Using biomass pyramids and body mass scaling relationships to predict freshwater fish densities at large spatial scales

Freshwater fisheries, which generate more than 30 billion dollars per year in the United States, are critically important resources.  Regional-scale assessments of freshwater fisheries are difficult to perform, however, as most studies have been conducted on discrete populations.  Here, I present a simple model that can be used to predict fish densities at very large spatial scales.  The model first assumes that energetic resources are transferred among trophic levels at a predictable rate (10% transfer efficiency).  It then uses the scaling relationship between body mass and abundance (-3/4 power) to predict the densities of fishes within higher trophic levels, at any spatial scale of interest.  Model predictions were evaluated by comparison with empirical data from four warm-water and four cold-water systems.  Predicted densities were within +/- 50% of the empirical densities in six of eight systems, and were within an order of magnitude in all systems.  Also, when sensitivity analyses were used to examine alternative parameter values, I found no evidence of a systematic bias in the model predictions.  I therefore conclude that the model is a useful means of predicting fish densities at large scales, in a quick and efficient manner.