Thermal tolerance and climate warming sensitivity in tropical snails

Abstract

Tropical ectotherms are predicted to be especially vulnerable to climate change because their thermal tolerance limits generally lie close to current maximum air temperatures. This prediction derives primarily from studies on insects and lizards and remains untested for other taxa with contrasting ecologies. We studied the HCT (heat coma temperatures) and ULT (upper lethal temperatures) of 40 species of tropical eulittoral snails (Littorinidae and Neritidae) inhabiting exposed rocky shores and shaded mangrove forests in Oceania, Africa, Asia and North America. We also estimated extremes in animal body temperature at each site using a simple heat budget model and historical (20years) air temperature and solar radiation data. Phylogenetic analyses suggest that HCT and ULT exhibit limited adaptive variation across habitats (mangroves vs. rocky shores) or geographic locations despite their contrasting thermal regimes. Instead, the elevated heat tolerance of these species (HCT=44.5±1.8°C and ULT=52.1±2.2°C) seems to reflect the extreme temperature variability of intertidal systems. Sensitivity to climate warming, which was quantified as the difference between HCT or ULT and maximum body temperature, differed greatly between snails from sunny (rocky shore; Thermal Safety Margin, TSM=-14.8±3.3°C and -6.2±4.4°C for HCT and ULT, respectively) and shaded (mangrove) habitats (TSM=5.1±3.6°C and 12.5±3.6°C). Negative TSMs in rocky shore animals suggest that mortality is likely ameliorated during extreme climatic events by behavioral thermoregulation. Given the low variability in heat tolerance across species, habitat and geographic location account for most of the variation in TSM and may adequately predict the vulnerability to climate change. These findings caution against generalizations on the impact of global warming across ectothermic taxa and highlight how the consideration of nonmodel animals, ecological transitions, and behavioral responses may alter predictions of studies that ignore these biological details.