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  • Large, industrial, fisheries and smaller scale fisheries are two very different areas with differing international data collection requirements and levels of interest domestically. Extensive data is held on industrial fisheries, including comprehensive stock assessments for many species. Industrial fisheries face transboundary issues where the fish move freely between EEZs and therefore inclusion in Ocean Accounts needs to be carefully thought through. Measurement of small-scale fisheries, reefs and associated ecosystems is challenging. Within the Pacific only a handful of countries have comprehensive vessel registries, with most not collecting comprehensive catch data. Often best available data on small scale and domestic coastal fisheries are from the Household Income and Expenditure Surveys (HIES) which now has a standard fisheries module. As much of the small scale and coastal catches are subsistence or for local sale these do not appear in normal market surveys, export data or structured buying records of businesses. What data exists for small scale fisheries tends to be disparate and held across multiple institutions and access can be hard, or impossible, to get. As a result, measuring year-on-year changes will be challenging and attributing changes more so.

  • Recent research suggest species abundance (fish stocks) can be estimated from data-poor fish stock assessments, where a review of methods suggests a Bayesian hierarchical framework is the most feasible approach [1]. Further research suggests developing relative abundance indices based on spatially detailed fisher catch and effort data [2].

  • Current fisheries accounting approaches have recognized the differing needs of commercial and small-scale fisheries from a data collection and account maintenance perspective. Nationally-based efforts to develop fisheries accounts have performed pilot studies to focus on either commercial or small-scale fisheries, directed either by a government or international entity (non-profit, NGO, UN partnerships). Accounting pilot studies on commercial fisheries include:

    • Natural Captial Accounting and Valuation of Ecosystem Services (NCAVES) project in China, relating fishing intensity to the loss of ecosystem services and net effects on marine GDP in 2018

    • Phillipines use of a satellite accounting approach determined in 2018 the fishing sector contributed the largest share of the Philippine ocean economy at 29% [3] which is instrumental in guiding the monitoring and assessment of ocean-related economic targets set in the 2017-2022 Philippine Development Plan (PDP).

    • Canada’s Department of Fisheries and Oceans (DFO) collaboration with Statistics Canada to apply to the ocean accounts framework in a pilot project to harmonize key ocean-related data, include commerical fisheries contribution to marine GDP.

  • Small-Scale Fisheries Account Development examples include:

    • Fiji Bureau of Statistics compilation and annual publication of subsistence, informal, and small-scale aquaculture GVA as part of its GDP compilation.

    • Environmental Defense Fund’s (EDF) work on community-level fisheries in Baja California, Mexico since 2015 to create satellite fishery accounts at remote fishing villages.

    • International Institute for Environment and Development (IIED) development of a toolkit for small scale fisheries in Costa Rica in 2019 which provides the framework to mainstream values of small scale fisheries in national accounts.

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  • In addition to environmental (state of the ocean) and fisheries related ecosystem datasets, Andries et. al. (2018) have demonstrated the increasing opportunity of Earth Observation data to complement or even replace traditional ground‐based methods of collecting environmental and socio‐economic data. Examples include, indicators of economic growth (Henderson, et al., 2011), socio‐economic activities (Chen & Nordhaus, 2011), urbanisation impacts on the environment (Ma et al., 2012), daytime and night-time fishing activities (Waluda et al, 2004; Straka et al., 2015).

  • One important element related to economic activity is maritime transport and associated port operations. Over 80 % of world merchandise trade by volume is being carried by sea and maritime transport remains the backbone supporting international trade. Maritime traffic is monitored at national and regional level through an International Maritime Organisation (IMO) regulation which requires Automated Identification System (AIS) to be fitted aboard all ships of 300 gross tonnage and upwards engaged on international voyages, cargo ships of 500 gross tonnage and upwards not engaged on international voyages and all passenger ships irrespective of size. The regulation requires that the exchange of AIS shall include the ship's identity, type, position, course, speed, navigational status and other safety-related information - automatically to appropriately equipped shore stations, other ships and aircraft. This data is used to monitor and track vessels globally as AIS signals can be detected by both shore stations and by satellite.

