Vegetation phenology in the Northern Hemisphere based on the solar-induced chlorophyll fluorescence

doi:10.17521/cjpe.2020.0376

Abstract

Abstract:

Aims Vegetation phenology is an important indicator to reflect the stages of vegetation growth, which is of great significance to the feedback to climate. Solar-induced chlorophyll fluorescence (SIF) is a by-product of photosynthesis, which provides the possibility to directly detect vegetation phenology at the global scale. In order to reveal the accuracy of phenology estimated by SIF of different forest types, we estimated phenology of three forest types in the Northern Hemisphere.

Methods Based on 35 eddy flux tower sites in the Northern Hemisphere during the period of 2007-2014, we estimated phenology of three typical forest types using SIF value and gross primary production (GPP) by double logistic growth model and dynamic threshold. Correlation analysis was used to evaluate the different potential of SIF in estimating phenology of different forest types.

Important findings Results showed that: 1) SIF was more suitable to estimate the timing of the start of growing season (SOS) than the timing of the end of growing season (EOS). 2) SOS based on SIF had the highest correlation with SOS based on GPP in mixed forests (MF). However, the SOS of deciduous broadleaf forest (DBF) and evergreen needleleaf forest (ENF) could not be accurately tracked by SIF value. 3) The preseason shortwave radiation (SR) was the primarily environmental factor of SOS.

Key words: vegetation phenology, northern forest, solar-induced chlorophyll fluorescence, climate change, shortwave radiation

ZHOU Wen, CHI Yong-Gang, ZHOU Lei. Vegetation phenology in the Northern Hemisphere based on the solar-induced chlorophyll fluorescence[J]. Chin J Plant Ecol, 2021, 45(4): 345-354.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2020.0376

https://www.plant-ecology.com/EN/Y2021/V45/I4/345

Figures/Tables 7

Fig. 1 Comparison between time series curves of solar-induced chlorophyll fluorescence (SIF) before and after the quality control.

Fig. 2 An example for determining the phenology based on daily solar-induced chlorophyll fluorescence (SIF) time series using double logistic growth model. Timing of the start of the growing season (SOS) and the end of the growing season (EOS) were plotted by green circle and orange circle. DOY, day of year.

Fig. 3 Seasonal trajectories of normalized solar-induced chlorophyll fluorescence (SIF) value and gross primary production (GPP). DBF, deciduous broadleaf forest; ENF, evergreen needleleaf forest; MF, mixed forests. DOY, day of year.

Fig. 4 Correlations between solar-induced chlorophyll fluorescence (SIF) value and gross primary production (GPP). DBF, deciduous broadleaf forest; ENF, evergreen needleleaf forest; MF, mixed forests.

Fig. 5 Scatterplots describing the relationship between timing of the start of growing season (SOS) and timing of the end of growing season (EOS) derived from solar-induced chlorophyll fluorescence (SIF) value and gross primary production (GPP). DOY, day of year; N, the years of all sites. DBF, deciduous broadleaf forest; ENF, evergreen needleleaf forest; MF, mixed forests.

Fig. 6 Distributions of timing of the start of the growing season (SOS) and timing of the end of the growing season (EOS) derived from solar-induced chlorophyll fluorescence (SIF) value and gross primary production (GPP). DBF, deciduous broadleaf forest; ENF, evergreen needleleaf forest; MF, mixed forests. DOY, day of year.

Fig. 7 Correlation coefficient (r) of environmental factors (shortwave radiation, air temperature, precipitation) in preseason and timing of the start of the growing season (SOS). **, p< 0.05. DBF, deciduous broadleaf forest; ENF, evergreen needleleaf forest; MF, mixed forests. The Y-axis represents the forest site name in FLUXNET.

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