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Mapping 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020.

Authors :
Zhu, Mengyao
Dai, Junhu
Wang, Huanjiong
Alatalo, Juha M.
Liu, Wei
Hao, Yulong
Ge, Quansheng
Source :
Earth System Science Data. 2024, Vol. 16 Issue 1, p277-293. 17p.
Publication Year :
2024

Abstract

Plant phenology refers to cyclic plant growth events, and is one of the most important indicators of climate change. Integration of plant phenology information is crucial for understanding the ecosystem response to global change and modeling the material and energy balance of terrestrial ecosystems. Utilizing 24 552 in situ phenological observations of 24 representative woody plant species from the Chinese Phenology Observation Network (CPON), we have developed maps delineating species phenology (SP) and ground phenology (GP) of forests over China from 1951 to 2020. These maps offer a detailed spatial resolution of 0.1 ∘ and a temporal resolution of 1 d. Our method involves a model-based approach to upscale in situ phenological observations to SP maps, followed by the application of weighted average and quantile methods to derive GP maps from the SP data. The resulting SP maps for the 24 woody plants exhibit a high degree of concordance with in situ observations, manifesting an average deviation of 6.9 d for spring and 10.8 d for autumn phenological events. Moreover, the GP maps demonstrate robust alignment with extant land surface phenology (LSP) products sourced from remote sensing data, particularly within deciduous forests, where the average discrepancy is 8.8 d in spring and 15.1 d in autumn. This dataset provides an independent and reliable phenology data source for China on a long-time scale of 70 years, and contributes to more comprehensive research on plant phenology and climate change at both regional and national scales. The dataset can be accessed at 10.57760/sciencedb.07995 (Zhu and Dai, 2023). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18663508
Volume :
16
Issue :
1
Database :
Academic Search Index
Journal :
Earth System Science Data
Publication Type :
Academic Journal
Accession number :
175503656
Full Text :
https://doi.org/10.5194/essd-16-277-2024