Toward predicting community-level effects of climate: relative temperature scaling of metabolic and ingestion rates

Predicting the effects of climate change on ecological communities requires an understanding of how environmental factors influence both physiological processes and species interactions. Specifically, the net impact of temperature on community structure depends on the relative response of physiological energetic costs (metabolism) and energetic gains (ingestion of resources) that mediate the flow of energy throughout a food web. However, the relative temperature scaling of metabolic and ingestion rates have rarely been measured for multiple species within an ecological assemblage and it is not known how, and to what extent, these relative scaling differences vary among species. To investigate the relative influence of these processes, I measured the temperature scaling of metabolic and ingestion rates for a suite of rocky intertidal species using a multiple regression experimental design. I compared oxygen consumption rates (as a proxy for metabolic rate) and ingestion rates by estimating the temperature scaling parameter of the universal temperature dependence (UTD) model, a theoretical model derived from first principles of biochemical kinetics and allometry. The results show that consumer metabolic rates (energetic costs) tend to be more sensitive to temperature than ingestion rates (energetic gains). Thus, as temperature increases, metabolic rates tend to increase faster relative to ingestion rates, causing the overall energetic efficiencies of these rocky intertidal invertebrates to decline. Metabolic and ingestion rates largely scaled in accordance with the UTD model; however, nonlinearity was evident in several cases, particularly at higher temperatures, in which alternative models were more appropriate. There are few studies where multiple rate dependencies are measured on multiple species from the same ecological community. These results indicate that there may be general patterns across species in the temperature scaling of biological rates, with important implications for forecasting temperature effects on ecological communities.