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Characterizing Vegetation Phenology Shifts on the Loess Plateau over Past Two Decades

Authors :
Tong Wu
Xiaoqian Xu
Xinsen Chen
Shixuan Lyu
Guotao Zhang
Dongdong Kong
Yongqiang Zhang
Yijuan Tang
Yun Chen
Junlong Zhang
Source :
Remote Sensing, Vol 16, Iss 14, p 2583 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Phenology is a critical mirror reflecting vegetation growth and has a major impact on terrestrial ecosystems. The Loess Plateau (LP) is a paramount ecological zone in China that has experienced considerable vegetation changes. However, understanding the dynamics of vegetation phenology is limited by ambiguous vegetation interpretation and anthropogenic-induced forces. This study combined the multi-climatic and anthropogenic datasets to characterize the interactions between phenology shifts and environmental variables. The principal findings were as follows: (1) Phenological shifts exhibit spatial heterogeneity and an interannually increasing trend in greenness (R2 > 0.6, p < 0.05). Notably, SOS (the start of the growing season) advances while EOS (the end of the growing season) delays in both the southeastern and northwestern regions. (2) SOS and EOS, primarily in the range of 100–150 and 285–320 days, respectively. Phenological changes vary depending on vegetation types. The forest has an early SOS, within 80–112 days, and a delayed EOS, within 288–320 days. The SOS of shrub is mainly within 80–144 days. (3) EOS shows a strong response to the preseason of each climate variable. Precipitation (R = 0.76), soil moisture (R = −0.64), and temperature (R = 0.89) are the governing determinants in shaping vegetation phenology. In addition, agriculture and urbanization play a significant role in shaping the spatial variations of SOS. These findings provide a basis for a systematic understanding of the processes that affect vegetation growth, which is crucial for maintaining the health and sustainability of arid and semiarid ecosystems.

Details

Language :
English
ISSN :
20724292
Volume :
16
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.917ec24a129468ab02bca5aee522ec3
Document Type :
article
Full Text :
https://doi.org/10.3390/rs16142583