Linking Fine-Scale Foraging Models and Network-Scale Predictions of Basal Energy Pools to Estimate Juvenile Steelhead Carrying Capacity in the John Day Basin, Oregon

Foraging models provide a mechanistic framework for integrating reach-scale physical habitat measurements with estimates of invertebrate drift to predict salmonid carrying capacity. In support of ongoing salmonid recovery planning efforts, the Columbia Habitat Monitoring Program (CHaMP) has parameterized foraging models for hundreds of reaches across the Columbia Basin with the ultimate goal of scaling these predictions upwards to estimate carrying capacity at the network and/or population scale(s). Although considerable progress has been made, there remain practical hurdles before this broader goal can be achieved, most notably in the area of extrapolating predictions from intensively surveyed reaches to those where necessary drift and physical data are lacking. Network-scale applications of foraging models must therefore consider cost-effective and reliable alternatives in order to realize their full potential. Here, we explore the potential to fill this void using food web theory in conjunction with output from models that make continuous predictions of (i) aquatic primary production and (ii) the relative contribution of allochthonous subsidies to food webs, based on a combination of landscape variables. Although a complex suite of biological and physical processes governs how basal energy ultimately becomes accessible to drift-feeding fishes, this approach shows considerable promise in an applied capacity-estimation context.