Global Ocean Accounts Partnership Secretariat · GOAP Technical Guidance on Ocean Accounting · circular
TG-1.3 applies the foundational Ocean Accounts concepts established in TG-0.1 to the specific governance context of marine spatial management and Marine Protected Areas. It bridges the Section 1 policy-decision guidance with the indicator derivation work in Section 2, demonstrating how extent and condition accounts compiled under SEEA EA methodology can directly inform MPA designation, effectiveness monitoring, and conservation finance decisions.
This Circular sets out how Ocean Accounts support marine spatial management decisions: Marine Protected Area designation and target tracking, effectiveness monitoring, and assessment of the economic impact of spatial restrictions.
Readers will learn how to apply ecosystem accounting outputs to three decision contexts:
For each, Section 3.2 states the account types required, the key indicators derived, and the operational procedure. Section 3.6 works a full before-after-control-impact assessment through to an ecosystem enhancement entry in the monetary asset account.
Indicator method is not set here. Condition variables are normalised and aggregated following TG-2.1 Aggregate Biophysical Indicators of Environmental State Sections 3.4 and 3.6, which is normative for this Circular, and asset valuation follows TG-3.1 Asset Accounts Section 3.5.3. For the broader spatial planning context within which MPAs sit, see TG-1.2 OA and Marine Spatial Planning.
Readers approaching Section 1 for the first time should begin with TG-1.0 Ocean Accounting and the Blue/Ocean Economy, the framing circular for the section, which sets out the ocean economy terminology used throughout, what an ocean account can and cannot certify about a blue economy claim, and the map from a policy question to the circular that answers it. It is recommended reading, not a prerequisite.
Marine spatial management encompasses the governance mechanisms through which human activities in marine areas are planned, regulated, and monitored. This includes Marine Spatial Planning (MSP), which organises the spatial allocation of ocean activities, and the designation and management of Marine Protected Areas (MPAs), which restrict or regulate activities in specific geographic areas to achieve conservation objectives. For UNCLOS maritime zone definitions (territorial sea, EEZ, continental shelf, ABNJ), see TG-0.6 Glossary (Exclusive Economic Zone entry). UNCLOS requires States to take measures to “protect and preserve the marine environment” (Part XII, Article 192) whilst recognising sovereign rights over resources within Exclusive Economic Zones (EEZs). Achieving conservation targets set by international agreements — including the Kunming-Montreal Global Biodiversity Framework target to protect 30% of marine areas by 2030 — requires reliable information systems to guide MPA designation, monitor outcomes, and support adaptive management.
The relevance of ocean accounts for marine conservation is recognised in CBD Decision 15/24 (2022), which encourages regional efforts towards ocean accounting and economic valuation of ecosystem services for marine and coastal biodiversity, and in related COP16 decisions on marine biodiversity.
Accounting boundary note: This Circular applies only to national marine waters (territorial sea and EEZ). Some MPAs straddle EEZ boundaries or are established under high-seas treaty frameworks — including the recently adopted BBNJ Agreement (2023) — and these scenarios introduce attribution and accounting boundary questions that are not yet standardised in SEEA EA or international guidance. Where an MPA straddles the EEZ boundary, compilers should restrict the national Ecosystem Accounting Area (EAA) to the EEZ portion and note the transboundary extent and any jointly managed area in account metadata. Guidance on fully transboundary and Areas Beyond National Jurisdiction (ABNJ) accounting is the subject of potential future GOAP Technical Guidance work. Cross-reference TG-1.2 OA and Marine Spatial Planning for transboundary MSP considerations.
Decision context: Countries must identify priority areas for protection to meet international commitments (Kunming-Montreal GBF Target 3: 30% of marine areas by 2030; SDG 14.5: at least 10% coverage) whilst ensuring ecological representativeness and connectivity. Designation decisions require baseline information on ecosystem distribution, condition, and irreplaceability.
