Stochastic modelling and synthesis of dynamic fish recruitment productivity in the Celtic Seas ecoregion

Abstract

The Celtic Seas ecoregion (CSE) is undergoing climatic and ecosystem changes, which can induce changes in fish productivity. Globally, the productivity of many stocks has shown evidence of change over decadal timescales. Varying factors might drive these dynamics in the CSE, but for many stocks, these mechanisms have not been fully understood to be included in management advice. We study dynamic productivity for 28 stocks in the Celtic Seas by tracking integrated stochastic signals in the relationship between stock size and recruitment using state-space modelling applying Peterman's Productivity Method. Our research objectives were to (i) fit Ricker stock-recruitment models with time-varying parameters to all age- or length-based assessed stocks in the CSE, (ii) evaluate which parameters vary in time, (iii) examine temporal characteristics of historical recruitment productivity, and (iv) evaluate productivity correlation across stocks. For 22 out of 28 stocks, at least one of the three time-varying parameter models had a better fit than the time-invariant model. In the CSE, fish productivity has diverse temporal patterns, with some stocks displaying relevant long-term decreasing productivity trends. Getting insight into temporal changes in recruitment productivity is very valuable and has important implications for sustainable fisheries.