Meeting Abstract
P1.85 Sunday, Jan. 4 Acclimation of thermal physiology in predictable and stochastic environments: a test of optimality theory SCHULER, Matthew S.; STORM, John J.; SEARS, Michael W.; COOPER, Brandon S.*; WILLIAMS, Ben H.; ANGILLETTA, Michael J.; Indiana State University; University of South Carolina – Upstate; Southern Illinois University; Indiana State University; Indiana State University; Indiana State University matt.s.schuler@gmail.com
Most environments vary stochastically, yet researchers rarely study the phenotypic responses of organisms to stochastic environmental conditions. Optimality models predict that stochastic environments favor generalists while predictable environments favor specialists. If environmental conditions change predictably between seasons, the optimal phenotype tracks the environment by specializing for the conditions of each season. To evaluate this theory, we exposed rough woodlice (Porcellio scaber) to four thermal environments: a constant 20C, a constant 10C, a steady decline from 20 to 10C, and a stochastic decline that mimicked natural conditions. To control for photoperiodic cues, the duration of photophase decreased according to the natural environment. After 45 d, we measured several aspects of thermal physiology, including the thermal sensitivity of locomotion, critical thermal maximum, and chill-coma recovery time. We fit six nonlinear models to the data and selected the best-fitting model using Akaikes information criterion. Data were bootstrapped to obtain confidence intervals for thermal optima and performance breadths. Contrary to our expectation, thermal treatments did not affect the thermal sensitivity of sprinting; woodlice from all treatments ran fastest at 33 to 34C and achieved > 80% of their maximal speed over a range of 10 to 11C. Furthermore, woodlice exposed to stochastically and predictably declining temperatures tolerated cold better than woodlice exposed to a constant temperature of either 10 or 20C. These results cast doubt on the assumptions of current models, suggesting the need to examine genetic constraints on the evolution of acclimation.
