An object for storing fishery data for analysis

`Name`

The name of the Data object. Single value. Character string

`Common_Name`

Common name of the species. Character string

`Species`

Scientific name of the species. Genus and species name. Character string

`Region`

Name of the general geographic region of the fishery. Character string

`LHYear`

The last historical year of the simulation (before projection). Single value. Positive integer

`MPrec`

The previous recommendation of a management procedure. Vector of length nsim. Positive real numbers

`Units`

Units of the catch/absolute abundance estimates. Single value. Character string

`MPeff`

The current level of effort. Vector of length nsim. Positive real numbers

`nareas`

Number of fishing areas. Vector of length nsim. Non-negative integer

`MaxAge`

Maximum age. Vector nsim long. Positive integer

`Mort`

Natural mortality rate. Vector nsim long. Positive real numbers

`CV_Mort`

Coefficient of variation in natural mortality rate. Vector nsim long. Positive real numbers

`vbLinf`

Maximum length. Vector nsim long. Positive real numbers

`CV_vbLinf`

Coefficient of variation in maximum length. Vector nsim long. Positive real numbers

`vbK`

The von Bertalanffy growth coefficient K. Vector nsim long. Positive real numbers

`CV_vbK`

Coefficient of variation in the von Bertalanffy K parameter. Vector nsim long. Positive real numbers

`vbt0`

Theoretical age at length zero. Vector nsim long. Non-positive real numbers

`CV_vbt0`

Coefficient of variation in age at length zero. Vector nsim long. Positive real numbers

`wla`

Weight-Length parameter alpha. Vector nsim long. Positive real numbers

`CV_wla`

Coefficient of variation in weight-length parameter a. Vector nsim long. Positive real numbers

`wlb`

Weight-Length parameter beta. Vector nsim long. Positive real numbers

`CV_wlb`

Coefficient of variation in weight-length parameter b. Vector nsim long. Positive real numbers

`steep`

Steepness of stock-recruitment relationship. Vector nsim long. Value in the range of one-fifth to 1

`CV_steep`

Coefficient of variation in steepness. Vector nsim long. Positive real numbers

`sigmaR`

Recruitment variability. Vector nsim long. Positive real numbers

`CV_sigmaR`

Coefficient of variation in recruitment variability. Vector nsim long. Positive real numbers

`L50`

Length at 50 percent maturity. Vector nsim long. Positive real numbers

`CV_L50`

Coefficient of variation in length at 50 per cent maturity. Vector nsim long. Positive real numbers

`L95`

Length at 95 percent maturity. Vector nsim long. Positive real numbers

`LenCV`

Coefficient of variation of length-at-age (assumed constant for all age classes). Vector nsim long. Positive real numbers

`LFC`

Length at first capture. Vector nsim long. Positive real numbers

`CV_LFC`

Coefficient of variation in length at first capture. Vector nsim long. Positive real numbers

`LFS`

Shortest length at full selection. Vector nsim long. Positive real numbers

`CV_LFS`

Coefficient of variation in length at full selection. Vector nsim long. Positive real numbers

`Vmaxlen`

Vulnerability of individuals at asymptotic length. Vector nsim long. Real number between 0 and 1.

`Year`

Years that corresponding to catch and relative abundance data. Vector nyears long. Positive integer

`Cat`

Total annual catches. Matrix of nsim rows and nyears columns. Non-negative real numbers

`CV_Cat`

Coefficient of variation in annual catches. Matrix nsim rows and either 1 or nyear columns. Positive real numbers. Note: built-in MPs use only the first value of

`CV_Cat`

for all years.`Effort`

Annual fishing effort. Matrix of nsim rows and nyears columns. Non-negative real numbers

`CV_Effort`

Coefficient of variation in annual effort. Matrix nsim rows and either 1 or nyear columns. Positive real numbers. Note: built-in MPs use only the first value of

`CV_Effort`

for all years.`Ind`

Relative total abundance index. Matrix of nsim rows and nyears columns. Non-negative real numbers

`CV_Ind`

Coefficient of variation in the relative total abundance index. Matrix nsim rows and either 1 or nyear columns. Positive real numbers. Note: built-in MPs use only the first value of

`CV_Ind`

for all years`SpInd`

Relative spawning abundance index. Matrix of nsim rows and nyears columns. Non-negative real numbers

`CV_SpInd`

Coefficient of variation in the relative spawning abundance index. Matrix nsim rows and either 1 or nyear columns. Positive real numbers.

`VInd`

Relative vulnerable abundance index. Matrix of nsim rows and nyears columns. Non-negative real numbers

`CV_VInd`

Coefficient of variation in the relative vulnerable abundance index. Matrix nsim rows and either 1 or nyear columns. Positive real numbers.

