Preprints
https://doi.org/10.5194/essd-2023-159
https://doi.org/10.5194/essd-2023-159
16 May 2023
 | 16 May 2023
Status: this preprint is currently under review for the journal ESSD.

Mapping 24 woody plant species phenology and ground forests phenology over China from 1951–2020

Mengyao Zhu, Junhu Dai, Huanjiong Wang, Juha M. Alatalo, Wei Liu, Yulong Hao, and Quansheng Ge

Abstract. Plant phenology refers to the cyclic plant growth events, and is one of the most important indicators of climate change. Integration of plant phenology information is of great significance for understanding the response of ecosystems to global change and simulating the material and energy balance of terrestrial ecosystems. Based on 24552 in-situ phenology observation records of 24 typical woody plants from the Chinese Phenology Observation Network (CPON), we map the species phenology (SP) and ground phenology (GP) of forests over China from 1951–2020, with a spatial resolution of 0.1° and a temporal resolution of 1 day. A model-based upscaling method was used to generate SP maps from in-situ SP observations, and then weighted average and quantile methods were used to generate GP maps from SP maps. The validation shows that the SP maps of 24 woody plants are largely consistent with the in-situ observations, with an average error of 6.9 days in spring and 10.8 days in autumn. The GP maps of forests have good agreement with the existing Land Surface Phenology (LSP) products derived by remote sensing data, particularly in deciduous forests, with an average difference of 8.8 days in spring and 15.1 days in autumn. The dataset provides an independent and reliable phenology data source on a long-time scale of 70 years in China, and contributes to more comprehensive research on plant phenology and climate change at regional and national scales. The dataset can be accessed at https://doi.org/10.57760/sciencedb.07995 (Zhu et al., 2023).

Mengyao Zhu et al.

Status: open (until 11 Jul 2023)

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Mengyao Zhu et al.

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Species phenology and ground phenology maps over China from 1951–2020 Mengyao Zhu and Junhu Dai https://doi.org/10.57760/sciencedb.07995

Mengyao Zhu et al.

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Short summary
This study utilized 24,552 in-situ phenology observation records from the Chinese Phenology Observation Network to model and map 24 woody plants species phenology and ground forests phenology over China from 1951–2020. These phenology maps are the first gridded, independent and reliable sources of phenological data in China, with a high spatial resolution of 0.1° and an average error of about 10 days. It contributes to more comprehensive research on plant phenology and global change.