Measuring phenotypes in fluctuating environments

Abstract

Abstract Despite considerable theoretical interest in how the evolution of phenotypic plasticity should be shaped by environmental variability and stochasticity, how individuals actually respond to these aspects of the environment within their own lifetimes remains unclear. We propose that this understanding has been hampered by experimental approaches that expose organisms to fluctuating environments (typically treatments where fluctuations in the environment are cyclical vs. erratic) for a pre‐determined duration while ensuring that the mean environment over that the entire exposure period is invariable. This approach implicitly assumes that responses to the mean and variance/predictability in the environment occur over the same time‐scale. If this assumption is false, one potential outcome is that phenotypic differences among the treatment groups might arise in response to differences in the mean environment that are present over shorter time periods among those same treatment groups. We illustrate an experimental design that (a) creates variation in the level of environmental predictability, (b) allows for estimation of the time‐scale over which the phenotypic response to the mean environment occurs and (c) permits statistical estimation of the effect of predictability in the environmental variable of interest while controlling for any effect of the mean environment over the relevant temporal scale. Using the clonally reproducing zooplankton species Daphnia magna, we test for within‐generation plasticity in the ability to tolerate high temperature following exposure to multiple temperature treatments with the same overall mean, but where the pattern of fluctuations differed among them. This approach revealed that heat tolerance in Daphnia was not influenced by variability in temperature per se nor the predictability of fluctuations in temperature but adjusted in response to the mean temperature they experienced 24 hr prior to measurement. Our results suggest that conclusions arising from studies that employ a single manipulation of environmental predictability and which cannot consider such potentially confounding effects may be premature. A free Plain Language Summary can be found within the Supporting Information of this article.