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应用生态学报 ›› 2025, Vol. 36 ›› Issue (5): 1519-1530.doi: 10.13287/j.1001-9332.202505.028

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1985—2023年中国滨海养殖池时空演变特征及其驱动因素

赵庆云1,2,3, 王晓杰2,3, 张清文2,3,4, 龙祥2,3, 宋洋2,3, 路峰5, 宋建彬5, 张保华1, 韩广轩2,3*   

  1. 1聊城大学地理与环境学院, 山东聊城 252000;
    2中国科学院烟台海岸带研究所中国科学院海岸带环境过程与生态修复重点实验室, 山东烟台 264003;
    3中国科学院黄河三角洲滨海湿地生态系统野外科学观测研究站, 山东东营 257500;
    4河海大学港口海岸与近海工程学院, 南京 210098;
    5山东黄河三角洲自然保护区管理局, 山东东营 257091
  • 收稿日期:2024-11-07 修回日期:2025-03-14 出版日期:2025-05-18 发布日期:2025-11-18
  • 通讯作者: *E-mail: gxhan@yic.ac.cn
  • 作者简介:赵庆云, 女, 2000年生, 硕士研究生。主要从事滨海湿地遥感研究。E-mail: 2481680675@qq.com
  • 基金资助:
    中国科学院国际大科学计划项目(121311KYSB20190029-4)和国家重点研发计划项目(2022YFF082101)

Spatial-temporal variations and driving factors of coastal aquaculture ponds in China from 1985 to 2023

ZHAO Qingyun1,2,3, WANG Xiaojie2,3, ZHANG Qingwen2,3,4, LONG Xiang2,3, SONG Yang2,3, LU Feng5, SONG Jianbin5, ZHANG Baohua1, HAN Guangxuan2,3*   

  1. 1School of Geography and Environment, Liaocheng University, Liaocheng 252000, Shandong, China;
    2CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, Shandong, China;
    3Yellow River Delta Field Observation and Research Station of Coastal Wetland Ecosystem, Chinese Academy of Sciences, Dongying 257500, Shandong, China;
    4College of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China;
    5Administration Bureau of Shandong Yellow River Delta Nature Reserve, Dongying 257091, Shandong, China
  • Received:2024-11-07 Revised:2025-03-14 Online:2025-05-18 Published:2025-11-18

摘要: 中国作为全球最大的海水养殖国,占全球养殖总产量的60%以上,沿海水产养殖业的发展对保障我国乃至全球粮食安全具有重要意义,并对滨海湿地生态环境产生重要影响。本研究基于1985—2023年遥感影像和社会经济数据,按照《湿地公约》定义的滨海湿地范围,采用面向对象分类方法,探究中国(台湾省除外,下同)滨海养殖池时空演变特征及其驱动因素。结果表明: 1985—2023年,中国滨海养殖池面积总体呈增长趋势,1985—2010年增速为68.3 km2·a-1,2010—2023年增速减小到17.1 km2·a-1。1985—2023年,中国不同典型沿海区域养殖池呈现明显的空间差异性,其中,辽东湾、渤海湾、北部湾养殖池面积呈现明显扩张趋势,而黄河三角洲、珠江三角洲、长江三角洲则呈现先增加后减少趋势。养殖池扩张的主要来源分别是淤泥质海滩(38.8%)、近海水域(33.3%)和滨海湿地植被(14.1%)。研究期内,淤泥质海滩面积与养殖池的扩张呈现出显著的负相关性,建筑用地、人口数量、GDP与滨海养殖池具有显著正相关性。研究期间,滨海养殖池的扩张主要是占用了滨海湿地,需要协调滨海湿地开发和保护。

关键词: 滨海湿地, 养殖池, 时空演变, 驱动因素

Abstract: As the world’s largest marine aquaculture country, China accounts for over 60% of the global aquaculture total production. The development of coastal aquaculture is of great significance for ensuring food security in China and even globally. Meanwhile, it also affects the ecological environment of coastal wetlands. Based on remote sensing images and socio-economic data from 1985 to 2023, and in line with the scope of coastal wetlands defined by The Ramsar Convention, we adopted an object-oriented classification method to explore the spatiotemporal variations and driving factors of coastal aquaculture ponds in China (excluding Taiwan Province, the same below). The results showed that the area of coastal aquaculture ponds in China generally presented an increasing trend from 1985 to 2023. The growth rate was 68.3 km2 per year from 1985 to 2010 and decreased to 17.1 km2 per year from 2010 to 2023. From 1985 to 2023, aquaculture ponds in different typical coastal regions of China exhibited obvious spatial variations. Specifically, the areas of aquaculture ponds in Liaodong Bay, Bohai Bay and Beibu Gulf showed obvious expansion trends, while those in the Yellow River Delta, Pearl River Delta and Yangtze River Delta showed a trend of increasing first and then decreasing. The main sources of the expansion of aquaculture ponds were muddy beaches (38.8%), offshore waters (33.3%), and coastal wetland vegetation (14.1%). During the study period, there was a significant negative correlation between the area of mudflats and the expansion of aquaculture ponds, while built-up land, population size and GDP showed significant positive correlations with coastal aquaculture ponds. The expansion of coastal aquaculture ponds was mainly occupied coastal wetland, and it is necessary to coordinate the development and protection of coastal wetlands.

Key words: coastal wetland, aquaculture pond, spatial-temporal evolution, driving factor