Coastal Wetland and Seagrass Accounting

TG-6.2 Section 6: Thematic Methodologies Applied Draft

Circular ID	TG-6.2
Version	7.0
Badge	Applied
Status	Draft
Last Updated	May 2026

1. Outcome

1This Circular provides guidance on compiling ecosystem accounts for mangroves and coastal wetlands. The accounts support four policy applications: blue carbon credit verification for voluntary and compliance carbon markets; coastal protection valuation for infrastructure planning; mangrove restoration prioritisation for climate adaptation; and REDD+ coastal extension for nationally determined contributions under the Paris Agreement.

2This Circular connects to TG-2.8 Climate Change Indicators, which draws on blue carbon sequestration rates compiled here; TG-2.9 Disaster Risk Indicators, which uses coastal protection measurements from Section 3.4; and TG-1.8 OA and Project-Level Finance, which applies carbon accounts and service valuations to blue bonds, debt-for-nature swaps, and payments for ecosystem services.

3This Circular is one of three thematic ecosystem circulars (alongside TG-6.1 Coral Reef Accounting and TG-6.3 Seagrass Ecosystem Accounting) that apply the methodological foundations from TG-3.1 Asset Accounts and TG-4.1 Ecosystem Extent to specific coastal ecosystem types. Together they feed into TG-6.5 Pelagic and Open Ocean Accounting and TG-6.6 Deep Sea and ABNJ Accounting.

2. Requirements

• 1TG-0.1 General Introduction to Ocean Accounts
• 2TG-3.1 Asset Accounts — in particular Section 3.4 on ecosystem asset accounts.
• 3TG-1.9 Valuation — foundational valuation concepts are not repeated here.
• 4TG-4.1 Ecosystem Extent — general extent accounting, spatial data requirements, and change detection.

3. Guidance Material

1Mangroves and coastal wetlands occupy the transitional zone between terrestrial and marine environments, classified within the MFT1 Brackish Tidal Systems biome of the IUCN Global Ecosystem Typology (GET). For the GET realm/biome/EFG hierarchy and the national crosswalk obligation, see TG-4.1 Section 3.2.4.¹ Key ecosystem functional groups are summarised in Table 3.0.1 below².

Functional group	Description
MFT1.2 Intertidal forests and shrublands (mangroves)	Characterised by salt-tolerant trees and shrubs with specialised adaptations including pneumatophores, salt excretion glands, and vivipary.
MFT1.3 Coastal saltmarshes and reedbeds	Dominated by salt-tolerant herbaceous plants and grasses in the upper intertidal zone.
MFT1.1 Coastal river deltas	Complex mosaics incorporating mangroves, saltmarshes, and other transitional ecosystem types.

2Sections 3.1—3.6 cover ecosystem extent, condition, blue carbon services, coastal protection, nursery habitat services, and valuation. Compilers should also consult TG-3.6 Thematic Accounts for the bridge to the SEEA-CF Thematic Carbon Stock Account referenced in Section 3.3. Section 3.7 presents a step-by-step compilation procedure and Section 3.8 provides a worked example.

3.1 Extent Accounting

1Ecosystem extent accounts record mangrove and coastal wetland area within an ecosystem accounting area (EAA), typically in hectares³. Extent accounts provide the spatial foundation for all subsequent condition and service accounts. For satellite sensor selection, cloud-cover management, tidal timing, and general accuracy assessment, see TG-4.1 Ecosystem Extent. Mangrove-specific considerations are noted below.

Ecosystem type classification

1Mangroves and coastal wetlands should be classified at the ecosystem functional group (EFG) level or finer national classifications⁴:

IUCN GET Code	Ecosystem Functional Group	Description
MFT1.2	Intertidal forests and shrublands	Mangrove forests and related tidal woody vegetation
MFT1.3	Coastal saltmarshes and reedbeds	Herbaceous tidal wetlands including salt marshes
MFT1.1	Coastal river deltas	Complex deltaic mosaics with multiple ecosystem types

2National classifications may disaggregate further by dominant species (e.g., Rhizophora-dominated vs. Avicennia-dominated) or structural characteristics. Temperate compilers should identify the most appropriate GET functional groups for their national context and document classification decisions transparently.

Remote sensing and accuracy assessment

1Remote sensing provides the primary data source for extent mapping. Mangrove-specific considerations supplementing TG-4.1 §3.3 are:

• 2L-band SAR (Sentinel-1, ALOS-2 PALSAR-2) for canopy height retrieval under cloud cover
• 3NDVI thresholds for mangrove vs saltmarsh discrimination
• 4Imagery acquired within ±2 hours of low tide for intertidal fringe mapping

5Saltmarsh-specific: Saltmarsh mapping requires high-resolution optical imagery (0.5—2 m) and LiDAR-derived elevation models to separate saltmarsh from adjacent upland vegetation. Multi-temporal classification exploiting phenological contrasts improves discrimination.

6Global datasets: Global Mangrove Watch provides annual mangrove extent maps from 1996 at 25-metre resolution⁵. The Global Tidal Wetland Change Dataset tracks saltmarsh, mangrove, and tidal flat changes globally⁶.

7Accuracy documentation must include: accuracy assessment method (area-based probability sampling); reference data source and collection date; overall, producer, and user accuracy by class; confusion matrix; and imagery source, acquisition date, resolution, and cloud cover or tidal stage. For national GHG inventory reporting, minimum overall accuracy of 85% is a widely applied convention (IPCC Good Practice Guidance)⁷. For carbon credit accounting under voluntary standards (e.g., Verra VM0033), methodology-specific requirements apply.

Change detection

1The extent account records changes between opening and closing periods using four categories⁸:

Change category	Description
Managed expansions	Increases due to restoration, afforestation, or coastal management.
Unmanaged expansions	Natural colonisation and succession.
Managed reductions	Conversion for aquaculture, agriculture, or urban development.
Unmanaged reductions	Natural losses from erosion, sea-level rise, or catastrophic events.

2Temporary losses from storm damage followed by regeneration should be treated as condition changes rather than extent changes⁹.

3Restored vs. naturally regenerated additions. Managed expansions should be disaggregated into two sub-categories in account metadata:

• 4Restored (planted) — counted as gained extent only after a survival check at year 3 post-planting to filter typical 30—60% three-year mortality. The threshold for entry into the extent account is canopy closure or the specified national cover percentage, whichever is reached first.
• 5Naturally regenerated — areas colonised by unassisted propagule recruitment, typically reaching the SEEA EA extent threshold at year 10—15.

6Carbon accumulation trajectories differ between sub-categories: planted monocultures accrue above-ground biomass faster initially but commonly reach lower long-term equilibrium carbon stocks than mixed naturally recruited stands. Compilers should document sub-category membership as this distinction is material for downstream carbon accounting and additionality analyses.

Extent account structure

1The extent account follows the standard SEEA EA structure¹⁰. The ecosystem asset recording methodology in TG-3.1 Asset Accounts Section 3.4 governs how extent entries flow into the asset balance sheet.

Entry	Mangroves (MFT1.2)	Saltmarshes (MFT1.3)	Deltas (MFT1.1)	Total
Opening extent (ha)
Additions to extent
- Managed expansions
- Unmanaged expansions
Reductions in extent
- Managed reductions
- Unmanaged reductions
Net change in extent
Closing extent (ha)

3.2 Condition Assessment

1Ecosystem condition accounts record ecosystem quality through variables reflecting composition, structure, and function¹¹. For the general ECT framework and condition variable selection, see TG-4.8 Physical Condition Measurement §3.1 and TG-4.9 Biological Condition Measurement §3.1. The variables below are mangrove- and wetland-specific applications of ECT classes, with an indication of whether each is estimable from remote sensing (RS) or field sampling (FS)¹².

2Physical state (A1): Tidal inundation regime (FS); sediment accretion/erosion rate (FS); groundwater level (FS).

3Chemical state (A2): Water salinity (FS); nutrient concentrations (FS); dissolved oxygen (FS).

4Compositional state (B1): Species richness (FS); community composition (FS); presence of key species (FS).

5Structural state (B2): Canopy cover (RS); canopy height (RS via LiDAR); above-ground biomass (RS via SAR/allometry); tree density (FS).

6Functional state (B3): Net Primary Productivity (RS via MODIS/Sentinel); litterfall rate (FS); regeneration success (FS).

7Landscape/seascape (C1): Hydrological connectivity (RS+FS); fragmentation (RS); edge effects (RS).

Key condition indicators

1Canopy cover is a primary structural indicator measurable through remote sensing, and describes forest density and intactness¹³.

2Species composition reflects ecological integrity. Presence of climax species (e.g., Rhizophora in many tropical settings) indicates mature, stable ecosystems¹⁴.

