MHQD empowers the prevention and control of marine environmental risks and promotes the ecological security system to achieve a virtuous cycle, which is the economic driving force to realize the ecological security of the national territory and build the marine community of destiny.

The role of MHQD on MES is as follows: (1) Provide financial guarantees and restoration funds. The establishment of MES barriers such as marine environmental pollution prevention and control, biodiversity protection, and orderly exploitation and utilization of resources is inseparable from the sustained and stable MHQD. MHQD can provide sufficient funds and advanced technology for the above MES construction links, ensure the implementation of MES early warning, green technology research and development, and specific pollution control projects, and effectively promote the smooth operation of the MES system. (2) Promote benign accumulation of the ecosystem. Green development is a particularly important part of MHQD. By optimizing the structure of marine industries, stimulating sea-related enterprises to innovate green production technologies, and investing in environmental technology R&D to counter the negative effects of sloppy production, we can reduce pollution emissions and resource waste, thus promoting the positive accumulation of marine ecosystems and improving MES. (3) The high-quality demands of the public drive the process of MES. MHQD reflects the desire of people in coastal areas for a high-quality living environment and the demand for sustainable development of the ocean. As people’s demand for high-quality green products and ecological services increases, the awareness of participation in environmental protection will also be enhanced. At the same time, the innovation requirements of MHQD can promote the improvement of MES-related regulations and systems and improve the modern governance system of MES. If the high-quality development is ignored, the extensive production mode will pose threats to the marine primitive ecology, resource environment, and human life, thus exerting a stressful effect on marine ecological security.

MES not only characterizes good marine ecological resources and natural environment but also indicates that the human activities and socio-economic complex system related to marine ecology maintain a relatively safe and stable health status. A good MES system not only provides sustainable and safe environmental conditions for MHQD but also provides support for its continuous optimization and upgrading.

The role of MES on MHQD is as follows: (1) Provide a safe environment and resource guarantees to lay a material foundation and production factors for high-quality development. A well-established marine ecosystem can protect nature, economy, and society from external threats, providing a sustainable safe environment for production and daily life in human society. Given that the quantity of ecological resources is finite, MES is the fundamental guarantee for the sustainable use of marine ecological resources. It can provide high-quality natural ecological resources and sufficient production factors to support MHDQ. (2) Utilizing the wealth-enhancing functions of ecosystems. The value transformation of ecosystem services and ecological products within the MES system can drive wealth enhancement for MHQD. Firstly, ecological resources are converted into ecological products through the processes of ‘valorisation’ and ‘marketisation.’ Secondly, the transformation of ecological resources into ecological assets is achieved through mechanisms such as ecological value compensation and green finance (Shujah-ur-Rahman et al., 2019). Finally, the conversion of ecological assets into ecological capital is realized through the operation of ecological services, thereby generating wealth, which effectively promotes the MHQD. (3) Providing a “source” of motivational mechanisms. The construction of an MES system requires a shift in thinking, achieving a transformation from “end-of-pipe governance” to “source prevention and front-end innovation.” This shift can drive the transformation of economic development momentum backwardly, promoting economic transition and industrial structure upgrading from the ‘source,’ thereby providing momentum for the MHQD. Simultaneously, the market-oriented concept of eco-intensification encourages businesses to seek the most efficient combination of production factors, prompting them to prioritize investments in technological capital, innovation, and R&D, while reducing their reliance on traditional resource-intensive inputs, thereby promoting higher-quality development. Overall, MES and MHQD can be two-way promotion and two-way inhibition, once touched ecological security “red line”, will also have a binding effect on quality development.

