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引用本文:蔡立哲,杨德援,赵小雨,林靖翔,陈昕韡,周细平,饶义勇,马丽,林和山,傅素晶.大亚湾软体动物群落和种群生态研究进展与展望[J].海洋科学,2022,46(6):124-134.
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大亚湾软体动物群落和种群生态研究进展与展望
蔡立哲1, 杨德援1, 赵小雨1,2, 林靖翔1, 陈昕韡1, 周细平2, 饶义勇3, 马丽4, 林和山4, 傅素晶4
1.厦门大学 环境与生态学院, 福建 厦门 361102;2.厦门大学 嘉庚学院环境科学与工程学院, 福建 漳州 363105;3.中国水产科学研究院 南海水产研究所, 广东 广州 510000;4.自然资源部 第三海洋研究所, 福建 厦门 361005
摘要:
近35年来,多家高校、科研机构和政府管理部门在大亚湾潮下带和潮间带进行了软体动物群落生态、种群生态和污染生态研究,揭示了不同生境软体动物的物种数、栖息密度和生物量的时空变化,为渔业生产和生态评估提供了基础资料。但早期有关文献难觅、信息不畅,导致软体动物分类存在同物异名和异物同名现象,一些中文学名和拉丁文学名张冠李戴,历史数据之间缺乏可比性等。作者提出了几点研究展望:(1)加强软体动物分类基础研究和科普宣传;(2)建立软体动物群落生态大数据式研究规则;(3)建立软体动物数据库;(4)人工智能及其他新技术和新方法的引入。本文可为科技工作者制订较完善的研究计划以及获得更精准的研究结果提供参考,可为政府部门提供决策依据。
关键词:  软体动物  群落生态  种群生态  污染生态  大亚湾
DOI:10.11759/hykx20211003001
分类号:Q13;Q178.53
基金项目:国家重点研发计划项目(2018YFC1407501)
Progress and prospects of mollusk community and population ecology in Daya Bay
CAI Li-zhe1, YANG De-yuan1, ZHAO Xiao-yu1,2, LIN Jing-xiang1, CHEN Xin-wei1, ZHOU Xi-ping2, RAO Yi-yong3, MA Li4, LIN He-shan4, FU Su-jing4
1.College of the Environment & Ecology, Xiamen University, Xiamen 361102, China;2.School of Environmental Science and Engineering, Xiamen University Tan Kah Kee College, Zhangzhou 363105, China;3.South China Sea Fisheries Research Institute, CAFS, Guangzhou 510000, China;4.Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
Abstract:
In the last 35 years, many universities, research institutions, and government environmental management agencies have conducted ecological studies on the mollusk community, population, and pollution in the subtidal and intertidal habitats of Daya Bay. These studies have revealed spatial and temporal variations in the number, density, and biomass of mollusk species. This research provides the basis for fishery production and ecological assessment. However, due to a lack of early consensus in the field, there are many synonyms and homonyms in mollusk classification and cases in which Chinese and Latin scientific names were misused, making it impossible to compare historical data. The author proposes several research paths: (1) strengthening basic research on mollusk classification and popularizing the science; (2) establishing rules for big data research on mollusk community ecology; (3) establishing a mollusk database; and (4) introducing artificial intelligence and other new technologies and methods. These pursuits would provide a reference for science and technology workers to make better research plans and obtain more accurate results and provide a decision-making basis for government agencies.
Key words:  mollusk  community ecology  population ecology  pollution ecology  Daya Bay
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