Bioassessment of Freshwater Ecosystems

Freshwater ecosystems have a primary role in the biosphere as conduits of water and nutrients from the continents to the sea. They also support unique and complex ecological communities and often define the structure and functioning of the surrounding terrestrial ecosystem. Because of this, and the critical role of fresh water as a human resource, ecologists are often asked to assess or monitor the “health”, “status” or “condition” of freshwater ecosystems.

We use three case studies to demonstrate the use of the Reference Condition Approach (RCA). The studies represent three markedly different environments: the lentic, near shore environment of the North American Great Lakes; tributaries of the Fraser River, a large, west-coast basin in Canada; and the upper Murrumbidgee River basin in the Australian Capital Territory.

The Reference Condition Approach (RCA) to environmental assessment depends on the identification and sampling of reference sites. The result is a database of biological and environmental attributes that represent the Reference Condition. The database is used to describe variation in the Reference Condition and build predictive models that explain as much as possible of the variation in biological characteristics among reference sites by variation in environmental variables among the sites. The description of variation in Reference Condition, the development of predictive models and the ultimate assessment of test sites are discussed in Chapters 4 and 5. In this chapter, we describe and discuss the steps involved in designing a study that will define the Reference Condition.

In the past, variability in the assessment of freshwater ecosystems has commonly been seen as a problem to be addressed in study design (Chapter 3) by restricting sampling spatially and temporally (e.g., upstream and downstream of an effluent in Autumn), and to particular habitats (e.g., profundal zones in lakes). In contrast, when using the Reference Condition Approach, we want to be sure that we adequately sample the natural variability among the freshwater ecosystems present in the region of interest (e.g., Simpson and Norris 2000). Then, an ecologically relevant comparison can be made between a particular test site (or set of sites exposed to some common stressor) and the appropriate Reference Condition. Variation in the Reference Condition, rather than being a problem, is a characteristic to be “captured” for the region being studied. We must measured and characterize it before we can assess a test site.

In science, a standard approach to hypothesis testing is to establish null and alternative hypotheses, collect data, and then determine the probability that those data would be collected if the null hypothesis were true (Quinn and Keough 2002). If the probability is small enough, we reject the null hypothesis and conclude that the alternative hypothesis is supported.

In the previous chapters we have described the Reference Condition Approach for assessing freshwater ecosystems. The method has several novel aspects that are advances in aquatic ecosystem assessment, It moves beyond more traditional assessment methods by describing variation in relatively widespread reference sites, by developing predictive models that relate biota to the characteristics of their environment, and by setting appropriate decision-making criteria that explicitly take uncertainty into account. However, just as for traditional methods, the end result is a determination that a site is or is not in Reference Condition. For management decisions this is still only a first step.

This book is a formal statement of the general principles and application of the Reference Condition Approach. So in this final chapter we draw together the major points of the book, describing the use of the Reference Condition Approach with benthic macroinvertebrate communities in the bioassessment of freshwater lakes and streams. We distil what we mean by the Reference Condition Approach, aspects of study design to identify the Reference Condition, how to explain and mathematically model variation, how to make decisions and use the outputs and, finally, where we see future developments taking place.