Social and Livelihood Dependencies on Ocean Ecosystems

1. Outcome

This Circular provides guidance on compiling indicators of social and livelihood dependencies on ocean ecosystems, enabling practitioners to quantify how populations, households, and communities rely on marine and coastal natural capital for economic sustenance, food security, cultural identity, and wellbeing. Ocean ecosystems underpin the livelihoods of hundreds of millions of people globally, particularly in coastal communities where fishing, aquaculture, tourism, and other marine-dependent activities provide employment, food security, and cultural sustenance^[1]. Understanding and measuring these dependencies is essential for identifying vulnerable populations, assessing the social dimensions of ocean sustainability, designing policies that protect both marine ecosystems and the communities that depend on them, and informing just transition planning as coastal economies adapt to environmental and economic change.

Upon completing this Circular, readers will understand how to compile dependency indicators across four key dimensions: employment dependency (measuring reliance on ocean-dependent sectors for income and jobs), nutritional dependency (quantifying contributions of marine resources to food security and dietary adequacy), cultural dependency (documenting non-material values and traditional practices), and vulnerability (assessing exposure and adaptive capacity of ocean-dependent populations). The guidance supports compilation of indicators aligned with policy frameworks including SDG 1 (No Poverty), SDG 2 (Zero Hunger)--particularly Target 2.3, which explicitly references fishers among the small-scale food producers whose productivity and incomes should be doubled^[2]--SDG 5 (Gender Equality) through its treatment of women's roles in fisheries value chains, SDG 8 (Decent Work and Economic Growth), SDG 10 (Reduced Inequalities) through its attention to equity dimensions of ocean access, and SDG 14 (Life Below Water)--particularly Target 14.7 on increasing "the economic benefits to small island developing States and least developed countries from the sustainable use of marine resources"^[3].

This Circular provides decision-relevant indicators for coastal poverty assessment, just transition planning as marine industries adapt to climate change and sustainability constraints, food security monitoring in fish-dependent populations, and the design of small-scale fisheries co-management arrangements. It connects the ecosystem service flows documented in TG-3.2 Flows from Environment to Economy to the social accounting approaches described in TG-3.5 Social Accounts, providing the methodological bridge between biophysical ecosystem contributions and human wellbeing outcomes. It draws on the economic activity classifications established in TG-3.3 Economic Activity and complements TG-1.5 Fisheries Management by extending the analysis from resource extraction to the full social system of dependencies. For the foundational framework and standards overview, see TG-0.1 General Introduction and TG-0.2 Standards Overview.

2. Requirements

This Circular requires familiarity with:

• TG-0.1 General Introduction to Ocean Accounts -- for the conceptual framework connecting ecosystems to economic activity
• TG-0.2 Standards Overview -- for the international statistical standards underpinning ocean accounting, including SNA 2025, SEEA, and classification systems
• TG-3.3 Economic Activity Relevant to the Ocean -- for the ocean economy thematic and extended accounting framework, industry classifications (ISIC), and supply and use table methodology used to measure ocean economic activity
• TG-3.5 Social Accounts -- for the broader framework of social accounting including wellbeing, equity, and vulnerability dimensions

For guidance on measuring ecosystem service flows from ocean ecosystems to the economy, see TG-3.2 Flows from Environment to Economy. For documentation of traditional marine knowledge and customary practices, see TG-3.6 Traditional Knowledge Accounts. For detailed guidance on labour market measurement, including the concepts of compensation of employees and employment status, see the 2025 SNA Chapter 16 on Labour^[4].

3. Guidance Material

Ocean ecosystems provide essential contributions to human livelihoods through multiple pathways: directly through employment in ocean-based industries; through provisioning of food and other marine products; through cultural, spiritual, and recreational benefits; and through the regulating services that protect coastal communities from hazards^[5]. The SEEA Ecosystem Accounting framework describes these contributions as ecosystem services--"the contributions of ecosystems to the benefits that are used in economic and other human activity"^[6]. This Circular provides guidance on measuring the human dependencies on these services, focusing on the social and livelihood dimensions that extend beyond purely economic measures.

While TG-3.5 Social Accounts establishes the general framework for social accounting in the ocean context--covering wellbeing, employment, equity, and vulnerability as broad accounting dimensions--this Circular applies that framework specifically to the measurement of livelihood dependencies. The distinct contribution of TG-2.3 is its focus on the dependency relationship itself: how populations, sectors, and communities rely on ocean ecosystems, and how changes in ecosystem condition translate into livelihood impacts. Where TG-3.5 asks "what is the social state?", this Circular asks "how dependent are communities on ocean ecosystems, and what happens if those ecosystems change?"

The Statistical Framework for Measuring the Sustainability of Tourism (SF-MST) observes that measuring sustainability requires understanding "the range of direct and indirect effects and the wide spectrum of stakeholders involved"^[7]. This principle applies equally to ocean dependencies: understanding the full scope of how people rely on ocean ecosystems requires systematic measurement across multiple dimensions including employment, nutrition, culture, and vulnerability.

3.1 Livelihood Dependency Framework

A livelihood dependency framework organizes the multiple ways in which individuals, households, and communities rely on ocean ecosystems for their economic, nutritional, cultural, and social sustenance. The framework distinguishes between direct and indirect dependencies, and between material and non-material dimensions of dependency.

