Date Awarded


Document Type


Degree Name

Doctor of Philosophy (Ph.D.)


Virginia Institute of Marine Science


John M. Hoenig

Committee Member

Mark J. Brush

Committee Member

John E. Graves

Committee Member

Ross J. Iaci

Committee Member

John F. Walter III


For data-limited fisheries, length-based mortality estimators are attractive as alternatives to age-structured models due to the simpler data requirements and ease of use of the former. This dissertation develops new extensions of mean length-based mortality estimators and applies them to federally-managed stocks in the southeastern U.S. and U.S. Caribbean.

Chapter 1 presents a review of length-based methods from the literature. Common themes regarding the methodology, assumptions, and diagnostics in these length-based methods are discussed. In Chapter 2, a simulation study evaluates the performance of the length-converted catch curve (LCCC), Beverton-Holt equation (BHE), and Length Based-Spawner Potential Ratio (LB-SPR) over a range of scenarios. Although the LCCC and BHE are older methods than LB-SPR, the former outperformed LB-SPR in many scenarios in the simulation. Overall, it was found that the three length-based mortality estimators are less likely to perform well for low M/K stocks (M/K is the ratio of the natural mortality rate and the von Bertalanffy growth parameter; this ratio describes different life history strategies of exploited fish and invertebrate populations), while various decision rules for truncating the length data for the LCCC and BHE were less influential. In Chapter 3, a multi-stock model is developed for the non-equilibrium mean length-based mortality estimator and then applied to the deepwater snapper complex in Puerto Rico. The multispecies estimator evaluates synchrony in changes to the mean length of multiple species in a complex. Synchrony in mortality can reduce the number of estimated parameters and borrows information from more informative species to lesser sampled species in the model. In Chapter 4, a new method is developed to estimate mortality from both mean lengths and catch rates (MLCR), which is an extension of the mean length-only (ML) model. to do so, the corresponding behavior for the catch rate following step-wise changes in mortality is derived. Application of both models to Puerto Rico mutton snapper shows that the MLCR model can provide more information to support a more complex mortality history with the two data types compared to the ML model. In Chapter 5, a suite of mean length-based mortality estimators is applied to six stocks (four in the Gulf of Mexico and two in the U.S. Atlantic) recently assessed with age-structured models. There was general agreement in historical mortality trends between the age-structured models and the mean length-based methods, although there were some discrepancies which are discussed. All models also agreed on the overfishing status in the terminal year of the assessment of the six stocks considered here when the mortality rates were compared relative to reference points. This dissertation develops new length-based assessment methods which consider multiple sources of data. The review guides prospective users on potential choices for assessment with length-based methods. Issues and diagnostics associated with the methods are also discussed in the review and highlighted in the example applications.




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