Gradual plasticity alters population dynamics in variable environments: thermal acclimation in the green alga Chlamydomonas reinhartdii

Abstract

Environmental variability is ubiquitous, but its effects on populations are not fully understood or predictable. Recent attention has focused on how rapid evolution can impact ecological dynamics via adaptive trait change. However, the impact of trait change arising from plastic responses has received less attention, and is often assumed to optimize performance and unfold on a separate, faster timescale than ecological dynamics. Challenging these assumptions, we propose that gradual plasticity is important for ecological dynamics, and present a study of the plastic responses of the freshwater green algae Chlamydomonas reinhardtii as it acclimates to temperature changes. First, we show that C. reinhardtii's gradual acclimation responses can both enhance and suppress its performance after a perturbation, depending on its prior thermal history. Second, we demonstrate that where conventional approaches fail to predict the population dynamics of C. reinhardtii exposed to temperature fluctuations, a new model of gradual acclimation succeeds. Finally, using high-resolution data, we show that phytoplankton in lake ecosystems can experience thermal variation sufficient to make acclimation relevant. These results challenge prevailing assumptions about plasticity's interactions with ecological dynamics. Amidst the current emphasis on rapid evolution, it is critical that we also develop predictive methods accounting for plasticity.

Keywords: beneficial acclimation hypothesis; ecological forecasting; environmental variation; phenotypic plasticity; temperature; thermal performance.

Figure 1.

Organismal performance changes in response to environmental change (say a shift from environment E₁ to E₂) through plastic and evolutionary processes over a range of temporal scales. Rapid plastic responses (a) allow individuals with a fixed genotype to change their phenotype quickly, leading to performance levels that match their reaction norm in environment E₂. By contrast, when plastic responses are gradual (b), phenotypic adjustments occur slowly. During this period, individuals may exceed or fall short of their eventual performance once adjusted to E₂ (i.e. the value given by their reaction norm). We refer to plastic responses that gradually improve performance following a perturbation as ‘beneficial’ (red); those that decrease performance are ‘detrimental’ (blue). Over longer exposures to E₂, evolutionary responses (c) spanning generations may improve the fitness (often correlated with performance) of the population of individuals, changing the reaction norm. Note that plastic and evolutionary responses may occur simultaneously, depending on the rate of plasticity, the amount of heritable genetic variation present, and the rate at which new variation arises. Finally, while plasticity typically concerns phenotypic changes within the lifespan of an individual, some plastic responses can extend across generations (e.g. in populations of genetically identical, asexual microbes). (Online version in colour.)

Figure 2.

Depending on their prior acclimation history (a, 14°C; or b, 33°C) the acute growth rates of C. reinhardtii populations over a range of temperatures can both exceed and fall short of their long-term, acclimated growth rates (grey). Lines and shading represent GAM regression fits and 95% CIs (electronic supplementary material, table S5).

Figure 3.

The growth rate of isogenic C. reinhardtii lines (left) at 30°C depend on whether they were previously acclimated to 14°C (black) or 30°C (grey). The pooled responses of strains 1–5 with a 14°C history do not differ from the original, mixed-genotype population (right). Points indicate average growth rate; error bars are 95% CIs.

Figure 4.

Populations of C. reinhardtii achieve different densities over 2 days of exposure to temperatures oscillating between 14°C and 30°C, depending on fluctuation frequency and their prior acclimation history (red/blue). Observations are contrasted with predicted values from: (i) a basic exponential growth model assuming rapid acclimation (black points with 95% confidence intervals). Because of this assumption, predictions are independent of acclimation history, so only a single mean prediction is provided; and (ii) an empirically parameterized model accounting for gradual acclimation (red/blue points with 95% confidence intervals).

Figure 5.

Phytoplankton can experience enough thermal variation in lakes to make gradual acclimation ecologically important. (a) Depth-specific lake temperatures for Crystal Bog (left column) and Sparkling Lake (right column). (b) The difference between acute and acclimated growth rates for a 14°C acclimated population illustrates the potential effects of a range of increases in temperature (black, GAM regression line with ±1 s.e. confidence band). Shaded empirical distributions highlight the probabilities of actually experiencing these temperature increases within 24 h, depending on lake identity and movement strategy.