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Habitat modification and fragmentation are considered as some of the factors that drive organism distribution and host use diversification. Indigenous African stem borer pests are thought to have diversified their host ranges to include maize [Zea mays L.] and sorghum [Sorghum bicolor (L.) Moench] in response to their increased availability through extensive cultivation. However, management efforts have been geared towards reducing pest populations in the cultivated fields with few attempts to understand possible evolution of "new" pest species. Recovery and growing persistence of Busseola segeta Bowden on maize (Zea mays L.) in Kakamega called for studies on the role of wild host plants on the invasion of crops by wild borer species. A two-year survey was carried out in a small agricultural landscape along the edge of Kakamega forest (Kenya) to assess host range and population genetic structure of B. segeta. The larvae of B. segeta were found on nine different plant species with the majority occurring on maize and sorghum. Of forty cytochrome b haplotypes identified, twenty-three occurred in both wild and cultivated habitats. The moths appear to fly long distances across the habitats with genetic analyses revealing weak differentiation between hosts in different habitats (FST = 0.016; p = 0.015). However, there was strong evidence of variation in genetic composition between growing seasons in the wild habitat (FST = 0.060; p < 0.001) with emergence or disappearance of haplotypes between habitats. Busseola segeta is an example of a phytophagous insect that utilizes plants with a human induced distribution range, maize, but does not show evidence of host race formation or reduction of gene flow among populations using different hosts. However, B. segeta is capable of becoming an important pest in the area and the current low densities may be attributed to the general low infestation levels and presence of a wide range of alternative hosts in the area.

BACKGROUND:Understanding the mechanisms that influence the population dynamics and spatial genetic structure of the vectors of pathogens infecting humans is a central issue in tropical epidemiology. In view of the rapid changes in the features of landscape pathogen vectors live in, this issue requires new methods that consider both natural and human systems and their interactions. In this context, individual-based model (IBM) simulations represent powerful yet poorly developed approaches to explore the response of pathogen vectors in heterogeneous social-ecological systems, especially when field experiments cannot be performed. METHODOLOGY/PRINCIPAL FINDINGS:We first present guidelines for the use of a spatially explicit IBM, to simulate population genetics of pathogen vectors in changing landscapes. We then applied our model with Triatoma brasiliensis, originally restricted to sylvatic habitats and now found in peridomestic and domestic habitats, posing as the most important Trypanosoma cruzi vector in Northeastern Brazil. We focused on the effects of vector migration rate, maximum dispersal distance and attraction by domestic habitat on T. brasiliensis population dynamics and spatial genetic structure. Optimized for T. brasiliensis using field data pairwise fixation index (FST) from microsatellite loci, our simulations confirmed the importance of these three variables to understand vector genetic structure at the landscape level. We then ran prospective scenarios accounting for land-use change (deforestation and urbanization), which revealed that human-induced land-use change favored higher genetic diversity among sampling points. CONCLUSIONS/SIGNIFICANCE:Our work shows that mechanistic models may be useful tools to link observed patterns with processes involved in the population genetics of tropical pathogen vectors in heterogeneous social-ecological landscapes. Our hope is that our study may provide a testable and applicable modeling framework to a broad community of epidemiologists for formulating scenarios of landscape change consequences on vector dynamics, with potential implications for their surveillance and control.