Account types required:
Key indicators derived:
Operational procedure: Compilers first establish the EAA corresponding to national marine waters (territorial sea and EEZ). Ecosystem extent accounts are compiled using the IUCN GET marine ecosystem classification, at the spatial resolution set out in TG-2.12 Spatial Data Frameworks Section 3.3, which is normative for minimum mapping units and Basic Spatial Unit resolution. The question for an MPA agency is not what resolution to specify but whether the resolution of the accounts available for the area is fine enough to resolve the designation boundaries and habitat patches the decision turns on; where it is not, TG-2.12 Section 3.3 sets out the data sources that would improve it. Each BSU is attributed to an ecosystem type and protection status (IUCN categories Ia-VI, OECM, or unprotected).
The extent account aggregates BSU areas by ecosystem type and protection status, producing a cross-tabulation that reveals coverage gaps. Condition accounts are compiled for a subset of high-priority ecosystem types (typically coral reefs, seagrass, mangroves) using available monitoring data. Reference conditions are established from historical baselines, comparison with protected reference sites, or ecological modelling. The resulting extent and condition data inform spatial prioritisation, with high-condition unprotected areas and low-representation ecosystem types identified as designation priorities.
Decision context: MPA managers and conservation agencies must assess whether protection is achieving intended outcomes — maintaining or improving ecosystem condition — and whether management interventions (zoning, enforcement, restoration) require adjustment. Effectiveness assessment requires comparison of outcomes against expectations or counterfactuals.
Account types required:
Key indicators derived:
Operational procedure: Effectiveness monitoring requires establishing a baseline condition account at or near the time of MPA designation, followed by periodic re-compilation (annually for intensively monitored sites, every 3—5 years for standard monitoring). Condition variables are selected from the ECT based on data availability and policy relevance, with priority given to variables responsive to management interventions (e.g., coral cover, fish biomass, water quality for marine reserves). Each condition variable is normalised against its reference value to produce a condition indicator on a 0—1 scale, with indicators aggregated into an overall Ecosystem Condition Index using area-weighted averaging. Comparing ECI trends inside versus outside MPAs provides evidence of protection effectiveness. Where condition is improving, this is recorded as ecosystem enhancement in the asset account, and where declining, as degradation. Reliable effectiveness assessment rests on counterfactual comparison: compilers should establish comparable condition accounts for unprotected control sites matched to MPA characteristics.
Decision context: Policymakers must assess the economic implications of MPA restrictions on fishing, tourism, and other marine uses, balancing conservation benefits against livelihood impacts and economic opportunity costs. This requires integrated environmental-economic analysis.
Account types required:
Key indicators derived:
Operational procedure: Economic impact assessment begins with ecosystem services supply accounts that quantify service flows in physical units (tonnes of fish provisioned, volume of coastal protection service, recreation visitor-days). Supply is attributed to specific ecosystem assets (MPAs, adjacent fishing grounds) using spatial models that link ecosystem characteristics to service generation. Use accounts record which economic units (fishing enterprises, tourism operators, coastal households) receive these services. Monetary valuation applies methods consistent with SEEA EA Chapter 9: exchange values for provisioned fish, avoided damage cost for coastal protection, travel cost or contingent valuation for recreation. Comparing service values before and after MPA designation reveals net economic effects. Where MPA restrictions reduce extractive service flows (reduced fishing area) but enhance long-term service capacity (stock recovery, habitat restoration), the extended supply-use framework enables integrated assessment of short-term costs versus long-term benefits.
Where primary valuation data (travel cost surveys, contingent valuation studies) are not available, compilers should apply the following tiered framework:
For detailed guidance on ecosystem services valuation, see TG-2.4 Environmental (including Ecosystem) Goods and Services.
The accounting approach rests on three properties: completeness (covering all relevant ecosystem types within the MPA boundary), consistency (applying the same classifications and methods across accounting periods), and coherence (ensuring data from different sources can be integrated).
When an MPA is designated, compiling baseline accounts establishes the starting point against which future changes can be measured. Baseline ecosystem extent accounts document the spatial distribution of ecosystem types at the time of protection, providing the foundation for monitoring changes in habitat coverage — for example, detecting expansion or contraction of seagrass meadows or coral reef area.
