which are aggregated within a multimetric index (MMI). MMIs provide a checksand-balances system to account for variable responses of metrics to multiple
stressors. Others prefer single-metric indices, most notably the observed-toexpected (O/E) index, which we introduce in Sect. 3.1. Developers of MMIs
commonly group metrics based on the general type of ecological information
they express. Metrics from different ecological categories are included in MMIs
in order to reduce the redundancy of information and increase the explanatory
power of indices. In practice, a vast array of assemblage-level metrics has been used
for aquatic bioassessments.
To provide relevant examples, we have assembled a short list of fish,
macroinvertebrate, and algae metrics, which we group into four broad categories
(Table 1). Diversity and composition metrics are taxonomy-based metrics associated with assemblage characteristics such as richness, evenness, diversity, and
dominance. Trait-based metrics incorporate information on ecological habits, habitats, morphology, life history, and life cycle characteristics of populations in the
assemblage of interest. Pollution tolerance metrics are numerical ratings of the
degree to which individuals in the assemblage are tolerant to stressors. Individual
condition metrics are associated with visually apparent morphological anomalies of
individual specimens. In addition to these general metric types, the absolute
abundance of fish and biomass of algae are also sometimes used, although the
absolute abundance of macroinvertebrates is rarely used.
In Sect. 2, we introduce the most widely used method for bioassessment, the
Reference Condition Approach (RCA) [30–32]. In Sect. 3, we discuss predictive
modeling of aquatic assemblages, which is conducted to control for the effects of
natural environmental variation in order to obtain an unambiguous determination of
anthropogenic effects. Once selected and properly calibrated for natural environmental variation, metrics are used individually, or are aggregated within an MMI, to
provide a scoring system that reflects the assemblage-inferred level of anthropogenic impairment at a given study site. This process, as well as methods for
evaluating the performance of metrics and indices, is reviewed in Sect. 4. In
Sect. 5, we take a broader perspective and present interviews with three experts
who provide valuable insights into some of the most important emerging issues and
challenges in the field of bioassessment.
2 The Reference Condition Approach
Reference conditions serve as surrogates for negative controls, representing the
assemblage characteristics at test sites that would occur in the absence of impairment. Following the RCA, reference conditions are derived from assemblage data
at least-disturbed reference sites (sensu Stoddard et al. [32]). In comparison to
experimental studies, where variation among replicates is carefully controlled and
expected to be minimal, variation among reference site assemblages is high and
difficult to predict. Replicate samples from the same site are generally insufficient
Principles for the Development of Contemporary Bioassessment Indices for. . .
237
stressors. Others prefer single-metric indices, most notably the observed-toexpected (O/E) index, which we introduce in Sect. 3.1. Developers of MMIs
commonly group metrics based on the general type of ecological information
they express. Metrics from different ecological categories are included in MMIs
in order to reduce the redundancy of information and increase the explanatory
power of indices. In practice, a vast array of assemblage-level metrics has been used
for aquatic bioassessments.
To provide relevant examples, we have assembled a short list of fish,
macroinvertebrate, and algae metrics, which we group into four broad categories
(Table 1). Diversity and composition metrics are taxonomy-based metrics associated with assemblage characteristics such as richness, evenness, diversity, and
dominance. Trait-based metrics incorporate information on ecological habits, habitats, morphology, life history, and life cycle characteristics of populations in the
assemblage of interest. Pollution tolerance metrics are numerical ratings of the
degree to which individuals in the assemblage are tolerant to stressors. Individual
condition metrics are associated with visually apparent morphological anomalies of
individual specimens. In addition to these general metric types, the absolute
abundance of fish and biomass of algae are also sometimes used, although the
absolute abundance of macroinvertebrates is rarely used.
In Sect. 2, we introduce the most widely used method for bioassessment, the
Reference Condition Approach (RCA) [30–32]. In Sect. 3, we discuss predictive
modeling of aquatic assemblages, which is conducted to control for the effects of
natural environmental variation in order to obtain an unambiguous determination of
anthropogenic effects. Once selected and properly calibrated for natural environmental variation, metrics are used individually, or are aggregated within an MMI, to
provide a scoring system that reflects the assemblage-inferred level of anthropogenic impairment at a given study site. This process, as well as methods for
evaluating the performance of metrics and indices, is reviewed in Sect. 4. In
Sect. 5, we take a broader perspective and present interviews with three experts
who provide valuable insights into some of the most important emerging issues and
challenges in the field of bioassessment.
2 The Reference Condition Approach
Reference conditions serve as surrogates for negative controls, representing the
assemblage characteristics at test sites that would occur in the absence of impairment. Following the RCA, reference conditions are derived from assemblage data
at least-disturbed reference sites (sensu Stoddard et al. [32]). In comparison to
experimental studies, where variation among replicates is carefully controlled and
expected to be minimal, variation among reference site assemblages is high and
difficult to predict. Replicate samples from the same site are generally insufficient
Principles for the Development of Contemporary Bioassessment Indices for. . .
237