3Hydrological connectivity governs coastal wetland function, affecting sediment supply, nutrient exchange, and biotic recruitment¹⁵. Disruption through road construction, aquaculture bunds, or drainage infrastructure is a major cause of degradation. Assess through tidal range comparison (observed vs. reference), distance to tidal inlet, and presence of flow barriers.

4Sediment elevation change indicates whether wetlands are maintaining pace with sea-level rise¹⁶. Surface Elevation Tables (SETs) provide direct measurements. Treat as a core indicator where relative sea-level rise exceeds 2 mm/yr, and as optional but recommended elsewhere. This indicator supports climate adaptation planning.

Reference conditions

1Reference conditions are required against which to assess current state, following SEEA EA Section 5.3¹⁷:

Reference approach	Description
Historical baselines	Pre-disturbance condition documented through historical records, early imagery, or sediment core analysis.
Minimally disturbed reference sites	Protected or relatively undisturbed examples of the same ecosystem type in the national territory or ecoregion.
Expert-defined targets	Expert assessment where historical data and reference sites are unavailable.

2Decision rule: Prefer (i) minimally disturbed contemporary reference sites in the same biogeographic region; fall back to (ii) historical baselines with documented source and date; fall back to (iii) expert-defined targets only where neither alternative exists. This decision rule mirrors the approach in TG-6.1.

3Condition variables are normalised using the formula defined in TG-2.1 Biophysical Indicators for Ocean Accounts Section 3.4.1. Each variable must be tagged as standard or inverse direction.

Sampling design for condition assessment

1SEEA EA does not prescribe minimum plot density. Required documentation: number of sampling units; spatial distribution and stratification; plot dimensions; extrapolation method; and data source and collection date¹⁸.

2Appropriate stratification variables include: ecosystem type and species composition; hydrological zone and inundation frequency; condition class; geomorphic setting (fringe vs. basin vs. riverine mangrove); and remote sensing-derived indicators (canopy cover, NDVI).

3Tier-appropriate guidance:

• 4Tier 1: Single composite estimate from published global or regional defaults; document source, year, and ecological match to accounting area.
• 5Tier 2: 2—4 satellite-derived strata, at least 3 field plots per stratum; area-weight stratum means by area.
• 6Tier 3: Howard et al. (2014) plot-level protocols with stratified random placement and replicated sediment cores. Minimum quadrat sizes: 7 m x 7 m for mangroves, 0.5 m x 0.5 m for saltmarsh.

7For seagrass condition assessment, see TG-6.3 Seagrass Ecosystem Accounting.

Carbon stock estimation — key distinction

1Carbon stocks in the condition account are derived by measuring each pool independently (above-ground biomass, below-ground biomass, soil organic carbon) in tC ha^-1. The normalised condition indicator (scaled 0—1) is a descriptor for tracking and communication. It is not a multiplier against a reference stock value. A degraded ecosystem with measured SOC of 200 tC ha^-1 against a reference of 471 tC ha^-1 has a condition indicator of approximately 0.42, but the carbon stock entered into the account is 200 tC ha^-1 multiplied by ecosystem area. SOC in particular degrades non-proportionally with above-ground condition: deep sediment SOC may remain largely intact even after surface biomass removal¹⁹.

Condition account structure

SEEA ECT Class	Variable	Unit	Reference Level	Opening Value	Closing Value	Change
Physical state	Tidal range ratio	% of reference	100%
Chemical state	Porewater salinity	ppt	Site-specific
Compositional state	Species richness	count	Pre-disturbance
Structural state	Canopy cover	%	Reference site
Structural state	Above-ground biomass	t C/ha	Reference site
Functional state	Net Primary Productivity	t C/ha/yr	Historical mean
Landscape	Hydrological connectivity index	0-1	1.0 (fully connected)

3.3 Blue Carbon Services

1Figure 6.2.1 maps three mangrove carbon pools to SEEA EA accounting destinations: biomass pools enter condition attributes; annual sequestration (Cseq) enters the regulating service account; carbon storage (Cstor) enters a condition attribute with a balance-sheet footnote (not yet standardised).

Figure 6.2.1 Blue-carbon pools map to SEEA EA destinations: biomass and soil burial feed Cseq; Cstor is a condition attribute; deep sediment is supplementary. Dashed paths mark non-standardised Cstor-to-condition link and >1 m durable store. Source: SEEA EA 2024, §§10.20-10.40 (ecosystem condition accounting); TG-6.2 draft, Section 3.3 (Blue Carbon Services) and the net sequestration identity (NECB = biomass increment + net soil burial). Adapted from: SEEA EA 2024 Figure 10.1 (ecosystem condition account structure), with GOAP extensions for blue carbon pool disaggregation, Cseq/Cstor derivation paths, soil burial routing, and the >1 m durable-store supplementary item.

Conceptual distinction: carbon stocks and carbon flows

1A carbon stock is the mass of carbon held in an ecosystem at a point in time (tC or tCO2e), a state variable in the condition account. A carbon flow is the rate of carbon movement between ecosystem and atmosphere over a defined period (tCO2e/yr), a change variable in the ecosystem services flow account. Conflating stock and flow produces results that cannot be compared across countries or time periods²⁰.

2Physical accounts must be compiled before monetary accounts. The recommended sequence is: (1) extent account; (2) condition account (carbon stocks per pool); (3) services flow account, physical; (4) services flow account, monetary.

IPCC Wetlands Supplement tier framework

1The primary reference for blue carbon accounting is the 2013 Supplement to the 2006 IPCC Guidelines: Wetlands, Chapter 4. Coverage by ecosystem type: mangroves (full Tier 1 across all carbon pools); tidal marshes and saltmarsh (partial Tier 1; biomass carbon stock changes require Tier 2+; soil carbon estimates carry ±50—90% uncertainty at Tier 1); seagrass (out of scope — see TG-6.3); tidal flats (not covered by the Wetlands Supplement)²¹.

2Kelp, sargassum, and other macroalgae are out of scope. Their attribution as carbon sinks remains scientifically unresolved, and no agreed IPCC accounting boundary exists.

3Minimum recommended tiers by use case:

Use case	Minimum tier	Rationale
National GHG inventory (UNFCCC reporting only)	Tier 1 acceptable as starting point	Permitted where coastal wetlands are not a key category
NDC contribution / REDD+ / Warsaw Framework	Tier 2	Country-specific emission factors required
Ocean account for policy planning	Tier 2	Physical precision required for spatial planning
Carbon project accreditation (VCS/Gold Standard)	Tier 3	VM0033 sets this threshold explicitly
Blue carbon credit issuance / financial instruments	Tier 3	Additionality, permanence, and leakage require site-specific baselines
High-precision ecosystem service valuation	Tier 3	Monetary reliability depends on physical account precision

4Countries should not remain at Tier 1 for key categories. Where blue carbon ecosystems make a material contribution to national GHG balances (e.g., Indonesia, Philippines, Madagascar, Australia), Tier 2 should be the minimum for NDC and national communications submissions²².

Scope boundary: aquaculture carbon claims

Note on scope

Bivalve aquaculture (oysters, mussels, clams) is outside scope. Animals are heterotrophs, and bivalve shell calcification (Ca2+ + 2HCO3- → CaCO3 + CO2 + H2O) produces CO2 as a by-product. Net atmospheric effects are contested. Shell formation is a metabolic process, not an ecosystem service delivered by a coastal ecosystem asset.

Seaweed farming is generally outside scope. In most operations, harvested biomass is consumed within months to years without durable long-term sequestration (SEEA EA para. 6.114). Emerging applications (deep-ocean sinking, biochar conversion) should be treated as experimental pending IPCC guidance²³.

Carbon stock accounting

1Mangroves and coastal wetlands store carbon in five pools requiring separate accounting²⁴:

Carbon Pool	Measurement Method	Typical Range	Accounting Treatment
Above-ground biomass	Allometric equations	50-250 tC/ha	Condition account (stock)
Below-ground biomass	Root:shoot ratios or allometry	30-150 tC/ha	Condition account (stock)
Dead wood	Field measurement (volume x density)	1-20 tC/ha (locally significant in disturbed forests)	Condition account (stock)
Litter	Quadrat harvest	0.5-5 tC/ha (minor)	Condition account (stock)
Soil organic carbon (0-1m)	Core sampling	200-1000 tC/ha	Condition account (stock)

2Above-ground biomass: Carbon content typically estimated at 45—50% of dry biomass weight²⁵.

3Below-ground biomass: Root:shoot ratios of 0.5—1.5 commonly applied. For mangroves with extensive stilt root systems, below-ground biomass may equal or exceed above-ground biomass²⁶.

4Dead wood and litter: Minor pools in most intact systems but locally significant in disturbed forests. Enumerate following IPCC Wetlands Supplement Chapter 4 protocols.

