Quantifying uncertainty and dynamical changes in multi‐species fishing mortality rates, catches and biomass by combining state‐space and size‐based multi‐species models

摘要: In marine management, fish stocks are often managed on a stock‐by‐stock basis using single‐species models. Many of these models based upon statistical techniques and good at assessing the current state making short‐term predictions; however, as they do not model interactions between stocks, lack predictive power longer timescales. Additionally, there size‐based multi‐species that represent key biological processes consider such predation competition for resources. Due to complexity models, difficult fit data, so many depend where exist, or ad hoc assumptions when not, parameters annual fishing mortality. this paper, we demonstrate by taking state‐space approach, uncertain can be treated dynamically, allowing us fit, with quantifiable uncertainty, directly data. We fitting parameters, including mortality, Celtic Sea, species without stock assessments. Consequently, errors in no propagate through underlying more transparent. Building internally consistent, will improve their credibility utility management. This may lead uptake being either used corroborate models; advice process make predictions into future; provide new way managing data‐limited stocks.