Landscapes, Learning Costs, and Genetic Assimilation

Mayley, Giles

doi:10.1162/evco.1996.4.3.213

Cited by 140 publications

(116 citation statements)

References 5 publications

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“…In contrast, a simulation model by Hinton and Nowlan (1987;see also Maynard Smith 1987) suggests that in a novel environment learning may accelerate the evolution of the innate component towards the optimum. A similar prediction has been obtained in artificial intelligence models (Belew 1989;Ackley and Littman 1991;French and Messinger 1994;Mayley 1996). These models provide some formal underpinning for the old (and vague) verbal arguments that learning (or more generally phenotypic plasticity) may accelerate evolution by allowing the population to explore greater ''phenotypic space,'' an idea known as the Baldwin effect (Baldwin 1896;Morgan 1896;Osborn 1896).…”

supporting

confidence: 58%

“…On the other hand, gaining experience is often costly and error-prone (Laverty and Plowright 1988;Sullivan 1988). The energy spent on information processing and the maintenance of underlying structures may also entail fitness costs (for reviews see Johnston 1982;Mayley 1996). Finally, alleles improving learning ability may have deleterious pleiotropic effects on other fitness-related traits (Mery and Kawecki 2003).…”

mentioning

confidence: 99%

“…This idea is conceptually related to genetic assimilation and received renewed interest from evolutionary biologists in the context of the role of phenotype in evolution (for review see Pigliucci and Murren 2003). Although some models (French and Messinger 1994;Mayley 1996, Ancel 2000 predicted that learning may both accelerate and slow down evolution depending on the assumptions about the constraints on learning and fitness, at the empirical level the controversy remains unresolved: these contradictory predictions have not been addressed experimentally.…”

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confidence: 99%

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The Effect of Learning on Experimental Evolution of Resource Preference in Drosophila Melanogaster

Mery

Kawecki

2004

Evol

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Abstract. Learning is thought to be adaptive in variable environments, whereas constant, predictable environments are supposed to favor unconditional, genetically fixed responses. A dichotomous view of behavior as either learned or innate ignores a potential evolutionary interaction between the learned and innate components of a behavioral response. We addressed this interaction in the context of oviposition substrate choice in Drosophila melanogaster, asking two main questions. First, will learning also evolve in a constant environment in which it always pays to show the same choice? Second, how does an opportunity to learn affect the evolution of the innate (genetic) component of oviposition substrate choice? We exposed experimental populations to four selection regimes, involving selection on oviposition substrate preference (an orange versus a pineapple medium). In two selection regimes the flies were selected for preference either for the orange medium, or for the pineapple medium. In the remaining two selection regimes the flies were also selected for preference for either orange or pineapple, but additionally could use past experience (aversion learning) to decide which medium it paid to avoid. Lines exposed to the latter selection regimes evolved improved learning ability, indicating that learning may be advantageous even if the same behavioral response is favored every generation. Furthermore, of the two selection regimes that favored oviposition on the pineapple medium, the regime that allowed for learning led to the evolution of a stronger innate preference for pineapple, than the regime that did not allow for learning. In contrast, of the two regimes that selected for oviposition on the orange medium, the one that allowed for learning led to a smaller evolutionary change of the innate preference. Thus, an opportunity to learn facilitated the evolution of innate preference under selection for preference for pineapple, but hindered it under selection for preference for orange. We discuss possible mechanisms for this effect. Behavioral responses of an animal reflect an interplay between an innate and a learned component (by innate we mean the heritable component, which determines the behavior of a naive individual). The innate, genetic component reflects the evolutionary history of the population. The learned component reflects experience accumulated within the individual's lifetime. The ability to modify behavior based on experience (i.e., learning ability) is itself a product of evolution, with notable genetic differences between related species or even conspecific populations (Gould-Beierle and Kamil 1998;Girvan and Braithwaite 1998;Jackson and Carter 2001). It is usually argued that learning is advantageous in variable environments, that is, when the fitness consequences of a given behavioral action change from generation to generation, or even within an individual's life span (for reviews see Johnston 1982; Stephens 1991; Dukas 1998). (Obviously, for learning to be useful the environment must not c...

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confidence: 58%

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confidence: 99%

mentioning

confidence: 99%

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The Effect of Learning on Experimental Evolution of Resource Preference in Drosophila Melanogaster

Mery

Kawecki

2004

Evol

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“…Once the new population is established, and if the new conditions remain consistent from one generation to the next, evolutionary theory predicts the loss of plasticity and the evolution of a canalised phenotype (that is, genetic assimilation; Waddington, 1961;Schlichting and Pigliucci, 1998;West-Eberhard, 2003); that is because adaptive plastic responses are both costly and limited (that is, plastic phenotypes are sub-optimal by definition; Behera, 1994;Mayley, 1996;Relyea, 2002;Steinger et al, 2003;Snell-Rood et al, 2010). Although the potential importance of genetic assimilation to evolutionary changes in founder populations has been theoretically demonstrated (Behera, 1994;Rollo, 1994;Mayley, 1996;Schlichting and Pigliucci, 1998;Pigliucci and Murren, 2003;Price et al, 2003;West-Eberhard, 2003;Schlichting, 2004;Badyaev, 2005;Lande, 2009), empirical evidence on this topic is rare. Perhaps for this very reason, it was suggested that genetic assimilation only has a minor role in evolution (de Jong, 2005).…”

