M-ICR009
14. Afforestation/reforestation
Last updated
14. Afforestation/reforestation
Last updated
Afforestation and reforestation
Under validation
Waiting for completion of validation
This methodology introduces the application of Net Ecosystem Exchange (NEE) as a comprehensive approach to quantifying carbon benefits from integral ecosystem management projects. Unlike traditional methods that measure individual carbon pools (e.g., biomass or soil) separately, NEE captures the total carbon flux of an ecosystem - the balance between CO2 absorbed through photosynthesis and released via ecosystem respiration. This holistic approach reduces uncertainties, simplifies measurements, and provides accurate and scalable carbon accounting.
The methodology applies to projects implementing land management practices aimed at enhancing ecosystem-level carbon removal. Due to the comprehensive nature of NEE, the methodology is applicable to all project activities that increase carbon sequestration and storage in terrestrial biomass. The methodology quantifies carbon removal enhancement from the implementation of sustainable land management. The methodology does not provide estimations of avoided emissions. This methodology relies on advanced dMRV tools that combine direct carbon flux measurements from eddy covariance ground stations with satellite-based remote sensing data. Eddy covariance stations capture real-time carbon flux, while machine learning models extrapolate these measurements using high-resolution satellite imagery. This integration enables scalable, accurate, and consistent monitoring of ecosystem-level carbon dynamics across large areas with 30-meter resolution. Key features of the NEE-based approach:
Ecosystem-Level Measurement: Biogenic carbon fluxes are assessed at the ecosystem level without separating individual carbon pools.
Intervention-Agnostic: The methodology uses remote sensing and independent measurements, avoiding reliance on specific interventions or carbon pools.
Ex-Post Assessment: Carbon removals are evaluated ex-post using primary NEE data from eddy covariance ground stations and satellite-based remote sensing.
Adaptive Uncertainty Management: As NEE measurement technology evolves, the methodology allows for ex-post refinement of NEE estimates and updates to uncertainty levels, improving accuracy over time.
The methodology incorporates a broad spectrum of integral ecosystem management practices aimed at achieving enhanced ecosystem-level carbon removal. These practices include, but are not limited to:
Direct ARR practices, such as manual planting, broadcast seeding, etc.;
Indirect ARR practices, such as assisted natural regeneration like herbivory enclosures, nature
Conservation activities;
Soil conservation and management, i.e. soil preservation, enhancement, and erosion control;
Sustainable grassland management such as rotational grazing.
The methodology employs a baselining approach that utilizes historical NEE data to model biogenic emissions and removals in the baseline scenario. This data is derived from the project area or representative monitoring areas that accurately reflect pre-project conditions. Non-biogenic emissions are quantified separately based on emission factors and inventory data. Project biogenic emissions and removals are calculated using ongoing NEE data. Carbon benefits are assessed ex-post by combining ongoing and historical NEE data, a non-biogenic emissions inventory, and adjustments for uncertainty.
Permanence is monitors by continuous NEE monitoring, capturing any carbon flux reversals and securing long-term carbon sequestration. The permanence of carbon storage in a product carbon pool is assessed using the life cycle assessment (LCA) approach.
