Modeling climate-proactive forest management and projected consequences for forest resilience and ecosystem services
Tuesday, August 3, 2021
ON DEMAND
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Kathleen M. Quigley, Gordon C. Reese and Brian R. Sturtevant, USDA Forest Service Northern Research Station, Rhinelander, WI, Lynne M. Westphal, Northern Research Station, USDA Forest Service, Evanston, IL, Jason Crabtree and Forrest D. Fleischman, University of Minnesota, St. Paul, MN, Jonathan R. Thompson and Joshua Plisinski, Harvard Forest, Harvard University, Petersham, MA, David N. Bengston, USDA Forest Service Northern Research Station, St. Paul, MN
Presenting Author(s)
Kathleen M. Quigley
USDA Forest Service Northern Research Station Rhinelander, WI, USA
Background/Question/Methods Novel forest management strategies, including assisted migration (AM), may be necessary to maintain forest health and ecosystem services as earth’s climate changes. However, implementing AM strategies that will have the intended consequences involves uncertainties regarding latitudinal and elevational biome shifts and the productivity and resiliency of future forests. For example, in the upper Midwest of the United States, species like spruce and fir are expected to decline as the climate becomes warmer and drier, highlighting the vulnerability of local forest ecosystems. Following consultation with local forest stakeholders, we used the LANDIS-II forest landscape model to simulate the effects of contrasting management strategies, varying from ‘business as usual’ (i.e. current forest management projected into the future) to management approaches that more proactively address climate change (AM introduced alongside novel harvest prescriptions). Under the climate proactive strategy, AM consisted of planting species better adapted to a warmer and drier climate, like oaks, following harvests of declining boreal species. Results/Conclusions Results indicate that high intensity planting efforts are needed to observe effects of AM on forest type distribution across the landscape as well as on ecosystem services. Furthermore, there was a significant time lag (> 50 years) before observing any such changes, which suggests that AM strategies should be implemented well ahead of projected forest decline to ensure forest health and productivity. Once established, AM species also appear to be very resilient to both wind and fire disturbance, as demonstrated by reduced post-disturbance mortality relative to business as usual forest management. Although AM species were susceptible to insect defoliation by forest tent caterpillar, deleterious effects were minor relative to the competitive advantages of these species. Overall, our results suggest that forest landscape models are a powerful tool for assessing the potential costs and benefits of novel forest management and for predicting the resiliency of future forests to natural disturbance.