Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA.
Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China.
Glob Chang Biol. 2021 May;27(9):1942-1951. doi: 10.1111/gcb.15542. Epub 2021 Feb 20.
Vegetation productivity first increases and then decreases with temperature; and temperature corresponding to the maximum productivity is called optimal temperature (T ). In this study, we used satellite derived near-infrared reflectance of vegetation (NIR ) data to map T of vegetation productivity at the spatial resolution of 0.1° on the Tibetan Plateau (TP), one of most sensitive regions in the climate system. The average T of non-forest vegetation on the TP is about 14.7°C, significantly lower than the T value used in current ecosystem models. A remarkable geographical heterogeneity in T is observed over the TP. Higher T values generally appear in the north-eastern TP, while the south-western TP has relatively lower T (<10°C), in line with the difference of climate conditions and topography across different regions. Spatially, T tends to decrease by 0.41°C per 100 m increase in elevation, faster than the elevational elapse rate of growing season temperature, implying a potential CO regulation of T in addition to temperature acclimation. T increases by 0.66°C for each 1°C of rising mean annual temperature as a result of vegetation acclimation to climate change. However, at least at the decadal scale, there is no significant change in T between 2000s and 2010s, suggesting that the T climate acclimation may not keep up with the warming rate. Finally, future (2091-2100) warming could be close to and even surpass T on the TP under different RCP scenarios without considering potential climate acclimation. Our analyses imply that the temperature tipping point when the impact of future warming shifts from positive to negative on the TP is greatly overestimated by current vegetation models. Future research needs to include varying thermal and CO acclimation effects on T across different time scales in vegetation models.
植被生产力最初随温度升高而增加，然后随温度升高而降低；与最大生产力相对应的温度称为最适温度（T）。在本研究中，我们利用卫星获取的植被近红外反射率（NIR）数据，以 0.1°的空间分辨率绘制了青藏高原（TP）植被生产力的 T 图，青藏高原是气候系统中最敏感的地区之一。青藏高原非森林植被的平均 T 约为 14.7°C，明显低于当前生态系统模型中使用的 T 值。在整个青藏高原上，T 存在显著的地理异质性。T 值较高的地区一般出现在青藏高原的东北部，而西南部的 T 值相对较低（<10°C），这与不同地区的气候条件和地形差异相吻合。从空间上看，T 随海拔每升高 100 米而降低 0.41°C，比生长季温度的海拔递减率快，这表明除了温度驯化外，T 还可能受到 CO 的调节。由于植被对气候变化的适应，T 随平均年气温每升高 1°C而升高 0.66°C。然而，至少在十年的时间尺度上，2000 年代和 2010 年代之间 T 没有明显变化，这表明 T 的气候驯化可能跟不上变暖的速度。最后，在不同 RCP 情景下，未来（2091-2100 年）变暖可能接近甚至超过青藏高原的 T，而不考虑潜在的气候适应。我们的分析表明，当前植被模型对青藏高原未来变暖对植被生产力影响从正转负的温度转折点的估计过高。未来的研究需要在不同的时间尺度上考虑植被模型中 T 的热和 CO 驯化效应的变化。
