Use of likelihood profiling over a global scaling parameter to structure the population dynamics model: An example using blue marlin in the Pacific Ocean

Modern stock assessment models can make use of a wide variety of data types, but measures of catch and relative abundance remain crucial to the estimates of the population abundance. Additional data types, such as the age or size composition of the catch, are useful for estimation of the age structure of the population. However, inappropriate data weightings or mis-specified selectivity process can result in the composition data asserting undue influence on the models estimate of abundance. Estimating the degree of degradation to the fit of data components from models with fixed absolute population scales provides information on the degree of influence that each component has on model results. Including additional model process in the selectivity parameterization or reducing the data weightings can be used to lessen the influence of secondary data components and therefore increase the importance of primary data components.