Taxonomic sufficiency: The influence of taxonomic resolution on freshwater bioassessments using benthic macroinvertebrates

Author:

Jones F. Chris1

Affiliation:

1. Trent University, Watershed Ecosystems Graduate Program, 1600 West Bank Drive, Peterborough, ON K9J 7B8, Canada (e-mail: ).

Abstract

Changing the taxonomic scale of a biotic-assemblage dataset influences our ability to detect ecological patterns. In bioassessments, a test-site’s biological community is compared against a benchmark to indicate ecosystem condition, but the taxonomic resolution needed to judge impairment reliably is the subject of much scientific debate. This paper reviews taxonomic sufficiency for freshwater benthic-macroinvertebrate bioassessments. Three main issues are discussed: (1) the ecological significance of different taxonomic aggregations; (2) trade-offs involving taxonomic detail and information content versus money, time, expertise, and data quality; and (3) sampling- and analytical-method-specific factors affecting taxonomic sufficiency. Although Species should be the default taxonomic level for bioassessments, taxonomic sufficiency is chiefly determined by a study’s purpose, and pragmatism often dictates reduced detail. When a taxonomic-minimalism approach is necessary, a quantitative criterion for taxonomic sufficiency should be specified; this criterion should be based on an optimization of cost-benefit trade-offs associated with different taxonomic scales. Mixed-level aggregations, as well as morpho-species and ecological-trait classifications should be considered in this optimization process. Looking to the future, closer ties between taxonomists and bioassessment researchers would benefit both of their disciplines. Such coordination would provide the autoecological information and better diagnostic tools (such as keys and molecular methods) needed for biomonitoring, and better (and more widespread) biomonitoring would fuel taxonomy’s resurgence.

Publisher

Canadian Science Publishing

Subject

General Environmental Science

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