The evolution of phenotypic plasticity when environments fluctuate in time and space

Abstract

Most theoretical studies have explored the evolution of plasticity when the environment, and therefore the optimal trait value, varies in time or space. When the environment varies in time and space, we show that genetic adaptation to Markovian temporal fluctuations depends on the between‐generation autocorrelation in the environment in exactly the same way that genetic adaptation to spatial fluctuations depends on the probability of philopatry. This is because both measure the correlation in parent‐offspring environments and therefore the effectiveness of a genetic response to selection. If the capacity to genetically respond to selection is stronger in one dimension (e.g., space), then plasticity mainly evolves in response to fluctuations in the other dimension (e.g., time). If the relationships between the environments of development and selection are the same in time and space, the evolved plastic response to temporal fluctuations is useful in a spatial context and genetic differentiation in space is reduced. However, if the relationships between the environments of development and selection are different, the optimal level of plasticity is different in the two dimensions. In this case, the plastic response that evolves to cope with temporal fluctuations may actually be maladaptive in space, resulting in the evolution of hyperplasticity or negative plasticity. These effects can be mitigated by spatial genetic differentiation that acts in opposition to plasticity resulting in counter‐gradient variation. These results highlight the difficulty of making space‐for‐time substitutions in empirical work but identify the key parameters that need to be measured in order to test whether space‐for‐time substitutions are likely to be valid.

The relative importance of plasticity versus genetic differentiation in explaining between population differences; a meta‐analysis

“…Two ideas may be put forward against this viewpoint. First, counter‐gradient patterns can also arise at equilibrium through adaptive plastic responses that have evolved to cope with both temporal and spatial environmental variation (King & Hadfield 2019) and there is little empirical work to gauge whether this is likely. Second, in our data, counter‐gradient variation, like maladaptive plasticity, is often associated with low phenotypic divergence, and while low phenotypic divergence could be driven by genetic and plastic responses that are large in magnitude but opposite in sign, it seems more likely that low phenotypic divergence is also associated with low genetic and plastic divergence.…”

Need to Seed? Ecological, Genetic, and Evolutionary Keys to Seed-Based Wetland Restoration

“…Phenotypic plasticity is particularly important in the context of climate change as it can influence species distribution and facilitate rapid evolution in response to changing environmental conditions (Sultan et al, 1998;Rice and Emery, 2003;Chevin et al, 2010;Havens et al, 2015). In ecosystems that are highly variable, as in wetland ecosystems, plasticity is expected to be high (Scheiner and Holt, 2012;King and Hadfield, 2019), and phenotypic differences between wetland plant populations may be less pronounced as compared to other ecosystems. However, because plasticity can have a genetic basis and can be driven by the maternal environment, subject to strong selection, and structured across the landscape, it should be considered for seed sourcing to ensure adequate sampling of plastic trait variation (section "Seed Collection Locations and Amounts"; Donohue et al, 2010;Walck et al, 2011;Su et al, 2018).…”

Differences in spatial versus temporal reaction norms for spring and autumn phenological events

“…Fig. 1C)-the former being a sign of countergradient local adaptation, the latter of cogradient local adaptation (20,21,32). For a worked-through example of how this methodology is applied to the current data, see SI Appendix, Text S1.…”