Measuring and Managing Resistance and Resilience Under Climate Change in Northern Great Lake Forests (USA)

Context: Climate change will have diverse and interacting effects on forests over the next century. One of the most pronounced effects may be a decline in resistance to chronic change and resilience to acute disturbances. The capacity for forests to persist and/or adapt to climate change remains largely unknown, in part because there is not broad agreement how to measure and apply resilience concepts. Objectives: We assessed the interactions of climate change, resistance, resilience, diversity, and alternative management of northern Great Lake forests. Methods: We simulated two landscapes (northern Minnesota and northern lower Michigan), three climate futures (current climate, a low emissions trajectory, and a high emissions trajectory), and four management regimes [business as usual, expanded forest reserves, modified silviculture, and climate suitable planting (CSP)]. We simulated each scenario with a forest landscape simulation model. We assessed resistance as the change in species composition over time. We assessed resilience and calculated an index of resilience that incorporated both recovery of pre-fire tree species composition and aboveground biomass within simulated burned areas. Results: Results indicate a positive relationship between diversity and resistance within low diversity areas. Simulations of the high emission climate future resulted in a decline in both resistance and resilience. Conclusions: Of the management regimes, the CSP regime resulted in some of the greatest resilience under climate change although our results suggest that differences in forest management are largely outweighed by the effects of climate change. Our results provide a framework for assessing resistance and resilience relevant and valuable to a broad array of ecological systems