Advertisement

Environmental Biology of Fishes

, Volume 97, Issue 5, pp 489–503 | Cite as

Mechanisms of drift-feeding behavior in juvenile Chinook salmon and the role of inedible debris in a clear-water Alaskan stream

  • Jason Neuswanger
  • Mark S. Wipfli
  • Amanda E. Rosenberger
  • Nicholas F. Hughes
Article

Abstract

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.

Keywords

Drift feeding Debris Foraging theory Chinook salmon Stream Prey detection Signal detection 

Notes

Acknowledgments

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.

Supplementary material

10641_2014_227_MOESM1_ESM.mp4 (111.9 mb)
ESM 1 (MP4 114557 kb)
10641_2014_227_MOESM2_ESM.mp4 (248.2 mb)
ESM 2 (MP4 254141 kb)
10641_2014_227_MOESM3_ESM.mp4 (7.6 mb)
ESM 3 (MP4 7784 kb)

References

  1. Abbott KR, Sherratt TN (2013) Optimal sampling and signal detection: unifying models of attention and speed-accuracy trade-offs. Behav Ecol 24:605–616. doi: 10.1093/beheco/art001 CrossRefGoogle Scholar
  2. Allen KR (1941) Studies on the biology of the early stages of the salmon (Salmo salar). J Anim Ecol 9:47–76CrossRefGoogle Scholar
  3. Bachman RA (1984) Foraging behavior of free-ranging wild and hatchery brown trout in a stream. Trans Am Fish Soc 113:1–32CrossRefGoogle Scholar
  4. Benson ER, Wipfli MS, Clapcott JE, Hughes NF (2013) Relationships between ecosystem metabolism, benthic macroinvertebrate densities, and environmental variables in a sub-arctic Alaskan river. Hydrobiologia 701:189–207. doi: 10.1007/s10750-012-1272-0 CrossRefGoogle Scholar
  5. Biro PA, Ridgway MS, McLaughlin RL (1996) Does the rate of foraging attempts predict ingestion rate for young-of-the-year brook trout (Salvelinus fontinalis) in the field? Can J Fish Aquat Sci 53:1814–1820CrossRefGoogle Scholar
  6. Bisson PA (1978) Diel food selection by two sizes of rainbow trout (Salmo gairdneri) in an experimental stream. Journal of the Fisheries Board of Canada 35:971–975CrossRefGoogle Scholar
  7. Bryan JE, Larkin PA (1972) Food specialization by individual trout. J Fish Res Board Can 29:1615–1624Google Scholar
  8. Carrasco M (2011) Visual attention: the past 25 years. Vision Res 51:1484–1525. doi: 10.1016/j.visres.2011.04.012 PubMedCentralPubMedCrossRefGoogle Scholar
  9. Dukas R (2002) Behavioural and ecological consequences of limited attention. Philos Trans R Soc Lond B Biol Sci 357:1539–1547. doi: 10.1098/rstb.2002.1063 PubMedCentralPubMedCrossRefGoogle Scholar
  10. Dukas R, Kamil AC (2001) Limited attention: the constraint underlying search image. Behav Ecol 12:192–199CrossRefGoogle Scholar
  11. Dunbrack RL (1992) Sub-surface drift feeding by coho salmon (Oncorhynchus kisutch, Walbaum): a model and test. J Fish Biol 40:455–464CrossRefGoogle Scholar
  12. Elliott JM, Hurley MA (1999) A new energetics model for brown trout, Salmo trutta. Freshw Biol 42:235–246CrossRefGoogle Scholar
  13. Fausch KD (1984) Profitable stream positions for salmonids: relating specific growth rate to net energy gain. Can J Zool 62:441–451CrossRefGoogle Scholar
  14. Gowan C, Fausch KD (2002) Why do foraging stream salmonids move during summer? Environ Biol Fish 64:139–153CrossRefGoogle Scholar
  15. Grant JWA, Noakes DLG (1986) A test of a size-selective predation model with juvenile brook charr, Salvelinus fontinalis. J Fish Biol 29:15–23CrossRefGoogle Scholar
  16. Grossman GD, Rincón PA, Farr MD, Ratajczak REJ (2002) A new optimal foraging model predicts habitat use by drift-feeding stream minnows. Ecol Freshw Fish 11:2–10CrossRefGoogle Scholar
