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Biological Endpoints and Discriminatory Capacity

Biological Endpoints

Inherent in this element is the existence of a viable data management system commensurate with the level of rigor (see Technical Element 9, Data Management).  State and Tribal bioassessment programs should develop indexes that have the capacity to discriminate classes of condition.  Index development can include single or multiple metrics, discriminant models, or other predictive models of the aquatic assemblage.  The index is developed and verified by independent data sets.  Calibrating the biological endpoint is perhaps the most critical aspect in reporting and documenting condition.  Programs typically establish more than one endpoint to distinguish among higher (e.g., outstanding natural resource waters, excellent warmwater habitat, or excellent/good habitat) and lower assessment categories (e.g., limited resource waters, fair/poor/very poor). 

Numerous methods are available for analyzing biological indicator data to assess ecological condition, including both univariate and multivariate analysis techniques.  The most common method of data analysis in the U.S. is use of a multimetric index, which combines several biological variables into a single, unitless index.  These variables, or metrics, are characteristics of the biota that change in some predictable way with increased human influence.  Use of multiple metrics to assess biological conditions maximizes the information available regarding the functions and processes of aquatic assemblages.  For a metric to be of value, it must be ecologically relevant to the biological assemblage or index under study and to the specified program objectives, and it must be sensitive to stressors.  RIVPACSExit EPA Disclaimer (River Prediction and Classification System) and its derivatives are empirical (statistical) models that predict the aquatic macroinvertebrates expected to occur at a site in the absence of environmental stress (Simpson et al. 1996).  A comparison of the invertebrates predicted to occur at the test sites with those actually collected (i.e., Observed/Expected) provides a measure of biological impairment.  The predicted taxa list also provides a “target” community to measure the success of any remediation measures taken to rectify identified impacts. 

Bonada et al. (2006) performed a comparative analysis on the more recent biomonitoring approaches, including multimetric and multivariate indices.  They identified 12 criteria for defining an ideal biomonitoring tool, which were elements of rationale for use, implementation into a program from a technical perspective, and performance in detecting biological impairment.  Bonada et al. (2006) found that both the multimetric indices and RIVPACS were highly regarded as effective tools, meeting 10 and 9 criteria, respectively.

Regardless of approach, the primary purpose of biological endpoints with appropriate discriminatory capacity is to establish levels of biological quality that can be used in determining attainment or non-attainment of the designated use.  USEPA recommends that each State or Tribe establish its biological endpoint(s) based on either index values from a statistical distribution of candidate reference sites or a discriminant model from a range of aquatic life conditions that includes reference conditions.  Estimates of variance, such as standard deviation, and power analysis can assist in determining how many assessment levels an index may represent.  States and Tribes must carefully document their rationale for selecting condition classes, including those that define gradations in quality or attainment status such as "good/fair/poor" or "full/partial attainment/non-attainment."  The endpoints should promote straightforward decisions when biological data are used to facilitate water quality management decisions.  Program decisions for applying the endpoints also need to be fully documented.

Some Frequently Asked Questions

Question:  Why is it important to link biological endpoints with the biological condition gradient (BCG)?
Answer:  If calibrated properly (i.e., a comprehensive database representing a high level of rigor), biological endpoints have the discriminatory capacity to differentiate multiple condition classes along the BCG (Figure 10-10).  The result provides the environmental manager a better foundation for making informed decisions regarding the water resource.

A conceptual illustration of the capability of increasingly comprehensive bioassessments to detect and discriminate along the biological condition gradient. Shaded areas represent relative degree of uncertainty.

Figure (above) A conceptual illustration of the capability of increasingly comprehensive bioassessments to detect and discriminate along the biological condition gradient.  Shaded areas represent relative degree of uncertainty.

Question: How are endpoints calibrated for aquatic life uses set upon reference conditions?
Answer: Thresholds for biological endpoints are established to differentiate attainable biocriteria for each aquatic life use. As an example, thresholds were set in Ohio for two designated uses, Warmwater Habitat (WWH) and Modified Warmwater Habitat (MWH). The 25th percentile of the biological index for the population of least disturbed regional reference sites was used to set numeric biocriteria for the WWH use designation (see Figure below); an exception was the HELP ecoregion where there were no least disturbed reference sites available. The 25th percentile of modified reference sites that represent best attainable conditions for channelized streams was used to set numeric biocriteria for the MWH use designation.


Figure showing The 25th percentile of least disturbed regional reference sites was used to set numeric biocriteria for the WWH use designation

IBI biocriteria thresholds for Ohio warmwater habitat (WWH) and modified warmwater habitat (MWH) aquatic life uses.

References

Bonada, N., N. Prat, V.H. Resh, and B. Statzner.  2006.  Developments in aquatic insect biomonitoring: A comparative analysis of recent approaches.  Annu. Rev. Entomol. 51:495-523.

Simpson, J., R. Norris, L. Barmuta, and P. Blackman.  1996.  Australian River assessment system:  National river health program predictive model manual.  http.//ausrivas.canberra.au.

Learn more about biological endpoints and thesholds:

 

Biological Indicators | Aquatic Biodiversity | Statistical Primer

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