Figure 2.3.1: Livelihood dependency framework--pathways from ocean ecosystem services to wellbeing outcomes

3.1.1 Defining ocean-dependent livelihoods

Ocean-dependent livelihoods encompass all forms of work and subsistence activities that rely substantially on marine and coastal ecosystems. The 2025 SNA recognizes that measuring wellbeing and sustainability requires extending measurement "beyond income and consumption to include...human capital as a produced asset"^[8], capturing the skills, knowledge, and capabilities that enable people to derive livelihoods from ocean resources. Human capital in the context of ocean-dependent livelihoods includes not only formal education but also the traditional ecological knowledge, navigation skills, and resource management capabilities that coastal communities develop through sustained engagement with marine environments.

Ocean-dependent livelihoods can be classified into three tiers. This classification parallels but does not replicate the SF-MST distinction between "direct effects" and "indirect and induced effects"^[9]: while the SF-MST categories apply to economic impact measurement, the dependency tiers below describe the directness of the livelihood relationship to ocean ecosystems. Compilers should document which classification they adopt and how it maps to SF-MST or other frameworks used in their context.

Primary dependencies: Livelihoods directly engaged in harvesting marine resources or providing services within marine ecosystems. These include:

• Commercial fishing (industrial, semi-industrial, and artisanal)
• Subsistence fishing and gleaning
• Aquaculture and mariculture operations
• Seaweed and shellfish harvesting
• Marine tourism operations (diving, snorkelling, whale watching, sport fishing)

Secondary dependencies: Livelihoods in sectors that process, distribute, or add value to marine resources:

• Seafood processing and packaging
• Fish marketing and distribution
• Boat building and repair
• Fishing gear manufacture and supply
• Tourism accommodation and services in coastal areas

Tertiary dependencies: Livelihoods supported by the multiplier effects of ocean-based economic activity:

• Retail and hospitality in fishing communities
• Transport services for coastal trade
• Financial and professional services to ocean industries
• Public administration related to marine management

These tiers correspond to the ocean economy industry classifications detailed in TG-3.3 Economic Activity, which provides the ISIC-based framework for identifying and measuring ocean-dependent, ocean-related, and partially ocean-related industries.

3.1.2 Dependency indicators

Dependency indicators quantify the extent to which populations, sectors, or regions rely on ocean ecosystems. Key indicator categories include:

Employment dependency indicators:

• Share of employment in ocean-dependent sectors (percent of total employment)
• Number of persons employed in fishing, aquaculture, and marine tourism
• Share of household income derived from ocean-dependent activities
• Employment concentration ratio (ocean employment in coastal areas relative to national average)

Nutritional dependency indicators:

• Share of dietary protein from marine sources
• Per capita fish consumption (kg per year)
• Share of households relying on subsistence fishing for food security
• Value of subsistence marine harvests relative to household consumption

Economic dependency indicators:

• Ocean sector value added as share of GDP (see TG-2.5 Ocean Economy Structure)
• Export earnings from marine products as share of total exports
• Share of government revenue from marine resource access fees and licenses

Cultural dependency indicators:

• Number of communities with traditional marine tenure systems
• Participation rates in traditional fishing practices
• Cultural sites of marine significance per coastal area
• Intergenerational transmission of marine knowledge and skills

The SEEA Ecosystem Accounting framework supports these indicators by providing the methodology for measuring ecosystem service flows. The SEEA EA notes that "the ecosystem accounting framework also supports the recording of flows of intermediate services, which are flows of services between and within ecosystem assets...Recording these flows supports an understanding of the dependencies among ecosystem assets"^[10]. Extending this logic to social dependencies, recording the flows of ecosystem services to human users supports understanding of livelihood dependencies.

3.2 Employment Indicators

Employment in ocean-dependent sectors represents one of the most tangible measures of livelihood dependency. The SF-MST provides detailed guidance on employment measurement that can be adapted for ocean accounting^[11]. While TG-3.5 Social Accounts covers general ocean sector employment measurement, this section focuses specifically on compiling employment as a dependency indicator--that is, measuring how reliant communities and populations are on ocean-based employment rather than simply counting jobs.

3.2.1 Direct employment

Direct employment encompasses all persons engaged in activities that harvest marine resources or operate within marine spaces. SDG indicator 14.7.1 measures "Sustainable fisheries as a proportion of GDP in small island developing States, least developed countries and all countries"^[12], while employment measures provide the complementary livelihood dimension.

Key direct employment categories for ocean accounting include:

Fisheries employment:

• Commercial fishing vessel crews (by vessel size category)
• Artisanal and small-scale fishers
• Subsistence fishers (including those not fully captured in formal employment statistics)
• Aquaculture workers (marine and brackish water operations)

SDG Target 2.3 calls for doubling "the agricultural productivity and incomes of small-scale food producers, in particular women, indigenous peoples, family farmers, pastoralists and fishers"^[13]. Employment accounts should distinguish small-scale fisheries from industrial operations to support monitoring of this target.

