The Public Data and Models Supporting Improved Forest Management 

Every credit issued under an Improved Forest Management (IFM) protocol is built upon a foundation of publicly available data, models, and frameworks for understanding regional timber producers and markets. The development and maintenance of these resources is critical for carbon quantification at the forest scale, and for the data-driven evolution of IFM baseline approaches.  

IFM Foundations 

Improved Forest Management projects involve translating raw measurements of individual trees into estimates of total forest carbon stocks over large project areas at project initiation and forecasting those carbon stocks under different management scenarios for decades into the future. This work depends on biomass estimation techniques such as allometric regression, biomass algorithms, and component ratio methods which are based on research projects dating as far back as the 1970’s (e.g., citations in Jenkins et al. 2003). IFM projects generally require projections of how forest carbon stocks will evolve over time under both baseline and project scenarios. The Forest Vegetation Simulator (FVS), developed and maintained by the USDA Forest Service, is the primary publicly available tool for this purpose. FVS models individual tree growth, mortality, and response to management activities across a wide range of forest types and regions, and it is widely accepted by offset registries and verifiers as the standard for forest carbon stock projections in the United States.  

Innovations in Additionality 

Robust, publicly available data products are key to the growth and continued innovation of the forest carbon markets. The USDA Forest Service’s Forest Inventory and Analysis (FIA) program, which has been running continuously since 1930, is the primary input for the calculation of common practice carbon values used to set baselines under the California Air Resources Board (CARB) Forest Protocol, which represents roughly 80% of the US-based Forestry and Land Use carbon credits issued to date. FIA data is also a vital input to the newer CCP-approved VM0045 protocol, which awards credits to IFM projects by comparing with-project stock change to observed stock change on similar forestlands outside of the project area, via a dynamic baseline matching process that sources plot-level data from national forest inventories. In a similar vein, the CCP-approved ACR IFM Methodology v2.1 utilizes data products such as the Landscape Change Monitoring System (LCMS), a remote sensing-based system for mapping and monitoring landscape change across the United States developed by USDA Forest Service, to set baseline harvesting rates to those observed on comparable forest ownerships in the region (Figure 1).  

As the forest carbon market has matured, demonstrating additionality and project integrity remain the central focus. The public data systems built and maintained by the U.S. Forest Service remain the indispensable foundation. Transparent, consistently collected, and freely accessible data means that baselines can be independently scrutinized, updated as forest conditions change, and applied in a standardized manner across projects. Amidst the current uncertainty around USDA Forest Service research funding during the current restructuring effort, the contributions of these services should be highlighted for all carbon market stakeholders.