Quantification of soil respiration in forest ecosystems across China
Quantification of soil respiration in forest ecosystems across China
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中国森林生态系统土壤呼吸量化
DOI：
10.1016/j.atmosenv.2014.05.071
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发表时间：
2014-09
影响因子：
5
通讯作者：
Baohua Guo
中科院分区：
文献类型：
--
作者：
Changhui Peng;Zhengyong Zhao;Zhiting Zhang;Baohua Guo
我们收集了139个年度森林土壤co2通量估计值和173个q10值（温度敏感性）估计值，这些估计值来自于中国森林生态系统的90项已发表的研究。分析了常绿阔叶林（EBF）、落叶阔叶林（DBF）、阔叶针叶混交林（BNMF）、常绿针叶林（ENF）、落叶针叶林（DNF）、竹林（BF）和灌木（SF） 7种森林生态系统的年土壤呼吸速率和温度敏感性。结果表明，中国森林生态系统年平均Rs速率为33.65 t CO2ha−1year−1。Rs率在7种林型间存在显著差异（P< 0.001），并受到年平均气温（MAT）、年平均降水量（MAP）和实际蒸散（AET）的显著正影响；但受纬度和海拔的负面影响。平均q10值为1.28，低于世界平均水平（1.4-2.0）。5 cm深度土壤温度的q10值在不同森林生态系统间的平均差异为2.46，随海拔高度和纬度的变化而显著降低，随海拔高度和纬度的变化而增加。人工神经网络（ANN）模型可以有效地预测中国森林生态系统的Rs。该研究有助于更好地了解中国森林生态系统的Rs及其对全球变暖的可能响应。
We collected 139 estimates of the annual forest soil CO2flux and 173 estimates of theQ10value (the temperature sensitivity) assembled from 90 published studies across Chinese forest ecosystems. We analyzed the annual soil respiration (Rs) rates and the temperature sensitivities of seven forest ecosystems, including evergreen broadleaf forests (EBF), deciduous broadleaf forests (DBF), broadleaf and needleleaf mixed forests (BNMF), evergreen needleleaf forests (ENF), deciduous needleleaf forests (DNF), bamboo forests (BF) and shrubs (SF). The results showed that the mean annual Rs rate was 33.65 t CO2ha−1year−1across Chinese forest ecosystems. Rs rates were significantly different (P< 0.001) among the seven forest types, and were significantly and positively influenced by mean annual temperature (MAT), mean annual precipitation (MAP), and actual evapotranspiration (AET); but negatively affected by latitude and elevation. The meanQ10value of 1.28 was lower than the world average (1.4–2.0). TheQ10values derived from the soil temperature at a depth of 5 cm varied among forest ecosystems by an average of 2.46 and significantly decreased with the MAT but increased with elevation and latitude. Moreover, our results suggested that an artificial neural network (ANN) model can effectively predict Rs across Chinese forest ecosystems. This study contributes to better understanding of Rs across Chinese forest ecosystems and their possible responses to global warming.
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影响因子：
6.2
作者：
Chen, Shutao;Huang, Yao;Pan, Genxing
通讯作者：
Pan, Genxing
DOI：
10.5860/choice.27-1569
发表时间：
1989-04
期刊：
--
影响因子：
--
作者：
P. D. Wasserman
通讯作者：
P. D. Wasserman
影响因子：
4
作者：
Schlesinger, WH;Andrews, JA
通讯作者：
Andrews, JA
影响因子：
0.7
作者：
L. Zuo
通讯作者：
L. Zuo
影响因子：
3.1
作者：
E. Levine;D. Kimes;V. Sigillito
通讯作者：
E. Levine;D. Kimes;V. Sigillito