Title: A Partial Bias Correction Factor for Stock–Recruitment Parameter Estimation in the Presence of Autocorrelated Environmental Effects
Abstract: Stock–recruitment time series often give a distorted picture of average recruitment rates, with high productivities per spawner being overrepresented at low stock sizes. This distortion is exaggerated by autocorrelation among years in environmental effects on productivity. The common procedure of fitting a stock–recruit curve and then analysing residuals from the curve will result in a substantial underestimate of the autocorrelation among environmental effects. Previous studies have recommended using Monte Carlo simulations to estimate the bias in stock–recruit model parameter estimates. These simulations can generally be avoided by using a simple correction equation. However, deviations from the corrected stock–recruit curve will not give better estimates of autocorrelation patterns in environmental effects, and hence will not help to provide better forecasts and stronger tests for factors that may be causing the effects.
Publication Year: 1990
Publication Date: 1990-03-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 37
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