Biological Theory

, Volume 2, Issue 3, pp 250–262 | Cite as

Niche Construction and Cognitive Evolution



Despite the fact that animal behavior involves a particularly powerful form of niche construction, few researchers have considered how the environmental impact of behavior may feed back to influence the evolution of the cognitive underpinnings of behavior. I explore a model that explicitly incorporates niche construction while tracking cognitive evolution. Agents and their stimuli are modeled as coevolving populations. The agents are born with “weights” attached to behaviors in a repertoire. Further, these agents are able to change these weights based on previous success and an inherited learning parameter. Both the agent and the stimulus receive payoffs through a behavioral interaction (where the payoff structure is influenced by the “genotype” of the stimulus). The behaving agent exhibits niche construction through its effects on stimuli (the “environment”), which can feed back to influence the value of different cognitive strategies. Here I focus on two forms of niche construction: (1) the stimulus and responding agent have common interests (positive niche construction) and (2) the stimulus and agent have dissimilar interests (negative niche construction). The form of niche construction qualitatively affects cognitive evolution (i.e., the initial behavioral probability distribution and the value of the learning parameter). Given a mutualism between the stimulus and responding agent, rapid learning and “fixed” behavioral distributions (i.e., most of the weight on a single behavior) evolve. Given an antagonism between the stimulus and agent, slower learning and “flexible” behavioral distributions (i.e., equal weight on different behaviors) evolve. I discuss these results in light of findings from the fields of ethology, psychology, and evolutionary ecology.


antagonism Baldwin effect coevolution feedback Goldilocks principle innate behavior Law of Effect learning mutualism niche construction 


