The impact of rising temperatures on biological systems is well-documented, particularly on coastal shores characterized by fluctuating temperatures. To study the effects of fluctuating temperatures on physiological performance, experiments often employ treatments that alternate between “blocks” of time exposed to minimum versus maximum temperatures. To test the efficacy of these approaches, we collected water temperatures from a mussel bed to drive 12-h field treatments and compared them to block treatments across different seasons. Our results showed that respiration rates for mussels under spring and fall temperatures were higher in the block compared to the field treatments. In contrast, mussels tested under summer temperatures showed higher rates under field versus block treatments. When simulating winter temperatures, rates in field and block treatments were similar. The thermal performance curves generated from the field and block data produced significantly different estimates of thermal optima, indicating a mismatch between lab-based temperature treatments and natural thermal regimes. The potential effects on physiological performance underscore the importance of using high-resolution temperature data and the need to ensure that the seasonal conditions being simulated in lab experiments match those being studied in the field.  

Field temperature data was collected via logger deployment (HOBO loggers). Respiration data was collected via lab experiments. Estimated parameters derived from thermal performance curves following the methods outlined in: Padfield, D., O'Sullivan, H., & Pawar, S. (2021). rTPC and nls. multstart: a new pipeline to fit thermal performance curves in R. Methods in Ecology and Evolution, 12(6), 1138-1143.