Title

Genetic and Biophysical Modeling Assessment of Connectivity in the Red Grouper, Epinephelus morio

Event Name/Location

13th International Coral Reef Symposium, Honolulu, Hawaii, June 19-24, 2016

Document Type

Conference Proceeding

Publication Date

6-2016

Abstract

Understanding connectivity of reef organisms is important to aid the conservation of biological diversity and facilitate sustainable fisheries. Common methods to assess reef connectivity include genetics, modeling, and tagging. Individually, these techniques can offer insight into population structure; however, the information acquired by a singular analysis is often subject to inherent limitations of the chosen method. Thus combining approaches may allow for better resolution of population structure and the biophysical factors driving it. We utilized both genetic analysis and biophysical modeling to assess connectivity dynamics and linkages of the red grouper (Epinephelus morio), a major reef fishery species found throughout the Gulf of Mexico (GOM) and southeastern USA (SE-USA). First, we used a model to incorporate ocean conditions and biotic traits of the grouper to deliver a spatial forecast of ‘source’ and ‘sink’ populations in the GOM and SE-USA spanning ten years. Next, using a suite of 13 polymorphic microsatellite markers we assessed the genetic population structure of red grouper across this same spatial scale to directly compare levels of connectivity between methods. Our population genetic survey of groupers suggested high connectivity and the presence of a single genetic population. Similarly, modelling the fish over ten years suggested panmixia over generations. Using a dual empirical and theoretical approach lessens error over one method alone and is important validation of both the genetic and biophysical modeling techniques used in this study.

Comments

Also presented at the 69th Annual Conference of the Gulf and Caribbean Fisheries Institute, Grand Cayman, United Kingdom, November 7-11, 2016

First Page

163

Last Page

163

ResearcherID

G-4080-2013