Doctor of Philosophy (Ph.D.)
Virginia Institute of Marine Science
John M. Hoenig
Spatial management of marine resources requires population dynamic parameters in much greater spatial detail than traditional stock assessments provide. This dissertation presents a suite of methods to improve the spatial prediction of population abundance, fishing and natural mortality and to make greater use of commercial catch data. The main objectives of this dissertation are to determine the efficacy of using the vast amount of data collected by on-board observers on commercial vessels in model-based estimation of abundance and to use the spatial autocorrelation to improve resource mapping and abundance estimation. The first paper presents a methodology for improving variogram estimation when samples exist from multiple years or regions sharing a similar process for generating spatial autocorrelation. In both simulations and in real datasets of oyster abundance the method proposed here reduced the likelihood of failing to obtain a variogram from a set of samples and improved the efficiency of variogram estimation. The second paper presents a simulation of the efficacy of using biased samples for geostatistical predictions. By creating and sampling spatially-autocorrelated datasets in a manner similar to a commercial fishery we found that model-based geostatistics provided a means of obtaining relatively unbiased predictions of abundance using this data. The next paper used catches obtained by onboard observers in the scallop fishery in Georges Bank Closed Area II in 1999 to obtain geostatistical abundance estimates. We used Vessel Monitoring System (VMS) effort data to obtain tows with less than 10% of the total effort. These tows provided geostatistical estimates of initial scallop abundance similar to a preseason fishery-independent survey. Local differences between the observer and survey predictions were driven primarily by data gaps. The last paper obtained spatially-explicit DeLury depletion estimates of dredge efficiency and scallop abundance using VMS data to correct for the actual fished area. Corrected-area efficiency estimates ranged between 20 and 55% with a mean of 45% and maps of abundance closely matched fishery-independent survey estimates. These results indicate that the there is tremendous potential to incorporate commercial fishery data for the purposes of obtaining quantitative resource assessment information.
© The Author
Walter, John F., "Incorporating space into stock assessments of marine species" (2006). Dissertations, Theses, and Masters Projects. William & Mary. Paper 1539616898.