Species with large geographic ranges commonly exhibit substantial phenotypic differences between local populations or races, often following predictable patterns along spatial and environmental gradients. In animals, ecogeographical rules (Mayr, 1956) have been described for over 150 years. For instance, Bergmann’s (1847) rule that across a species’ geographic range individual body mass increases with latitude (putatively because reduced surface/volume ratio minimizes energy loss in colder environments) has been confirmed in birds (Ashton, 2002), mammals (Meiri & Dayan, 2003) and insects (Huey et al., 2000). Plants have been extensively studied regarding morphological and phenological differences between altitudinal and geographic races or ecotypes (Bonnier, 1895; Turesson, 1922; Clausen et al., 1940; Knight, 1973; Gurevitch, 1992; Linhart & Grant, 1996; Etterson, 2004).
The origin of these patterns has long been of interest to evolutionists and ecologists. Correlation between phenotypes and environmental variables may be caused either by genetic differences between populations or by phenotypic plasticity, the direct influence of the environment on development of individual phenotypes. Genetic differences often evolve by local adaptation owing to natural selection in a heterogeneous environment. Random genetic drift may also cause genetic differentiation of spatially distributed populations, but this will correlate with environmental variables only in special cases (Cavalli-Sforza et al., 1993; Francois et al., 2010).
In plants, the basis of geographic variation within species has been investigated using common garden experiments and reciprocal transplantation, sometimes combined with controlled crosses (Hall, 1932; Clausen et al., 1940, 1947; Linhart & Grant, 1996). A classic example is the long-term study of Clausen, Keck and Hiesey, who placed ecomorphs of Potentilla glandulosa at various altitudes to investigate differences in height, branching and phenology (Clausen et al., 1940). In animals, the contributions of genetic differentiation and plasticity to biogeographic patterns has been studied in the laboratory and in the wild (Stillwell, 2010). Laboratory experiments on ectotherms focused on the ‘temperature-size rule’ whereby individuals reared at higher temperature develop smaller adult size (Atkinson, 1994), as a possible explanation of Bergmann’s rule (vanVoorhies, 1996; Partridge & Coyne, 1997). Studies of natural populations used statistical methods to test whether the observed phenotype–environment correlation exceeds that expected from plasticity alone (Phillimore et al., 2010).
A major finding common to these studies is that phenotypic differentiation among geographic races or ecotypes is generally caused by a combination of partially adaptive phenotypic plasticity and genetic differences (Clausen et al., 1940; James et al., 1997; Schlichting & Pigliucci, 1998; Gilchrist & Huey, 2004; Kingsolver & Huey, 2007; Wilczek et al., 2009; Phillimore et al., 2010). For example, James et al. (1997) measured the contribution of phenotypic plasticity to latitudinal clines in body size traits of Drosophila melanogaster in Australia, by comparing the phenotypes of individuals collected in the wild to those of lineages from the same locations bred in a laboratory environment. They showed that latitudinal clines were always steeper in the wild than in the laboratory environment, indicating a contribution from plasticity. Table 1 shows that plasticity accounts for a substantial proportion (56% on average) of the slopes of the clines they observed in nature. Similarly, for the classic experiment on altitudinal ecotypes of Potentilla glandusa in California (Clausen et al., 1940, tables 3, 5 and 7), we estimated that 54% of variance in plant size was attributable to plasticity. This was measured as the variance of the mean reaction norm (averaged over races) across environments, divided by the total variance of population means across races and environments (assigning size 0 to races that do not grow in a given environment). Plasticity is thus an important component of observed geographic variation.
|Trait||Contribution of plasticity (%)*|
Phenotypic plasticity itself can vary substantially among populations of the same species (Morin et al., 1999; Gilchrist & Huey, 2004; Kingsolver & Huey, 2007; Lind et al., 2011). However, only a few empirical studies have investigated the reasons for observed levels of plasticity in a spatially heterogeneous environment (Lind et al., 2011), and factors determining the quantitative contribution of plasticity to geographic variation are not well understood. Theoretical models of the evolution of plasticity in the presence of gene flow may help to identify those factors, and to generate testable predictions.