  • Vessels engaged in fisheries activities also need to report their locations. The vessel monitoring system (VMS) is a satellite-based monitoring system which at regular intervals provides data to the fisheries authorities on the location, course and speed of vessels. AIS and VMS real-time, historical and traffic density data, are key elements for evaluating the maritime transport component within an Ocean Accounting framework. Further to this, the environmental signature of the maritime transport community on the ocean ecosystem can be monitored through Earth observation. One such example is the monitoring and reporting of oil spills from vessels. 

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[4] Available as a formatted report and concise table (links embedded).

[Figure on Data Platforms under development]

4.2.8 Modelling

  • In the past, measured data and modelled data relevant to the ocean are often used for different purposes and by different communities. However, an emerging approach is to consider measured datasets and modelled data within the same information infrastructure. That is, models can fill in gaps by estimating data from what has been observed in other locations or periods. Similarly, measured data can be used as additional input to models. Together, they can support the development of future scenarios.

  • The SEEA-EEA Expert Forum (UNSD 2015) suggested a review of ecosystem services models with the intent of better understanding opportunities for applying them for official statistics. A review was initiated, but not completed (Bordt, Jackson and Ivanov, 2015). The SEEA-EEA Technical Recommendations (United Nations, 2017) include a brief review of some ecosystem services-related biophysical models.

  • The term “modelling” for the purposes of this paper is intended to include any quantitative or qualitative approach used in the absence of measured data. This would include estimation, interpolation, projection and scenario approaches.

  • Other than estimating or projecting the provision of ecosystem services, models have also been developed to estimate fish stock dynamics, economic production/consumption, ocean and climate dynamics and potential impacts from natural disasters.

  • As with the ecosystem services-related models reviewed, it is expected that other models and the accounting approach could be mutually reinforcing: (a) estimating accounts data where data are unavailable and (b) using accounts data and classifications in models. Projecting future conditions are generally out of the scope of the SEEA itself, but the calculation of asset values depends on assumptions about the future stream of services. It has been suggested that to accomplish this, a baseline future scenario would be required. For example, estimating a future stream of services based on expected changes in the extent and condition of the stock. Table 32 and Figure 18 illustrate potential linkages between modelling approaches and Ocean Accounts.

  • Better linking accounts with models is one approach to linking individual models together. For example, models focussing on stocks could be linked to models on production and consumption if concepts and classifications were aligned.

  • Options to be explored include (a) using modelling approaches to estimate missing data in accounts, (b) using accounts to provide data to models, (c) using scenario approaches to estimate future conditions, and (d) other projection approaches.

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  • Decision-making about the ocean is increasingly informed by a range of laws, policies, and processes designed to pursue defined strategic objectives, and/or plan use of ocean space in an integrated manner. Prevalent features of ocean policy and governance in this context include:

  • Strategic development plans for the ocean economy, including the proliferating range of national “Blue Economy”, “Ocean Economy” and “Blue Growth” plans that establish multi-sectoral development objectives and targets aligned with diverse guiding principles. A regionally representative list of examples includes the European Union’s Blue Growth Strategy, South Africa’s Operation Phakisa Oceans Economy strategy, Fiji’s National Ocean Policy, and Chapter 41 of China’s 13th Five-Year Plan for Economic and Social Development focusing on “widening space” for the Blue Economy.

  • Marine spatial planning (MSP): is commonly defined as a public process of analysing and allocating the spatial and temporal distribution of human activities in marine areas to achieve ecological, economic and social objectives that are usually specified through a political process. Diverse MSP approaches are implemented by at least 70 countries across all major regions.

  • Ocean Accounts can perform several support functions for strategic and planning decisions that may justify a decision to invest effort and resources to compile them. By virtue of their holistic and integrated structure, Ocean Accounts can be used as a basis for analysing the economic relevance of the ocean’s environmental assets, the environmental implications of ocean-based economic activity, and wide a range of other relationships that impact on the ability of countries to achieve sustainable development. This analysis supports the identification and evaluation of policy response options, in terms of their impacts on assets (environmental, social, economic) that underpin development, and on the flows of services and benefits from these assets.

  • More specifically, the Ocean Accounts Framework provides a basis for compiling three broad domains of aggregate indicators that are directly relevant to performance monitoring of ocean development strategy:

    • Ocean product, focusing on the economic outputs of human activity regarding the ocean, with monetary components aggregating to ocean Gross Domestic Product or net domestic product (NDP),

    • Benefits received by nationals from the ocean, including physical measures of ecosystem services, and monetary measures of ocean income that can be aggregated to net national income (NNI) and gross national income (GNI). Income measures can be (and benefit from being) disaggregated to show the importance of the ocean for different segments of the population, for example women, indigenous peoples, and other marginalised groups.