The SEEA for Agriculture, Forestry and Fisheries (SEEA AFF) provides an integrated framework describing how "biophysical and management information relevant to agriculture, forestry and fisheries production can be integrated into the statistical framework"^[14]. This framework supports linking employment data to production and ecosystem condition data. For guidance on integrating fisheries stock assessment data with employment accounts, see TG-1.5 Fisheries Management.

Marine tourism employment: SDG Target 8.9 calls for implementing "policies to promote sustainable tourism that creates jobs"^[15]. Marine tourism employment includes:

• Tour operators for marine activities (diving, snorkelling, boat tours)
• Recreational fishing guides and charter operators
• Beach and coastal recreation facility staff
• Marine wildlife watching operators
• Coastal accommodation workers directly serving marine tourists

The SF-MST notes that "employment in tourism industries is known for the fact that it often consists of a small core of permanent staff complemented with staff with a temporary contract and on-call workers"^[16]. This seasonal and precarious employment pattern is common across marine tourism and affects vulnerability assessments.

Other direct ocean employment:

• Maritime transport workers
• Offshore energy sector employees
• Port and harbour workers
• Coastal construction and maintenance workers
• Marine research and conservation workers

3.2.2 Indirect employment

Indirect employment arises in sectors that supply goods and services to ocean-dependent industries. The SF-MST describes these as activities "in the supply chain of tourism characteristic products"^[17]--for ocean accounting, the analogous concept encompasses supply chains for fishing, aquaculture, marine tourism, and other ocean sectors.

Measuring indirect employment requires either:

• Input-output analysis to trace supply chain linkages
• Establishment surveys that identify suppliers to ocean industries
• Employment estimates based on intermediate consumption patterns

The SF-MST notes that full measurement of indirect effects "would also require a single reference location to have information on all of the other locations that are connected"^[18]. For practical compilation, countries may focus on key supply chain sectors known to have significant connections to ocean industries.

Key indirect employment categories include:

• Fishing equipment and gear manufacture
• Boat building and repair services
• Seafood processing and packaging
• Cold chain and transport logistics
• Marine fuel and supplies provision
• Professional and financial services to ocean industries

3.2.3 Induced employment

Induced employment results from the spending of wages earned in ocean-dependent sectors. When fishers, tourism workers, or seafood processors spend their incomes on housing, food, education, and other goods and services, additional employment is generated throughout the economy.

Induced effects are typically estimated using economic multipliers derived from input-output models. The SF-MST recommends that "at relevant places...there is discussion of the types of indirect and induced effects that might be considered as part of a wider analysis"^[19]. For ocean dependency indicators, induced employment estimates can illustrate the broader economic significance of ocean-based livelihoods but should be presented separately from direct and indirect measures.

Table 2 summarizes the data requirements and methodological approaches for compiling employment dependency indicators across the three tiers.

Table 2: Employment dependency indicator data requirements by tier

3.2.4 Employment characteristics

Beyond counting employment, ocean accounts should characterize employment quality using the decent work framework dimensions described in TG-3.5 Social Accounts. The 2025 SNA provides comprehensive guidance on labour market measurement, including employment status, compensation of employees, and the distinction between formal and informal employment^[20]. Key characteristics include:

Table 1: Employment characteristics relevant to ocean dependency analysis

The SF-MST recommends that employment data be compiled with these characteristics to assess social sustainability^[21]. For ocean accounts, such disaggregation reveals important patterns--for example, the high proportion of informal employment in small-scale fisheries, or the seasonal concentration of marine tourism employment.

3.3 Food Security and Nutrition

Marine ecosystems contribute fundamentally to global food security, providing essential protein, micronutrients, and fatty acids that support healthy diets^[22]. Understanding nutritional dependencies on ocean ecosystems is essential for both food security policy and for assessing the human welfare implications of ecosystem change. This section addresses the dependency dimension of marine food provisioning; for the ecosystem service flow perspective, see TG-3.2 Flows from Environment to Economy, Section 3.1 on provisioning services.

3.3.1 Protein dependency

Fish and other aquatic foods are a primary source of animal protein for billions of people globally, with particularly high consumption in coastal regions, Small Island Developing States, and countries with extensive traditional fishing cultures^[23]. SDG Target 2.1 calls for ending hunger and ensuring "access by all people...to safe, nutritious and sufficient food all year round"^[24].

Key protein dependency indicators include:

Per capita consumption:

• Fish consumption in kilograms per person per year
• Share of animal protein from aquatic sources
• Trend in fish consumption over time

Population-level dependencies:

• Number of persons deriving 20% or more of animal protein from fish
• Number of persons in fish-dependent communities (where fish provides majority of animal protein)
• Geographic distribution of protein dependency (coastal vs inland populations)

Nutritional quality:

• Contribution of fish to essential micronutrient intake (omega-3 fatty acids, vitamin D, iodine, zinc)
• Role of small fish in addressing hidden hunger (micronutrient deficiencies)

The SEEA Ecosystem Accounting framework treats biomass provisioning services as ecosystem contributions to "the growth of biomass of marine animals (e.g. fish and shellfish) that are captured for nutrition"^[25]. Nutritional dependency indicators measure the human welfare dimension of these provisioning services.