Condition variables are selected and normalised following the procedure in TG-2.1 Aggregate Biophysical Indicators of Environmental State Sections 3.2—3.4, which is normative for this Circular. Every condition indicator in this Circular, including those in the worked example in Section 3.6, is derived using the TG-2.1 Section 3.4.1 transformation Indicator = (V -- L) / (U -- L), with the inverse-polarity and logarithmic-scale variants set out there. Both an upper reference (U) and a lower reference (L) are required for every linearly transformed variable; an upper reference alone is not sufficient. For marine ecosystems, relevant condition variables may include those summarised in Table 1.3.1 below. In the Ocean Accounts Framework (TG-0.1 General Introduction to Ocean Accounts), the economic pressures that drive changes in the chemical state variables — such as nutrient loading and pollution discharge — correspond to Edge E1 (pollution/residuals from economy to environment).
Table 1.3.1: Marine ecosystem condition variables relevant to MPA baselines
SEEA EA recommends measuring condition relative to a reference condition that reflects, where possible, the natural or undegraded state of the ecosystem (SEEA EA para 5.69). For marine ecosystems, establishing appropriate reference conditions may require drawing on historical data, scientific literature, expert knowledge, or comparison with similar unimpacted areas.
Table 1 illustrates a simplified ecosystem condition account structure for an MPA.
Table 1: Illustrative ecosystem condition account for a marine protected area
Lower reference values in this illustration are indicative. Compilers must establish both anchors from national or regional evidence and document them, following TG-2.1 Section 3.4.2.
Individual condition variables can be aggregated into composite condition indices to provide summary assessments of ecosystem health. An ECI value of 1 indicates reference condition, whilst values below 1 indicate degradation.
Aggregation methods, the default among them, and their implications for interpretation are set out in TG-2.1 Section 3.6. The worked example in Section 3.6 of this Circular uses the arithmetic mean across condition variables, and the area-weighted mean across habitat sub-accounts, in both cases following TG-2.1.
Figure 1.3.1 sets out the four sequential steps by which heterogeneous condition variables are measured, normalised against baseline condition, compiled and aggregated to a composite ECI, and then tracked across accounting periods.
· Figure 1.3.1
Source SEEA EA 2024 ch. 5 (ecosystem condition accounts, variables, indicators and reference levels); IUCN-WCPA protected-area management-effectiveness framework. See TG-1.3 (MPA condition assessment) and TG-2.1 (aggregate biophysical indicators).
For MPA management, condition indices can be constructed at different scales: individual ecosystem assets (e.g., a specific reef), ecosystem types within the MPA (e.g., all coral reef area), or the entire protected area. Tracking changes in these indices over time provides a quantitative basis for assessing whether management interventions are achieving conservation objectives.
SEEA EA provides explicit accounting treatments for changes in ecosystem condition. Ecosystem enhancement is defined as “the increase in the value of an ecosystem asset over an accounting period that is associated with an improvement in the condition of the asset during that accounting period” (SEEA EA para 10.15), whilst ecosystem degradation is defined as “the decrease in the value of an ecosystem asset over an accounting period that is associated with a decline in the condition of the ecosystem asset during that accounting period” (SEEA EA para 10.21). These accounting entries enable tracking of whether ecosystems within MPAs are improving (net enhancement), stable (no net change), or declining despite protection (net degradation).
The accounting framework distinguishes between changes due to human activity (recorded as degradation or enhancement) and changes due to natural processes (recorded as other changes in volume). This distinction is analytically important for MPA assessment — for example, distinguishing coral decline due to reduced local pressures (management success) from decline due to thermal stress associated with climate change (external driver). Attribution of observed condition changes to drivers should draw on expert assessment, scientific literature, or statistical attribution studies.
Where the source or causality of a condition change cannot be reliably attributed to either anthropogenic or natural drivers, compilers should not attempt to disaggregate the change between “degradation” and “other volume changes.” Instead, record the total condition change without attribution and document the limitation in account metadata. Recording the change without attribution mirrors the treatment in extent accounts, where planned and unplanned additions and reductions are recorded separately only when reliably known (SEEA EA para 10.21; see also SEEA EA guidance on extent-account planned/unplanned changes). Cross-reference TG-2.8 Climate Change Indicators for attribution approaches when climate drivers are a principal confound.
