Empirical Models Predicting Population Abundance and Productivity in Lotic Systems

Stream ecologists have yet to produce general predictive models of abundance and productivity of lotic organisms. The large number of factors affecting species abundance, differences in fauna and flora among ecoregions, and the cost of calibrating models combine to put in question our hope of producing general mechanistic models that yield quantitative predictions. Similar seemingly insurmountable difficulties have been recognised in other systems and, at least in limnology, an alternative to mechanistic models has clearly emerged: the use of a set of relatively simple regression models describing empirical relationships that are combined to yield predictions of interest. Although smaller, a similar set of empirical models exists for running water systems, and published data permit the estimation of many more. Here I review a subset of published and unpublished models to illustrate how they can be used to: 1) serve as reference values for the interpretation of measurements made in particular conditions, 2) yield estimates of abundance and productivity of populations and assemblages that can be used directly for management decisions or to test ecological theories, and 3) serve as heuristic tools to generate hypotheses about factors that affect community structure. Two major weaknesses are made clear by this treatment. The 1st is the large uncertainty associated with most predictions. This uncertainty will be reduced only by models that include better predictors, or sacrifice generality for precision. The 2nd weakness is the existing gap in the body of empirical models that prevents some useful, and perhaps more interesting, predictions. This gap will only be filled by a concerted effort of stream ecologists to produce more empirical relationships, to report them in a useful format, and to create data and model repositories. In alleviating these 2 weaknesses lies one of the most challenging tasks of our discipline.