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Wang, S.;  Li, W.;  Xing, L. Marine Management. Encyclopedia. Available online: https://encyclopedia.pub/entry/27428 (accessed on 07 July 2024).
Wang S,  Li W,  Xing L. Marine Management. Encyclopedia. Available at: https://encyclopedia.pub/entry/27428. Accessed July 07, 2024.
Wang, Shuhong, Weiyao Li, Lu Xing. "Marine Management" Encyclopedia, https://encyclopedia.pub/entry/27428 (accessed July 07, 2024).
Wang, S.,  Li, W., & Xing, L. (2022, September 21). Marine Management. In Encyclopedia. https://encyclopedia.pub/entry/27428
Wang, Shuhong, et al. "Marine Management." Encyclopedia. Web. 21 September, 2022.
Marine Management
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This entry is adapted from the peer-reviewed paper 10.3390/w14172626

The ocean is the cradle of human life and provides abundant material resources for human beings. As an important source of modern economic commodities and social activities, it is not only the focus of sustainable ecological development but also of economic and societal development. If the study of the ocean is not improved upon with better statistics, models, systems, and security measures, societal and economic development of the ocean will face further problems. Therefore, the best way to utilize the ocean has become a key issue in current research. Meanwhile, amarine ecological damageppropriate methods and ideas to solve the problems facing marine economic development and marine management from different perspectives are discussed.

marine ecological damage economic system ecosystem

1. Marine Ecological Environment

1.1. Marine Ecological Environment Protection

1.1.1. Marine Ecological Loss Assessment and Compensation

The scientific definition of “marine ecological damage” is the premise of damage assessment and damage relief. However, no universally recognized definition of “marine ecological damage” is available at present, although many scholars and relevant legal systems of European and North and South American countries have elaborated on the concept of “ecological damage” or “environmental damage”. For example, Lahnstein [1] posits that ecological damage refers to “physical damage to nature; that is, damage to soil, water, air, climate, landscape, animals and plants living in it and their interactions”. E. S. Scheblyakov et al. [2] has defined the concept of environmental damage as “the change, deterioration, or destruction of any part or whole of environmental resources, resulting in adverse effects on human beings and nature”. In 2000, the European Union’s White Paper on Environmental Responsibility defined environmental damage as “including damage to biodiversity and damage in the form of polluted sites”. In 2004, the EU Environmental Responsibility Directive on the Prevention and Remedy of Environmental Damage (2004/35/CE) [3] clearly included “damage of Natural Resource Service” into the scope of what is considered “damage”.
Ecological damage assessment is an entire process, from the physical condition of ecological damage to the expression of monetary value. By confirming the ecological damage caused by human activities or pollution events, economic measurements of the damage are conducted, and the ecological damage is expressed with monetary indicators. Two problems are involved in determining the physical amount of ecological damage. The first is how to select a variable index that represents ecological damage (i.e., damage factor). The second is how to determine the amount of ecological damage. Cendrero [4] and de Mulder et al. [5] found that damage factors caused by reclamation mainly focus on fishery resources, mammals such as seals, habitat resources such as mangroves and coral reefs, wetland water quality, and coastal tourism resources such as beaches. Studies have also been conducted on marine ecological damage caused by toxic leaks and land-based pollution. For example, McConnell et al. [6] have all analyzed land-based pollution and other emergencies and evaluated the damage they cause to fisheries and beaches.
Compensation for ecological damage is based on the previous environmental utility level of individual members of the public who suffer losses, and standard compensation is the monetary amount that can ensure the integrity of environmental welfare on an individual level. Based on the above definition, several scholars have used environmental resource value assessment methods to conduct monetary assessments of resource or ecological damage in emergencies, such as oil spills and dangerous chemical leaks, and take this as the basis for measuring damages.

1.1.2. Coastal Zone Ecological Environment Management and Protection

Several scholars have studied ecological environment management modes of coastal zones. For example, Hassanali [7] proposed the use of more sustainable, fair, and feasible means to manage the current ecological environment of Trinidad and Tobago’s coastal region. Yu et al. [8] analyzed the main driving factors of reclamation in the Beibu Gulf of Guangxi and interpreted these factors to facilitate decision making for ecological and environmental management in the gulf’s coastal zone. Smith and Rodriguez–Labajos [9] analyzed an existing indicator system in coastal areas and compared this system with the needs of coastal stakeholders in developing countries, on the basis of which they proposed an indicator system that could be part of a systematic eco-environmental management framework for coastal zones.
Sea-level rise is also important to coastal ecological environment management. To ensure effective coastal ecological environment management, developed countries have specifically conducted monitoring studies on the impact of sea-level rise to identify changes in various natural systems, such as seawater intrusion, storm surge intensification, coastal erosion, and lowland inundation [10][11][12][13][14][15], which have, respectively, caused the expansion of seawater intrusion, inundation range, population migration, possible economic loss, and coastal wetland area loss in coastal zones, to reflect different types of impact and degrees of harm [16][17][18][19][20]. Although a comprehensive monitoring and management system for coastal ecological environment damage caused by sea-level rise has not yet been created, the development trend is gradually shifting toward comprehensive quantitative and fine management, with increased consideration provided to applying research results in coastal environment planning, design, and management.

