There are thousands of species of mosquitoes, but only a handful of these species carry pathogens that cause human diseases. Here, we study two species, Aedes albopictus and Aedes aegypti, which transmit infections such as dengue, Zika, Mayaro virus, and La Crosse virus. Curtailing these diseases is a good reason to consider control of mosquito populations. However, mosquitoes are quite hardy and spraying of pesticides is typically a short-term solution. Thus, more long-term solutions require careful thought about mosquito populations, including early juvenile aquatic stages: egg, larva, and pupa. In this dissertation, we examine the factors that affect the dynamics of aquatic stages by creating mathematical models. The goal is to assess what key biological features most impact the total population. Both Aedes albopictus and Aedes aegypti lay eggs in small containers, producing limitations on space and food. We investigate how restricting resources changes development time, survival to adulthood, and body mass at emergence. The interactions between these changes are complicated, so to disentangle their effects we create three different mathematical models. The first model is discrete in time and focuses on the best way to incorporate the influence of larval density. We compare the impact of larval density by inputting seven different functional forms altering survival and development time. Larval density used in the model is determined from the average of the population size over the past one to thirty-six days. The second model is also discrete in time but focuses on the interaction between survival, development time, and mass. This model considers three levels of mass. Here, we use the density-dependent function determined from our first model and fit the maximum value for development time from experimental data. Survival values are fit using constants and a density-dependent function. Finally, growth is built in as a function of food. Food decreases at each time point as a function of the total larvae in the environment. We compare between model formulations with Akaike information criterion. The third model examines the ramifications of constricting resources on growth verses death. We employ a partial differential equation that has three independent variables: time, age, and mass. We find that density dependence is highly influential in the maturation of mosquitoes, and it is more essential to include its impacts on development time than on survival. These findings can be incorporated into a larger framework of disease dynamics, and give insight into better control of mosquitoes and disease spread. / Doctor of Philosophy / There are thousands of species of mosquitoes, but only a handful of these species spread human diseases. We specifically study mosquitoes that transmit diseases such as dengue and Zika, which plague large portions of the world. One way to reduce disease spread by mosquitoes is to eliminate the mosquito population, but mosquitoes are becoming resistant to commonly used insecticides. Thus, additional ways to combat mosquitoes are needed. To do so requires a better understanding of how mosquito populations change. This necessitates incorporating information from all life stages of the mosquito, including the juvenile stages that live in the water. In this dissertation, we examine various factors that affect the population size and characteristics of young mosquitoes by creating mathematical models. The goal is to assess what key biological features most impact the population. As young mosquitoes live in aquatic environments, there are limitations on space and food. We investigate how restricting resources changes the time it takes for mosquitoes to develop into adults, how many survive to adulthood, and what their body mass is as new adults. These outcomes interact in complicated way. To disentangle this, we create three different mathematical models. The first model focuses on the best way to incorporate the influence of limiting space or density on population size. The second model focuses on the interaction between mosquito body mass, survival, and time spent as a juvenile. The third model examines how resources alter growth and death and the ensuing mass of mosquitoes. Models are fit to experimental data and validated based on how accurately they describe known patterns. We find that population density is highly influential in the maturation of juvenile mosquitoes and its most important effect is on time spent as a juvenile mosquito. By correlating growth of juvenile mosquitoes to density and resources, our second model is better able to reproduce data. These findings provide important understanding on mosquito populations, which provides insight into how to better control mosquitoes and the diseases they spread.

<p>New and old mosquito-borne diseases have emerged and re-emerged in temperate regions over the recent past, but an understanding of mosquito population dynamics, a fundamental step toward disease control, remains elusive. In particular, we are still lacking reliable predictive models of mosquito abundance in temperate areas due to the subtle links between the fluctuation of mosquito population and highly heterogeneous environmental drivers. Hence, this doctoral dissertation presents an interdisciplinary approach towards an improved understanding and prediction of the fluctuations in mosquito abundance in temperate regions. In the first part of this dissertation a hierarchical Gompertz-based model is used to assess the relative importance of endogenous (density dependence) and exogenous (environmental forcings) controls and their interactions in regulating the dynamics of a West Nile Virus vector (Culex pipiens) in the Po River delta in Italy. The results clearly detect the effects of density-dependence in the observed population dynamics for the mosquito species analyzed and highlight the controls exerted by environmental forcings and habitat conditions. Subsequently, the characteristic scales of temporal variability in mosquito populations, and the representativeness of observations at different sampling resolutions, are investigated using a 10 year daily mosquito sample from Brunswick County, North Carolina. The species present in the sample (among which Aedes vexans and Culiseta melanura are addressed in greater detail, as vectors of East Equine Encephalitis and West Nile Virus) are investigated using a combination of time series analysis, individual based simulations, and density-dependent modeling approaches. Significant population fluctuations with characteristic periodicity between 2 days and several years are found in response to different regulation mechanisms. In particular, the observed fast fluctuations are importantly determined by a varying mosquito activity, rather than by reproduction/mortality processes, driven by rapid changes in meteorological conditions. Finally, in the third part of this study, a state space reconstruction (SSR) approach is used to understand how the predictability of mosquito abundance varies with aggregation time scale and with the prediction horizon, and how much can the prediction of mosquito abundance be improved by using daily observations compared to the commonly used once-per-week samples. The results show that the predictability of mosquito abundance decreases as the time scale of the models increases from one week to one month, while the predictability of per capita growth rate increases together with the modeling scale. It is also shown that the prediction of mosquito per capita growth rate can be improved using daily abundance observations. Furthermore, many mosquito models compare the observed and predicted abundance as a measure of model performance. However, my results suggest that short term forecasts of mosquito abundance may appear to have a significant capability due to the positive autocorrelation between abundance in subsequent time steps, even when the model's ability to predict the abundance change is low. Model capability should thus be evaluated comparing observed and modelled per capita rates of change.</p> / Dissertation