中国沿海红树林树高变异与环境适应机制

doi:10.17521/cjpe.2023.0033

摘要/Abstract

摘要：

深入理解中国沿海红树林树高变异及其机制, 可以为中国沿海红树林修复、造林及重建红树林生态系统提供科学依据。该研究以1990-2022年发表的所有关于中国土壤、气候和潮差与红树林树高相关的文献为研究资料, 建立红树林树高与环境因子数据库, 对比红树林树高和环境因子在广西与东南沿海之间的差异, 并分析环境因子与红树林树高的关系及影响广西沿海与东南沿海红树林树高的关键因子。结果表明: (1)广西沿海红树林树高显著低于东南沿海的红树林。(2)广西与东南沿海的环境因子存在显著差异, 其中年降雨量、平均潮差、土壤盐度在广西最高; 土壤pH、土壤全氮含量和土壤全磷含量在广西最低。(3)除年降雨量、土壤有机质含量与红树林树高相关性不显著外, 其余环境因子与红树林树高显著相关。其中, 平均潮差、土壤pH和土壤盐度与红树林树高显著负相关; 年平均气温、土壤密度、土壤全氮含量和土壤全磷含量与红树林树高显著正相关。(4)结构方程模型结果显示, 平均潮差、土壤全磷含量和土壤pH是影响红树林树高最关键的环境因子, 年降雨量和年平均气温可直接影响红树林树高或通过调控其他环境因子之间相互关系从而间接影响红树林树高。(5)线性混合效应模型显示, 年平均气温、平均潮差和土壤盐度是限制广西沿海红树林树高的主要因素; 而东南沿海地区(除福建外)红树林的树高主要受到土壤因子限制。

关键词: 红树林, 树高, 环境因子, 结构方程模型, 线性混合效应分析, 中国沿海

Abstract:

Aims The aim of this study is to develop a comprehensive understanding of the variations in tree height and the underlying mechanisms shaping them in China’s coastal mangroves. This knowledge will serve as a scientific foundation for the restoration and afforestation efforts in China’s coastal mangrove regions, as well as the reconstruction of mangrove ecosystems.
Methods To achieve this, we conducted a comprehensive analysis of existing literature spanning the years 1990 to 2022, examining the interplay between soil composition, climate conditions, and tidal range in relation to tree height within China’s mangrove ecosystems. We established a database of mangrove tree height and environmental factors to compare the differences in tree height and environmental factors between mangroves in Guangxi and the Southeast China coast. Additionally, we analyzed the relationship between environmental factors and mangrove tree height as well as the key factors affecting the tree height of mangroves in Guangxi coast and the Southeast China coast.
Important findings Our findings reveal noteworthy disparities in tree height between Guangxi coastal mangroves and those found along the Southeast China coast. These variations in tree height are associated with significant differences in environmental factors between these regions. Specifically, Guangxi exhibits the highest mean annual precipitation, mean tidal range, and soil salinity, while recording the lowest levels of soil pH, soil total nitrogen content, and total phosphorus content. Upon closer analysis, we identified significant correlations between various environmental factors and mangrove tree height. Notably, mean tidal range, soil pH, and soil salinity displayed significant negative associations with mangrove tree height, whereas mean annual temperature, soil density, soil total nitrogen content, and soil total phosphorus content showed significant positive correlations. The results derived from structural equation models highlighted the paramount influence of mean tidal range, total soil phosphorus content, and soil pH on mangrove tree height. Mean annual precipitation and mean annual temperature directly impact the radial growth of mangroves or indirectly influence tree height by regulating the interactions among other environmental factors. Further examination using linear mixed-effects models demonstrated that the mean annual temperature, mean tidal range, and soil salinity emerged as the primary limiting factors affecting the radial growth of mangroves along the coast of Guangxi. In contrast, soil factors predominantly constrained the radial growth of mangroves in the Southeast China coastal areas (excluding Fujian).

Key words: mangroves, tree height, environmental factor, structural equation model, linear mixed-effect analysis, coastal areas of China

盘远方, 潘良浩, 邱思婷, 邱广龙, 苏治南, 史小芳, 范航清. 中国沿海红树林树高变异与环境适应机制. 植物生态学报, 2024, 48(4): 483-495. DOI: 10.17521/cjpe.2023.0033

PAN Yuan-Fang, PAN Liang-Hao, QIU Si-Ting, QIU Guang-Long, SU Zhi-Nan, SHI Xiao-Fang, FAN Hang-Qing. Variations in tree height among mangroves and their environmental adaptive mechanisms in China’s coastal areas. Chinese Journal of Plant Ecology, 2024, 48(4): 483-495. DOI: 10.17521/cjpe.2023.0033

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2023.0033

https://www.plant-ecology.com/CN/Y2024/V48/I4/483

图/表 6

图1 文献中红树林研究样地在中国沿海地区的分布。FJ, 福建样地; GD, 广东样地; GX, 广西样地; HN, 海南样地; 浙江和港澳台地区数据缺乏。

Fig. 1 Distribution of mangrove research literature in coastal areas of China. FJ, Fujian plots; GD, Guangdong plots; GX, Gangxi plots; HN, Hainan plots; lack of data in Zhejiang, Hong Kong, Macau, Taiwan of China.