1.2. Storm Surge Disaster Risk and Loss Assessment

The marine economy has increasingly become a new growth point for national economic development. In China, reliance on marine resources to achieve sustainable economic development against the current global marine background is an inevitable trend [21]. However, the role of this reliance in storm surge disasters should not be ignored when developing the marine economy. To reduce the possibility of storm surge disasters related to economic development and decrease losses from storm surge disasters, it is crucial to maintain a reasonable level of economic development. Although the current level of economic development along China’s coastal area is improving, it is still at a lower stage, which is not conducive to alleviating the degree of storm surge disaster losses. This urges China to actively seek methods to guide economic development and effectively consider the economic and ecological social benefits of coastal areas.
Storm surge disaster loss assessment is a systematic project involving a very wide range of methods, in which risk assessment is an important research focus. Storm surge disaster risk-assessment methods have been widely studied in European and North and South American countries and applied when conducting empirical research in various different cities. This research provides the scientific basis for formulating reasonable disaster-prevention plans and has achieved good results. The United States was the first country worldwide to conduct a national storm surge disaster risk assessment. In the early 1990s, the National Oceanic and Atmospheric Administration, in combination with the Federal Emergency Management Agency (FEMA) and state governments nationwide, conducted storm surge disaster risk-assessment work that shifted the focus of storm surge disaster prevention and mitigation in the storm surge disaster risk assessment and regionalization, providing auxiliary decisional support for government disaster prevention and mitigation departments.
In research on models and quantitative methods of disaster loss assessment, studies from the United States started earlier and achieved more results; however, a few are specifically for storm surge disaster loss assessment. The SLOSH model was first used to estimate storm surge loss in the United States in 1992. Water depth and ground digital elevation data were input into the model through a geographic information system (GIS) to determine the storm surge disaster risk area and estimate storm surge losses. The seven-step common methodology (CM) vulnerability assessment method proposed by the International Panel on Climate Change in 1997 established an assessment index system that considered five factors: social, economic, ecosystem, cultural, and historical heritage loss. Okuyama [22] added the time series concept to the static input–output model and constructed a dynamic input–output model to evaluate indirect economic losses caused by natural disasters. FEMA and the National Academy of Building Sciences developed the multi-disaster loss assessment model HAZUS-MH in 2003, which mainly examines three disaster types: earthquakes, hurricanes, and floods. In 2003, The United Nations Economic and Social Council for Latin America and the Caribbean proposed a set of methods to assess the socioeconomic impact of natural disasters, integrating loss assessments with long-term national (regional) socioeconomic development plans.
Furthermore, Narayan [23] used a computable general equilibrium model to assess tropical cyclone disaster losses and study their impact on a short-term macroeconomy. In addition, some scholars analyzed the input–output model, computable general equilibrium model, social accounting matrix, and disaster loss evaluation models (e.g., mathematical programming), and constructed a disaster-affected computable general equilibrium model to evaluate the indirect economic losses to associated sectors and associated areas resulting from the interruption of the water system in Portland, USA, caused by an earthquake disaster like the one that happened on February 28, 2001. Hallegatte [24] proposed a modeling framework based on an input–output table to examine the consequences of natural disaster losses during the reconstruction stage. Erdik and Else [25] established a new earthquake rapid-response system function to estimate the loss time of the city after an earthquake. Finally, Hayashi [26] noted that it is impossible to quickly assess economic losses after any natural disaster without post-disaster reconstruction plans and financial budgets.

1.3. Storm Surge Disaster Monitoring and Early Warning and Emergency Management

At present, relatively mature methods, such as satellites and marine and ground observation stations, have been used worldwide, to monitor and forecast typhoon storm surge formation, movement, type, and characteristics. China, the United States, the United Kingdom, Japan, and other developed countries have established storm surge disaster-prediction systems; however, research on storm surge disaster monitoring and early warning management is relatively sparse [27][28]. Regarding emergency management of storm surge disaster losses, the initial studies mostly focused on technical aspects such as GIS software specifications, spatial data acquisition technology, disaster models and their spatial distribution, and visualization results. Since then, scholars have gradually increased their research on natural disaster early warning management [29][30][31], and the application of GIS technology in storm surge disaster loss emergency response management has also attracted increasing attention. The success of storm surge disaster loss emergency management is affected by many factors, with the effectiveness of emergency management institutions being key to improving storm surge disaster loss emergency management efficiency. Sufficient resources and resource integration are crucial for emergency management to successfully deal with storm surge disaster losses. Furthermore, an emergency management auxiliary decision support system is important for the emergency management of storm surge disaster losses. The emergency management system of China and developed countries such as the United States, the United Kingdom and Japan has been relatively perfected. In the United States, FEMA developed a disaster assessment and simulation software system named HazUS-MH, forming a disaster emergency management mechanism based on risk management and the five-layer emergency management organization system of “federal, state, county, city, and community”. In addition, FEMA has applied GIS technology to predict the hazards of natural disasters. Furthermore, the Japanese government has also invested significant human and material resources to conduct technical research on disaster prevention and mitigation of storm surges, mainly including the country’s immediate response system and disaster prevention and rescue system.

2. Marine Ecosystem

2.1. Marine Eco-Economic System

The marine eco-economic system is a complex dynamic system, which includes three subsystems: marine economy, marine ecology, and marine society. From an impact mechanism perspective, Costanza [32] has argued that human beings are blindly driven by economic interests, which has seriously damaged the ocean and led to coastal disasters that cause sizeable economic, societal, and ecological losses. He has also posited that a common vision of sustainable utilization of the ocean should be developed. Beaumont et al. [33] proposed that materials and services to improve marine biodiversity could play a fundamental role in the effective utilization of marine ecosystems. From a development measurement perspective, Bolam et al. [34] and Vassallo et al. [35] have comprehensively evaluated marine economic development from aspects of the marine environment, marine organisms, and the marine ecosystem, in combination with the concept of sustainable development, and summarized the basis and methods for marine ecological evaluation.
In addition, Martinez et al. [36] showed the necessity of vigorously promoting the assessment of the marine ecological economy to realize the most valuable sustainable development in coastal areas. Jin et al. [37] scientifically evaluated marine fishery management by using the ecological and economic integration framework. Based on the economic data of coastal cities and marine ecological data, a general equilibrium model of the marine economy and the marine food chain model were combined to construct sub-models of economic and ecological systems, respectively. Armstrong [38] constructed an eco-economic model based on protected marine areas and explained how the marine economic system affects the marine ecosystem. Pioch et al. [39] proposed criteria for ecological, social, and economic benefits when studying issues in the field of marine economy.

