Mosquito dispersal in context

Mosquito dispersal plays an important role in mosquito ecology and mosquito-borne pathogen transmission. While reaction-diffusion and patch-based models with simple flux assumptions for emigration have played a predominant role in modeling mosquito dispersal, mosquito behavioral ecology – in particular, the process of searching for resources – is usually ignored by diffusion-based models. We thus set out to analyze mosquito movement using highly mimetic models, to see what we could learn from a different approach. Here, we present two behavioral state microsimulation models, in which mosquitoes are in behavioral states and search for required resources, which are distributed on a landscape. Models of this sort are laborious and challenging to work with, so we developed ramp.micro , an R package to build, solve, analyze, and visualize behavioral state microsimulation models for mosquitoes. Mosquito population dispersal is an emergent feature in these complex systems, so we developed new methods to describe and understand it. We show that population structure might not be revealed by a crude analysis of observed mosquito movement patterns, unless it can somehow account for sequences of flights for mosquitoes in behavioral states trying to accomplish a goal. We also show that even when resources are distributed randomly and uniformly, mosquito populations tend to form highly spatially structured communities. We also show that some heterogeneity in mosquito population densities is attributed to features of a network defined by searching and the spatial distribution of resources. These models highlight the importance of understanding mosquito behavioral states and resource availability in understanding mosquito population dispersal, and they point to the importance of local context. Motivated by these dynamics, spatial models for mosquito ecology and mosquito-borne pathogen transmission would benefit from considering resource availability as a factor affecting mosquito movement and dispersal.