
SP - 25
EP - 32
JO - Soil and Tillage Research
JF - Soil and Tillage Research
ER -