2.2. Evaluating the Marine Ecological Environment Carrying Capacity

According to Bishop [40], environmental carrying capacity refers to the intensity of human activities that a region can permanently sustain under the conditions of an acceptable standard of living. The author stated that environmental carrying capacity refers to the ability of the natural environment or social environment system to bear human development activities without significant environmental degradation. Most studies on ecological carrying capacity are based on population ecology. Furthermore, carrying capacity can refer to “economic carrying capacity” or “ecological carrying capacity”. Ecological carrying capacity refers to the equilibrium point reached between the population and the environment in the absence of hunting and other disturbances. The absence of hunting or hunting at a normal level has little impact on the population, and ecological carrying capacity is only determined by limited habitat resources, and ecosystem carrying capacity is the maximum population that a specific ecosystem can support in a specific time.
According to the different ideas regarding how ecological carrying capacity should be measured, its evaluation methods can be divided into three categories. The first category includes comprehensive evaluation methods based on various index systems, including a comprehensive evaluation index system, an ecological footprint model, a state space method, and a supply-and-demand balance method. The second category is the product cycle comprehensive evaluation method, including the cure theory method and life cycle method. Finally, the third category comprises comprehensive evaluation methods that combine different disciplines and methods, including the natural vegetation net primary productivity evaluation method, the system dynamics method, and the “3S technology” comprehensive analysis method.
By combining the characteristics of the marine economy, scholars have inherited and innovated the methods used to evaluate ecological carrying capacity. For example, Adrianto et al. [41] used Tidung Island in Jakarta as a case study to evaluate tourism activities from the perspective of the impact on the island’s socioecological system through the coupling model of social and ecological carrying capacity, and then calculated the optimal carrying capacity to provide references for marine tourism management. Sun et al. [42] proposed a marine ecological carrying capacity framework and used the AHP–entropy-based TOPSIS method to evaluate marine ecological carrying capacity in Shandong Province from multiple perspectives. Du et al. [43] combined an energy system analysis of marine ranching and the accounting rules of the energy ecological footprint model to analyze the sources of uncertainty in the evaluation of marine ranching resources and environmental carrying capacity, and, based on the Dempster–Shafer evidence theory, reduced the uncertainty of the original model by introducing expert experience and an Emergy ecological footprint approach that considers uncertainty. Tang et al. [44] proposed the concept of spatial scenarios, which are highly unified in socioeconomic attributes, land cover, ecological function, and externalities, and can replace land use/land cover in the traditional three-dimensional ecological footprint model in order to establish a new coastal ecological carrying capacity assessment framework.

2.3. Marine Ecological Security

As the ocean’s strategic position becomes increasingly prominent, its ecological security also becomes increasingly important [45]. Although ecological security problems are mostly caused by humans’ improper use of resources and the environment, scholars increasingly believe that marine resources and environmental quality is deeply correlated with human society’s economic development level and environmental policy response [46]. Although marine resource development and utilization are necessary to realize “sea power”, the rapid development of regional marine economies at the expense of marine resources and the environment of consumption, so dominated by the economic development of the marine economy development mode must eventually lead to the exposure of marine resource depletion and environmental problems.
Therefore, with the continuous development and increasing utilization of the human marine economy, the concept of ecological security has been introduced into the marine field in an increasingly wide manner [47]. Marine ecological security refers to the state of equilibrium in which the marine ecosystem can maintain its structure and function undamaged or less damaged and provide balanced and stable natural resources for the sustainable development of human ecology, economy, and society within a certain spatiotemporal range. Unlike the narrow meaning of “marine ecological health”, marine ecological security incorporates more extensive content, which primarily includes three aspects: the security of the symbiotic relationship between marine ecology and the marine economy, marine ecological security, and marine economic security. All three constitute a causal order: the first is the security motivation of the latter two aspects and the second aspect provides the guaranteed security of ecological services for the third aspect.
Well-known ecologists, Ma et al. [48], first proposed their theory of a “socioeconomic–natural” composite ecosystem in 1984 [49]. This theory has provided a foundation for the development of the concept and related model of the coordinated development of the ecological economy and society. As a competitive symbiotic complex of social, economic, and ecological subsystems, the marine ecological security system not only involves unilateral ecological content but also a comprehensive ecological and economic system with complex coupling relationships [50]. However, there are still relatively few specialized works on marine ecological security, with most studies mainly exploring the concept definition, evaluation, and analysis of marine ecological security. Du and Gao [51] defined marine ecological security from the perspective of the ocean itself as the ability of the marine ecosystem to recover from a certain degree of threat and maintain a healthy state. Du and Sun [45] comprehensively considered the relationship between economic development and the ocean and posited that marine ecological security is a comprehensive balance between environmental protection, resource protection, and the sustainable development of economic activities.
The marine ecosystem is complex and dynamic but is also controllable [52]. Therefore, some scholars evaluated the current status of marine ecological security based on their own research to pave the way for further optimization. For example, Gao et al. [53] conducted a dynamic evaluation on the ecological security of Pingtan Island. Du and Gao [51] constructed an evaluation index system for the safety of marine ecological pastures and identified the best path for the ecological management of marine pastures. Meanwhile, some scholars have also made methodological and theoretical innovations. Considering the complex relationships among factors affecting marine ecological conditions, Wang [46] studied the evaluation of marine ecological security based on a neural network algorithm. Focusing on issues related to marine ecological security caused by the degradation of marine ecosystem services and functions, Huang et al. [54] constructed an evaluation index system for marine ecological services and standardized the evaluation criteria and weight determination method. Bogadóttir [55] evaluated and discussed the negative impact of economic growth on the ocean and the relationship between current ocean development strategies and long-term sustainability and human well-being.
Marine ecological security has an irreplaceable role in social, economic, and natural systems. Therefore, it is necessary to reasonably monitor and evaluate the protection effect of marine ecological security and effectively solve the contradiction between economic development and ecological protection [56]. However, although many achievements of marine ecological security assessment have developed from a simple description of concepts and definitions to a point at which an accurate quantitative assessment is performed (but most of all belong to the ecological theory of the lack of evaluation), the warning effect is small, and the existing research results cannot be directly used to solve the problems of the marine ecosystem. Therefore, it is necessary to conduct more in-depth research according to the marine ecosystem’s characteristics themselves [53].

