Richard Gomulkiewicz

Adaptive phenotypic plasticity: consensus and controversy.

Phenotypic plasticity is an environmentally based change in the phenotype. Understanding the evolution of adaptive phenotypic plasticity has been hampered by dissenting opinions on the merits of different methods of description, on the underlying genetic mechanisms, and on the way that plasticity is affected by natural selection in a heterogeneous environment. During much of this debate, the authors of this article have held opposing views. Here, we attempt to lay out current issues and summarize the areas of consensus and controversy surrounding the evolution of plasticity and the reaction norm (the set of phenotypes produced by a genotype over a range of environments).

Quantitative genetics and the evolution of reaction norms

We extend methods of quantitative genetics to studies of the evolution of reaction norms defined over continuous environments. Our models consider both spatial variation (hard and soft selection) and temporal variation (within a generation and between generations). These different forms of environmental variation can produce different evolutionary trajectories even when they favor the same optimal reaction norm. When genetic constraints limit the types of evolutionary changes available to a reaction norm, different forms of environmental variation can also produce different evolutionary equilibria. The methods and models presented here provide a framework in which empiricists may determine whether a reaction norm is optimal and, if it is not, to evaluate hypotheses for why it is not.

Long‐distance gene flow and adaptation of forest trees to rapid climate change

Forest trees are the dominant species in many parts of the world and predicting how they might respond to climate change is a vital global concern. Trees are capable of long-distance gene flow, which can promote adaptive evolution in novel environments by increasing genetic variation for fitness. It is unclear, however, if this can compensate for maladaptive effects of gene flow and for the long-generation times of trees. We critically review data on the extent of long-distance gene flow and summarise theory that allows us to predict evolutionary responses of trees to climate change. Estimates of long-distance gene flow based both on direct observations and on genetic methods provide evidence that genes can move over spatial scales larger than habitat shifts predicted under climate change within one generation. Both theoretical and empirical data suggest that the positive effects of gene flow on adaptation may dominate in many instances. The balance of positive to negative consequences of gene flow may, however, differ for leading edge, core and rear sections of forest distributions. We propose future experimental and theoretical research that would better integrate dispersal biology with evolutionary quantitative genetics and improve predictions of tree responses to climate change.

Hot Spots, Cold Spots, and the Geographic Mosaic Theory of Coevolution

Species interactions commonly coevolve as complex geographic mosaics of populations shaped by differences in local selection and gene flow. We use a haploid matching‐alleles model for coevolution to evaluate how a pair of species coevolves when fitness interactions are reciprocal in some locations (“hot spots”) but not in others (“cold spots”). Our analyses consider mutualistic and antagonistic interspecific interactions and a variety of gene flow patterns between hot and cold spots. We found that hot and cold spots together with gene flow influence coevolutionary dynamics in four important ways. First, hot spots need not be ubiquitous to have a global influence on evolution, although rare hot spots will not have a disproportionate impact unless selection is relatively strong there. Second, asymmetries in gene flow can influence local adaptation, sometimes creating stable equilibria at which species experience minimal fitness in hot spots and maximal fitness in cold spots, or vice versa. Third, asymmetries in gene flow are no more important than asymmetries in population regulation for determining the maintenance of local polymorphisms through coevolution. Fourth, intraspecific allele frequency differences among hot and cold spot populations evolve under some, but not all, conditions. That is, selection mosaics are indeed capable of producing spatially variable coevolutionary outcomes across the landscapes over which species interact. Altogether, our analyses indicate that coevolutionary trajectories can be strongly shaped by the geographic distribution of coevolutionary hot and cold spots, and by the pattern of gene flow among populations.

The evolutionary ecology of metacommunities.

Research on the interactions between evolutionary and ecological dynamics has largely focused on local spatial scales and on relatively simple ecological communities. However, recent work demonstrates that dispersal can drastically alter the interplay between ecological and evolutionary dynamics, often in unexpected ways. We argue that a dispersal-centered synthesis of metacommunity ecology and evolution is necessary to make further progress in this important area of research. We demonstrate that such an approach generates several novel outcomes and substantially enhances understanding of both ecological and evolutionary phenomena in three core research areas at the interface of ecology and evolution.

Gene flow and geographically structured coevolution

Many of the dynamic properties of coevolution may occur at the level of interacting populations, with local adaptation acting as a force of diversification, as migration between populations homogenizes these isolated interactions. This interplay between local adaptation and migration may be particularly important in structuring interactions that vary from mutualism to antagonism across the range of an interacting set of species, such as those between some plants and their insect herbivores, mammals and trypanosome parasites, and bacteria and plasmids that confer antibiotic resistance. Here we present a simple geographically structured genetic model of a coevolutionary interaction that varies between mutualism and antagonism among communities linked by migration. Inclusion of geographic structure with gene flow alters the outcomes of local interactions and allows the maintenance of allelic polymorphism across all communities under a range of selection intensities and rates of migration. Furthermore, inclusion of geographic structure with gene flow allows fixed mutualisms to be evolutionarily stable within both communities, even when selection on the interaction is antagonistic within one community. Moreover, the model demonstrates that the inclusion of geographic structure with gene flow may lead to considerable local maladaptation and trait mismatching as predicted by the geographic mosaic theory of coevolution.