3.3.2 Subsistence harvesting

Beyond commercial fisheries, subsistence harvesting provides essential food for coastal and island communities, often without being captured in formal economic statistics. Subsistence fishing includes:

• Small-scale artisanal fishing for household consumption
• Gleaning of shellfish, seaweed, and other intertidal resources
• Reef fishing and spearfishing in traditional territories
• Harvesting of sea cucumbers, sea urchins, and other marine invertebrates

The SEEA EA notes that ecosystem services include contributions to both marketed and non-marketed benefits^[26]. For subsistence harvesting, the ecosystem service (fish provisioning) flows directly to households without entering market transactions. This treatment is consistent with the ecosystem service flow accounting in TG-3.2 Flows from Environment to Economy, which records provisioning services regardless of whether the resulting benefits enter markets. It also aligns with the artisanal fisheries coverage in TG-1.5 Fisheries Management, which addresses small-scale fisheries governance alongside industrial operations. SDG Target 14.b emphasizes the importance of providing "access for small-scale artisanal fishers to marine resources and markets"^[27].

Measuring subsistence dependencies requires:

• Household surveys capturing marine harvesting activities
• Participatory assessments with coastal communities
• Time-use surveys documenting harvesting activity
• Estimation of physical quantities harvested for own consumption

The monetary value of subsistence harvests can be imputed using local market prices for equivalent products. This valuation allows integration with economic accounts and comparison with formal sector production. The 2025 SNA provides guidance on valuing own-account production for inclusion in household income and consumption measures^[28].

3.3.3 Food security vulnerability

Food security encompasses four dimensions: availability, access, utilization, and stability^[29]. Ocean ecosystem dependencies affect each dimension:

Availability: Marine ecosystems supply fish and other aquatic foods. Changes in ecosystem condition (overfishing, habitat loss, climate impacts) directly affect food availability.

Access: Poverty, market structure, and governance arrangements determine which populations can access marine foods. Equity in access is addressed in TG-3.5 Social Accounts.

Utilization: Safe food handling, nutritional knowledge, and cooking practices affect how marine foods contribute to nutrition.

Stability: Seasonal variation in fish availability, stock fluctuations, and climate variability affect the reliability of marine food supplies.

Indicators of food security vulnerability related to ocean ecosystems include:

• Share of households reporting inadequate fish availability
• Price volatility of marine food products
• Seasonal patterns in fish consumption
• Alternative protein source availability for fish-dependent communities

3.4 Cultural and Recreational Dependencies

Beyond material livelihoods, ocean ecosystems support non-material dimensions of human wellbeing through cultural connections, recreational opportunities, and spiritual significance. The SEEA EA describes cultural services as "experiential and intangible services related to the perceived or actual qualities of ecosystems whose existence and functioning contribute to a range of cultural benefits"^[30]. While TG-3.2 Flows from Environment to Economy documents the ecosystem service flows themselves (Section 3.1.3 on cultural services), this section addresses the human dependency dimension--how communities and populations rely on these cultural services for their wellbeing and identity.

3.4.1 Cultural ecosystem services

Marine cultural services encompass:

Recreation-related services: The ecosystem contributions to recreational activities including swimming, diving, snorkelling, surfing, recreational fishing, and wildlife watching^[31]. Coral reefs, beaches, and marine protected areas attract visitors seeking marine recreation experiences. The SEEA EA notes that "recreation-related services are considered final ecosystem services since they are directly enjoyed by people"^[32].

Indicators of recreational dependency include:

• Visitor days to marine recreation areas
• Participation rates in marine recreational activities
• Economic expenditure on marine recreation
• Accessibility of marine recreation opportunities across population groups

Visual amenity services: The contribution of marine seascapes to aesthetic enjoyment and property values^[33]. Coastal views affect residential amenity, tourism attractiveness, and community identity.

Education and research services: The contribution of marine ecosystems to scientific research, environmental education, and the generation of knowledge^[34]. Marine research stations, coastal field sites, and marine education programs depend on functioning ocean ecosystems.

Spiritual, artistic, and symbolic services: The contributions to cultural identity, spiritual practices, and artistic inspiration^[35]. For many coastal and island cultures, the ocean holds profound spiritual significance that cannot be adequately captured through quantitative indicators.

3.4.2 Cultural identity and traditional practices

For Indigenous Peoples and traditional coastal communities, cultural dependencies on ocean ecosystems may be the most fundamental dimension of human-ocean relationships. The TNFD notes that "Indigenous Peoples and Local Communities manage or have tenure over" significant proportions of remaining intact natural areas^[36], with analogous relationships existing for traditional marine territories.

Cultural identity dependencies include:

• Traditional fishing practices and their role in cultural transmission
• Ceremonial and ritual uses of marine resources
• Oral traditions and stories related to the ocean
• Place-based identity connected to specific marine areas
• Traditional governance systems for marine resources (see TG-3.6 Traditional Knowledge Accounts)

Measuring cultural dependencies requires participatory and qualitative approaches, as described in TG-3.5 Social Accounts and TG-3.6 Traditional Knowledge Accounts. Both circulars emphasize the need for community-led methods that respect Indigenous data sovereignty. Quantitative proxies may include:

• Number of communities with active traditional marine tenure systems
• Participation rates in traditional fishing practices by age group
• Documentation of marine cultural heritage sites
• Rates of intergenerational transmission of marine knowledge

3.4.3 Tourism and recreation economies

Marine tourism represents a significant economic expression of cultural and recreational dependencies. SDG Target 14.7 calls for increasing "the economic benefits to small island developing States and least developed countries from the sustainable use of marine resources, including through sustainable management of fisheries, aquaculture and tourism"^[37].

