Temporal variation of thermal sensitivity to global warming: Acclimatization in the guitarist beetle, Megelenophorus americanus (Coleoptera: Tenebrionidae) from the Monte Desert

ARAGON-TRAVERSO, JUAN HECTOR; PIÑEIRO, MAURICIO; OLIVARES, JUAN PABLO SEGUNDO; SANABRIA, EDUARDO ALFREDO

COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY A-MOLECULAR AND INTEGRATIVE PHYSIOLOGY

ELSEVIER SCIENCE INC

Año: 2023

1095-6433

Global warming is a major threat to biodiversity, the increase in mean temperature plus the higher rate and intensity of heat waves can severely affect organisms by exposing them to temperatures beyond their tolerance limits. Desert ectotherms are particularly vulnerable due to their dependence on environmental temperatures in an extreme habitat. Thermal tolerance changes depending on environmental conditions, studying these fluctuations provides a better understanding of species susceptibility to global warming. Tenebrionids are successful desert-inhabiting ectotherm taxa because of a series of adaptations for heat tolerance and water loss. We studied the seasonal variation (acclimatization) of thermal tolerance in Megelenophorus americanus, a widely distributed species in the Monte Desert (Argentina). To do this, we measured environmental and operative temperatures: body temperature (Tb), soil temperature (Ts), air temperature (Ta), environmental temperature (Te) and maximum temperature (Tmax), and tolerance proxies volunteer thermal maximum (VTmax), Fluid release (FR) and critical thermal maximum (CTmax) in a population of M. americanus from San Juan province, Argentina from October to March (full activity season). We found that Ts and Ta are accurate predictors of Tb, suggesting thermoconformism. All tolerance proxies showed differences among months, suggesting a natural acclimatization process in situ. Insects were found operating beyond VTmax (thermal stress) but they were far from reaching CTmax under natural conditions. Organisms present different degrees of tolerance plasticity that should be considered when predicting potential impacts of climate change.