Theory on the evolution of plasticity in a heterogeneous environment has concentrated on constraints preventing the evolution of perfect plasticity which, if it occurred, would preclude local genetic adaptation. Via & Lande (1985) predicted that with no cost or constraint, perfect plasticity (where the mean phenotype matches the optimum phenotype in all environments) should evolve, regardless of the frequency of each environment, or whether selection is hard or soft. With a cost of plasticity such that more plastic genotypes have lower fitness, van Tienderen (1991) showed that under hard selection, specialists and/or generalists may evolve, depending on initial conditions. Even without a cost, the equilibrium plasticity is limited by the predictability of the environment when development and selection occur in different environments owing to temporal changes in the environment or individual dispersal (Gavrilets & Scheiner, 1993; de Jong, 1999). Imperfect environmental cues produce a similar result (Tufto, 2000a).
Few theoretical studies have investigated the evolution of spatial differentiation in plasticity itself. de Jong and others showed that in a spatially heterogeneous environment, the combination of a life cycle with unpredictable selection and spatial variation in the strength of density dependence after selection could cause the evolution of a polymorphic reaction norm at the level of the metapopulation (de Jong, 1999, 2005; Sasaki & de Jong, 1999; de Jong & Behera, 2002). However, these studies did not explicitly quantify geographic variation in plasticity.
Here, we investigate (i) how plasticity and its evolution modify the impact of gene flow on local adaptation and demography; (ii) how plasticity differentiates across discrete localities and continuous spatial environments. We incorporated plasticity (and its evolution) into an analytical model of the interaction of genetic and demographic processes, with dispersal between local populations differing in abundance, mean phenotype and environment. This was also recently done using individual-based simulations by Thibert-Plante & Hendry (2010) in the context of ecological speciation, but these authors did not specifically investigate how plasticity differentiates across space. They used a model where the plastic response depends on the distance of the mean phenotype from the local optimum, and plasticity cannot exceed a predetermined threshold. The empirical justifications for such a model are unclear, so it is worth re-examining these subjects using more conventional models of plasticity and its evolution, based on empirically well-established norms of reaction describing how the average phenotype of a genotype changes with the environment of development (Gavrilets & Scheiner, 1993; Scheiner, 1993).
Local adaptation and gene flow in spatially heterogeneous environments have been intensively analysed theoretically because of their close connection to evolution of a species’ ecological niche (Holt & Gaines, 1992) and geographic range (Kirkpatrick & Barton, 1997; Holt, 2003). With local genetic adaptation, gene flow from a differentiated population causes local maladaptation, lowering the mean fitness of the recipient population (Lenormand, 2002). This may reduce local population size if the maladaptive influence of immigrants on population growth rate exceeds their direct demographic contribution to population abundance. Furthermore, gene flow increases genetic variance, accelerating adaptive evolution, but also increasing the variance load from stabilizing selection. With gene flow between populations having different optimum phenotypes but otherwise equivalent, Ronce & Kirkpatrick (2001) showed that a small initial difference in deme size can produce a highly asymmetric outcome, where one population becomes a source that is self-sustaining in the absence of immigration and the other population a sink that is not self-sustaining (Pulliam, 1988). This results from a feedback loop (termed migrational meltdown), whereby the larger deme sends more migrants, thus causing more maladaptation in the smaller deme and augmenting differences in population size. A similar process can restrict a species’ range in continuous space over a steep environmental gradient (Haldane, 1956; Kirkpatrick & Barton, 1997; Polechova et al., 2009). These studies emphasized that the impact of gene flow on local adaptation and its interaction with demography should be most pronounced for populations at the edge of a species’ range, or in marginal habitats that receive more migrants than they produce, resulting in net immigration (Kawecki, 2004, 2008). The limiting case is a ‘black-hole sink’ with immigration but no emigration (Gomulkiewicz et al., 1999; Tufto, 2001), a particular case of the ‘continent–island’ model of dispersal where the island is not self-sustaining.
Few models investigated how plasticity and its evolution affect the phenotypic differentiation of populations and the demographic consequences of gene flow (but see Thibert-Plante & Hendry, 2010). To address this, we first consider a population occupying a marginal habitat (the ‘island’) receiving immigrants from a much larger population in the core habitat of the species (the ‘continent’). The environment differs between the core and marginal habitats, with different local optimum phenotypes for a quantitative trait. We investigate the consequences of constant or evolving plasticity on local adaptation and demography on the island, and the basis of phenotypic differentiation between the core and marginal habitats. We then turn to a spatially explicit model of gene flow along a continuous environmental gradient to analyse how evolving plasticity affects geographic variation in plasticity and a species’ geographic range at equilibrium. We show that, provided they correspond to environments of decanalization, marginal and edge populations are characterized by increased plasticity, which generally improves local adaptation and increases population size.