Impacts of extreme weather events on daily vegetation phenological development in the Lesser Khingan Mountains of China

Phenological development is intricately linked to climate change, and existing evidence suggests that the frequent occurrence of extreme weather events (EWEs) exerts a more profound influence on phenology. However, most prior studies have primarily focused on revealing the impact of overall extreme...

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Main Authors: Danyao Zhu, Luhe Wan, Wei Gao
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:Ecological Indicators
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Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X25000950
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author Danyao Zhu
Luhe Wan
Wei Gao
author_facet Danyao Zhu
Luhe Wan
Wei Gao
author_sort Danyao Zhu
collection DOAJ
description Phenological development is intricately linked to climate change, and existing evidence suggests that the frequent occurrence of extreme weather events (EWEs) exerts a more profound influence on phenology. However, most prior studies have primarily focused on revealing the impact of overall extreme weather conditions over a period on specific phenological transition dates. There is an urgent need to obtain short-term, continuous development processes to deeply understand the underlying response mechanisms. In this study, we developed and assessed the Daily Phenological Development Model (DPDM) to explore the continuous influence relationship between remotely sensed vegetation phenology and EWEs in the Lesser Khingan Mountains of northeastern China from 2000 to 2022. The DPDM effectively captures daily vegetation phenological development during both spring and autumn, with R2 values of 0.84 ± 0.06 and 0.78 ± 0.08, respectively. Additionally, our findings indicate that increased precipitation and more frequent hot events accelerate leaf greening and slow down leaf browning. In contrast, heavy rainfall, frost events and droughts negatively impact vegetation growth. Among these factors, frost events have the most significant inhibitory effect on spring vegetation growth. Furthermore, evergreen needleleaf forests demonstrate the strongest resistance to EWEs in all vegetation types. These insights provide valuable contributions to the accurate assessment and forecasting of vegetation phenology under climate change.
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spelling doaj-art-1834b7e830da42779cf0a92bb311224e2025-08-20T02:43:32ZengElsevierEcological Indicators1470-160X2025-02-0117111316610.1016/j.ecolind.2025.113166Impacts of extreme weather events on daily vegetation phenological development in the Lesser Khingan Mountains of ChinaDanyao Zhu0Luhe Wan1Wei Gao2Department of Geography, College of History and Culture, Mudanjiang Normal University, Mudanjiang 157012, ChinaHeilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China; Heilongjiang Wuyiling Wetland Ecosystem National Observation and Research Station, Yichun 153000, China; Corresponding author at: No. 1, Shida Road, Limin Economic Development Zone, Harbin 157012, China.Department of Computer, Harbin Finance University, Harbin 150030, ChinaPhenological development is intricately linked to climate change, and existing evidence suggests that the frequent occurrence of extreme weather events (EWEs) exerts a more profound influence on phenology. However, most prior studies have primarily focused on revealing the impact of overall extreme weather conditions over a period on specific phenological transition dates. There is an urgent need to obtain short-term, continuous development processes to deeply understand the underlying response mechanisms. In this study, we developed and assessed the Daily Phenological Development Model (DPDM) to explore the continuous influence relationship between remotely sensed vegetation phenology and EWEs in the Lesser Khingan Mountains of northeastern China from 2000 to 2022. The DPDM effectively captures daily vegetation phenological development during both spring and autumn, with R2 values of 0.84 ± 0.06 and 0.78 ± 0.08, respectively. Additionally, our findings indicate that increased precipitation and more frequent hot events accelerate leaf greening and slow down leaf browning. In contrast, heavy rainfall, frost events and droughts negatively impact vegetation growth. Among these factors, frost events have the most significant inhibitory effect on spring vegetation growth. Furthermore, evergreen needleleaf forests demonstrate the strongest resistance to EWEs in all vegetation types. These insights provide valuable contributions to the accurate assessment and forecasting of vegetation phenology under climate change.http://www.sciencedirect.com/science/article/pii/S1470160X25000950Vegetation phenologyExtreme weather eventsBayesian hierarchical modelEVI2
spellingShingle Danyao Zhu
Luhe Wan
Wei Gao
Impacts of extreme weather events on daily vegetation phenological development in the Lesser Khingan Mountains of China
Ecological Indicators
Vegetation phenology
Extreme weather events
Bayesian hierarchical model
EVI2
title Impacts of extreme weather events on daily vegetation phenological development in the Lesser Khingan Mountains of China
title_full Impacts of extreme weather events on daily vegetation phenological development in the Lesser Khingan Mountains of China
title_fullStr Impacts of extreme weather events on daily vegetation phenological development in the Lesser Khingan Mountains of China
title_full_unstemmed Impacts of extreme weather events on daily vegetation phenological development in the Lesser Khingan Mountains of China
title_short Impacts of extreme weather events on daily vegetation phenological development in the Lesser Khingan Mountains of China
title_sort impacts of extreme weather events on daily vegetation phenological development in the lesser khingan mountains of china
topic Vegetation phenology
Extreme weather events
Bayesian hierarchical model
EVI2
url http://www.sciencedirect.com/science/article/pii/S1470160X25000950
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AT luhewan impactsofextremeweathereventsondailyvegetationphenologicaldevelopmentinthelesserkhinganmountainsofchina
AT weigao impactsofextremeweathereventsondailyvegetationphenologicaldevelopmentinthelesserkhinganmountainsofchina