Evaluating the Barrier Assessment Technique Derived from FishXing Software and the Upstream Movement of Brook Trout through Road Culverts

Abstract

Anthropogenic barriers to fish passage, such as culverts and dams, are major factors impeding the persistence and recovery of aquatic species. Considerable work has focused on mitigating these impacts; however, activities associated with measuring and restoring connectivity of aquatic ecosystems often face challenges in determining the passability of barriers by aquatic species. Hydrological modeling software that incorporates biological aspects of a focal species is often used as a relatively inexpensive method for assessing barrier passability for restoration decisions. However, the biological relevance of these approaches remains to be rigorously tested. We assessed passage rates of PIT-tagged Brook Trout Salvelinus fontinalis through four road culverts and adjacent reference sites (unaltered areas of the streams) on the island of Newfoundland to determine whether upstream passage through road culverts was more restrictive than unaltered reference areas of the stream. Next, we examined the usefulness of barrier passability predictions derived from FishXing software by comparing them with in situ movement data for this species. Brook Trout passage for three of the four reference sites had a significantly higher range of passable stream flows compared with that for culverts, indicating the presence of velocity barriers in culverts. However, FishXing predictions of suitable fish passage discharges were conservative, and tagged fish successfully navigated partial barriers that were at least 2–3 times the upper limits of stream flow predicted to allow successful passage. The results of our study show a clear need for an improved understanding of fish movement through these structures so that barrier assessment techniques can be refined. The implications of not doing so may lead to restoration actions that result in limited biological benefit.

Received February 6, 2013; accepted July 2, 2013

ACKNOWLEDGMENTS

The authors are grateful to M. Langdon, T. Mulrooney, and R. Collier (Parks Canada) and C. Pennell and C. Kelly (Fisheries and Oceans Canada) for tagging fish and maintaining telemetry stations. Furthermore, the authors acknowledge the input and guidance from I. Gidge, R. Randall, M. Underwood, and the Landscape Ecology and Spatial Analysis Lab at Memorial University for valuable feedback throughout the study. Support for this research was provided by Parks Canada Action on the Ground Funding, Canadian Foundation for Innovation, and Natural Sciences and Engineering Research Council Discovery grants to Y.F.W. and by AMEC Environment and Infrastructure grant to D.C.