Inferring prior distributions of recruitment compensation metrics from life-history parameters and allometries

Abstract

The recruitment compensation metrics, the stock–recruit steepness (h) and compensation ratio (κ), are difficult to estimate, yet they are integral components of contemporary fishery models. To aid in the estimation of κ and h, a hybrid method to construct their prior distributions for a species is developed. The method is hybrid because it integrates (i) a meta-analysis of the relationship between maximum rates of recruit production (α) and asymptotic lengths obtained across fish species of different life histories and (ii) species-specific unfished spawning biomass per recruit (Φ0). This method is applied to five finfish species found off the East Coast of the United States. Uncertainty is introduced by sampling growth parameters, α, and natural mortality and — through Monte Carlo simulations — propagated into Φ0, κ, and h for the Beverton–Holt and Ricker stock–recruit relationships. Descriptive statistics and parameters from probability density functions of the simulated distributions of κ and h are generated. The method developed requires fewer inputs than the reproductive ecology method while likewise allowing the development of species-specific statistics for κ and h. These statistics, rather than their counterparts generated from classical meta-analyses, are better suited for use in fishery models.