Tourism dependency indicators connect to the broader ocean economy measurement described in TG-2.5 Ocean Economy Structure:

• Tourism GDP attributable to marine attractions
• Employment in marine tourism relative to total tourism employment
• International visitor arrivals motivated by marine experiences
• Revenue from marine protected area visitation

The SF-MST provides the statistical framework for "linking ecosystem accounting to measures of tourism activity"^[38], enabling integration of cultural ecosystem service flows with tourism economic accounts.

3.5 Vulnerability Indicators

Livelihood dependencies create vulnerabilities when the ecosystems or resources upon which livelihoods depend are subject to degradation, depletion, or disruption. The IPCC defines vulnerability as "the propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts and elements, including sensitivity or susceptibility to harm and lack of capacity to cope and adapt"^[39]. TG-3.5 Social Accounts provides the general vulnerability and resilience framework for ocean social accounts; this section applies that framework specifically to livelihood dependencies, focusing on how to measure the vulnerability that arises from reliance on ocean ecosystems.

3.5.1 Exposure to ocean-related risks

Ocean-dependent communities face multiple risks:

Ecological risks: Overfishing, habitat degradation, pollution, and invasive species can reduce the productivity of marine ecosystems and the services they provide. The SEEA EA describes ecosystem condition indicators that track these changes (see TG-2.1 Biophysical Indicators).

Climate risks: Ocean warming, acidification, sea level rise, and changing storm patterns directly affect marine ecosystems and coastal communities. SDG Target 14.2 calls for managing marine ecosystems "including by strengthening their resilience"^[40]. SDG Target 1.5 calls for building "the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events"^[41].

Economic risks: Volatile commodity prices, changing trade policies, and market disruptions can undermine the economic viability of ocean-dependent livelihoods.

Governance risks: Weak or inequitable governance arrangements may fail to protect community access rights or ensure sustainable management.

Exposure indicators include:

• Share of coastal population in areas exposed to sea level rise or storm surge
• Dependence on fish stocks assessed as overfished or uncertain
• Share of employment in sectors exposed to climate-sensitive marine conditions
• Concentration of livelihoods in single marine resources or activities

3.5.2 Sensitivity indicators

Sensitivity measures how significantly populations would be affected by changes in ocean ecosystems or disruptions to ocean-based activities:

Economic sensitivity:

• Share of household income from ocean-dependent sources
• Availability of alternative livelihood options
• Asset base and savings to buffer income losses
• Access to credit and insurance

Nutritional sensitivity:

• Share of dietary protein from marine sources
• Availability and affordability of alternative protein sources
• Nutritional status (particularly in children and pregnant women)

Social sensitivity:

• Poverty rates in ocean-dependent communities
• Age structure of workforce (older workers less adaptable)
• Social marginalization affecting access to support
• Housing and infrastructure quality in coastal settlements

3.5.3 Adaptive capacity indicators

Adaptive capacity encompasses the resources, institutions, and capabilities that enable communities to respond to change:

Human capital:

• Educational attainment in coastal communities
• Occupational skills transferable to other sectors
• Health status affecting work capacity

Social capital:

• Strength of community organizations and networks
• Collective action capacity for resource management
• Access to information and decision-making processes

Financial capital:

• Access to savings and financial services
• Insurance coverage for weather and market risks
• Access to credit for livelihood diversification

Institutional capital:

• Social protection coverage (see SDG indicator 1.3.1)^[42]
• Governance capacity for adaptive management (see TG-3.7 Governance Accounts)
• Policy support for livelihood transitions

The SF-MST notes that vulnerability assessment should consider "the dependence of tourism activity on a given water supply and the associated potential vulnerability of tourism activity"^[43]. The same principle applies to ocean dependencies: understanding the specific ecosystem services on which livelihoods depend, and the current and projected condition of those services, enables targeted vulnerability assessment.

3.5.4 Livelihood vulnerability indicator summary

Table 3 provides a summary of livelihood vulnerability indicators organized by the exposure-sensitivity-adaptive capacity framework. Each indicator is linked to the account type within the Ocean Accounts framework that supplies the relevant data.

Table 3: Livelihood vulnerability indicators by component

3.5.5 Composite vulnerability indices

Vulnerability indicators across exposure, sensitivity, and adaptive capacity dimensions can be combined into composite vulnerability indices that identify priority populations or areas for policy attention. The IPCC vulnerability framework^[39:1] and the TNFD approach to dependency analysis^[36:1] both provide conceptual foundations for such indices in the ocean context. Composite vulnerability indices should:

• Use transparent and replicable methodology
• Weight components based on local context and priorities
• Be validated through community consultation
• Be updated as conditions change
• Document the theoretical framework underpinning the choice of components and weights

For guidance on integrated indicator frameworks and quality assurance of composite indices, see TG-0.7 Quality Assurance.

