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林业科学 ›› 2026, Vol. 62 ›› Issue (5): 213-226.doi: 10.11707/j.1001-7488.LYKX20250305

• 综合评述 • 上一篇    下一篇

森林全周期阶段划分方法综述:概念、范式与展望

周超凡1,雷相东1,张晓红2,刘兆刚3,齐静3,卢军1,*()   

  1. 1. 林木资源高效生产全国重点实验室 中国林业科学研究院资源信息研究所 北京 100091
    2. 国家林业和草原局国际合作交流中心 北京 100714
    3. 东北林业大学林学院 哈尔滨 150040
  • 收稿日期:2025-05-13 修回日期:2025-11-18 出版日期:2026-05-10 发布日期:2026-05-12
  • 通讯作者: 卢军 E-mail:junlu@ifrit.ac.cn
  • 基金资助:
    “十四五”国家重点研发计划项目(2022YFD2200502)。

Review of Forest Life-Cycle Stage Classification Methods: Concepts, Paradigms, and Prospects

Chaofan Zhou1,Xiangdong Lei1,Xiaohong Zhang2,Zhaogang Liu3,Jing Qi3,Jun Lu1,*()   

  1. 1. State Key Laboratory of Efficient Production of Forest Resources Institute of Forest Resource Information Techniques, Chinese Academy of Forestry Beijing 100091
    2. International Cooperation Center of the National Forestry and Grassland Administration Beijing 100714
    3. College of Forestry, Northeast Forestry University Harbin 150040
  • Received:2025-05-13 Revised:2025-11-18 Online:2026-05-10 Published:2026-05-12
  • Contact: Jun Lu E-mail:junlu@ifrit.ac.cn

摘要:

森林阶段划分是理解森林动态和实施森林可持续经营的核心科学问题。针对当前研究中概念混淆、方法适用性不清的挑战,本研究系统梳理和评述主流的森林全周期阶段划分方法,明晰其理论基础和应用边界,以期为森林精准经营提供理论依据和实践指南。首先,辩证地厘清“森林演替”(群落尺度物种更替)和“森林发育”(林分尺度结构动态)两大核心概念的内涵、区别与联系,为后续方法评述和归类奠定理论基础。进而,从历史演进视角将现有方法归纳为四大范式体系:1) 时序范式(龄组划分法)——以林龄为单一划分指标,服务于木材永续利用,该方法操作简便,但难以刻画复杂森林的结构特征;2) 结构范式(森林循环阶段划分法)——基于林隙动态理论,揭示原始林的自然结构循环过程,是生物多样性保护的生态标尺;3) 生态范式(正向演替阶段划分法)——依据物种功能群的替代序列,阐释群落演替的宏观规律,为生态恢复提供理论框架;4) 融合范式(近自然发育阶段划分法)——面向全周期经营,将结构动态与经营目标相结合,是连接生态理论和经营实践的桥梁。综合分析表明,四大范式各有其独特的产生背景、适用尺度和局限性,方法选择取决于具体应用场景或经营目标。当前,该领域面临三大核心挑战,即概念融合的复杂性、量化与标准化不足以及气候变化对传统发育和演替路径干扰带来的不确定性。未来,森林全周期阶段划分研究将迈向以精准化、智能化、动态化为特征的深度融合发展新阶段,重点发展方向包括构建融合结构与生态功能的精确量化指标体系,发展能够整合气候预测模型的“气候智能型”动态划分框架,最终通过深度融合先进探测技术与人工智能算法,有望实现从“人工判别”到“智能感知”的范式革命,为全球森林的精准监测和高质量经营提供颠覆性的技术支撑。

关键词: 森林阶段划分, 演替, 发育, 划分范式, 全周期经营

Abstract:

Forest stage classification is a core scientific issue for understanding forest dynamics and implementing sustainable forest management. In response to the challenges of conceptual ambiguity and methodological applicability in current research, this paper systematically reviews and evaluates mainstream classification methods for forest life-cycle stage classification, clarifying their theoretical foundations and application boundaries, so as to provide theoretical basis and practical guidance for precision forest management. The paper first dialectically distinguishes the connotation, difference and connection between the two core concepts of forest succession (species replacement at the community scale) and forest development (structural dynamics at the stand scale), thereby establishing the theoretical cornerstone for the following method review and classification. Furthermore, from the perspective of historical evolution, the paper categorizes existing methods into four major paradigms: 1) Chronological paradigm (age-group classification): with stand age as a single division indicator to serve sustainable timber production, this method is easy to apply, but insufficient to capture complex structures. 2) Structural paradigm (forest cycle stage classification): based on the gap dynamics theory, this method reveals the natural structural cycle of primeval forests and serves as an ecological benchmark for biodiversity conservation. 3) Ecological paradigm (successional stage classification): based on the substitution sequence of functional species groups, this method explains macro-level community succession laws and provides a theoretical framework for ecological restoration. 4) Integrative paradigm (close-to-nature developmental stage classification): oriented toward life-cycle management, combining structural dynamics with management objectives, this method serves as a bridge between ecological theory and management practice. Comprehensive analysis shows that each paradigm has its own historical background, applicable scale, and limitations, thus, the choice of method depends on specific application scenarios or management objectives. Currently, this field faces three core challenges: the complexity of conceptual integration, insufficient quantification and standardization, and the uncertainties introduced by climate change disrupting traditional development and succession pathways. Future research on forest life-cycle stage classification will evolve toward a new phase of deep integration characterized by precision, intelligence, and dynamics. Key development directions include: constructing accurate quantitative indicator systems that integrate structural and ecological functions, developing “climate-smart” dynamic classification frameworks that incorporate climate prediction models. Ultimately, through the deep integration of advanced sensing technologies and artificial intelligence algorithms, a paradigm shift from “manual judgment” to “intelligent perception” is expected, providing transformative technical support for precision monitoring and high-quality management of global forests.

Key words: forest stage classification, succession, development, classification paradigm, life-cycle management

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