Warming increases the differences among spring phenology models under future climate change

Yunhua Mo; Xiran Li; Yahui Guo; Yongshuo Fu

doi:10.3389/fpls.2023.1266801

Warming increases the differences among spring phenology models under future climate change

Front Plant Sci. 2023 Oct 23:14:1266801. doi: 10.3389/fpls.2023.1266801. eCollection 2023.

Authors

Yunhua Mo¹, Xiran Li², Yahui Guo², Yongshuo Fu¹

Affiliations

¹ College of Water Sciences, Beijing Normal University, Beijing, China.
² College of Urban and Environmental Sciences, Central China Normal University, Wuhan, China.

Abstract

Phenological models are built upon an understanding of the influence of environmental factors on plant phenology, and serve as effective tools for predicting plant phenological changes. However, the differences in phenological model predictive performance under different climate change scenarios have been rarely studied. In this study, we parameterized thirteen spring phenology models, including six one-phase models and seven two-phase models, by combining phenological observations and meteorological data. Using climatic data from two Shared Socioeconomic Pathways (SSP) scenarios, namely SSP126 (high mitigation and low emission) and SSP585 (no mitigation and high emission), we predicted spring phenology in Germany from 2021 to 2100, and compared the impacts of dormancy phases and driving factors on model predictive performance. The results showed that the average correlation coefficient between the predicted start of growing season (SOS) by the 13 models and the observed values exceeded 0.72, with the highest reaching 0.80. All models outperformed the NULL model (Mean of SOS), and the M1 model (driven by photoperiod and forcing temperature) performed the best for all the tree species. In the SSP126 scenario, the average SOS advanced initially and then gradually shifted towards a delay starting around 2070. In the SSP585 scenario, the average SOS advanced gradually at a rate of approximately 0.14 days per year. Moreover, the standard deviation of the simulated SOS by the 13 spring phenology models exhibited a significant increase at a rate of 0.04 days per year. On average, two-phase models exhibited larger standard deviations than one-phase models after approximately 2050. Models driven solely by temperature showed larger standard deviations after 2060 compared to models driven by both temperature and photoperiod. Our findings suggest investigating the release mechanisms of endodormancy phase and incorporating new insights into future phenological models to better simulate the changes in plant phenology.

Keywords: PEP725; SSP scenarios; climate change; future prediction; spring phenological model.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was funded by the Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (42261144755), the joint fund for regional innovation and development of NSFC (U21A2039), the Joint China-Sweden Mobility Program (Grant No. CH2020-8656), and the 111 Project (B18006).