4. Compilation Considerations

4.1 Data sources

Social and livelihood dependency indicators draw on diverse data sources:

Household surveys: Labour force surveys provide employment data; living standards surveys capture consumption and income patterns; specialized coastal community surveys can provide targeted dependency information.

Administrative records: Fishing licenses, vessel registrations, marine worker registrations, and tourism statistics provide administrative data on ocean sector participation.

Fisheries data: Catch statistics, vessel monitoring data, and stock assessments provide physical measures of resource extraction that can be linked to employment and livelihood data.

Participatory assessments: Community consultations and participatory mapping document dependencies not captured in formal statistics, particularly for subsistence activities and cultural dimensions.

For detailed guidance on data sources and collection methods, see TG-4.2 Survey Methods and TG-4.3 Administrative Data.

4.2 Compilation Procedure

This section provides a step-by-step procedure for compiling the core livelihood dependency indicators described in Section 3. The procedure assumes that basic ocean economy accounts have been compiled following TG-3.3 Economic Activity and that relevant household survey data are available. Compilers should adapt the procedure to national data circumstances.

Step 1: Compile ocean employment dependency ratio

Objective: Measure the share of total employment attributable to ocean-dependent sectors.

Data requirements:

• Labour force survey with industry classification at ISIC Rev. 4 4-digit level
• Fisheries registry or administrative records for fishing employment
• Tourism employment data disaggregated by coastal/marine tourism

Procedure:

1. Extract employment counts for ocean-dependent industries from labour force survey:

   • ISIC 0311 (Marine fishing)
   • ISIC 0321 (Marine aquaculture)
   • ISIC 50 (Water transport)
   • Coastal tourism share of ISIC 55 (Accommodation), 56 (Food and beverage services), 79 (Travel agencies)

2. Adjust for informal and subsistence employment using fisheries registry:

   • Cross-check survey totals against fishing license/registration counts
   • If survey underestimates artisanal/small-scale fishers, apply adjustment factor based on registry coverage
   • Document adjustment methodology in metadata

3. Sum employment across ocean industries to derive direct ocean employment total

4. Compute ocean employment dependency ratio:

   Ocean employment ratio = Direct ocean employment / Total employment

5. Report both absolute employment count and percentage share

Output: Ocean employment dependency ratio (percent), with metadata documenting survey source, reference period, and any adjustments for informal employment.

Step 2: Compile fish protein dependency ratio

Objective: Measure the contribution of marine-sourced protein to total animal protein supply.

Data requirements:

• Food balance sheet or household consumption and expenditure survey
• Fish catch statistics (commercial + subsistence)
• Protein content conversion factors by species or species group

Procedure:

1. Compile total fish supply from food balance sheet:

   • Domestic catch (commercial + estimated subsistence)
   • Plus imports, minus exports
   • Minus non-food uses (fishmeal, pet food, waste)
   • Equals fish available for human consumption (tonnes edible weight)

2. Apply protein content factor:

   Fish protein supply (tonnes) = Fish available for consumption (tonnes) × Average protein content factor

   Use species-specific factors where possible; otherwise apply regional average (typically 0.16--0.20, with 0.18 as common benchmark)

3. Compile total animal protein supply from food balance sheet:

   • Sum protein from meat, fish, dairy, eggs
   • Align reference period with fish data

4. Compute fish protein dependency ratio:

   Fish protein dependency = Fish protein supply / Total animal protein supply

5. Compute per capita fish protein:

   Per capita fish protein (kg/year) = Fish protein supply / Population

Output: Fish protein dependency ratio (percent) and per capita fish protein supply (kg/year), with metadata on protein conversion factors and data sources.

Step 3: Compile livelihood vulnerability index

Objective: Produce composite vulnerability index for ocean-dependent coastal community using exposure, sensitivity, and adaptive capacity components.

Data requirements:

• Spatial data on coastal flood and cyclone risk zones
• Household survey with income and asset modules
• Coastal community education and employment data
• Fish stock status assessments

Procedure:

1. Define the spatial unit for vulnerability assessment:

   • Coastal administrative unit (district, municipality)
   • Or specific coastal community
   • Document spatial boundaries and population

2. Compile and normalize exposure indicators (scale 0--1, higher = greater exposure):

   • Flood risk: Share of settlement in 1-in-50-year flood zone
   • Cyclone frequency: Annual average cyclone landfalls (past 20 years), normalized by maximum observed
   • Stock risk: Share of local catch from stocks assessed as overfished or uncertain
   • Compute exposure score as simple average of normalized indicators

3. Compile and normalize sensitivity indicators (scale 0--1, higher = greater sensitivity):

   • Income dependence: Average share of household income from fishing/ocean sectors (from household survey)
   • Housing quality: Share of households in informal or non-code housing
   • Dietary dependence: Share of animal protein from fish (from household consumption survey)
   • Compute sensitivity score as simple average of normalized indicators

4. Compile and normalize adaptive capacity indicators (scale 0--1, higher = greater capacity):

   • Educational attainment: Average years of schooling, normalized by national average
   • Financial inclusion: Share of households with savings account or insurance coverage
   • Livelihood diversity: Shannon diversity index of employment across industries, normalized
   • Compute adaptive capacity score as simple average of normalized indicators

5. Compute composite vulnerability index:

   Vulnerability index = (Exposure + Sensitivity - Adaptive Capacity) / 3

   The formula subtracts adaptive capacity because higher capacity reduces net vulnerability.

