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Accelerating shifts in global climate have focused the attention of ecologists and physiologists on extreme environmental events. However, the dynamic process of physiological acclimatization complicates study of these events’ consequences. Depending on the range of plasticity and the amplitude and speed of environmental variation, physiology can be either in tune with the surroundings or dangerously out of synch. We implement a modified quantitative approach to identifying extreme events in environmental records, proposing that organisms are stressed by deviations of the environment from the current level of acclimatization, rather than by the environment’s absolute state. This approach facilitates an unambiguous null model for the consequences of environmental variation, identifying a unique subset of events as ‘extremes’. Specifically, it allows one to examine how both the temporal extent (the acclimatization window) and type of an environmental signal affect the magnitude and timing of extreme environmental events. For example, if physiology responds to the moving average of past conditions, a longer acclimatization window generally results in greater imposed stress. If instead physiology responds to historical maxima, longer acclimatization windows reduce imposed stress, albeit perhaps at greater constitutive cost. This approach should be further informed and tested with empirical experiments addressing the history-dependent nature of acclimatization. 

Body temperature affects plants’ and animals’ performance, but these effects are complicated by thermal variation through time within an individual and variation through space among individuals in a population. This review and synthesis describes how the effects of thermal variation—in both time and space—can be estimated by applying a simple, nonlinear averaging scheme. The method is first applied to the temporal variation experienced by an ndividual, providing an estimate of the individual’s average performance. The method is then applied to the scale-dependent thermal variation among individuals, which is modelled as a 1/f-noise phenomenon. For an individual, thermal variation reduces average performance, lowers the temperature of maximum performance (Topt) and contracts the range of viable temperatures. Thermal variation among individuals similarly reduces performance and lowers Topt, but increases the viable range of average temperatures. These results must be viewed with caution, however, because they do not take into account the time-dependent interaction between body temperature and physiological plasticity. Quantifying these interactions is perhaps the largest challenge for ecological and conservation physiologists as they attempt to predict the effects of climate change. 

Intertidal communities of wave-swept rocky shores have served as a powerful model system for experiments in ecology, and mussels (the dominant competitor for space in the mid-intertidal zone) play a central role in determining community structure in this physically stressful habitat. Consequently, the ability to account for mussels’ physiological responses to thermal stress affects ecologists’ capacity to predict the impacts of a warming climate on this ecosystem. Here, we examined the effect of heating rate on cardiac thermal tolerance in the ribbed mussel, Mytilus californianus, comparing populations from high and low sites in the intertidal zone where emersion duration leads to different mean daily heating rates. Two temperature-related cardiac variables were examined: (1) the critical temperature (Tcrit) at which heart rate (HR) precipitously declines, and (2) flatline temperature (FLT) where HR reaches zero. Mussels were heated in air at slow, moderate and fast rates, and HR was measured via an infrared sensor affixed to the shell. Faster heating rates significantly increased Tcrit in high- but not low-zone mussels, and Tcrit was higher in high- versus low-zone mussels, especially at the fastest heating rate. By contrast, FLT did not differ between zones, and was minimally affected by heating rate. As heating rate significantly impacted high- but not low-zone mussels’ cardiac thermal tolerance, realistic zone-specific heating rates must be used in laboratory tests if those tests are to provide accurate information for ecological models attempting to predict the effects of increasing temperature on intertidal communities. 

Animals must balance their rates of energetic intake and expenditure while foraging. Several mathematical models have been put forward as energetically optimal foraging strategies when the food environment is sparse (i.e., the distance between food patches in the environment is much larger than the distance from which the forager can perceive food). In particular, Lévy walks with a power law exponent approaching 1 are considered optimal for destructive foragers. However, these models have yet to explore the role of sensory perception in foraging success as the distance between food patches approaches the distance from which the forager can perceive food. Here, we used an agent-based modeling approach to address this question. Our results concur that lower values of the power law exponent (i.e. values approaching 1) result in the most food found, but in contrast to previous studies, we note that, in many cases, lower exponents are not optimal when we consider food found per unit distance traveled. For example, higher values of the exponent resulted in comparable or higher foraging success relative to lower values when the forager's range of sensory perception was restricted to an angle±30° from its current heading. In addition, we find that sensory perception has a larger effect on foraging success than the power law exponent. These results suggest that a deeper examination of how animals perceive food sources from a distance may affect longstanding assumptions regarding the optimality of Lévy walk foraging patterns, and lend support to the developing theoretical shift towards models that place increasing emphasis on how organisms interact with their environments.