Table 1.

Summary of frequently used terms, including acronyms and abbreviations. Detailed description of the models is available in the Methods section.

TermDescription
General
AMAssessment model
FInstantaneous fishing mortality
MInstantaneous natural mortality
MAModel averaging, a MP that averages the catch advice from two AMs
MPManagement procedure
nraNot rho adjusted (MP)
OMOperating model
PmatProportion of mature individuals in the survey age composition, used as an OM indicator in the closed-loop simulation
raRho adjusted (MP)
rhoA metric used to describe the magnitude and direction of the retrospective pattern
SRAStock Reduction Analysis, the age-structured model used as the AM in MPs and for developing OMs
SSBSpawning stock biomass
Models
M02Cod AM with constant M = 0.2
MRAMPCod AM where M has increased to 0.4
MCCod OM conditioned assuming MCs from observed values (catch is underreported) and constant M = 0.2
IMCod OM conditioned assuming an increase in natural mortality to 0.45
MCIMCod OM conditioned with both MCs and an increase in M
BasePollock AM with dome survey selectivity
FlatSelPollock AM with flat-topped survey selectivity
SSPollock OM with more extreme dome survey selectivity compared to Base
SWBPollock OM with dome survey selectivity; conditioning model upweighted survey likelihoods to remove retrospective pattern.
SWFPollock OM with flat-topped survey selectivity; conditioning model upweighted survey likelihoods to remove retrospective pattern
Performance metrics
PNOFProbability of not overfishing (F < FMSY) in the OM
PB50Probability of exceeding 50% SSBMSY in the OM
TermDescription
General
AMAssessment model
FInstantaneous fishing mortality
MInstantaneous natural mortality
MAModel averaging, a MP that averages the catch advice from two AMs
MPManagement procedure
nraNot rho adjusted (MP)
OMOperating model
PmatProportion of mature individuals in the survey age composition, used as an OM indicator in the closed-loop simulation
raRho adjusted (MP)
rhoA metric used to describe the magnitude and direction of the retrospective pattern
SRAStock Reduction Analysis, the age-structured model used as the AM in MPs and for developing OMs
SSBSpawning stock biomass
Models
M02Cod AM with constant M = 0.2
MRAMPCod AM where M has increased to 0.4
MCCod OM conditioned assuming MCs from observed values (catch is underreported) and constant M = 0.2
IMCod OM conditioned assuming an increase in natural mortality to 0.45
MCIMCod OM conditioned with both MCs and an increase in M
BasePollock AM with dome survey selectivity
FlatSelPollock AM with flat-topped survey selectivity
SSPollock OM with more extreme dome survey selectivity compared to Base
SWBPollock OM with dome survey selectivity; conditioning model upweighted survey likelihoods to remove retrospective pattern.
SWFPollock OM with flat-topped survey selectivity; conditioning model upweighted survey likelihoods to remove retrospective pattern
Performance metrics
PNOFProbability of not overfishing (F < FMSY) in the OM
PB50Probability of exceeding 50% SSBMSY in the OM
Table 1.

Summary of frequently used terms, including acronyms and abbreviations. Detailed description of the models is available in the Methods section.

TermDescription
General
AMAssessment model
FInstantaneous fishing mortality
MInstantaneous natural mortality
MAModel averaging, a MP that averages the catch advice from two AMs
MPManagement procedure
nraNot rho adjusted (MP)
OMOperating model
PmatProportion of mature individuals in the survey age composition, used as an OM indicator in the closed-loop simulation
raRho adjusted (MP)
rhoA metric used to describe the magnitude and direction of the retrospective pattern
SRAStock Reduction Analysis, the age-structured model used as the AM in MPs and for developing OMs
SSBSpawning stock biomass
Models
M02Cod AM with constant M = 0.2
MRAMPCod AM where M has increased to 0.4
MCCod OM conditioned assuming MCs from observed values (catch is underreported) and constant M = 0.2
IMCod OM conditioned assuming an increase in natural mortality to 0.45
MCIMCod OM conditioned with both MCs and an increase in M
BasePollock AM with dome survey selectivity
FlatSelPollock AM with flat-topped survey selectivity
SSPollock OM with more extreme dome survey selectivity compared to Base
SWBPollock OM with dome survey selectivity; conditioning model upweighted survey likelihoods to remove retrospective pattern.
SWFPollock OM with flat-topped survey selectivity; conditioning model upweighted survey likelihoods to remove retrospective pattern
Performance metrics
PNOFProbability of not overfishing (F < FMSY) in the OM
PB50Probability of exceeding 50% SSBMSY in the OM
TermDescription
General
AMAssessment model
FInstantaneous fishing mortality
MInstantaneous natural mortality
MAModel averaging, a MP that averages the catch advice from two AMs
MPManagement procedure
nraNot rho adjusted (MP)
OMOperating model
PmatProportion of mature individuals in the survey age composition, used as an OM indicator in the closed-loop simulation
raRho adjusted (MP)
rhoA metric used to describe the magnitude and direction of the retrospective pattern
SRAStock Reduction Analysis, the age-structured model used as the AM in MPs and for developing OMs
SSBSpawning stock biomass
Models
M02Cod AM with constant M = 0.2
MRAMPCod AM where M has increased to 0.4
MCCod OM conditioned assuming MCs from observed values (catch is underreported) and constant M = 0.2
IMCod OM conditioned assuming an increase in natural mortality to 0.45
MCIMCod OM conditioned with both MCs and an increase in M
BasePollock AM with dome survey selectivity
FlatSelPollock AM with flat-topped survey selectivity
SSPollock OM with more extreme dome survey selectivity compared to Base
SWBPollock OM with dome survey selectivity; conditioning model upweighted survey likelihoods to remove retrospective pattern.
SWFPollock OM with flat-topped survey selectivity; conditioning model upweighted survey likelihoods to remove retrospective pattern
Performance metrics
PNOFProbability of not overfishing (F < FMSY) in the OM
PB50Probability of exceeding 50% SSBMSY in the OM
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