Coastal Louisiana ecosystem assessment and restoration program: The role of ecosystem forecasting in evaluating restoration planning in the Mississippi River Deltaic Plain

Abstract

The development of ecosystem management plans to restore and rehabilitate natural resources requires an understanding of how specific ecological mechanisms regulate the structure and function of ecosystems. To achieve restoration goals, comprehensive plans and engineering designs must effectively change environmental drivers at the regional level to reduce stress conditions at the local environment that are responsible for ecosystem degradation. This document focuses on the Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) ecosystem forecasting framework and how it can be used to support the analysis of Louisiana’s coastal restoration plans. Specifically, the framework is designed to (1) develop and incorporate conceptual ecological models that can be used to integrate ecological needs and opportunities with engineering designs, (2) utilize wetland loss rates to describe the most likely “future without” scenario for a variety of ecosystem attributes, (3) estimate broad ecosystem responses to restoration alternatives based on processes associated with succession of geomorphic and ecological systems, and (4) calculate ecological benefits for incorporation into decision support tools associated with large-scale geomorphic and hydrologic processes. This paper provides a brief overview of the spatial framework and modular design of the CLEAR ecosystem forecasting framework and describes in greater detail the evolution of the landscape change module, concepts for its refinement, and how it was utilized in evaluating a coastal restoration alternative proposed in the Coastal Protection and Restoration Authority Preliminary Draft Master Plan. Such projections by the CLEAR forecasting framework can evaluate processes and conditions that result in sustainable coastal ecosystems with habitat functions that support higher trophic levels.