Simulating Timber Harvest to Assess Potential Impacts to Forest Wildlife Habitat on State Lands in Minnesota, USA

Forest management and planning efforts often account for many resource objectives and benefits, including wildlife habitat. In particular, newly approved management goals and harvest targets on state lands in Minnesota were examined for their potential impact on wildlife habitat. Using a list of stands planned for potential harvest and a regional wildlife habitat model, habitat effects were assessed for 173 native, forest-dependent wildlife species on state lands. Leveraging forest type– and region-specific harvest probabilities and post-examination lag times to harvest, three simulation efforts covering the spectrum of possible outcomes were used to estimate habitat change from 2020 to 2030. In the most realistic simulation, 31.8% of species exhibited statistically significant positive habitat change, 11.6% significant negative change, and 56.6% nonsignificant or no change. Compared with simulations reflecting more extreme levels of harvest, the realistic simulation showed the greatest compromise between negative and positive shifts in habitat. Results reflect tradeoffs in wildlife habitat preferences such that changes in management that positively affect certain species often negatively affect others. Tradeoffs may be addressed by providing flexibility to individual managers where a targeted prescription is justified for a specific species, all while continuing broad statewide forest management goals. Study Implications: This study investigated how forest stands planned for management examination at a state-agency level may affect wildlife habitat over a 10-year horizon using a series of simulations. When broadly considering many wildlife species at this scale, changes in forest management show tradeoffs in habitat effects between species. Balancing this tradeoff for statewide habitat, managers should focus on targeted management for individual species based on local forest conditions and individual manager expertise.