Mechanisms of drift-feeding behavior in juvenile Chinook salmon and the role of inedible debris in a clear-water Alaskan stream
Drift-feeding fish are challenged to discriminate between prey and similar-sized particles of debris, which are ubiquitous even in clear-water streams. Spending time and energy pursuing debris mistaken as prey could affect fish growth and the fitness potential of different foraging strategies. Our goal was to determine the extent to which debris influences drift-feeding fish in clear water under low-flow conditions when the distracting effect of debris should be at a minimum. We used high-definition video to measure the reactions of drift-feeding juvenile Chinook salmon (Oncorhynchus tshawytscha) to natural debris and prey in situ in the Chena River, Alaska. Among all potential food items fish pursued, 52 % were captured and quickly expelled from the mouth, 39 % were visually inspected but not captured, and only 9 % were ingested. Foraging attempt rate was only moderately correlated with ingestion rate (Kendall’s τ = 0.55), raising concerns about the common use of foraging attempts as a presumed index of foraging success. The total time fish spent handling debris increased linearly with foraging attempt rate and ranged between 4 and 25 % of total foraging time among observed groups. Our results help motivate a revised theoretical view of drift feeding that emphasizes prey detection and discrimination, incorporating ideas from signal detection theory and the study of visual attention in cognitive ecology. We discuss how these ideas could lead to better explanations and predictions of the spatial behavior, prey selection, and energy intake of drift-feeding fish.
KeywordsDrift feeding Debris Foraging theory Chinook salmon Stream Prey detection Signal detection
This work was supported by the Arctic-Yukon-Kuskokwim Sustainable Salmon Initiative, the Institute of Arctic Biology, Alaska EPSCoR NSF award #OIA-1208927 and the state of Alaska, and the Department of Biology and College of Natural Sciences and Mathematics at the University of Alaska Fairbanks. David Neuswanger, Milo Adkison, and three anonymous reviewers helpfully critiqued this manuscript. This work was conducted under IACUC protocols #134754-1 and #175627-1. Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply endorsement by the U.S. Government.
- Bryan JE, Larkin PA (1972) Food specialization by individual trout. J Fish Res Board Can 29:1615–1624Google Scholar
- Grubb TCJ (2003) The mind of the trout: a cognitive ecology for biologists and anglers. University of Wisconsin Press, MadisonGoogle Scholar
- Guensch GR, Hardy TB, Addley RC (2001) Examining feeding strategies and position choice of drift-feeding salmonids using an individual-based, mechanistic foraging model. Can J Fish Aquat Sci 58:446–457Google Scholar
- Gutierrez L (2011) Terrestrial invertebrate prey for juvenile Chinook salmon: abundance and environmental controls in an interior Alaskan river. M.S. Thesis, University of Alaska FairbanksGoogle Scholar
- Hollander M, Wolfe DA (1999) Nonparametric statistical methods. John Wiley & Sons, Inc, USAGoogle Scholar
- Kutner MH, Nachtsheim CJ, Neter J, Li W (2005) Applied Linear Statistical Models, 5th edn. McGraw-Hill/Irwin, New YorkGoogle Scholar
- Staddon JER, Gendron RP (1983) Optimal detection of cryptic prey may lead to predator switching. Am Nat 843-848Google Scholar
- Wickens TD 2001. Elementary signal detection theory. Oxford University Press.Google Scholar