Meta-analyses of the effects of major global change drivers on soil respiration across China

环境科学 降水 生态系统 全球变暖 全球变化 气候变化 酸雨 陆地生态系统 生物群落 土壤呼吸 中国 碳循环 草原 大气科学 生态学 土壤水分 地理 生物 土壤科学 气象学 考古 地质学
作者
Jiguang Feng,Jingsheng Wang,Ding Lubin,Pingping Yao,Mengping Qiao,Yao Shuaichen
出处
期刊:Atmospheric Environment [Elsevier BV]
卷期号:150: 181-186 被引量:45
标识
DOI:10.1016/j.atmosenv.2016.11.060
摘要

Soil respiration (Rs) is affected largely by major global change drivers, global meta-analysis studies have synthesized the available information to determine how Rs responds to these drivers. However, little is known about the effects of these drivers on Rs across China. Here, we conducted a meta-analysis to synthesize 80 studies published in the literature with 301 paired comparisons to quantify the responses of Rs to simulated warming, nitrogen addition, precipitation increase and acid rain across Chinese terrestrial ecosystem. Results showed that global change drivers significantly changed Rs across Chinese ecosystems. Warming, nitrogen addition, and precipitation increase significantly increased Rs by 9.08%, 5.21%, 31.68%, respectively, while simulated acid rain decreased Rs by 7.06%. The responses of Rs to warming, nitrogen addition, and precipitation increase are similar in both direction and magnitude to those reported in global syntheses, except for higher response ratio under precipitation increase in China. In addition, the responses of Rs were different among ecosystem types, and among experimental treatments. Warming significantly increased Rs in croplands but did not change in forests and grasslands. The effect magnitude of N addition on Rs in grasslands and croplands was much higher than those in other ecosystems. In general, precipitation increase stimulated Rs in different ecosystems, and its effect magnitudes increased with changed precipitation levels. However, acid rain inhibited Rs in different biomes and intensities of acid rain. Our findings contribute to better understanding of how Rs will change under global change, and provide important parameters for carbon cycle model at the regional scale.
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