OOS 2-6 - Leveraging data and models to fill gaps in monitoring, reporting, and verification of forest-based climate mitigation

Many nations, including the United States (US), plan to rely on forest-based climate mitigation activities, such as protection and improved forest management, to create additional and long-term carbon sequestration and contribute to emission reduction targets. Forest simulation models can be useful for anticipating forest change and testing alternative scenarios. There is a great diversity of models that simulate forest systems, including growth and yield models, forest landscape models, and dynamic global vegetation models. Each have key capabilities, or explicit representation of key processes, needed to fill gaps in monitoring, reporting and verification, as well as specific areas for improvement, such as accurately and precisely representing forest response to changing climate. The strength of empirical forestry models is their long history of development and use for site-specific forest management. However, they often lack representation of the direct influence of climate on tree growth and hence should be expected to extrapolate poorly to novel climate conditions. The most widely used growth and yield model in the US, the Forest Vegetation Simulator (FVS), which also forms the basis for several forest carbon calculators, does not currently include the direct effect of climate variation on tree growth. Key to filling gaps is the use of multiple data sources with information at complementary spatial and temporal scales. We illustrate this with the creation of a climate-sensitive version of FVS, parameterized with annually resolved tree-ring and spatially representative forest inventory data. We validated tree growth predictions from a suite of alternative models with independent observations, and evaluated model performance in terms of accuracy, precision, and bias. We then compared predictions of future growth made by the existing model used in FVS, i.e., without climate effects, to those of our updated models, including those with climate effects. We found that the incorporation of climate effects improves model performance, where growth is currently overpredicted by FVS. Diameter growth projected with improved, climate-sensitive models is less than the future tree growth projected by the current climate-insensitive FVS model. A climate-sensitive forest simulator and decision support tool will improve planning of site-level climate mitigation activities in the US by providing more realistic expectations of the carbon sequestration potential of forests undergoing climate change. Greater investment in model development, including the addition of new data sources, provides a path forward to better assessment and anticipation of forest-based climate mitigation.