Date of Award

Spring 5-3-2018

Level of Access Assigned by Author

Open-Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Ecology and Environmental Sciences

Advisor

Yong Chen

Second Committee Member

Richard Wahle

Third Committee Member

Damian Brady

Additional Committee Members

Andrew Pershing, Lawrence Jacobson

Abstract

The American lobster (Homarus americanus) support one of the most valuable fisheries in the United States. A growing body of literature recognizes the importance of environmental variables in regulating this species’ biogeography and population dynamics. However, the current lobster stock assessment and management do not explicitly consider the impact of environmental variables such as water temperature and assumes spatiotemporal variabilities in the lobster environment as random background noises. Furthermore, while climate-induced changes in marine ecosystems continue to impact the productivity of lobster fisheries, studies that model lobster response to altered environmental conditions associated with climate change are lacking. As such, evaluating changes in lobster biogeography and population dynamics, as well as explicitly incorporating quantified lobster response to altered environmental conditions into the specie’s stock assessment will be critical for effective lobster fisheries management in a changing environment.

This dissertation research developed a modeling framework to assess and incorporate environmental variability in assessment and management of American lobster stocks in the Gulf of Maine, Georges Bank, and southern New England. This modeling framework consists of: 1) a qualitative bioclimate envelope model to quantify the spatiotemporal variability in availability of suitable lobster habitat; 2) a statistical climate-niche model to quantify spatiotemporal variability of lobster distribution; and 3) a process-based population size-structured assessment model to incorporate the effect of environmental variable such as water temperature in lobster population dynamics. The developed modeling framework was used to predict climate-driven changes in lobster habitat suitability and distribution, as well as to determine whether incorporating the environmental effects can better inform historical recruitment especially for years when recruitment was very low or very high.

The first component of the framework provides a qualitative bioclimate envelope model to evaluate the spatiotemporal variability of suitable lobster habitat based on four environmental variables (bottom temperature, bottom salinity, depth, and bottom substrate type. The bioclimate envelope model was applied to lobsters in Long Island Sound and inshore Gulf of Maine waters. In the Long Island Sound, an examination of the temporal change in annual median habitat suitability values identified possible time blocks when habitat conditions were extremely poor and revealed a statistically significant decreasing trend in availability of suitable habitat for juveniles during spring from 1978 to 2012. In the Gulf of Maine, a statistically significant increasing trend in habitat suitability was observed for both sexes and stages (juvenile and adult) during the spring (April–June), but not during the fall (September–November).

The second component of the framework provides a statistical niche model to quantify the effects of environmental variables on lobster abundance and distribution. The statistical niche model was used to estimate spatiotemporal variation of lobster shell disease in Long Island Sound, and to quantify environmental effects on season, sex- and size-specific lobster distributions in the Gulf of Maine. In the Long Island Sound, the statistical niche model found that spatial distribution of shell disease prevalence was strongly influenced by the interactive latitude and longitude effects, which possibly indicates a geographic origin of shell disease. In the Gulf of Maine, the statistical niche model indicated that bottom temperature and salinity impact on lobster distribution were more pronounced during spring, and predicted significantly higher lobster abundance under a warm climatology scenario.

The third component of the framework provides a size-structured population model that can incorporate the environmental effects to inform recruitment dynamics. The size-structured population model was applied to the Gulf of Maine/Georges Bank lobster stock, where climate-driven habitat suitability for lobster recruitments was used to inform the recruitment index. The performance of this assessment model is evaluated by comparing relevant assessment outputs such as recruitment, annual fishing mortality, and magnitude of retrospective biases. The assessment model with an environment-explicit recruitment function estimated higher recruitment and lower fishing mortality in the early 2000s and late 2010s. Retrospective patterns were also reduced when the environmentally-driven recruitment model was used.

This dissertation research is novel as it provides the comprehensive framework that can quantify impacts of environmental variability on lobster biogeography and population dynamics at high spatial and temporal scales. The modeling approaches developed in this study facilitate the need to invoke assumptions of environment at non-equilibrium and demonstrate the importance of considering environmental variability in the assessment and management of the lobster fisheries. This dissertation is dedicated to increase the breadth of knowledge about the dynamics of lobster populations and ecosystems and renders a novel first step towards sustainable management of this species given the expected changes in the Northwest Atlantic ecosystem.

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