Section: Introductionmentioning

confidence: 99%

Island colonisation and the evolutionary rates of body size in insular neonate snakes

Aubret

2014

Heredity

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Island colonisation by animal populations is often associated with dramatic shifts in body size. However, little is known about the rates at which these evolutionary shifts occur, under what precise selective pressures and the putative role played by adaptive plasticity on driving such changes. Isolation time played a significant role in the evolution of body size in island Tiger snake populations, where adaptive phenotypic plasticity followed by genetic assimilation fine-tuned neonate body and head size (hence swallowing performance) to prey size. Here I show that in long isolated islands (46000 years old) and mainland populations, neonate body mass and snout-vent length are tightly correlated with the average prey body mass available at each site. Regression line equations were used to calculate body size values to match prey size in four recently isolated populations of Tiger snakes. Rates of evolution in body mass and snout-vent length, calculated for seven island snake populations, were significantly correlated with isolation time. Finally, rates of evolution in body mass per generation were significantly correlated with levels of plasticity in head growth rates. This study shows that body size evolution occurs at a faster pace in recently isolated populations and suggests that the level of adaptive plasticity for swallowing abilities may correlate with rates of body mass evolution. I hypothesise that, in the early stages of colonisation, adaptive plasticity and directional selection may combine and generate accelerated evolution towards an 'optimal' phenotype.

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“…Another virtue of evolutionary simulations is that, like models in artificial intelligence, they force their creator to be explicit in every detail. Consider the work of Mayley (1996) on the Baldwin effect-this effect is very close to the concerns of the target article as it involves an interaction between learning and genetic evolution. Mayley uses an evolutionary simulation to demonstrate that the conditions under which the Baldwin effect will result in the genetic fixation of a learned trait are not straightforward.…”

Section: Commentarymentioning

confidence: 99%

Evolutionary simulation modelling clarifies interactions between parallel adaptive processes

Bullock

Noble

2000

Behav. Brain Sci.

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The teleological language in the target article is ill-advised, as it obscures the question of whether ecological and cultural inheritances are directed or random. The authors present a very broad palette of explanatory possibilities; evolutionary simulation models could help narrow down the processes important in a particular case. Examples of such models are offered in the areas of language change and the Baldwin effect. CommentaryThe central theoretical message of the target article is that, through modifying their environment, organisms affect the selection pressures acting on them.The extent to which previous students of evolution have been unaware of this interaction is debatable; for example, orthodox models of coevolution address changes in selection pressure brought about by the evolution of new traits.The novel contribution made in this article is simply to note that, to the extent that these new traits affect the environment, they may have additional effects on selection which may persist for longer than the lifetime of an individual organism. Nevertheless, the authors are to be commended for 1 outlining a theoretical framework that makes these matters explicit.We were somewhat alarmed by the authors' pervasive use of teleological language in describing the processes of "niche construction". Whilst evolution is clearly an undirected process, and ontogenetic development (including learning) is equally clearly goal-directed, the status of some nascent, intermediate adaptive level is far less straightforward. In their use of terms such as "counteractive niche construction", do the authors mean to suggest that cultural or ecological inheritance should be considered to be purposive after the fashion of individual learning? If so, must there have been natural selection for the ability to construct niches in the same way that there has been natural selection for the ability to learn? The issue is not merely a linguistic one, since we know that very different dynamics are to be expected from directed as opposed to non-directed adaptive systems. Consider that, since mutations in general are deleterious, niches constructed due to genetic mutation (e.g., web building by spiders) will be rare success stories among many failures. However, since the fitness consequences of novel learned behaviours may be distributed very differently to those of genetic mutations, and will depend on the specific learning mechanism involved, the success rate of niches constructed through learning (e.g., the learned use of a grubbing tool by woodpecker finches) will differ accordingly.The interaction between genetic evolution, learning, and intervening adaptive processes will turn on specific facts about genetic constraints, learning biases, and the environment of the organisms involved. Although we appreciate the value of the target article in introducing such a wide range of explanatory possibilities, individual cases demand individual explanations. A move in this direction has been achieved by the emerging field of evolutio...

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Landscapes, Learning Costs, and Genetic Assimilation

Cited by 140 publications

References 5 publications

The Effect of Learning on Experimental Evolution of Resource Preference in Drosophila Melanogaster

The Effect of Learning on Experimental Evolution of Resource Preference in Drosophila Melanogaster

Island colonisation and the evolutionary rates of body size in insular neonate snakes

Evolutionary simulation modelling clarifies interactions between parallel adaptive processes

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