The cognitive buffer hypothesis posits that environmental variability can be a major driver of the evolution of cognition because an enhanced ability to produce flexible behavioural responses facilitates coping with the unexpected. Although comparative evidence supports different aspects of this hypothesis, a direct connection between cognition and the ability to survive a variable and unpredictable environment has yet to be demonstrated. Here, we use complementary demographic and evolutionary analyses to show that among birds, the mechanistic premise of this hypothesis is well supported but the implied direction of causality is not. Specifically, we show that although population dynamics are more stable and less affected by environmental variation in birds with larger relative brain sizes, the evolution of larger brains often pre-dated and facilitated the colonization of variable habitats rather than the other way around. Our findings highlight the importance of investigating the timeline of evolutionary events when interpreting patterns of phylogenetic correlation.
Subscribe to Journal
Get full journal access for 1 year
only $9.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Bennett, P. M. & Harvey, P. H. Relative brain size and ecology in birds. J. Zool. 207, 151–169 (1985).
Isler, K. & van Schaik, C. P. Metabolic costs of brain size evolution. Biol. Lett. 2, 557–560 (2006).
Iwaniuk, A. N. & Nelson, J. E. Developmental differences are correlated with relative brain size in birds: a comparative analysis. Can. J. Zool. 81, 1913–1928 (2003).
Barton, R. A. & Capellini, I. Maternal investment, life histories, and the costs of brain growth in mammals. Proc. Natl Acad. Sci. USA 108, 6169–6174 (2011).
Sol, D. in Cognitive Ecology II (eds Dukas, R. & Ratcliffe, J. M.) 111–134 (Univ. Chicago Press, Chicago, 2009).
Potts, R. Variability selection in hominid evolution. Evol. Anthropol. 7, 81–96 (1998).
Reader, S. M. & Laland, K. N. Social intelligence, innovation, and enhanced brain size in primates. Proc. Natl Acad. Sci. USA 99, 4436–4441 (2002).
Lefebvre, L. Brains, innovations, tools and cultural transmission in birds, non-human primates, and fossil hominins. Front. Hum. Neurosci. 7, 245 (2013).
Sol, D., Székely, T., Liker, A. & Lefebvre, L. Big-brained birds survive better in nature. Proc. R. Soc. B 274, 763–769 (2007).
Maille, A. & Schradin, C. Survival is linked with reaction time and spatial memory in African striped mice. Biol. Lett. 12, 20160346 (2016).
Shultz, S., Bradbury, R. B., Evans, K. L., Gregory, R. D. & Blackburn, T. M. Brain size and resource specialization predict long-term population trends in British birds. Proc. R. Soc. B 272, 2305–2311 (2005).
Maklakov, A. A., Immler, S., Gonzalez-Voyer, A., Rönn, J. & Kolm, N. Brains and the city: big-brained passerine birds succeed in urban environments. Biol. Lett. 7, 730–732 (2011).
Vincze, O. Light enough to travel or wise enough to stay? Brain size evolution and migratory behavior in birds. Evolution 70, 2123–2133 (2016).
Sayol, F. et al. Environmental variation and the evolution of large brains in birds. Nat. Commun. 7, 13971 (2016).
Sol, D., Bacher, S., Reader, S. M., Lefebvre, L. & Price, S. E. T. D. Brain size predicts the success of mammal species introduced into novel environments. Am. Nat. 172, S63–S71 (2008).
Sol, D. et al. Unraveling the life history of successful invaders. Science 337, 580–583 (2012).
Amiel, J. J., Tingley, R. & Shine, R. Smart moves: effects of relative brain size on establishment success of invasive amphibians and reptiles. PLoS ONE 6, e18277 (2011).
Lefebvre, L. & Sol, D. Brains, lifestyles and cognition: are there general trends? Brain Behav. Evol. 72, 135–144 (2008).
Kotrschal, A., Corral-Lopez, A., Amcoff, M. & Kolm, N. A larger brain confers a benefit in a spatial mate search learning task in male guppies. Behav. Ecol. 26, 527–532 (2015).
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).
Lefebvre, L., Reader, S. M. & Sol, D. Brains, innovations and evolution in birds and primates. Brain Behav. Evol. 63, 233–246 (2004).
Sol, D., Lefebvre, L. & Rodríguez-Teijeiro, J. D. Brain size, innovative propensity and migratory behaviour in temperate Palaearctic birds. Proc. R. Soc. B 272, 1433–1441 (2005).
Sauer, J. R., Fallon, J. E. & Johnson, R. Use of North American Breeding Bird Survey data to estimate population change for bird conservation regions. J. Wildlife Manage. 67, 372–389 (2003).
