Cognitive performance is linked to group size and affects fitness in Australian magpies

Abstract

The social intelligence hypothesis states that the demands of social life drive cognitive evolution1,2,3. This idea receives support from comparative studies that link variation in group size or mating systems with cognitive and neuroanatomical differences across species3,4,5,6,7, but findings are contradictory and contentious8,9,10. To understand the cognitive consequences of sociality, it is also important to investigate social variation within species. Here we show that in wild, cooperatively breeding Australian magpies, individuals that live in large groups show increased cognitive performance, which is linked to increased reproductive success. Individual performance was highly correlated across four cognitive tasks, indicating a ‘general intelligence factor’ that underlies cognitive performance. Repeated cognitive testing of juveniles at different ages showed that the correlation between group size and cognition emerged in early life, suggesting that living in larger groups promotes cognitive development. Furthermore, we found a positive association between the task performance of females and three indicators of reproductive success, thus identifying a selective benefit of greater cognitive performance. Together, these results provide intraspecific evidence that sociality can shape cognitive development and evolution.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: The relationship between group size and cognition.
Figure 2: The relationship between group size and general cognitive performance.
Figure 3: The relationship between general cognitive performance and group size in juveniles.
Figure 4: The relationship between female traits and reproductive success.

References

  1. 1

    Humphrey, N. in Growing Points in Ethology (eds Bateson, P. P. G. & Hinde, R. A. ) 303–317 (Cambridge Univ. Press, 1976)

    Google Scholar 

  2. 2

    Byrne, R. W. & Whiten, A. Machiavellian Intelligence: Social Expertise and the Evolution of Intellect in Monkeys, Apes, and Humans (Clarendon, 1988)

  3. 3

    Shultz, S. & Dunbar, R. I. The evolution of the social brain: anthropoid primates contrast with other vertebrates. Proc. R. Soc. B 274, 2429–2436 (2007)

    Article  PubMed  Google Scholar 

  4. 4

    Bond, A. B., Kamil, A. C. & Balda, R. P. Social complexity and transitive inference in corvids. Anim. Behav. 65, 479–487 (2003)

    Article  Google Scholar 

  5. 5

    Street, S. E., Navarrete, A. F., Reader, S. M. & Laland, K. N. Coevolution of cultural intelligence, extended life history, sociality, and brain size in primates. Proc. Natl Acad. Sci. USA 114, 7908–7914 (2017)

    Article  CAS  PubMed  Google Scholar 

  6. 6

    Forss, S. I. F., Willems, E., Call, J. & van Schaik, C. P. Cognitive differences between orang-utan species: a test of the cultural intelligence hypothesis. Sci. Rep. 6, 30516 (2016)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  7. 7

    Fox, K. C. R., Muthukrishna, M. & Shultz, S. The social and cultural roots of whale and dolphin brains. Nat. Ecol. Evol. 1, 1699–1705 (2017)

    Article  PubMed  Google Scholar 

  8. 8

    Holekamp, K. E. Questioning the social intelligence hypothesis. Trends Cogn. Sci. 11, 65–69 (2007)

    Article  PubMed  Google Scholar 

  9. 9

    DeCasien, A. R., Williams, S. A. & Higham, J. P. Primate brain size is predicted by diet but not sociality. Nat. Ecol. Evol. 1, 0112 (2017)

    Article  Google Scholar 

  10. 10

    Sayol, F. et al. Environmental variation and the evolution of large brains in birds. Nat. Commun. 7, 13971 (2016)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  11. 11

    Morand-Ferron, J., Cole, E. F. & Quinn, J. L. Studying the evolutionary ecology of cognition in the wild: a review of practical and conceptual challenges. Biol. Rev. Camb. Philos. Soc. 91, 367–389 (2016)

    Article  PubMed  Google Scholar 

  12. 12

    Thornton, A. & Lukas, D. Individual variation in cognitive performance: developmental and evolutionary perspectives. Phil. Trans. R. Soc. B 367, 2773–2783 (2012)

    Article  PubMed  Google Scholar 

  13. 13

    Sallet, J. et al. Social network size affects neural circuits in macaques. Science 334, 697–700 (2011)

    Article  ADS  CAS  PubMed  Google Scholar 

  14. 14

    Kanai, R ., Bahrami, B ., Roylance, R . & Rees, G. Online social network size is reflected in human brain structure. Proc. R. Soc. B 279, 1327–1334 (2012)

    Article  CAS  PubMed  Google Scholar 

  15. 15

    Fischer, S., Bessert-Nettelbeck, M., Kotrschal, A. & Taborsky, B. Rearing-group size determines social competence and brain structure in a cooperatively breeding cichlid. Am. Nat. 186, 123–140 (2015)

    Article  PubMed  Google Scholar 

  16. 16

    MacLean, E. L. et al. The evolution of self-control. Proc. Natl Acad. Sci. USA 111, E2140–E2148 (2014)

    Article  CAS  PubMed  Google Scholar 

  17. 17

    Plomin, R. The genetics of G in human and mouse. Nat. Rev. Neurosci. 2, 136–141 (2001)