The establishment of a MES indicator system necessitates a dual consideration of the marine environment and resource status, while also thoroughly encompassing the pressures associated with emissions, consumption, and ecological restoration (Jiao et al., 2023). It should also account for the socio-economic system’s capacity to respond to and maintain ecological security pressures, facilitating comprehensive, multi-tiered, and multi-dimensional assessments. This process is both complex and pioneering. In terms of assessment logic, the International Organization for Economic Cooperation and Development (OECD) and the United Nations Environment Programme (UNEP) jointly proposed the “Pressure-State-Response” (PSR) model in 1990, which is widely used in ecological security assessment studies (Liu and Meng, 2021).The model is capable of reflecting the sustainability of ecosystems under human influence through dynamic causal relationships. By thoroughly collecting and organizing indicators for the previously studied PSR model (Wang et al., 2021a), we conducted theoretical analysis, field research, and expert consultations to construct an MES indicator system based on the classic PSR model ( Table 1 ), which comprises 3 dimension layers and 13 indicator layers.

The ecological security “pressure” dimension takes into account the negative impacts of human beings, society, and nature on MES; the ecological security “state” dimension covers the situation of the oceans themselves and their carrying capacity for human activities; the ecological security “response” dimension refers to the measures taken by governments, enterprises, and individuals to maintain MES within a reasonable range. It represents the human capacity to respond to pressures and negative conditions affecting MES.

The MHQD is an integration of various systems. Clarifying and quantifying the characteristics of the MHQD and measuring its level is a complex system engineering task. It is not exclusively centred on the growth of the economic system; instead, it also emphasizes the need for coordinated interaction between the economic system and external factors, including the environment and society (Wu et al., 2023). Consequently, the “Five Development Concepts” proposed by the nation have indeed become the action guidelines for pursuing high-quality development (Liu and Zhou, 2023). The five dimensions they encompass, namely “innovative, coordinated, green, open and shared development”, form the logical framework for China’s high-quality economic development. Among these, “innovative” acts as the core driving force, “coordinated” is an intrinsic requirement, “green” is the predominant form, “open” is the only path, and “shared development” is the ultimate value destination. These five dimensions collectively guide the pursuit of high-quality development in various fields, including the marine economy. With reference to the objectives and tasks of the national high-quality development strategy, we have constructed an index system comprising 5 dimension layers and 31 indicator layers by drawing on the results of the existing research (Ma et al., 2019; Liu P. et al., 2021; Sun et al., 2021), including “economic development”, “innovation driven”, “green cycle”, “improvement of people’s livelihood”, and “land-sea coordination” ( Table 2 ). The selection of indicators fully considers multiple dimensions such as the economy, society, resources, and environment, ensuring they possess comprehensiveness, scientificity, and effectiveness.

The “economic development” serves as a measure of the operational status of the marine economy, manifesting in three aspects: economic scale, economic vitality, and economic openness. We employ a suite of indicators, including the “GOP in coastal regions”, the “cargo throughput of coastal ports”, and the “value added by the marine industry”, to quantify the economic scale. Additionally, we track the “ratio of marine secondary industry to tertiary industry” and the “proportion of marine tertiary industry” to gauge the economic vitality. Furthermore, to assess the level of economic openness, we consider metrics such as the “actual utilization of foreign investment”, the “total value of imports and exports”, and the “foreign exchange earnings from coastal tourism”. The “innovation driven “ is the core driving force for the MHQD, characterized by innovation resources and innovation efficiency. The “investment intensity of marine scientific research funds”, the “marine R&D Staff”, and the “R&D topics for marine research and development institutions” are three indicators that effectively reflect the driving force of innovation. In terms of innovation efficiency, we represent this aspect with the following three indicators: the “number of marine science and technology patents granted per capita”、the “number of marine science and technology papers published per capita”, and the “marine labour Productivity. The “green cycle” concept is instrumental in assessing the level of circular governance. It encompasses several secondary indicators, including the “energy consumption per unit of GOP”、the “comprehensive utilization of coastal industrial solid waste”, “coastal industrial water reuse rate”, and others. The concept of “improvement of people’s livelihood” embodies the essence and goal of high-quality economic development, which is fundamentally people-oriented. This focus on the well-being of the population is manifested in three key areas: social security, education development, and economic conditions. These areas are further defined by seven secondary indicators that encompass a broad spectrum of social well-being, including aging, education, employment, healthcare, and income. The “land-sea coordination” is a key measure for accelerating the construction of a maritime power. It emphasizes the overall regional development and promotes regional economic growth as indicators of assessment. Below are five secondary indicators: the “urban to rural income ratio”, the “proportion of coastal marine GDP to national marine GDP”, the “proportion of the added value of marine industry to the GOP”, and others.

