>> Urban−rural gradients reveal joint control of elevated CO2 and temperature on extended photosynthetic seasons
题名：Urban−rural gradients reveal joint control of elevated CO2 and temperature on extended photosynthetic seasons
来源：Nature Ecology and Evolution
发表年代：2019年
作者：Songhan Wang, Weimin Ju, Josep Peñuelas , Alessandro Cescatti, Yuyu Zhou, Yongshuo Fu , Alfredo Huete, Min Liu, Yongguang Zhang*
Abstract Photosynthetic phenology has large effects on the land–atmosphere carbon exchange. Due to limited experimental assessments, a comprehensive understanding of the variations of photosynthetic phenology under future climate and its associated controlling factors is still missing, despite its high sensitivities to climate. Here, we develop an approach that uses cities as natural laboratories, since plants in urban areas are often exposed to higher temperatures and carbon dioxide (CO2) concentrations, which reflect expected future environmental conditions. Using more than 880 urban–rural gradients across the Northern Hemisphere (≥30° N), combined with concurrent satellite retrievals of Sun-induced chlorophyll fluorescence (SIF) and atmospheric CO2, we investigated the combined impacts of elevated CO2 and temperature on photosynthetic phenology at the large scale. The results showed that, under urban conditions of elevated CO2 and temperature, vegetation photosynthetic activity began earlier (−5.6 ± 0.7 d), peaked earlier (−4.9 ± 0.9 d) and ended later (4.6 ± 0.8 d) than in neighbouring rural areas, with a striking two- to fourfold higher climate sensitivity than greenness phenology. The earlier start and peak of season were sensitive to both the enhancements of CO2 and temperature, whereas the delayed end of season was mainly attributed to CO2 enrichments. We used these sensitivities to project phenology shifts under four Representative Concentration Pathway climate scenarios, predicting that vegetation will have prolonged photosynthetic seasons in the coming two decades. This observationdriven study indicates that realistic urban environments, together with SIF observations, provide a promising method for studying vegetation physiology under future climate change.