    Article  CAS  PubMed  Google Scholar 

  18. 18

    Chandra, S. B., Hosler, J. S. & Smith, B. H. Heritable variation for latent inhibition and its correlation with reversal learning in honeybees (Apis mellifera). J. Comp. Psychol. 114, 86–97 (2000)

    Article  CAS  PubMed  Google Scholar 

  19. 19

    Isden, J., Panayi, C., Dingle, C. & Madden, J. Performance in cognitive and problem-solving tasks in male spotted bowerbirds does not correlate with mating success. Anim. Behav. 86, 829–838 (2013)

    Article  Google Scholar 

  20. 20

    Shaw, R. C., Boogert, N. J., Clayton, N. S. & Burns, K. C. Wild psychometrics: evidence for ‘general’ cognitive performance in wild New Zealand robins, Petroica longipes. Anim. Behav. 109, 101–111 (2015)

    Article  Google Scholar 

  21. 21

    Hopkins, W. D., Russell, J. L. & Schaeffer, J. Chimpanzee intelligence is heritable. Curr. Biol. 24, 1649–1652 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. 22

    Galsworthy, M. J. et al. Assessing reliability, heritability and general cognitive ability in a battery of cognitive tasks for laboratory mice. Behav. Genet. 35, 675–692 (2005)

    Article  PubMed  Google Scholar 

  23. 23

    Buchanan, K. L., Grindstaff, J. L. & Pravosudov, V. V. Condition dependence, developmental plasticity, and cognition: implications for ecology and evolution. Trends Ecol. Evol. 28, 290–296 (2013)

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24

    Plomin, R. & Deary, I. J. Genetics and intelligence differences: five special findings. Mol. Psychiatry 20, 98–108 (2015)

    Article  CAS  PubMed  Google Scholar 

  25. 25

    Boogert, N. J., Anderson, R. C., Peters, S., Searcy, W. A. & Nowicki, S. Song repertoire size in male song sparrows correlates with detour reaching, but not with other cognitive measures. Anim. Behav. 81, 1209–1216 (2011)

    Article  Google Scholar 

  26. 26

    Hughes, J. M. et al. High levels of extra-group paternity in a population of Australian magpies Gymnorhina tibicen: evidence from microsatellite analysis. Mol. Ecol. 12, 3441–3450 (2003)

    Article  CAS  PubMed  Google Scholar 

  27. 27

    Kotrschal, A. et al. Artificial selection on relative brain size in the guppy reveals costs and benefits of evolving a larger brain. Curr. Biol. 23, 168–171 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. 28

    Arnold, K. E ., Ramsay, S. L ., Donaldson, C. & Adam, A. Parental prey selection affects risk-taking behaviour and spatial learning in avian offspring. Proc. R. Soc. B 274, 2563–2569 (2007)

    Article  PubMed  Google Scholar 

  29. 29

    Silk, J. B., Alberts, S. C. & Altmann, J. Social bonds of female baboons enhance infant survival. Science 302, 1231–1234 (2003)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    Croston, R., Branch, C. L., Kozlovsky, D. Y., Dukas, R. & Pravosudov, V. V. Heritability and the evolution of cognitive traits. Behav. Ecol. 26, 1447–1459 (2015)

    Article  Google Scholar 

  31. 31

    Pike, K. N. How much do Helpers help? Variation in Helper Behaviour in the Cooperatively Breeding Western Australian Magpie. MSc Thesis, Univ. Western Australia (2016)

  32. 32

    Kaplan, G. Australian Magpie: Biology and Behaviour of an Unusual Songbird (CSIRO Publishing, 2004)

  33. 33

    Edwards, E. K., Mitchell, N. J. & Ridley, A. R. The impact of high temperatures on foraging behaviour and body condition in the Western Australian Magpie Cracticus tibicen dorsalis. Ostrich 86, 137–144 (2015)

    Article  Google Scholar 

  34. 34

    Morand-Ferron, J. Why learn? The adaptive value of associative learning in wild populations. Curr. Opin. Behav. Sci. 16, 73–79 (2017)

    Google Scholar 

  35. 35

    Sherry, D. F. in Cognitive Ecology: the Evolutionary Ecology of Information Processing and Decision Making (ed. Dukas, R. ) 261–296 (Univ. Chicago Press, 1998)

    Google Scholar 

  36. 36

    Lotem, A. & Halpern, J. Y. Coevolution of learning and data-acquisition mechanisms: a model for cognitive evolution. Phil. Trans. R. Soc. B 367, 2686–2694 (2012)

    Article  PubMed  Google Scholar 

  37. 37

    Leadbeater, E. What evolves in the evolution of social learning? J. Zool. 295, 4–11 (2015)

    Article  Google Scholar 

  38. 38

    Amici, F., Aureli, F. & Call, J. Fission–fusion dynamics, behavioral flexibility, and inhibitory control in primates. Curr. Biol. 18, 1415–1419 (2008)

