Doctor of Philosophy (Ph.D.)
Degree Granting Department
Cameron H. Ainsworth, Ph.D.
Frank E. Muller-Karger, Ph.D.
Steven Murawski, Ph.D.
Ernst B. Peebles, Ph.D.
Michael J. Schirripa, Ph.D.
ecosystem models, fisheries management, larval dispersal, marine protected area
Connectivity is a major contributor to the overall dynamics of marine populations. However, it still remains challenging to describe connectivity on ecologically meaningful scales of time and space. This is a major impediment to evaluating the impacts of marine protected area with respect to fisheries management objectives.
This dissertation brings together a wide array of spatial and connectivity information in the Gulf of Mexico (GOM) with the goal of 1) understanding the spatial distribution of fish populations and source-sink dynamics and 2) evaluating whether this information can be integrated, through a modeling framework, to identify closed areas that could be beneficial to fisheries management in the Gulf of Mexico.
First, a generalized additive modelling (GAM) approach is used to describe the distribution of a large number of species groups (i.e. functional groups) across the Gulf of Mexico (GOM) using a large fisheries independent data set (SEAMAP) and climate scale (decades) oceanographic conditions. Next a numerical Lagrangian particle transport model was developed that incorporates two major connectivity processes; site specific larval production and oceanographic transport for an entire large marine ecosystem and over multiple years. The two components are then combined to develop larval dispersal patterns for the entire GOM and identify areas operating as larval sources and sinks. Last, this information is integrated into an end-to-end ecosystem model to evaluate effectiveness of closing source and sink areas for the management of reef fish fisheries.
Closed area managemeny simlautions for reef fish indicated closing reef fish source areas, as opposed to sinks, in the GOM is most efficient method of increasing total biomass and yield. However, the impacts across individual functional groups were site specific. Ultimately, these simulations demonstrate the inclusion of connectivity information could improve fishery management objectives in an ecosystem context.
Scholar Commons Citation
Drexler, Michael, "Evaluating the use of larval connectivity information in fisheries models and management in the Gulf of Mexico" (2018). USF Tampa Graduate Theses and Dissertations.