Sea turtles are long-lived, globally distributed animals with a complex life-history. Individuals from different populations often share the same foraging areas (mixed stock aggregations). Understanding patterns of dispersal and connectivity between reproductive populations and mixed stock aggregations is fundamental for the development of effective conservation plans. Recently, green sea turtle (Chelonia mydas) populations in several reproductive areas have increased, providing an opportunity to evaluate how demographic changes in reproductive areas impact dispersal to, and the composition of, mixed stock aggregations. In this dissertation, I evaluated how dispersal from reproductive populations in the Greater Caribbean to mixed stock aggregations may have changed over time (Chapter 2). I analyzed mitochondrial DNA haplotypes from samples collected from nesting females captured at Melbourne Beach, Florida, USA, and in-water juveniles from two mixed stock aggregations in central Florida (Indian River Lagoon and Trident Basin) over two time periods. Over a 15-year period there were small variations in the composition of the mixed stocks, without a clear relationship to the recent growth in reproductive populations. I developed a modification to the established "many-to-many" mixed stock model to use the distance between source populations and mixed stock aggregations to weight model estimates. In Chapter 3 I created a simulation to understand how sample size and the level of similarity in relation to haplotype frequency between source populations can impact mixed stock model estimates. I determined that a minimum of 150 samples from each mixed stock aggregation is required to accurately estimate contributions from source populations to mixed stock aggregations for most cases using data currently available in the literature. Improving the resolution of the genetic marker used (i.e., increasing the distinction of haplotype frequencies between source populations) can produce similar results using a smaller number of samples. Finally, in Chapter 4 I evaluated genetic structure of green turtle populations in the Greater Caribbean using a next-generation sequencing approach. I used the same sampling scheme as Chapter 2, with samples from a nesting beach (Melbourne Beach, FL) and two mixed stock aggregations (Indian River Lagoon and Trident Basin, Florida). I identified 4 distinct populations within the samples, and similar to the mtDNA assessment in Chapter 2, the genomic approach also showed small variations in the composition of mixed stock aggregations over a 15-year period. I used a coalescent model to evaluate how these populations diverged from one another, and found strong support for current gene flow among all 4 populations. Results from my analyses reiterate the complexity of sea turtle's dispersal dynamics, and the level of connectivity among populations in the Greater Caribbean. Future studies using mixed stock analysis should consider sample size with more than 150 samples per mixed stock aggregation and the use of more refined genetic markers. Also, genomic assessments of across multiple reproductive aggregations are required for a deeper understanding of other aspects of their ecology.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2670 |
| Date | 01 January 2023 |
| Creators | Stahelin, Gustavo |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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