2 Works

Data from: Frequency-dependence shapes the adaptive landscape of imperfect Batesian mimicry

Susan D. Finkbeiner, Patricio A. Salazar, Sofia Nogales, Cassidi E. Rush, Adriana D. Briscoe, Ryan I. Hill, Marcus R. Kronforst, Keith R. Willmott & Sean P. Mullen
Despite more than a century of biological research on the evolution and maintenance of mimetic signals, the relative frequencies of models and mimics necessary to establish and maintain Batesian mimicry in natural populations remains understudied. Here we investigate the frequency-dependent dynamics of imperfect Batesian mimicry, using predation experiments involving artificial butterfly models. We use two geographically distinct populations of Adelpha butterflies that vary in their relative frequencies of a putatively defended model (Adelpha iphiclus) and...

Data from: Testing the adaptive hypothesis of Batesian mimicry among hybridizing North American admiral butterflies

Evan Breaux Kristiansen, Susan D. Finkbeiner, Ryan Isaac Hill, Louis Prusa & Sean Patrick Mullen
Batesian mimicry is characterized by phenotypic convergence between an unpalatable model and a palatable mimic. However, because convergent evolution may arise via alternative evolutionary mechanisms, putative examples of Batesian mimicry must be rigorously tested. Here we used artificial butterfly facsimiles (N=4000) to test the prediction that 1) palatable Limenitis lorquini butterflies should experience reduced predation when in sympatry with their putative model, Adelpha californica, 2) protection from predation on L. lorquini should erode outside of...

Registration Year

  • 2018

Resource Types

  • Dataset


  • University of Chicago
  • University of the Pacific
  • Boston University
  • University of Florida
  • University of California, Irvine