Social-ecological challenges for cost-effective restoration of degraded ecosystems

Background/Question/Methods: A variety of ecosystems around the world are becoming rapidly degraded by global change and human activity. Restoration of these ecosystems may result in significant benefits and is becoming a common practice. However, restoration actions, such as reintroduction of species and eradication of invasive species, are expensive. Therefore, it is important to determine whether, where, when and how to restore. This is challenging as ecosystems are complex and their control may combine multiple actions, by several agents, to simultaneously achieving multiple goals. In my talk, I will propose a solution in three steps. First, I will present a general model where population growth can be induced or inhibited by active restoration and I will find the optimal restoration strategy. Second, I will use optimal control with constraint optimization for resolving conflicting conservation goals where actions for reaching one goal have negative impacts on the other goal. Specifically, I will focus on a case study where eradication of hybrid Spartina, an invasive plant, has threatened the recovery of an endangered bird that uses Spartina for nesting habitat. Third, I will present a solution, based on dynamic game theory, for the case where several agents contribute to restoration.

Results/Conclusions: First, I will show that when restoring for a single goal by a single agent, restoration should take place until a certain threshold is approached and possibly again during the final stage of the recovery process. Next, I will show that in the presence of conflicting goals, optimal management entails less intensive treatment over longer timescales, to fit with the timescale of natural processes. Therefore, managers should simultaneously consider multiple, potentially conflicting goals, which may require flexibility in timing of budgetary expenditures. Finally, I will show that when multiple agents restore the same ecosystem, under certain conditions there is a way to coordinate cooperation among agents by utilizing the course of time: There exists a solution (Nash equilibrium) where all agents actively participate, albeit slowly enough, such that no agent would like to free-ride.