Is there plasticity in developmental instability? The effect of daily thermal fluctuations in an ectotherm

Abstract

Diversified bet‐hedging (DBH) by production of within‐genotype phenotypic variance may evolve to maximize fitness in stochastic environments. Bet‐hedging is generally associated with parental effects, but phenotypic variation may also develop throughout life via developmental instability (DI). This opens for the possibility of a within‐generation mechanism creating DBH during the lifetime of individuals. If so, DI could in fact be a plastic trait itself; if a fluctuating environment indicates uncertainty about future conditions, sensing such fluctuations could trigger DI as a DBH response. However, this possibility has received little empirical attention. Here, we test whether fluctuating environments may elicit such a response in the clonally reproducing crustacean Daphnia magna. Specifically, we exposed genetically identical individuals to two environments of different thermal stability (stable vs. pronounced daily realistic temperature fluctuations) and tested for effects on DI in body mass and metabolic rate shortly before maturation. Furthermore, we also estimated the genetic variation in DI. Interestingly, fluctuating temperatures did not affect body mass, but metabolic rate decreased. We found no evidence for plasticity in DI in response to environmental fluctuations. The lack of plasticity was common to all genotypes, and for both traits studied. However, we found considerable evolvability for DI, which implies a general evolutionary potential for DBH under selection for increased phenotypic variance.

Acclimation capacity and rate change through life in the zooplankton Daphnia

“…The same period was chosen for both hardening treatments so that size/age effects on any acclimation response would be more comparable. The temperatures implemented during development and the range in temperature experienced during hardening was within the range observed in the wild for the population from which the experimental genotype was sourced [21].…”

Fluctuating thermal environments and time‐dependent effects on fruit fly egg‐hatching performance

“…Insights about the suitability of a thermal landscape for a given species should consider not only average thermal values but also variability in thermal values (Bozinovic, Medina, Alruiz, Cavieres, & Sabat, ; Bozinovic, Sabat, Rezende, & Canals, ; Estay, Lima, & Bozinovic, ). Theoretical (Katz, Brush, & Parlange, ) and empirical studies (Easterling et al., ) have demonstrated that daily and seasonal variation in temperature affects organisms’ ecology and fitness (Clavijo‐Baquet et al., ; Gilbert & Miles, ; Kielland, Bech, & Einum, ; Messenger & Flitters, ; Roitberg & Mangel, ; Saarinen, Laakso, Lindström, & Ketola, ). In addition, thermal extremes, defined as events that alter the distribution of ambient temperature without influencing the mean and the variance (Ummenhofer & Meehl, ), have also been shown to have outstanding effects on physiological performance and survival (Bozinovic, Medina, et al., ; Kingsolver & Woods, ).…”

Measuring phenotypes in fluctuating environments

“…For the pond from which the experimental genotype originates, there is a high autocorrelation in mean temperature over short time‐scales (e.g. r > .9 with a one‐day lag, supplementary data in Kielland et al, ). Thus, the fine‐scale tracking in temperature tolerance observed here ( c .…”

“…For example, predictable fluctuations in temperature around a given mean have been shown to influence the growth, development and physiology of individuals (e.g. Kern, Cramp, & Franklin, 2015;Kielland, Bech, & Einum, 2017;Niehaus, Wilson, & Franklin, 2006;Sørensen, Schou, Kristensen, & Loeschcke, 2016;Verheyen & Stoks, 2019). Furthermore, theoretical models assert that the optimal phenotype may also be influenced by the level of environmental predictability (Arnoldini, Mostowy, Bonhoeffer, & Ackermann, 2012;Donaldson-Matasci, Lachmann, & Bergstrom, 2008;Reed, Waples, Schindler, Hard, & Kinnison, 2010).…”