Periodic environmental fluctuations are ubiquitous. Species exhibit distinct strategies for dealing with fluctuations, which occur in various abiotic or biotic factors (including temperature, light, and precipitation, or resource abundance, predation, and population density). In many cases, these different strategies enable species to coexist by partitioning their activity or resource consumption in time. For example, we know that marine phytoplankton exhibit differences in their thermal tolerances (or reaction norms) attributable to the temperature variations they experience in the ocean. When the range of variation is sufficiently large, both warm- and cold-adapted species can coexist.
Many studies have focused on relationships between the mean, range, and frequency of fluctuating environments and properties of communities. However, equally important is the distribution of environmental states that accumulate as the environment travels back and forth between its extremes. Here, we explore how the distribution of temperatures experienced over a fluctuation influences species coexistence and trait distributions. We investigate a variety of deterministic, periodic fluctuations, using eco-evolutionary modeling techniques (adaptive dynamics) to determine sets of evolutionary stable states (ESSs) across different environments. This helps us understand how differences the shape (or distribution) of environmental variation between environments might drive differences in species or functional diversity.
Results/Conclusions
We found that increasing the amplitude of fluctuations increases diversity, but only up to a point. For sinusoidal fluctuations with a fixed period and species with finite niche widths (ie, a finite range of temperatures permitting growth), increasing amplitude ultimately decreases diversity, as intermediate environmental states occur too rapidly to support species with intermediate traits. This result depends on the form and rate of mortality experienced outside of species’ niches, a factor that is often ignored.
Altering the distribution of environmental states experienced across fluctuations (using sine-, square-, triangle-waves, and other more complicated and/or asymmetric fluctuations) altered ESS trait distributions. In general, we found that fluctuations with asymmetric distributions of environmental states exhibited skewed trait distributions. Any environmental model lacking a uniform distribution of environmental states produced trait distributions with uneven spacing.
These results suggest that there are often unconsidered consequences of assuming sinusoidal variation when modeling variable or seasonal environments, as this choice carries an implicit assumption about the underlying distribution of environmental conditions. More generally, studying eco-evolutionary processes in fluctuating environments is important for understanding both how contemporary systems function, as well as how they may respond as climate change alters patterns of variation across the globe.