Purdue University Graduate School
Schraidt_MScThesis_Final.pdf (1.7 MB)

Population Connectivity in Lake Michigan Yellow Perch

Download (1.7 MB)
posted on 2020-12-09, 15:33 authored by Claire SchraidtClaire Schraidt

Yellow perch (Perca flavescens) are an ecologically and economically important species in the Great Lakes. In Lake Michigan, there is substantial interest in restoring Yellow perch to their historic abundance. Populations in Lake Michigan began to decline dramatically in the late 1980s and, despite management efforts, have not rebounded. Understanding stock structure is imperative for implementing successful management strategies, but assessing population structure in yellow perch is particularly challenging. Yellow perch disperse on surface currents during a 30-40 day larval period where dispersal is difficult to observe directly and varies interannually. In order to better understand yellow perch population structure and connectivity, we sequenced 960 individuals, collected at 20 sampling locations across Lake Michigan using restriction site-associated DNA sequencing (RADseq). We used 3337 single nucleotide polymorphisms (SNPs) to observe genetic differences between populations and paired these findings with a Lagrangian particle tracking model to explain patterns of connectivity and gene flow. We showed that Green Bay and the main basin of Lake Michigan are genetically distinct populations. Within these two genetic groups, drivers for population structure appear to be very different. Green Bay shows distinct populations across its 150 kilometers, consistent with isolation by distance. These populations show lower global allelic richness and heterozygosity than the main basin. In contrast, the main basin shows low but significant genetic distance (measured as pairwise FST) and higher allelic richness and observed heterozygosity, appearing to behave more like a marine system. To validate this observation, we paired these findings with a Lagrangian particle tracking model to explain patterns of connectivity and gene flow and found that distances derived from these particle tracking models were significantly correlated with the genetic distances observed between main basin populations.


Great Lakes Fishery Commission 2018_CHR_44072


Degree Type

  • Master of Science


  • Forestry and Natural Resources

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Mark Christie

Additional Committee Member 2

Tomas Höök

Additional Committee Member 3

Paris Collingsworth

Usage metrics



    Ref. manager