This benthic index, although developed for EMAP-Estuaries in the Louisianian Province, is easily applied to 

 benthic data from other sampling programs in the northern Gulf of Mexico (see the examples in Engle and 

 Summers [1998]). This benthic index has been successfully applied by others in order to assess benthic 

 conditions in specific estuaries on the Gulf coast. Alabama's Department of Environmental Management 

 effectively used this benthic index to assess the sediment quality in the estuaries of their state (Carlton etal. 

 1998). Similarly, this EMAP benthic index successfully discriminated degraded from undegraded sites in a 

 regional assessment of environmental conditions in Galveston Bay, Texas (C. Gorham-Test, unpublished 

 data). The Texas Natural Resource Conservation Commission applied this benthic index to sites in a targeted 

 study of land use in Galveston Bay and found significant correlations with site rankings based on sediment 

 toxicity tests and sediment chemical concentrations (G. Guillen and L. Broach, pers. comm.). Although the 

 Louisianian Province is geographically widespread, we caution the application of the index outside of this 

 biogeographic region. The environmental stresses affecting the benthos in Gulf of Mexico estuaries may 

 differ from those affecting other regions (e.g., the Mid-Atlantic or Pacific Northwest). 



We have successfully synthesized benthic community information into a benthic index of ecological condition 

 that provides environmental managers with an alternate way to assess the status of benthic communities 

 over large geographical areas. A response indicator like the benthic index provides a numerical quantification 

 of the response of the benthic communities to environmental stresses (Summers et al. 1 995). Because the 

 benthic index is scalable and the criteria for determining the classification of degraded or undegraded are 

 numeric, the application of the benthic index to other estuaries is straightforward. 



Summary 



The results of this evaluation show that the benthic index is an appropriate indicator for determining the 

 extent of degraded benthic communities in a regional monitoring program. The indicator is conceptually 

 relevant to both the assessment question and ecological function. When part of the collection for a suite of 

 indicators, collecting sediment for benthos is easily implemented and standardized methods are well- 

 established. The greatest cost of implementing the benthic index is in the laboratory processing charges. 

 Temporal and spatial variability have been minimized by both the EMAP-E sample design and rigorous 

 training and QC of the field and laboratory personnel. Probably the greatest concern in the implementation 

 of this indicator is the discriminatory ability of the benthic index. The percent efficiency of the benthic index 

 to classify independent sites was adequate but not as high as we had hoped. Because the EMAP-E design 

 is not limited to specific habitat types but characterizes a region as a whole, there is, inherently, a high degree 

 of variability in the benthic communities in the Gulf of Mexico region. We may have sacrificed a level of 

 precision in favor of a generalized index that is applicable across a wide geographic area. 



Potential users have criticized this index approach because of various perceived difficulties in application. 

 Several reviewers have expressed that indices of biotic integrity (IBIs) are easier to understand. We would 

 agree that the IBIs modeled after Karr (1981 ) are more intuitive in that the models are forced to incorporate 

 the conceptual framework of the developer. The EMAP benthic index employs the same generalized approach 

 but assumes multi-stressor relationships and depends solely on the data to delineate which benthic parameters 

 relate to the observed situation. The IBIs are also perceived to be easier to employ. Clearly, they may be 

 easier to develop than the proposed benthic index but the scoring on multiple habitats of 4 to 7 parameters is 

 certainly more involved than inserting 5 parameters into an equation. The normalization to force the range to 

 be between and 10 is for ease of interpretation and does not need to be done {i.e., if not normalized, the 

 cut-off between poor condition and marginal condition is 0.0). Finally, the index proposed here is applicable 

 over a wide range of environmental conditions and geography and provides comparable scores over these 



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