The Temporal Spectrum of Adult Mosquito Population Fluctuations: Conceptual and Modeling Implications

Abstract

An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks) are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month) observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month) environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual) mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the abundance of the underlying population.

The predictability of mosquito abundance from daily to monthly timescales

“…This may be due to the fact that observed daily abundance can be significantly affected by uncertainties (e.g., mosquito activity can significantly change apparent abundance with no change in the underlying population; Jian et al. ). However, adding daily information (in the abundance, Model 6, or in the rainfall, Model 7) to the weekly aggregated model modestly reduced the prediction errors (Table ).…”

“…, Jian et al. ). This observation suggests the inclusion in the SSR of current and historical mosquito abundance, as well as of past and present values of the environmental forcings (temperature, rainfall, and day length).…”

“…Details about the mosquito and weather dataset and about the species studied can be found in Jian et al. ().…”

“…, Jian et al. ). Thus, we systematically explored the inclusion of current and past values of observed precipitation (P), current values of temperature (T), and day length (D, computed as described in Allen et al.…”

“…, Jian et al. ). Furthermore, the formulation of a comparative synthesis of existing studies on mosquito population prediction is hampered by the use of performance metrics with low sensitivity (affected by highly correlated observations) and by a lack of systematic evaluations of mosquito abundance predictability as a function of observational frequency and prediction lead time.…”