A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density.

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

Aggregation and a strong Allee effect in a cooperative outbreak insect.

Most species that are negatively impacted when their densities are low aggregate to minimize this effect. Aggregation has the potential to change how Allee effects are expressed at the population level. We studied the interplay between aggregation and Allee effects in the mountain pine beetle (Dendroctonus ponderosae Hopkins), an irruptive bark beetle that aggregates to overcome tree defenses. By cooperating to surpass a critical number of attacks per tree, the mountain pine beetle is able to breach host defenses, oviposit, and reproduce. Mountain pine beetles and Hymenopteran parasitoids share some biological features, the most notable of which is obligatory host death as a consequence of parasitoid attack and development. We developed spatiotemporal models of mountain pine beetle dynamics that were based on the Nicholson-Bailey framework but which featured beetle aggregation and a tree-level attack threshold. By fitting our models to data from a local mountain pine beetle outbreak, we demonstrate that due to aggregation, attack thresholds at the tree level can be overcome by a surprisingly low ratio of beetles per susceptible tree at the stand level. This results confirms the importance of considering aggregation in models of organisms that are subject to strong Allee effects.