Background: Aedes albopictus and Culex pipiens larvae reared in the same breeding site compete for resources, with an asymmetrical outcome that disadvantages only the latter species. The impact of these interactions on the overall ecology of these two species has not yet been assessed in the natural environment. In the present study, the temporal patterns of adult female mosquitoes from both species were analysed in north-eastern Italy, and substantial temporal shifts between abundance curves of Cx. pipiens and Ae. albopictus were observed in several sites. To understand which factors can drive the observed temporal shifts, we developed a mechanistic model that takes explicitly into account the effect of temperature on the development and survival of all mosquito stages. We also included into the model the effect of asymmetric interspecific competition, by adding a mortality term for Cx. pipiens larvae proportional to the larval abundance of Ae. albopictus within the same breeding site. Model calibration was performed through a Markov Chain Monte Carlo approach using weekly capture data collected in our study sites during 2014 and 2015.
Results: In almost half of observation sites, temporal shifts were due to competition, with an early decline of Cx. pipiens caused by the concurrent rise in abundance of its competitor, and this effect was enhanced by higher abundance of both species. We estimate that competition may reduce Cx. pipiens abundance in some sites by up to about 70%. However, in some cases temporal shifts can also be explained in the absence of competition between species resulting from a "temporal niche" effect, when the optimal fitness to environmental conditions for the two species are reached at different times of the year.
Conclusions: Our findings demonstrate the importance of considering ecological interactions and, in particular, competition between mosquito species in temperate climates, with important implications for risk assessment of mosquito transmitted pathogens, as well as the implementation of effective control measures.
Keywords: Computational model; Mosquito population dynamics; Species interaction; Temporal shift; Vector abundance.