广西红树林植物群落—海水—沉积物复合结构特征及其典型相关性耦合优化

第43卷第2期生态科学43(2): 16–29 2024年3月Ecological Science Mar. 2024 黄良美, 于晓燕, 李丽和, 等. 广西红树林植物群落—海水—沉积物复合结构特征及其典型相关性耦合优化[J]. 生态科学, 2024, 43(2): 16–29.

HUANG Liangmei, YU Xiaoyan, LI Lihe, et al. The canonical correlation coupling and optimization for the structural characteristics of the combined sediment-sea water-plants community system in the Mangrove Forests, Guangxi Province[J]. Ecological Science, 2024, 43(2): 16–29.

广西红树林植物群落—海水—沉积物复合结构特征及其典型相关性耦合优化

黄良美1,*, 于晓燕1, 李丽和1, 韦锋1, 李嘉力1, 孙翔2

1. 广西壮族自治区生态环境监测中心, 南宁 530028

2. 广西大学资源环境与材料学院, 南宁 530004

【摘要】为有效观测红树林植物群落—海水—沉积物复合生态环境系统, 评价红树林湿地生态环境质量。基于广西山口和北仑河口2个红树林保护区内的植物群落样方调查、海水与沉积物监测分析数据, 阐述了植物群落—海水—沉积物的基本结构特征; 用主成分分析、多重典型相关权重系数排序、频次计数及专家知识判读等方法, 渐进耦合优化出一套指标体系, 拟合植物群落—海水—沉积物间的理想数量关系, 验证群落关键指标耦合优化作用。结果表明: (1)非对称性的49项初始指标耦合优化成对称性的24项后, 群落—海水—沉积物间由无典型相关性表现出显著或极显著典型相关性。3者间的典型相关性大小顺序为沉积物—海水(第一、二典型相关系数及其显著水平分别为C1=0.994, p=0.0001; C2=0.993, p=0.001)> 沉积物—群落关系(C1=0.997, p=0.001,C2=0.0.984, p=0.008)> 群落—海水关系(C1=0.987, p=0.042; C2=0.902, p=0.423)。(2)群落作为水环境与沉积物间的有机生命系统, 最大构件数对海水和沉积物有较理想的耦合优化作用, 最大重要值对海水有明显耦合优化作用, 最大胸径比总种数的耦合作用要突出。(3)均值内敛和样本增加可提高结构模型的典型相关显著性, 结合专家知识判读法则可拓展结构模型, 并提高典型相关系数值及其显著性水平。主成分分析—典型相关分析—专家知识判读的联合应用是很好的指标属性耦合优化方法, 适用于复合生态系统的关联耦合及其生态环境质量评价。

关键词：典型相关分析; 数据集; 红树林; 广西

doi:10.14108/ki.1008-8873.2024.02.003 中图分类号：X82 文献标识码：A 文章编号：1008-8873(2024)02-016-14 The canonical correlation coupling and optimization for the structural characteristics of the combined sediment-sea water-plants community system in the Mangrove Forests, Guangxi Province

HUANG Liangmei1,*, YU Xiaoyan1, LI Lihe1, WEI Feng1, LI Jiali1, SUN Xiang2

1. Guangxi Ecological and Environmental Monitoring Center, Nanning 530028, China

2. School of Resource, Environment and Material, Guangxi University, Nanning 53004, China

Abstract: To effectively observe the complex sediment-sea water-plants community system in the Mangrove Forests, and to

收稿日期: 2021-09-18; 修订日期: 2021-12-01

基金项目:广西重点研发计划项目(AB21196063)和(AB18050014); 广西自然科学基金面上项目(2018GXNSFAA050040); 国家自然科学基金项目

2期黄良美, 等. 广西红树林植物群落—海水—沉积物复合结构特征及其典型相关性耦合优化 17 accurately assess its integrated eco-environmental quality, a fitted optimal model is needed. The study focused on coupling

and optimizing the canonical correlation on the model of the complex sediment-sea water-plants community. Firstly, indices

system was proposed by compiling indicators for quantifying ecological characteristics of mangrove plants community,

indicators for assessing sea water quality and sediment environmental quality, which was then applied in two Mangrove