5Sediment organic carbon (SOC): The largest pool in most coastal wetlands, typically 70—95% of total ecosystem carbon. Representative ranges: mangrove SOC 500—1,500 tCO2e/ha to 1-metre depth (potentially exceeding 3,000 tCO2e/ha in Southeast Asian deep peat soils); saltmarsh SOC 200—700 tCO2e/ha. Methods that neglect soil cores will underestimate total ecosystem carbon.

6The standard accounting depth is 1 metre (IPCC 2013 Wetlands Supplement). For mangrove systems with deep peat soils, compilers may additionally report carbon stocks to bedrock or depth of organic accumulation as a supplementary item, clearly distinguishing these from the 1-metre figures²⁷.

7Carbon market deeper-deposit requirement: Verra VM0033 requires sampling to refusal or 3 m (whichever is shallower) for credit issuance. Where the account supports both SEEA reporting and credit issuance, report (a) 0—1 m stock for SEEA/inventory comparability and (b) full-depth stock to refusal or 3 m as a supplementary item.

8Soil-carbon sampling and laboratory protocol (Kauffman & Donato 2012, CIFOR WP86 Sections 4—5; Howard et al. 2014 Chapter 4):

• 9Core count and depth intervals: minimum 6 cores per plot at 0—15, 15—30, 30—50, and 50—100 cm intervals (plus deeper intervals where the deeper-deposit protocol applies).
• 10Compaction correction: record extruded core length against cored interval length; apply ratio as depth-correction factor. Sediment compression of 20—40% during coring is common.
• 11Laboratory method: dry combustion using an elemental analyser preferred. Where Walkley-Black wet oxidation is used, apply a recovery factor of 1.30 unless site-specific calibration exists.
• 12Loss-on-ignition: requires site- or species-specific calibration against dry combustion before use for accounting purposes.

13The three-tier hierarchy for blue carbon stock measurement maps to the IPCC Wetlands Supplement tier framework (see use-case table above). Murdiyarso et al. (2023) provide a national-scale worked example of the Tier 1 to Tier 2 transition for Indonesian mangroves²⁸.

Allometric equations and uncertainty

1Selection rule — use the most specific equation available, in order:

1. 2Species-specific local equation from destructive sampling within the accounting area.
2. 3Regional species-specific substitute from the same species in a climatically analogous region. Price et al. (2024) confirmed common allometric equations hold for three transatlantic mangrove species across wide climate gradients.
3. 4Pantropical equation with measured wood density: Komiyama et al. (2005): AGB (kg) = 0.251 x rho x D^2.46; BGB (kg) = 0.199 x rho^0.899 x D^2.22, where rho is wood density (g cm^-3) and D is DBH (cm).
4. 5Pantropical default without measured wood density — lowest confidence; document as a limitation²⁹.

6For saltmarsh, Butler et al. (2025) demonstrated models explaining up to 89.3% of biomass variance for Southeast Australian species. Destructive harvest protocols from Howard et al. (2014) remain the standard fallback: 0.25 m2 quadrats and a 0.42—0.45 carbon content factor.

7Equation applicability ranges:

Equation	Predictors	Calibrated on	DBH range (cm)	Reported error	Recommended use
Komiyama et al. (2005) pantropical	DBH, wood density	Mixed species (Thailand, Indonesia, Panama)	5—49	RSE approx. 12%	Default; flag extrapolation outside DBH range
Komiyama et al. (2008) species-specific	DBH (species-specific coefficients)	Multiple Rhizophora, Avicennia, Bruguiera, Sonneratia	Varies 2—40	Species-dependent	Preferred where species represented and stand analogous
Kauffman & Donato (2012) / Kauffman et al. (2016)	DBH	Mixed neotropical and Indo-Pacific	2—50	Reported in source	Standard for protocol-level consistency
Butler et al. (2025) saltmarsh	Canopy diameter, height	SE Australian saltmarsh species	n/a	R^2 up to 0.893	Saltmarsh AGB where species and structure analogous

8Compilers must: (a) confirm species and DBH range fall within the calibration domain; (b) flag extrapolation as documented uncertainty; and (c) record the equation reference in account metadata.

9DBH measurement conventions (Kauffman & Donato 2012 Section 3.2; Howard et al. 2014 Chapter 3):

• 10Rhizophora spp. — 1.3 m above the highest prop root.
• 11Avicennia spp. — 1.3 m above substrate; pneumatophores not measured as stems.
• 12Sonneratia spp. — 1.3 m above substrate; multi-stemmed individuals reported as sum of basal area.
• 13Bruguiera spp. — 1.3 m above substrate.
• 14Excoecaria agallocha, Heritiera spp. — measure immediately above buttress where buttresses exceed 1.3 m.
• 15Coppicing/multi-stemmed — record each stem >5 cm DBH separately; sum basal area for biomass.

16Uncertainty quantification: Allometric equation uncertainty typically constitutes 30—75% of total biomass estimation uncertainty³⁰. Where Monte Carlo simulation is feasible, sample from each parameter’s error distribution across 1,000+ iterations and report mean and 95% confidence interval. Where not feasible, report known confidence intervals from the equation’s published validation. Uncertainty is documented in the technical annex, not embedded in account tables.

Carbon sequestration measurement

1Carbon sequestration is the ongoing removal of CO2 from the atmosphere, distinct from carbon storage³¹. For mangroves and coastal wetlands, it occurs through biomass accumulation (net growth of vegetation) and sediment burial (organic matter incorporation into accreting sediments)³².

2Global average sequestration rates: mangroves approximately 1.5—2.5 tCO2/ha/yr; saltmarshes approximately 0.5—2.0 tCO2/ha/yr³³³⁴.

3Net sequestration identity (operational rule for the flow account):

Net carbon sequestration (period t) = Gross biomass increment + Net soil C accumulation — Mortality and respiration losses — Conversion and degradation emissions

4The retention (stock) service is recorded in the condition account. The sequestration (flow) service is recorded in the services flow account using the net identity above. Reporting stock change and additionally applying a sequestration rate per hectare constitutes double counting.

Approach	Description
Biomass change methods	Repeated measurements of vegetation structure with allometric equations applied to compute net biomass increment between censuses.
Sediment carbon burial rate	Radioisotope dating (210Pb CRS, optionally cross-validated with 137Cs) to establish sediment accumulation rates.
Eddy covariance	Direct measurement of net ecosystem CO2 exchange (NEE) for intensive sites. NEE captures gas-phase flux only; do not substitute NEE for burial or vice versa. NEE and burial together approximate Net Ecosystem Carbon Balance (NECB) when combined with lateral flux and harvest terms (Chapin et al. 2006).

Sediment carbon burial rate measurement

1The sediment carbon burial rate, also termed the organic carbon accumulation rate (CAR), measures carbon passing below the zone of active decomposition into stable, anoxic long-term storage. It is distinct from standing stock and from short-term surface accumulation.

2Lead-210 (210Pb) CRS model — primary method: The Constant Rate of Supply (CRS) model is recommended for vegetated coastal sediments, as it allows sedimentation rates to vary, which is appropriate for blue carbon systems. The carbon accumulation rate is:

3CAR (g C cm^-2 yr^-1) = SAR x DBD x %OC

4where SAR is sediment accumulation rate (cm yr^-1); DBD is dry bulk density (g cm^-3); %OC is organic carbon content. To convert: 1 g C cm^-2 yr^-1 = 10 tC ha^-1 yr^-1.

5Published global mean rates (Arias-Ortiz et al. 2018): mangroves approximately 1.74 tC ha^-1 yr^-1 (range 0.08—4.26); saltmarshes approximately 2.10 tC ha^-1 yr^-135.

6Methodological note — mixed layer correction: Calculate CAR from accumulation rates below the surface mixed layer. Using near-surface values inflates the estimate because carbon in the mixed layer is not yet durably stored (Piñeiro-Juncal et al. 2023).

7Marker horizon method (feldspar plots) — operational alternative: Feldspar clay spread across 50 x 50 cm plots captures recent accretion over months to years. Operationally simple but systematically overestimates long-term burial rates. Use only to characterise recent accretion dynamics. Do not extrapolate to centennial burial rates without correction (Cahoon et al. 1995)³⁶.

8Report the method used and time window. For 210Pb CRS, report as centennial mean and, where temporal variation is evident, as a 10- or 25-year recent average. For marker horizons, report as an explicit short-term estimate.

Human disturbance and the accounting treatment of emissions

1When a blue carbon ecosystem is disturbed or converted, the account captures consequences through three mechanisms³⁷:

1. 2The extent account records area reduction (ha), disaggregated by conversion type (Section 3.1).
2. 3The condition account records carbon stock decline across all pools.
3. 4The services flow account records change in service supply: where NECB falls to zero or below following disturbance, the carbon sequestration service entry is set to zero (SEEA EA para. 6.114). Emission pulses are not recorded as negative service flows.

