Integrating demographic and environmental variables to calculate an egg production index for the Eastern Bering Sea snow crab (Chionoecetes opilio)

Abstract

The complex life-history of the snow crab suggests that estimates of mature female biomass may not correlate proportionally with actual egg production. We calculate an egg production index (EPI) for the Eastern Bering Sea (EBS) snow crab using a simulation model that follows mature females from the molt-to-maturity through various reproductive stages (primiparous and multiparous) and reproductive cycles (annual and biennial). The model is parameterized with an estimate of annual instantaneous natural mortality, M, from a separate statistical model. The egg production model runs from 1980 to 2014, but the EPI is calculated only for 1985–2014 to be able to unambiguously assign mature females to the various component reproductive categories. Estimated M was 0.68yr−1 for 1980–2014. Linear regression of EPI lagged one year with stock assessment estimates of mature female biomass had an R2 of 0.78, but with a mean absolute percent error of 82% between observed and model predictions; mature female biomass is thus a variable and uneven predictor of egg production. On average, primiparous females contributed 46% to total annual egg production and multiparous females the remaining 54%. Multiparous females in an annual cycle made the largest contribution to the EPI, responsible for 50% of annual egg production. Sensitivity analysis showed that egg production increased by a factor of 1.75 on average when only annual spawning was assumed. Multiparous females were found to co-occur almost exclusively with larger older males, such as those targeted by the fishery; due to the large proportion of egg production from multiparous females, this co-occurrence pattern has potential fishery management implications. The EPI will allow for future recruitment and population dynamics studies to use a more accurate measure of EBS snow crab reproductive potential, especially when considering the effects of climate change and environmental variability. Further demographic research will help refine EPI estimates.