Sauer, J. R. et al. The North American Breeding Bird Survey: Results and Analysis 1966–2015 Version 2.07.2017 (USGS Patuxent Wildlife Research Center, 2017); http://www.mbr-pwrc.usgs.gov/bbs/.
Smith, A. C., Hudson, M.-A. R., Downes, C. & Francis, C. M. Estimating breeding bird survey trends and annual indices for Canada: how do the new hierarchical Bayesian estimates differ from previous estimates? Can. Field Nat. 128, 119–134 (2014).
Clark, J. R. et al. North American Bird Conservation Initiative: Bird Conservation Region Descriptions, a Supplement to the North American Bird Conservation Initiative Bird Conservation Regions Map (US NABCI Committee, Washington DC, 2000).
Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).
Colwell, R. K. Predictability, constancy, and contingency of periodic phenomena. Ecology 55, 1148–1153 (1974).
Botero, C. A., Dor, R., McCain, C. M. & Safran, R. J. Environmental harshness is positively correlated with intraspecific divergence in mammals and birds. Mol. Ecol. 23, 259–268 (2014).
Sheehan, M. J. et al. Different axes of environmental variation explain the presence vs. extent of cooperative nest founding associations in Polistes paper wasps. Ecol. Lett. 18, 1057–1067 (2015).
Bjørnstad, O. N. & Grenfell, B. T. Noisy clockwork: time series analysis of population fluctuations in animals. Science 293, 638–643 (2001).
Ricklefs, R. E. & Scheuerlein, A. Comparison of aging-related mortality among birds and mammals. Exp. Gerontol. 36, 845–857 (2001).
McNab, B. K. Food habits, energetics, and the population biology of mammals. Am. Nat. 116, 106–124 (1980).
Lindstedt, S. L. & Boyce, M. S. Seasonality, fasting endurance, and body size in mammals. Am. Nat. 125, 873–878 (1985).
Rubenstein, D. R. & Lovette, I. J. Temporal environmental variability drives the evolution of cooperative breeding in birds. Curr. Biol. 17, 1414–1419 (2007).
Devictor, V., Julliard, R. & Jiguet, F. Distribution of specialist and generalist species along spatial gradients of habitat disturbance and fragmentation. Oikos 117, 507–514 (2008).
Ives, A., Dennis, B., Cottingham, K. & Carpenter, S. Estimating community stability and ecological interactions from time-series data. Ecol. Monogr. 73, 301–330 (2003).
Dennis, B., Ponciano, J. M., Lele, S. R., Taper, M. L. & Staples, D. F. Estimating density dependence, process noise, and observation error. Ecol. Monogr. 76, 323–341 (2006).
Sauer, J. R. & Link, W. A. Analysis of the North American Breeding Bird Survey using hierarchical models. Auk 128, 87–98 (2011).
Brook, B. W. & Bradshaw, C. J. A. Strength of evidence for density dependence in abundance time series of 1198 species. Ecology 87, 1445–1451 (2006).
Ishida, Y. et al. Genetic connectivity across marginal habitats: the elephants of the Namib Desert. Ecol. Evol. 6, 6189–6201 (2016).
Pagel, M. Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters. Proc. R. Soc. B 255, 37–45 (1994).
Green, D. M. The ecology of extinction: population fluctuation and decline in amphibians. Biol. Conserv. 111, 331–343 (2003).
Wells, J. C. K. & Stock, J. T. The biology of the colonizing ape. Am. J. Phys. Anthropol. 134, 191–222 (2007).
Roth, T. C., LaDage, L. D., Freas, C. A. & Pravosudov, V. V. Variation in memory and the hippocampus across populations from different climates: a common garden approach. Proc. R. Soc. B 279, 402–410 (2012).
Kozlovsky, D. Y., Branch, C. L. & Pravosudov, V. V. Problem-solving ability and response to novelty in mountain chickadees (Poecile gambeli) from different elevations. Behav. Ecol. Sociobiol. 69, 635–643 (2015).
Benson-Amram, S., Dantzer, B., Stricker, G., Swanson, E. M. & Holekamp, K. E. Brain size predicts problem-solving ability in mammalian carnivores. Proc. Natl Acad. Sci. USA 113, 2532–2537 (2016).
Dunbar, R. I. M. & Shultz, S. Evolution in the social brain. Science 317, 1344–1347 (2007).
Emery, N. J., Seed, A. M., von Bayern, A. M. P. & Clayton, N. S. Cognitive adaptations of social bonding in birds. Phil. Trans. R. Soc. B 362, 489–505 (2007).
