Traits-based approaches in bioassessment and ecological risk assessment : strengths, weaknesses, opportunities and threats

We discuss the application of traits-based bioassessment approaches in retrospective bioassessment as well as in prospective ecological risk assessments in regulatory frameworks. Both approaches address the interaction between species and stressors and their consequences at different levels of biological organization, but the fact that a specific species may be less abundant in a potentially impacted site compared with a reference site is, regrettably, insufficient to provide diagnostic information. Species traits may, however, overcome the problems associated with taxonomy-based bioassessment. Trait-based approaches could provide signals regarding what environmental factors may be responsible for the impairment and, thereby, provide causal insight into the interaction between species and stressors. For development of traits-based (TBA), traits should correspond to specific types of stressors or suites of stressors. In this paper, a strengths, weaknesses, opportunities, and threats (SWOT) analysis of TBA in both applications was used to identify challenges and potentials. This paper is part of a series describing the output of the TERA (Traits-based ecological risk assessment: Realising the potential of ecoinformatics approaches in ecotoxicology) Workshop held between 7 and 11 September, 2009, in Burlington, Ontario, Canada. The recognized strengths were that traits are transferrable across geographies, add mechanistic and diagnostic knowledge, require no new sampling methodology, have an old tradition, and can supplement taxonomic analysis. Weaknesses include autocorrelation, redundancy, and inability to protect biodiversity directly. Automated image analysis, combined with genetic and biotechnology tools and improved data analysis to solve autocorrelation problems were identified as opportunities, whereas low availability of trait data, their transferability, their quantitative interpretation, the risk of developing nonrelevant traits, low quality of historic databases, and their standardization were listed as threats