Habitat Suitability and Restoration Potential in Estuaries: Integrating Monitoring and Land Cover Data Using EMAP Probabilistic Survey Methods
Lisa M. Smith and Janet A. Nestlerode
U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, Florida
Since 2000, EPA’s National Coastal Assessment (NCA) has collected water and sediment quality data for the estuaries of the U.S. to assess estuarine water quality and sediment quality at state, regional and national scales. The NCA probability survey design serves as a foundation upon which habitat suitability indices (HSIs) can be calculated from water quality, sediment quality and land cover data. Single HSI values are most often developed for a specific site or for an entire estuary. To refine estuary-scale application of HSI models, we used U.S. Fish and Wildlife Service (USFWS) HSI models for brown shrimp (Farfantepenaeus aztecus) to calculate HSI values for each NCA station in Mobile Bay, Alabama. We aggregated these HIS values to estimate the areal percentage of habitat suitability for the whole estuary. Each station HSI value was assigned a numeric score ranging from 0-6 (0 =not suitable; 6 =optimal). The scores were analyzed using a cumulative distribution function (CDF) to estimate the areal extent of habitat suitability for brown shrimp in Mobile Bay. The distribution of habitat suitability could be used to target habitat restoration efforts, evaluate restoration potential, and to develop BMPs for Mobile Bay. Probabilistic surveys are statistically powerful tools for integrating monitoring data, land cover data and HSI models into estuary-scale assessments. The extensive coverage of these type data mean that these tools can be applied to multiple species at multiple scales.