4.7 Article

Preseason heat requirement and days of precipitation jointly regulate plant phenological variations in Inner Mongolian grassland

期刊

AGRICULTURAL AND FOREST METEOROLOGY
卷 314, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.agrformet.2021.108783

关键词

Phenology; Climate change; Green-up; Flowering; Brown-down; Inner mongolian grassland

资金

  1. Strategic Priority Research Program of the Chinese Academy of Sciences [XDA26010103]
  2. National Natural Science Foundation of China [41775156]

向作者/读者索取更多资源

This study examined plant phenological records from 26 sites in Inner Mongolian temperate grassland from 1982 to 2019 and found that pre-season climate primarily regulates plant phenology, while the warming trend has little influence.
Under global climate change, particularly warming, plant phenology may vary significantly thereby influencing a series of ecosystem functionalities. However, observational evidences of the variation of plant phenology and its association with climate change in temperate grassland are limited. In this study, we collated plant phenological records during the period from 1982 to 2019 at 26 sites in Inner Mongolian temperate grassland to elucidate the association of plant phenology with a series of environmental variables. The results showed that a trend of warming, particularly during May-September, occurred over the study period. However, this warming did not significantly influence plant phenology (e.g., green-up, flowering and brown-down) of four dominant plant species (i.e., Stipa, L. Chinensis, A. Cristatum and A. Frigida). Rather, multivariate regression considering a series of climatic and edaphic factors revealed that preseason climate predominantly regulates the dynamics of plant phenology. Specifically, heat requirement (HR) and days of precipitation (DOP) during the preseason were the two most influential controls on plant phenology. Our findings highlight the importance of incorporating precipitation as an additional predictor variable in current temperature-based phenology models for application in temperate grassland.

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