Applying spatial analysis of genetic and environmental data to predict connection corridors to the New World screwworm populations in South America

Acta Trop. 2014 Oct:138 Suppl:S34-41. doi: 10.1016/j.actatropica.2014.04.003. Epub 2014 Apr 14.

Abstract

The myiasis causing New World screwworm (NWS) fly is responsible for substantial losses to livestock breeders in the Americas. Due to the negative impact of the NWS fly in animal health, expansion of successful NWS fly eradication programmes is under discussion. However, the effects of geography and environmental diversity on NWS population structure and migration patterns need to be assessed before any political decision is made to implement such a programme. We present a GIS tool to construct potential connection corridors among sampling localities based on genetic and environmental data. We integrate, through a home-made python script, a friction raster based on a Maxent niche model and the pairwise ΦST statistic. Among 38 NWS fly sampling localities from South America, we find a high population connectivity among the sampling localities from the south of the Amazon region. The region along the Atlantic Ocean was identified as the most probable migration corridor between the north (NAG) and the south (SAG) of the Amazon region. The approach highlighted previously undetected population structure within NAG showing low to medium connectivity through the Andes, correlating with current understanding of NWS fly migration in South America. Also, the approach is flexible, allowing future research to incorporate other niche simulations and genetic differentiation metrics. With this flexibility, the tool could become part of any AW-IPM by helping to target regions for control.

Keywords: Cochliomyia hominivorax; Ecological niche Modelling; GIS; Myiasis; Pest control; Phylogeography.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animal Migration
  • Animals
  • Biota
  • Diptera / classification*
  • Diptera / genetics*
  • Diptera / growth & development
  • Geographic Information Systems
  • Models, Statistical
  • Phylogeography*
  • South America
  • Spatial Analysis