Population Structure and Spatial Influence of Agricultural Variables on Hessian Fly Populations in the Southeastern United States

Abstract

Population structure dictates the evolution of each population, and thus, the species as a whole. Incorporating spatial variables with population genetic statistics allows for greater discovery beyond traditional population genetics alone and can inform management decisions. The understanding of population structure in Hessian fly, Mayetiola destructor (Say), a pest of wheat, has been limited in the past. We scored 14 microsatellite loci from 12 collections of Hessian fly in the southeastern United States. Through Bayesian clustering analysis, we found two major populations of Hessian fly covering the entire southeastern United States. We evaluated correlations between agriculturally significant spatial variables and population genetic differentiation to test if genetic structure has an ecological component in a wheat agro-ecosystem. Our results suggest the total amount of alternative host plants in the county may be driving some genetic differentiation. Although planting date may also be influential, geographic distance, mean annual temperature, and harvested wheat for grain do not seem to be contributing factors. The ecological or spatial component to population structure, however, may be minimal compared to factors such as genetic drift.

Population Structure and the Colonization Route of One of the Oldest North American Invasive Insects: Stories from the Worn Road of the Hessian Fly, Mayetiola destructor (Say)

“…In the current study, however, a higher K value was found, further refining the population genetic structure in the southeastern US and providing similar results as the higher K values (e.g. K = 4) in Morton et al [54]. These results suggest divergence between different regions with a higher level of gene flow within a region.…”

“…All collections fit into pseudo-regional populations, with the exception of FlSC and HoMS, which stood independently as their own population. With respect to the populations in the southeastern US, overall similar results were found previously [54]; however, the additional collections added to the resolution of the population genetic structure. For example, Morton et al [54] found K = 2 in the southeastern populations, although there was more structure when looking at a higher K value.…”

“…With respect to the populations in the southeastern US, overall similar results were found previously [54]; however, the additional collections added to the resolution of the population genetic structure. For example, Morton et al [54] found K = 2 in the southeastern populations, although there was more structure when looking at a higher K value. In the current study, however, a higher K value was found, further refining the population genetic structure in the southeastern US and providing similar results as the higher K values (e.g.…”

“…These results suggest divergence between different regions with a higher level of gene flow within a region. The population genetic structure of North America very closely matches the regional association of wheat class data (http://webarchives.cdlib.org/sw15d8pg7m/http:/ers.usda.gov/Briefing/Wheat/maps.htm), as suggested by Black et al [12] and Morton et al [54]. This suggests that populations could be closely associated with a local adaptation to a particular wheat class, although this hypothesis remains to be explicitly tested.…”

The evolution of Hessian fly from the Old World to the New World: Evidence from molecular markers

“…Microsatellites (SSRs) and SNPs have been used successfully to characterize populations in insects (Behura, ; Morton et al ., ). Microsatellites have the advantages of rapid evolution, frequently multiple alleles, and likely selective neutrality (Li et al ., ), but with these advantages come a high likelihood of evolutionary reversals (homoplasy) in allele size (van Zijll de Jong et al ., ) and problems in scoring the alleles accurately (Selkoe & Toonen, ).…”