Ex-Ante Carbon Estimation for Tree Planting

Updated 2026-11-02 · 4 min read · By the akar.earth specialist team

Ex-ante carbon estimate guide for tree planting: growth, survival, buffer and uncertainty deductions, and how to keep projections conservative.

An ex-ante carbon estimate forecasts how many tonnes of CO2 a tree-planting project will remove over its crediting period, before any trees have grown, by combining planting plans, growth models, survival assumptions and the methodology’s deductions. It is used for feasibility, finance and the project design document; credits are issued only on measured ex-post results, so a credible estimate is a conservative one.

The estimation chain

1. Planting schedule. Hectares planted per year, by stratum and species mix.
2. Survival and stocking. Trees per hectare over time after mortality and replanting. See seedling survival rates.
3. Growth. Diameter and height (or biomass) by age, from local yield tables, growth studies or permanent plots.
4. Biomass. Apply allometric equations and wood density per species.
5. Carbon pools. Add below-ground biomass with root-to-shoot ratios; dead wood or soil only if the methodology includes them. See carbon pools.
6. Convert to CO2e. Carbon fraction × 44/12. See CO2 from biomass.
7. Subtract the baseline. Carbon that would have accumulated anyway (for VM0047 area-based projects, reflected in the performance benchmark).
8. Subtract leakage, for example displaced grazing or cropping.
9. Apply uncertainty deductions expected from your sampling design.
10. Deduct the buffer contribution based on the non-permanence risk rating.
11. Account for harvest if timber is cut: long-term average carbon may limit creditable removals.

The result is net creditable removals per year. Present it as a range (low, central, high), not a single number.

Where the numbers come from

Worked structure (no invented numbers)

For each stratum and year: removals = (stock at year t − stock at year t−1) × area × survival adjustment. Then sum across strata, subtract baseline and leakage, apply the expected uncertainty deduction, and deduct the buffer. A spreadsheet or model should make every one of these lines visible. Tools like the ARR carbon estimator and akar carbon simulator follow this structure for early screening.

Sensitivity testing

Run scenarios on the parameters that matter most:

• Growth rate (slower and faster than central).
• Survival and replanting success.
• Planting delays (hectares slipping a year or two).
• Harvest timing for timber species.
• Buffer percentage.
• Carbon price, for the financial model.

If the project only works in the optimistic case, it does not work.

Updating the estimate over time

An ex-ante estimate should be a living model. After the first monitoring period, replace assumed survival and growth with measured values, recalibrate by stratum, and re-run the forecast. Share the comparison with investors and buyers; a project that shows how measured results track the forecast, and explains the gaps, earns more trust than one that never revisits its numbers. Keep the original PDD version for the audit trail.

Ex-ante numbers and the market

Forward sales, prepayments and offtake agreements are often sized on ex-ante estimates. Sizing contracts at the conservative end, with delivery schedules that allow for slippage, protects both sides. See carbon prepayment finance.

Common mistakes

• Using peak growth rates from good sites for the whole area.
• Forgetting the slow first years before canopy closure.
• Ignoring the baseline because land “is degraded anyway”.
• Counting planned hectares that have no signed landholder agreements.
• Treating the gross removals as sellable credits.
• Not updating the estimate after the first monitoring data.

What good evidence looks like

For a VVB reviewing the PDD, provide: the planting schedule; parameter table with sources; growth model and its fit; allometry and wood density sources; baseline, leakage, uncertainty and buffer assumptions; and the calculation workbook or code. For buyers and lenders, add sensitivity results and a comparison with ex-post data once available. Ex-ante figures in the project design document should match the financial model.

Indonesia specifics

Growth varies sharply between wet lowlands, seasonal dry regions such as Nusa Tenggara, and highlands. Published growth data exists for major plantation species but is thin for many native and fruit trees, so local pilot plots are valuable. Fire risk in seasonal areas and near peat should be reflected in survival and buffer assumptions.

Our carbon modelling service builds ex-ante models that VVBs and investors can audit. See the ARR hub for the wider project process.