Chelsea M. Berns

Understanding the origin of biodiversity has been a major focus in evolutionary and ecological biology for well over a century, and several patterns and mechanisms have been proposed to explain this diversity. I am an evolutionary and ecological biologist, interested in the evolution of phenotypic diversity and sexual dimorphism.

Broadly, in my research I use hummingbirds as a model system to understand evolutionary patterns and the processes of phenotypic change. Hummingbirds offer a unique opportunity to study sexual dimorphism, as they exhibit sexual dimorphism of bill morphology, and elucidate the underlying mechanisms responsible for it. Bill morphology is a critical trait under strong selection pressures due to its role in foraging efficiency, and this morphology can affect niche differentiation among species and between sexes. Thus, I took a microevolutionary approach to examine sexual size and shape dimorphism in hummingbird beaks for my Ph.D. research. I then scaled out to a macroevolutionary picture of how rates of evolution and magnitude of sexual dimorphism affects species diversification and species richness. Using landmark-based geometric morphometrics to quantify these morphological differences, I have been examining rates of phenotypic evolution and morphological disparity both within and between 270 species of hummingbirds.

Lake Ontario2

Contact Information

Chelsea M. Berns, Ph.D.
Department of Biology
1101 Camden Avenue
Salisbury, MD 21801
cmberns @ salisbury.edu

Research and Teaching Interests

    TEACHING:

  • Zoology and Biology, majors and non-majors
  • Vertebrate/invertebrate Biology, majors and non-majors
  • Environmental Science
  • Ecology and Evolution of Reproduction
  • Evolution
  • Morphometrics
  • Ornithology
  • Phylogenetics
  • Ecology
  • Anatomy and Physiology
  • Human Anatomy
  • Research Methods
  • Senior Research
  • RESEARCH:

  • Phenotypic Diversity
  • Evolutionary Biology
  • Geometric Morphometrics
  • Rates of Evolution
  • Ornithology
  • Statistics and R Programming