3. Marine Accounting System

3.1. Statistical Accounting System of Marine Economy in China

China’s relatively complete statistical system was established in 1952 but did not include marine economic statistics at that time. In 1990, the State Oceanic Administration promulgated the National Marine Statistical Index System and Index Interpretation, which covers eight categories of marine industries, including marine transportation, coastal tourism, marine fisheries, marine minerals, marine energy, seawater utilization, the marine salt industry, and marine drugs. In 1993, the scope of the marine industry statistics in China’s Marine Statistics Yearbook was adjusted again to include seven categories: marine fisheries, the marine salt industry, ports and shipping, coastal international tourism, offshore oil and gas, marine science and technology and education, and marine services. In 1994, the “marine shipbuilding” industry was further added to the “China Marine Statistics Annual Report,” and “marine transportation” was replaced by “ports and marine transportation”. In 1995, the “Notice on Marine Statistics in Coastal Areas” was issued, marking the official start of marine economic statistics in coastal provinces and cities. This was the first marine economic statistical accounting system formulated by the State Oceanic Administration, which established the general framework of China’s marine economic accounting for the future, expanded the industrial scope of marine economic statistical accounting, and provided a foundation for the subsequent improvement of marine statistical accounting.
In 1999, to further improve the marine economic statistics and accounting system, the National Bureau of Statistics implemented the System of Comprehensive Statements of Marine Statistics, incorporating marine economic statistics and accounting into the national statistical accounting system, clearly defining coastal areas and coastal provinces (municipalities and autonomous regions), and clarifying the scope of marine economic statistics. Furthermore, according to the “Classification and Code of National Economy Industries”, the “Classification and Code of Marine Economy Statistics” was issued, which adjusted the principles and methods of classification of marine economy statistics, classified the marine economy statistics plan according to the order of the first, second, and third industries, increased the marine industry to 12 categories, and expanded the scope of accounting of marine economy industries. At the same time, the marine industry has made minor adjustments. These adjustments have clarified industry classifications, adapted to the needs of marine industry development, improved various types of marine economy industries, and refined classifications under each industry. In 2006, the State Oceanic Administration released the marine industry’s classification and those of related industries. Through splitting and merging, the marine economic activities are divided into three levels: large class, medium class, and small class. These classes solve the problem of statistical range overlap, expand the scope of marine economic statistics calculation, and achieve hierarchical statistical accounting for marine economic regions.
To fully reflect the overall development of the marine economy and its contribution to the national economy in the China National Economic Accounting System (2002) overall framework, basic principles and calculation methods are based on the coastal marine economic accounting systems in developed countries. In 2005, China issued the Marine Economic Accounting System Implementation Plan, which first created marine economic subject accounting and basic accounting, extended the calculation of the marine economic accounting system framework, and provided accounting content such as marine economic GDP accounting, the input and output of accounting, and fixed capital accounting, while at the same time building the ocean GDP accounting methods and models. It also called for nationwide accounting of gross marine product. In 2006, the National Bureau of Statistics approved the Gross Marine Product Accounting System, which was subsequently implemented nationwide in 2007. To adapt to economic development and changes, improve the statistical system and classification, and accurately reflect the final results of marine economic activities in a certain period, several revised versions of the Gross Marine Product Accounting System were released in 2008, 2011, 2013, 2016, and 2019. The latest revision of the Gross Marine Product Accounting System in 2019 is mainly applied to the calculation of the gross marine product and marine industrial infrastructure of coastal provinces and cities. The scope of industry calculation is determined according to the Classification of Marine and Related Industries, and the specific accounting results are published through the Statistical Bulletin of China’s Marine Economy [21].

