Pairing ecological modeling and human dimensions in structured decision making: Road management for a declining species

Abstract Natural resource managers face difficult decisions navigating competing objectives, tradeoffs, and uncertainty. Exacerbating the challenge, management of natural resources often intersects with public areas and user groups, prompting managers to consider impacts to societal interests and the diverse preferences of affected groups. Structured decision making (SDM) has emerged as an effective framework for addressing complex natural resource problems. However, few applications have incorporated substantive social science methods to more fully characterize the values and preferences from affected groups to inform decisions. We describe a collaborative SDM process to identify management decisions that best address road threats to a declining species, the diamondback terrapin ( Malaclemys terrapin ), in coastal Georgia, USA, while balancing socioeconomic objectives like human safety, satisfaction, and cost. Because this decision context affects large public user groups, we used human dimensions surveys to characterize social objectives, their relative importance, and groups' support for alternatives. We then paired this information with ecological modeling and expert judgment to predict the effects of 20 management alternatives on objective outcomes. The SDM process showed that the best‐ and worst‐performing management strategies were consistent across all participant groups, showing agreement despite variation in the importance groups assigned to objectives. The best‐performing strategy overall did not rank best for any one objective but included complementary actions (roadside barriers, warning signage, conservation awareness campaigns) that addressed multiple road‐associated threats and performed well across most objectives. Our results provide direct recommendations for addressing terrapin conservation and socioeconomic goals for Georgia, with insights applicable to other road contexts. Furthermore, our study demonstrates the efficacy of using human dimensions research within an SDM framework to inform management decisions by better measuring preferences of large public groups and pairing this information alongside ecological modeling for a robust evaluation of socioecological outcomes.