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Published on: January 27, 2019
Thermal performance of the Chagas disease vector, Triatoma infestans, under thermal variability
Sabrina Clavijo-Baquet1, Grisel Cavieres2, Avia González2
1Laboratorio de Etología, Ecología y Evolución, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay.
Abstract:
Vector-borne diseases (VBD) are particularly susceptible to climate change because most of the diseases' vectors are ectotherms, which themselves are susceptible to thermal changes. The Chagas disease is one neglected tropical disease caused by the protozoan parasite, Trypanosoma cruzi. One of the main vectors of the Chagas disease in South America is Triatoma infestans, a species traditionally considered to be restricted to domestic or peridomestic habitats, but sylvatic foci have also been described along its distribution. The infestation of wild individuals, together with the projections of environmental changes due to global warming, urge the need to understand the relationship between temperature and the vector's performance. Here, we evaluated the impact of temperature variability on the thermal response of T. infestans. We acclimated individuals to six thermal treatments for five weeks to then estimate their thermal performance curves (TPCs) by measuring the walking speed of the individuals. We found that the TPCs varied with thermal acclimation and body mass. Individuals acclimated to a low and variable ambient temperature (18°C ± 5°C) exhibited lower performances than those individuals acclimated to an optimal temperature (27°C ± 0°C); while those individuals acclimated to a low but constant temperature (18°C ± 0°C) did not differ in their maximal performance from those at an optimal temperature. Additionally, thermal variability (i.e., ± 5°C) at a high temperature (30°C) increased performance. These results evidenced the plastic response of T. infestans to thermal acclimation. This plastic response and the non-linear effect of thermal variability on the performance of T. infestans posit challenges when predicting changes in the vector's distribution range under climate change.
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