Abstract

Molecular data are useful in determining if populations are isolated and for species delimitation. Researchers and managers currently recognize five subspecies of raccoons (Procyon lotor) in Florida, based largely on perceived geographic isolation due to the island ranges of four subspecies. In this study, I provide the first estimate of phylogenetic relationships and population divergences within Florida raccoons using a molecular dataset. I analyze the mitochondrial control region, cytochrome b gene, and eight nuclear microsatellite loci to test two hypotheses: 1) the five, morphologically and geographically-defined subspecies of raccoon in Florida represent genetically distinct populations and (2) due to differing range sizes and habitat variation between island and mainland subspecies, the four island populations should exhibit reduced levels of genetic diversity and smaller effective population sizes compared to the mainland population. My results indicate no evidence of historical differentiation between the subspecies, but suggest a recent restriction of gene flow among three clusters of raccoons. The three clusters do not correlate to traditional geographies for subspecies identification. I provide evidence of reduced genetic diversity in island populations of raccoons compared to their mainland counterparts. These data stress the importance of using multiple lines of evidence when naming taxa to avoid misinforming the taxonomy.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu

Graduation Date

2015

Semester

Summer

Advisor

Hoffman, Eric

Degree

Master of Science (M.S.)

College

College of Sciences

Department

Biology

Degree Program

Biology

Format

application/pdf

Identifier

CFE0006233

URL

http://purl.fcla.edu/fcla/etd/CFE0006233

Language

English

Release Date

February 2016

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Included in

Biology Commons

Share

COinS