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Fish pool their experience to solve problems collectively


Access to information is a key advantage of grouping. Although experienced animals can lead others to solve problems, less is known about whether partially informed individuals can pool experiences to overcome challenges collectively. Here we provide evidence of such ‘experience-pooling’. We presented shoals of sticklebacks (Gasterosteus aculeatus) with a two-stage foraging task requiring them to find and access hidden food. Individual fish were either inexperienced or had knowledge of just one of the stages. Shoals containing individuals trained in each of the stages pooled their expertise, allowing more fish to access the food, and to do so more rapidly, compared with other shoal compositions. Strong social effects were identified: the presence of experienced individuals increased the likelihood of untrained fish completing each stage. These findings demonstrate that animal groups can integrate individual experience to solve multi-stage problems, and have implications for our understanding of social foraging, migration and social systems.

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Figure 1: Number and rate of goal zone and feeder entries.
Figure 2: Proportion of naive fish entering the goal and feeder areas.


  1. Krause, J. & Ruxton, G. D. Living in Groups (Oxford Univ. Press, 2002).

    Google Scholar 

  2. Danchin, É. et al. Public information: from nosy neighbors to cultural evolution. Science 305, 487–491 (2004).

    Article  CAS  Google Scholar 

  3. Couzin, I. D. et al. Effective leadership and decision-making in animal groups on the move. Nature 433, 513–516 (2005).

    Article  CAS  Google Scholar 

  4. Couzin, I. D. Collective cognition in animal groups. Trends Cogn. Sci. 13, 36–43 (2009).

    Article  Google Scholar 

  5. Krause, J., Ruxton, G. D. & Krause, S. Swarm intelligence in animals and humans. Trends Ecol. Evol. 25, 28–34 (2010).

    Article  Google Scholar 

  6. Sumpter, D. J. Collective Animal Behavior (Princeton Univ. Press, 2010).

    Book  Google Scholar 

  7. Laland, K. N., Atton, N. & Webster, M. M. From fish to fashion: experimental and theoretical insights into the evolution of culture. Phil. Trans. R. Soc. Lond. B 366, 958–968 (2011).

    Article  CAS  Google Scholar 

  8. Ward, A. J. et al. Fast and accurate decisions through collective vigilance in fish shoals. Proc. Natl Acad. Sci. USA 108, 2312–2315 (2011).

    Article  CAS  Google Scholar 

  9. Berdahl, A. et al. Emergent sensing of complex environments by mobile animal groups. Science 339, 574–576 (2013).

    Article  CAS  Google Scholar 

  10. Ioannou, C. C. Swarm intelligence in fish? The difficulty in demonstrating distributed and self-organised collective intelligence in (some) animal groups. Behav. Process. (2016).

  11. Ward, A. J. W. & Webster, M. M. Sociality: The Behaviour of Group Living Animals (Springer, 2016).

    Book  Google Scholar 

  12. Bonabeau, E., Dorigo, M. & Theraulaz, G. Swarm Intelligence: From Natural to Artificial Systems (Oxford Univ. Press, 1999).

    Google Scholar 

  13. Garnier, S., Gautrais, J. & Theraulaz, G. The biological principles of swarm intelligence. Swarm Intel. 1, 3–31 (2007).

    Article  Google Scholar 

  14. Codling, E. A., Pitchford, J. W. & Simpson, S. D. Group navigation and the ‘many-wrongs principle’ in models of animal movement. Ecology 88, 1864–1870 (2007).

    Article  CAS  Google Scholar 

  15. Codling, E. A. & Bode, N. W. Balancing direct and indirect sources of navigational information in a leaderless model of collective animal movement. J. Theor. Biol. 394, 32–42 (2016).

    Article  Google Scholar 

  16. Morand-Ferron, J. & Quinn, J. L. Larger groups of passerines are more efficient problem solvers in the wild. Proc. Natl Acad. Sci. USA 108, 15898–15903 (2011).

    Article  CAS  Google Scholar 

  17. Dyer, J. R. et al. Leadership, consensus decision making and collective behaviour in humans. Phil. Trans. R. Soc. Lond. B 364, 781–789 (2009).

    Article  Google Scholar 

  18. Ioannou, C. C., Singh, M. & Couzin, I. D. Potential leaders trade off goal-oriented and socially oriented behavior in mobile animal groups. Am. Nat. 186, 284–293 (2015).

    Article  Google Scholar 

  19. Jolles, J. W. et al. The role of social attraction and its link with boldness in the collective movements of three-spined sticklebacks. Anim. Behav. 99, 147–153 (2015).

    Article  Google Scholar 

  20. Webster, M. M. Experience and motivation shape leader–follower interactions in fish shoals. Behav. Ecol. 28, 77–84 (2017).

    Article  Google Scholar 

  21. Conradt, L. et al. ‘Leading according to need’ in self-organizing groups. Am. Nat. 173, 304–312 (2009).

    Article  CAS  Google Scholar 

  22. Day, R. L. et al. Interactions between shoal size and conformity in guppy social foraging. Anim. Behav. 62, 917–925 (2001).

    Article  Google Scholar 

  23. Atton, N. et al. Information flow through threespine stickleback networks without social transmission. Proc. R. Soc. Lond. B 279, 4272–4278 (2012).

    Article  CAS  Google Scholar 

  24. Krause, S. et al. Swarm intelligence in humans: diversity can trump ability. Anim. Behav. 81, 941–948 (2011).

    Article  Google Scholar 

  25. Reader, S. M. & Laland, K. N. Diffusion of foraging innovations in the guppy. Anim. Behav. 60, 175–180 (2000).

    Article  CAS  Google Scholar 

  26. Atton, N. et al. Familiarity affects social network structure and discovery of prey patch locations in foraging stickleback shoals. Proc. R. Soc. Lond. B 281, 20140579 (2014).

    Article  CAS  Google Scholar 

  27. Webster, M. M. & Laland, K. N. Evaluation of a non-invasive tagging system for laboratory studies using three-spined sticklebacks (Gasterosteus aculeatus). J. Fish Biol. 75, 1868–1873 (2009).

    Article  CAS  Google Scholar 

  28. R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).

  29. Therneau, T. M. & Lumley, T. survival: Survival analysis v. 2.41-2. (2015).

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This work was funded by an ERC Advanced Grant to K.N.L. (EVOCULTURE, ref. 232823). We thank K. Meacham for assistance in preparing the manuscript.

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M.M.W. designed and performed the experiments. M.M.W., A.W. and K.N.L. analysed the data and co-authored the paper.

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Correspondence to Mike M. Webster.

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The authors declare no competing financial interests.

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Supplementary Methods; Supplementary Figures 1–4; Supplementary Tables 1–3 (PDF 308 kb)

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Webster, M., Whalen, A. & Laland, K. Fish pool their experience to solve problems collectively. Nat Ecol Evol 1, 0135 (2017).

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