  17. Grubb TCJ (2003) The mind of the trout: a cognitive ecology for biologists and anglers. University of Wisconsin Press, MadisonGoogle Scholar
  18. 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
  19. 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
  20. Harvey BC, Railsback SF (2007) Estimating multi-factor cumulative watershed effects on fish populations with an individual-based model. Fisheries 32:292–296CrossRefGoogle Scholar
  21. Hayes JW, Stark JD, Shearer KA (2000) Development and test of a whole-lifetime foraging and bioenergetics growth model for drift-feeding brown trout. Trans Am Fish Soc 129:315–332CrossRefGoogle Scholar
  22. Hayes JW, Hughes NF, Kelly LH (2007) Process-based modelling of invertebrate drift transport, net energy intake and reach carrying capacity for drift-feeding salmonids. Ecol Model 207:171–188CrossRefGoogle Scholar
  23. Hazelton PD, Grossman GD (2009) The effects of turbidity and an invasive species on foraging success of rosyside dace (Clinostomus funduloides). Freshw Biol 54:1977–1989. doi: 10.1111/fwb.2009.54.issue-9 CrossRefGoogle Scholar
  24. Hill J, Grossman GD (1993) An energetic model of microhabitat use for rainbow trout and rosyside dace. Ecology 74:685–698CrossRefGoogle Scholar
  25. Hollander M, Wolfe DA (1999) Nonparametric statistical methods. John Wiley & Sons, Inc, USAGoogle Scholar
  26. Holling CS (1959) Some characteristics of simple types of predation and parasitism. Can Entomol 91:385–398CrossRefGoogle Scholar
  27. Hughes NF, Dill LM (1990) Position choice by drift-feeding salmonids - model and test for arctic grayling (Thymallus arcticus) in sub-arctic mountain streams, interior Alaska. Can J Fish Aquat Sci 47:2039–2048CrossRefGoogle Scholar
  28. Hughes NF, Kelly LH (1996) A hydrodynamic model for estimating the energetic cost of swimming maneuvers from a description of their geometry and dynamics. Can J Fish Aquat Sci 53:2484–2493CrossRefGoogle Scholar
  29. Hughes NF, Hayes JW, Shearer KA, Young RG (2003) Testing a model of drift-feeding using three-dimensional videography of wild brown trout, Salmo trutta, in a New Zealand river. Can J Fish Aquat Sci 60:1462–1476CrossRefGoogle Scholar
  30. Irvine JR, Northcote TG (1982) Significance of sequential feeding patterns of juvenile rainbow trout in a large lake-fed river. Trans Am Fish Soc 111:446–452CrossRefGoogle Scholar
  31. Jenkins TM Jr (1969) Social structure, position choice, and micridistribution of two trout Species (Salmo trutta and Salmo gairdneri) resident in mountain streams. Anim Behav Monogr 2:57–123CrossRefGoogle Scholar
  32. Jenkins AR, Keeley ER (2010) Bioenergetic assessment of habitat quality for stream-dwelling cutthroat trout (Oncorhynchus clarkii bouvieri) with implications for climate change and nutrient supplementation. Can J Fish Aquat Sci 67:371–385. doi: 10.1139/F09-193 CrossRefGoogle Scholar
  33. Kiflawi M, Genin A (1997) Prey flux manipulation and the feeding rates of reef-dwelling planktivorous fish. Ecology 78:1062–1077CrossRefGoogle Scholar
  34. Kutner MH, Nachtsheim CJ, Neter J, Li W (2005) Applied Linear Statistical Models, 5th edn. McGraw-Hill/Irwin, New YorkGoogle Scholar
  35. McLaughlin RL, Grant JWA, Noakes DLG (2000) Living with failure: the prey capture success of young brook charr in streams. Ecol Freshw Fish 9:81–89CrossRefGoogle Scholar
  36. McNicol RE, Scherer E, Murkin EJ (1985) Quantitative field investigations of feeding and territorial behavior of young-of-the-year brook charr, Salvelinus fontinalis. Environ Biol Fish 12:219–229CrossRefGoogle Scholar
