Mosquito population dynamics is shaped by the interaction among larval density, season, and land use
Solano, N.; Herring, E. C.; Hintz, C. W.; Newberry, P. M.; Schatz, A. M.; Walker, J. W.; Osenberg, C. W.; Murdock, C. C.
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ABSTRACT (English)Understanding how variation in key abiotic and biotic factors interact at spatial scales relevant for mosquito fitness and population dynamics is crucial for predicting current and future mosquito distributions and abundances, and the transmission potential for human pathogens. However, studies investigating the effects of environmental variation on mosquito traits have investigated environmental factors in isolation or in laboratory experiments that examine constant environmental conditions that often do not occur in the field. To address these limitations, we conducted a semi-field experiment in Athens, Georgia using the invasive Asian tiger mosquito (Aedes albopictus). We selected nine sites that spanned natural variation in impervious surface and vegetation cover to explore effects of the microclimate (temperature and humidity) on mosquitoes. On these sites, we manipulated conspecific larval density at each site. We repeated the experiment in the summer and fall. We then evaluated the effects of land cover, larval density, and time of season, as well as interactive effects, on the mean proportion of females emerging, juvenile development time, size upon emergence, and predicted per capita population growth (i.e., fitness). We found significant effects of larval density, land cover, and season on all response variables. Of most note, we saw strong interactive effects of season and intra-specific density on each response variable, including a non-intuitive decrease in development time with increasing intra-specific competition in the fall. Our study demonstrates that ignoring the interaction between variation in biotic and abiotic variables could reduce the accuracy and precision of models used to predict mosquito population and pathogen transmission dynamics, especially those inferring dynamics at finer-spatial scales across which transmission and control occur.
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