Incorporating traits in aquatic biomonitoring to enhance causal diagnosis and prediction

Joseph M. Culp*, David G. Armanini, Michael J. Dunbar, Jessica M. Orlofske, N. LeRoy Poff, Amina I. Pollard, Adam G. Yates, Grant C. Hose

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

87 Citations (Scopus)

Abstract

The linkage of trait responses to stressor gradients has potential to expand biomonitoring approaches beyond traditional taxonomically based assessments that identify ecological effect to provide a causal diagnosis. Traits-based information may have several advantages over taxonomically based methods. These include providing mechanistic linkages of biotic responses to environmental conditions, consistent descriptors or metrics across broad spatial scales, more seasonal stability compared with taxonomic measures, and seamless integration of traits-based analysis into assessment programs. A traits-based biomonitoring approach does not require a new biomonitoring framework, because contemporary biomonitoring programs gather the basic siteby-species compositionmatrices requiredtolink communitydata to the traitsdatabase. Impediments tothe adoption of traits-based biomonitoring relate to the availability, consistency, and applicability of existing trait data. For example, traits generalizationsamong taxa across biogeographical regions are rare, andnoconsensus exists relative tothe requiredtaxonomic resolutionandmethodology for traits assessment. Similarly, we must determine if traits form suites that are related to particular stressor effects, and whether significant variation of traits occurs among allopatric populations. Finally, to realize the potential of traits-based approaches in biomonitoring, a concerted effort to standardize terminology is required, along with the establishment of protocols to ease the sharing and merging of broad, geographical trait information.

Original languageEnglish
Pages (from-to)187-197
Number of pages11
JournalIntegrated Environmental Assessment and Management
Volume7
Issue number2
DOIs
Publication statusPublished - Apr 2011

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