Effects of Streamflow Diversion on a Fish Population: Combining Empirical Data and Individual-Based Models in a Site-Specific Evaluation

Abstract

Resource managers commonly face the need to evaluate the ecological consequences of specific water diversions of small streams. We addressed this need by conducting 4 years of biophysical monitoring of stream reaches above and below a diversion and applying two individual-based models of salmonid fish that simulated different levels of behavioral complexity. The diversion of interest captured about 24% of streamflow between June and October but had little or no effect over the remainder of the year. The change in biomass of Rainbow Trout Oncorhynchus mykiss and steelhead (anadromous Rainbow Trout) over the dry season (June–October) favored the upstream control over the downstream diversion reach over 4 years (2008–2011). Dry-season growth did not differ consistently between the two reaches but did exhibit substantial annual variation. Longer-term observations revealed that in both reaches most fish growth occurred outside the period of dry-season diversion. After calibration to the upstream control reach, both individual-based models predicted the observed difference in fish biomass between control and diversion reaches at the ends of the dry seasons. Both models suggested the difference was attributable in part to differences in habitat structure unrelated to streamflow that favored the upstream reach. The two models both also reproduced the large seasonal differences in growth, small differences between reaches in individual growth, and natural distributions of growth among individuals. Both the empirical data and simulation modeling suggested that the current level of diversion does not threaten the persistence of the salmonid population. In multiyear simulations using the two models, the model incorporating greater flexibility in fish behavior exhibited weaker population-level responses to more extreme reductions in dry-season streamflow. We believe the application of individual-based models in this case has placed resource managers in a relatively strong position to forecast the consequences of future environmental alterations at the study site.

Received March 22, 2013; accepted October 17, 2013

ACKNOWLEDGMENTS

Loren Everest identified the field site. Justin Garwood, Monty Larson, Megan Arnold, Michael Hellmair, Tyler McCraney, and Mary Meyerpeter provided field assistance. Reference to trade names does not imply endorsement by the U.S. Government.