Photosynthetic response to a winter heatwave in leading and trailing edge populations of the intertidal red alga Corallina officinalis (Rhodophyta)

Abstract

Abstract Marine heatwaves (MHWs) caused by anthropogenic climate change are becoming a key driver of change at the ecosystem level. Thermal conditions experienced by marine organisms across their distribution, particularly towards the equator, are likely to approach their physiological limits, resulting in extensive mortality and subsequent changes at the population level. Populations at the margins of their species’ distribution are thought to be more sensitive to climate-induced environmental pressures than central populations, but our understanding of variability in fitness-related physiological traits in trailing versus leading-edge populations is limited. In a laboratory simulation study, we tested whether two leading (Iceland) and two trailing (Spain) peripheral populations of the intertidal macroalga Corallina officinalis display different levels of maximum potential quantum efficiency (Fv/Fm) resilience to current and future winter MHWs scenarios. Our study revealed that ongoing and future local winter MHWs will not negatively affect leading-edge populations of C. officinalis , which exhibited stable photosynthetic efficiency throughout the study. Trailing edge populations showed a positive though non-significant trend in photosynthetic efficiency throughout winter MHWs exposure. Poleward and equatorward populations did not produce significantly different results, with winter MHWs having no negative affect on Fv/Fm of either population. Additionally, we found no long-term regional or population-level influence of a winter MHWs on this species’ photosynthetic efficiency. Thus, we found no statistically significant difference in thermal stress responses between leading and trailing populations. Nonetheless, C. officinalis showed a trend towards higher stress responses in southern than northern populations. Because responses rest on a variety of local population traits, they are difficult to predict based solely on thermal pressures.