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  1. Ancel LW (1999) A quantitative model of the Simpson-Baldwin effect. Journal of Theoretical Biology 196: 197–209.CrossRefGoogle Scholar
  2. Ancel LW (2000) Undermining the Baldwin expediting effect: Does phenotypic plasticity accelerate evolution? Theoretical Population Biology 58: 307–319.CrossRefGoogle Scholar
  3. Arnold SJ (1978) Evolution of a special class of modifiable behaviors in relation to environmental pattern. American Naturalist 112: 415–427.CrossRefGoogle Scholar
  4. Baldwin JM (1896) A new factor in evolution. American Naturalist 30: 441–451.CrossRefGoogle Scholar
  5. Bergman A, Feldman MW (1995) On the evolution of learning: Representation of a stochastic environment. Theoretical Population Biology 48: 251–276.CrossRefGoogle Scholar
  6. Bond AB, Kamil AC (2002) Visual predators select for crypticity and polymorphism in virtual prey. Nature 415: 609–613.CrossRefGoogle Scholar
  7. Boni MF, Feldman MW (2005) Evolution of antibiotic resistance by human and bacterial niche construction. Evolution 59: 477–491.Google Scholar
  8. Bush RR, Mosteller F (1955) Stochastic Models for Learning. New York: Wiley.CrossRefGoogle Scholar
  9. Dukas R (1998) Evolutionary ecology of learning. In: Cognitive Ecology: The Evolutionary Ecology of Information Processing and Decision Making (Dukas R, ed), 129–174. Chicago: University of Chicago Press.Google Scholar
  10. Edwards TC (1989) Similarity in the development of foraging mechanics among sibling ospreys. Condor 91: 30–36.CrossRefGoogle Scholar
  11. Feldman MW, Aoki K, Kumm J (1996) Individual versus social learning: Evolutionary analysis in a fluctuating environment. Anthropological Science 104: 209–232.CrossRefGoogle Scholar
  12. Godfrey-Smith P (1998) Complexity and the Function of Mind in Nature. Cambridge: Cambridge University Press.Google Scholar
  13. Gould JG, Marler P (1987) Learning by instinct. Scientific American 256: 74–85.CrossRefGoogle Scholar
  14. Hinton GE, Nowlan SJ (1987) How learning can guide evolution. Complex Systems 1: 495–502.Google Scholar
  15. Johnston TD (1982) Selective costs and benefits in the evolution of learning. Advances in the Study of Behavior 12: 65–106.CrossRefGoogle Scholar
  16. Kerr B (2007) The ecological and evolutionary dynamics of model bacteriocin communities. In: Bacteriocins: Ecology and Evolution (Riley MA, Chavan MA, eds), 111–134. Berlin: Springer.CrossRefGoogle Scholar
  17. Kerr B, Feldman MW (2003) Carving the cognitive niche: Optimal learning strategies in homogeneous and heterogeneous environments. Journal of Theoretical Biology 220: 169–188.CrossRefGoogle Scholar
  18. Kerr B, Riley MA, Feldman MW, Bohannan BJM (2002) Local dispersal promotes biodiversity in a real-life game of rock-paper-scissors. Nature 418: 171–174.CrossRefGoogle Scholar
  19. Kerr B, Schwilk DW, Bergman A, Feldman MW (1999) Rekindling an old flame: A haploid model for the evolution and impact of flammability in resprouting plants. Evolutionary Ecology Research 1: 807–833.Google Scholar
  20. Laland KN, Odling-Smee FJ, Feldman MW (1996) The evolutionary consequences of niche construction: A theoretical investigation using two-locus theory. Journal of Evolutionary Biology 9: 293–316.CrossRefGoogle Scholar
  21. Laland KN, Odling-Smee FJ, Feldman MW (1999) Evolutionary consequences of niche construction and their implications for ecology. Proceedings of the National Academy of Sciences of the USA 96: 10242–10247.CrossRefGoogle Scholar
  22. Laland KN, Sterelny K (2006) Seven reasons (not) to neglect niche construction. Evolution 60: 1751–1762.CrossRefGoogle Scholar
  23. Lewontin RC (1978) Adaptation. Scientific American 239 (3): 156–169.CrossRefGoogle Scholar
  24. Lewontin RC (1982) Organism and environment. In: Learning, Development and Culture (Plotkin HC, ed), 151–170. New York: Wiley.Google Scholar
  25. Lewontin RC (1983) Gene, organism and environment. In: Evolution from Molecules to Men (Bendall DS, ed), 273–285. Cambridge: Cambridge University Press.Google Scholar
  26. Lloyd JE (1965) Aggressive mimicry in Photuris: Firefly femmes fatales. Science 149: 653–654.CrossRefGoogle Scholar
  27. Lorenz K, Tinbergen N (1970) Taxis and instinctive behavior pattern in egg-rolling by the Graylag goose. In: Lorenz K, Studies in Animal and Human Behaviour, vol. 1, 316–350. Cambridge, MA: Harvard University Press. German orig. 1938.CrossRefGoogle Scholar
  28. Mameli M, Bateson P (2006) Innateness and the sciences. Biology and Philosophy 21: 155–188.CrossRefGoogle Scholar
  29. Mery F, Kawecki TJ (2002) Experimental evolution of learning ability in fruit flies. Proceedings of the National Academy of Sciences of the USA 99: 14274–14279.CrossRefGoogle Scholar
  30. Mery F, Kawecki TJ (2004) The effect of learning on experimental evolution of resource preference in Drosophila melanogaster. Evolution 58: 757–767.CrossRefGoogle Scholar
  31. Michaelidis CI, Demary KC, Lewis SM (2006) Male courtship signals and female signal assessment in Photinus greeni fireflies. Behavioral Ecology 17: 329–335.CrossRefGoogle Scholar
  32. Odling-Smee FJ, Laland KN, Feldman MW (1996) Niche construction. American Naturalist 147: 641–648.CrossRefGoogle Scholar
  33. Odling-Smee FJ, Laland KN, Feldman MW (2003) Niche Construction: The Neglected Process in Evolution. Princeton, NJ: Princeton University Press.Google Scholar
  34. Papaj DR (1994) Optimizing learning and its effect on evolutionary change in behavior. In: Behavioral Mechanisms in Evolutionary Ecology (Real LA, ed), 133–153. Chicago: University of Chicago Press.Google Scholar
  35. Plotkin HC, Odling-Smee FJ (1979) Learning, change and evolution: Inquiry into the teleonomy of learning. Advances in the Study of Behavior 10: 1–41.CrossRefGoogle Scholar
  36. Schwilk DW (2003) Flammability is a niche construction trait: Canopy architecture affects fire intensity. American Naturalist 162: 725–733.CrossRefGoogle Scholar
  37. Schwilk DW, Kerr B (2002) Genetic niche-hiking: An alternative explanation for the evolution of flammability. Oikos 99: 431–442.CrossRefGoogle Scholar
  38. Stephens DW (1987) On economically tracking a variable environment. Theoretical Population Biology 32: 15–25.CrossRefGoogle Scholar
  39. Stephens DW (1991) Change, regularity, and value in the evolution of animal learning. Behavioral Ecology 2: 77–89.CrossRefGoogle Scholar
  40. Sterelny K (2003) Thought in a Hostile World: The Evolution of Human Cognition. Malden, MA: Blackwell.Google Scholar
  41. Thorndike EL (2000) Animal Intelligence: Experimental Studies. New Brunswick: Transaction. Orig. 1911.Google Scholar
  42. Tinbergen N (1989) The Study of Instinct. Oxford: Oxford University Press.Google Scholar
  43. Tolman EC (1948) Cognitive maps in rats and men. Psychological Review 55: 189–208.CrossRefGoogle Scholar
  44. Turner JS (2000) The Extended Organism: The Physiology of Animal-Built Structures. Cambridge, MA: Harvard University Press.Google Scholar

Copyright information

© Konrad Lorenz Institute for Evolution and Cognition Research 2008

Authors and Affiliations

  1. 1.Department of BiologyUniversity of WashingtonSeattleUSA

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