Heat hardening in a tropical lizard: geographic variation explained by the predictability and variance in environmental temperatures. (29th December 2015) - Phillips, Ben L.; Muñoz, Martha M.; Hatcher, Amberlee; Macdonald, Stewart L.; Llewelyn, John; Lucy, Vanessa; Moritz, Craig
Summary: Over the coming decades, our planet will experience a dramatic increase in average temperatures and an increase in the variance around those temperatures leading to more frequent and harsher heat waves. These changes will impact most species and impose strong selection on physiological traits. Rapid acclimation is the most direct way for organisms to respond to such extreme events, but we currently have little understanding of how the capacity to mount such plastic responses evolves. Accordingly, there is some urgency to determine how the physiological response to high temperatures varies within species, and how this variation is driven by the environment. Here, we investigate heat‐hardening capacity – a rapid physiological response that confers a survival advantage under extreme thermal stress – across 13 populations of a rain forest lizard, Lampropholis coggeri, from the tropics of north‐eastern Australia. Our results reveal that heat hardening is constrained in these lizards by a hard upper thermal limit for locomotor function (approximately 43 °C). Further, hardening response shows strong geographic variation associated with thermal environment: lizards from more predictable and more seasonal thermal environments exhibited greater hardening compared with those from more stochastic and less seasonal habitats. This finding – that predictability in thermal variation influences hardening capacity – aligns closely with theoretical expectations. Our results suggest that tropical species may harbour adaptive variation in physiological plasticity that they can draw from in response to climate change, and this variation is spatially structured in locally adapted populations. Our results also suggest that, by using climatic data, we can predict which populations contain particular adaptive variants; information critical to assisted gene flow strategies. Abstract : Lay Summary