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生态学杂志 ›› 2026, Vol. 45 ›› Issue (9): 2817-2834.doi: 10.13292/j.1000-4890.202609.020

• ·红树林湿地生态学专栏·(专栏组织专家:曹文志、王文卿、宋长春) • 上一篇    下一篇

红树林林龄估算与生态功能响应研究进展

李诗华1,2*,曾吉雨1,韦旭1,苏颖1,张婷婷1,张康耀1   

  1. 1福州大学先进制造学院, 福建晋江 362251; 2自然资源部海洋空间资源管理技术重点实验室, 杭州 310012)

  • 出版日期:2026-09-10 发布日期:2026-09-07

Research progress on mangrove age estimation and ecological function responses.

LI Shihua1,2*, ZENG Jiyu1, WEI Xu1, SU Ying1, ZHANG Tingting1, ZHANG Kangyao1   

  1. (1College of Advanced Manufacturing, Fuzhou University, Jinjiang 362251, Fujian, China; 2Key Laboratory of Ocean Space Resource Management Technology, MNR, Hangzhou 310012, China).

  • Online:2026-09-10 Published:2026-09-07

摘要: 红树林是全球生产力最高、生物多样性最丰富的生态系统之一,具备显著的固碳能力,并提供其他多种生态系统服务。林龄是预测红树林生长、碳积累及生态服务变化的关键参数,然而,目前适用于红树林林龄估算方法尚不完善,致使生态评估存在明显的不确定性。本文梳理了红树林林龄估算的四类主要技术路径及其适用条件与局限性,并归纳了生态服务对林龄变化的响应规律。现有研究方法主要包括传统实测、光学遥感时间序列分析、激光雷达结构反演和多源遥感融合。其中,传统实测法可在样地尺度实现高精度单木测年,但受热带树种年轮不规则、适用范围小及采集成本高等限制;光学遥感法能够基于长时间序列影像识别红树林建群年份,适用于区域尺度龄级制图,但易受云雾、潮位、混合像元和植被指数饱和影响;激光雷达可提供冠层高度和垂直结构信息,为林龄反演提供结构约束,但数据覆盖和时间连续性不足;多源融合法能够综合时间轨迹与结构参数,是提升红树林林龄估算精度的重要方向,但仍面临多源数据尺度不匹配、样地验证不足和误差传播复杂等问题。已有研究表明,中国红树林林龄结构受历史保护修复工程和区域气候梯度共同影响,人工恢复林比例较高,呈由北向南递增的纬度分异格局,整体林龄结构趋于年轻化。针对上述局限,本文建议未来研究应加强长期样地建设、造林档案整合、多源遥感协同反演、区域化参数模型构建和不确定性评估,推动形成全国尺度红树林林龄数据库。红树林林龄显著调控碳汇、海岸带防护和生物多样性等功能,是恢复规划与碳补偿评估的关键参数。本文可为红树林碳汇评估、生态修复成效评价和海岸带生态系统管理提供理论依据与技术参考。


关键词: 红树林, 林分年龄, 遥感, 生态服务

Abstract: Mangroves are among the most productive and biodiverse ecosystems globally, possessing substantial carbon sequestration capacity and providing a wide range of ecosystem services. Stand age is a critical parameter for predicting mangrove growth, carbon accumulation, and the changes in ecosystem services. However, current approaches for the estimation of mangrove age remain insufficiently developed, leading to considerable uncertainty in ecological assessments. This review synthesizes four major methodological pathways and their applicable conditions and limitations for mangrove age estimation, as well as the response patterns of ecological services to variations in forest age. Current approaches mainly include traditional field-based measurements, optical remote sensing time-series analysis, LiDAR-based structural inversion, and multi-source remote sensing integration. Traditional field-based methods can achieve high-precision individual tree dating at the plot scale, but their applicability is constrained by irregular growth rings in tropical species, limited spatial representativeness, and high sampling costs. Optical remote sensing approaches enable the identification of mangrove establishment years using long-term image time series and are therefore suitable for regional-scale age-class mapping. Nevertheless, their performance is strongly affected by cloud contamination, tidal fluctuations, mixed-pixel effects, and vegetation index saturation. LiDAR techniques provide canopy height and vertical structural information, offering important structural constraints for age inversion. However, their application is limited by insufficient spatial coverage and temporal continuity. Multi-source fusion approaches, which integrate temporal trajectories with structural parameters, represent an important direction for improving mangrove age estimation accuracy. Nevertheless, these methods still face challenges associated with scale mismatch among datasets, insufficient field validation, and complex uncertainty propagation. Existing studies indicate that the age structure of mangroves in China is jointly shaped by historical conservation, restoration programs, and regional climatic gradients. The proportion of artificially restored forests is relatively high, exhibiting a latitudinal gradient that increases from north to south, with the overall age structure tending toward rejuvenation. In response to current methodological limitations, future research should prioritize the establishment of long-term monitoring plots, integration of afforestation archives, synergistic inversion using multi-source remote sensing, development of regionalized parameter models, and comprehensive uncertainty assessment frameworks, ultimately supporting the construction of a national-scale mangrove age database. Mangrove stand age significantly regulates ecological functions such as carbon sequestration, coastal protection, and biodiversity conservation, which represents a key parameter for restoration planning and carbon offset assessment. This review provides both theoretical foundations and technical references for mangrove carbon sink assessment, ecological restoration evaluation, and coastal ecosystem management.


Key words: mangrove, stand age, remote sensing, ecosystem services