  37. Metcalfe NB, Huntingford FA, Thorpe JE (1987) Predation risk impairs diet selection in juvenile salmon. Anim Behav 35:931–933CrossRefGoogle Scholar
  38. Nakayama K, Martini P (2011) Situating visual search. Vision Res 51:1526–1537. doi: 10.1016/j.visres.2010.09.003 PubMedCrossRefGoogle Scholar
  39. Nislow KH, Folt CL, Parrish DL (2000) Spatially explicit bioenergetic analysis of habitat quality for age-0 Atlantic salmon. Trans Am Fish Soc 129:1067–1081CrossRefGoogle Scholar
  40. O'Brien WJ, Showalter JJ (1993) Effects of current velocity and suspended debris on the drift feeding of Arctic grayling. Trans Am Fish Soc 122:609–615CrossRefGoogle Scholar
  41. Palmer J (1995) Attention in visual search: distinguishing four causes of a set-size effect. Curr Dir Psychol Sci 4:118–123CrossRefGoogle Scholar
  42. Piccolo JJ, Hughes NF, Bryant MD (2008a) Water velocity influences prey detection and capture by drift-feeding juvenile coho salmon (Oncorhychus kisutch) and steelhead (Oncorhynchus mykiss irideus). Can J Fish Aquat Sci 65:266–275CrossRefGoogle Scholar
  43. Piccolo JJ, Hughes NF, Bryant MD (2008b) Development of net energy intake models for drift-feeding juvenile coho salmon and steelhead. Environ Biol Fish 83:259–267CrossRefGoogle Scholar
  44. Ringler NH (1979) Selective predation by drift-feeding brown trout (Salmo trutta). J Fish Res Board Can 36:392–403CrossRefGoogle Scholar
  45. Ringler NH (1985) Individual and temporal variation in prey switching by brown trout, Salmo trutta. Copeia 1985:918–926CrossRefGoogle Scholar
  46. Skelhorn J, Rowland HM, Speed MP, De Wert L, Quinn L, Delf J, Ruxton GD (2010) Size-dependent misclassification of masquerading prey. Behav Ecol 21:1344–1348. doi: 10.1093/beheco/arq159 CrossRefGoogle Scholar
  47. Speed MP, Ruxton GD (2010) Imperfect Batesian mimicry and the conspicuousness costs of mimetic resemblance. Am Nat 176:E1–14. doi: 10.1086/652990 PubMedCrossRefGoogle Scholar
  48. Staddon JER, Gendron RP (1983) Optimal detection of cryptic prey may lead to predator switching. Am Nat 843-848Google Scholar
  49. Van Winkle W, Jager HI, Railsback SF, Holcomb BD, Studley TK, Balridge JE (1998) Individual-based model of sympatric populations of brown, and rainbow trout for instream flow assessment: model description, and calibration. Ecol Model 110:175–207CrossRefGoogle Scholar
  50. Webster JR, Benfield EF, Ehrman TP, Schaeffer MA, Tank JL, Hutchens JJ, D'Angelo DJ (1999) What happens to allochthonous material that falls into streams? A synthesis of new and published information from Coweeta. Freshw Biol 41:687–705CrossRefGoogle Scholar
  51. Wickens TD 2001. Elementary signal detection theory. Oxford University Press.Google Scholar
  52. Wolfe JM (1998) What can 1 million trials tell us about visual search? Psychol Sci 9:33–39CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Jason Neuswanger
    • 1
  • Mark S. Wipfli
    • 2
  • Amanda E. Rosenberger
    • 3
  • Nicholas F. Hughes
    • 4
  1. 1.Department of Biology and WildlifeUniversity of Alaska FairbanksFairbanksUSA
  2. 2.U.S. Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit, Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksUSA
  3. 3.U.S. Geological Survey, Missouri Cooperative Fish and Wildlife Research Unit, Department of Fisheries and WildlifeUniversity of MissouriColumbiaUSA
  4. 4.Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksUSA

Personalised recommendations