3.2. Value Accounting of Marine Resource Assets

Marine resource assets accounting includes both physical quantity and value quantity accounting, which is the premise of value quantity accounting and can systematically show the actual ownership and consumption of marine resources in China and the flow of marine resource assets during the accounting period. The ultimate goal of marine resource assets physical volume accounting is value volume accounting, which requires asset valuation and adopts different valuation methods according to various development and utilization modes and resource attributes.
The asset-based management of marine resources must comprehensively consider national management requirements and accounting technical support, clarify the status and role of marine resources in the reform of natural resources and the ecological environment management system, and technologically connect environmental economic accounting with marine economic accounting [57]. Wang et al. [57] planned and designed an accounting table of expected service flows of marine ecosystems based on SEEA experimental ecosystem accounting and discussed the pricing of marine ecosystem services and the selection of asset discount rates. They also noted the possibility of using the NPV method to calculate marine ecosystem assets and create marine ecosystem asset accounts. Wang et al. [57] analyzed marine ecosystem services and their accounting and introduced the concept of the “fourth industry” on the basis of the current marine economic accounting framework, which is conducive to a more scientific assessment of the benefits, products, and services obtained from the ocean.
Although countries have made significant progress in expanding the scope of and improving the framework for marine accounting, only a few scholars have incorporated social and cultural factors into marine statistical accounting and ocean governance [58][59]. Thus, social and cultural values have not received due attention. Marine economic management decisions are also affected by incomplete information [60][61]. Perkiss et al. [62] suggests that critical accounting be incorporated into the marine statistical accounting framework to contribute to addressing issues in the ocean governance process, such as sustainability, subsidies, and illegal fishing.

3.3. Statistical Accounting Methods for the Marine Economy

The traditional statistical accounting of the marine economy ignores the prices or costs of the marine environment, which may not provide a scientific and accurate basis for the macrocontrol of marine undertakings and the formulation of marine policies. To accurately reflect the ecological and environmental costs paid during the development of the marine economy, as well as promote high-quality marine economic development, many scholars are committed to incorporating environmental prices or costs into statistical accounting for the marine economy and discussing how to build a green marine economy accounting system.

3.3.1. Stripping Coefficient Method

The stripping coefficient method can undoubtably be applied to the calculation of the total value of the marine economy, and its scientific nature has been widely recognized internationally. The main idea of this method is to select indicators reflecting marine and related industries from national income accounts and calculate the output value of marine-related industries by using the stripping coefficient. Many countries use this method to calculate the value of their marine economy. For example, Australia has mainly used the satellite accounts of the marine industry, industrial survey method, and general equilibrium model stripping method in marine economy evaluation research. In 1998, Canada issued a report entitled the “Contribution of Canadian Marine Industry to National Economy”, which proposed calculating the stripping coefficient by the proportion of stripping and calculating the total output value of the marine industry by the stripping coefficient.
In October 2002, China used the stripping coefficient for the first time to conduct marine economic statistics in a national survey of maritime employment. However, it is still a significant problem to determine the stripping coefficient of all the sea-related industries at present, and the proposed methods have their own limitations. The marine fishery service, marine oil and gas industry, marine passenger transportation, marine cargo transportation, marine technology service industry, marine fishery wholesale, and marine aquatic product retail industries are suitable for the stripping method to calculate the added value of the industry. How to construct the ocean coefficient stripping method in a manner that is suitable for different industries is a key step in marine economic statistics. Therefore, the actual situation of different marine industries should be fully considered in the process of marine industry stripping, so as to construct an accurate and effective ocean industry stripping coefficient.

3.3.2. Input–Output Table

In the early discussion on the contribution of the marine economy to GNP, the input–output table of the national economy was generally used to measure the contributions; however, no input–output table of the marine economy was compiled [63]. However, as the interrelationship between marine and coastal economies became clear, countries began to refine the marine industry sector data and improve the feasibility of compiling input–output tables of the marine economy. García-de-la-Fuente et al. [64] were the first to apply the input–output model to quantify and compare the economic contributions of marine recreational and commercial fishing to regional economies in Europe. Carvalho and Inacio de Moraes [65] quantified Brazil’s coastal and marine economy in 2015 by estimating and establishing the national input–output matrix of the marine sector, which was the first time that Brazil’s coastal economy and marine economy were presented using the input–output model. Suris-Regueiro et al. [66] also proposed an input–output approach to comprehensively estimate the economic impact of production in the activity sectors affected by ocean planning, including the total economic impact of direct, indirect, and induced impacts.
Although much research has been conducted on input–output theory at home and abroad, some problems remain in relation to theory and application. Due to the different national conditions of various countries, it is difficult to unify the definition and classification standards of marine economic sectors, the division scope of output and input indicators is still vague, and the statistical caliber is not uniform. However, input–output is generally calculated by value quantity, which lacks the basis of physical measurement and the standard of the value quantity calculation method. At the same time, no one has proposed and solved detailed problems such as the time delay and discontinuity when compiling the input–output table or how to compile the input–output extension table for years with unpublished data. Only by clarifying the classification system of the marine sector and specific input–output accounting methods, as well as the continuity of structure and producer prices, can specific and feasible solutions be made.

3.3.3. Marine Resources Balance Sheet

The compilation of the marine resources balance sheet plays an important role in promoting the statistical accounting of the marine economy. Although neither an authoritative theoretical framework nor a compilation method has been established at home or abroad, governments and scholars in Western countries have conducted many beneficial explorations into the accounting of natural resources and the environmental economy. Havranek et al. [67] showed that developed Western countries such as the United Kingdom and the United States have strengthened the definition and protection of marine resource property rights in the form of legislation. On this basis, marine resource asset accounting has been added to the work of natural resource asset accounting and is regarded as an important part of it. Obst et al. [68] studied the relationship between marine resource consumption and marine economic growth and further proposed that marine resources should be regarded as an important part of the national asset accounting system, positing that the changes in marine resource assets should be included in the assessment indicator system for marine ecological environment development. However, there are various types and structures for the compilation of the balance sheet of marine resources, including embedded statements, independent statements, and consolidated statements. Based on the accounting method of assets and liabilities of marine resources, the compilation of physical statement of assets and liabilities of marine resources can adopt the compiling procedure of classification before synthesis, the statistical principle of stock before flow, and the accounting method of physical assets and liabilities before value. In terms of an accounting system, the Integrated Environmental and Economic Accounting System (SEEA2012) and National Economic Accounting System (SNA2008), as the most internationally recognized natural resources accounting and national balance sheet compilation systems, have important reference significance for marine resource balance sheets. However, compared with other natural resources, the survey, monitoring and statistical accounting of marine resources are more difficult because the significant characteristics of marine resources, such as seasonality, fluidity, latent nature, complexity, and the monetary measurement conditions of natural resources and environment are not mature. Thus, the concrete implementation of the preparation of a balance sheet for marine resources is considerably difficult. It is also difficult for countries to have a unified standard in terms of the category, classification, and methods of accounting items. Therefore, disputes exist in the balance sheet compilation for marine resources in terms of the definition of property rights, technical methods, and elements of value accounting, which need to be resolved.