5The physical measure for the carbon sequestration service is the Net Ecosystem Carbon Balance (NECB), preferred over Net Ecosystem Productivity because NECB additionally captures disturbance losses, harvest, and lateral fluxes.

6Emission pulses from conversion are directed to the SEEA-CF Air Emission Accounts and to the SEEA-CF Thematic Carbon Stock Account (SEEA-CF 2028 Guidance Note D1, November 2025). Apply IPCC 2013 Wetlands Supplement Chapter 4 emission factors³⁸:

Pool	Conversion driver	Default emission factor (IPCC 2013 WS)	Time profile
Above-ground biomass	Clear-cut (any driver)	(1 — harvested wood C retention fraction) x AGB stock	Year of conversion
Soil organic carbon (0—1 m)	Drainage for aquaculture, agriculture, settlements	7.9 t C ha-1 yr-1 (~29 t CO2 ha-1 yr-1) — tropical default for drained mangrove soils (Table 4.13, Section 4.2.2)	20 years post-drainage
Soil organic carbon (0—1 m)	Erosion exposing buried C	Site-specific (no Tier 1 default)	Year of exposure
Below-ground biomass	Conversion	Released with AGB unless retained as residue	Year of conversion

7The 7.9 t C ha^-1 yr^-1 factor is expressed in tonnes of carbon. Multiply by 44/12 for tCO2e. Cross-reference TG-2.8 Climate Change Indicators for NDC reporting.

Permanence and reversibility — accounting treatment

1Physical carbon stocks are recorded at their measured face value. Risk adjustment belongs to the monetary valuation layer, not the physical account (SEEA EA para. 6.115)³⁹.

2SEEA EA para. 6.114: “Where net carbon sequestration is zero or negative, the level of service supplied by an ecosystem is zero.” A “permanence buffer” is a voluntary carbon market mechanism (e.g., Verra VM0033) and must not be applied to SEEA EA physical accounts.

3Where blue carbon ecosystems are identified as “at risk”: (a) prioritise high-quality measurement of the retention component (opening stock in tCO2e); and (b) update stock measurements more frequently, annually if feasible⁴⁰.

Non-CO2 greenhouse gases (CH4 and N2O)

1CH4 (methane) contains one carbon atom per molecule and can be included in the carbon account expressed in tonnes of carbon. N2O contains no carbon and is out of scope for the carbon account⁴¹.

2Methane: Include as an additional row in the carbon service account expressed in tC. A bridge table linking the carbon account (tC) to a GHG account (tCO2e) is recommended as a supplementary output. Where CH4 flux measurements are unavailable, apply IPCC Tier 1 defaults and document the omission.

3Peer-reviewed evidence (Rosentreter et al. 2021, 2022) confirms CH4 emissions from tropical coastal wetlands can substantially offset CO2 sequestration benefits when expressed in CO2e.

4Supplementary GHG budget table: Where a complete climate assessment is required, compile a supplementary table: CO2, CH4 (x GWP100 = 28), N2O (x GWP100 = 265), expressed as tCO2e yr^-1. This is supplementary and does not modify the core carbon account structure.

Tidal export and lateral carbon fluxes — scope note

1Lateral carbon fluxes (DOC, POC, macroalgae from coastal ecosystems to the open ocean) are out of scope. No agreed accounting methodology exists, and attribution and permanence cannot be reliably established under any adopted framework⁴². Excluding lateral export introduces a conservative bias. Mangroves export an estimated 11—56 tC ha^-1 yr^-1 as POC and DOC (Bouillon et al. 2008). Future iterations will incorporate lateral export guidance as the evidence base matures.

Linking blue carbon accounts to national GHG inventories

1Blue carbon ecosystem accounts are ecosystem accounts under the SEEA EA spatial perspective. National GHG inventories use the IPCC sector-based LULUCF framework. The two are complementary but not directly interchangeable⁴³.

2The carbon sequestration service flow (NECB > 0, tCO2e yr^-1) corresponds directly to the sink function reported in LULUCF 4.C.1 (Coastal Wetlands). The extent account provides IPCC activity data. The retention service (opening stock, tCO2e) has no direct UNFCCC inventory equivalent.

3IPCC reporting category and unit conversion: Blue carbon ecosystems are reported under LULUCF subcategory 4.C.1 — Coastal Wetlands. Multiply NECB in tC/yr by 3.664 to obtain tCO2/yr, and multiply carbon stocks in tC by 3.664 for tCO2e comparison.

4Crosswalk — SEEA extent account to IPCC activity data:

• 5Managed reductions (aquaculture conversion) → IPCC “Land converted to Settlements” or “Land converted to Cropland”
• 6Unmanaged reductions (erosion/SLR) → IPCC “Wetlands remaining Wetlands” with degradation flag
• 7Managed expansions (restoration) → IPCC “Land converted to Wetlands (revegetation)”

8Large coastal wetland countries and peat-specific guidance: For countries where coastal wetlands are a key category (Indonesia, Philippines, Malaysia, Madagascar, Australia, Brazil, Mexico), Tier 2 is the minimum for NDC and national communications. For countries with substantial coastal peatland (particularly Indonesia and Malaysia), apply IPCC Wetlands Supplement Chapter 4 Section 4.3 peat decomposition emission factors in addition to standard biomass and surface soil estimates.

9Recommended integration pathway: Compile SEEA extent and condition accounts at the highest feasible tier; derive NECB via stock-difference method; classify data quality against IPCC tier framework; report to national GHG inventory compiler as Tier 2 or Tier 3 LULUCF input; document reconciliation between SEEA account boundaries and IPCC reporting categories. The SEEA-CF 2028 Guidance Note D1 (Carbon Stock Account, November 2025) describes the bridge table mechanism.

Carbon condition account (stock variables)

Carbon Pool	Unit	Opening Stock (tC/ha)	Opening Total (tCO2e)	Closing Stock (tC/ha)	Closing Total (tCO2e)	Change (tCO2e)
Above-ground biomass	tC/ha
Below-ground biomass	tC/ha
Dead wood	tC/ha
Litter	tC/ha
Soil organic carbon (0-1m)	tC/ha
Total carbon stock	tC/ha

Carbon services flow account (flow variables)

Service Component	Physical Measure	Unit	Value
Carbon Retention
Opening stock (reference for retention service)	tCO2e	tCO2e
Carbon Sequestration (NECB)
Net biomass carbon accumulation	tCO2e/yr	tCO2e/yr
Net sediment carbon burial rate	tCO2e/yr	tCO2e/yr
CH4 emissions (if measured)	tC/yr	tC/yr
Total net sequestration (NECB)	tCO2e/yr	tCO2e/yr

3.4 Coastal Protection Services

1Coastal protection services are the ecosystem contributions of mangroves, saltmarshes, and other coastal wetlands in protecting shorelines from erosion, wave damage, and storm surge⁴⁴. The measurement approaches here are consistent with TG-6.1 Coral Reef Accounting Section 3.4, which supports cross-ecosystem aggregation. For general valuation methodology, see TG-1.9 Valuation.

Wave attenuation and storm surge reduction

1Mangroves and saltmarshes reduce wave energy through friction with vegetation⁴⁵. Wave height reductions of 13—66% per 100 metres of mangrove forest have been demonstrated, with higher attenuation in denser vegetation and lower water depths⁴⁶. Saltmarshes attenuate approximately 78—95% over 100-metre widths⁴⁷.

2Coastal wetlands also reduce storm surge heights by 4—50 cm per km of forest width depending on storm intensity and forest characteristics⁴⁸⁴⁹. Key factors determining supply:

• 3Forest width and density
• 4Species composition (different root structures provide varying resistance)
• 5Bathymetry and coastal slope
• 6Storm characteristics

7Reference values for benefit transfer and simplified spatial models:

• 8Minimum mangrove width threshold: 100 m for sheltered coastlines; 500 m for open-ocean exposed coasts (ABS 2022).
• 9Wave-height attenuation: 30—70% per 100 m of vegetated width (McIvor et al. 2012); apply lower end to sparse/fragmented stands, upper end to dense mature stands.
• 10Global benefit transfer: Menendez et al. (2020) report approximately USD 65 billion/yr avoided flood damages across 14 Mha globally; order-of-magnitude USD 4,600/ha/yr global average, adjusted by PPP and coastline exposure before local application.

11Compilers with hydrodynamic modelling capacity should follow the World Bank expected damage function approach (World Bank 2016)⁵⁰. Cross-reference TG-2.8 Climate Change Indicators for the linkage to climate-vulnerability indicators.

Physical measurement

1Recommended metrics⁵¹:

• 2Wave attenuation rate (% reduction per 100m width)
• 3Storm surge reduction (cm reduction per km width)
• 4Shoreline erosion prevention (m/yr erosion avoided)
• 5Protected coastline length (km fronted by wetlands)

6Beneficiary identification is essential: residential and commercial property owners; infrastructure; agricultural land; coastal communities.

