Graduation Year


Document Type




Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Marine Science

Major Professor

Cameron Ainsworth, Ph.D.

Committee Member

Chris Stallings, Ph.D.

Committee Member

Steve Murawski, Ph.D.

Committee Member

Isaac Kaplan, Ph.D.

Committee Member

Michael Schirripa, Ph.D.


Ecosystem modeling, Atlantis, reef fish, integrated ecosystem assessment, ecosystem-based fisheries management


Fisheries managers have the potential to significantly improve reef fish management in the Gulf of Mexico through the use of ecosystem-based approaches to fisheries management. Ecosystem-based approaches are needed to address the effects of fishing on trophodynamic interactions, to better account for ecosystem-scale processes in model projections, and to recognize the short and long-term biomass tradeoffs associated with making regulatory choices. My research was concentrated around three objectives: (1) characterizing the trophodynamic interactions between Gulf of Mexico fishes, in order to construct an invaluable tool (a Gulf of Mexico Atlantis model) to be used in ecological hypothesis testing and policy performance evaluation for years to come; (2) predicting ecological indicators for the Gulf of Mexico that both respond to fishing pressure and are robust to observational error, and; (3) evaluating the performance of an ecosystem-based policy options for managing reef fish species in the Gulf of Mexico. To accomplish these objectives, a spatial, trophodynamic ecosystem model- Atlantis, was employed to represent the Gulf of Mexico marine ecosystem.

To characterize trophic interactions between modeled species, I applied a maximum likelihood estimation procedure to produce Dirichlet probability distributions representing the likely contribution of prey species to predators’ diets. This provided mode values (the peak of the distribution) and associated error ranges, which describe the likely contribution of a prey item in a predator’s diet. The mode values were used to parameterize the availabilities (diet) matrix of the Gulf of Mexico Atlantis model. Investigating trophic interactions was useful for determining which species within the Atlantis model were data rich, and justified the emphasis on reef fish species and their prey items in subsequent analyses.

Once parameterized and calibrated, I used the Atlantis model to project ecological indicators over a 50 year time horizon (2010-2060) under varying levels of fishing mortality. Principal component analysis was used to evaluate ecological indicator trajectories in multivariate space, to rank indicators according to how well they describe variability in ecosystem structure (termed ‘importance’), to reveal redundancies in the information conveyed, to quantify interannual noise and to determine how robust indicators are to observational error. Reef fish catch, Red snapper biomass, King mackerel biomass and Species richness indicators ranked the highest in terms of importance and robustness to error and in having low levels of interannual noise (i.e., requiring less frequent monitoring). I then used a management strategy evaluation (MSE) framework in Atlantis to evaluate some of these same indicators under an ecosystem-based approach to fisheries management – using robust harvest control rules to manage reef fishes. I found that this ecosystem-based policy option was able to maintain higher reef fish biomass, catch and ecosystem-wide biodiversity under any given level of fishing mortality when compared to a status quo management approach. These results suggest that harvesting under the HCRs encourages an alternative ecosystem state with a more Pareto-efficient tradeoff frontier than the status-quo policy. A potentially reduced extinction risk for reef fish is plausible under this ecosystem-based policy option.

This research provides a quantitative look at the fishery performance and ecological tradeoffs associated with various policy options. MSE methodology using ecosystem-based policy performance metrics is also demonstrated. Tool development and findings from this research should aid in the development of ecosystem-based policies for this region.