The relative power of genome scans to detect local adaptation depends on sampling design and statistical method

Although genome scans have become a popular approach towards understanding the genetic basis of local adaptation, the field still does not have a firm grasp on how sampling design and demographic history affect the performance of genome scans on complex landscapes. To explore these issues, we compared 20 different sampling designs in equilibrium (i.e. island model and isolation by distance) and nonequilibrium (i.e. range expansion from one or two refugia) demographic histories in spatially heterogeneous environments. We simulated spatially complex landscapes, which allowed us to exploit local maxima and minima in the environment in 'pair' and 'transect' sampling strategies. We compared F(ST) outlier and…

• VP
  Virginia Polytechnic Institute and State University
• GC
  Genome Canada
• FG
  Forest Genetics Council of British Columbia
• GB
  Genome British Columbia
• UO
  University of British Columbia
• AI
  Alberta Innovates Bio Solutions
• UO
  University of California, Davis
• NS
  Natural Sciences and Engineering Research Council of Canada