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Constraints of background risk on space use and learning in Trinidadian guppies


Constraints of background risk on space use and learning in Trinidadian guppies

Allan, Jamie (2022) Constraints of background risk on space use and learning in Trinidadian guppies. Masters thesis, Concordia University.

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Predators affect prey populations by driving prey to adopt costly antipredator strategies. Spatial neophobia mitigates the risks of novel spaces by reducing space use and is inducible through exposure to short-term elevated background risk. We hypothesized that background risk influences the ability to learn safe refuge sites through decreased exploration of novel habitats; specifically, high risk constrains the ability to learn safe refuge sites. We conducted three experiments using shoals of five female guppies pre-exposed to high or low background risk. The shoals explored an eight-arm radial maze reinforced by different combinations of foraging patches, predator models, or empty arms, then were exposed to chemical alarm cue or distilled water without reinforcements. We found no evidence to support that background risk affects the speed or accuracy of the initial decision to flee following cue exposure. We saw an overall preference for arms that previously contained food over arms that were either empty or contained predator models, suggesting that prey learned safe areas. We also showed that fish given alarm cue entered predator arms more than those given distilled water, suggesting that an acute threat leads prey to make more mistakes. While there is no evidence that background risk affects space use and learning, our results indicate that guppies can learn and use safety information, while predation threats compromise their ability to use this information. Our study provides insight into the complexity of behavioural trade-offs. This has implications for conservation initiatives seeking to understand prey habitat selection.

Divisions:Concordia University > Faculty of Arts and Science > Biology
Item Type:Thesis (Masters)
Authors:Allan, Jamie
Institution:Concordia University
Degree Name:M. Sc.
Date:4 March 2022
Thesis Supervisor(s):Brown, Grant E.
Keywords:Background risk, predation risk, space use, neophobia, spatial learning
ID Code:990568
Deposited By: JAMIE ALLAN
Deposited On:16 Jun 2022 14:24
Last Modified:16 Jun 2022 14:24


Broglio, C., Rodríguez, F., & Salas, C. (2003). Spatial cognition and its neural basis in teleost fishes. Fish and Fisheries, 4(3), 247–255. https://doi.org/10.1046/j.1467-2979.2003.00128.x
Brown, C., & Laland, K. (2006). Social learning in fishes. In C. Brown, K. Laland, & J. Krause (Eds.), Fish Cognition and Behavior (pp. 186–202). Blackwell Publishing.
Brown, G. E., Chivers, D. P., Elvidge, C. K., Jackson, C. D., & Ferrari, M. C. O. (2014). Background level of risk determines the intensity of predator neophobia in juvenile convict cichlids. Behavioral Ecology and Sociobiology, 68, 127–133. https://doi.org/10.1007/s00265-013-1629-z
Brown, G. E., Elvidge, C. K., Ramnarine, I., Ferrari, M. C. O., & Chivers, D. P. (2015). Background risk and recent experience influences retention of neophobic responses to predators. Behavioral Ecology and Sociobiology, 69, 737–745. https://doi.org/10.1007/s00265-015-1888-y
Brown, G. E., Ferrari, M. C. O., Elvidge, C. K., Ramnarine, I., & Chivers, D. P. (2013). Phenotypically plastic neophobia: a response to variable predation risk. Proceedings of the Royal Society B: Biological Sciences, 280(1756), 20122712. https://doi.org/10.1098/rspb.2012.2712
Chittka, L., Skorupski, P., & Raine, N. E. (2009). Speed-accuracy tradeoffs in animal decision making. Trends in Ecology and Evolution, 24(7), 400–407. https://doi.org/10.1016/j.tree.2009.02.010
Chivers, D. P., Brown, G. E., & Ferrari, M. C. O. (2012). The evolution of alarm substances and disturbance cues in aquatic animals. In C. Brönmark & L.-A. Hansson (Eds.), Chemical Ecology in Aquatic Systems (pp. 127–139). Oxford University Press.
Chivers, D. P., McCormick, M. I., Mitchell, M. D., Ramasamy, R. A., & Ferrari, M. C. O. (2014). Background level of risk determines how prey categorize predators and non-predators. Proceedings of the Royal Society B: Biological Sciences, 281(20140355). https://doi.org/10.1098/rspb.2014.0355
Chivers, D. P., & Smith, R. J. F. (1998). Chemical alarm signalling in aquatic predator-prey systems: A review and prospectus. Ecoscience, 5(3), 338–352. https://doi.org/10.1080/11956860.1998.11682471
Crane, A. L., Bairos‐Novak, K. R., Goldman, J. A., & Brown, G. E. (2022). Chemical disturbance cues in aquatic systems: a review and prospectus. Ecological Monographs, 92(1), e01487. https://doi.org/10.1002/ecm.1487
Crane, A. L., Brown, G. E., Chivers, D. P., & Ferrari, M. C. O. (2020a). An ecological framework of neophobia: from cells to organisms to populations. Biological Reviews, 95(1), 218–231. https://doi.org/10.1111/brv.12560