MES and MHQD systems are complementary, interpenetrating, and constraining each other, the coupled coordination degree model we adopted to measure the level of synergistic development of the composite system is feasible (Bian et al., 2022):

In which C ( t ) and R ( t ) are the degree of coupling and coupling coordination between MES and MHQD, respectively (Equations 1, 3). The value interval is 0~1, the larger the value of R , indicating that the stronger the coupling coordination of the composite system. V ( t ) is the integrated inter-system coordination index (Equation 2). α 、 β is the coefficient to be determined and α + β = 1 , in accordance with relevant national policies for integrated development and security, MES and MHQD systems are complementary and equally important (Geng and Ji, 2021) so take α = β = 0.5 . U i ( t ) represents the composite index of MES and MHQD. This paper examines the degree of coupling coordination of two subsystems, so the adjustment coefficient k is taken as 2. V ( t ) is the integrated inter-system coordination index. In order to make a more accurate judgment of the degree of coupling coordination between the two systems in the study area, referring to the related research (Tsaur et al., 2006; Guo and Li, 2014; Song, 2021) we divided the coordination grade of the two systems based on the existing classification methods, the coupling coordination degree is classified by the median segmentation method (Cheng et al., 2019; Zameer et al., 2020; see Table 3 ).

In order to clarify the extent to which inter-regional (among 3MMECs) and intra-regional (among provinces and cities) discrepancy affect the overall regional differences in the synergy of MES and MHQD, we use the method of Dagum Gini coefficient and its decomposition to explore the magnitude, sources and evolutionary dynamics of the differentiation in the level of synergy. The formula is as follows (Equation 4):

In which k represents the total number of coastal regions, j and h is a regional subscript, n indicating the number of provinces and cities, i and m indicating the subscripts for provinces and cities, respectively. n j ( n h ) represents the number of provinces and cities within region j ( h ) , R j i ( R h m ) is a measure of the level of synergistic development of the provinces and cities i ( m ) in j ( h ) region, while R ¯ denotes the mean value of the coupling coordination of all examined Provinces and cities. The overall differences are decomposed into three parts: intra-group contribution ( G w ), inter-group net contribution ( G n b ), and intensity of transvariation ( G t ), G = G w + G n b + G t (Zhang et al., 2021a; Li et al., 2022).

Kernel density estimation is a method of applying continuous density profiles to describe the spatial distribution of a variable (Yu et al., 2021; Zhang et al., 2021a). We employ the method here to analyse the dynamic evolution trends of spatial patterns of distributional location, morphology, and polarization characteristics. We adopt the Gaussian kernel function in this paper (Chen et al., 2019).

We select the 3MMECs in China as a study area, involving 11 coastal provinces and cities (excluding Hong Kong, Macao, and Taiwan). Among them, the Northern Maritime Economic Circle (NMEC) consists of the regions of Tianjin, Hebei, Liaoning, and Shandong. The Eastern Maritime Economic Circle (EMEC) consists of the regions of Jiangsu, Shanghai, and Zhejiang while the Southern Maritime Economic Circle (SMEC) includes Fujian, Guangdong, Guangxi, and Hainan. The data are mainly obtained from the 2009-2020 China Marine Statistical Yearbook, China Marine Economy Statistical Bulletin, China Marine Ecological Environment Status Bulletin, and statistical yearbooks of coastal provinces and municipalities directly under the central government, etc. The missing data are estimated by using the trend extrapolation method and interpolation method.

