Estimating stock status from relative abundance and resilience

Manuel Dureuil,Gianpaolo Coro,Donna Dimarchopoulou,Henning Winker,Daniel Pauly,Rainer Froese,Athanassios C Tsikliras,Giuseppe Scarcella,Maria Lourdes Deng Palomares,Nazli Demirel,Emory Anderson

doi:10.1093/icesjms/fsz230

Abstract

Abstract The Law of the Sea and regional and national laws and agreements require exploited populations or stocks to be managed so that they can produce maximum sustainable yields. However, exploitation level and stock status are unknown for most stocks because the data required for full stock assessments are missing. This study presents a new method [abundance maximum sustainable yields (AMSY)] that estimates relative population size when no catch data are available using time series of catch-per-unit-effort or other relative abundance indices as the main input. AMSY predictions for relative stock size were not significantly different from the “true” values when compared with simulated data. Also, they were not significantly different from relative stock size estimated by data-rich models in 88% of the comparisons within 140 real stocks. Application of AMSY to 38 data-poor stocks showed the suitability of the method and led to the first assessments for 23 species. Given the lack of catch data as input, AMSY estimates of exploitation come with wide margins of uncertainty, which may not be suitable for management. However, AMSY seems to be well suited for estimating productivity as well as relative stock size and may, therefore, aid in the management of data-poor stocks.

Highlights

The Law of the Sea (UNCLOS, 1982) commits its signatories to manage the exploitation of fish and invertebrates so that these 35 populations are large enough to generate maximum sustainable yields (MSY)
abundance maximum sustainable yields (AMSY) predictions of population dynamic parameters (r, kq, 45 MSYq), fishing pressure (F/FMSY), and stock status (B/be above the MSY level (BMSY)) at the end of the time series were compared with the “true” values used to produce the simulated data
To better understand the influence of the priors and of the Monte Carlo filtering on the results, the simulated data were analyzed twice by AMSY, first 50 without and with the Monte Carlo filters described above

Summary

Introduction

The Law of the Sea (UNCLOS, 1982) commits its signatories to manage the exploitation of fish and invertebrates so that these 35 populations are large enough to generate maximum sustainable yields (MSY). Methods that make best use of available data combined with general knowledge and Monte Carlo approaches have 45 recently been developed on the basis of previous work in fish population dynamics (Graham, 1935; Schaefer, 1954, 1957; Beverton and Holt, 1957; Ricker, 1975), such as CMSY (Froese et al, 2017) for catch data and LBB (Froese et al, 2018a, 2019) to estimate relative biomass levels from length frequency data. Time series of abundance are useful in that they allow trend analyses such as comparing current cpue to the average of previous years (e.g. ICES, 20 2017) It is often unclear whether such abundance trajectories refer to a stock fluctuating around unexploited stock size, around a stock size close to collapse, or somewhere in between. If reliable catch data are available, this ambiguity is best addressed by combining cpue trends with catch data, e.g. in sur plus production models (Schaefer, 1954; Pella and Tomlinson, 1969; Fox, 1970; Froese et al, 2017; Pedersen and Berg, 2017; Winker et al, 2018)

Objectives

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Results

Discussion

Conclusion