Meta-analysis of estuarine nurseries

Densities of juvenile fishery species and other animals (all generally 100 mm total length) were summarized for shallow estuarine areas along coastal Texas and Louisiana. The purpose was to identify where these species live (delineate their habitat) and to analyze density patterns within habitats that would be useful in distinguishing EFH. Analyses were restricted to data collected with enclosure drop sampler techniques that have been shown to provide comparable density estimates among highly diverse shallow-water areas. Habitat types evaluated included Spartina alterniflora marsh edge (SAME), mixed-vegetation marsh edge, inner marsh (5 m from open water), submerged aquatic vegetation (SAV), oyster reefs, and shallow nonvegetated bottom (SNB). All habitat types are likely essential for some fishery species. The analysis highlighted many of the challenges confronted in determining habitat-use patterns and emphasized the need for additional systematic sampling to examine geographic variability in habitat use and to examine distribution patterns within habitats. However, in addition to analyses of intra-habitat densities, the identification of EFH requires information on functional relationships between fishery species and habitat characteristics. In a second paper, the nursery role of salt marshes was examined for transient nekton by searching the global literature for data on density, growth, and survival of juvenile fishes and decapod crustaceans in marsh areas. We analyzed density data from 32 studies conducted world-wide using a meta-analyses to test hypotheses. Based on fish density, habitat types could be ranked from highest to lowest as: seagrass vegetated marsh edge, nonvegetated marsh, open water, macroalgae, oyster reefs vegetated inner marsh. However, patterns of habitat use varied among the various fishes and decapod crustaceans represented.

Assess selection of estuarine habitats

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Each sample was assigned a unique identification code. Field collected samples were tagged redundantly (e.g. one label inside of the collection vessel and a matching label attached to the outside of the vessel). The identifier and its associated information (e.g. date, location, habitat) was recorded on field data sheets. Once a sample arrived at the laboratory, the label remained with the sample throughout the various stages of sample processing. After data were entered into an Excel spreadsheet or similar database file, the information was printed out and compared against the field data sheets by two biologists. Corrections were made at this time and saved. The electronic file was also sorted and examined by the Lab Supervisor or other project personnel in a variety of ways to look for outliers, missing data, and other potential errors.

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