Effects of spatial scale and foraging efficiency on the predictions made by spatially-explicit models of fish growth rate potential

Spatially-explicit modeling of fish growth rate potential is a relatively new approach that uses physical and biological properties of aquatic habitats to map spatial patterns of fish growth rate potential. Recent applications of spatially-explicit models have used an arbitrary spatial scale and have assumed a fixed foraging efficiency. We evaluated the effects of spatial scale, predator foraging efficiency (combined probabilities of prey recognition, attack, capture, and ingestion), and predator spatial distribution on estimates of mean growth rate potential of chinook salmon, Oncorhynchus tshawytscha. We used actual data on prey densities and water temperatures taken from Lake Ontario during the summer, as well as, simulated data assuming binomial distribution of prey. Results show that a predator can compensate for low foraging efficiency by inhabiting the most profitable environments (regions of high growth rate potential). Differences exist in predictions of growth rate potential across spatial scales of observation and a single scale may not be adequate for interpreting model results across seasons. Continued refinements of this modeling approach must focus on the assumptions of stationary distributions of predator and prey populations and predator foraging tactics.