References

  1. Lahnstein, C. A market-based analysis of financial insurance issues of environmental liability taking special account of Germany, Austria, Italy and Spain. In Deterrence, Insurability, and Compensation in Environmental Liability: Future Developments in the European Union; Oxford University Press: Oxford, UK, 2003; pp. 305–307.
  2. Scheblyakov, E.S.; Farafontova, E.L.; Kurbatova, S.M.; Rakhinsky, D.V. On the concept and types of harm to the environment. IOP Conf. Ser. Earth Environ. Sci. 2020, 548, 062025.
  3. Directive 2004/35/CE of the European Parliament and of the Council of 21 April 2004 on Environmental Liability with Regard to the Prevention and Remedying of Environmental Damage. Regulation, European, T. E. P. & T. C. of. 2004.
  4. Cendrero, A.; Díaz de Terán, J.R.; Salinas, J.M. Environmental-economic evaluation of the filling and reclamation process in the Bay of Santander, Spain. Environ. Geol. 1981, 3, 325–336.
  5. de Mulder, E.F.J.; Van Bruchem, A.J.; Claessen, F.A.M.; Hannink, G.; Hulsbergen, J.G.; Satijn, H.M.C. Environmental impact assessment on land reclamation projects in the Netherlands: A case history. Eng. Geol. 1994, 37, 15–23.
  6. McConnell, K.E.; Morrison, B.G. Assessment of Economic Damages to the Natural Resources of New Bedford Harbor: Damages to the Commercial Lobster Fishery; Department of Agricultural and Resource Economics, University of Maryland: College Park, MD, USA, 1986.
  7. Hassanali, K. Improving ocean and coastal governance in Trinidad and Tobago—Moving towards ICZM. Ocean Coast. Manag. 2015, 106, 1–9.
  8. Yu, G.H.; Liao, Y.Q.; Liao, Y.; Zhao, W.; Chen, Q.; Kou, J.; Liu, X. Research on integrated coastal zone management based on remote sensing: A case study of Guangxi Beibu Gulf. Reg. Stud. Mar. Sci. 2021, 44, 101710.
  9. Smith, D.J.; Rodríguez-Labajos, B. Turning the wheel away from biophysical indicators in coastal zone management: Towards a stakeholder-based systemic framework. Ecol. Indic. 2021, 125, 107527.
  10. Dean, R.G. Equilibrium Beach Profiles: USA Atlantic and Gulf Coasts. Ocean Engineering Report No 12; Department of Civil Engineering, University of Delaware: Newark, DE, USA, 1977; pp. 35–42.
  11. Bray, M.J.; Hooke, J.M. Prediction of soft-cliff retreat with accelerating sea-level rise. J. Coast. Res. 1997, 13, 453–467.
  12. Cooper, J.A.G.; Pilkey, O.H. Sea-level rise and shoreline retreat: Time to abandon the Bruun Rule. Glob. Planet. Change 2004, 43, 157–171.
  13. Zhang, K.; Douglas, B.C.; Leatherman, S.P. Global warming and coastal erosion. Clim. Change 2004, 64, 41–58.
  14. Lee, E.M. Coastal cliff recession risk: A simple judgement-based model. Q. J. Eng. Geol. Hydrogeol. 2005, 38, 89–104.
  15. Brown, I.; Jude, S.; Koukoulas, S.; Nicholls, R.; Dickson, M.; Walkden, M. Dynamic simulation and visualization of coastal erosion. Comput. Environ. Urban Syst. 2012, 30, 840–860.
  16. Bodge, K.R. Representing equilibrium beach profiles with an exponential expression. J. Coast. Res. 1992, 8, 47–55.
  17. Bates, P.D.; De Roo, A.P.J. A simple raster-based model for floodplain inundation. J. Hydrol. 2000, 236, 54–77.
  18. Leckebusch, G.C.; Ulbrich, U. On the relationship between cyclones and extreme windstorm events over Europe under climate change. Glob. Planet. Change 2004, 44, 181–193.
  19. Dawson, R.J.; Hall, J.W.; Bates, P.D.; Nicholls, R.J. Quantified analysis of the probability of flooding in the Thames Estuary under imaginable worst-case sea level rise scenarios. Water Resour. Dev. 2005, 21, 577–591.
  20. Cohen, M.J.; Brown, M.T.; Shepherd, K.D. Estimating the environmental costs of soil erosion at multiple scales in Kenya using emergy synthesis. Agric. Ecosyst. Environ. 2006, 114, 249–269.
  21. Song, M.L.; Pan, X.F.; Pan, X.U. Assessment of China’s marine ecological carrying capacity. In Sustainable Marine Resource Utilization in China; Song, M., Pan, X.-F., Pan, X.-Y., Eds.; Elsevier: Amsterdam, The Netherlands, 2020; pp. 29–62.
  22. Okuyama, Y. Economic modeling for disaster impact analysis: Past, present, and future. Econ. Syst. Res. 2007, 19, 115–124.
  23. Narayan, P.K. Macroeconomic impact of natural disasters on a small island economy: Evidence from a CGE model. Appl. Econ. Lett. 2003, 10, 721–723.
  24. Hallegatte, S. An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina. Risk Anal. 2008, 28, 779–799.
