Mosquito population dynamics is shaped by the interaction among larval density, season, and land use.

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.

Para poder predecir la distribución y abundancia de las poblaciones de mosquitos y la transmisión potencial de patógenos a humanos, es crucial comprender cómo factores abióticos y bióticos clave para el éxito reproductivo y la dinámica poblacional de los mosquitos interactúan a escalas relevantes. Sin embargo, los estudios que han investigado los efectos de variables ambientales en las características demográficas de los mosquitos han considerado su efecto de forma aislada o en experimentos de laboratorio bajo condiciones ambientales constantes que, a menudo, no reflejan lo que ocurre en el campo. Para abordar estas limitaciones, llevamos a cabo un experimento de semi-campo en Athens, Georgia, utilizando el mosquito invasor tigre asiático (Aedes albopictus). Seleccionamos nueve sitios que abarcaban variaciones naturales en la superficie impermeable y cobertura vegetal para explorar los efectos del microclima (temperatura y humedad) en los mosquitos. También manipulamos la densidad de larvas de tigre asiático en dos experimentos que fueron realizados en el verano y otoño. Evaluamos los efectos de la cobertura vegetal, la densidad de larvas, la temporada climática, y la interacción entre estas variables en la proporción de hembras que emergieron, el tiempo de desarrollo de las larvas, el tamaño al momento de la emergencia, y el crecimiento demográfico per cápita previsto (éxito reproductivo). Encontramos efectos significativos de la densidad de larvas, la variación de la cobertura vegetal y la estación del año en todas las variables de respuesta. Más notablemente, observamos un fuerte efecto de la interacción entre la temporada climática y la densidad de larvas en todas las variables de respuesta, incluyendo una disminución no intuitiva en el tiempo de desarrollo con el aumento de la competencia intraespecífica en el otoño. Nuestro estudio evidencia que ignorar la interacción entre variables abióticas y bióticas podría reducir la exactitud y precisión de los modelos utilizados para predecir las dinámicas de las poblaciones de mosquitos, y por tanto, de la transmisión de patógenos. Esto, especialmente en modelos que infieren estas dinámicas a escalas espaciales más finas, en las cuales ocurre la transmisión y el control.

Land cover affects microclimate and temperature suitability for arbovirus transmission in an urban landscape.

The emergence of mosquito-transmitted viruses poses a global threat to human health. Combining mechanistic epidemiological models based on temperature-trait relationships with climatological data is a powerful technique for environmental risk assessment. However, a limitation of this approach is that the local microclimates experienced by mosquitoes can differ substantially from macroclimate measurements, particularly in heterogeneous urban environments. To address this scaling mismatch, we modeled spatial variation in microclimate temperatures and the thermal potential for dengue transmission by Aedes albopictus across an urban-to-rural gradient in Athens-Clarke County GA. Microclimate data were collected across gradients of tree cover and impervious surface cover. We developed statistical models to predict daily minimum and maximum microclimate temperatures using coarse-resolution gridded macroclimate data (4000 m) and high-resolution land cover data (30 m). The resulting high-resolution microclimate maps were integrated with temperature-dependent mosquito abundance and vectorial capacity models to generate monthly predictions for the summer and early fall of 2018. The highest vectorial capacities were predicted for patches of trees in urban areas with high cover of impervious surfaces. Vectorial capacity was most sensitive to tree cover during the summer and became more sensitive to impervious surfaces in the early fall. Predictions from the same models using temperature data from a local meteorological station consistently over-predicted vectorial capacity compared to the microclimate-based estimates. This work demonstrates that it is feasible to model variation in mosquito microenvironments across an urban-to-rural gradient using satellite Earth observations. Epidemiological models applied to the microclimate maps revealed localized patterns of temperature suitability for disease transmission that would not be detectable using macroclimate data. Incorporating microclimate data into disease transmission models has the potential to yield more spatially precise and ecologically interpretable metrics of mosquito-borne disease transmission risk in urban landscapes.