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中国沿海11省(市、自治区)休闲渔业空间分布及影响因素分析
引用本文:陈桂莹,赵奇蕾,祁思琼,陈新军.中国沿海11省(市、自治区)休闲渔业空间分布及影响因素分析[J].中国农业资源与区划,2023,44(8):64-73.
作者姓名:陈桂莹  赵奇蕾  祁思琼  陈新军
作者单位:1.上海海洋大学海洋科学学院,上海 201306;2.农业农村部大洋渔业开发重点实验室,上海 201306;3.国家远洋渔业工程技术研究中心,上海 201306;4.大洋渔业资源可持续开发省部共建教育部重点实验室,上海 201306
基金项目:上海市海洋渔业科学与技术专业建设项目(B1-5002-17-0001)
摘    要:目的 对沿海休闲渔业进行空间布局分析,有利于更好地调动不同省(市、自治区)的资源禀赋,促进休闲渔业发展,优化休闲渔业的空间规划。方法 文章以我国沿海11个省(市、自治区)8 552个休闲渔业经营单位为研究对象,综合运用平均最近邻、Thiessen多边形、核密度估计法、地理探测器,多维度分析我国沿海11个省(市、自治区)休闲渔业空间分布情况,并对其影响因素进行探讨。结果 (1)我国沿海11省(市、自治区)休闲渔业整体上呈现集聚型的分布形态,有显著的“两环一带”密度分布特征;旅客周转量、等级公路密度、与主城区的平均距离对休闲渔业空间分布的解释力最强。(2)休闲渔业与交通干线、景区酒店均有良好的空间耦合关系。(3)随着与市中心的距离递增,休闲渔业数量呈现先增后减的倒“U”型变化规律,并在距离市中心50km处形成了休闲渔业环城游憩带;所有影响因子在进行交互后均产生了双因子增强或非线性增强的作用。结论 在影响因素中,休闲渔业与主城区的距离、旅客周转量、旅行社接待人次数是主导因素;5A景区数量、生活垃圾无害化处理率、人均公园绿地面积是驱动因素;城镇居民人均可支配收入、等级公路密度是诱发因素;政府行为、热点事件是调节因素,各因素相互作用,共同形成沿海11个省(市、自治区)休闲渔业的空间格局。

关 键 词:休闲渔业  空间分布  影响因素  地理探测器  沿海省市
收稿时间:2022/4/30 0:00:00

ANALYSIS ON SPATIAL DISTRIBUTION AND INFLUENCING FACTORS OF RECREATIONAL FISHERY IN 11 COASTAL PROVINCES OF CHINA
Chen Guiying,Zhao Qilei,Qi Siqiong,Chen Xinjun.ANALYSIS ON SPATIAL DISTRIBUTION AND INFLUENCING FACTORS OF RECREATIONAL FISHERY IN 11 COASTAL PROVINCES OF CHINA[J].Journal of China Agricultural Resources and Regional Planning,2023,44(8):64-73.
Authors:Chen Guiying  Zhao Qilei  Qi Siqiong  Chen Xinjun
Institution:1.College of Marine Sciences,Shanghai Ocean University, Shanghai 201306, China;2.Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China;3.National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, China;4.Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China
Abstract:Spatial distribution analysis of coastal recreational fishery is conducive to better mobilize the local resource endowment of different provinces (cities) for the development of recreational fishery and optimize the spatial layout planning of recreational fishery. This study took 8 552 recreational fishery business units in 11 coastal provinces as the research object, comprehensively used the average nearest neighbor, Thiessen-Polygon, nuclear density estimation method and geographic detector to analyze the spatial distribution of recreational fishery in 11 coastal provinces of China, and discussed the factors affecting the spatial distribution of recreational fishery in 11 coastal provinces of China. The results showed that: (1) The recreational fishery in 11 coastal provinces of China presented a clustered distribution form on the whole, with the significant density distribution characteristic of "two rings and one belt". (2) The passenger turnover, the density of grade roads and the average distance from the main urban area had the strongest explanatory power to the spatial distribution of recreational fishery. Recreational fishery had a close spatial coupling relationship with traffic trunk roads, scenic spots and hotels. With the increasing distance from the city center, the number of recreational fisheries showed an inverted U-shaped change and the recreational fishery belt around the city was formed 50km away from the city center. (3) After interaction, all influencing factors exerted the effect of double factor enhancement or nonlinear enhancement. In summary, among the factors affecting the spatial distribution of recreational fishery, the distance between recreational fishery and the main urban area, passenger turnover and the number of receptions of travel agencies are the leading factors; The number of 5A scenic spots, the harmless treatment rate of domestic waste and the per capita green space area of parks are the driving factors; The per capita disposable income of urban residents and the density of grade roads are the inducing factors; Government behavior and hot events are the regulatory factors. All factors interact to finally form the spatial pattern of recreational fishery in 11 coastal provinces of China.
Keywords:recreational fishery  spatial distribution  influencing factor  geographic detector  coastal provinces and cities
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