6. Interpret result using threshold classification:

   • 0.00--0.20: Low vulnerability
   • 0.20--0.40: Moderate vulnerability
   • 0.40--1.00: High vulnerability

Output: Composite livelihood vulnerability index (0--1 scale) with component scores, spatial unit definition, and interpretation guide.

Step 4: Document methodology and metadata

For all compiled indicators, document:

• Data sources (survey instrument, administrative system, reference period)
• Estimation methods (calculation formulas, adjustment factors, normalization procedures)
• Limitations and uncertainties (sampling error, coverage gaps, imputation methods)
• Quality assessment per TG-0.7 Quality Assurance

This documentation supports transparency and enables indicator updates in subsequent periods.

4.3 Worked Example

This section presents a worked numerical example for compiling the three core dependency indicators described in the compilation procedure (Section 4.2). The example uses synthetic data for a hypothetical Small Island Developing State (SIDS) to illustrate the calculation steps. Compilers should substitute national data sources as described in Section 4.1.

Employment dependency indicators

The ocean employment ratio measures the share of total employment attributable to ocean-dependent sectors. Direct ocean employment is compiled by summing employment across primary dependency categories using data from labour force surveys, fisheries registries, and tourism statistics.

Step 1 -- Sum direct ocean employment by sector:

Step 2 -- Compute the ocean employment ratio:

Ocean employment ratio = Ocean employment / Total employment

= 54,500 / 420,000 = 13.0%

Step 3 -- Estimate total ocean-dependent employment using an indirect multiplier:

Input-output analysis for the national economy yields an ocean sector employment multiplier of 1.8, meaning that each direct ocean job supports an additional 0.8 jobs in supply chains and induced spending.

Total ocean-dependent jobs = 54,500 × 1.8 = 98,100

Total ocean-dependent employment share = 98,100 / 420,000 = 23.4%

Compilers should report both the direct ratio (13.0%) and the multiplier-adjusted ratio (23.4%), noting the multiplier source and methodology. Multiplier estimates are sensitive to the scope of industries included and should be validated against input-output tables as described in TG-3.3 Economic Activity.

Nutritional dependency indicators

The fish protein dependency ratio measures the contribution of marine-sourced protein to total animal protein supply. Data are drawn from food balance sheets and household consumption surveys.

Step 1 -- Estimate fish protein supply:

Fish protein supply = Annual fish supply × Average protein content

= 45,000 tonnes × 0.18 = 8,100 tonnes fish protein

The protein content factor of 0.18 (18% of edible weight) is a standard conversion factor for mixed fish species; compilers should adjust this factor based on the species composition of the national catch.

Step 2 -- Compute the fish protein dependency ratio:

Fish protein dependency ratio = Fish protein supply / Total animal protein supply

= 8,100 / 32,000 = 25.3%

Step 3 -- Compute per capita fish protein supply:

Per capita fish protein = Fish protein supply / Population

= 8,100 tonnes / 2.1 million persons = 3.86 kg per capita per year

A fish protein dependency ratio of 25.3% indicates substantial nutritional reliance on marine resources. Values above 20% are commonly used as thresholds for identifying fish-dependent populations. Per capita fish protein supply can be compared against FAO global averages (approximately 3.3 kg per capita per year) to contextualize national dependency levels.

Livelihood vulnerability index

A composite livelihood vulnerability index aggregates exposure, sensitivity, and adaptive capacity indicators into a single summary measure, following the IPCC vulnerability framework referenced in Section 3.5. Each component is normalized to a 0--1 scale where higher values indicate greater exposure, greater sensitivity, or greater adaptive capacity respectively.

Step 1 -- Compile component scores for a coastal fishing community:

Step 2 -- Compute the composite vulnerability index:

Vulnerability = (Exposure + Sensitivity - Adaptive Capacity) / 3

= (0.72 + 0.65 - 0.45) / 3 = 0.92 / 3 = 0.31

Step 3 -- Interpret the result:

A vulnerability index of 0.31 indicates moderate vulnerability on a 0--1 scale. The formula subtracts adaptive capacity because higher adaptive capacity reduces net vulnerability. Compilers should note that:

• Values below 0.20 suggest low vulnerability (strong adaptive capacity relative to exposure and sensitivity)
• Values between 0.20 and 0.40 suggest moderate vulnerability
• Values above 0.40 suggest high vulnerability warranting priority policy attention

The example community scores high on exposure (0.72) and sensitivity (0.65) but has limited adaptive capacity (0.45), driven primarily by low savings and insurance coverage (0.35). Policy interventions targeting financial inclusion and livelihood diversification would improve adaptive capacity and reduce the composite vulnerability score.

For guidance on weighting, normalization methods, and quality assurance of composite indices, see TG-2.1 Indicator Design Principles and TG-0.7 Quality Assurance.

4.4 Decision Use Cases

This section describes four policy decision contexts where livelihood dependency indicators compiled following this Circular directly inform management choices. The use cases illustrate how dependency indicators translate into actionable policy insights.