Crane, A. L., Demers, E. E., Feyten, L. E. A., Ramnarine, I. W., & Brown, G. E. (in press). Exploratory decisions of Trinidadian guppies when uncertain about predation risk. Animal Cognition. https://doi.org/10.1007/s10071-021-01575-4
Crane, A. L., Feyten, L. E. A., Ramnarine, I. W., & Brown, G. E. (2020b). High-risk environments promote chemical disturbance signalling among socially familiar Trinidadian guppies. Oecologia, 193, 89–95. https://doi.org/10.1007/s00442-020-04652-6
Dall, S. R. X., Giraldeau, L. A., Olsson, O., McNamara, J. M., & Stephens, D. W. (2005). Information and its use by animals in evolutionary ecology. Trends in Ecology and Evolution, 20(4), 187–193. https://doi.org/10.1016/j.tree.2005.01.010
Dingemanse, N. J., Kazem, A. J. N., Réale, D., & Wright, J. (2010). Behavioural reaction norms: animal personality meets individual plasticity. Trends in Ecology and Evolution, 25(2), 81–89. https://doi.org/10.1016/j.tree.2009.07.013
Elvidge, C. K., Chuard, P. J. C., & Brown, G. E. (2016). Local predation risk shapes spatial and foraging neophobia patterns in Trinidadian guppies. Current Zoology, 62(5), 457–462. https://doi.org/10.1093/cz/zow013
Ferrari, M. C. O., Sih, A., & Chivers, D. P. (2009). The paradox of risk allocation: a review and prospectus. Animal Behaviour, 78(3), 579–585. https://doi.org/10.1016/j.anbehav.2009.05.034
Feyten, L. E. A., Crane, A. L., Ramnarine, I. W., & Brown, G. E. (2021). Predation risk shapes the use of conflicting personal risk and social safety information in guppies. Behavioral Ecology, 32(6), 1296–1305. https://doi.org/10.1093/beheco/arab096
Fox, J., & Weisberg, S. (2019). car: Companion to applied regression (R package version 3.0). https://socialsciences.mcmaster.ca/jfox/Books/Companion/%0A
Godin, J.-G. J. (1997). Evading predators. In J.-G. J. Godin (Ed.), Behavioural Ecology of Teleost Fishes (pp. 191–236).
Goldman, J. A., Feyten, L. E. A., Ramnarine, I. W., & Brown, G. E. (2020). Sender and receiver experience alters the response of fish to disturbance cues. Current Zoology, 66(3), 255–261. https://doi.org/10.1093/cz/zoz050
Goldman, J. A., Singh, A., Demers, E. E. M., Feyten, L. E. A., & Brown, G. E. (2019). Does donor group size matter? The response of guppies (Poecilia reticulata) and convict cichlids (Amatitlania nigrofasciata) to disturbance cues from conspecific and heterospecific donors. Canadian Journal of Zoology, 97(4), 319–325. https://doi.org/10.1139/cjz-2018-0170
Greenberg, R. (2003). The role of neophobia and neophilia in the development of innovative behaviour of birds. In S. M. Reader & K. N. Laland (Eds.), Animal Innovation (pp. 175–196). Oxford University Press.
Greenberg, R., & Mettke-Hofmann, C. (2001). Ecological aspects of neophobia and neophilia in birds. In V. Nolan & C. F. Thompson (Eds.), Current Ornithology (Vol. 16, pp. 119–178). Springer US. https://doi.org/10.1007/978-1-4615-1211-0
Hasenjager, M. J., & Dugatkin, L. A. (2017). Fear of predation shapes social network structure and the acquisition of foraging information in guppy shoals. Proceedings of the Royal Society B: Biological Sciences, 284(1867), 20172020. https://doi.org/10.1098/rspb.2017.2020
Inglis, I. R., Langton, S., Forkman, B., & Lazarus, J. (2001). An information primacy model of exploratory and foraging behaviour. Animal Behaviour, 62(3), 543–557. https://doi.org/10.1006/anbe.2001.1780
Johnson, D. D. P., Blumstein, D. T., Fowler, J. H., & Haselton, M. G. (2013). The evolution of error: error management, cognitive constraints, and adaptive decision-making biases. Trends in Ecology & Evolution, 28(8), 474–481. https://doi.org/10.1016/j.tree.2013.05.014
Kelley, J. L., & Magurran, A. E. (2006). Learned defences and counterdefenses in predator-prey interactions. In C. Brown, K. Laland, & J. Krause (Eds.), Fish Cognition and Behavior (pp. 28–48). Blackwell Publishing.
Kendal, R. L., Coolen, I., van Bergen, Y., & Laland, K. N. (2005). Trade-offs in the adaptive use of social and asocial learning. Advances in the Study of Behavior, 35, 333–379. https://doi.org/10.1016/S0065-3454(05)35008-X
