This work was carried out under the provision of the ICCAT Atlantic Wide Research Programme for Bluefin Tuna (GBYP), funded by the European Union, several ICCAT CPCs, the ICCAT Secretariat and by other entities (see: http://www.iccat.int/GBYP/en/Budget.htm). The contents of this paper do not necessarily reflect the point of view of ICCAT or other funders and in no ways anticipate ICCAT future policy in this area.
The Atlantic-Wide Research Programme on Bluefin Tuna (GBYP) is investigating MSE for
providing robust advice consistent with the precautionary approach. MSE aims to reveal
management procedures that are robust to uncertainties in data collection, population and
fishing dynamics. In MSE these uncertainties are represented by alternative operating models (OMs).
In this PRELIMINARY interactive demo, the user can choose different sets of operating models to investigate
how uncertainties affect performance trade-offs and stock projections for multiple candidate management procedures.
Median/mean of the selected performance metrics over all simulations and selected OMs
East
West
Table 2.
Median and interquantile range of the selected performance metrics over all simulations and selected OMs
East Area
West Area
Figure 1.
Zeh plot showing the median, interquartile and 90% interquantile range for a selected performance metric integrated over all simulations and selected OMs
Results plotted for OMset 1
East Area
West Area
Figure 2.
Zeh plot showing results for OM set 1 operating models individually. Plotted are the median, interquartile and 90% interquantile range for a selected performance metric over all simulations
East Area
West Area
Figure 3.
As Figure 1 but showing multiple performance metrics simultaneously. Plotted are the median, interquartile and 90% interquantile range for three performance metrics over all simulations
Eastern Area
Western Area
Figure 4.
A trade-off plot showing median performance over all selected OMs and simulations.
Area / Stock Trade-offs
Figure 5.
A trade-off plot showing inter stock / area median performance over all selected OMs and simulations.
! does not account for OM weights !
Eastern Stock
Western Stock
Figure 6.
Catch (by area) and SSB (by stock) projections calculated over all selected OMs and simulations.
! does not account for OM weights !
Eastern Stock
Western Stock
Figure 7.
As figure 6 but showing uncertainty in Catch (by area) and SSB (by stock) outcomes for up to three MPs. The projected values of catch (by area) and SSB (by stock) are the mean values across all simulations and selected OMs.
Eastern Stock
Western Stock
Figure 8.
As figure 7 but showing by-simulation results for a single OM for up to two MPs. The projected values of catch (by area) and SSB (by stock) are the mean values across all simulations and selected OMs.
! does not account for OM weights !
Eastern Stock
Western Stock
Figure 9.
Harvest rate (U) relative to UMSY (by stock) projections calculated over all selected OMs and simulations.
Eastern Stock
Western Stock
Figure 10.
Radar plots show the mean of the performance metrics (over all simulations and selected OMs).
Radar plots are intended to distinguish good and bad performing CMPs according to the shaded area. It follows
that some metrics are either inverted (denoted with an i) or are a reciprocal (r) such that larger plotted
areas reflect better performance.
Figure 11.
As Figure 9 but allowing for cross-stock performance evaluation. Plots show the mean of the performance metrics (over all simulations and selected OMs).
Radar plots are intended to distinguish good and bad performing CMPs according to the shaded area. It follows
that some metrics are either inverted (denoted with an i) or are a reciprocal (r) such that larger plotted
areas reflect better performance.
Results plotted for OMset 1
East area / eastern stock
West area / western stock
Figure 12.
Worm plot showing results for OMset 1. Solid line with points represents
the unweighted median. The shaded area is the 80% interquantile range. Thin lines are
individual simulations