COEVOLUTIONARY CLINES ACROSS SELECTION MOSAICS

Abstract. Much of the dynamics of coevolution may be driven by the interplay between geographic variation in reciprocal selection (selection mosaics) and the homogenizing action of gene flow. We develop a genetic model of geographically structured coevolution in which gene flow links coevolving communities that may differ in both the direction and magnitude of reciprocal selection. The results show that geographically structured coevolution may lead to allele‐frequency clines within both interacting species when fitnesses are spatially uniform or spatially heterogeneous. Furthermore, the results show that the behavior and shape of clines differ dramatically among different types of coevolutionary interaction. Antagonistic interactions produce dynamic clines that change shape rapidly through time, producing shifting patterns of local adaptation and maladaptation. Unlike antagonistic interactions, mutualisms generate stable equilibrium patterns that lead to fixed spatial patterns of adaptation. Interactions that vary between mutualism and antagonism produce both equilibrium and dynamic clines. Furthermore, the results demonstrate that these interactions may allow mutualisms to persist throughout the geographic range of an interaction, despite pockets of locally antagonistic selection. In all cases, the coevolved spatial patterns of allele frequencies are sensitive to the relative contributions of gene flow, selection, and overall habitat size, indicating that the appropriate scale for studies of geographically structured coevolution depends on the relative contributions of each of these factors.

Dos and don'ts of testing the geographic mosaic theory of coevolution

The geographic mosaic theory of coevolution is stimulating much new research on interspecific interactions. We provide a guide to the fundamental components of the theory, its processes and main predictions. Our primary objectives are to clarify misconceptions regarding the geographic mosaic theory of coevolution and to describe how empiricists can test the theory rigorously. In particular, we explain why confirming the three main predicted empirical patterns (spatial variation in traits mediating interactions among species, trait mismatching among interacting species and few species-level coevolved traits) does not provide unequivocal support for the theory. We suggest that strong empirical tests of the geographic mosaic theory of coevolution should focus on its underlying processes: coevolutionary hot and cold spots, selection mosaics and trait remixing. We describe these processes and discuss potential ways each can be tested.

Demographic and Genetic Constraints on Evolution

Populations unable to evolve to selectively favored states are constrained. Genetic constraints occur when additive genetic variance in selectively favored directions is absent (absolute constraints) or present but small (quantitative constraints). Quantitative—unlike absolute—constraints are presumed surmountable given time. This ignores that a population might become extinct before reaching the favored state, in which case demography effectively converts a quantitative into an absolute constraint. Here, we derive criteria for predicting when such conversions occur. We model the demography and evolution of populations subject to optimizing selection that experience either a single shift or a constant change in the optimum. In the single‐shift case, we consider whether a population can evolve significantly without declining or else declines temporarily while avoiding low sizes consistent with high extinction risk. We analyze when populations in constantly changing environments evolve sufficiently to ensure long‐term growth. From these, we derive formulas for critical levels of genetic variability that define demography‐caused absolute constraints. The formulas depend on estimable properties of fitness, population size, or environmental change rates. Each extends to selection on multivariate traits. Our criteria define the nearly null space of a population’s G matrix, the set of multivariate directions effectively inaccessible to it via adaptive evolution.

The phenomenology of niche evolution via quantitative traits in a 'black-hole' sink.

Previous studies of adaptive evolution in sink habitats (in which isolated populations of a species cannot persist deterministically) have highlighted the importance of demographic constraints in slowing such evolution, and of immigration in facilitating adaptation. These studies have relied upon either single–locus models or deterministic quantitative genetic formulations. We use individual–based simulations to examine adaptive evolution in a ‘black–hole’ sink environment where fitness is governed by a polygenic character. The simulations track both the number of individuals and their multi–locus genotypes, and incorporate, in a natural manner, both demographic and genetic stochastic processes. In agreement with previous studies, our findings reveal the central parts played by demographic constraints and immigration in adaptation within a sink (adaptation is more difficult in environments with low absolute fitness, and higher immigration can accelerate adaptation). A novel finding is that there is a ‘punctuational’ pattern in adaptive evolution in sink environments. Populations typically stay maladapted for a long time, and then rapidly shift into a relatively adapted state, in which persistence no longer depends upon recurrent immigration.