    Article  CAS  PubMed  Google Scholar 

  39. 39

    Boogert, N. J., Giraldeau, L.-A. & Lefebvre, L. Song complexity correlates with learning ability in zebra finch males. Anim. Behav. 76, 1735–1741 (2008)

    Article  Google Scholar 

  40. 40

    Rowe, C. & Healy, S. D. Measuring variation in cognition. Behav. Ecol. 25, 1287–1292 (2014)

    Article  Google Scholar 

  41. 41

    Griffin, A. S. & Guez, D. Innovative problem solving in nonhuman animals: the effects of group size revisited. Behav. Ecol. 26, 722–734 (2015)

    Article  Google Scholar 

  42. 42

    Nowicki, S., Searcy, W. & Peters, S. Brain development, song learning and mate choice in birds: a review and experimental test of the “nutritional stress hypothesis”. J. Comp. Physiol. A 188, 1003–1014 (2002)

    Article  CAS  Google Scholar 

  43. 43

    Burnham, K. P . & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, 2002)

  44. 44

    Symonds, M. R. E. & Moussalli, A. A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion. Behav. Ecol. Sociobiol. 65, 13–21 (2011)

    Article  Google Scholar 

  45. 45

    Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010)

    Article  CAS  PubMed  Google Scholar 

  46. 46

    Nakagawa, S. & Schielzeth, H. Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists. Biol. Rev. Camb. Philos. Soc. 85, 935–956 (2010)

    PubMed  Google Scholar 

Download references

Acknowledgements

We thank E. Russell and the late I. Rowley for access to their life-history records, and for allowing us to continue work on their Guildford magpie population; A. Wolton for help with fieldwork; R. Lymbery for help with statistical analyses; and N. Boogert and A. Young for helpful comments and discussion. This work was funded by an ARC Discovery grant awarded to A.R.R., A.T. and M. B. V. Bell, and a University of Western Australia International Postgraduate Research Scholarship and Endeavour Research Fellowship awarded to B.J.A. A.T. received additional support from a BBSRC David Phillips Fellowship (BB/H021817/1).

Author information

Affiliations

Authors

Contributions

B.J.A., A.R.R. and A.T. conceived and designed the study. B.J.A. wrote the manuscript. B.J.A. and E.K.E. carried out data collection. All authors discussed results and commented on the manuscript.

Corresponding authors

Correspondence to Benjamin J. Ashton or Amanda R. Ridley or Alex Thornton.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks T. Bugnyar and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Figure 1 Adult cognitive test set.

ac, The cognitive test series used to quantify individual variation in inhibitory control (a), associative and reversal learning (b) and spatial memory (c).

Extended Data Figure 2 Developmental trajectory of cognitive performance.

a, b, The developmental trajectory of Australian magpies at 100, 200 and 300 days after fledging for two cognitive traits: behavioural inhibition (a; n = 48 trials) and spatial memory (b; n = 46 trials). c, Developmental trajectory for behavioural inhibition and spatial memory combined (n = 94 trials). Green dots, individuals from small groups (containing 1–7 individuals); blue dots, individuals from large groups (≥8 individuals). Scores are measured as either the number of trials taken to succeed at the task or the number of locations searched, so lower scores indicate better performance. Source data

Extended Data Figure 3 Frequency distribution of general cognitive performance in relation to group size.

a, b, Frequency distribution of general cognitive performance among individuals in small groups (a; containing <8 individuals, n = 29 individuals) and large groups (b, >8 individuals, n = 17 individuals). Source data

Extended Data Figure 4 Juvenile cognitive test batteries.

ai, Cognitive test batteries presented to individuals at 100 (ac), 200 (df) and 300 (gi) days after fledging, containing four tasks designed to quantify inhibitory control (a, d, g), associative and reversal learning (b, e, h) and spatial memory (c, f, i). b is shown in black and white, because individuals were unable to complete the associative and reversal learning tasks at 100 days after fledging. Red circles indicate that individuals had to search a different location at each age tested in order to obtain the food reward in the spatial memory task.

Extended Data Figure 5 Example of the lids used in the cognitive tasks.

The lids used in the associative learning, reversal learning and spatial memory tasks. The lids were held firmly in place by elastic bands, and swivelled when pecked, allowing individuals to search wells for their contents.

Extended Data Table 1 Principal component analysis (adults)
Extended Data Table 2 Repeatability of cognitive performance
Extended Data Table 3 Principal component analysis (200 days after fledging)
Extended Data Table 4 Principal component analysis (300 days after fledging)

Supplementary information

Supplementary Information

This file contains Supplementary Results and Discussion, Supplementary References and Supplementary Tables 1-26. (PDF 1175 kb)

Life Sciences Reporting Summary (PDF 72 kb)

PowerPoint slides

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ashton, B., Ridley, A., Edwards, E. et al. Cognitive performance is linked to group size and affects fitness in Australian magpies. Nature 554, 364–367 (2018). https://doi.org/10.1038/nature25503

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing