低效林及其改造研究进展
Research progress on degraded forest and its restoration
我国低效林普遍存在结构单一、生态功能退化、蓄积量与碳汇能力下降、病虫害频发及综合效益低等问题,严重制约国家生态安全屏障构建及“双碳”战略目标的实现。因此,低效林改造已成为推动森林生态系统高质量发展与多功能协同提升的关键举措。本文系统综述了我国低效林及其改造的研究进展,基于对低效林类型划分、成因机制及空间分布差异的深入分析,构建了以“更新复壮、结构优化、功能提升”为核心的技术路径。评述了遥感监测、人工智能、大数据、虚拟仿真及数字孪生等新兴技术在低效林改造全链条中的应用现状,从生态效益、碳汇增量及社会经济价值等多维度建立了改造成效评价体系。研究成果旨在为提升我国森林生态系统多功能性、维持系统韧性与稳定性提供理论支撑,为服务国家生态安全与绿色低碳发展战略提供重要参考。
Existing degraded forest in China generally face multiple challenges, including monotonous structure, degraded ecological functions, declining biomass and carbon sequestration capacity, frequent pest infestations, and reduced comprehensive benefits, which severely constrain the construction of national ecological security barriers and the achievement of “dual carbon” strategic goals. Therefore, degraded forest restoration has become a key measure to promote high-quality development and multifunctional synergistic improvement of forest ecosystems. This paper systematically reviews the research progress in degraded forest restoration in China. Based on an in-depth analysis of classification, causal mechanisms, and spatial distribution differences of degraded forest, it constructs a technical pathway centered on “regeneration and rejuvenation, structural optimization, and functional enhancement”. Additionally, it provides a critical review of current applications of emerging technologies such as remote sensing monitoring, artificial intelligence, big data, virtual simulation, and digital twins across the entire restoration chain. Furthermore, a comprehensive evaluation system for restoration effectiveness was established from multiple dimensions, including ecological benefits, carbon sequestration increments and socio-economic value. The research findings aim to provide theoretical support for enhancing the multifunctionality of China ,s forest ecosystems, maintaining system resilience and stability, and offer important references for serving national ecological security and green, low-carbon development strategies.
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国家重点研发计划(2022YFF1300401)
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