Quantitative population dynamics modeling is needed to evaluate the stock status and fisheries management plans to provide robust model and management strategies. Atlantic Weakfish (Cynoscion regalis), one important commercial and recreational fish species along the west coast of Atlantic Ocean that was found to be declining in recent years, was selected as an example species. My study aimed to explore the possible spatial heterogeneity of CPUE (catch per unit effort) year trend based on three fishery independent surveys and explore the influence of nonstationary natural mortality on the fisheries management through a MSE (Management Strategy Evaluation) algorithm based on the Weakfish stock assessment results. Five models for catch rate standardization were constructed based on the NEAMAP (NorthEast Area Monitoring and Assessment Program) survey data and the ‘best' two models were selected based on the ability to capture nonlinearity and spatial autocorrelation. The selected models were then used to fit the other two survey data to compare the CPUE year trend of Weakfish. Obvious differences in distribution pattern of Weakfish along latitude and longitude were detected from these three surveys as well as the CPUE year trend. To test the influence of the model selection on the MSE, five stock-recruitment models and two forms of statistical catch-at-age models were used to evaluate the fishery management strategies. The current biomass-based reference point tends to be high if the true population dynamics have nonstationary natural mortality. A flexible biomass based reference point to match the nonstationary process is recommended for future fisheries management. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/78094 |
| Date | 12 July 2016 |
| Creators | Zhang, Yafei |
| Contributors | Fisheries and Wildlife Sciences, Jiao, Yan, Haas, Carola A., Frimpong, Emmanuel A. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Thesis, Text |
| Format | application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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