Adaptation and application of multivariate AMBI (M-AMBI) in US coastal waters.

The multivariate AMBI (M-AMBI) is an extension of the AZTI Marine Biotic Index (AMBI) that has been used extensively in Europe, but not in the United States. In a previous study, we adapted AMBI for use in US coastal waters (US AMBI), but saw biases in salinity and score distribution when compared to locally calibrated indices. In this study we modified M-AMBI for US waters and compared its performance to that of US AMBI. Index performance was evaluated in three ways: 1) concordance with local indices presently being used as management tools in three geographic regions of US coastal waters, 2) classification accuracy for sites defined a priori as good or bad and 3) insensitivity to natural environmental gradients. US M-AMBI was highly correlated with all three local indices and removed the compression in response seen in moderately disturbed sites with US AMBI. US M-AMBI and US AMBI did a similar job correctly classifying sites as good or bad in local validation datasets (83 to 100% accuracy vs. 84 to 95%, respectively). US M-AMBI also removed the salinity bias of US AMBI so that lower salinity sites were not more likely to be incorrectly classified as impaired. The US M-AMBI appears to be an acceptable index for comparing condition across broad-scales such as estuarine and coastal waters surveyed by the US EPA's National Coastal Condition Assessment, and may be applicable to areas of the US coast that do not have a locally derived benthic index.

Relationship of taxonomic error to frequency of observation.

Biological nomenclature is the entry point to a wealth of information related to or associated with living entities. When applied accurately and consistently, communication between and among researchers and investigators is enhanced, leading to advancements in understanding and progress in research programs. Based on freshwater benthic macroinvertebrate taxonomic identifications, inter-laboratory comparisons of >900 samples taken from rivers, streams, and lakes across the U.S., including the Great Lakes, provided data on taxon-specific error rates. Using the error rates in combination with frequency of observation (FREQ; as a surrogate for rarity), six uncertainty/frequency classes (UFC) are proposed for approximately 1,000 taxa. The UFC, error rates, FREQ each are potentially useful for additional analyses related to interpreting biological assessment results and/or stressor response relationships, as weighting factors for various aspects of ecological condition or biodiversity analyses and helping set direction for taxonomic research and refining identification tools.

Step-by-step calculation and spreadsheet tools for predicting stressor levels that extirpate genera and species.

In 2011, the United States Environmental Protection Agency (USEPA) released a field-based method for estimating the extirpation of freshwater aquatic benthic invertebrates by ionic mixtures dominated by HCO3- , SO42- , and Ca2+ measured as specific conductivity (SC). The estimate of extirpation was SC at the 95th centile (XC95) of a weighted cumulative frequency distribution (CFD) of a genus or species over a range of SC. A CFD of XC95 values was used to predict the SC at which 5% of genera were likely to be extirpated. Because there are many uses for XC95 values and many data sets that could be analyzed using this method, we laid out a step-by-step method for calculating XC95 values and the stressor level that predicts a 5% extirpation of genera (HC05). Although the calculations can be done with a handheld calculator, we developed 2 downloadable Microsoft Excel® spreadsheet calculation tools that are easy to use to calculate XC95 values, to plot a taxon's XC95 cumulative frequency distribution with increasing SC, and to plot probabilities of observing a taxon at a particular SC. They also plot cumulative frequency distributions of XC95 values and calculate HC05 values. In addition to the tools, we share an example and the output of XC95 values for 176 distinct aquatic benthic invertebrates in Appalachia, in West Virginia, USA. Integr Environ Assess Manag 2018;14:174-180. © 2017 SETAC.