| A mechanistic approach of predicting habitat and growth for drift-feeding stream salmonids was developed. The approach was based on the cause-and-effect relationships of environmental variables, resource conditions, physiological attributes of the fish, and daily net energy intake (DNEI) (joules/day) coupled with multidimensional hydrodynamics modeling. The environmental variables and resource conditions used in the analysis were discharge, depth, velocity, diel fluctuating temperature, turbidity, day length, drift density, and drift size. The physiological variables included were daily maximum consumption, daily energy losses, fish size, swimming cost, optimum swimming speed, and maximum sustained swimming speed. DNEI was calculated by means of a daily energy balance using a drift-foraging model that included each of the variables.; The DNEI model predictions of high-energy habitat matched the observed habitat utilization for a wide size range of rainbow/redband trout ( Oncorhynchus mykiss spp.) in the Klamath River, California/Oregon, USA, and cutthroat trout (O. clarki) in St. Charles Creek, Idaho, USA. In addition, the DNEI foraging model accurately predicted the observed growth of fish in a hydro peaking section of the Klamath River.; The DNEI modeling showed that temperature, drift density, turbidity, and to a lesser extent, the velocity field adjacent to fish can have a large effect on the estimated habitat suitability. The effect of temperature, drift density, and turbidity (by inference) on total habitat was nearly as large as the effect of a wide range of river discharge (10 to 212 cms) on total habitat. In a specific application of the DNEI growth model to hydro peaking versus non-peaking scenarios in a reach of the Klamath River, the potential increase in drift density due to non-peaking had a large effect on modeled growth (229% increase). Two-dimensional hydrodynamics modeling results showed that given accurate topography, boundary conditions, and calibration, the models accurately represented the depth and velocity fields in natural river channels.; We show how the environmental variables, resource conditions, and fish sizes (ecological data layers) can be combined to predict drift-feeding DNEI habitat, growth, and, in general, aquatic habitat using multidimensional ecological templates (MET). We discuss some implications of the modeling approach and suggest that it has important application to habitat restoration planning, environmental impact assessments, and instream flow assessments. |
