我国海洋生态效率时空演变特征及影响因素OACHSSCD
Research on the spatio-temporal characteristics and influencing factors of marine eco-efficiency in China
探究海洋生态效率时空演变特征与提升路径,对于推进海洋高质量发展、建设海洋强国具有重要的意义.基于2008-2022年我国52个地级市的面板数据,运用非期望产出超效率SBM模型、核密度估计和Tobit模型等方法分析海洋生态效率时空演变特征及影响因素.结果表明:(1)2008-2022年,我国海洋生态效率均值呈现先下降后上升的趋势;2022年高生态效率水平城市占比34.62%,相较2008年提升了 17.31%;(2)我国海洋生态效率空间分布整体呈现北低南高趋势,区域差异先增大后减小,多数年份表现显著空间自相关,低值聚集区分布在北部海洋经济圈,高值聚集区出现在东部、南部海洋经济圈;(3)海洋经济发展水平和海洋生态效率符合环境库兹涅茨曲线,其拐点出现在海洋经济贡献率为41.8%时;(4)海洋固碳服务单位面积价值、环境规制对海洋生态效率具有显著的正向影响,环境规制对效率的影响在发达地区更加明显,产业结构高级化、对外开放程度对海洋生态效率具有显著的负向影响.未来应推动传统海洋产业转型升级,构建"梯度化"环境规制体系,实行区域差异化治理以构建人海和谐的海洋生态环境.
Exploring the spatiotemporal evolution characteristics and improvement paths of marine ecological efficiency(MEE)is of great significance for advancing high-quality marine development,promoting the coordinated development of marine resources utilization and ecological protection,and solidifying the foundation for building a maritime power.Based on panel data of 52 coastal prefecture-level cities in China from 2008 to 2022,this study employs the undesirable super-efficiency SBM model to accurately measure MEE levels,uses kernel density estimation to reveal dynamic temporal evolution characteristics,and applies the Tobit model to empirically test the action mechanisms of influencing factors,comprehensively examining the spatiotemporal evolution patterns and driving factors of MEE.The results indicate that:(1)From 2008 to 2022,China's average MEE showed a U-shaped trend of first declining and then rising-declining in the early stage due to extensive marine economic development and over-exploitation of resources,and recovering in the later period driven by ecological protection policies and green industrial transformation.In 2022,cities with high MEE accounted for 34.62%,representing a 17.31 percentage point increase from 17.31%in 2008.(2)The overall spatial distribution of MEE exhibited obvious north-south disparity,with generally lower levels in northern coastal cities and higher levels in southern coastal cities.Regional disparities first widened due to differences in development models and resource endowments,then narrowed with the advancement of regional collaborative governance.Moran's I test showed significant positive spatial autocorrelation in most years,with low-value agglomerations concentrated in the northern marine economic circle and high-value agglomerations in the eastern and southern marine economic circles.(3)The relationship between marine economic development level and MEE conforms to the Environmental Kuznets Curve:MEE decreases in the initial stage of extensive development,and after the marine economic contribution rate reaches the inflection point of 41.8%,MEE improves continuously driven by high-quality economic development and technological innovation.(4)The per unit area value of marine carbon sequestration services positively promotes MEE by optimizing the marine ecological structure,while environmental regulation exerts a significant positive impact by restricting pollution emissions-this effect is more pronounced in developed regions with higher policy execution efficiency.In contrast,industrial structure upgrading and the degree of opening-up have a significant short-term negative impact on MEE.In the future,efforts should focus on accelerating the green transformation of traditional marine industries,constructing a gradient environmental regulation system tailored to regional development levels,and implementing differentiated governance strategies based on the resource endowments of different marine economic circles,so as to realize the harmonious coexistence of marine ecosystems and human activities.
杨帆;洪珊;石琳
浙江海洋大学经济与管理学院,舟山 316000浙江海洋大学经济与管理学院,舟山 316000浙江海洋大学图书馆,舟山 316000
海洋生态效率非期望产出超效率SBM模型时空演变影响因素
marine ecological efficiencyundesirable outputsuper-efficiency SBM modelspatiotemporal evolutioninfluence factors
《生态学报》 2026 (11)
5685-5699,15
国家社会科学基金重大研究专项(24VHQ002)
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