Big City Living: A Global Meta-Analysis Reveals Positive Impact of Urbanization on Body Size in Lizards

2020 
Urban environments pose different selective pressures than natural ones, leading to changes in animal behavior, physiology, and morphology. Understanding how animals respond to urbanization could inform the management of urban habitats. Non-avian reptiles have important roles in ecosystems worldwide, yet their responses to urbanization have not been as comprehensively studied as those of mammals and birds. However, unlike mammals and birds, most reptiles cannot easily move away from disturbances, making the selective pressure to adapt to urban environments especially strong. In recent years, there has been a surge in research on the responses of lizards to urbanization, yet no formal synthesis has determined what makes an urban lizard, in other words, which phenotypic traits are most likely to change with urbanization and in which direction? Here, we present a qualitative synthesis of the literature and a quantitative phylogenetic meta-analysis comparing phenotypic traits between urban and non-urban lizard populations. The most robust finding from our analysis is that urban lizards are larger than their non-urban counterparts. This result remained consistent between sexes and taxonomic groups. Hence, lizards that pass through the urban filter have access to better resources, more time for foraging, and/or there is selection on attaining a larger body size. Other results included an increase in the diameters of perches used and longer limb and digit lengths, although this may be a result of increased body size. Urban lizards were not bolder, more active or exploratory, and did not differ in immune responses than non-urban populations. Overall, studies are biased to a few geographic regions and taxa. More than 70% of all data came from three species of anoles in the family Dactyloidae, making it difficult to generalize patterns to other clades. Thus, more studies are needed across multiple taxa and habitats to produce meaningful predictions that could help inform conservation and management of urban ecological communities.
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