Best of both worlds: Acclimation to fluctuating environments confers advantages and minimizes costs of constant environments

Thermal acclimation is often considered critical in organismal responses to novel thermal conditions. Our understanding of the physiological implications of acclimation is largely derived from lab studies with simplified thermal regimes that fail to account for any variation that animals would experience naturally (i.e. diel variation). As such, constant temperature acclimation experiments may produce a flawed understanding of acclimation in the wild.
To fill this gap, we acclimated lizards (Amphibolurus muricatus) under three thermal regimes (Hot Constant, Cold Constant and Alternating) and compared their physiological responses (Metabolic Rate, Sprint Speed, Thermal Preferences and Thermal Limits).

We found that animals maintained constantly at hot temperatures (preferred temperature, 35°C) gained sprint performance increases, not seen in those maintained constantly at cold temperatures (20°C), yet suffered costs to growth (in younger animals) and maintenance (mass loss in older animals). Animals maintained at alternating temperatures (12 hr 20°C; 12 hr 35°C) had performance benefits matching animals in the hot treatment, without experiencing reductions in juvenile growth and adult mass.

Animals acclimated under hot temperatures showed a significant lower preferred and voluntary maximum temperatures compared to animals acclimated under a cold temperature regime.
We found no impact of acclimation treatment on behavioural thermal limits or Standard Metabolic Rate.

Overall, we show that alternating between access to preferred temperatures and having periods of energetic rest confer the greatest benefits for our animals. These results highlight the importance of natural body temperature variation for enhancing overall ectotherm performance and physiology, and the costs of novel thermal environments that fail to provide this variation.

Methods
Data was collected using standard methods of closed system respirometry, sprint performance, thermal preferences and limits. 

Processed in Kinovea (sprint), Warthog (SMR), Excel (Thermal Preferences).  Data wrangling and analysis in R.