Abstract:Abstract. Examples of convergent evolution suggest that natural selection can often produce predictable evolutionary outcomes. However, unique histories among species can lead to divergent evolution regardless of their shared selective pressures-and some contend that such historical contingencies produce the dominant features of evolution. A classic example of convergent evolution is the set of Anolis lizard ecomorphs of the Greater Antilles. On each of four islands, anole species partition the structural habi… Show more
“…The classical adaptive radiation studies on ecomorph divergence in Anolis lizards reveal strong, repeated, convergent evolution across island systems [Losos et al, 1998;Langerhans et al, 2006]. Interestingly, while Anolis ecomorphs have evolved many times independently, there is no parallel evolution between ecomorph and brain structure [Powell and Leal, 2012].…”
Section: Concerted and Mosaic Brain Evolution In Lizardsmentioning
is unclear. Here, we examined the volumes of the 6 major neural subdivisions across 14 species of the agamid lizard genus Ctenophorus (dragons). These species have diverged multiple times in behaviour, ecology, and body morphology, affording a unique opportunity to test neuroevolutionary models across species. We assigned each species to an ecomorph based on habitat use and refuge type, then used MRI to measure total and regional brain volume. We found evidence for both mosaic and concerted brain evolution in dragons: concerted brain evolution with respect to body size, and mosaic brain evolution with respect to ecomorph. Specifically, all brain subdivisions increase in volume relative to body size, yet the tectum and rhombencephalon also show opposite patterns of evolution with respect to ecomorph. Therefore, we find that both models of evolution are occurring simultaneously in the same structures in dragons, but are only detectable when examining particular drivers of selection. We show that the answer to the question of whether concerted or mosaic brain evolution is detected in a system can depend more on the type of selection measured than on the clade of animals studied.
AbstractThe brain plays a critical role in a wide variety of functions including behaviour, perception, motor control, and homeostatic maintenance. Each function can undergo different selective pressures over the course of evolution, and as selection acts on the outputs of brain function, it necessarily alters the structure of the brain. Two models have been proposed to explain the evolutionary patterns observed in brain morphology. The concerted brain evolution model posits that the brain evolves as a single unit and the evolution of different brain regions are coordinated. The mosaic brain evolution model posits that brain regions evolve independently of each other. It is now understood that both models are responsible for driving changes in brain morphology; however, which factors favour concerted or mosaic brain evolution
“…The classical adaptive radiation studies on ecomorph divergence in Anolis lizards reveal strong, repeated, convergent evolution across island systems [Losos et al, 1998;Langerhans et al, 2006]. Interestingly, while Anolis ecomorphs have evolved many times independently, there is no parallel evolution between ecomorph and brain structure [Powell and Leal, 2012].…”
Section: Concerted and Mosaic Brain Evolution In Lizardsmentioning
is unclear. Here, we examined the volumes of the 6 major neural subdivisions across 14 species of the agamid lizard genus Ctenophorus (dragons). These species have diverged multiple times in behaviour, ecology, and body morphology, affording a unique opportunity to test neuroevolutionary models across species. We assigned each species to an ecomorph based on habitat use and refuge type, then used MRI to measure total and regional brain volume. We found evidence for both mosaic and concerted brain evolution in dragons: concerted brain evolution with respect to body size, and mosaic brain evolution with respect to ecomorph. Specifically, all brain subdivisions increase in volume relative to body size, yet the tectum and rhombencephalon also show opposite patterns of evolution with respect to ecomorph. Therefore, we find that both models of evolution are occurring simultaneously in the same structures in dragons, but are only detectable when examining particular drivers of selection. We show that the answer to the question of whether concerted or mosaic brain evolution is detected in a system can depend more on the type of selection measured than on the clade of animals studied.
AbstractThe brain plays a critical role in a wide variety of functions including behaviour, perception, motor control, and homeostatic maintenance. Each function can undergo different selective pressures over the course of evolution, and as selection acts on the outputs of brain function, it necessarily alters the structure of the brain. Two models have been proposed to explain the evolutionary patterns observed in brain morphology. The concerted brain evolution model posits that the brain evolves as a single unit and the evolution of different brain regions are coordinated. The mosaic brain evolution model posits that brain regions evolve independently of each other. It is now understood that both models are responsible for driving changes in brain morphology; however, which factors favour concerted or mosaic brain evolution
“…Common patterns of repeated ( parallel or convergent) evolution of the same performance-environment relationships emphasise the role that selection plays in generating among-taxa variation in locomotor performance, and in the physiological, morphological and behavioural traits that determine performance (Taylor and McPhail, 1985;McGuigan et al, 2003;Langerhans and DeWitt, 2004;Langerhans et al, 2006;Dalziel et al, 2012;Franssen et al, 2013;Fu et al, 2013;da Silva et al, 2014;Haas et al, 2015;Nelson et al, 2015). Despite the adaptive significance of locomotion, how the variation in locomotion is generated among individuals within a population, which is what natural selection acts upon, is relatively poorly understood.…”
There is good evidence that natural selection drives the evolution of locomotor performance, but the processes that generate the among-individual variation for selection to act on are relatively poorly understood. We measured prolonged swimming performance, U crit , and morphology in a large cohort (n=461) of wild-type zebrafish (Danio rerio) at ∼6 months and again at ∼9 months. Using mixedmodel analyses to estimate repeatability as the intraclass correlation coefficient, we determined that U crit was significantly repeatable (r=0.55; 95% CI: 0.45-0.64). Performance differences between the sexes (males 12% faster than females) and changes with age (decreasing 0.07% per day) both contributed to variation in U crit and, therefore, the repeatability estimate. Accounting for mean differences between sexes within the model decreased the estimate of U crit repeatability to 21% below the naïve estimate, while fitting age in the models increased the estimate to 14% above the naïve estimate. Greater consideration of factors such as age and sex is therefore necessary for the interpretation of performance repeatability in wild populations. Body shape significantly predicted U crit in both sexes in both assays, with the morphology-performance relationship significantly repeatable at the population level. However, morphology was more strongly predicative of performance in older fish, suggesting a change in the contribution of morphology relative to other factors such as physiology and behaviour. The morphologyperformance relationship changed with age to a greater extent in males than females.
“…The ''evolution of similar features independently in different evolutionary lineages'' (Futuyma, 1998) has been found in many organismal phenotypes, from ecology, behavior, and morphology (Blackledge and Gillespie, 2004;Grenier and Greenberg, 2005;Langerhans et al, 2006;Melville et al, 2006;Moore and Willmer, 1997;Nevo, 1979;Wiens et al, 2006;Wittkopp et al, 2003) to genes, proteins, enzymes or enzyme active sites (Charnock et al, 2002;Chen et al, 1997;Govindarajan and Goldstein, 1996;Kornegay et al, 1994;Lawn et al, 1997;Mattevi et al, 1996). Virtually all current biology texts address this phenomenon (e.g., Campbell et al, 2003, p. 307;Freeman, 2005, p. 501;Starr and Taggart, 2004, p. 313).…”
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