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Climate drivers of seed rain phenology of subtropical forest communities along an elevational gradient.

Authors :
Yang, Liu
Shen, Zehao
Wang, Xuejing
Wang, Shaopeng
Xie, Yuyang
Larjavaara, Markku
Zhang, Jie
Li, Guo
Source :
International Journal of Biometeorology. Jun2023, Vol. 67 Issue 6, p1095-1104. 10p.
Publication Year :
2023

Abstract

Seed rain phenology (the start and end date of seed rain) is an essential component of plant phenology, critical for understanding population regeneration and community dynamics. However, intra- and inter-annual changes of seed rain phenology along environmental gradients have rarely been studied and the responses of seed rain phenology to climate variations are unclear. We monitored seed rain phenology of four forest communities in four years at different elevations (900 m, 1450 m, 1650 m, 1900 m a.s.l.) of a subtropical mountain in Central China. We analyzed the spatiotemporal patterns of seed rain phenology of 29 common woody plant species (total observed species in the seed rain), and related the phenological variations to seed number and climatic variables using mixed-effect models with the correlation matrix of phylogeny. We found that changes in the period length were mainly driven by the end rather than the start date. The end date and the period length of seed rain were significantly different between the mast and non-mast seeding years, while no significant elevation-related trend was detected in seed rain phenology variation. Seed number, mean temperature in spring (Tspr), and winter (Twin), summer precipitation (Psum) had significant effects on seed rain phenology. When Tspr increased, the start date of seed rain advanced, while the end date was delayed and the seed rain period length was mainly prolonged by a higher seed number, Twin and Psum. Forest canopy might have a buffering effect on understory climatic conditions, especially in precipitation that lead to difference in seed rain phenology between canopy and shrub species. Our novel evidence of seed rain phenology can improve prediction of community regeneration dynamics in responding to climate changes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00207128
Volume :
67
Issue :
6
Database :
Academic Search Index
Journal :
International Journal of Biometeorology
Publication Type :
Academic Journal
Accession number :
164305385
Full Text :
https://doi.org/10.1007/s00484-023-02481-9