Improving estimations of ecosystem respiration with asymmetric daytime and nighttime temperature sensitivity and relative humidity

Abstract

Accurately quantifying ecosystem respiration (ER) is crucial for understanding the feedback between the terrestrial carbon (C) cycle and climate change. However, the current estimation of ER by partitioning net ecosystem exchange (NEE) meets a great challenge due to the response difference of daytime and nighttime respiration to temperature and the effects of air humidity. In this study, we modified daytime flux partitioning methods to estimate ER by integrating the different daytime and nighttime temperature sensitivities of ER (E0, day and E0, night, referred to as DT-E0) and then relative humidity (DT-RH) based on eddy covariance and isotopic data at three sites. Our results showed that diurnal and seasonal patterns of daytime ER derived from DT-E0 and DT-RH agreed well with isotopic data, but were considerably different from previous widely used methods (e.g., nighttime (NT) and daytime (DT) methods). The daily mean ER with DT-E0 was 6%∼18% less than those with NT and DT, suggesting that the difference between E0, night and E0, day greatly affects ER estimates. By adding RH, the difference in mean ER estimated by DT-RH and DT-E0 was largest in the dry period at CN-Qia, suggesting that the change in RH at dawn and dusk may significantly influence ER and E0 in the water-limited season. In addition, the magnitude of inhibition by light in the daytime ER from DT was less than that from DT-RH, especially in forest ecosystems, indicating the previous underestimation of light inhibition for ER. Our study highlights the crucial importance of diurnal variations in E0 and RH in accurately estimating ER, which may need to be incorporated into regional and global models to improve the assessment of global C budgets.