DOES ENVIRONMENTAL ROBUSTNESS PLAY A ROLE IN FLUCTUATING ENVIRONMENTS?

Fluctuating environments are expected to select for individuals that have highest geometric fitness over the experienced environments. This leads to the prediction that genetically determined environmental robustness in fitness, and average fitness across environments should be positively genetically correlated to fitness in fluctuating environments. Because quantitative genetic experiments resolving these predictions are missing, we used a full‐sib, half‐sib breeding design to estimate genetic variance for egg‐to‐adult viability in Drosophila melanogaster exposed to two constant or fluctuating temperatures that were above the species’ optimum temperature, during development. Viability in two constant environments (25°C or 30°C) was used to estimate breeding values for environmental robustness of viability (i.e., reaction norm slope) and overall viability (reaction norm elevation). These breeding values were regressed against breeding values of viability at two different fluctuating temperatures (with a mean of 25°C or 30°C). Our results based on genetic correlations show that average egg‐to‐adult viability across different constant thermal environments, and not the environmental robustness, was the most important factor for explaining the fitness in fluctuating thermal environments. Our results suggest that the role of environmental robustness in adapting to fluctuating environments might be smaller than anticipated.     

Do mites evolving in alternating host plants adapt to host switch?

A fluctuating environment may be perceived as a composition of different environments, or as an environment per se, in which it is the fluctuation itself that poses a selection pressure. If so, then organisms may adapt to this alternation. We tested this using experimental populations of spider mites that have been evolving for 45 generations in a homogeneous environment (pepper or tomato plants), or in a heterogeneous environment composed of an alternation of these two plants approximately at each generation. The performance (daily oviposition rate and juvenile survival) of individuals from these populations was tested in each of the homogeneous environments, and in two alternating environments, one every 3 days and the other between generations. To discriminate between potential genetic interactions between alleles conferring adaptation to each host plant and environmental effects of evolving in a fluctuating environment, we compared the performance of all lines with that of a cross between tomato and pepper lines. As a control, two lines within each selection regime were also crossed. We found that crosses between alternating lines and between pepper and tomato lines performed worse than crosses between lines evolving in homogeneous environments when tested in that environment. In contrast, alternating lines performed either better or similarly to lines evolving in homogeneous environments when tested in a fluctuating environment. Our results suggest that fluctuating environments are more than the juxtaposition of two environments. Hence, tests for adaptation of organisms evolving in such environments should be carried out in fluctuating conditions.     

EVOLUTION OF GENERALISTS AND SPECIALISTS IN SPATIALLY HETEROGENEOUS ENVIRONMENTS

Quantitative genetic models are used to investigate the evolution of generalists and specialists in a coarse-grained environment with two habitat types when there are costs attached to being a generalist. The outcomes for soft and hard selection models are qualitatively different. Under soft selection (e.g., for juvenile or male-reproductive traits) the population evolves towards the single peak in the adaptive landscape. At equilibrium, the population mean phenotype is a compromise between the reaction that would be optimal in both habitats and the reaction with the lowest cost. Furthermore, the equilibrium is closer to the optimal phenotype in the most frequent habitat, or the habitat in which selection on the focal trait is stronger. A specialist genotype always has a lower fitness than a generalist, even when the costs are high. In contrast, under hard selection (e.g., for adult or female-reproductive traits) the adaptive landscape can have one, two, or three peaks; a peak represents a population specialized to one habitat, equally adapted to both habitats, or an intermediate. One peak is always found when the reaction with the lowest cost is not much different from the optimal reaction, and this situation is similar to the soft selection case. However, multiple peaks are present when the costs become higher, and the course of evolution is then determined by initial conditions, and the region of attraction of each peak. This implies that the evolution of specialization and phenotypic plasticity may not only depend on selection regimes within habitats, but also on contingent, historical events (migration, mutation). Furthermore, the evolutionary dynamics in changing environments can be widely different for populations under hard and soft selection. Approaches to measure costs in natural and experimental populations are discussed.     

Why does the magnitude of genotype‐by‐environment interaction vary?

Genotype‐by‐environment interaction (G × E), that is, genetic variation in phenotypic plasticity, is a central concept in ecology and evolutionary biology. G×E has wide‐ranging implications for trait development and for understanding how organisms will respond to environmental change. Although G × E has been extensively documented, its presence and magnitude vary dramatically across populations and traits. Despite this, we still know little about why G × E is so evident in some traits and populations, but minimal or absent in others. To encourage synthetic research in this area, we review diverse hypotheses for the underlying biological causes of variation in G × E. We extract common themes from these hypotheses to develop a more synthetic understanding of variation in G × E and suggest some important next steps.     

The role of migration in the evolution of phenotypic switching

Stochastic switching is an example of phenotypic bet hedging, where an individual can switch between different phenotypic states in a fluctuating environment. Although the evolution of stochastic switching has been studied when the environment varies temporally, there has been little theoretical work on the evolution of phenotypic switching under both spatially and temporally fluctuating selection pressures. Here, we explore the interaction of temporal and spatial change in determining the evolutionary dynamics of phenotypic switching. We find that spatial variation in selection is important; when selection pressures are similar across space, migration can decrease the rate of switching, but when selection pressures differ spatially, increasing migration between demes can facilitate the evolution of higher rates of switching. These results may help explain the diverse array of non-genetic contributions to phenotypic variability and phenotypic inheritance observed in both wild and experimental populations.     