We employed the ArcGIS10.8 software to explore the spatial distribution of the level of synergy of MES and MHQD. From 2009-2020, the evolution trend in the level of synergy between MES and MHQD has shown an incremental fluctuation, and there is a significant non-equilibrium development between different circles. EMEC had the highest coordination level, followed by NMEC and SMEC. The reason for this is that there are significant regional differences among these circles, leading to severe polarization and hindering the mutual promotion and coordinated development of the composite systems ( Figure 2 ). The level of synergistic development of composite systems was distributed into four types, i.e., primary Coordinated, barely Coordination, on the verge of dissonance and mild dissonance ( Figure 3 ; Table 3 ), and underwent the period of development, transitional and acceptable period of dissonance. Specifically, in 2009, Shandong, Jiangsu, Shanghai, and Guangdong as high-level regions were in the stage of barely coordinated, while Tianjin, Hebei, Liaoning, Zhejiang, and Fujian were on the verge of dissonance. From 2013 to 2017, the synergistic development of the composite system has undergone dynamic adjustments, resulting in an overall improvement. By 2020, with the advancement of the sustainable marine development goals, the regions that originally had a higher level of coordinated development among the 3MMEC are further developing. The characteristics are manifested by the fact that Shandong, Jiangsu, Shanghai, and Guangdong have consistently been high-level regions in the coordinated development of the marine complex system, belonging to the primary coordination and barely coordinated levels, indicating that there are regional high-level areas within each of the 3MMECs. The analysis also shows that Guangxi and Hainan have consistently been at a level of mildly dissonance and are considered low-level regions in terms of coordinated development. Liaoning, Zhejiang, and Fujian have transitioned from on the verge of dissonance in 2009 to a level of mildly dissonance in 2020, and these provinces are concentrated in the NMEC and SMEC. Tianjin and Hebei, which are located in the NMEC, are at a level of on the verge of dissonance. The results of these classifications indicate that there is significant regional heterogeneity among 3MMECs, and there is also a degree of spatial imbalance within each circle.

The previous sections (sections 4.3) revealed the spatial imbalance characteristics of the coordinated development level of MHQ-MES composite system. To further explore the factors influencing regional differences, we here construct a spatial weight matrix with economic implications and introduces a spatial econometric model to analyse the key driving factors causing the differences in the level of coordination of the composite system, as well as to examine their impact magnitude and spatial spillover effects. The results of the Hausman test indicate that a fixed effects model should be chosen ( Table 6 ). The LM test results show that, except for the LM-err test which is not significant, both the Robust LM-err, LM-lag, and Robust LM-lag tests have passed the 1% significant level test. Overall, the spatial lag model appears to be slightly superior to the spatial error model; the LR test indicates that the spatial Dubin model (SDM) cannot be degenerated into a Spatial Autoregressive model (SAR) or a Spatial Error Model (SEM).

Therefore, we choose the SDM with spatial fixed effects for the analysis of influencing factors. We obtain the results of the total, direct, and indirect effects ( Table 7 ), the sign of the spatial lag coefficient “ρ” is significantly positive, and there is a positive spatial correlation in the degree of coupling coordination of MES and MHQD among 3MMECs, with significant spatial spillover effects, which validates the rationality of the spatial measurement model construction.

From the regression results at the national level, with the implementation of the “science and technology to develop the sea” strategy, “innov” has a positive driving effect on the synergy of MES and MHQD. The direct effect coefficient is 0.083, and the indirect effect coefficient is 0.0747, passing the test of significance level of 1% and 10%, respectively. The spatial spillover effect of “struc” on local and neighbouring areas is not significant. Industrial restructuring can revitalize economic vitality, but the spatial spillover effect of synergistic between MES and MHQD in local and neighbouring areas is not significant in a short period of time. The direct and indirect effects for “open” are 0.0351 and 0.1353, respectively, both of which pass the 1% significance level test. With the benefit of China’s reform and opening-up policy, the spatial spillover effect on neighbouring regions is significant, while the neighbouring regions can effectively benefit from the results of the region’s opening-up policy. The direct effect and indirect coefficient of “lab” both pass the 1% significance level test. Marine professionals, as a fundamental element in the growth of marine science and technology, play a decisive role in marine environmental protection. The positive indirect effect may be due to the sharing of scientific and technological achievements and the exchange of talents in the region, thus positively affecting the synergistic effect of the peripheral region-shaped composite system. The impact of “inter” on the local region has a positive but weak effect (0.0065), this probability is due to the lagged effect of policy adjustments. However, local impacts on neighbouring areas have not yet developed a statistically significant effect, so the focus is therefore on the influence of other factors. The direct effect coefficient of “wellb” is significantly positive, indirect effect is not significant. The reason may be that the social welfare policies of the region will attract the inflow of talents and other advantageous resources from the neighbouring regions, forming a “siphoning effect” on the neighbouring regions, thus making it difficult to promote the benign synergistic evolution of the composite system in the neighbouring regions.

