Review of contemporary cetacean stock assessment models

Abstract

Model-based methods of analysis are widely used to conduct cetacean stock assessments, and to provide the operating models on which management strategy evaluation is based. This paper reviews recent assessments and management strategy evaluations for cetacean populations, with a view towards establishing ‘best practice’ guidelines for such analyses. The models on which these analyses are based range from simple exponential trend models that ignore density-dependence to complex multi-stock age-sex- and stage-structured models that form the basis for management strategy evaluation. Most analyses assume that density-dependence is on calf survival (which implicitly includes maturity and pregnancy rate), but it could also impact the survival rate of adults or the age-at-maturity. Cetaceans seldom have more than one calf per female each year, which limits the variation in calf numbers, and places an upper limit on the effects of density-dependent calf survival. The models differ in terms of whether the population projections start when substantial catches first occurred or whether allowance is made for time-varying carrying capacity by starting the model in a more recent year. Most of the models are deterministic, but account needs to be taken of variation in cohort strength for analyses that include age-composition data or for species that are relatively short-lived. A limited number of analyses include process variability using a statespace-like modelling framework. For some stocks, abundance is so low that ideally both demographic and environmental variability should be included in models. The primary source of data for parameter estimation is a time-series of estimates of absolute abundance, although some approaches considered used a variety of data types, including relative abundance indices, mark-recapture data and minimum abundance estimates based on haplotype counts. In general, at least one estimate of absolute abundance is needed for parameter estimation; this is because there is a lack of catch-induced declines in abundance captured by indices of relative abundance that could be used to provide information on absolute abundance. Similarly, information on abundance from age- and length- composition data is limited. Most of the analyses quantify uncertainty using Bayesian methods to allow information on biological parameters, particularly the intrinsic rate of growth and the relative population at which maximum production occurs, to be included in the analyses, along with sensitivity testing. The future for the models on which assessments and management strategy evaluations are based will often involve multi-stock models that include age-, sex- and spatial-structure and are fitted as state-space formulations, although at present such models are often too computationally intensive to be feasible for implementation or there is insufficient information in the data to estimate the parameters representing all the processes, leading to simplifications, with the result that the performance of some of the methods of assessment used for cetacean stocks needs to be better understood, including through simulation testing.