Assessing the causal relationships of ecological integrity: a re-evaluation of Karr's iconic Index of Biotic Integrity

The Index of Biotic Integrity (IBI) has been widely used since the 1980s to estimate ecological integrity-the capacity of an ecosystem to support and maintain its full range of components and processes. Despite this, IBI approaches have been criticized for their lack of objectivity, of justification for the selection of metrics, and of statistical rigor. In this paper, we assessed the potential of canonical correspondence analysis (CCA) and Structural equation modeling (SEM) as complementary methods for assessing ecological integrity. We use an iconic freshwater ecosystem dataset from Northeastern Illinois to assess ecological integrity using both classical IBI approach, and compare this with alternative methods. When we attempt to replicate the IBI methodology, we find issues with the approach including the possibility of the same IBI value for many possible levels of ecological integrity. We showed with the use of other methods (CCA) that the use of tolerant species, total abundance, and total richness-all defining components in IBI -can result in misleading interpretations of ecological integrity and that IBI scores might not comprehensively depict integrity scenarios. Structural equation modeling allowed us to test a conceptual causal model of ecological integrity. We found that water quality had an effect on the diversity and abundance of fish, and these in turn had an effect on trophic function, revealing important relationships between variables that contribute to ecological integrity. We conclude that CCA and SEM can complement multimetric indices, like IBI, and help with the development of more reliable, objective, and science-based estimations of ecosystem integrity, as well as generate testable hypotheses about ecological integrity.