Evaluating costs of heavy metal tolerance in a widely distributed, invasive butterfly.

Organismal tolerance to environmental pollution is thought to be constrained by fitness costs, where variants with higher survival in polluted environments have lower performance in nonpolluted environments. Yet, costs are not always detected in empirical studies. One hypothesis suggests that whether tolerance costs emerge depends on the degree of heterogeneity populations experience with respect to pollution exposure. For instance, in populations confined to local environments where pollution is persistent, selection may favour alleles that enhance pollution tolerance but reduce performance in nonpolluted environments (costs). However, in broadly distributed populations that undergo selection in both polluted and nonpolluted patches, costs should be eroded. Understanding tolerance costs in broadly distributed populations is relevant to management of invasive species, which are highly dispersive, wide ranging, and often colonize disturbed or polluted patches such as agricultural monocultures. Therefore, we conducted a case study quantifying costs of tolerance to zinc pollution (a common heavy metal pollutant) in wild cabbage white butterflies (Pieris rapae). This wide ranging, highly dispersive and invasive pest periodically encounters metal pollution by consuming plants in urban and agricultural settings. In contrast to expected costs of tolerance, we found that cabbage white families with greater zinc tolerance also produced more eggs and had higher reproductive effort under nonpolluted conditions. These results contribute to a more general hypothesis of why costs of pollution tolerance vary across studies: patchy selection with pollutants should erode costs and may favour genotypes that perform well under both polluted and nonpolluted conditions. This might partly explain why widely distributed invasive species are able to thrive in diverse, polluted and nonpolluted habitats.

Selective processes in development: implications for the costs and benefits of phenotypic plasticity.

Adaptive phenotypic plasticity, the ability of a genotype to develop a phenotype appropriate to the local environment, allows organisms to cope with environmental variation and has implications for predicting how organisms will respond to rapid, human-induced environmental change. This review focuses on the importance of developmental selection, broadly defined as a developmental process that involves the sampling of a range of phenotypes and feedback from the environment reinforcing high-performing phenotypes. I hypothesize that understanding the degree to which developmental selection underlies plasticity is key to predicting the costs, benefits, and consequences of plasticity. First, I review examples that illustrate that elements of developmental selection are common across the development of many different traits, from physiology and immunity to circulation and behavior. Second, I argue that developmental selection, relative to a fixed strategy or determinate (switch) mechanisms of plasticity, increases the probability that an individual will develop a phenotype best matched to the local environment. However, the exploration and environmental feedback associated with developmental selection is costly in terms of time, energy, and predation risk, resulting in major changes in life history such as increased duration of development and greater investment in individual offspring. Third, I discuss implications of developmental selection as a mechanism of plasticity, from predicting adaptive responses to novel environments to understanding conditions under which genetic assimilation may fuel diversification. Finally, I outline exciting areas of future research, in particular exploring costs of selective processes in the development of traits outside of behavior and modeling developmental selection and evolution in novel environments.

Toward a population genetic framework of developmental evolution: the costs, limits, and consequences of phenotypic plasticity.

Adaptive phenotypic plasticity allows organisms to cope with environmental variability, and yet, despite its adaptive significance, phenotypic plasticity is neither ubiquitous nor infinite. In this review, we merge developmental and population genetic perspectives to explore costs and limits on the evolution of plasticity. Specifically, we focus on the role of modularity in developmental genetic networks as a mechanism underlying phenotypic plasticity, and apply to it lessons learned from population genetic theory on the interplay between relaxed selection and mutation accumulation. We argue that the environmental specificity of gene expression and the associated reduction in pleiotropic constraints drive a fundamental tradeoff between the range of plasticity that can be accommodated and mutation accumulation in alternative developmental networks. This tradeoff has broad implications for understanding the origin and maintenance of plasticity and may contribute to a better understanding of the role of plasticity in the origin, diversification, and loss of phenotypic diversity.

Brain size: a global or induced cost of learning?

The role of brain size as a cost of learning remains enigmatic; the nature and timing of such costs is particularly uncertain. On one hand, comparative studies suggest that congenitally large brains promote better learning and memory. In that case, brain size exacts a global cost that accrues even if learning does not take place; on the other hand, some developmental studies suggest that brains grow with experience, indicating a cost that is induced when learning occurs. The issue of how costs are incurred is an important one, because global costs are expected to constrain the evolution of learning more than would induced costs. We tested whether brain size represented a global and/or an induced cost of learning in the cabbage white butterfly, Pieris rapae. We assayed the ability of full sibling families to learn to locate either green hosts, for which butterflies have an innate search bias, or red hosts, which are more difficult to learn to locate. Naïve butterflies were sacrificed at emergence and congenital brain volume estimated as a measure of global costs; experienced butterflies were sacrificed after learning and change in brain volume estimated as a measure of induced costs. Only for the mushroom body, a brain region involved in learning and memory in other insects, was volume at emergence related to learning or host-finding. Butterfly families that emerged with relatively larger mushroom bodies showed a greater tendency to improve their ability to find red hosts across the two days of host-search. The volume of most brain regions increased with time in a manner suggesting host experience itself was important: first, total number of landings during host-search was positively related to mushroom body calyx volume, and, second, experience with the red host was positively related to mushroom body lobe volume. At the family level, the relative volume of the mushroom body calyx and antennal lobes following learning was positively related to overall success in finding red hosts. Overall, our results suggest that within species, brain size might act as a small global cost of learning, but that environment-specific changes in brain size might reduce the overall costs of neural tissue in the evolution of learning.