A temperature threshold to identify the driving climate forces of the respiratory process in terrestrial ecosystems

作者:Zhang, Zhiyuan; Zhang, Renduo*; Zhou, Yang; Cescatti, Alessandro; Wohlfahrt, Georg; Sun, Minmin; Zhang, Huanyuan; Qi, Jiaxin; Zhu, Juan; Magliulo, Vincenzo; Tao, Feng; Chen, Guanhong
来源:European Journal of Soil Biology, 2018, 89: 1-8.
DOI:10.1016/j.ejsobi.2018.08.001

摘要

Terrestrial ecosystem respiration (R-e) is the second largest carbon flux between the biosphere and atmosphere. Therefore, climate-driven changes of R-e greatly impact on future atmospheric CO2 concentration. The aim of this study was to derive an air temperature threshold to identify the driving climate forces of the respiratory process in terrestrial ecosystems within different temperature zones. A global dataset of 647 site-years of ecosystem flux data and related variables were collected at 152 sites. The quantile regression was applied to evaluate relationships between the maximum realizable R-e rates and mean annual air temperature (MAT) as well as other micrometeorological factors (i.e., atmospheric CO2 concentration, atmospheric water content, soil heat flux, sensible heat flux, latent heat flux, precipitation, relative humidity, and soil water content). Our analysis revealed an ecosystem threshold of MAT of 11 +/- 2.3 degrees C. In ecosystems with MATs lower than the threshold, the maximum R-e rates were primarily dependent on temperature and respiration was mainly a temperature-driven process. In ecosystems with MATs higher than the threshold, besides MAT, other factors, such as water availability and surface heat flux, became significant driving forces of the maximum R-e rates and respiration was a multi-factor-driven process. Temperature played the key role in generation of the maximum R-e rates in the terrestrial ecosystems, while other driving forces reduce the maximum R-e rates and the temperature sensitivity of the respiratory process. According to a regression tree analysis, MAT was also the most influencing factor of mean R-e rates among the climate forces. The information from this study should be useful to predict the respiratory process in terrestrial ecosystems with different temperatures under the climate change.