Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

Peixin Ren; Zelin Liu; Xiaolu Zhou; Changhui Peng; Jingfeng Xiao; Songhan Wang; Xing Li; Peng Li

doi:10.1186/s40663-021-00309-9

Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

For Ecosyst. 2021;8(1):31. doi: 10.1186/s40663-021-00309-9. Epub 2021 May 19.

Authors

Peixin Ren¹, Zelin Liu¹, Xiaolu Zhou¹, Changhui Peng^{1

2}, Jingfeng Xiao³, Songhan Wang^{4

5}, Xing Li³, Peng Li¹

Affiliations

¹ College of Geographic Science, Hunan Normal University, Changsha, 410081 China.
² Department of Biology Sciences, Institute of Environment Sciences, University of Quebec at Montreal, C.P. 8888, Succ. Centre-Ville, Montreal, H3C 3P8 Canada.
³ Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824 USA.
⁴ International Institute for Earth System Sciences, Nanjing University, Nanjing, 210023 China.
⁵ Jiangsu Provincial Key Laboratory of Geographic Information Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, 210023 China.

Abstract

Background: Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions.

Results: Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGS_sif and EGS_evi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland.

Conclusions: Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

Supplementary information: The online version contains supplementary material available at 10.1186/s40663-021-00309-9.

Keywords: Carbon cycle; Climate change; Eddy covariance; Evergreen vegetation; MODIS; Plant phenology; Solar-induced Fluorescence.

Publication types

Research Support, Non-U.S. Gov't