Garamszegi, L. Z., Møller, A. P. & Erritzøe, J. Coevolving avian eye size and brain size in relation to prey capture and nocturnality. Proc. R. Soc. B 269, 961–967 (2002).
Myhrvold, N. P. et al. An amniote life-history database to perform comparative analyses with birds, mammals, and reptiles. Ecology 96, 3109–3109 (2015).
Iwaniuk, A. N. & Nelson, J. E. Can endocranial volume be used as an estimate of brain size in birds? Can. J. Zool. 80, 16–23 (2002).
Sol, D. et al. Evolutionary divergence in brain size between migratory and resident birds. PLoS ONE 5, e9617 (2010).
Lima-Ribeiro, M. S. et al. EcoClimate: a database of climate data from multiple models for past, present, and future for macroecologists and biogeographers. Biodivers. Informatics 10, 1–21 (2015).
Osborne, J. Notes on the use of data transformations. Pract. Assess. Res. Eval. 8, 1–7 (2002).
Smith, A. C., Hudson, M.-A. R., Downes, C. M. & Francis, C. M. Change points in the population trends of aerial-insectivorous birds in North America: synchronized in time across species and regions. PLoS ONE 10, e0130768 (2015).
Plummer, M. rjags: Bayesian Graphical Models Using MCMC (R Foundation for Statistical Computing, 2013); https://cran.r-project.org/web/packages/rjags/index.html.
Plummer, M., Best, N., Cowles, K. & Vines, K. CODA: convergence diagnosis and output analysis for MCMC. R News 6, 7–11 (2006).
Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences. Stat. Sci. 7, 457–472 (1992).
Gaston, K. J. & McArdle, B. H. The temporal variability of animal abundances: measures, methods and patterns. Phil. Trans. R. Soc. B 345, 335–358 (1994).
Jetz, W. & Rubenstein, D. R. Environmental uncertainty and the global biogeography of cooperative breeding in birds. Curr. Biol. 21, 72–78 (2011).
Harmon, L. J., Weir, J. T., Brock, C. D., Glor, R. E. & Challenger, W. GEIGER: investigating evolutionary radiations. Bioinformatics 24, 129–131 (2008).
Pinheiro, J. et al. nlme: Linear and Nonlinear Mixed Effects Models. (R Foundation for Statistical Computing, Vienna, 2016); https://CRAN.R-project.org/package=nlme.
R Development Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna, 2008).
Orme, D. et al. The caper Package: Comparative Analysis of Phylogenetics and Evolution in R v0.5.2.. (R Foundation for Statistical Computing, Vienna, 2013. http://cran.r-project.org/web/packages/caper/index.html.
Maddison, W. P. & FitzJohn, R. G. The unsolved challenge to phylogenetic correlation tests for categorical characters. Syst. Biol. 64, 127–136 (2015).
Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).
Pagel, M., Meade, A., Crespi, A. E. B. J. & Losos, E. J. B. Bayesian analysis of correlated evolution of discrete characters by reversible‐jump Markov chain Monte Carlo. Am. Nat. 167, 808–825 (2006).
Barbeitos, M. S., Romano, S. L. & Lasker, H. R. Repeated loss of coloniality and symbiosis in scleractinian corals. Proc. Natl Acad. Sci. USA 107, 11877–11882 (2010).
We thank B. Carlson for invaluable feedback on an earlier draft of this manuscript. We are also grateful to the BBS and the countless volunteers that participate annually in this yearly survey. Bayesian analyses were run in the Washington University Center for High Performance Computing (CHPC), which is partially funded by NIH grants 1S10RR022984-01A1 and 1S10OD018091-01. We thank M. Tobias for his helpful advice on HPC.
The authors declare no competing financial interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Supplementary Tables 1–3, Supplementary Figures 1–3
Data for 126 species used in population analyses. Variable descriptions can be found in the methods section of the manuscript.
Data for 2,062 species used in estimating relative brain sizes, including 1,288 species included in global evolutionary analyses. Variable descriptions can be found in the methods section of the manuscript.
About this article
Cite this article
Fristoe, T.S., Iwaniuk, A.N. & Botero, C.A. Big brains stabilize populations and facilitate colonization of variable habitats in birds. Nat Ecol Evol 1, 1706–1715 (2017). https://doi.org/10.1038/s41559-017-0316-2
Animal Cognition (2021)
Modification of the third phase in the framework for vertebrate species persistence in urban mosaic environments
Nature Ecology & Evolution (2020)
Scientific Reports (2020)
Biological Invasions (2020)