Growing season average temperature range is the optimal choice for Q10 incubation experiments of SOM decomposition
文献类型：期刊论文
| 作者 | Pan, Jun1,2; He, Nianpeng3,4; Liu, Yuan3; Xu, Li3,4; Li, Mingxu3; Li, Chao5 |
| 刊名 | ECOLOGICAL INDICATORS
 |
| 出版日期 | 2022-12-01 |
| 卷号 | 145页码:7 |
| ISSN号 | 1470-160X |
| 关键词 | Soil organic matter Decomposition Temperature sensitivity Incubation Temperature range Warming |
| DOI | 10.1016/j.ecolind.2022.109749 |
| 通讯作者 | He, Nianpeng(henp@igsnrr.ac.cn) |
| 英文摘要 | Temperature sensitivity (Q(10)) of soil organic matter (SOM) decomposition is an essential parameter that reflects the feedback relationship between climate warming and atmospheric CO2 concentration and plays a key role in accurately estimating changes in soil carbon pools and their feedback to climate change. Setting the incubation temperature range (ITR) scenario is essential to accurately estimate the temperature sensitivity of SOM decomposition; however, this has been widely ignored. To address this issue, we conducted a systematic incubation experiment using 54 soils covering the most typical ecosystems in China and nine ITR scenarios. The results showed that ITR scenarios had a significant effect on Q(10) in different ecosystems and soil types. Combining the results of fitting mean annual temperature (MAT) to the Q(10) of different ITR and the interpretation rate of factors (including climate, soil, and microbial community composition) to the Q(10) of different ITR, the results indicate that the growing season average temperature range (GSA) scenario had better performance than the other ITR scenarios and should be the optimum ITR scenario. Furthermore, the variation of main influence factors of Q(10) across different ecosystems should be accounted for to accurately predict the feedback between soil C cycle and climate change. Overall, our findings highlight the importance of the ITR for the estimates of Q(10) using widespread experimental data, providing a reference for subsequent experiments accurately measure Q(10), as well as compare and compile global data to better predict the feedback between the global carbon cycle and climate change. |
| WOS关键词 | ORGANIC-MATTER DECOMPOSITION ; SOIL RESPIRATION ; SENSITIVITY ; FORESTS ; ECOSYSTEM ; MINERALIZATION ; GRASSLAND ; INVASIONS ; PATTERNS ; GRADIENT |
| 资助项目 | National Natural Science Foundation of China ; CAS Project for Young Scientists in Basic Research ; National Science and Technology Basic Resources Survey Program of China ; [32171544] ; [42141004] ; [31988102] ; [YSBR-037] ; [2019FY101300] |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:000910854300003 |
| 资助机构 | National Natural Science Foundation of China ; CAS Project for Young Scientists in Basic Research ; National Science and Technology Basic Resources Survey Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/189305]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | He, Nianpeng |
| 作者单位 | 1.Beijing Forestry Univ, Sch Ecol & Nat Conservat, Beijing 100083, Peoples R China 2.Beijing Forestry Univ, Inst Forestry & Climate Change Res, Beijing 100083, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 5.Minzu Univ China, Coll Life & Environm Sci, Beijing 100081, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pan, Jun,He, Nianpeng,Liu, Yuan,et al. Growing season average temperature range is the optimal choice for Q10 incubation experiments of SOM decomposition[J]. ECOLOGICAL INDICATORS,2022,145:7. |
| APA | Pan, Jun,He, Nianpeng,Liu, Yuan,Xu, Li,Li, Mingxu,&Li, Chao.(2022).Growing season average temperature range is the optimal choice for Q10 incubation experiments of SOM decomposition.ECOLOGICAL INDICATORS,145,7. |
| MLA | Pan, Jun,et al."Growing season average temperature range is the optimal choice for Q10 incubation experiments of SOM decomposition".ECOLOGICAL INDICATORS 145(2022):7. |
入库方式： OAI收割
来源：地理科学与资源研究所
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