Where decline is observed in both protected and unprotected areas and scientific evidence links the decline to climate-driven thermal stress, the change may be attributed to natural processes (other volume changes) rather than management failure. Where decline is observed only in poorly enforced MPAs but not in well-enforced sites experiencing similar environmental conditions, the differential may be attributed to management effectiveness and recorded as anthropogenic degradation.
Changes in ecosystem services flow provide another dimension for assessing MPA effectiveness. Table 3.4.2 below summarises four ecosystem service effectiveness indicators that accounts can track to assess whether protection is maintaining or enhancing the capacity of marine ecosystems to deliver services.
Table 3.4.2: Ecosystem service effectiveness indicators for MPA assessment
For detailed guidance on compiling ecosystem services accounts for marine ecosystems, see TG-2.4 Environmental (including Ecosystem) Goods and Services. The combined presentation of ecosystem and economic accounts is addressed in TG-3.8 Combined Presentations.
Credible effectiveness assessment often requires counterfactual analysis — comparing outcomes within the MPA against what would have occurred without protection. The counterfactual approach requires selecting control sites that are comparable to the MPA in terms of baseline ecosystem characteristics, environmental conditions, and human pressure levels, but differ in protection status. Condition accounts are compiled for both MPA and control sites using identical variable selection, reference conditions, and aggregation methods. The difference in condition trends between MPA and control sites provides an estimate of the protection effect.
Three principal counterfactual designs are applicable:
Each design should be applied according to standard counterfactual-design practice for the specific study context. Minimum data requirements depend on the research question, expected effect size, and spatial and temporal grain of available monitoring data; no universal thresholds are prescribed here. Where none of the designs is feasible due to data limitations, compilers should report descriptive condition trends with an explicit caveat that causal attribution is not supported by the available data.
The 2030 Agenda for Sustainable Development includes SDG 14 “Life Below Water” with targets directly relevant to marine spatial management. SDG Target 14.5 calls for countries to “conserve at least 10 per cent of coastal and marine areas, consistent with national and international law and based on the best available scientific information,” with indicator 14.5.1 measuring “coverage of protected areas in relation to marine areas”. SDG Target 14.2 addresses sustainable management and protection of marine and coastal ecosystems, monitored through indicator 14.2.1 on “proportion of national exclusive economic zones managed using ecosystem-based approaches.”
Ecosystem extent accounts can directly inform reporting on protected area coverage, whilst condition and services accounts support assessment of whether protection is achieving intended ecosystem management outcomes. The alignment between ocean accounts and SDG 14 indicators is detailed in TG-2.10 Multilateral Environmental Agreement Indicators.
The Kunming-Montreal Global Biodiversity Framework, adopted at CBD COP15 in December 2022, establishes the ambition to protect 30% of marine areas by 2030 (Target 3) and to ensure that areas under protection are “effectively conserved and managed” through “ecologically representative, well-connected and equitably governed systems of protected areas”. The Framework explicitly calls for integration of biodiversity values into national accounting processes (Target 14), and related CBD decisions have recognised the role of ocean accounts in supporting marine conservation.
The GBF Target 3 coverage classification is the primary framing for the governance overlay on extent accounts in this Circular (see Section 3.2.1). The GBF classification distinguishes IUCN categories Ia-VI and Other Effective Area-Based Conservation Measures (OECMs) as defined under the KM-GBF. SDG 14.5.1 coverage totals can be derived from the same account as a complementary indicator. Compilers should not maintain duplicate or competing coverage tables.