Selection in a fluctuating environment leads to decreased genetic variation and facilitates the evolution of phenotypic plasticity

Changes in the environment are expected to induce changes in the quantitative genetic variation, which influences the ability of a population to adapt to environmental change. Furthermore, environmental changes are not constant in time, but fluctuate. Here, we investigate the effect of rapid, continuous and/or fluctuating temperature changes in the seed beetle Callosobruchus maculatus, using an evolution experiment followed by a split-brood experiment. In line with expectations, individuals responded in a plastic way and had an overall higher potential to respond to selection after a rapid change in the environment. After selection in an environment with increasing temperature, plasticity remained unchanged (or decreased) and environmental variation decreased, especially when fluctuations were added; these results were unexpected. As expected, the genetic variation decreased after fluctuating selection. Our results suggest that fluctuations in the environment have major impact on the response of a population to environmental change; in a highly variable environment with low predictability, a plastic response might not be beneficial and the response is genetically and environmentally canalized resulting in a low potential to respond to selection and low environmental sensitivity. Interestingly, we found greater variation for phenotypic plasticity after selection, suggesting that the potential for plasticity to evolve is facilitated after exposure to environmental fluctuations. Our study highlights that environmental fluctuations should be considered when investigating the response of a population to environmental change.     

Adapt or disperse: understanding species persistence in a changing world

The majority of studies on environmental change focus on the response of single species and neglect fundamental biotic interactions, such as mutualism, competition, predation, and parasitism, which complicate patterns of species persistence. Under global warming, disruption of community interactions can arise when species differ in their sensitivity to rising temperature, leading to mismatched phenologies and/or dispersal patterns. To study species persistence under global climate change, it is critical to consider the ecology and evolution of multispecies interactions; however, the sheer number of potential interactions makes a full study of all interactions unfeasible. One mechanistic approach to solving the problem of complicated community context to global change is to (i) define strategy groups of species based on life‐history traits, trophic position, or location in the ecosystem, (ii) identify species involved in key interactions within these groups, and (iii) determine from the interactions of these key species which traits to study in order to understand the response to global warming. We review the importance of multispecies interactions looking at two trait categories: thermal sensitivity of metabolic rate and associated life‐history traits and dispersal traits of species. A survey of published literature shows pronounced and consistent differences among trophic groups in thermal sensitivity of life‐history traits and in dispersal distances. Our approach increases the feasibility of unraveling such a large and diverse set of community interactions, with the ultimate goal of improving our understanding of community responses to global warming.     

The genetics of phenotypic plasticity. III. Genetic correlations and fluctuating asymmetries

We examined the relationship of three aspects of development, phenotypic plasticity, genetic correlations among traits, and developmental noise, for thorax length, wing length, and number of sternopleural bristles in Drosophila melanogaster. We used 14 lines which had previously been selected on either thorax length or plasticity of thorax length in response to temperature. A half-sib mating design was used and offspring were raised at 19° C or 25° C. We found that genetic correlations were stable across temperatures despite the large levels of plasticity of these traits. Plasticities were correlated among developmentally related traits, thorax and wing length, but not among unrelated traits, lengths and bristle counts. Amount of developmental noise, measured as fluctuating asymmetry and within-environmental variation, was positively correlated with amount of plasticity only for some traits, thorax length and bristle number, and only at one temperature, 25° C.     

Inside the heads of David and Goliath: environmental effects on brain morphology among wild and growth-enhanced coho salmon Oncorhynchus kisutch

Transgenic and wild-type individual coho salmon Oncorhynchus kisutch were reared in hatchery and near-natural stream conditions and their brain and structure sizes were determined. Animals reared in the hatchery grew larger and developed larger brains, both absolutely and when controlling for body size. In both environments, transgenics developed relatively smaller brains than wild types. Further, the volume of the optic tectum of both genotypes was larger in the hatchery animals and the cerebellum of transgenics was smaller when reared in near-natural streams. Finally, wild types developed a markedly smaller telencephalon under hatchery conditions. It is concluded that, apart from the environment, genetic factors that modulate somatic growth rate also have a strong influence on brain size and structure.     

Evolution of adaptive phenotypic traits without positive Darwinian selection

Recent evidence suggests the frequent occurrence of a simple non-Darwinian (but non-Lamarckian) model for the evolution of adaptive phenotypic traits, here entitled the plasticity-relaxation-mutation (PRM) mechanism. This mechanism involves ancestral phenotypic plasticity followed by specialization in one alternative environment and thus the permanent expression of one alternative phenotype. Once this specialization occurs, purifying selection on the molecular basis of other phenotypes is relaxed. Finally, mutations that permanently eliminate the pathways leading to alternative phenotypes can be fixed by genetic drift. Although the generality of the PRM mechanism is at present unknown, I discuss evidence for its widespread occurrence, including the prevalence of exaptations in evolution, evidence that phenotypic plasticity has preceded adaptation in a number of taxa and evidence that adaptive traits have resulted from loss of alternative developmental pathways. The PRM mechanism can easily explain cases of explosive adaptive radiation, as well as recently reported cases of apparent adaptive evolution over ecological time.