中国森林生态系统土壤呼吸温度敏感性空间变异特征及影响因素
收稿日期: 2019-11-04
录用日期: 2020-02-02
网络出版日期: 2020-03-26
基金资助
国家自然科学基金(31670708);国家自然科学基金(31670710);国家自然科学基金(31901366);中央高校基本科研业务费专项资金(2015ZCQ-SB-02)
Spatial variation and controlling factors of temperature sensitivity of soil respiration in forest ecosystems across China
Received date: 2019-11-04
Accepted date: 2020-02-02
Online published: 2020-03-26
Supported by
National Natural Science Foundation of China(31670708);National Natural Science Foundation of China(31670710);National Natural Science Foundation of China(31901366);Fundamental Research Funds for the Central Universities(2015ZCQ-SB-02)
土壤呼吸的温度敏感性(Q10)是陆地碳循环与气候系统间相互作用的关键参数。尽管已有大量关于不同类型森林Q10季节和年际变化规律的研究, 但是对Q10在区域尺度的空间变异特征及其影响因素仍认识不足, 已有结果缺乏一致结论。该研究通过整合已发表论文, 构建了中国森林生态系统年尺度Q10数据集, 共包含399条记录、5种森林类型(落叶阔叶林(DBF)、落叶针叶林(DNF)、常绿阔叶林(EBF)、常绿针叶林(ENF)、混交林(MF))。分析了不同森林类型Q10的空间变异特征及其与地理、气候和土壤因素的关系。结果显示, 1) Q10介于1.09到6.24之间, 平均值(±标准误差)为2.37 (± 0.04), 且在不同森林类型之间无显著差异; 2)当考虑所有森林类型时, Q10随纬度、海拔、土壤有机碳含量(SOC)和土壤全氮含量(TN)的增加而增大, 随经度、年平均气温(MAT)、平均年降水量(MAP)的增加而减小。气候(MAT、MAP)和土壤(SOC、TN)因素间存在相互作用, 共同解释了33%的Q10空间变异, 其中MAT和SOC是Q10空间变异的主要驱动因素; 3)不同类型森林Q10对气候和土壤因素的响应存在差异。在DNF中Q10随MAP的增加而减小, 而其他类型森林中Q10与MAP无显著相关性; 在EBF、DBF、ENF中Q10随TN的增加而增大, 但Q10对TN的敏感性在EBF中最高, 在ENF中最低。这些结果表明, 尽管Q10有一定的集中分布趋势, 但仍有较大范围的空间变异, 在进行碳收支估算时应注意尺度问题。Q10的主要驱动因素和Q10对环境因素的响应随森林类型而变化, 在气候变化情景下, 不同森林类型间Q10可能发生分异。因此, 未来的碳循环-气候模型还应考虑不同类型森林碳循环关键参数对气候变化的响应差异。
郑甲佳, 黄松宇, 贾昕, 田赟, 牟钰, 刘鹏, 查天山 . 中国森林生态系统土壤呼吸温度敏感性空间变异特征及影响因素[J]. 植物生态学报, 2020 , 44(6) : 687 -698 . DOI: 10.17521/cjpe.2019.0300
Aims Our objective was to determine the spatial variation of the temperature sensitivity of soil respiration (Q10) and it’s controlling factors in forest ecosystems across China.
Methods Based on published papers, the field measurement data of soil respiration were collected to build the dataset of annual Q10 in forest ecosystems across China. Further, the spatial variation and the drivers of Q10 in different forest types were analyzed.
Important findings The results showed that 1) Q10 ranges from 1.09 to 6.24, with a mean value (± standard error) of 2.37 (± 0.04) and no significant difference among different forest types; 2) When all forest types were considered, Q10 increased with increasing latitude, altitude, soil organic carbon content (SOC) and soil total nitrogen content (TN), but decreased with increasing longitude, mean annual temperature (MAT) and mean annual precipitation (MAP). Climate (MAT, MAP) and soil (SOC, TN) factors together explained 32.8% variations in Q10. MAT and SOC were considered as the primary factors driving the spatial variation of Q10. 3) Q10 of different forest types responded differently to climate and soil factors. Q10 decreased with the increase of MAP in the deciduous needleleaf forest (DNF), while Q10 showed no significant correlation with MAP in other forest types. Q10 increased with the increase of TN in evergreen broadleaved forest (EBF), deciduous broadleaved forest (DBF), evergreen needleleaf forest (ENF), and the sensitivity of Q10 to TN was the highest in EBF and the lowest in ENF. Although Q10 showed concentrated distribution trend, more attention should be paid to the large range of variation in future C budget studies. The primary driving factors and the response to environmental factors of Q10 varied among forest types. Under the scenario of future climate change, Q10 may vary divergently among different forest types. Therefore, the divergent responses of key parameters of carbon cycle in different forest types to climate change should also be considered in future carbon-climate models.
Key words： soil respiration; temperature sensitivity; carbon cycle; CO2 flux; soil carbon flux
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