Simulating the heterogeneous consequences of widespread forest health treatments for California mixed conifer forest resilience to climate change and wildfire
Principal Investigator: Lara M. Kueppers
Project Partners: John Battles, Polly Buotte, Jackie Shuman, and Jeff Leddy. Data contributions from Alex Hall, Adrian Das, Eric Knapp, Patricia Manley, and Malcolm North.
Institution: University of California, Berkeley
Project Type: Demonstration State Forests
Grant Award: #8GG19806
Amount awarded: $499,660
Award Date: September, 2019
Since 2013, California has experienced its largest, most deadly, and most destructive fires in recorded history, extreme drought, and record tree mortality. Due to the effects of a changing climate, future area burned, drought, and tree mortality are expected to increase. There is a widely recognized need to make CA forests more resilient, provide long-term carbon storage, and reduce GHG and black carbon emissions. Yet, as the climate changes, tree physiology, demography and competitive outcomes are expected to shift due to feedbacks among climate, plant traits, forest structure and fire regimes, leading to potentially novel forest conditions. These feedbacks are not mechanistically captured in models currently used in forest planning and management. In this project, we are benchmarking a new process-based model framework that captures these feedbacks, CLM-FATES, against forest responses to thinning and prescribed fire treatments measured in state, federal and university forests in multiple locations in California. We are using CLM-FATES to answer these research questions for California mixed conifer forest, within which lie many CalFire-FRAP high priority watersheds:
1. How do the interactions among initial stand structure, forest health treatment, and climate change affect future forest structure and function?
2. Which treatments are most likely to limit CO2 emissions from future wildfire?
3. Which treatments are likely to promote resilience of carbon storage and stand structure to future fire and drought?
We employ a 3-dimensional matrix of future simulation experiments to capture interactions among initial stand structure, forest health treatment and climate change. Treatments will cover a range of thinning and prescribed fire approaches, guided by stakeholder input. Stand density will capture the range of stand conditions in current and historical mixed conifer forests, and climate projections will encompass the variability in projected temperature and precipitation change in the CMIP6 database across California. We will address each of our questions by quantifying differences among simulations in aboveground carbon, growth rate, stand density, stand composition, area burned, fire intensity, CO2 emissions from fire, and multiple traditional and novel metrics of resilience.
Our analyses will inform and support implementation of the 2018 Forest Carbon Plan, the 2018 Strategic Fire Plan, and the 5th Climate Change Assessment. There is uncertainty in future climate projections, but our research will enable managers to assess the influence of this uncertainty on forest health treatment (thinning and prescribed fire) effects across a range of stand density and environmental conditions. This will provide additional input to selection of forest health treatments that promote forest resilience and carbon storage stability and limit future CO2 emissions, given the existing stand conditions in a project area.
Hanbury-Brown, A.R., Ward, R.E. and Kueppers, L.M. (2022), Forest regeneration within Earth system models: current process representations and ways forward. New Phytol, 235: 20-40. https://doi.org/10.1111/nph.18131
Hanbury-Brown, A.R., Powell, T.L., Muller-Landau, H.C., Wright, S.J. and Kueppers, L.M. (2022), Simulating environmentally-sensitive tree recruitment in vegetation demographic models. New Phytol, 235: 78-93. https://doi.org/10.1111/nph.18059