Use Case 1: Coastal poverty targeting

Decision context: A national poverty reduction programme seeks to identify coastal communities requiring targeted support. Standard poverty headcount data exist but do not reveal which poor households also face high exposure to ocean ecosystem degradation.

Dependency indicators used:

• Ocean employment dependency ratio by coastal administrative unit
• Fish protein dependency ratio by household consumption survey cluster
• Livelihood vulnerability index combining exposure, sensitivity, and adaptive capacity

Application: Combine poverty mapping with dependency indicators to identify communities that are both poor and highly dependent on ocean ecosystems. Prioritize these "high-dependency, high-poverty" communities for interventions addressing both poverty and ecosystem resilience. Communities with high dependency but low poverty may require different policy responses focused on sustaining livelihoods rather than poverty alleviation.

Policy outcome: Improved targeting of social protection, livelihood diversification programmes, and ecosystem restoration investments to communities where both poverty and ecosystem dependency are high.

Use Case 2: Just transition planning for fisheries reform

Decision context: A country is implementing new fisheries regulations to reduce overfishing, which will reduce total allowable catch and eliminate some fishing licenses. Policy-makers need to identify which communities and workers will be most affected and design compensation and transition support.

Dependency indicators used:

• Employment dependency indicators by fishing community (direct, indirect, induced employment)
• Share of household income from fishing activities
• Employment characteristics (age, sex, educational attainment, alternative skill sets)
• Adaptive capacity indicators (access to credit, social protection coverage)

Application: Map the spatial distribution of fishing-dependent employment and household income shares against the proposed license reductions. Identify communities where >30% of employment depends on fishing and where adaptive capacity (education, alternative skills) is low. Design differentiated transition packages: early retirement for older fishers near retirement age; retraining and job placement for younger workers with transferable skills; direct income support for households with high fishing income dependency and limited alternatives.

Policy outcome: Socially equitable fisheries reform that protects livelihoods while achieving sustainability objectives, with compensation and support tailored to community-specific dependency profiles.

Use Case 3: Food security monitoring in coastal zones

Decision context: A Ministry of Health monitors national nutrition indicators and seeks to understand whether coastal populations face distinct food security risks related to marine ecosystem change or fishing access restrictions.

Dependency indicators used:

• Fish protein dependency ratio by region
• Share of households relying on subsistence fishing
• Nutritional quality indicators (contribution to micronutrient intake)
• Price volatility of marine food products

Application: Identify coastal regions where >40% of animal protein comes from fish and where subsistence fishing provides >20% of household consumption. Establish nutrition surveillance in these high-dependency zones to track changes in dietary adequacy alongside monitoring of fish stock status and coastal access. If fish protein dependency is high and fish stocks are declining, trigger contingency food security responses (school feeding programmes with alternative protein sources, nutrition supplementation, support for alternative protein production).

Policy outcome: Proactive food security interventions in fish-dependent populations, preventing malnutrition before it occurs by linking nutrition surveillance to ecosystem condition monitoring.

Use Case 4: Marine protected area design with livelihood safeguards

Decision context: A conservation agency plans to expand marine protected areas (MPAs) to meet biodiversity targets, but must ensure that MPA boundaries and management rules do not disproportionately harm fishing-dependent communities.

Dependency indicators used:

• Spatial distribution of fishing effort and subsistence harvesting
• Cultural dependency indicators (traditional marine tenure systems, culturally significant sites)
• Income and employment dependency by coastal community
• Alternative livelihood options available in affected areas

Application: Overlay proposed MPA boundaries with maps of fishing dependency and cultural significance. Identify coastal communities that currently derive >50% of income from areas proposed for strict protection. Adjust MPA boundaries to avoid complete exclusion of high-dependency communities, or design co-management zones where sustainable fishing and cultural practices continue under community governance. Where displacement is unavoidable, quantify affected livelihoods and design compensation mechanisms including alternative livelihood support and benefit-sharing from MPA tourism revenues.

Policy outcome: Conservation gains achieved without imposing uncompensated livelihood losses, with MPA governance structures that recognize and support the dependencies of coastal communities on marine ecosystems.

These use cases demonstrate that livelihood dependency indicators are not merely descriptive statistics but provide the empirical foundation for designing socially informed, equitable ocean governance decisions.

4.5 Spatial considerations

Livelihood dependencies are spatially concentrated in coastal communities, requiring attention to geographic disaggregation:

• Compile indicators for coastal administrative units separately from national totals
• Align social data boundaries with marine spatial units used in environmental accounts
• Identify hotspots where high dependency coincides with ecosystem stress

4.6 Temporal considerations

Dependencies may vary seasonally (monsoon fishing patterns, tourism seasons) and change over time (shifts in employment structure, declining fish stocks). Time series data enable:

• Identification of seasonal vulnerability periods
• Tracking of long-term dependency trends
• Assessment of livelihood transitions

5. Acknowledgements

This Circular has been approved for public circulation and comment by the GOAP Technical Experts Group in accordance with the Circular Publication Procedure.

Authors: UNSW, WRI, Rebecca Shellock, Cheryl Fernandez-Abila, Crystal Bradley

Reviewers: Kirsten Oleson

6. References