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...

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Main Authors: Yutong Liang, Jinxin Yang, Qiang Yang, Wenkai Chen, Juncheng Fan, Yuanyuan Chen
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/13/12/1980
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author Yutong Liang
Jinxin Yang
Qiang Yang
Wenkai Chen
Juncheng Fan
Yuanyuan Chen
author_facet Yutong Liang
Jinxin Yang
Qiang Yang
Wenkai Chen
Juncheng Fan
Yuanyuan Chen
author_sort Yutong Liang
collection DOAJ
description 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.
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spelling doaj-art-a3ab9afedfaa47c1ad40eb0c84ce36e22025-08-20T02:43:32ZengMDPI AGLand2073-445X2024-11-011312198010.3390/land13121980Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in ChinaYutong Liang0Jinxin Yang1Qiang Yang2Wenkai Chen3Juncheng Fan4Yuanyuan Chen5College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, ChinaVegetation 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.https://www.mdpi.com/2073-445X/13/12/1980meteorological factorsvegetation phenologyclimate changepartial correlationridge regression
spellingShingle Yutong Liang
Jinxin Yang
Qiang Yang
Wenkai Chen
Juncheng Fan
Yuanyuan Chen
Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China
Land
meteorological factors
vegetation phenology
climate change
partial correlation
ridge regression
title Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China
title_full Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China
title_fullStr Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China
title_full_unstemmed Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China
title_short Response of Vegetation Phenology to Meteorological Factors in Different Eco-Geographic Zones in China
title_sort response of vegetation phenology to meteorological factors in different eco geographic zones in china
topic meteorological factors
vegetation phenology
climate change
partial correlation
ridge regression
url https://www.mdpi.com/2073-445X/13/12/1980
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