Hilltopping influences spatial dynamics in a patchy population of tiger moths

Dispersal is a key driver of spatial population dynamics. Dispersal behavior may be shaped by many factors, such as mate-finding, the spatial distribution of resources, or wind and currents, yet most models of spatial dynamics assume random dispersal. We examined the spatial dynamics of a day-flying moth species (Arctia virginalis) that forms mating aggregations on hilltops (hilltopping) based on long-term adult and larval population censuses. Using time-series models, we compared spatial population dynamics resulting from empirically-founded hilltop-based connectivity indices, and modeled the interactive effects of temperature, precipitation, and density dependence. Model comparisons supported hilltop-based connectivity metrics over random connectivity, suggesting an effect of hilltopping behavior on dynamics. We also found strong interactive effects of temperature and precipitation on dynamics. Simulations based on fitted time series models showed lower patch occupancy and regional synchrony, and higher colonization and extinction rates when hilltopping was included, with potential implications for the probability of persistence of the patch network. Overall, our results show the potential for dispersal behavior to have important effects on spatial population dynamics and persistence, and we advocate inclusion of such non-random dispersal in metapopulation models.

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Modeling and simulation of the spatial population dynamics of the Aedes aegypti mosquito with an insecticide application

Parasites & Vectors ◽

10.1186/s13071-020-04426-2 ◽

2020 ◽

Vol 13 (1) ◽

Author(s):

Monalisa R. Silva ◽

Pedro H. G. Lugão ◽

Grigori Chapiro

Keyword(s):

Population Dynamics ◽

Partial Differential Equations ◽

Aedes Aegypti ◽

Differential Equations ◽

Large Scale ◽

Spatial Dynamics ◽

Partial Differential ◽

Insecticide Application ◽

Spatial Population ◽

Spatial Population Dynamics

Abstract Background The Aedes aegypti mosquito is the primary vector for several diseases. Its control requires a better understanding of the mosquitoes’ live cycle, including the spatial dynamics. Several models address this issue. However, they rely on many hard to measure parameters. This work presents a model describing the spatial population dynamics of Aedes aegypti mosquitoes using partial differential equations (PDEs) relying on a few parameters. Methods We show how to estimate model parameter values from the experimental data found in the literature using concepts from dynamical systems, genetic algorithm optimization and partial differential equations. We show that our model reproduces some analytical formulas relating the carrying capacity coefficient to experimentally measurable quantities as the maximum number of mobile female mosquitoes, the maximum number of eggs, or the maximum number of larvae. As an application of the presented methodology, we replicate one field experiment numerically and investigate the effect of different frequencies in the insecticide application in the urban environment. Results The numerical results suggest that the insecticide application has a limited impact on the mosquitoes population and that the optimal application frequency is close to one week. Conclusions Models based on partial differential equations provide an efficient tool for simulating mosquitoes’ spatial population dynamics. The reduced model can reproduce such dynamics on a sufficiently large scale.

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