Simulating spatial complexity in dry conifer forest restoration: implications for conservation prioritization and scenario evaluation

CONTEXT: Several initiatives seek to increase the pace and scale of dry forest restoration and fuels reduction to enhance forest resilience to wildfire and other stressors while improving the quality and reliability of key ecosystem services. Ecological effects models are increasingly used to prioritize these efforts at the landscape-scale based on simulated treatment outcomes. OBJECTIVES: Treatments are often simulated using uniform post-treatment target conditions or proportional changes to baseline forest structure variables, but do not account for the common objective of restoration to mimic the complex forest structure that was present historically which is thought to provide an example of structural conditions that contributed to ecosystem diversity and resilience. METHODS: We simulate spatially homogenous fire hazard reduction treatments along with heterogeneous restoration treatments in dry conifer forests to investigate how spatial complexity affects ecological indicators of (1) forest structural heterogeneity, (2) forest and watershed vulnerability to high-severity fire, and (3) feasibility of future prescribed fire use. RESULTS: Our results suggest that spatially explicit restoration treatments should produce similar wildfire and prescribed fire outcomes as homogeneous fuels reduction treatments, but with greater forest structural heterogeneity. The lack of strong tradeoffs between ecological objectives suggests the primary benefit of spatially complex treatments is to increase forest structural heterogeneity which may promote biodiversity. CONCLUSIONS: We show that landscape-scale prioritization to maximize ecological benefits can change when spatially complex restoration treatments are modeled. Coupling landscape-scale management simulations and ecological effects models offers flexible decision support for conservation assessment, prioritization, and planning.