A generic weather-driven model to predict mosquito population dynamics applied to species of Anopheles, Culex and Aedes genera of southern France

Population of the temperate mosquito, Culex pipiens, decreases in response to habitat climatological changes in future

“…By incorporating the effect of diapause into the model, the population increase during autumn is suppressed because some active adults shift to the diapause state, and thus, the model output becomes consistent with the population trends observed in the field (Figure 2). The increasing trend observed in simulations for diapausing adults during autumn was consistent with that shown by Ezanno et al [2015] for the seasonal distribution of C. pipiens in France by using a population dynamics model incorporating diapause. Thus, incorporating the effect of diapause is essential for modeling mosquito population dynamics in temperate regions, even under current climate conditions.…”

“…The effect of soil moisture on larval carrying capacity was not strong, contrary to the positive effect referred in many studies [ Morin and Comrie , ; Tran et al ., ; Jia et al ., ]. The increasing and decreasing population levels obtained were similar to that reported in other studies on population dynamics models [ Ezanno et al ., ; Marini et al ., ]. However, a marked decrease in active adult mosquitoes was noted for populations under future climate conditions (Figure ), remarkably differing from the predictions obtained in previous studies [ Marini et al ., ].…”

“…The increasing trend observed in simulations for diapausing adults during autumn was consistent with that shown by Ezanno et al . [] for the seasonal distribution of C. pipiens in France by using a population dynamics model incorporating diapause. Thus, incorporating the effect of diapause is essential for modeling mosquito population dynamics in temperate regions, even under current climate conditions.…”

“…Cailly et al [2012] improved Anopheles spp. population model by incorporating the effect of diapause based on limited observation data; further, the diapause effect was incorporated into models for Aedes albopictus [Tran et al, 2013;Jia et al, 2016] and Culex pipiens [Ezanno et al, 2015;Marini et al, 2016]. However, the population dynamics incorporating diapause are not completely understood because few studies focus on diapause characteristics in each mosquito species, including photoperiod and temperature thresholds [e.g., Oda, 1971;Hawley et al, 1987;Pumpuni et al, 1992;Lacour et al, 2015].…”

Complementarity of empirical and process-based approaches to modelling mosquito population dynamics with Aedes albopictus as an example—Application to the development of an operational mapping tool of vector populations

“…Two main approaches are used to understand and predict mosquito population dynamics: i) process-based (or mechanistic) models describing biological knowledge within a mathematical or computational framework, and ii) empirical (or statistical) models, which try to find, from the observed data, a predictive function of the response variable (mosquito populations) based on a set of predictors within a statistical or a machine learning framework. Both approaches have been successfully applied to different mosquito species and geographical contexts [5][6][7][8][9][10][11][12][13][14][15][16][17], resulting in a better understanding of their distribution [5-8, 11, 12, 16] and dynamics [9,10,13,17,18] and the assessment of different mosquito control strategies [19,20]. However, most case studies only develop one of the two approaches (either empirical [5-8, 11, 12, 14, 16] or process-based [9,10,13,15,17] depending on the availability of data and knowledge), and do not compare the capacity of the two approaches to predict mosquito population dynamics.…”