{"title":"西南火烧区植被绿度和冠层高度短期恢复的驱动因素","authors":"Pan Xie, ZhiGao Yang, Feng Liu, Xin Wu","doi":"10.1016/j.indic.2025.100950","DOIUrl":null,"url":null,"abstract":"<div><div>Forest fires are major disturbances to forest ecosystem structure and function. Understanding post-fire vegetation recovery and its drivers is crucial for forest restoration. This study investigates 20 forest sites burned in Southwest China in 2020. Post-fire vegetation recovery was evaluated in two dimensions using multi-source remote sensing: vegetation greenness represented by Enhanced Vegetation Index (EVI) and canopy height. Recovery was quantified with Relative Recovery Index (RRI) and annual growth rate. A Generalized Additive Model (GAM) was employed to explore the driving effects of multiple factors,including topography, climate, fire severity, and pre-fire vegetation conditions, on post-fire vegetation recovery. It was found that there was an asynchrony between the recovery of EVI and canopy height after fire, EVI recovered faster than canopy height after fire (RRI≤0, 38.27 % vs 6.37 %; RRI 0.5–1.0, 53.8 % vs 17.4 %), thus potential overestimation for forest recovery if assessed using optical indices solely. GAM results indicated that EVI recovery was primarily driven by precipitation, temperature, fire severity, and pre-fire EVI; canopy height recovery was mainly influenced by slope, fire severity, and pre-fire canopy height, with elevation and precipitation influenced recovery through interactions with other factors. High fire severity enhanced EVI recovery but suppressed canopy height recovery, while pre-fire vegetation conditions negatively affected the short-term recovery of both metrics. For both single and interactive driving factors, the effects on the recovery of EVI and canopy height were predominantly nonlinear rather than purely linear. The results advance knowledge of post-fire vegetation recovery mechanisms and support informed evaluation and management of affected ecosystems.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"28 ","pages":"Article 100950"},"PeriodicalIF":5.6000,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Drivers of short-term recovery in vegetation greenness and canopy height in burned areas of Southwest China\",\"authors\":\"Pan Xie, ZhiGao Yang, Feng Liu, Xin Wu\",\"doi\":\"10.1016/j.indic.2025.100950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Forest fires are major disturbances to forest ecosystem structure and function. Understanding post-fire vegetation recovery and its drivers is crucial for forest restoration. This study investigates 20 forest sites burned in Southwest China in 2020. Post-fire vegetation recovery was evaluated in two dimensions using multi-source remote sensing: vegetation greenness represented by Enhanced Vegetation Index (EVI) and canopy height. Recovery was quantified with Relative Recovery Index (RRI) and annual growth rate. A Generalized Additive Model (GAM) was employed to explore the driving effects of multiple factors,including topography, climate, fire severity, and pre-fire vegetation conditions, on post-fire vegetation recovery. It was found that there was an asynchrony between the recovery of EVI and canopy height after fire, EVI recovered faster than canopy height after fire (RRI≤0, 38.27 % vs 6.37 %; RRI 0.5–1.0, 53.8 % vs 17.4 %), thus potential overestimation for forest recovery if assessed using optical indices solely. GAM results indicated that EVI recovery was primarily driven by precipitation, temperature, fire severity, and pre-fire EVI; canopy height recovery was mainly influenced by slope, fire severity, and pre-fire canopy height, with elevation and precipitation influenced recovery through interactions with other factors. High fire severity enhanced EVI recovery but suppressed canopy height recovery, while pre-fire vegetation conditions negatively affected the short-term recovery of both metrics. For both single and interactive driving factors, the effects on the recovery of EVI and canopy height were predominantly nonlinear rather than purely linear. The results advance knowledge of post-fire vegetation recovery mechanisms and support informed evaluation and management of affected ecosystems.</div></div>\",\"PeriodicalId\":36171,\"journal\":{\"name\":\"Environmental and Sustainability Indicators\",\"volume\":\"28 \",\"pages\":\"Article 100950\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2025-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental and Sustainability Indicators\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S266597272500371X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental and Sustainability Indicators","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266597272500371X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
森林火灾是对森林生态系统结构和功能的重大干扰。了解火灾后植被恢复及其驱动因素对森林恢复至关重要。本研究调查了2020年中国西南地区被烧毁的20个森林遗址。利用多源遥感对火灾后植被恢复情况进行了评价:以增强植被指数(Enhanced vegetation Index, EVI)为代表的植被绿度和冠层高度。回收率用相对回收率指数(RRI)和年增长率进行量化。采用广义加性模型(GAM)探讨地形、气候、火灾严重程度和火灾前植被条件等多种因素对火灾后植被恢复的驱动作用。结果表明,林火后EVI的恢复与林冠高度之间存在不同步性,EVI的恢复速度快于林火后的林冠高度(RRI≤0,38.27% vs . 6.37%; RRI 0.5 ~ 1.0, 53.8% vs . 17.4%),单纯使用光学指标评价森林恢复可能存在高估的可能性。GAM结果表明,EVI恢复主要受降水、温度、火灾严重程度和火灾前EVI驱动;林冠高度恢复主要受坡度、火灾严重程度和火灾前林冠高度的影响,海拔和降水通过与其他因素的相互作用影响林冠高度恢复。高的火灾严重程度促进了EVI的恢复,但抑制了冠层高度的恢复,而火灾前的植被条件对这两个指标的短期恢复都有负面影响。无论是单一驱动因子还是交互驱动因子,对EVI和冠层高度恢复的影响均以非线性为主,而非纯线性。研究结果促进了对火灾后植被恢复机制的认识,并为受影响生态系统的知情评估和管理提供了支持。
Drivers of short-term recovery in vegetation greenness and canopy height in burned areas of Southwest China
Forest fires are major disturbances to forest ecosystem structure and function. Understanding post-fire vegetation recovery and its drivers is crucial for forest restoration. This study investigates 20 forest sites burned in Southwest China in 2020. Post-fire vegetation recovery was evaluated in two dimensions using multi-source remote sensing: vegetation greenness represented by Enhanced Vegetation Index (EVI) and canopy height. Recovery was quantified with Relative Recovery Index (RRI) and annual growth rate. A Generalized Additive Model (GAM) was employed to explore the driving effects of multiple factors,including topography, climate, fire severity, and pre-fire vegetation conditions, on post-fire vegetation recovery. It was found that there was an asynchrony between the recovery of EVI and canopy height after fire, EVI recovered faster than canopy height after fire (RRI≤0, 38.27 % vs 6.37 %; RRI 0.5–1.0, 53.8 % vs 17.4 %), thus potential overestimation for forest recovery if assessed using optical indices solely. GAM results indicated that EVI recovery was primarily driven by precipitation, temperature, fire severity, and pre-fire EVI; canopy height recovery was mainly influenced by slope, fire severity, and pre-fire canopy height, with elevation and precipitation influenced recovery through interactions with other factors. High fire severity enhanced EVI recovery but suppressed canopy height recovery, while pre-fire vegetation conditions negatively affected the short-term recovery of both metrics. For both single and interactive driving factors, the effects on the recovery of EVI and canopy height were predominantly nonlinear rather than purely linear. The results advance knowledge of post-fire vegetation recovery mechanisms and support informed evaluation and management of affected ecosystems.