The land use, land-use change and forestry (LULUCF) sector is one of the most effective tools for mitigating climate change. According to scientific estimates, forests can provide up to one third of emissions reductions (mitigation) by 2030., which the world urgently needs to keep warming below 1.5°C. Although 90 % Nationally Determined Contributions (NDCs) include forests or land use, the reality of implementation is alarming: of the 63 countries monitored, 38 have set specific forest targets, but only 21 of them have submitted the REDD+ technical annex required by the international mechanism.

1. Introduction to PLANT and the strategic context of the LULUCF sector

This gap between political ambition and technical readiness helps bridge the instrument PLANT (Paris Agreement LULUCF Assessment & NDC Tool). As an agile database, UNDP is systematizing data for 56 REDD+ countries and 16 subnational jurisdictions, transforming scattered information into strategic insights. For government officials, this is not just a technical exercise; it is a matter of national sovereignty. Systematizing publicly available data allows countries to own their data, reduce reliance on external third-party estimates, and make autonomous decisions about how to effectively allocate resources to meet their climate commitments.

This strategic data oversight is the first step towards making national forestry data compatible with the strict methodological requirements that we discuss in the next section.

2. Methodological foundations and data sources for the LULUCF sector

Ensuring global trust in climate reporting relies on standardization. Without a uniform methodology, it is impossible to compare individual countries' contributions or verify real progress in carbon sequestration.

The PLANT tool integrates key methodological foundations that ensure technical integrity:

• Application of IPCC (2006) guidelines: The data are classified according to categories 3.B (Soil) and 3.D (Other, mainly harvested wood products).
• Conversion to CO₂: To achieve comparability, the global warming potential (GWP) is used. Country-reported values are used as a priority; in their absence, values from the IPCC Fifth Assessment Report (AR5) are applied.
• Analysis of net vs. gross emissions: The database works with net emissions, which take into account the dynamics of both emissions and removals. Gross emissions are only included where detailed data disaggregation allows.

Data source hierarchy in PLANT:

• GHGI (Greenhouse Gas Inventories): Official greenhouse gas inventories.
• NC (National Communications): National communications sent to the UNFCCC.
• BUR (Biennial Update Reports): Biennial updated reports, often containing REDD+ technical annexes.

Inconsistencies in national methodologies and missing time series have historically distorted global trends. Therefore, cross-checking and validation by international experts within PLANT is essential. Without this credibility, national data remain only internal estimates, which no country can defend to international investors. This readiness to collect data is a fundamental building block for the new transparency requirements.

3. Implementation of the Enhanced Transparency Framework (ETF) and transition to BTR

The year 2024 defines a new era of climate policy. With full activation enhanced transparency framework (ETF) The era of the voluntary MRV system ends and the period of mandatory biennial transparency reporting (BTR) begins.

A key element of the ETF is the so-called "structured summary" (according to paragraph 77 of the MPGs), which serves to track the progress of the NDC. If a country fails to report this data, it risks not only reputational risk in the global assessment (Global Stocktake), but also de facto disqualification from international support mechanisms.

The identification of „critical information gaps“ in PLANT serves as a strategic roadmap for capacity building. However, ETF readiness is only an administrative framework; the actual financial valorization of forests takes place in accordance with technical standards such as ART/TREES.

4. Technical standards and market potential (ART/TREES and JNR)

For countries that view their forests as a strategic asset, voluntary market standards such as ART/TREES or JNR (Verra) gateway to massive funding. However, these standards do not accept administrative promises, but only exact technical results.

The PLANT methodology emphasizes three critical factors in this area:

1. Discounting results: Emissions reductions (ER) that have already been sold under other projects (e.g. VCS, Plan Vivo) or paid under performance-based payments (RBP) must be deducted from the total potential.
2. Methodological deviations: PLANT models the differences between national reference levels and more stringent standard requirements (e.g. historical average vs. projections).
3. Uncertainty assessment (Monte Carlo): This is the point where financial success breaks down. If a country does not use Monte Carlo simulation to calculate uncertainty, PLANT applies a zero discount in the simulation. However, in the reality of the market, this means that such credits will either be unsellable or drastically penalized.

Categorization of compliance with standards in PLANT:

1. Yes: Full compliance.
2. Partially: Partial fulfillment of requirements.
3. Well: Inconsistency.
4. To be evaluated: Insufficient information for assessment.
5. Informational: General requirements without the need for scoring.

Senior Advisor Warning: The lack of forest degradation data is the most common barrier. Without it, TREES certification is virtually impossible, costing the country millions of dollars in potential revenue. Technical compliance with the standards directly determines the market value of forest ecosystems.

5. Simulation of the NDC trajectory and estimation of excess emission reductions

Modeling trajectories to 2030 is essential to understand sectoral linkages. The PLANT simulator allows visualizing the „closed loop of the NDC“: if energy emissions increase, the LULUCF sector must increase its ambition, otherwise the country will not meet its national target.

The simulator logic works with four scenarios:

• BAU (Business as Usual): Development without additional policies.
• Unconditional goal: Reductions achieved through own efforts.
• Conditional target (ER Conditional on $): Emission reduction (ER) results dependent on international financing.
• NDC Target Surplus: The estimated excess of reductions over and above the targets that a country can offer to the market without jeopardizing its own compliance with the Paris Agreement.

Simulation limits: As the UNFCCC has not yet issued detailed guidance for targets for a specific year, PLANT uses a simplified linear projection. This model serves as a strategic indicator, not as comprehensive national modelling, and is intended to identify trends.

6. Methodological limitations and recommendations for future improvements

PLANT is a navigation tool, but its accuracy depends on the quality of the inputs. We identify three main barriers:

• Inconsistent time series: The lack of annual forest cover data makes it impossible to accurately determine reference levels.
• Forest degradation: Reporting on degradation remains the weakest link in national inventories, which directly threatens access to financing.
• Data dynamics: Tracking new submissions across the various UNFCCC portals is a logistical challenge.

Recommendations for future improvements:

• Implementation of financial and budgetary trajectories to link emissions to costs.
• Targeted validation by national experts to eliminate technical uncertainties.
• Improving degradation data collection to increase the chance of certification according to the TREES standard.

Despite its limitations, PLANT provides an invaluable starting point for countries looking to transform their forests from a cost item to a strategic climate asset. However, we strongly appeal to national governments to validate these preliminary assessments and supplement them with their own data. Only transparency and precision in data will ensure that forests fulfill their role in the fight against climate change while also bringing countries a fair financial reward. JRi&CO2AI