图2 广西与东南沿海红树林树高比较(平均值±标准差)。FJ, 福建; GD, 广东; GX, 广西; HN, 海南; GX1, 广西文献中的研究数据; GX2, 2017年广西沿海270个10 m × 10 m的红树林样方调查数据。不同小写字母表示差异显著(p < 0.05)。

Fig. 2 Comparison of tree height of mangroves in coast of Guangxi and Southeast China (mean ± SD). FJ, Fujian; GD, Guangdong; GX, Guangxi; HN, Hainan; GX1, research data in literature of Guangxi; GX2, survey data of 270 mangrove plots of 10 m × 10 m along the coast of Guangxi in 2017. Different lowercase letters indicate significant differences (p < 0.05).

图3 广西与东南沿海地区环境因子比较(平均值±标准差)。MAP, 年降雨量; MAT, 平均气温; MTR, 平均潮差; pH, 土壤pH; SD, 土壤密度; SOM, 有机质含量; SS, 土壤盐度; TN, 土壤全氮含量; TP, 土壤全磷含量。FJ, 福建; GD, 广东; GX, 广西; HN, 海南。不同小写字母表示存在显著的差异(p < 0.05)。

Fig. 3 Comparison of environmental factors in coast of Guangxi and Southeast China (mean ± SD). MAP, mean annual precipitation; MAT, mean annual air temperature; MTR, mean tidal range; pH, soil pH; SD, soil density; SOM, soil organic matter content; SS, soil salinity; TN, soil total nitrogen content; TP, soil total phosphorus content. FJ, Fujian; GD, Guangdong; GX, Guangxi; HN, Hainan. Different lowercase letters indicate significant differences (p < 0.05).

图4 环境因子与红树林树高的关系。H, 树高; MAP, 年降雨量; MAT, 年平均气温; MTR, 平均潮差; pH, 土壤pH; SD, 土壤密度; SOM, 土壤有机质含量; SS, 土壤盐度; TN, 土壤全氮含量; TP, 土壤全磷含量。图中灰色区域表示95%的置信区间。

Fig. 4 Relationship between environmental factors and tree height of mangroves. H, tree height; MAP, mean annual precipitation; MAT, mean annual air temperature; MTR, mean tidal range; pH, soil pH; SD, soil density; SOM, soil organic matter content; SS, soil salinity; TN, soil total nitrogen content; TP, soil total phosphorus content. Grey areas indicate 95% confidence interval.

图5 环境因子对红树林树高影响的结构方程模型。H, 树高; pH, 土壤pH; MAP, 年降雨量; MAT, 年平均气温; MTR, 平均潮差; SD, 土壤密度; SOM, 土壤有机质含量; SS, 土壤盐度; TN, 土壤全氮含量; TP, 土壤全磷含量。*, p < 0.05; **, p < 0.01; ***, p < 0.001。红色箭头表示正相关, 蓝色箭头表示负相关, 箭头的粗细代表相关性的强弱。

Fig. 5 Structural equation model for the effect of environmental factors on tree height of mangroves. H, tree height; pH, soil pH; MAP, mean annual precipitation; MAT, mean annual air temperature; MTR, mean tidal range; SD, soil density; SOM, soil organic matter content; SS, soil salinity; TN, soil total nitrogen content; TP, soil total phosphorus content. *, p < 0.05; **, p < 0.01; ***, p < 0.001. Red arrows indicate positive correlation; blue arrows indicate negative correlation, thickness of arrows represent the strength of the correlation.

图6 环境因子对树高影响的线性混合效应模型。FJ, 福建; GD, 广东; GX, 广西; HN, 海南。pH, 土壤pH; MAP, 年降雨量; MAT, 年平均气温; MTR, 平均潮差; SD, 土壤密度; SOM, 土壤有机质含量; SS, 土壤盐度; TN, 土壤全氮含量; TP, 土壤全磷含量。绿色表示显著负相关(p < 0.05), 紫色表示显著正相关(p < 0.05), 黑色表示相关性不显著(p > 0.05)。

Fig. 6 Linear mixed-effects model of environmental factors on tree height. FJ, Fujian; GD, Guangdong; GX, Guangxi. HN, Hainan. pH, soil pH; MAP, mean annual precipitation; MAT, mean annual air temperature; MTR, mean tidal range; SD, soil density; SOM, soil organic matter content; SS, soil salinity; TN, soil total nitrogen content; TP, soil total phosphorus content. Green indicate significant negative correlation (p < 0.05), purple indicates significant positive correlation (p < 0.05), black indicates no significant correlation (p > 0.05).

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