Coastal protection service account

Metric	Unit	Value
Mangrove fringe width	m
Wave attenuation rate	% per 100m
Coastline protected	km
Population protected	persons
Property value protected	$
Average annual protection service	$ avoided damages/yr

3.5 Nursery Habitat Services

1Mangroves and coastal wetlands provide nursery habitat through structural complexity (roots and stems providing refuge), food resources (detritus and invertebrate prey), environmental moderation (reduced wave energy and thermal buffering), and connectivity to offshore adult habitats⁵². The nursery function supports commercial and subsistence fisheries by providing juvenile habitat.

Ecological basis and intermediate service accounting

1Nursery services are classified as intermediate ecosystem services in SEEA EA (para 6.15): they contribute to the final biomass provisioning services recorded in fisheries accounts⁵³. To avoid double counting, nursery service values should not be added to the fisheries production they support. Record separately as an intermediate input using the supply-use framework in SEEA EA Chapter 7. If a fisheries accounting circular is compiled (e.g., TG-6.7), document the linkage explicitly⁵⁴.

Species-habitat relationships

1Key evidence linking mangrove/wetland habitat to fisheries productivity⁵⁵:

• 2Juvenile density surveys quantifying fish and invertebrate use of wetland habitats
• 3Tagging and genetic studies tracing adult fish to nursery origins
• 4Correlations between wetland extent and fisheries catch at regional scales

5Published syntheses document positive relationships between mangrove area and catches of penaeid shrimp, mud crabs, barramundi, and snappers⁵⁶. Anneboina & Kumar (2017) estimated the marginal effect at 1.86 t/ha fringe mangrove per year (~USD 1,900/ha/yr), derived from a stochastic production frontier model and not applicable as a universal transfer value without local calibration⁵⁷.

Fish recruitment metrics

Metric	Description
Juvenile fish density	Individuals per unit area or volume of habitat.
Species composition	Diversity and proportion of commercially important species.
Growth rates	Productivity of the nursery habitat.
Survival rates	Proportion of juveniles surviving to recruit to adult populations.
Recruitment contribution	Proportion of adult population derived from wetland nurseries.

1Where field data are limited, wetland area with demonstrated fish use (based on published studies for the biogeographic region) provides a Tier 1 proxy.

2Allocation rule for intermediate vs final service value. Record the intermediate nursery service at its marginal contribution to the final catch: production-function elasticity of catch with respect to nursery habitat multiplied by catch value. The final fisheries provisioning entry is reported net of this intermediate value. Published estimates indicate 30—50% of penaeid shrimp catch in tropical mangrove countries is traceable to mangrove nursery use (Hutchison et al. 2014). Cross-reference TG-4.10 Fisheries Statistics and EBM for the fisheries-account interface.

Nursery service account structure

Metric	Unit	Value
Wetland nursery habitat area	ha
Juvenile fish density	individuals/ha
Commercially important species	count
Annual recruitment to fisheries	tonnes
Proportion from wetland nurseries	%
Contribution to fisheries production	tonnes/yr

Provisioning services — partition with fisheries account

• 1Plant-derived NTFPs: timber poles, fuelwood, honey, tannin, palm fronds, medicinal plants, dyes, and resins — recorded in this circular’s provisioning section.
• 2Mangrove-substrate fauna harvest: mud crab, cockle, wild shrimp post-larvae, mudskipper — route through the fisheries account (TG-4.10) where catch statistics exist. Where unavailable, record here as provisional pending fisheries account integration. The intermediate nursery allocation rule applies to wild post-larvae collection.

3.6 Valuation Methods

1Monetary valuation applies the general framework from TG-1.9 Valuation to mangrove- and wetland-specific contexts⁵⁸.

Carbon pricing

1For blue carbon services⁵⁹:

2Social cost of carbon (SCC): Appropriate for the carbon retention component, applied as: (opening stock in tCO2e) x (SCC per tCO2e) x (rate of return). The SEEA Valuation gives a range of USD 14.9—80.5/t CO2 in 2020⁶⁰, though subsequent analyses have revised that range substantially upward. Applying SCC to retention (standing stock) remains an area of active methodological debate, and the SEEA EA 2021 adopts the two-component model (Keith et al. 2019).

3Compliance market prices: Appropriate for the carbon sequestration component⁶¹. Specify price source, date, and any adjustments applied. VCM prices are not recommended for SEEA-EA-aligned monetary accounts: VCM prices historically underestimate exchange values⁶². Obtain current prices from the World Bank State and Trends of Carbon Pricing report or national carbon pricing instruments.

Avoided damage valuation

1Coastal protection services are valued using avoided damage cost methods⁶³. The expected damage function (EDF) approach requires:

Element	Description
Hazard modelling	Probability distribution of storm events and surge heights/wave energy.
Exposure assessment	Identification and valuation of assets at risk.
Vulnerability functions	Relationship between hazard intensity and damage extent.
Counterfactual analysis	Comparison of damages with and without wetland protection.

2Menendez et al. (2020) estimated global mangrove flood protection benefits exceed USD 65 billion annually⁶⁴⁶⁵.

3Replacement cost methods provide a Tier 2 alternative; for seawall unit cost benchmarks and annualisation procedure, see TG-3.2 Flows from Environment to Economy Section 3.5⁶⁶.

4Benefit transfer: Where primary EDF analysis is not feasible, draw on published global and regional valuations (Menendez et al. 2020; InVEST Coastal Vulnerability model), adjusting for coastline exposure, asset density, and PPP.

Productivity change methods

1Nursery habitat services are valued using productivity change methods⁶⁷:

Step	Description
Production function estimation	Statistical relationship between wetland area/condition and fisheries catch.
Marginal productivity calculation	Additional catch attributable to marginal wetland area.
Market value application	Multiplication by appropriate fish prices.

2Anneboina & Kumar (2017) estimated gross value at ~USD 1,900/ha/yr using a production frontier model for Indian mangroves⁶⁸⁶⁹.

Aggregation and double counting

1Carbon and coastal protection services are largely independent and additive. Nursery services are intermediate inputs and must not be summed with fisheries production values (see Section 3.5 allocation rule). The SEEA EA supply-use framework ensures each service flow is recorded once⁷⁰⁷¹.

Valuation summary table

Service	Valuation Method	Tier	Key Parameters
Carbon retention	Social cost of carbon	1-3	Carbon price, discount rate
Carbon sequestration	Compliance market price	2-3	Compliance market prices (VCM prices not SEEA-aligned)
Coastal protection	Avoided damage cost	2-3	Storm probabilities, asset values
Coastal protection	Replacement cost	2	Engineering cost estimates
Coastal protection	Benefit transfer	1	Published global estimates, PPP adjustment
Nursery habitat	Productivity change	2-3	Production function, fish prices
Nursery habitat	Habitat extent proxy	1	Area of suitable habitat, regional unit values

3.7 Compilation Procedure

1Step 1: Data Collection

2Compile: (1) spatial data (Landsat, Sentinel-2, SAR, national vegetation maps, protected area boundaries); (2) extent data (remote sensing, national wetland inventories, Global Mangrove Watch); (3) condition data (field surveys, remote sensing variables); (4) carbon data (biomass measurements, sediment cores, allometric equations, literature values); (5) service data (wave attenuation studies, storm assessments, fisheries statistics, juvenile fish surveys); (6) valuation data (carbon prices, coastal property values, fish prices, engineering cost estimates). Coordinate across environmental ministries, statistical offices, meteorological agencies, and fisheries authorities.

3Step 2: Classification and Mapping

4Map national classifications to IUCN GET functional groups (MFT1.1, MFT1.2, MFT1.3). Define EAA boundaries. Classify ecosystems by remote sensing. Validate using ground-truth surveys.

5Step 3: Extent Account Compilation

6Generate baseline extent map; detect changes using multi-date imagery; classify as managed/unmanaged expansions or reductions; populate extent account. Validate: Closing extent = Opening extent + Additions — Reductions.

7Step 4: Condition Assessment

8Confirm minimum tier (IPCC Wetlands Supplement Tier Framework, Section 3.3) and record in account metadata. Select condition variables from all six ECT classes; measure using field surveys and remote sensing; establish reference conditions; normalise into indicators; compile condition account.

9Step 5: Ecosystem Service Quantification

10Blue carbon: Measure carbon stocks by pool; enter NECB into services flow account; document disturbance events and direct emission pulses to SEEA-CF accounts. Compile carbon condition account (stocks) and carbon services flow account (flows) as two separate tables.

11Coastal protection: Map mangrove/wetland fringe and forest width; identify protected coastline and beneficiary populations; estimate wave attenuation; quantify storm surge reduction.

12Nursery habitat: Delineate nursery habitat; measure juvenile fish density and species composition; estimate recruitment contribution; link extent/condition to fisheries production using production functions.