  25. Erdik, M.; Şeşetyan, K.; Demircioğlu, M.B.; Hancılar, U.; Zülfikar, C. Rapid earthquake loss assessment after damaging earthquakes. Soil Dyn. Earthquake Eng. 2011, 31, 247–266.
  26. Hayashi, M. A quick method for assessing economic damage caused by natural disasters: An epidemiological approach. Int. Adv. Econ. Res. 2012, 18, 417–427.
  27. Rabinovich, A.B.; Stephenson, F.E. Longwave measurements for the coast of British Columbia and improvements to the tsunami warning capability. Nat. Hazards 2004, 32, 313–343.
  28. Dube, S.K.; Poulose, J.; Rao, A.D. Numerical simulation of storm surge associated with severe cyclonic storms in the Bay of Bengal during 2008–2011. Mausam 2013, 64, 193–202.
  29. Wemer, M.G.F.; Schellekens, J.; Kwadyk, J.C.J. Flood early warning systems for hydrological (sub) catchments. Encycl. Hydrol. Sci. 2006, 15, 173–192.
  30. Tseng, C.P.; Chen, C.W. Natural disaster management mechanisms for probabilistic earthquake loss. Nat. Hazards 2012, 60, 1055–1063.
  31. Smith, K.L. The Surface Impacts of Arctic Stratospheric Ozone Variability; American Geophysical Union: Washington, DC, USA, 2013.
  32. Costanza, R. The ecological, economic, and social importance of the oceans. Ecol. Econ. 1999, 31, 199–213.
  33. Beaumont, N.J.; Austen, M.C.; Atkins, J.P.; Burdon, D.; Degraer, S.; Dentinho, T.P.; Derous, S.; Holm, P.; Horton, T.; van Ierland, E.; et al. Identification, definition and quantification of goods and services provided by marine biodiversity: Implications for the ecosystem approach. Mar. Pollut. Bull. 2007, 54, 253–265.
  34. Bolam, S.G.; Rees, H.L.; Somerfield, P.; Smith, R.; Clarke, K.R.; Warwick, R.M.; Atkins, M.; Garnacho, E. Ecological consequences of dredged material disposal in the marine environment: A holistic assessment of activities around the England and Wales coastline. Mar. Pollut. Bull. 2006, 52, 415–426.
  35. Vassallo, P.; Fabiano, M.; Vezzulli, L.; Sandulli, R.; Marques, J.; Jorgensen, S. Assessing the health of coastal marine ecosystems: A holistic approach based on sediment micro and meio-benthic measures. Ecol. Indic. 2006, 6, 525–542.
  36. Martínez, M.L.; Intralawan, A.; Vázquez, G.; Pérez-Maqueo, O.; Sutton, P.; Landgrave, R. The coasts of our world: Ecological, economic and social importance. Ecol. Econ. 2007, 63, 254–272.
  37. Jin, D.; Hoagland, P.; Morin Dalton, T.M. Linking and ecological models for a marine ecosystem. Ecol. Econ. 2003, 46, 367–385.
  38. Armstrong, C.W. A note on the ecological–economic modelling of marine reserves in fisheries. Ecol. Econ. 2007, 62, 242–250.
  39. Pioch, S.; Saussola, P.; Kilfoyleb, K.; Spieler, R. Ecological design of marine construction for socio-economic benefits: Ecosystem integration of a pipeline in coral reef area. Procedia Environ. Sci. 2011, 9, 148–152.
  40. Unsworth, R.E.; Bishop, R.C. Assessing natural resource damages using environmental annuities. Ecol. Econ. 1994, 11, 35–41.
  41. Adrianto, L.; Kurniawan, F.; Romadhon, A.; Bengen, D.G.; Sjafrie, N.D.M.; Damar, A.; Kleinertz, S. Assessing social-ecological system carrying capacity for urban small island tourism: The case of Tidung Islands, Jakarta Capital Province, Indonesia. Ocean Coast. Manag. 2021, 212, 105844.
  42. Sun, J.; Miao, J.C.; Mu, H.R.; Xu, J.; Zhai, N. Sustainable development in marine economy: Assessing carrying capacity of Shandong province in China. Ocean Coast. Manag. 2022, 216, 105981.
  43. Du, Y.W.; Wang, Y.C.; Li, W.S. Emergy ecological footprint method considering uncertainty and its application in evaluating marine ranching resources and environmental carrying capacity. J. Cleaner Prod. 2022, 336, 130363.
  44. Tang, Y.Z.; Wang, M.D.; Liu, Q.; Hu, Z.; Zhang, J.; Shi, T.; Wu, G.; Su, F. Ecological carrying capacity and sustainability assessment for coastal zones: A novel framework based on spatial scene and three-dimensional ecological footprint model. Ecol. Modell. 2022, 466, 109881.
  45. Du, Y.; Sun, X. Influence paths of marine ranching ecological security in China based on probabilistic linguistic term sets and qualitative comparative analysis. Int. J. Fuzzy Syst. 2020, 23, 228–242.
  46. Wang, X. A neural network algorithm based assessment for marine ecological environment. J. Coast. Res. 2020, 107, 145–148.
  47. Ke, X.; Mougharbel, A.; Guo, H.; Wang, D.; Wang, Y.; Min, F. Early warning simulation of urban ecological security in the Yangtze River Economic Belt: A case study of Chongqing, Wuhan, and Shanghai. J. Environ. Plan. Manag. 2020, 63, 1811–1833.
