Thermal performance curves (TPCs), which quantify how an ectotherm's body temperature (T b ) affects its performance or fitness, are often used in an attempt to predict organismal responses to climate change. Here, we examine the key -but often biologically unreasonable -assumptions underlying this approach; for example, that physiology and thermal regimes are invariant over ontogeny, space and time, and also that TPCs are independent of previously experienced T b. We show how a critical consideration of these assumptions can lead to biologically useful hypotheses and experimental designs. For example, rather than assuming that TPCs are fixed during ontogeny, one can measure TPCs for each major life stage and incorporate these into stage-specific ecological models to reveal the life stage most likely to be vulnerable to climate change. Our overall goal is to explicitly examine the assumptions underlying the integration of TPCs with T b , to develop a framework within which empiricists can place their work within these limitations, and to facilitate the application of thermal physiology to understanding the biological implications of climate change.

The interaction of climate and the timing of low tides along the West Coast of the United States creates a complex mosaic of thermal environments, in which northern sites can be more thermally stressful than southern sites. Thus, climate change may not lead to a poleward shift in the distribution of intertidal organisms, as has been proposed, but instead will likely cause localized extinctions at a series of "hot spots." Patterns of exposure to extreme climatic conditions are temporally variable, and tidal predictions suggest that in the next 3 to 5 years "hot spots" are likely to appear at several northern sites.

ANRV292-ES37-14 ARI

Abstract. We explicitly quantified spatial and temporal patterns in the body temperature of an ecologically important species of intertidal invertebrate, the mussel Mytilus californianus, along the majority of its latitudinal range from Washington to southern California, USA. Using long-term (five years), high-frequency temperature records recorded at multiple sites, we tested the hypothesis that local ''modifying factors'' such as the timing of low tide in summer can lead to large-scale geographic mosaics of body temperature. Our results show that patterns of body temperature during aerial exposure at low tide vary in physiologically meaningful and often counterintuitive ways over large sections of this species' geographic range. We evaluated the spatial correlations among sites to explore how body temperatures change along the latitudinal gradient, and these analyses show that ''hot spots'' and ''cold spots'' exist where temperatures are hotter or colder than expected based on latitude. We identified four major hot spots and four cold spots along the entire geographic gradient with at least one hot spot and one cold spot in each of the three regions examined (WashingtonOregon, Central California, and Southern California). Temporal autocorrelation analysis of year-to-year consistency and temporal predictability in the mussel body temperatures revealed that southern animals experience higher levels of predictability in thermal signals than northern animals. We also explored the role of wave splash at a subset of sites and found that, while average daily temperature extremes varied between sites with different levels of wave splash, yearly extreme temperatures were often similar, as were patterns of predictability. Our results suggest that regional patterns of tidal regime and local pattern of wave splash can overwhelm those of large-scale climate in driving patterns of body temperature, leading to complex thermal mosaics of temperature rather than simple latitudinal gradients. A narrow focus on population changes only at range margins may overlook climatically forced local extinctions and other population changes at sites well within a species range. Our results emphasize the importance of quantitatively examining biogeographic patterns in environmental variables at scales relevant to organisms, and in forecasting the impacts of changes in climate across species ranges.

Recent meta-analyses have shown that the effects of climate change are detectable and significant in their magnitude, but these studies have emphasized the utility of looking for large-scale patterns without necessarily understanding the mechanisms underlying these changes. Using a series of case studies, we explore the potential pitfalls when one fails to incorporate aspects of physiological performance when predicting the consequences of climate change on biotic communities. We argue that by considering the mechanistic details of physiological performance within the context of biophysical ecology (engineering methods of heat, mass and momentum exchange applied to biological systems), such approaches will be better poised to predict where and when the impacts of climate change will most likely occur.