13Step 6: Monetary Valuation

14Apply carbon pricing (SCC for retention, compliance market price for sequestration; VCM prices are not SEEA-aligned). Calculate avoided damages or replacement costs for coastal protection. Estimate productivity contributions for nursery habitat. Document assumptions, price sources, and uncertainty. For finance instrument applications, refer to TG-1.8 OA and Project-Level Finance⁷².

15Step 7: Account Integration and Balancing

16Reconcile accounts for mutual consistency. Check stock-flow balancing identities. Link to national ocean accounts, climate accounts, and fisheries accounts. Prepare metadata. Compile time series.

Note on additionality, leakage, and baseline analyses

Where account outputs are intended to support carbon market instruments or results-based payments, additionality assessment, counterfactual baseline construction, and leakage analysis are applied on top of the account by the relevant market methodology (e.g., Verra VM0033). Document pre-intervention carbon stock values in the condition account to facilitate subsequent additionality assessment.

3.8 Worked Example

1This worked example demonstrates the full accounting sequence for a hypothetical coastal zone in a Southeast Asian setting. All data are synthetic and illustrative.

2Setting: 8,000 ha of mangrove forest (MFT1.2) and 3,000 ha of salt marsh (MFT1.3), totalling 11,000 ha dominated by Rhizophora and Avicennia species.

3Step 1: Extent account (year t to t+1)

Entry	Mangroves (MFT1.2)	Saltmarshes (MFT1.3)	Total
Opening extent (ha)	8,000	3,000	11,000
Additions to extent
— Managed expansions (restoration planting)	120	25	145
— Unmanaged expansions (natural colonisation)	45	15	60
Total additions	165	40	205
Reductions in extent
— Managed reductions (aquaculture conversion)	200	10	210
— Unmanaged reductions (erosion, storm damage)	65	30	95
Total reductions	265	40	305
Net change in extent	-100	0	-100
Closing extent (ha)	7,900	3,000	10,900

4Interpretation: Net loss of 100 ha of mangroves driven by aquaculture conversion exceeding restoration. Saltmarshes showed no net change.

5Step 2: Condition account

6Condition indicators derived from field survey and remote sensing, using minimally disturbed reference sites:

Condition variable	Observed value	VH (reference)	VL (degraded)	Indicator score
Canopy cover	72%	90%	20%	0.74
Seedling density	3,200 stems/ha	5,000	500	0.60
Sediment accretion rate	4.5 mm/yr	6.0	1.0	0.70
Water quality (dissolved oxygen)	5.8 mg/L	7.0	3.0	0.70

7Composite condition index (equal weights): (0.74 + 0.60 + 0.70 + 0.70) / 4 = 0.69

8Indicator score calculated using the normalisation formula in TG-2.1 Section 3.4.1. Example: canopy cover indicator = (72 - 20) / (90 - 20) = 52 / 70 = 0.74.

9Important: The condition index of 0.69 is a tracker, not a carbon stock multiplier. Each pool is measured independently and entered at its measured value.

10Step 2b: Carbon condition account (mangroves, MFT1.2)

Carbon pool	Method	Opening (tC/ha)	Closing (tC/ha)	Opening total (tC)	Closing total (tC)
Above-ground biomass	Komiyama et al. (2005) allometric	120	116	960,000	916,400
Below-ground biomass	Root:shoot ratio 0.70	84	81	672,000	640,000
Dead wood	Field inventory	5	5	40,000	39,500
Litter	Litterfall traps	2	2	16,000	15,800
SOC (0—1 m)	Sediment coring, bulk density	450	447	3,600,000	3,531,300
Total		661	651	5,288,000	5,143,000

11Opening: 8,000 ha. Closing: 7,900 ha (100 ha lost to aquaculture). Carbon fraction: 45% of dry biomass for AGB/BGB. SOC expressed directly in tC.

12Net change: 5,143,000 — 5,288,000 = —145,000 tC (driven primarily by the 100 ha conversion event).

13Step 3a: Carbon services flow account (annual flows)

Service flow component	Physical measure	Unit	Annual value
Net biomass carbon accumulation	NECB — biomass pools	tCO2e/yr	29,300
Net sediment carbon burial (SOC)	CAR x area x (1 — mixed layer adjustment)	tCO2e/yr	29,200
Emissions from conversion event	100 ha aquaculture conversion, IPCC Wetlands Supplement factors	tCO2e/yr	—38,000
Net carbon sequestration service supply	NECB (floored at zero where negative)	tCO2e/yr	20,500

14NECB: (29,300 + 29,200) — 38,000 = 20,500 tCO2e/yr. The conversion emission reflects an annualised multi-year pulse. The emission pulse is additionally directed to SEEA-CF Air Emission Accounts (aquaculture sector). Carbon retention service (5,288,000 tC = 19,407,000 tCO2e opening stock) is recorded in the condition account above.

15Step 3b: Ecosystem service monetary valuation summary

Service	Physical quantity	Monetary value (USD)
Carbon sequestration	20,500 tCO2e/yr	1,640,000 (at USD 80/t CO2e)
Coastal protection	85 km coastline protected	6,400,000 (avoided damage)
Fisheries nursery habitat	2,100 tonnes recruitment	3,900,000 (productivity change)
Timber and NTFPs	1,500 m³ timber; assorted NTFPs	950,000 (market price)
Total valued services		12,890,000

16Carbon sequestration: 20,500 x USD 80 = USD 1,640,000.

17Coastal protection: Expected damage function approach; avoided damages across storm probability distribution = USD 6.4 million/yr.

18Nursery habitat: Marginal contribution: 0.25 t catch/ha/yr. Nursery area: 8,400 ha (8,000 ha mangrove fringe + 400 ha salt marsh adjacent to tidal creeks; 2,600 ha inland salt marsh excluded as lacking direct fish access). Contribution: 8,400 x 0.25 = 2,100 t/yr. At average fish price USD 1,857/t: USD 3,900,000. Note: If fisheries provisioning is separately valued in national accounts (TG-6.7), exclude the nursery value from the total to avoid double counting. Presented here for illustrative purposes.

19Step 4: Asset valuation

Asset value = Annual service value x PV annuity factor (4%, 25 years) Asset value = 12,890,000 x 15.62 = USD 201,300,000

20PV annuity factor: [1 - (1 + 0.04)^-25] / 0.04 = 15.62.

21Step 5: Upward connections to policy circulars

22TG-2.8: Carbon sequestration rate of 20,500 tCO2e/yr and above-ground carbon stocks feed into NDC blue carbon reporting and SDG 13 monitoring.

23TG-2.9: Coastal protection value of USD 6.4 million/yr and 85 km protected coastline feed into vulnerability assessments for disaster risk reduction.

24TG-1.8: Asset value of USD 201.3 million and annual service flows provide the measurement foundation for blue bonds, debt-for-nature swaps, or payments for ecosystem services.

25All values are illustrative. The carbon price of USD 80/t CO2e should be replaced with the prevailing compliance market price or social cost of carbon applicable in the compiler’s jurisdiction.

Figure 6.2.2 One mangrove ecosystem asset supplies a service bundle: two final services may be summed; nursery is intermediate; extent is counted once. Final/intermediate role is user-context dependent (SEEA EA para. 6.49). Source: TG-6.2, Sections 3.3--3.6 (mangrove service bundle worked example); final/intermediate distinction per SEEA EA 2024, paras. 6.24 and 6.49; nursery treatment per para 6.15. Adapted from: SEEA EA 2024 ecosystem service concepts (Chapter 6), with GOAP extensions (final/intermediate routing, single-extent caution, beneficiary sub-labels, illustrative-subset framing).

4. Acknowledgements

1This Circular has been approved for public circulation and comment by the GOAP Technical Experts Group in accordance with the Circular Publication Procedure.

2Authors: [To be confirmed]

3Reviewers: [To be confirmed]

5. References and Further Reading

1SEEA framework and ecosystem accounting:

• 2United Nations (2021). System of Environmental-Economic Accounting — Ecosystem Accounting (SEEA EA). United Nations Statistical Papers Series F No. 124. New York: United Nations.
• 3United Nations (2022). Monetary Valuation of Ecosystem Services and Assets for Ecosystem Accounting. Technical Report v1.5. New York: UNSD/UNEP.
• 4United Nations Statistics Division (2023). Method of the Ecosystem Condition Account. New York: UNSD/UNEP.
• 5UNSD/SEEA Technical Committee (2025). Draft Guidance Note D1 — Carbon Stock Account. November 2025.
• 6UNSD/SEEA Technical Committee (2025). Draft Guidance Note B3 — Treatment of Carbon Flows in the SEEA CF. November 2025.
• 7Keith, H., Vardon, M., Lindenmayer, D., & Mackey, B. (2019). Accounting for carbon stocks and flows: storage and sequestration are both ecosystem services. 25th Meeting of the London Group on Environmental Accounting.
• 8Edens, B., Elsasser, P., & Ivanov, A. (2019). Discussion Paper 6: Defining and valuing carbon-related services in the SEEA EEA. UN Statistics Division.

