The loss of ecosystem services due to climate change and coastal development is projected to have significant impacts on local economies and conservation of natural resources. Consequently, there has been an increase in coastal management activities such as living shorelines, oyster reef restoration, marsh restoration, beach and dune nourishment, and revegetation projects.
A capstone example is based on a recent barrier island restoration assessment project at Dauphin Island, Alabama.
Dauphin Island and the remainder of the barrier islands fronting the Mississippi Sound have been historically losing surface area and their capacity to protect mainland natural resources and infrastructure is diminishing. Rising sea levels, severe and frequent storms, and engineering activities all threaten the sustained subaerial presence. Moreover, loss of barrier island area threatens the estuarine ecosystem of Mississippi Sound and its resources, and exposes the mainland coast to increasing saltwater intrusion and damage from future storms.
Coastal management decisions are complex and include challenging trade-offs. Decision science offers a useful framework to address such complex problems. Here, we provide a synthesis about how decision science can help to integrate research from multiple disciplines (physical and life sciences) with management of coastal and marine systems. Specifically, we discuss the importance of considering concepts and techniques from ecology, coastal geology, geomorphology, climate science, oceanography, and decision analysis when developing conservation plans for coastal restoration. We illustrate the process with several coastal restoration studies.
This project included the development of geomorphological and ecological models. We show how decision science can be used as a framework to combine geomorphological and ecological modeling to help inform management decisions while considering uncertainty about system changes and risk tolerance. We also build on our examples through a review of recently developed techniques for spatial conservation planning for land acquisition decisions and the application of adaptive management for sequential decisions.
Gaining an understanding of the island’s historical evolution as well as the physical, topographic, bathymetric, geologic, and oceanographic setting was necessary to help maximize the likelihood of restoration success. These factors have not only played an important role in understanding how the island has evolved over time but will govern how it will respond in the future.
Major uncertainties in restoration project planning and design center largely around climate change, relative sea level change, and how to predict system responses to these changes over time. These uncertainties are especially relevant to the ecological, social, resource, and fiscal objectives for restoration options on Dauphin Island. In an effort to reduce these uncertainties, climate and sea level change considerations were integrated into the various technical analyses as described in the previous tabs.
The results of these analyses provided valuable insight into possible future island conditions should no action be taken. For example, the model results for the most severe storm (increased occurrence and intensity) and increased sea level (higher value) scenario predicted breaching on both sides of the Katrina Cut structure. Additionally, the analyses indicated the breaching could, in turn, influence the water quality in parts of the Mississippi Sound resulting in changes to oyster and seagrass habitat suitability on the lee side of Dauphin Island. The models also predicted increased loss of beach and dune habitat along both the east and west ends of the island as well as the conversion of intertidal marsh habitat to intertidal flat or estuarine open water habitats as a consequence of high sea level change rates. The results of these analyses were ultimately used to inform the development of specific restoration measures that could meet objectives and be evaluated through the integrated modeling framework and structured decision-making process.