Kramer, D. L., Rangeley, R. W., & Chapman, L. J. (1997). Habitat selection: patterns of spatial distribution from behavioural decisions. In J.-G. J. Godin (Ed.), Behavioural Ecology of Teleost Fishes (pp. 38–80). Oxford University Press.
Lenth, R. (2020). emmeans: Estimated marginal means, aka least-squares means (R package version 1.5.1.). https://cran.r-project.org/package=emmeans
Lilly, M. V., Lucore, E. C., & Tarvin, K. A. (2019). Eavesdropping grey squirrels infer safety from bird chatter. PLoS ONE, 14(9), 4–8. https://doi.org/10.1371/journal.pone.0221279
Lima, S. L. (1998). Nonlethal effects in the ecology of predator-prey interactions. BioScience, 48(1), 25–34. https://doi.org/10.2307/1313225
Lima, S. L., & Bednekoff, P. A. (1999). Temporal variation in danger drives antipredator behavior: the predation risk allocation hypothesis. The American Naturalist, 153(6), 649–659. https://doi.org/10.1086/303202
Lima, S. L., & Dill, L. M. (1990). Behavioral decisions made under the risk of predation: a review and prospectus. Canadian Journal of Zoology, 68(4), 619–640. https://doi.org/10.1139/z90-092
Luttbeg, B., Ferrari, M. C. O., Blumstein, D. T., & Chivers, D. P. (2020). Safety cues can give prey more valuable information than danger cues. American Naturalist, 195(4), 636–648. https://doi.org/10.1086/707544
Mettke-Hofmann, C. (2014). Cognitive ecology: Ecological factors, life-styles, and cognition. Wiley Interdisciplinary Reviews: Cognitive Science, 5(3), 345–360. https://doi.org/10.1002/wcs.1289
Mettke-Hofmann, C., Winkler, H., Hamel, P. B., & Greenberg, R. (2013). Migratory new world blackbirds (icterids) are more neophobic than closely related resident icterids. PLoS ONE, 8(2). https://doi.org/10.1371/journal.pone.0057565
Odling-Smee, L., Simpson, S. D., & Braithwaite, V. A. (2006). The role of learning in fish orientation. In C. Brown, K. Laland, & J. Krause (Eds.), Fish Cognition and Behavior (pp. 119–138). Blackwell Publishing.
Peckarsky, B. L., Abrams, P. A., Bolnick, D. I., Dill, L. M., Grabowski, H., Luttbeg, B., Orrock, J. L., Peacor, S. D., Preisser, E. L., Oswald, J., Trussell, G. C., Peckarsky, L., Bolnick, I., Abrams, P. A., Dill, M., Grabowski, H., Orrock, J. L., Preisser, L., Peacor, S. D., & Trussell, C. (2008). Revisiting the classics : considering nonconsumptive effects in textbook examples of predator — prey interactions. Ecology, 89(9), 2416–2425. https://doi.org/10.1890/07-1131.1
Preisser, E. L., & Bolnick, D. I. (2008). The many faces of fear: Comparing the pathways and impacts of nonconsumptive predator effects on prey populations. PLoS ONE, 3(6), 5–8. https://doi.org/10.1371/journal.pone.0002465
Preisser, E. L., Bolnick, D. I., & Benard, M. E. (2005). Scared to death? The effects of intimidation and consumption in predator-prey interactions. Ecology, 86(2), 501–509. https://doi.org/10.1890/04-0719
R Core Team. (2019). R: A language and environment for statistical computing (3.6.2). R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/
Ripley, B., & Venables, W. (2016). nnet: Feed-forward neural networks and multinomial log-linear models (R package version 7.3-12). https://cran.r-project.org/package=nnet
Rodriguez, F., Broglio, C., Duran, E., Gomez, A., & Salas, C. (2006). Neural mechanisms of learning in teleost fishes. In C. Brown, K. N. Laland, & J. Krause (Eds.), Fish Cognition and Behavior (pp. 243–277). Blackwell Publishing.
Sih, A., Ziemba, R., & Harding, K. C. (2000). New insights on how temporal variation in predation risk shapes prey behavior. Trends in Ecology and Evolution, 15(1), 3–4. https://doi.org/10.1016/S0169-5347(99)01766-8
Smith, R. J. F. (1997). Avoiding and deterring predators. In J.-G. J. Godin (Ed.), Behavioural Ecology of Teleost Fishes (pp. 163–190). Oxford University Press.
The jamovi Project. (2021). jamovi (1.6). https://www.jamovi.org
Warburton, K. (2006). Learning of foraging skills by fishes. In C. Brown, K. N. Laland, & J. Krause (Eds.), Fish Cognition and Behavior (pp. 9–27). Blackwell Publishing.
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