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Defining Fisheries Reference Points Given Time-Varying Life History Parameters
Gavin Fay
,
CSIRO Wealth from Oceans National Research Flagship, CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia
Elizabeth Fulton
,
CSIRO Wealth from Oceans National Research Flagship, CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia
Geoff Tuck
,
CSIRO Wealth from Oceans National Research Flagship, CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia
Athol Whitten
,
CSIRO Wealth from Oceans National Research Flagship, CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia
Judith Upston
,
CSIRO Wealth from Oceans National Research Flagship, CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia
Variability over time in life history parameters is well-documented for many commercially exploited fish populations, with examples including (but not limited to) changes in natural mortality, growth, stock productivity, fecundity, and length at maturity. Accepting that these life history variables change when conducting stock assessments has implications for the calculation of fisheries reference points used to determine management action, as these will by design also change through time with the changes in parameter values. Methods for incorporating changes in biological parameters into stock assessment software are becoming well-established. How to choose relevant reference points for providing management action given such changes, however, remains an elusive challenge.
Using single- and multi-species models of commercial fisheries in Southeast Australia, we demonstrate the importance of accounting for changes in life history when calculating commonly used reference points. Focusing on incorporating changes in natural mortality rates due to trophic interactions, we then apply Management Strategy Evaluation (MSE) to compare the performance of alternative methods of calculating the values of fisheries reference points for harvest control rules currently used to determine scientific advice for setting catch quotas. Simulation scenarios are evaluated by calculating performance measures related to maintaining biomass, catches, and meeting management objectives with respect to risk of stock decline. Highlighting the differences in results from approaches that assume time-invariant biology (invariably the status quo) with those that take a more responsive and dynamic approach when calculating reference points, we discuss both the utility and efficacy of applying management methods that account for such changes.