The Taskforce on Nature-related Financial Disclosures (TNFD) has developed recommendations for businesses to assess and report on nature-related dependencies, impacts, risks, and opportunities. Ocean Accounts compiled for MPAs provide data on ecosystem condition and services that can contribute to such assessments. Guidance on mapping ocean account outputs to specific corporate disclosure frameworks — including the TNFD LEAP approach (Locate, Evaluate, Assess, Prepare) — falls within the scope of private-sector-focused Technical Guidance circulars rather than this NSO-facing circular. For organisations seeking to use national ocean account statistics in corporate reporting, the mapping is set out in TG-1.11 OA and the Private Sector Section 3.3, with the LEAP approach in Section 3.2.
Accounts support adaptive management by providing a systematic basis for tracking outcomes and adjusting strategies. The cyclical nature of accounting — with regular updates to extent, condition, and services data — aligns with adaptive management frameworks that emphasize learning from management interventions and adjusting approaches based on observed results.
For MPA managers, accounts can inform decisions such as:
This section presents a synthetic worked example demonstrating how ecosystem condition accounts can be applied to assess MPA effectiveness using a before-after-control-impact (BACI) design. All data are hypothetical but structured to illustrate operational procedures.
A coastal nation designated a 15,000-hectare marine protected area in 2018 to protect coral reef ecosystems. The MPA includes 3,500 ha of coral reef habitat, 4,000 ha of seagrass meadows, and 7,500 ha of pelagic water column. Management objectives include maintaining coral cover above 30%, improving fish biomass to within 20% of unfished levels, and ensuring water quality meets reference conditions for pH and nutrient levels. A control site of comparable size and baseline characteristics but without protection restrictions was identified 50 km away.
The worked example in Sections 3.6.2—3.6.7 focuses on the coral reef sub-account (3,500 ha). Section 3.6.8 extends the example to the seagrass meadow sub-account (4,000 ha) and demonstrates area-weighted ECI aggregation across benthic habitat types.
At the time of designation, baseline condition accounts were compiled for both the MPA and control site using field surveys, remote sensing, and water quality monitoring. The following condition variables were measured:
Table 2: Baseline condition variables for MPA and control site (2018)
Notes: DIN = dissolved inorganic nitrogen. Upper reference values are based on regional historical data and comparison with remote pristine sites; lower reference values on regional records of fully degraded sites of the same habitat type. Both anchors are required by the TG-2.1 Section 3.4.1 transformation and must be documented (TG-2.1 Section 3.4.2). pH uses the categorical step deduction in TG-2.1 Section 3.4.1 and takes no lower anchor. Fish biomass reference represents a single-species maximum sustainable yield benchmark (B_MSY estimated at approximately 40% of unfished biomass) used here for the provisioning service assessment context (Use Case 3); for ecosystem-level condition accounting (Use Cases 1 and 2), an unfished or near-pristine biomass reference is more appropriate. See SEEA EA Chapter 5 (reference conditions) and FAO Technical Guidelines for Responsible Fisheries No. 4.
Each condition variable is normalised to a 0—1 scale using the transformation in TG-2.1 Section 3.4.1, applying the polarity recorded for it in Table 2:
Indicator = (V -- L) / (U -- L)Indicator = (L -- V) / (L -- U)Indicator = 1.00 -- (0.10 x n), where n is the number of complete 0.05-unit steps in the deviation DIndicators are capped at 1.00 and clamped at 0; any observation beyond an anchor is noted in account metadata. Composite indices below use the arithmetic mean across the six variables, following TG-2.1 Section 3.6.
Worked check (MPA water clarity, 2018): (14 -- 4) / (20 -- 4) = 10 / 16 = 0.63. Worked check (MPA DIN, 2018): (1.0 -- 0.4) / (1.0 -- 0.1) = 0.6 / 0.9 = 0.67. Worked check (MPA pH, 2018): D = 8.2 — 8.05 = 0.15, which falls in the 0.15 <= D < 0.20 band, so n = 3 and the indicator is 1.00 -- 0.30 = 0.70.
Table 3: Baseline condition indicators (2018)
After six years of protection and enforcement, condition monitoring was repeated at both sites using identical protocols.
