US Geological Survey
Optimizing historic preservation under climate change: Decision support for cultural resource adaptation planning in national parks
Date of this Version
Land Use Policy 83 (2019) 379–389
Climate change poses great challenges for cultural resource management, particularly in coastal areas. Cultural resources, such as historic buildings, in coastal areas are vulnerable to climate impacts including inundation, deterioration, and destruction from sea-level rise and storm-related flooding and erosion. However, research that assesses the trade-offs between actions for protecting vulnerable and valuable cultural resources under bud- getary constraints is limited. This study focused on developing a decision support model for managing historic buildings at Cape Lookout National Seashore. We designed the Optimal Preservation Decision Support (OptiPres) model to: (a) identify optimal, annual adaptation actions for historic buildings across a 30-year planning hor- izon, (b) quantify trade-offs between different actions and the timing of adaptation actions under constrained budgets, and (c) estimate the effectiveness of budget allocations on the resource value of historic buildings. Our analysis of the model suggests that: (1) funding allocation thresholds may exist for national parks to maintain the historical significance and use potential of historic buildings under climate change, (2) the quantitative as- sessment of trade-offs among alternative adaptation actions provides generalizable guidance for decision makers about the dynamics of their managed system, and (3) the OptiPres model can identify cost-efficient approaches to allocate funding to maintain the historical value of buildings vulnerable to the effects of climate change. Therefore, the OptiPres model, while not designed as a prescriptive decision tool, allows managers to understand the consequences of proposed adaptation actions. The OptiPres model can guide park managers to make cost- effective climate adaptation decisions for historic buildings more transparently and robustly.
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