    • Change in the ocean balance sheet, which provide an important sustainability indicator when the balance sheet is sufficiently comprehensive including both environmental assets and other subcomponents of national wealth (e.g. SNA 2008 produced assets) recognised in the Ocean Accounts Framework.

  • Ocean Accounts also provide a holistic and coherent “common set of facts” consistent with the Marine Spatial Planning (MSP) framework, which aims to understand and allocate the human use of marine areas over space and time to meet social, economic and environmental targets. As such, MSP provides a framework for relating diverse sets of data, where plans are formed through the integration and consideration of:

    • Governance data to define MSP targets.

    • Socio-economic data to define human activities and the relationships of environmental goods and services with society.

    • Environmental and biophysical data inform the context of the area in which the plan will be implemented.

  • Whilst MSP is ideal for integrating diverse sets of data, there is a lack of standardised statistics or reporting structure between spatial plans at a regional or international scale. Frameworks for Socio-economic statistics and reporting exist and are widely applied (e.g. SNA) although are mostly limited to the national level and are heavily aggregated. Environmental and biophysical data are collected in the context of addressing discrete issues in space and time and are thus often opportunistic and incomparable.

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Table footnotes:

[1] https://soe.environment.gov.au/theme/coasts/topic/2016/integrated-coastal-management-frameworks, https://doi.org/10.1016/0964-5691(93)90020-Y 

[2] https://oceanpanel.org/sites/default/files/2020-05/BP14%20IOM%20Full%20Paper%20Final%20WebBP14 IOM Full Paper Final Web.pdf

[3] See: https://www.preventionweb.net/files/43291_sendaiframeworkfordrren.pdf

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  • Supplementary comments regarding disaster preparedness and response: Ocean accounting and DPR should seemingly go hand in hand. Preparedness for disasters both from a management standpoint and an economic viewpoint are essential to help maintain the stability and sustainability of a disaster-prone area, such as a coastal community or small islands. Analysis conducted by Phaup and Kirschner (2010) identify that budgeting and accounting for natural disasters oftentimes comes after the disaster. What they found was that in cases of pre-budgeting for disaster relief, there were both pros and cons. On the plus side, the policies set in place through this pre-budgeting determination will allow for a more stable and reliable method of allocating funding. Additionally, these policies can be used to provide financial incentives and opportunities to increase national savings, reduce risk exposure, and increase mitigation before disasters. Conversely, there then can be less consumption of those would-be savings.

  • Ocean accounting provides a structure and approach to measuring and accounting for ecosystem services in relation to disaster risk reduction using nature-based solutions. The European Union defines nature-based solutions as those that are “inspired and supported by nature, which are cost-effective, simultaneously provide environmental, social and economic benefits and help build resilience. Such solutions bring more, and more diverse, nature and natural features and processes into cities, landscapes and seascapes, through locally adapted, resource-efficient and systemic interventions." There are several examples of nature-based solutions to disaster risk reduction with respect to the ocean. For instance, healthy coral reefs act as natural breakwaters that significantly reduce wave energy and mangroves provide cost-effective coastal protection services from strong wind and waves resulted from hydro-meteorological disasters such as storms, cyclones and tsunamis; they are also essential habitats for aquatic resources which help improve lives and livelihoods of coastal communities.

  • Japan, New Zealand, and Turkey provide examples of how budgeting for national disasters, though the cases provided were earthquake related, primarily, can be an effective way to help recovery efforts and funding, mainly through national insurance programs. In regards to ocean accounting as a means for disaster risk tracking and response, but using what is known about the socioeconomic impact of oceans, from oil extraction, ecotourism, shipping, and other use cases, the valuation of our oceans can help determine what policy mandates are necessary to allocate funds for disaster tracking and response.

