Preprints
https://doi.org/10.5194/essd-2021-452
https://doi.org/10.5194/essd-2021-452
 
31 Mar 2022
31 Mar 2022
Status: a revised version of this preprint is currently under review for the journal ESSD.

Vegetation photosynthetic phenology metrics in northern terrestrial ecosystems: a dataset derived from a gross primary productivity product based on solar-induced chlorophyll fluorescence

Jing Fang1,2, Xing Li3, Jingfeng Xiao4, Xiaodong Yan5, Bolun Li3, and Feng Liu1,2 Jing Fang et al.
  • 1CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China
  • 2Center of Plant Ecology, Core Botanical Gardens, Chinese Academy of Sciences, Wuhan, 430074, China
  • 3Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
  • 4Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
  • 5State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Abstract. Vegetation phenology can profoundly modulate the climate-biosphere interactions and thus plays a key role in regulating the terrestrial carbon cycle and the climate. However, most previous phenology studies are based on the traditional vegetation indices, which are inadequate to characterize the seasonal activity of photosynthesis. Here, we generated an annual vegetation photosynthetic phenology dataset with a spatial resolution of 0.05 degree from 2001 to 2020, using the latest gross primary productivity product based on solar-induced chlorophyll fluorescence (GOSIF-GPP). We combined smoothing splines with multiple change-point detection to retrieve the phenology metrics: start of the growing season (SOS), end of the growing season (EOS), and length of growing season (LOS) for terrestrial ecosystems in the Northern Hemisphere. We found that the derived phenology metrics agreed better with in situ observations from the flux tower sites than vegetation indices and MODIS-GPP. Our phenology metrics captured the spatial-temporal patterns of the single and double growing season in the Northern Hemisphere. The double season was mainly from the cropland rotation and ecosystems having two different phenological cycles. In addition, we observed a trend toward advanced SOS in about 62.98 % of the land area, with a mean rate of 0.14 ± 0.01 days year-1, a trend toward delayed EOS in about 61.87 % of the area, with a mean rate of 0.19 ± 0.16 days year-1, and a trend toward extended LOS in about 70.52 % of the area, with a mean rate of 0.33 ± 0.17 days year-1. Our phenology product can be used for validating and developing phenology models or carbon cycle models, for evaluating satellite remote sensing phenology, and for monitoring climate change impacts on terrestrial ecosystems. The data are available at https://doi.org/10.6084/m9.figshare.17195009.v2 (Fang et al. 2021).

Jing Fang et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-452', Anonymous Referee #1, 10 May 2022
    • AC1: 'Reply on RC1', Jing Fang, 06 Jul 2022
  • RC2: 'Comment on essd-2021-452', Anonymous Referee #2, 20 Jun 2022
    • RC3: 'Reply on RC2', Anonymous Referee #2, 20 Jun 2022
    • AC2: 'Reply on RC2', Jing Fang, 06 Jul 2022

Jing Fang et al.

Data sets

Vegetation photosynthetic phenology metrics in northern terrestrial ecosystems: a dataset derived from a gross primary productivity product based on solar-induced chlorophyll fluorescence Jing Fang, Xing Li, Jingfeng Xiao, Xiaodong Yan, Bolun Li, Feng Liu https://doi.org/10.6084/m9.figshare.17195009.v2

Jing Fang et al.

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Short summary
The dataset provided the vegetation photosynthetic phenology instead of traditional phenology to represent plant seasonal activities. This dataset had the latest period (2001–2020) and a fine spatial resolution (0.05 degree). Our phenology metrics revealed the spatial-temporal patterns of the multiple growing seasons in the Northern Hemisphere. The dataset will facilitate various research such as developing models, evaluating phenology shifts, and monitoring climate change worldwide.