Niu Shuli, Luo Yiqi, Fei Shenfeng, Yuan Wenping, Schimel David, Law Beverly E, Ammann Christof, Altaf Arain M, Arneth Almut, Aubinet Marc, Barr Alan, Beringer Jason, Bernhofer Christian, Andrew Black T, Buchmann Nina, Cescatti Alessandro, Chen Jiquan, Davis Kenneth J, Dellwik Ebba, Desai Ankur R, Etzold Sophia, Francois Louis, Gianelle Damiano, Gielen Bert, Goldstein Allen, Groenendijk Margriet, Gu Lianhong, Hanan Niall, Helfter Carole, Hirano Takashi, Hollinger David Y, Jones Mike B, Kiely Gerard, Kolb Thomas E, Kutsch Werner L, Lafleur Peter, Lawrence David M, Li Linghao, Lindroth Anders, Litvak Marcy, Loustau Denis, Lund Magnus, Marek Michal, Martin Timothy A, Matteucci Giorgio, Migliavacca Mirco, Montagnani Leonardo, Moors Eddy, William Munger J, Noormets Asko, Oechel Walter, Olejnik Janusz, U Kyaw Tha Paw, Pilegaard Kim, Rambal Serge, Raschi Antonio, Scott Russell L, Seufert Günther, Spano Donatella, Stoy Paul, Sutton Mark A, Varlagin Andrej, Vesala Timo, Weng Ensheng, Wohlfahrt Georg, Yang Bai, Zhang Zhongda, Zhou Xuhui
Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA.
Institute of Global Environmental Change Research, Fudan University, Shanghai, China.
New Phytol. 2012 May;194(3):775-783. doi: 10.1111/j.1469-8137.2012.04095.x. Epub 2012 Mar 7.
• It is well established that individual organisms can acclimate and adapt to temperature to optimize their functioning. However, thermal optimization of ecosystems, as an assemblage of organisms, has not been examined at broad spatial and temporal scales. • Here, we compiled data from 169 globally distributed sites of eddy covariance and quantified the temperature response functions of net ecosystem exchange (NEE), an ecosystem-level property, to determine whether NEE shows thermal optimality and to explore the underlying mechanisms. • We found that the temperature response of NEE followed a peak curve, with the optimum temperature (corresponding to the maximum magnitude of NEE) being positively correlated with annual mean temperature over years and across sites. Shifts of the optimum temperature of NEE were mostly a result of temperature acclimation of gross primary productivity (upward shift of optimum temperature) rather than changes in the temperature sensitivity of ecosystem respiration. • Ecosystem-level thermal optimality is a newly revealed ecosystem property, presumably reflecting associated evolutionary adaptation of organisms within ecosystems, and has the potential to significantly regulate ecosystem-climate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.
• 个体生物能够适应温度以优化其功能，这一点已得到充分证实。然而，作为生物集合体的生态系统的热优化，尚未在广泛的时空尺度上进行研究。
• 在这里，我们汇总了来自全球169个涡度协方差站点的数据，并量化了生态系统层面属性——净生态系统交换（NEE）的温度响应函数，以确定NEE是否表现出热最优性，并探索其潜在机制。
• 我们发现，NEE的温度响应呈峰值曲线，最优温度（对应于NEE的最大幅度）在多年间和不同站点上与年平均温度呈正相关。NEE最优温度的变化主要是总初级生产力温度适应（最优温度向上移动）的结果，而非生态系统呼吸温度敏感性变化的结果。
• 生态系统层面的热最优性是一种新揭示的生态系统属性，大概反映了生态系统内生物的相关进化适应，并且有可能显著调节生态系统 - 气候变化反馈。NEE的热最优性对于理解变化环境中生态系统的基本属性以及全球模型的基准测试具有重要意义。
