Advancing forest carbon projections requires improved convergence between ecological and economic models.

Forests have the potential to contribute significantly to global climate policy efforts through enhanced carbon sequestration and storage in terrestrial systems and wood products. Projections models simulate changes future in forest carbon fluxes under different environmental, economic, and policy conditions and can inform landowners and policymakers on how to best utilize global forests for mitigating climate change. However, forest carbon modeling frameworks are often developed and applied in a highly disciplinary manner, e.g., with ecological and economic modeling communities typically operating in silos or through soft model linkages through input-output parametric relationships. Recent disciplinary divides between economic and ecological research communities confound policy guidance on levers to increase forest carbon sinks and enhance ecosystem resilience to global change. This paper reviews and summarizes the expansive literature on forest carbon modeling within economic and ecological disciplines, discusses the benefits and limitations of commonly used models, and proposes a convergence approach to better integrating ecological and economic systems frameworks. More specifically, we highlight the critical feedback loops that exist when economic and ecological carbon models operate independently and discuss the benefits of a more integrated approach. We then describe an iterative approach that involves the sharing of methodology, perspectives, and data between the regimented model types. An integrated approach can reduce the limitations or disciplinary bias of forest carbon models by exploiting and merging their relative strengths.