Long-term monitoring shows that the poleward range edges of intertidal biota have shifted by as much as 50 km per decade, faster than most recorded shifts of terrestrial species. Although most studies have concentrated on species-range edges, recent work emphasizes how modifying factors such as regional differences in the timing of low tide can overwhelm large-scale climatic gradients, leading to a mosaic of environmental stress. We discuss how changes in the mean and variability in climatic regimes, as modified by local and regional factors, can lead to complex patterns of species distribution rather than simple range shifts. We describe how ecological forecasting may be used to generate explicit hypotheses regarding the likely impacts of different climatic change scenarios on the distribution of intertidal species and how related hindcasting methods can be used to evaluate changes that have already been detected. These hypotheses can then be tested over a hierarchy of temporal and spatial scales using coupled field and laboratory-based approaches.

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.

Thermal stress has been considered to be among the most important determinants of organismal distribution in the rocky intertidal zone. Yet our understanding of...

▪ Abstract 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.