  • Supplementary comments regarding MPAs: The largest MPAs are offshore regions that include the water column and seabed, although protections may also extend to coastal environments, such as wetlands and estuaries.[4] There are several motivations for the designation of an MPA, such as the conservation or restoration of certain ecological and cultural features that are considered significant due to their vulnerability, rarity and uniqueness. Other MPAs may be formed for the protection and conservation of natural resources for research or sustaining socio-economic activities, such as nurseries for fisheries production.[5] MPAs are managed by governments at a variety of scales (local to international), with often complex governance and legislative structures. Cutting through the minutiaand bureaucracy of what the specific intent or definition of marine protected areas, at the core, conservation and management of aquatic resources are key.

  • Marine Protected Areas can be considered the spatial (and temporal) management of certain human activities, to protect, conserve and restore the ecosystem goods and services, and resulting benefits to society that these areas provide. MPAs recognise the pressures and impacts imposed by certain human activities and limit their intensity and distribution. Therefore, the designation of MPAs requires an understanding of ecological, social, and cultural significance of an area, in addition to the trade-offs from managing human activities on flows of ecosystem goods and services and resulting transfer of benefits. Ecosystem-based Marine Spatial Plans are ideally positioned to designate MPAs, as a means of balancing socio-economic and environmental values towards sustainable development.

  • Marine Protected Areas play crucial roles evidence of which is within scope of ocean accounting. They not only provide and transport goods and services for human well-being, but also they have inherent value beyond economics, in the form of “environmental costs sustained for the generation of natural stocks and ecosystem service flows.” A case study assessing the value of natural capital in the central Italian islands of Ventotene and S. Stefano was completed by using an energy accounting based model on biophysical and trophodynamic environments accounts. The natural capital was estimated based on the work done by the biosphere in the location of the model and used to determine the ecological value of natural capital stocks. The results of this case study provided support for policy makers and local managers to show the monetary and ecological value for developing MPAs.

  • In California, work is ongoing to show the linkages between two different acts: the Marine Life Management Act, aimed at improving and developing sustainable fisheries and best management practices, and the Marine Life Protection Act to implement a network of MPAs. The research is using the principles of ocean accounting, which this document may be able to help boost their work even more, to show how adaptive management of MPAs quantifiably improved fishery health and reduced environmental impact. Additionally, they would use the information from a life history model to show how the impact of increased resilience to environmental variability, such as climate change, found in an MPA, would benefit fisheries.

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  • Finance and investment decisions focus on the allocation of monetary resources from the public or private sector to maximise value, where the prioritisation of such values may be economic, environmental and/or social in nature. As noted in the World Economic Forum’s Ocean Finance Handbook, “Both investors and the projects that they invest in must be able to provide information on their performance, status and some means of forecasting for the future. These abilities rely on good data management—ranging from data collection to analysis and proper and secure storage. Without effective data management, it becomes nearly impossible to predict how much return on investment a project is likely to generate, and therefore what sort of investor to try to attract, or how to structure an investment proposition. It also impedes the ability for an investment project to be assessed once it is underway, to determine whether performance is meeting expectations and if not, to correct course.”

  • Gaps in investment-relevant data are particularly acute for environmental assets and associated flows of goods, services and risks. These gaps not only arise from the absence of relevant data, but from its fragmentation, accessibility and quality. The Ocean Finance Handbook further notes, “building a system to collect data, and to interpret data in order to provide the information investors need, is therefore a key pre-requisite for investment in the sustainable blue economy”.

  • Ocean Accounts support finance and investment decisions by providing standardised and integrated statistical time-series that cover connections between a wide range of social, economic and environmental circumstances, and provide the basis for generating relevant indicators and analyses. More specifically, they provide a reporting system that is thematically aligned with the growing range of criteria frameworks for public and private sector investment, including:

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  • Technical advice: All of the use cases summarised above depend on technical advice informed by analyses such as cost-benefit assessment, environmental and social impact assessments, and a wide variety of forecasting and modelling techniques. Ocean Accounts provide a broad-scope and standardised data input into the analytical processes, reinforcing the quality of analytical outputs. A range of technical advice use cases for SEEA Accounts are discussed in detail in SEEA 2012: Applications and Extensions —these apply equally to the Ocean Accounts Framework given the general compatibility of the latter with the former. The experimental components of the OAF concerning governance accounting are intended to support a wider range of technical analysis methods that rely on integrated use of qualitative and quantitative information, including but not limited to political economy analysis,[2] system dynamics modelling,[3] agent-based modelling,[4] and governance mapping.

