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Nonlinear response of ecosystem respiration to gradient warming in paddy field in Northeast China
Agricultural and Forest Meteorology ( IF 6.2 ) Pub Date : 2021-11-19 , DOI: 10.1016/j.agrformet.2021.108721
Xiaowen Song 1 , Qian Chen 1 , Kexin Wang 1 , Xianjin Zhu 1 , Tao Zhang 1 , Bei Sun 1 , Guojiao Wang 1 , Hong Yin 1 , Xiaoxue Wang 2 , Shaojie Guo 1
Affiliation  

Ecosystem respiration (ER) is greatly affected by global warming and responds nonlinearly to different warming levels. However, the mechanisms of the response of ER to gradient warming in paddy field remain obscure. Studying the effects and mechanisms of different warming levels on ER and its components in paddy field ecosystems will provide a theoretical basis for predicting future carbon budgets under climate change scenarios. In this study, 2-year gradient warming experiments with 5 warming treatments (+0 °C [control, CK], +0.3 °C [500 W warming, T1], +0.6 °C [1000 W warming, T2], +1.0 °C [1500 W warming, T3], +2.3 °C [3000 W warming, T4]) were performed by using a free air temperature increasing (FATI) system in paddy field in Northeast China. ER and its two components, autotrophic respiration (AR) and heterotrophic respiration (HR), were measured to reveal the mechanisms of the response of ER to gradient warming. The results showed that ER, AR and HR increased significantly under warming treatments and exhibited nonlinear responses to different warming levels. The maximum increases in ER, AR and HR appeared in the 1500 W warming treatment. The nonlinear response of AR was primarily related to total plant biomass (TB), while the nonlinear response of HR was closely related to soil microbial biomass carbon (MBC). Furthermore, warming nonlinearly enhanced the AR/ER ratios but reduced the HR/ER ratios. The AR/ER ratios were much greater than the HR/ER ratios. ER was closely correlated with its two components, and its nonlinear response might mainly derive from that of AR. The results highlight that the nonlinear response patterns of ER and its components to warming should be taken into global carbon cycling models to predict future carbon-climate feedbacks.

更新日期:2021-11-20
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