Low Genetic Variability in Bemisia tabaci MEAM1 Populations within Farmscapes of Georgia, USA.

Bemisia tabaci is a whitefly species complex comprising important phloem feeding insect pests and plant virus vectors of many agricultural crops. Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED) are the two most invasive members of the B. tabaci species complex worldwide. The diversity of agroecosystems invaded by B. tabaci could potentially influence their population structure, but this has not been assessed at a farmscape level. A farmscape in this study is defined as heterogenous habitat with crop and non-crop areas spanning ~8 square kilometers. In this study, mitochondrial COI gene (mtCOI) sequences and six microsatellite markers were used to examine the population structure of B. tabaci MEAM1 colonizing different plant species at a farmscape level in Georgia, United States. Thirty-five populations of adult whiteflies on row and vegetable crops and weeds across major agricultural regions of Georgia were collected from fifteen farmscapes. Based on morphological features and mtCOI sequences, five species/cryptic species of whiteflies (B. tabaci MEAM1, B. tabaci MED, Dialeurodes citri, Trialeurodes abutiloneus, T. vaporariorum) were found. Analysis of 102 mtCOI sequences revealed the presence of a single B. tabaci MEAM1 haplotype across farmscapes in Georgia. Population genetics analyses (AMOVA, PCA and STRUCTURE) of B. tabaci MEAM1 (microsatellite data) revealed only minimal genetic differences among collected populations within and among farmscapes. Overall, our results suggest that there is a high level of gene flow among B. tabaci MEAM1 populations among farmscapes in Georgia. Frequent whitefly population explosions driven by a single or a few major whitefly-suitable hosts planted on a wide spatial scale may be the key factor behind the persistence of a single panmictic population over Georgia's farmscapes. These population structuring effects are useful for delineating the spatial scale at which whiteflies must be managed and predicting the speed at which alleles associated with insecticide resistance might spread.