  48. Ma, C.; Wang, X.; Jiang, B. Ocean energy development under the background of carbon emissions peak and carbon neutrality in China. IOP Conf. Ser.: Earth Environ. Sci. 2022, 966, 012003.
  49. Bilgen, S.; Sarıkaya, İ. Exergy for environment, ecology and sustainable development. Renew. Sustain. Energy Rev. 2015, 51, 1115–1131.
  50. Wu, Y.W.; Wang, Y.-J.; Wang, Y.-L. Ecological security of economic belt from the symbiosis perspective—A case study of the Yangtze River Economic Belt. IOP Conf. S. Earth Environ. Sci. 2020, 568, 012008.
  51. Du, Y.; Gao, K. Ecological security evaluation of marine ranching with AHP-entropy-based TOPSIS: A case study of Yantai, China. Mar. Policy 2020, 122, 104223.
  52. Sheng, X.C.; Cao, Y.; Zhou, W.; Zhang, H.; Song, L. Multiple scenario simulations of land use changes and countermeasures for collaborative development mode in Chaobai River region of Jing-Jin-Ji, China. Habitat Int. 2018, 82, 38–47.
  53. Gao, S.; Sun, H.; Cao, G.; Zhao, L.; Wang, R.; Xu, M. Dynamic assessment of island ecological security under urbanization: A case study of Pingtan Island in the Southeast Coast of China. Environ. Earth Sci. 2018, 77, 531.
  54. Hao, H.; Bin, C.; Zhiyuan, M.; Zhenghua, L.; Senlin, Z.; Weiwei, Y.; Jianji, L.; Wenjia, H.; Jianguo, D.; Guangcheng, C. Assessing the ecological security of the estuary in view of the ecological services—A case study of the Xiamen Estuary. Ocean Coast. Manag. 2017, 137, 12–23.
  55. Bogadóttir, R. Blue growth and its discontents in the Faroe Islands: An island perspective on blue (de)growth, sustainability, and environmental justice. Sustain. Sci. 2020, 15, 103–115.
  56. Wimberly, M.C.; Narem, D.M.; Bauman, P.J.; Carlson, B.T.; Ahlering, M.A. Grassland connectivity in fragmented agricultural landscapes of the north-central United States. Biol. Conserv. 2018, 217, 121–130.
  57. Wang, T.; He, G.-S.; Zhou, Q.-L.; Gao, J.-Z.; Deng, L.-J. Designing a framework for marine ecosystem assets accounting. Ocean Coast. Manag. 2018, 163, 92–100.
  58. Martin, J.C.; Mongruel, R.; Levrel, H. Integrating cultural ecosystem services in an ecosystem satellite account: A case study in the Gulf of Saint-Malo (France). Ecol. Econ. 2018, 143, 141–152.
  59. Becker, N.; Lavee, D. Commercial development and conservation values: The case of Rosh Haniqra marine reserve in Israel. J. Infrastruct. Syst. 2009, 1, 193–217.
  60. Foley, P.; Pinkerton, E.; Wiber, M.G.; Stephenson, R.L. Full-spectrum sustainability: An alternative to fisheries management panaceas. Ecol. Soc. 2020, 25, 1.
  61. Stephenson, R.L.; Hobday, A.J.; Allison, E.H.; Armitage, D.; Brooks, K.; Bundy, A.; Cvitanovic, C.; Dickey-Collas, M.; Grilli, N.M.; Gomez, C.; et al. The quilt of sustainable ocean governance: Patterns for practitioners. Front. Mar. Sci. 2021, 8, 630547.
  62. Perkiss, S.; McIlgorm, A.; Nichols, R.; Lewis, A.R.; Lal, K.K.; Voyer, M. Can critical accounting perspectives contribute to the development of ocean accounting and ocean governance? Mar. Policy 2022, 136, 104901.
  63. Kwak, S.J.; Yoo, S.H.; Chang, J.I. The role of the maritime industry in the Korean national economy: An input-output analysis. Mar. Policy 2005, 29, 371–383.
  64. García-de-la-Fuente, L.; García-Flórez, L.; Fernández-Rueda, M.P.; Alcázar-Álvarez, J.; Colina-Vuelta, A.; Fernández-Vázquez, E.; Ramos-Carvajal, C. Comparing the contribution of commercial and recreational marine fishing to regional economies in Europe. An input-output approach applied to Asturias (Northwest Spain). Mar. Policy 2020, 118, 104024.
  65. Carvalho, A.B.; Inácio de Moraes, G. The Brazilian coastal and marine economies: Quantifying and measuring marine economic flow by input-output matrix analysis. Ocean Coast. Manag. 2021, 213, 105885.
  66. Surís-Regueiro, J.C.; Santiago, J.L.; González-Martínez, X.M.; Garza-Gil, M.D. Estimating economic impacts linked to marine spatial planning with input-output techniques. Application to three case studies. Mar. Policy 2021, 129, 104541.
  67. Havranek, T.; Horvath, R.; Zeynalov, A. Natural resources and economic growth: A meta-analysis. World Dev. 2016, 88, 134–151.
  68. Obst, C.; Vardon, M. Recording environmental assets in the national accounts. Oxf. Rev. Econ. Policy 2014, 30, 126–144.
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