Chrome Extension
WeChat Mini Program
Use on ChatGLM

Comparative performance of data-poor CMSY and data-moderate SPiCT stock assessment methods when applied to data-rich, real-world stocks

ICES JOURNAL OF MARINE SCIENCE(2021)

Cited 30|Views5
No score
Abstract
All fish stocks should be managed sustainably, yet for the majority of stocks, data are often limited and different stock assessment methods are required. Two popular and widely used methods are Catch-MSY (CMSY) and Surplus Production Model in Continuous Time (SPiCT). We apply these methods to 17 data-rich stocks and compare the status estimates to the accepted International Council for the Exploration of the Sea (ICES) age-based assessments. Comparison statistics and receiver operator analysis showed that both methods often differed considerably from the ICES assessment, with CMSY showing a tendency to overestimate relative fishing mortality and underestimate relative stock biomass, whilst SPiCT showed the opposite. CMSY assessments were poor when the default depletion prior ranges differed from the ICES assessments, particularly towards the end of the time series, where some stocks showed signs of recovery. SPiCT assessments showed better correlation with the ICES assessment but often failed to correctly estimate the scale of either F/F-MSY of B/B-MSY, with the indices lacking the contrast to be informative about catchability and either the intrinsic growth rate or carrying capacity. Results highlight the importance of understanding model tendencies relative to data-rich approaches and warrant caution when adopting these models.
More
Translated text
Key words
benchmarking,data-limited stock assessment,management advice,model bias,surplus production models
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined