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- Title
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
- 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).
- Subjects
CHINA; PHENOLOGY; PLANT species; PLANT phenology; WOODY plants; DECIDUOUS forests; CLIMATE change; SPRING
- Publication
Earth System Science Data, 2024, Vol 16, Issue 1, p277
- ISSN
1866-3508
- Publication type
Article
- DOI
10.5194/essd-16-277-2024