9IPCC and national inventory:

• 10IPCC (2013). 2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands. Geneva: IPCC.
• 11IPCC (2019). 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, Chapter 7: Wetlands. Geneva: IPCC.
• 12GFOI (2025). Blue Carbon Guidance for National Greenhouse Gas Inventories. Rome: FAO/Global Forest Observations Initiative.
• 13Blue Carbon Partnership (2021). Coastal Wetlands in National Greenhouse Gas Inventories.

14Ecosystem classification and extent:

• 15IUCN (2020). Global Ecosystem Typology 2.0. Biome MFT1 Brackish Tidal Systems. Gland: IUCN.
• 16Bunting, P., et al. (2018). “The Global Mangrove Watch — A New 2010 Global Baseline.” Remote Sensing, 10(10), 1669.
• 17Murray, N.J., et al. (2019). Global Tidal Wetland Change Dataset. Nature Scientific Data.

18Field methods and blue carbon measurement:

• 19Howard, J., Hoyt, S., Isensee, K., Telszewski, M., & Pidgeon, E. (eds.) (2014). Coastal Blue Carbon: Methods for Assessing Carbon Stocks and Emissions Factors in Mangroves, Tidal Salt Marshes, and Seagrass Meadows. Arlington: Conservation International, IOC-UNESCO, IUCN.
• 20Kauffman, J.B., & Donato, D.C. (2012). Protocols for the measurement, monitoring and reporting of structure, biomass and carbon stocks in mangrove forests. Working Paper 86. Bogor: CIFOR. DOI: 10.17528/cifor/003749.
• 21Kauffman, J.B., et al. (2016). Protocols for the measurement, monitoring and reporting of structure, biomass, carbon stocks and greenhouse gas emissions in tropical peat swamp forests. PSW-GTR-373. Pacific Southwest Research Station: USFS.
• 22Kauffman, J.B., et al. (2011). “Ecosystem carbon stocks of Micronesian mangrove forests.” Wetlands, 31(2), 343-352.
• 23Lewis, R.R. (2005). “Ecological engineering for successful management and restoration of mangrove forests.” Ecological Engineering, 24(4), 403-418.
• 24Kodikara, K.A.S., et al. (2017). “Have mangrove restoration projects worked? An in-depth study in Sri Lanka.” Restoration Ecology, 25(5), 705-716.
• 25Nelson, D.W., & Sommers, L.E. (1996). “Total carbon, organic carbon, and organic matter.” In Methods of Soil Analysis Part 3: Chemical Methods. Madison: SSSA.
• 26Chapin, F.S., et al. (2006). “Reconciling carbon-cycle concepts, terminology, and methods.” Ecosystems, 9(7), 1041-1050.
• 27Komiyama, A., Poungparn, S., & Kato, S. (2005). “Common allometric equations for estimating the tree weight of mangroves.” Journal of Tropical Ecology, 21(4), 471-477.
• 28Komiyama, A., Ong, J.E., & Poungparn, S. (2008). “Allometry, biomass, and productivity of mangrove forests: a review.” Aquatic Botany, 89(2), 128-137.
• 29Arias-Ortiz, A., et al. (2018). “210Pb-derived sediment and carbon accumulation rates in vegetated coastal ecosystems.” Biogeosciences, 15, 6791-6818.
• 30Cahoon, D.R., et al. (1995). “Accretion and canal impacts in a rapidly subsiding wetland II — Feldspar marker horizon technique.” Estuaries, 18(3), 490-497.
• 31Piñeiro-Juncal, N., Leiva-Dueñas, C., & Serrano, O. (2023). “How to quantify blue carbon sequestration rates in seagrass meadow sediment.” Carbon Footprints.
• 32Murdiyarso, D., et al. (2023). “Deriving emission factors for mangrove blue carbon ecosystem in Indonesia.” Carbon Balance and Management, 18, 11.

33Allometric equations:

• 34Price, J.P., et al. (2024). “Global Data Compilation Across Climate Gradients Supports the Use of Common Allometric Equations for Three Transatlantic Mangrove Species.” Ecology and Evolution, e70577.
• 35Butler, S., et al. (2025). “Allometric Biomass Equations to Quantify Carbon Content of Southeast Australian Saltmarsh Vegetation.” Science of The Total Environment.
• 36Berger, A., et al. (2020). “Variability and uncertainty in forest biomass estimates from different allometric equations.” Carbon Balance and Management, 15, 8.

37Carbon stocks and biogeography:

• 38Twilley, R.R., Rovai, A.S., & Riul, P. (2018). “Coastal morphology explains global blue carbon distributions.” Nature Communications, 9, 2997.
• 39Bouillon, S., et al. (2008). “Mangrove production and carbon sinks: A revision of global budget estimates.” Global Biogeochemical Cycles, 22(2).
• 40Duarte, C.M., et al. (2005). Major role of marine vegetation on the oceanic carbon cycle. Biogeosciences, 2, 1-8.
• 41Mcleod, E., et al. (2011). “A blueprint for blue carbon.” Frontiers in Ecology and the Environment, 9(10), 552-560.
• 42Chmura, G.L., et al. (2003). “Global carbon sequestration in tidal, saline wetland soils.” Global Biogeochemical Cycles, 17(4).
• 43Bertram, C., et al. (2021). “The blue carbon wealth of nations.” Nature Climate Change, 11, 704-710.
• 44Macreadie, P.I., et al. (2025). “Predicting climate mitigation through carbon burial in blue carbon ecosystems — challenges and pitfalls.” Global Change Biology, 31, e70022.

45Non-CO2 greenhouse gases:

• 46Rosentreter, J.A., et al. (2021). “Methane and Nitrous Oxide Emissions Complicate Coastal Blue Carbon Assessments.” Global Biogeochemical Cycles, 35(2), e2020GB006858.
• 47Rosentreter, J.A., et al. (2022). “Methane and nitrous oxide emissions complicate the climate benefits of teal and blue carbon wetlands.” One Earth, 5(12), 1336-1347.

48Carbon markets and financial instruments:

• 49Verra (2018). VM0033 Methodology for Tidal Wetland and Seagrass Restoration, Version 1.0.
• 50High Level Panel for a Sustainable Ocean Economy (2023). Blue Carbon Handbook. Washington DC: Ocean Panel.
• 51Lim, A.S.L., et al. (2025). “Towards the inclusion of managed macroalgal ecosystems in the IPCC greenhouse gas inventory.” National Science Review, nwaf391.

52Coastal protection:

• 53World Bank (2016). Managing Coasts with Natural Solutions: Guidelines for Measuring and Valuing the Coastal Protection Services of Mangroves and Coral Reefs. Washington DC: World Bank.
• 54Menendez, P., et al. (2020). “The global flood protection benefits of mangroves.” Scientific Reports, 10, 4308.
• 55McIvor, A.L., et al. (2012). The Response of Mangrove Soil Surface Elevation to Sea Level Rise. Cambridge: The Nature Conservancy and Wetlands International.

56Nursery habitat services:

• 57Nagelkerken, I., et al. (2008). “The habitat function of mangroves for offshore fish and shellfish populations.” Aquatic Botany, 89(2), 155-185.
• 58Hutchison, J., et al. (2014). “The role of mangroves in supporting marine fisheries.” PLOS ONE, 9(10).
• 59Anneboina, L.R., & Kumar, K.S.K. (2017). “Economic analysis of mangrove and marine fishery linkages in India.” Ecosystem Services, 24, 114-123.