Table 4: Monitoring results and condition indicators (2024)
The MPA site recorded improvement in condition (ECI increased from 0.53 to 0.69), whilst the control site recorded decline (0.48 to 0.43). The treatment effect — the difference in change between MPA and control — is +0.21 points on the ECI scale (MPA change +0.16; control change −0.05; treatment effect = 0.16 − (−0.05) = 0.21), indicating that protection contributed approximately 21 percentage points of condition improvement beyond background environmental trends.
The condition improvement in the MPA is recorded as ecosystem enhancement in the monetary ecosystem asset account. The two method choices this requires — perpetuity or finite horizon, and the functional form linking condition to service capacity — are set out in TG-3.1 Asset Accounts Section 3.5.3 and must be documented in account metadata.
This illustration applies a perpetuity, on the basis that the designation has no terminal date, and a linear condition-to-service scaling as a screening-level approximation only. Both are choices a compiler must justify rather than defaults.
Baseline asset value (2018): the coral reef ecosystem within the MPA (3,500 ha) generated ecosystem services valued at USD 500/ha/year at baseline condition (ECI = 0.53). At a 4% discount rate in perpetuity, the baseline asset value = (USD 500/ha × 3,500 ha) / 0.04 = USD 43.75 million.
Current asset value (2024): after condition improvement to ECI = 0.69, linear scaling gives a service flow of USD 500/ha × (0.69 / 0.53) = USD 650.94/ha/year. Current asset value = (USD 650.94/ha × 3,500 ha) / 0.04 = USD 56.96 million.
Ecosystem enhancement: the increase in asset value attributable to improved condition = USD 56.96M − USD 43.75M = USD 13.21 million over the six-year period, or approximately USD 2.20 million per year on average.
Because the scaling is linear, the enhancement figure moves in direct proportion to the ECI ratio, and any error in the condition indicators propagates undamped into the asset value. See TG-2.4 Environmental (including Ecosystem) Goods and Services for service flow estimation methods.
This worked example simplifies several aspects of real-world MPA assessment:
The same BACI procedure applied to the coral reef sub-account in Sections 3.6.2—3.6.7 can be extended to seagrass meadows and other benthic habitats present within the MPA. Appropriate condition variables for a seagrass sub-account include percent cover, shoot density (shoots/m²), and epiphyte load (as an indicator of eutrophication pressure). Other benthic sub-types (e.g., soft-sediment benthos, shellfish beds) should use variables appropriate to their IUCN GET functional group. So that managers and reporting agencies can distinguish habitat-specific trends from overall MPA condition, sub-type ECIs should be reported separately alongside the aggregate MPA ECI — not only as components of the aggregate.
The MPA-wide aggregate is the area-weighted mean of the sub-type ECIs, following TG-2.1 Section 3.6.1.
Table 5: Illustrative area-weighted ECI aggregation across benthic sub-accounts (2024)
Illustrative seagrass ECI based on percent cover, shoot density, and epiphyte load indicators, normalised against upper and lower references using the same TG-2.1 Section 3.4.1 transformation as the coral reef sub-account.
Pelagic sub-accounts (7,500 ha in this scenario) are excluded from this aggregation for want of condition data, and the excluded area is stated with the index as TG-2.1 Section 3.6.1 requires. Practitioners with pelagic condition data (e.g., chlorophyll-a, dissolved oxygen, plankton biomass) may extend the area-weighted ECI to include a pelagic component using those variables and the same normalisation procedure.
Authors: [To be confirmed]
Reviewers: [To be confirmed]
Cite this report
OA and Marine Spatial Management (including MPAs) (2026) (GOAP Technical Guidance on Ocean Accounting, TG-1.3, v0.8.1). GOAP Secretariat. https://guidance.oceanaccounts.org/circulars/section-1/1-3-marine-spatial-management/
guidance.oceanaccounts.org/circulars/section-1/1-3-marine-spatial-management
© 2026 Global Ocean Accounts Partnership Secretariat · CC BY-NC 4.0 · The report, its PDF and this deck are built from the same source.
Swipe on touch screens. Print gives one landscape page per slide. The address keeps the slide number, so a link opens on the right slide. On a phone in portrait the deck becomes a scrolling document.