  • Integrated reporting: The Ocean Accounts Framework provides a holistic structure, that can be used organise the information required for integrated reporting of social, economic and environmental conditions related to oceans. This includes reporting of progress towards national ocean-based and general development objectives, and international commitments including the Paris Agreement on Climate Change, Sendai Framework for Disaster Risk Reduction, Convention on Biological Diversity, and the Sustainable Development Goals (SDGs). In particular, Ocean Accounts facilitate the structuring of information relevant to SDG 14 and its ten associated Targets, which call on all countries and stakeholders to conserve and sustainably use the oceans, seas and marine resources for sustainable development.   

  • Meeting international commitments: The compilation of Ocean Accounts directly implements a range of international commitments, including but not limited to: SDG Target 15.9 calling on all countries and stakeholders, by 2020, to integrate ecosystem and biodiversity values into national and local planning, development processes, poverty reduction strategies and accounts; and SDG Target 17.19 calling on all countries and stakeholders, by 2030, to build on existing initiatives to develop measurements of progress on sustainable development that complement Gross Domestic Product, and support statistical capacity-building in developing countries. In addition to these commitments countries have agreed to comprehensive indicator frameworks for the major post-2015 commitments concerning sustainable development, namely the Paris Agreement on Climate Change, Sendai Framework for Disaster Risk Reduction, Addis Ababa Action Agenda on Finance for Sustainable Development, and the 2030 Agenda for Sustainable Development including the SDGs. A selection of specific links between Ocean Accounts and reporting against these commitments are discussed below.

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Figure 22 The availability of data to monitor and report on the indicators measuring the global targets of the Sendai Framework and disaster-related targets of the SDGs. Source: Sendai Framework data readiness review 2017 – Global summary report, UNISDR.

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4.4 Research use cases for Ocean Accounts

  • The structure and data provided by Ocean Accounts provides many opportunities for subsequent research by an interdisciplinary set of physical, biological, ecological, and social scientists. It is important that ocean accounting systems are proactively designed to be able to support a range of research inquiries, and that it be adaptive to results obtained from ongoing research (e.g., new metrics or indicators that should be included).

  • Trend analysis is a key potential use for the Ocean Accounts by researchers. With a reliable data sets at multiple scales that are collected at reliable time steps, researchers will be able to use accounts to evaluate how key metrics are evolving over time globally and within specified sub-global regions. For example, a researcher could investigate average global sea surface temperature trends and then evaluate how those trends are different or similar across ocean regions. Drivers for identified trends could then be hypothesized and identified.

  • Evaluation of interactions across metrics or indicators included in the ocean accounting system is another likely research use. By compiling consistent data across time and space on physical, ecological, and socioeconomic metrics, the accounting system provides a mechanism for understanding covarying indicators and the nature of their relationship (e.g., proportional or inversely proportional). For example, changes in sea surface temperatures can be correlated with observed changes in fish species distributions to determine if there is a positive correlation between the movement of species and temperature trends; this can also be combined with evaluation of global and national economic indicators for the fishing sector (e.g., its profitability) to evaluate the distribution of impacts from the temperature change. Appropriate controls for other potential drivers of change would need to be included.

  • Researchers may also make use of accounting systems to evaluate how political and policy structures influence trends in metrics included in the accounts. Controlling for other variables, this kind of a global data set may allow for improved evaluation of policies that are successful (or at least correlated with) moving an indicator from one level to another. For example, different fishery management systems can be compared with the collected data on fish species impacted by the various management systems.

  • The spatial nature of the data collected in the Ocean Accounts would allow for research into the varying global distribution of included indicators over time. This will allow researchers to spatially identify global hot spots of change (whether in fish species location, sea surface temperature, energy exploitation, or other topic areas). Such research can help disentangle broad average global changes to identify specific potential regional areas of concern.  

  • Finally, the accounts and the research analyses described above can provide guidance and a rationale for future lines of research inquiry. For example, identification of a correlation between a fish species and a sea surface temperature change can suggest further research into the causal mechanism for that correlation. A trend analysis showing a decline in the extent of an upwelling area may likewise prompt research into the drivers that may be causing that change. The advantage of a consistent, publicly available global data set is that it can provide this type of intellectual stimulation for a global network of researchers.

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