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Evaluation of the lake macroinvertebrate integrity index (LMII) and alternate indices for eastern U.S. lakes and reservoirs
Citation:
North, S., J. KURTENBACH, K. A. BLOCKSOM, AND F. BORSUK. Evaluation of the lake macroinvertebrate integrity index (LMII) and alternate indices for eastern U.S. lakes and reservoirs. Presented at National Water Quality Monitoring Conference, Denver, CO, April 25 - 29, 2009.
Impact/Purpose:
The goal of this research is to develop methods and indicators that are useful for evaluating the condition of aquatic communities, for assessing the restoration of aquatic communities in response to mitigation and best management practices, and for determining the exposure of aquatic communities to different classes of stressors (i.e., pesticides, sedimentation, habitat alteration).
Description:
We applied the Lake Macroinvertebrate Integrity Index (LMII) to 69 lakes and reservoirs across the eastern United States. Genus-level sub-littoral benthos samples, collected by EPA Regions 2 and 3 in 2007, were used to calcualte LMII scores for each lake. We investigated relationships between LMII and physical habitat, water chemistry, and land use variables collected by the National Lakes Assessment (NLA) team in 2007. LMII was analyzed by its ability to discriminate between lakes of differing NLA impairment status and by its relationships to known physical, chemical, and land use gradients. Using Barbour et al. (1996) box plot scoring guidance, LMII performed well for mixed sediment lakes, but poorly for muck lakes and sand lakes. LMII performed better for hard lakes (conductivity >100 uS) than soft lakes (conductivity < 100 uS), and for natural lakes than reservoirs. Major patterns of environmental variation were detected by principal component analysis (PCA). Because LMII performance was generally poor across lakes, we created two alternate indices using candidate metrics for widespread application. Thirty additional metrics were considered, selecting those that demonstrated the strongest linkages to taxonomic and environmental distributions across the study area. Alternate indices differed from one another by relative foci on pollution tolerance versus other taxonomic attributes. Non-metric multidimensional scaling (MNS) revealed overall community composition by plotting lakes in species space. The model converged upon a 3-dimensional solution that captured 80% of species variation. Ordination joint plots and Spearman correlations linked biota composition to water chemistry and substrate gradients, revealing stronger linkages to both alternate indices than to the original LMII. Rank-transformed Multi-Response Permutation Procedures (MRPP) validated NMS groupings by index, sediment and lake status, rejecting groupings by NLA class, cluster or trophic state. Research findings can be used to implement biological criteria in state water quality programs in EPA Regions 2 and 3, more accurately determine aquatic life use support for 305(b) reports and 303(d) listing, and prioritize lakes for protection.