Hundred year projected carbon loads and species compositions for four National Forests in the northwestern USA

Abstract

Background: Forests are an important component of the global carbon balance, and climate sensitive growth and yield models are an essential tool when predicting future forest conditions. In this study, we used the dynamic climate capability of the Forest Vegetation Simulator (FVS) to simulate future (100 year) forest conditions on four National Forests in the northwestern USA: Payette National Forest (NF), Ochoco NF, Gifford Pinchot NF, and Siuslaw NF. Using Forest Inventory and Analysis field plots, aboveground carbon estimates and species compositions were simulated with Climate-FVS for the period between 2016 and 2116 under a no climate change scenario and a future climate scenario. We included a sensitivity analysis that varied calculated disturbance probabilities and the dClim rule, which is one method used by Climate-FVS to introduce climate-related mortality. The dClim rule initiates mortality when the predicted climate change at a site is greater than the change in climate associated with a predetermined shift in elevation. Results: Results of the simulations indicated the dClim rule influenced future carbon projections more than estimates of disturbance probability. Future aboveground carbon estimates increased and species composition remained stable under the no climate change scenario. The future climate scenario we tested resulted in less carbon at the end of the projections compared to the no climate change scenarios for all cases except when the dClim rule was disengaged on the Payette NF. Under the climate change scenario, species compositions shifted to climatically adapted species or early successional species. Conclusion: This research highlights the need to consider climate projections in long-Term planning or future forest conditions may be unexpected. Forest managers and planners could perform similar simulations and use the results as a planning tool when analyzing climate change effects at the National Forest level.