Nonlinear response of ecosystem respiration to multiple levels of temperature increases

Abstract

Global warming exerts profound impacts on terrestrial carbon cycles and feedback to climates. Ecosystem respiration (ER) is one of the main components of biosphere CO2 fluxes. However, knowledge regarding how ER responds to warming is still lacking. In this study, a manipulative experiment with five simulated temperature increases (+0℃ [Control], +2.1℃ [warming 1, W1], +2.7℃ [warming 2, W2], +3.2℃ [warming 3, W3], +3.9℃ [warming 4, W4]) was conducted to investigate ER responses to warming in an alpine meadow on the Tibetan Plateau. The results showed that ER was suppressed by warming both in dry and wet years. The responses of ER to warming all followed a nonlinear pattern. The nonlinear processes can be divided into three stages, the quick‐response stage (W1), stable stage (W1–W3), and transition stage (W4). Compared with the nonlinear model, the linear model maximally overestimated the response ratios of ER to warming 2.2% and 3.2% in 2015 and 2016, respectively, and maximally underestimated the ratio 7.0% and 2.7%. The annual differences in ER responding to warming were mainly attributed to the distinct seasonal distribution of precipitation. Specially, we found that the abrupt shift response of ER to warming under W4 treatment in 2015, which might be regulated by the excitatory effect of precipitation after long‐term drought in the mid‐growing season. This study highlights the importance of the nonlinearity of warming effects on ER, which should be taken into the global‐C‐cycling models for better predicting future carbon–climate feedbacks.

Multiple‐scale negative impacts of warming on ecosystem carbon use efficiency across the Tibetan Plateau grasslands

“…It is worth noting that the CUEe declines by a greater magnitude under HW than under LW. A strongly attenuated net carbon sink under HW has been reported for alpine meadow ecosystems (N. Chen, Zhu, et al., 2019; Ganjurjav et al., 2016; N. Li et al., 2011). This implies that increased warming in the future would greatly decrease the CUEe, leading to a weaker carbon sequestration capacity of alpine grassland ecosystems.…”

“…Increased soil respiration (SR) induced by precipitation pulses is inversely related to the preprecipitation SM (Y. Liu, Zhao, et al., 2019). Our previous study found that due to severe declines in SM induced by drought and warming, increases in ER under HW induced by precipitation pulses were stronger than in other treatments during the seasonal drought of 2015 (N. Chen, Zhu, et al., 2019). Though not as severe as the drought in 2015, other growing seasons also experienced a brief seasonal drought, and the ‘Birch’ effect may partly contribute to increases in ER under HW.…”

“…For example, stronger negative effects of warming on GEP than on ER would decrease CUEe (N. Chen, Zhang, et al., 2019). More importantly, numerous studies have documented the nonlinear responses of GEP and ER to warming, and their sensitivities varied significantly under multiple‐level warming (N. Chen, Zhu, et al., 2019; Quan et al., 2019). This may lead to the nonlinear responses of the CUEe to warming.…”

Carbon Balance of Grasslands on the Qinghai-Tibet Plateau under Future Climate Change: A Review

“…However, the effect on carbon emissions is more pronounced when water content is lower, and studies showed that plants were less affected by water as they grow when the soil water content exceeds 22% [61]. Moreover, when the soil water content is greater than 18.13%, the higher the soil water content, the lower the ecosystem respiration intensity [81]. Therefore, when the water in the ecosystem exceeds a certain threshold, the dominant factor of carbon emission may change.…”

Linking global terrestrial CO<sub>2</sub> fluxes and environmental drivers: inferences from the Orbiting Carbon Observatory 2 satellite and terrestrial biospheric models

“…Recent advances in OCO-2 retrievals from the NASA ACOS science team have led to widespread reductions in observation errors (e.g., O'Dell et al, 2018). Reducing the errors in satellite observations of CO 2 is critical for understanding CO 2 sources and sinks using inverse modeling, as even small biases in the observations can have an impact on the CO 2 flux estimate (e.g., Chevallier et al, 2007Chevallier et al, , 2014Feng et al, 2016;Miller et al, 2018). For example, Miller et al (2018) evaluated the extent to which OCO-2 retrievals can detect patterns in biospheric CO 2 fluxes and found that an early version of the OCO-2 retrievals (version 7) is only equipped to provide accurate flux constraints across very large continental or hemispheric regions; by contrast, in a follow-up paper, Miller and Michalak (2020) revisited satellite capabilities in light of recently improved OCO-2 retrievals, and the authors argued that new OCO-2 retrievals can be used to constrain CO 2 fluxes for more detailed regions (i.e., for seven global biomes).…”