Richard B. Lowell

A review of potential methods of determining critical effect size for designing environmental monitoring programs

The effective design of field studies requires that sample size requirements be estimated for important endpoints before conducting assessments. This a priori calculation of sample size requires initial estimates for the variability of the endpoints of interest, decisions regarding significance levels and the power desired, and identification of an effect size to be detected. Although many programs have called for use of critical effect sizes (CES) in the design of monitoring programs, few attempts have been made to define them. This paper reviews approaches that have been or could be used to set specific CES. The ideal method for setting CES would be to define the level of protection that prevents ecologically relevant impacts and to set a warning level of change that would be more sensitive than that CES level to provide a margin of safety; however, few examples of this approach being applied exist. Program-specific CES could be developed through the use of numbers based on regulatory or detection limits, a number defined through stakeholder negotiation, estimates of the ranges of reference data, or calculation from the distribution of data using frequency plots or multivariate techniques. The CES that have been defined often are consistent with a CES of approximately 25%, or two standard deviations, for many biological or ecological monitoring endpoints, and this value appears to be reasonable for use in a wide variety of monitoring programs and with a wide variety of endpoints.

Utility of field-based artificial streams for assessing effluent effects on riverine ecosystems

Experimentation using field-based artificial streams provides a promising, complimentary approach to biomonitoring assessments because artificial streams provide control over relevant environmental variables and true replication of treatments. We have used large and small artificial stream systems, based in the field, to examine the effect of treated bleached kraft pulp mill effluent (BKME) on the benthos of three large rivers in western Canada. Under natural regimes of temperature, water chemistry, and insolation, these artificial streams provide current velocities and substrata to food chains or food webs that are representative of those in the study river. With these tools we have shown that BKME stimulated mayfly growth in the Thompson River above that which could be accounted for by fertilization of their algal food supply. In contrast, moulting frequency was inhibited at high BKME concentrations. Results from artificial streams also indicate that increased algal biomass and abundances of benthic communities downstream of BKME outfalls were induced by nutrient enrichment from the effluent. BKME treatments did not change diatom species richness in the Fraser River, or diatom species diversity in either the Athabasca or Fraser Rivers. Artificial streams provide a means of understanding the mechanisms of stressor effects over a continuum ranging from single stressor effects on specific taxa to the effects of multiple stressors on communities and ecosystems. Because riverside deployment provides environmental realism within a replicated experimental design, this approach can (i) address questions that cannot be examined using laboratory tests or field observations, (ii) improve our mechanistic understanding of stressor effects on riverine ecosystems, and (iii) can contribute directly to the development, parameterization, and testing of models for predicting ecosystem-level responses.

Effects of pulp and paper mill effluent on fish: a temporal assessment of fish health across sampling cycles.

The Canadian environmental effects monitoring (EEM) program is a regulated, cyclical, industry-funded program designed to determine whether receiving water impacts exist when a mill is in compliance with its discharge limits. The results from three cycles of the fish monitoring program (1992 to 2004) are available from over 200 surveys of fish compared between sites located upstream and downstream of pulp and paper mill effluent outfalls. Previous meta-analyses have shown a national average response pattern across cycles characterized by an increase in endpoints measuring energy storage and growth and a decrease in a reproductive endpoint, consistent with a response of nutrient enrichment in combination with some form of metabolic disruption. Although the national average pattern of effects was temporally consistent, there was some variability in the magnitude of effects among cycles. Questions were raised as to whether the intercycle variability was due to changes in effluent quality or due, at least in part, to other factors. The present study compares responses over the first three cycles, and shows that the choice of sentinel species is likely to be a major contributing factor to the variability in observed effects. Subset analyses using studies from mills that used the same sentinel species across cycles reveal fairly uniform responses and little evidence of significant improvements in overall fish health from cycles one to three. However, a meta-analysis using 1991 data collected from 10 mills before the implementation of the EEM program and data from the same mills collected during cycles one to three of the program reveal significantly reduced effects on relative liver weight and potential improvements in other endpoints.

Dealing with heterogeneous regression slopes in analysis of covariance: new methodology applied to environmental effects monitoring fish survey data

Analysis of covariance (ANCOVA) is a powerful statistical method which incorporates one or more covariates into the analysis to reduce error associated with measurement. ANCOVA (modeling response as a function of fish size) is frequently used to analyze environmental effects monitoring (EEM) fish survey data. In approximately 12% of fish survey data sets taken from cycles 1 to 3 of Environment Canada’s EEM database for pulp and paper mills, the standard assumption of parallel regression slopes is not met. For the first three cycles of the EEM program, these data sets were classified as indicating a mill effect, but for the most part were excluded from subsequent analyses aimed at quantifying the effect. We present two different methods for initially dealing with data sets that exhibit heterogeneous slopes so that they can be analyzed using the parallel slope model. The first method identifies data sets where heterogeneous slopes are forced by a few high-influence observations. The second approach identifies data sets where a model with heterogeneous slopes is statistically, but not practically, significant: with a high coefficient of determination for the parallel slope model. These new methodologies are applied to EEM pulp and paper data sets and about 55% of cases with heterogeneous slopes can be described by a parallel slope model. We also discuss a third method that can be used to describe mill effects when regression slopes remain heterogeneous even after applying the above two methods, enabling comparison with a critical effect size. These new methodologies could benefit the EEM program by enabling more data sets to be incorporated into meta-analyses and be used to make more equitable mill monitoring decisions in the future.

Response to Huebert et al. (2011) comments on Canada's EEM program on Canada's EEM program

In Canada, metal mines and pulp and paper mills, subjected respectively to the Metal Mining Effluent Regulations (MMER) and the Pulp and Paper Effluent Regulations (PPER) pursuant to the Fisheries Act, are required to conduct environmental effects monitoring (EEM) as a condition to deposit effluent into water. Both regulations indicate that EEM studies shall be carried out, their results interpreted and reported in accordance with generally accepted standards of good scientific practice, (sections 7[3] and 28[3] of MMER and PPER, respectively). In a previous Learned Discourse, Huebert et al. (2011) indicated that the EEM program is an invaluable tool for evaluating MMER effluent guidelines, and also suggested 3 changes in methodology referred to in the EEM technical guidance documents. Specifically, they identified issues dealing with: 1) replication of reference and exposure areas, 2) designation of alpha (a), and 3) calculation of the Bray-Curtis Index (BCI). We respond to each of these issues in the following discussion.