Collaborative spatial planning for forest restoration and resilience in the southeastern United States’ interior highlands

Prioritizing restoration-focused ecosystem management across large areas is challenging when multiple goals are at stake and goals vary among forest managers. This complexity is compounded when forest restoration tools including prescribed fire and silviculture have variable efficacy across landscapes and among management goals. Collaboration between scientists and resource managers to design analyses that address these complexities can clarify contingencies and tradeoffs and provide flexible decision support. White oak and shortleaf pine forests and woodlands have shown strong declines in the eastern United States, and restoration goals are shared by a wide range of stakeholders. We used a collaborative analysis to (1) quantify spatially variable restoration potential for these two species and for wildfire risk reduction potential, and (2) prioritize landscapes for active management under a scenario planning framework. Spatial modeling and optimization relied on several interrelated engagement approaches with diverse partners and experts to generate varied planning scenarios and spatial outputs that reflect a range of prioritization options. Beginning with pre-project engagement with initial key partners, we progressively established a network of scientists, planners, and managers to provide expert input through continuous interaction in an ad-hoc advisory group, and through a series of formal scenario planning and science delivery workshops. Analytical results suggested widespread but geographically variable restoration and risk management opportunities. They also revealed geographic tradeoffs among objectives under the varying management goals and spatial constraints of the planning scenarios. We report the collaborative aspects of a process that connected expert knowledge, landscape data and models, and management support for co-produced science, arguing that collaborative planning increases the likelihood of successful ecosystem restoration.