We further discuss the effects of spatial effects by sub-region in order to compare the characteristics of the differences of different influencing factors of 3MMECs.

The direct effect coefficients of “innov” on the 3MMECs are all positive and pass the significance test of 1% and 5%, only the indirect effect coefficient for the NMEC passes the significance test and is significantly negative. Innovation-driven saves the consumption of resources and energy while promoting the transformation and upgrading of the marine economy, injecting new kinetic energy into the synergistic promotion of MES and MHQD. However, provinces of NMEC like Shandong with improved innovation capability enhance the “adsorption” effect on the innovation resources of the backward regions in the neighbourhoods, which further inhibits the benign spiral development of the composite system in the neighbouring regions.

The direct effect coefficients of “struc” on the EMEC and SMEC passed the significance level tests of 5% and 10%. The optimization and upgrading of industries have had a negative effect on the composite system of NMEC for a short period of time, but the overall impact is not significant. In terms of spatial spillovers, it shows a significant negative effect only on the SMEC. It shows that the industrial structure of the SMEC has obvious polarization effects and is susceptible to the negative influence of the “struc” from neighbouring provinces.

The direct effects of “open” on the 3MMECs are positive and tested at the 5% and 10% levels of significance, which are stronger than the indirect effects. This suggests that the implementation of marine international trade policies has a significant positive impact on the synergistic development of MES and MHQD, which is particularly strong in NMEC and EMEC. In terms of indirect effects, only the NMEC passes the significance test. The spatial “diffusion” effect led to a radiation-driven effect on the coordinated development of the neighbouring regions along the open route. At the same time, as an important “gateway” to the outside world, more attention has been paid to the restoration and improvement of the ecosystems.

The direct and indirect effects of “lab” on the 3MMECs passed the significance level tests of 1%, 5%, and 10%. In terms of spatial spillover effects, human capital has a significant positive contribution to the EMEC. There is a spatial “squeeze” effect of labour, which promotes the spillover of the coordinated development trend of the marine composite system in inter-regional exchanges, and effectively leads to the enhancement of the coordinated level of MES and MHQD in neighbouring provinces and cities. In SMEC and NMEC, the indirect effects are significantly negative. With economic and policy advantages, the “return effect” leads to the loss of human capital in neighbouring provinces, which in turn has a dampening effect on the coordinated development of composite systems.

The direct effect of “inter” did not pass the significance level test except for the SMEC. The coefficient of indirect effects on NMEC and EMEC are significantly negative. Local environmental regulation and preferential policies generate competitive advantages in relevant areas, which inhibits the coordinated development in the neighbouring regions. The central province led by Guangdong in SMEC, in collaboration with the remaining three provinces and cities, has effectively reduced the additional cost of marine environmental regulations by raising the standards of environmental regulations, and promoting the synergistic development of composite systems in the region.

The direct effect coefficients of “wellb” on the NMEC and EMEC are significantly positive while on the SMEC are insignificantly negative. The indirect effect coefficient on the NMEC and SMEC is significantly negative. The improvement of urban infrastructure support of NMEC and SMEC, especially the great abundance of education and medical resources, has produced a “siphon effect”, a phenomenon in which resource elements are gathered in resource-advantaged areas, which is conducive to the synergistic development of the region’s composite system.