Biases in biomass estimates: The effect of bin width in size-structured stock assessment methods

Abstract

Size-structured assessment models require size data to be binned, but it is unclear how a specified bin width can impact the ability of an assessment to estimate quantities important in management. Biases in estimated mature biomass are demonstrated here when increasing the bin width using a simulation framework based on the Pribilof Islands red king crab (PIRKC) assessment. Several potential sources of bias were explored through simulation. The bias was removed by applying an alternative assessment method which used a finer approximation of the integral representing the probability of a crab molting from one size bin. Trade-offs exist at both sides of the bin width spectrum. Precision and model stability may suffer when bin width is too large; slowed parameter estimation and problems fitting multinomial likelihoods to length frequency data may appear when bin widths are too small. Simulation studies (like the one presented here) are useful for identifying optimal bin width for management related tasks.