Nature Reserve, named Shankou and Beilunhekou of Guangxi Province. Then, principal component analysis (PCA) was

adopted to optimize structural data sets of canonical correlation, and canonical correlation analysis (CCA) was adopted to

explore the multiple relationships among plant community, sea water, and sediment. Finally, the order of indicators was

optimized and the ideal CCA model of plant community-sea water-sediment was established by using an integrated method of

CCA standardized canonical coefficients, frequency count, and expert knowledge. Results showed that: (1) The ideal fitted

24 indicators with symmetry were reduced from the initial 49 indicators with asymmetry after coupling and optimizing

process. Canonical correlations among plant community, sea water and sediment were also transformed from nothing to something. The optimization canonical correlations were showed as the following orders, sediment-sea water > plant community-sediment > plant community-sea water. Meanwhile, sea water and sediment had the highest canonical correlation

coefficients (their first and second canonical correlation with its significant test were as follows: c1=0.994, p=0.0001;

c2=0.993, p=0.0005, respectively), plant community had very strong canonical correlation with sediment (c1=0.997, p=

0.001; c2=0.0.984, p=0.008, respectively), and effective canonical correlation was also found between plant community and

sea water (c1= 0.987, p=0.042; c2=0.902, p=0.423, respectively). (2) As the important life organism between sea water and

sediment, plant community’s biggest important value, biggest branching number, and biggest DBH were the very useful

fitted indicators for sea water and sediment data sets. Meanwhile, the biggest DBH was more important than the total spices

number. (3) Both the mean matrix of multiple CCA and increasing samples could improve the significant level on the plant

community-sea water-sediment model, whereas the explored matrix for the combined method of the special judgement could

both improve the canonical correlation values and their significant level. Integrated method of PCA-CCA-SK could optimize

the attributes of indictors very well, and couple the correlation of complex ecosystem effectively, as well as be fitted for the comprehensive eco-environmental quality assessment currently.

Key words:canonical correlation analysis; data sets; mangrove forests; Guangxi Province.

0 前言

红树林是重要的湿地生态系统, 具有强大的固碳、储碳能力, 在防治污染、净化水体和维持生物多样性等方面发挥着重要作用。随着我国新时代休养生息生态环境治理体系的全面推进, 观测、监控和评价红树林生态质量, 耦合优化复合生态系统关联性, 追因水环境与沉积物污染源, 已成为重要研究课题。广西天然红树林面积大, 种类健全, 前人已开展了较多的研究, 如植物种类组成、景观类型和生态承载力等[1-3]; 对种群结构特征、基因分子标记、凋落物碳输出和微生物等[4-7]进行探索。目前, 面向广西红树林的海平面上升与海岸生态系统脆弱、景观格局改变与水环境质量、湿地沉积物重金属和抗生素污染与潜在生态风险等[8-11]研究受到广泛关注。对广西红树林生态恢复与重建、病虫害防控等方面研究[12-13]也有报道。

然而, 对广西红树林植物群落—海水—沉积物复合生态系统开展立体同步观测, 探索它们之间作用过程和数量关系的研究鲜有报道。现有基于因果律和相关律的数量分析方法中, 暂无可对多系统多属性多界面开展数量分析的成熟通用模型。虽然主维目标, 但无法对系统进行耦合。典型相关分析能对系统进行耦合, 但其对指标信息的提取需要借助结构方程[14]的原始指标权重系数和相关性系数进行判别筛选, 过程复杂, 且可能存在权重系数与相关性系数前后矛盾的地方。因此, 有必要将二者的优势结合进行方法探索, 提取关键性指标, 关联耦合复合生态系统, 探讨关键指标的耦合作用及生态学机理。

本文按照监测技术规范, 对山口和北仑河口2个红树林保护区的植物群落开展同步样方调查, 海水水质与沉积物测试分析, 摸清群落—海水—沉积物复合生态系统结构特征。通过主成分分析、典型相关性分析、频次计数和专家知识判读的联合应用, 耦合优化出一套群落—海水—沉积物指标体系, 从数量关系上刻画复合生态系统结构与功能相关性和作用机理。研究旨在为广西红树林湿地复合生态系统监测及其生态环境质量评价提供参考。

1 材料与方法

1.1 研究区监测布点设计及其质量控制

广西红树林主要分布在山口、铁山港、钦州湾、江平和北仑河口等地区。山口红树林自然保护区位