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Footnotes

1. 1

   IUCN GET, Biome MFT1 description; SEEA EA, Appendix A3.2 presents the IUCN GET reference classification. ↩

2. 2

   SEEA EA, para 4.11-4.12 on ecosystem type classification and the relationship between national classifications and the international reference classification. ↩

3. 3

   SEEA EA, para 4.1: “Ecosystem extent is the size of an ecosystem asset. It is usually measured in terms of spatial area.” ↩

4. 4

   SEEA EA, para 4.11-4.12 on ecosystem type classification. ↩

5. 5

   Global Mangrove Watch provides globally consistent annual mangrove extent maps; available at www.globalmangrovewatch.org. ↩

6. 6

   Murray et al. (2019) on global tidal wetland change mapping. ↩

7. 7

   SEEA EA, para 4.14-4.16 on accounting entries for extent changes. ↩

8. 8

   IPCC (2006/2019 Refinement), Volume 4, Chapter 3 on consistent representation of lands. See also Bunting et al. (2018) on Global Mangrove Watch accuracy assessment procedures. ↩

9. 9

   SEEA EA, para 4.16. ↩

10. 10

    SEEA EA, Table 4.1 provides the ecosystem extent account structure. ↩

11. 11

    SEEA EA, para 5.1: “Ecosystem condition accounts provide a structured approach to recording and aggregating data describing the characteristics of ecosystem assets and how they have changed.” ↩

12. 12

    SEEA EA, Table 5.1 presents the SEEA Ecosystem Condition Typology with six classes. ↩

13. 13

    SEEA EA, para 5.36. ↩

14. 14

    SEEA EA, para 5.35. ↩

15. 15

    Hydrological connectivity is fundamental to tidal wetland function; disruption is a major driver of degradation globally. ↩

16. 16

    SEEA EA, para 5.11 notes ecosystem resilience considerations; sediment elevation monitoring is critical for sea-level rise adaptation. ↩

17. 17

    SEEA EA, Section 5.3 on reference conditions for ecosystem condition assessment. ↩

18. 18

    UNSD (2023), Method of the Ecosystem Condition Account; Howard et al. (2014) on minimum plot specifications for blue carbon surveys; GFOI (2025) on sampling requirements for national inventory submissions. ↩

19. 19

    SEEA EA, paras 6.110-6.115; UNSD (2023), Method of the Ecosystem Condition Account. SOC non-proportional degradation is well-established: deep sediment SOC may persist for centuries even after surface biomass removal because anaerobic conditions limit decomposition. ↩

20. 20

    United Nations (2022), Monetary Valuation Technical Report v1.5, Section 4.2.9; Keith et al. (2019), London Group paper on accounting for carbon stocks and flows. ↩

21. 21

    IPCC (2013), Wetlands Supplement, Chapter 4; IPCC (2019) Refinement, Volume 4, Chapter 7. Tidal flat accounting gaps acknowledged in GFOI (2025). ↩

22. 22

    IPCC (2013), Wetlands Supplement, Chapter 4 escalation guidance; High Level Panel for a Sustainable Ocean Economy (2023), Blue Carbon Handbook. ↩

23. 23

    SEEA EA, para 6.114; Lim et al. (2025) on macroalgal ecosystem inclusion in IPCC inventories. ↩

24. 24

    IPCC 2013 Wetlands Supplement provides methodology for blue carbon stock accounting across five standard pools. ↩

25. 25

    Above-ground biomass carbon fraction of 0.47 is sourced from IPCC 2006 Guidelines Volume 4 Chapter 4 Table 4.3 (forest biomass carbon fraction). Below-ground biomass carbon fraction of 0.39 is the mangrove-specific value derived from Kauffman et al. (2011) measurements and tabulated in Howard et al. (2014) Table 3.1; this should not be attributed solely to Kauffman & Donato (2012). ↩

26. 26

    Komiyama et al. (2008) on mangrove root:shoot ratios and allometry. ↩

27. 27

    IPCC 2013 Wetlands Supplement recommends 1-metre depth for sediment carbon reporting as the standard minimum. Howard et al. (2014) provide coring protocols for depths beyond 1 metre in high-carbon systems. ↩

28. 28

    IPCC (2013), Wetlands Supplement, Chapter 4; Murdiyarso et al. (2023) on national-scale Tier 2 methodology in Indonesia; Howard et al. (2014) on Tier 3 field protocols. ↩

29. 29

    Komiyama et al. (2005) pantropical equations; Price et al. (2024) on transatlantic species validation; Butler et al. (2025) on saltmarsh allometry; Howard et al. (2014) on destructive harvest protocols. ↩

30. 30

    Berger et al. (2020) on allometric uncertainty quantification; SEEA EA conventions on uncertainty reporting in metadata rather than account tables. ↩

31. 31

    The distinction between carbon storage (stock) and sequestration (flow) is fundamental to carbon accounting; see SEEA Valuation Section 4.2.9. ↩

32. 32

    SEEA Valuation, Section 4.2.9 on carbon sequestration measurement. ↩

33. 33

    Duarte et al. (2005); Mcleod et al. (2011) on mangrove carbon sequestration rates. ↩

34. 34

    Chmura et al. (2003) on saltmarsh carbon sequestration. ↩

35. 35

    Arias-Ortiz et al. (2018) global synthesis of 210Pb-derived carbon accumulation rates. ↩

36. 36

    Cahoon et al. (1995) on the feldspar marker horizon technique; Piñeiro-Juncal et al. (2023) on mixed layer corrections and burial rate quantification. ↩

37. 37

    SEEA EA, paras 6.110-6.115 on disturbance treatment in ecosystem accounts; IPCC 2013 Wetlands Supplement, Chapter 4. ↩

38. 38

    UNSD/SEEA Technical Committee (2025), Draft Guidance Note D1 — Carbon Stock Account; UNSD/SEEA Technical Committee (2025), Draft Guidance Note B3; IPCC (2013), Wetlands Supplement, Chapter 4 emission factors for conversion events. ↩

39. 39

    SEEA EA, paras 6.110-6.115. ↩

40. 40

    SEEA EA, para 6.114; Verra (2018), VM0033; Bertram et al. (2021) on blue carbon wealth of nations and risk assessment. ↩

41. 41

    Rosentreter et al. (2021, 2022); UNSD/SEEA Technical Committee (2025), Draft Guidance Note D1. ↩

42. 42

    Bouillon et al. (2008) on mangrove carbon export; High Level Panel for a Sustainable Ocean Economy (2023), Blue Carbon Handbook; Howard et al. (2014). ↩

43. 43

    GFOI (2025), Blue Carbon Guidance for National GHG Inventories; UNSD/SEEA Technical Committee (2025), Draft Guidance Note D1; IPCC (2013), Wetlands Supplement, Chapter 4; Blue Carbon Partnership (2021). ↩

44. 44

    SEEA EA, Section 6.3 on ecosystem service reference list includes coastal protection. ↩

45. 45

    Wave attenuation by mangroves has been extensively studied; see McIvor et al. (2012) review. ↩

46. 46

    Wave attenuation rates vary widely; ranges from synthesis studies. ↩

47. 47

    Saltmarsh wave attenuation from Moller et al. (2014) and related studies. ↩

48. 48

    Storm surge attenuation mechanisms differ from wave attenuation; both contribute to coastal protection. ↩

49. 49

    Storm surge reduction estimates from Krauss et al. (2009) and related studies. ↩

50. 50

    SEEA Valuation, Section 4.2.13 references World Bank (2016). ↩

51. 51

    World Bank (2016) provides detailed methodology for coastal protection measurement. ↩

52. 52

    Blue carbon terminology established by Nellemann et al. (2009); widely adopted in IPCC and UNFCCC contexts. For seagrass-specific guidance, see TG-6.3 Seagrass Ecosystem Accounting. ↩

53. 53

    SEEA EA reference list definition of nursery population and habitat maintenance services; SEEA Valuation, Section 4.2.14. ↩

54. 54

    SEEA EA, para 6.15. ↩

55. 55

    Quantifying nursery-fisheries linkages is essential but methodologically challenging. ↩

56. 56

    Multiple studies document mangrove-fisheries correlations; see Hutchison et al. (2014) meta-analysis. ↩

57. 57

    SEEA Valuation, Section 4.2.14 citing Anneboina and Kumar (2017). ↩

58. 58

    SEEA EA, Chapter 10 on ecosystem asset valuation; SEEA Valuation provides comprehensive guidance. ↩

59. 59

    SEEA Valuation, Section 4.2.9 on carbon pricing approaches. ↩

60. 60

    SEEA Valuation, Section 4.2.9 on social cost of carbon estimates. ↩

61. 61

    SEEA Valuation, Section 4.2.9 on compliance market prices. ↩

62. 62

    United Nations (2022), Monetary Valuation Technical Report v1.5, Section 4.2.9; Edens et al. (2019); Keith et al. (2019). ↩

63. 63

    SEEA Valuation, Section 4.2.13 on coastal protection valuation methods. ↩

64. 64

    SEEA Valuation, Section 4.2.13. ↩

65. 65

    SEEA Valuation, Section 4.2.13 citing Menendez et al. (2020). ↩

66. 66

    SEEA Valuation, Section 4.2.13 notes replacement cost as Tier 2 method. ↩

67. 67

    SEEA Valuation, Section 4.2.14 on productivity change methods for nursery services. ↩

68. 68

    SEEA Valuation, Section 4.2.14. ↩

69. 69

    SEEA Valuation, Section 4.2.14 citing Anneboina and Kumar (2017). ↩

70. 70

    SEEA EA, Section 7.3 on avoiding double counting in ecosystem service accounting. ↩

71. 71

    SEEA EA supply-use framework ensures consistent recording of service flows. ↩

72. 72

    Verra (2018), VM0033 Methodology for Tidal Wetland and Seagrass Restoration. ↩