Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China

Vegetation phenology is highly sensitive to climate change, and an examination of vegetation phenology across diverse climatic conditions is crucial for identifying key factors influencing vegetation dynamics. However, there is a significant lack of macroscopic research and quantitative assessments on the response of vegetation phenology to meteorological factors in large-scale zones. This study employed Whittaker filtering and dynamic thresholding to extract phenological parameters of vegetation in China. Trend analysis was used to investigate the spatiotemporal changes in vegetation phenology from 1982 to 2022, while partial correlation and ridge regression analysis were conducted to quantify the response of vegetation in different zones to meteorological factors. The findings of this study demonstrate that over the past four decades, the start of the growing season (SOS) of vegetation in China has progressively advanced annually, whereas the end of the growing season (EOS) has progressively delayed annually, leading to an annual increase in the length of the growing season (LOS). Notably, these changes exhibit significant spatial variations. The response of vegetation phenology to temperature and precipitation is relatively complex and is closely related to local climatic conditions, humidity, vegetation type, etc. Different zones and diverse vegetation types have very different sensitivities to the same meteorological factor, sometimes even demonstrating contrasting responses. Consequently, this study is expected to clarify the response relationship between different vegetation ecosystems and meteorological factors in large-scale areas.

Authors

Institutions

Publication Details

Journal
Land
Published
2024-11-21
DOI
https://doi.org/10.3390/land13121980
Citations
2
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
0.75
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China

Yutong Liang, Juncheng Fan, Wenkai Chen, Jinxin Yang et al.
2 citations
Land
Remote Sensing and Land Use
0.75
article

Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China

Yutong Liang, Juncheng Fan, Wenkai Chen, Jinxin Yang, Yuanyuan Chen, Qiang Yang
article en
2 citations

Abstract

Vegetation phenology is highly sensitive to climate change, and an examination of vegetation phenology across diverse climatic conditions is crucial for identifying key factors influencing vegetation dynamics. However, there is a significant lack of macroscopic research and quantitative assessments on the response of vegetation phenology to meteorological factors in large-scale zones. This study employed Whittaker filtering and dynamic thresholding to extract phenological parameters of vegetation in China. Trend analysis was used to investigate the spatiotemporal changes in vegetation phenology from 1982 to 2022, while partial correlation and ridge regression analysis were conducted to quantify the response of vegetation in different zones to meteorological factors. The findings of this study demonstrate that over the past four decades, the start of the growing season (SOS) of vegetation in China has progressively advanced annually, whereas the end of the growing season (EOS) has progressively delayed annually, leading to an annual increase in the length of the growing season (LOS). Notably, these changes exhibit significant spatial variations. The response of vegetation phenology to temperature and precipitation is relatively complex and is closely related to local climatic conditions, humidity, vegetation type, etc. Different zones and diverse vegetation types have very different sensitivities to the same meteorological factor, sometimes even demonstrating contrasting responses. Consequently, this study is expected to clarify the response relationship between different vegetation ecosystems and meteorological factors in large-scale areas.

LandVol. 13(12)
Nanjing Forestry University (CN)
Climate action
Openalex Percentile: Top 29%
Remote Sensing and Land Use
0.75
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.