PARENT SESSION
Oral Session # 3: Fish Ecology.
Presiding: M Ford
Monday, August 4. 8:00 AM to 11:30 AM, SITCC Meeting Room 102.
Estimating age and stage-specific demographic parameters for scup, Stenotomus chrysops, using model selection.
Kelly, Stephanie*,1, 1 University of Rhode Island, Kingston, RI
ABSTRACT- Identifying environmental and demographic processes that account for fluctuations in the abundance of organisms is a central goal of population ecology. For commercially valuable fish species, such as scup (Stenotomus chrysops) in Long Island Sound, understanding population dynamics is important in developing regulations and management practices for the harvest of these species. Historically, changes in the abundance or harvest of commercially important species have been difficult to predict because many of the factors regulating their dynamics are poorly understood. In many cases, it is the demographic rates of specific ages or stages that have the largest influence on the growth rate and resulting population size. The goal of this study was to determine the demographic structure of the scup population by identifying the number of ages/stages and vital rates justified by census data. The strength of evidence in the empirical data from the Long Island Sound Trawl Survey (LISTS) for age and stage-structured models of scup was examined using maximum likelihood estimation and model selection. Initial results indicate support for models that distinguish between two age/stage classes. Although scup can be aged quite accurately, it appears that the identification of individual age classes may not be necessary to the development of accurate models. Additional population effects, including density dependence and environmental variance, will be incorporated into the age/stage structured models to further evaluate scup population dynamics. Results of this study will provide a more thorough understanding of the demographic processes regulating the scup population in Long Island Sound and serve as a basis for the development of more effective management strategies.
Key words: model selection, demographic parameters, Stenotomus chrysops, maximum likelihood estimation