ABSTRACT
Preserving the abundance and stocking of oaks (Quercus spp.) has become increasingly challenging in temperate hardwood forests of the eastern US in recent decades due to a remarkable shift in dominance to mesophytic species (e.g., red maple Acer rubrum). Studies have shown that efforts to sustain oaks while restraining maples yield limited success. Given that a significant portion of forestlands in the eastern U.S. are privately owned, it is critical to assess whether current forest management on cross-ownership forests can achieve those objectives. However, such assessments are rare. In this study, we employed a landscape modeling approach to investigate the long-term outcomes (i.e., 150-year forest composition and structure) of business-as-usual management and alternative management in a large, temperate hardwood forest landscape in Ohio, US. The business-as-usual management continues the current existing management practices, whereas the alternative management increases the pace and scale of forest management on both private and public lands to favor oaks. We compared the basal area and relative dominance for oaks (including Q. alba, Q. coccinea, Q. prinus, Q. rubra, and Q. velutina) and maples (including A. rubrum, A. saccharinum, and A. saccharum). Our results demonstrate that the implementation of business-as-usual management practices on both private and public lands may not effectively ensure the long-term sustainability of oak populations, but instead promote the proliferation of maple species over time. By contrast, alternative management on both private and public lands can effectively sustain oaks across a range of diameter classes while mitigating the growth of large, dominant maples. Our study emphasizes the influential role of private lands in driving oak-maple dynamics at the regional scale, as they can generate significant regional effects even when public lands continue with their business-as-usual management practices. Starting conditions based on landownership are crucial considerations for understanding these dynamics over time.