Impact of time-varying productivity on estimated stock–recruitment parameters and biological reference points

Models with time-varying parameters are increasingly being considered in the assessment of fish stocks, but their reliability when used to derive biological reference points or benchmarks has not been thoroughly evaluated. Here, we evaluated stock–recruitment models with and without time-varying pro...

Full description

Saved in:
Bibliographic Details
Published in:Canadian journal of fisheries and aquatic sciences 2020-05, Vol.77 (5), p.836-847
Main Authors: Holt, Carrie A, Michielsens, Catherine G.J
Format: Article
Language:English
Subjects:
Adapters
Benchmarks
Biological production
Computer simulation
Conservation
Empirical analysis
Evaluation
Exploitation
Fishes
Freshwater
Mathematical models
Maximum sustainable yield
Modelling
Oncorhynchus nerka
Parameter estimation
Productivity
Recruitment
Recruitment (fisheries)
Reliability analysis
Rivers
Salmon
Simulation
Spawning populations
Stock assessment
Stocks
Sustainable yield
Variables
Yield forecasting
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Models with time-varying parameters are increasingly being considered in the assessment of fish stocks, but their reliability when used to derive biological reference points or benchmarks has not been thoroughly evaluated. Here, we evaluated stock–recruitment models with and without time-varying productivity in a simulation framework for sockeye salmon (Oncorhynchus nerka) under different scenarios of productivity and exploitation. Ignoring trends in productivity led to overestimates of productivity and underestimates of capacity when both exploitation rates and productivity declined over time, resulting in an underestimation on average of benchmarks of biological status. Despite being less biased, time-varying models had relatively poor fit based on AIC c and BIC model selection criteria. Our simulation results were compared with empirical analyses of 12 Fraser River sockeye salmon stocks in British Columbia, Canada. Although benchmarks were less biased when based on time-varying models, underlying true benchmarks based on spawner abundances at maximum sustainable yield, S MSY , trend downwards when productivity declines, which may not be aligned with conservation objectives. We conclude with best practices when adapting biological benchmarks to time-varying productivity.
ISSN:0706-652X
1205-7533
DOI:10.1139/cjfas-2019-0104