Using Multiple Taxonomic Groups to Index the Ecological Condition of Lakes

Abstract

Biological indicators of communitiestypically reflect a common environmental signalreflecting the general condition of the ecosystem, as well asindividual signals by indicators differentiallysensitive to particular environmental conditions. Wedescribe here a method of integrating and interpretingsuch indicators from 19 New England lakes for fivetaxonomic groups (diatoms, benthos, zooplankton, fish,and birds). Our approach provides a systematicstandardized way to integrate multiple metrics fromdifferent taxonomic groups by addressing four elementscrucial to analyzing data from multiple indicators: covariate control, re-scaling of data, standardizing the sign of responses, and dimensional reduction. We evaluated the biologicalmetrics against individual environmental stressors andagainst multivariate physicochemical metricscharacterizing general anthropogenic stress among thelakes. The method detected a response to variationin the gross environmental condition of the lakes thatwas correlated across taxa and metrics. In addition,a differential response to near shore conditions wasdemonstrated for fish. The success of the approach inthis study lends support to its general application toecological monitoring involving complex data sets.