Overcoming gaps in a seasonal time series of Japanese anchovy abundance to analyse interannual trends

Abstract

Monitoring and understanding the level of exploitation and stock status of target and bycatch species are essential for effective fishery management and conserving biological diversity. Pursuit of these objectives is often challenging where yield statistics are unavailable, especially when scientific surveys are spatially and seasonally unbalanced. To address this issue, we attempt to combine recently developed methods to construct an assessment framework using Japanese anchovy (“anchovy”; Engraulis japonicus) in the Bohai Sea as an example. First, based on data from surveys conducted in spring, summer and autumn in the Bohai Sea during 2009–2019, we developed a seasonal spatio-temporal model for anchovy to interpolate missing observations thereby obtaining a continuous time series of abundance. Then, we fitted the abundance maximum sustainable yield (AMSY) model using the spring, summer, autumn, and seasonal average indices of abundance to obtain long-term trends in the stock status of anchovy. The model indicated that at the end of the survey series in 2019 there was a 17.6%–22.6% probability that the anchovy stock was in a sustainable state, 51.1%–69.3% probability it was in a period of recovery and 10.3%–29.8% probability it was declining. The relative stock size gained significant recovery throughout the study period, reaching a healthy level during 2016–2018. Our assessment framework enabled the estimation of anchovy stock status in the Bohai Sea in the absence of yield data, a process which will facilitate the assessment of other fishery resources in waters without yield statistics to provide estimates of local stock status for managers to take measures to avoid local depletion of those resources.

Keywords

• Seasonal spatio-temporal model
• CPUE series continuity
• Stock assessment
• AMSY
• Population restoration
• Resource rebuilding