Jie Xi , Wei Fu , Luca Maria Francesco Fabris , Jiping Wen , Zhouyu Fan , Yitong Pan , Siyu Wang
{"title":"将植物、动物和土著实践整合到规定燃烧的空间优化中","authors":"Jie Xi , Wei Fu , Luca Maria Francesco Fabris , Jiping Wen , Zhouyu Fan , Yitong Pan , Siyu Wang","doi":"10.1016/j.jenvman.2025.124833","DOIUrl":null,"url":null,"abstract":"<div><div>Climate change has intensified wildfire activity, necessitating a shift towards sustainable fire management strategies that embrace the concept of fire coexistence. Fire coexistence recognizes the role of fire as a natural ecological process and integrates the adaptations of flora (e.g., fire-resistant bark, regenerative capacity), fauna (e.g., fuel reduction through grazing, creation of natural firebreaks), and traditional land management practices (e.g., controlled burns, agricultural firebreaks) that enable ecosystems to persist with fire. These \"coexistence factors\" are crucial for effective prescribed burning, ensuring minimal disruption to fire-adapted species and maximizing long-term ecosystem resilience. While prescribed burning is a recognized management tool, a comprehensive framework for spatially integrating these coexistence factors into regional-scale planning is lacking. This study addresses this gap by developing a novel approach that spatially optimizes prescribed burning by integrating fire risk and coexistence capacity. Applying this approach to the Jialing River watershed (China), a fire-prone mountainous region, we use machine learning and deep learning to predict fire risk and identify areas with high coexistence potential. Zonation 5 is then employed for spatial prioritization. Results reveal a significant spatial correlation between fire risk and coexistence capacity, with high-value clusters concentrated in the central and southern parts of the study area, particularly around the Jialing River and forested regions. Specifically, 4% of the study area in the central and southern regions (value > 0.679) was classified as very high fire risk, while the top 10% of the area exhibited high coexistence capacity (value > 0.9). Based on Zonation 5 optimization, 5% of fire-prone forests with high coexistence capacity were identified as priority areas for prescribed burning, concentrated primarily in eastern Beibei. This integrated approach offers valuable guidance for policymakers, land planners, and stakeholders in sustainably managing fire hazards in similar mountainous regions globally.</div></div>","PeriodicalId":356,"journal":{"name":"Journal of Environmental Management","volume":"379 ","pages":"Article 124833"},"PeriodicalIF":8.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating flora, fauna, and indigenous practices into spatial optimization for prescribed burning\",\"authors\":\"Jie Xi , Wei Fu , Luca Maria Francesco Fabris , Jiping Wen , Zhouyu Fan , Yitong Pan , Siyu Wang\",\"doi\":\"10.1016/j.jenvman.2025.124833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Climate change has intensified wildfire activity, necessitating a shift towards sustainable fire management strategies that embrace the concept of fire coexistence. Fire coexistence recognizes the role of fire as a natural ecological process and integrates the adaptations of flora (e.g., fire-resistant bark, regenerative capacity), fauna (e.g., fuel reduction through grazing, creation of natural firebreaks), and traditional land management practices (e.g., controlled burns, agricultural firebreaks) that enable ecosystems to persist with fire. These \\\"coexistence factors\\\" are crucial for effective prescribed burning, ensuring minimal disruption to fire-adapted species and maximizing long-term ecosystem resilience. While prescribed burning is a recognized management tool, a comprehensive framework for spatially integrating these coexistence factors into regional-scale planning is lacking. This study addresses this gap by developing a novel approach that spatially optimizes prescribed burning by integrating fire risk and coexistence capacity. Applying this approach to the Jialing River watershed (China), a fire-prone mountainous region, we use machine learning and deep learning to predict fire risk and identify areas with high coexistence potential. Zonation 5 is then employed for spatial prioritization. Results reveal a significant spatial correlation between fire risk and coexistence capacity, with high-value clusters concentrated in the central and southern parts of the study area, particularly around the Jialing River and forested regions. Specifically, 4% of the study area in the central and southern regions (value > 0.679) was classified as very high fire risk, while the top 10% of the area exhibited high coexistence capacity (value > 0.9). Based on Zonation 5 optimization, 5% of fire-prone forests with high coexistence capacity were identified as priority areas for prescribed burning, concentrated primarily in eastern Beibei. This integrated approach offers valuable guidance for policymakers, land planners, and stakeholders in sustainably managing fire hazards in similar mountainous regions globally.</div></div>\",\"PeriodicalId\":356,\"journal\":{\"name\":\"Journal of Environmental Management\",\"volume\":\"379 \",\"pages\":\"Article 124833\"},\"PeriodicalIF\":8.4000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Environmental Management\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0301479725008096\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/9 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Management","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0301479725008096","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/9 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Integrating flora, fauna, and indigenous practices into spatial optimization for prescribed burning
Climate change has intensified wildfire activity, necessitating a shift towards sustainable fire management strategies that embrace the concept of fire coexistence. Fire coexistence recognizes the role of fire as a natural ecological process and integrates the adaptations of flora (e.g., fire-resistant bark, regenerative capacity), fauna (e.g., fuel reduction through grazing, creation of natural firebreaks), and traditional land management practices (e.g., controlled burns, agricultural firebreaks) that enable ecosystems to persist with fire. These "coexistence factors" are crucial for effective prescribed burning, ensuring minimal disruption to fire-adapted species and maximizing long-term ecosystem resilience. While prescribed burning is a recognized management tool, a comprehensive framework for spatially integrating these coexistence factors into regional-scale planning is lacking. This study addresses this gap by developing a novel approach that spatially optimizes prescribed burning by integrating fire risk and coexistence capacity. Applying this approach to the Jialing River watershed (China), a fire-prone mountainous region, we use machine learning and deep learning to predict fire risk and identify areas with high coexistence potential. Zonation 5 is then employed for spatial prioritization. Results reveal a significant spatial correlation between fire risk and coexistence capacity, with high-value clusters concentrated in the central and southern parts of the study area, particularly around the Jialing River and forested regions. Specifically, 4% of the study area in the central and southern regions (value > 0.679) was classified as very high fire risk, while the top 10% of the area exhibited high coexistence capacity (value > 0.9). Based on Zonation 5 optimization, 5% of fire-prone forests with high coexistence capacity were identified as priority areas for prescribed burning, concentrated primarily in eastern Beibei. This integrated approach offers valuable guidance for policymakers, land planners, and stakeholders in sustainably managing fire hazards in similar mountainous regions globally.
期刊介绍:
The Journal of Environmental Management is a journal for the publication of peer reviewed, original research for all aspects of management and the managed use of the environment, both natural and man-made.Critical review articles are also welcome; submission of these is strongly encouraged.