Abstract:Observation errors and process errors are the main source for the uncertainties of the biomass dynamics model. These errors are harmful to fisheries management because they can lead to biased estimation for some key management quantities such as biomass, fishing mortality and their related biological reference points. Simulation approach has been widely used to examine the effects of observed and process errors and evaluate the ability of the stock assessment model for providing robust catch advice. In this study, we use simulation approach to examine and quantify the impacts of observation and process errors on the population dynamics, assessment and management of Chilean jack mackerel in the southeast Pacific. Based on the biomass dynamics model and real catch and catch per unit fishing effort (CPUE) data, the operating model was built to describe the "true" population dynamics and fisheries for jack mackerel stock, and generate "true" time-series CPUE data. Assuming errors in CPUE has lognormal distribution, 100 sets of simulated time-series CPUE data were generated respectively by adding low level and high level random errors to the "true" CPUE. The assessing model was also based on the biomass dynamics model but low and high level process errors were added by setting low and high coefficient of variation, CV. We refer to the assessing model as "high" error when both observed and process errors were subject to high level and "low" error when both errors were subject to low level. Relative errors (RE) of biomass, fishing mortality, BMSY and FMSY were used to measure the disparity between the operating model and assessment model. Constant fishing mortality rate was considered as harvest control rules. Four constant fishing mortality scenarios with current level (F2014) and at 1.25, 0.75 and 0.5 were input to operating model and assessing models to do projections respectively. The results of the projections of the operating and assessing models were compared to analyze the impacts of random observed and process errors on the "true" and simulated population dynamics. The management advice derived from the assessing models, i.e., values of a certain level of F2014 estimated by the assessing models, was employed to the "true" population and the projections were done again to predicted biomass and total allowable catch (TAC). We refer to these predicted biomass and TAC as the theoretical biomass and TAC. The "true" population dynamics and fisheries showed that jack mackerel biomass was less than 50% BMSY during the period of 1997-2014 while fishing mortality rate was greater than FMSY except the last three years. The estimated parameters instantaneous growth rate r and hatchability coefficient q by assessing model were greater than those by operating model, but carry capacity K and biomass of the first year (B1997) were smaller than that by the operating model. Median REs of biomass and BMSY were negative while median REs of fishing mortality rate and FMSY were positive, and absolute value of these median REs were proportional to the error level. These results indicated that BMSY and time-series biomass were overestimated, and FMSY as well as time-series fishing mortality rate were underestimated because of the observed and process errors, and the degree of over- or under- estimation related to the error level. The projections of operating and assessing models showed that simulated biomass trend in the future ten years (from 2015 to 2024) will increase for all the four fishing mortality rate scenarios, but the increase rate or the recovery rate of jack mackerel biomass will decrease with the fishing mortality rate increasing, i.e., the stock needs more time to reach the level of BMSY. The predicted biomass and TAC in future by the assessing model were overestimated when compared to the "true" future biomass predicted by the operating model. Furthermore, the predicted annual TAC, biomass and the 80% confidence intervals of biomass by the high error assessing model were greater than those predicted by the low error assessing model. When the values of the four level F2014 estimated by the lower and high error assessing models were input to the operating model, the predicted theoretical biomass, ratio between biomass and BMSY and TAC in future ten years were less than their simulated and "true" values. The projection results of low and high error assessing model indicated that the fishing mortality rate was set to 0.5F2014 (equal to 0.073 and 0.074 for the low and high error assessing model respectively) in future was best for the jack mackerel stock. Under this fishing mortality rate (0.073 and 0.074), jack mackerel biomass is lower than the simulated and "true" biomass. Although the theoretical value will still increase, the rate of increase will be slow and the stock can recover until the year of 2023. On the other side, the theoretical TAC which means the actual catch for the fisheries, are higher than the expected TAC (i.e., the simulated TAC). Moreover, the higher the error level is, the bigger differences between the theoretical and simulated biomass and TAC are, and this can result in the increase of risk that the jack mackerel stock will be overfished with overfishing.