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福建泉州湾河口湿地时空动态及其驱动机理
引用本文:林津,洪宇,林志玮,阙翔,刘金福,连海峰.福建泉州湾河口湿地时空动态及其驱动机理[J].北京林业大学学报,2021,43(6):75-82.
作者姓名:林津  洪宇  林志玮  阙翔  刘金福  连海峰
作者单位:1.福建农林大学计算机与信息学院,福建 福州 350002
基金项目:中央引导地方科技发展资金项目(2020L3006),数字福建环境监测物联网实验室开放课题(202008),福建农林大学科技创新专项(CXZX2020149C)
摘    要:   目的   为探究福建泉州湾河口湿地生态系统环境破坏及景观结构变化的原因,   方法   以泉州湾河口湿地为研究区域,基于Landsat TM遥感影像提取地物信息,构建土地利用动态度模型,运用景观格局指数分析景观空间结构特征;建立不同时期土地利用转移概率矩阵,确定土地类型间数量转移关系;应用灰色关联度模型分析红树林湿地面积变化驱动力。   结果   (1)1990—2018年天然湿地面积占比呈减少趋势,人工湿地呈增加趋势;从景观水平看,湿地斑块分布呈规则化,聚拢程度减少,景观类型丰富。(2)红树林、互花米草群落动态度波动大,红树林面积比例以2000年为分界点,呈先减后增趋势;1990—2000年红树林主要向水域、养殖池转出,2010—2018年滩涂和互花米草群落转出为红树林。(3)2000年来,红树林面积大小与其他土地类型面积变化关联性强,尤其受到国内生产总值、园林绿地面积影响较大。   结论   泉州湾河口湿地红树林呈恢复趋势,互花米草群落蔓延速率减缓,生态环境逐步改善。该研究为湿地保护与生态恢复提供科学实践依据。 

关 键 词:泉州湾河口湿地    红树林    遥感监测    面向对象    景观格局    灰色关联度
收稿时间:2020-11-21

Spatiotemporal dynamics and its driving mechanism of the Quanzhou Bay Estuary Wetland,Fujian Province of eastern China
Lin Jin,Hong Yu,Lin Zhiwei,Que Xiang,Liu Jinfu,Lian Haifeng.Spatiotemporal dynamics and its driving mechanism of the Quanzhou Bay Estuary Wetland,Fujian Province of eastern China[J].Journal of Beijing Forestry University,2021,43(6):75-82.
Authors:Lin Jin  Hong Yu  Lin Zhiwei  Que Xiang  Liu Jinfu  Lian Haifeng
Institution:1.College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China2.College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China3.Cross-Strait Nature Reserve Research Center of Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China4.Key Laboratory for Ecology and Resource Statistics of Fujian Province, Fuzhou 350002, Fujian, China
Abstract:   Objective   The natural conditions of Quanzhou Bay estuary wetland are superior, including mangrove, tidal flats and wetlands. In recent years, due to human activities and other factors, its ecological environment and wetland landscape structure have been damaged to a certain extent.   Method   Taking Quanzhou Bay estuary wetland as the research area, we extracted information based on the Landsat TM remote sensing images. We constructed a dynamic land-use model, using landscape pattern index to analyze its landscape spatial structure characteristics. By establishing Markov matrixes of land types between different periods, we could determine the number transfer relationship between land types. We used the Grey Incidence Analysis to study the driving force of mangrove wetland area change.   Result   (1) From 1990 to 2018, the proportion of natural wetland areas showed a decreasing trend and the ratio of constructed wetland showed an increasing trend. From the landscape-level perspective, the types were abundant, and their distributions of wetland patches were regular.The degree of aggregation illustrated a reducing trend. (2) The dynamics of mangrove and Spartina alterniflora communities fluctuated widely, and the proportion of mangroves was the cut-off point in 2000, showing a trend of first decreasing and then increasing. From 1990 to 2000, mangroves mainly transferred into water areas and culture ponds, and from 2010 to 2018, many tidal flats and Spartina alterniflora communities moved into mangroves. (3) Since 2000, mangrove’s area had a strong correlation with other land types affected by human activities; among the social and economic factors, GDP and green space area had great influence on it.   Conclusion   According to the temporal and spatial changes of wetland types, mangroves’ area showed a recovery trend. The spread of Spartina alterniflora communities slowed down, and the ecological environment was gradually improved, which provides scientific and practical basis for wetland protection and ecological restoration. 
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