`AddInd`

Optional additional indices. Array of dimensions

`nsim`

, n additional indices, and`nyears`

(length`Year`

).`CV_AddInd`

Coefficient of variation for additional indices. Array of same dimensions as

`AddInd`

`AddIndV`

Vulnerability-at-age schedules for the additional indices. Array with dimensions:

`nsim`

, n additional indices,`MaxAge+1`

.`AddIunits`

Units for the additional indices - biomass (1; default) or numbers (0). Numeric vector length n.ind.

`AddIndType`

Index calculated from total stock (1, default), spawning stock (2), or vulnerable stock (3). Numeric vector of length n.ind

`Rec`

Recent recruitment strength. Matrix of nsim rows and nyears columns. Non-negative real numbers

`CV_Rec`

Log-normal CV for recent recruitment strength. Matrix nsim rows and either 1 or nyear columns. Positive real numbers. Note: built-in MPs use only the first value of

`CV_Rec`

for all years.`ML`

Mean length time series. Matrix of nsim rows and nyears columns. Non-negative real numbers

`Lc`

Modal length of catches. Matrix of nsim rows and nyears columns. Positive real numbers

`Lbar`

Mean length of catches over Lc. Matrix of nsim rows and nyears columns. Positive real numbers

`Vuln_CAA`

Optional vulnerability-at-age schedule for catch-at-age samples. Used to condition OM for closed-loop simulation testing. Replaces the fleet selectivity schedule in the OM used to generate CAA samples. Matrix with dimensions

`nsim`

x`MaxAge+1`

.`CAA`

Catch at Age data (numbers). Array of dimensions nsim x nyears x MaxAge+1. Non-negative integers

`Vuln_CAL`

Optional vulnerability-at-length schedule for catch-at-length samples. Used to condition OM for closed-loop simulation testing. Replaces the fleet selectivity schedule in the OM used to generate CAL samples. Matrix with dimensions

`nsim`

x`length(CAL_mids)`

.`CAL_bins`

The values delimiting the length bins for the catch-at-length data. Vector. Non-negative real numbers

`CAL_mids`

The values of the mid-points of the length bins. Optional, calculated from

`CAL_bins`

if not entered. Vector. Non-negative real numbers.`CAL`

Catch-at-length data. An array with dimensions nsim x nyears x length(CAL_mids). Non-negative integers. By default the CAL data will be the retained lengths (i.e, not including discards). If

`OM@control$CAL =="removals"`

then the CAL data will include all removals (retained + discards).`Dep`

Stock depletion SSB(current)/SSB(unfished). Vector nsim long. Fraction.

`CV_Dep`

Coefficient of variation in current stock depletion. Vector nsim long. Positive real numbers

`Abun`

An estimate of absolute current vulnerable abundance. Vector nsim long. Positive real numbers

`CV_Abun`

Coefficient of variation in estimate of absolute current stock size. Vector nsim long. Positive real numbers

`SpAbun`

An estimate of absolute current spawning stock abundance. Vector nsim long. Positive real numbers

`CV_SpAbun`

Coefficient of variation in estimate of absolute spawning current stock size. Vector nsim long. Positive real numbers

`FMSY_M`

An assumed ratio of FMSY to M. Vector nsim long. Positive real numbers

`CV_FMSY_M`

Coefficient of variation in the ratio in FMSY/M. Vector nsim long. Positive real numbers

`BMSY_B0`

The most productive stock size relative to unfished. Vector nsim long. Fraction

`CV_BMSY_B0`

Coefficient of variation in the position of the most productive stock size relative to unfished. Vector nsim long. Positive real numbers

`Cref`

Reference or target catch level (eg MSY). Vector of length nsim. Positive real numbers

`CV_Cref`

Log-normal CV for reference or target catch level. Vector of length nsim. Positive real numbers

`Bref`

Reference or target biomass level (eg BMSY). Vector of length nsim. Positive real numbers

`CV_Bref`

Log-normal CV for reference or target biomass level. Vector of length nsim. Positive real numbers

`Iref`

Reference or target relative abundance index level (eg BMSY / B0). Vector of length nsim. Positive real numbers

`CV_Iref`

Log-normalCV for reference or target relative abundance index level. Vector of length nsim. Positive real numbers

`t`

The number of years corresponding to AvC and Dt. Single value. Positive integer

`AvC`

Average catch over time t. Vector nsim long. Positive real numbers

`CV_AvC`

Coefficient of variation in average catches over time t. Vector nsim long. Positive real numbers

`Dt`

Depletion over time t SSB(now)/SSB(now-t+1). Vector nsim long. Fraction

`CV_Dt`

Coefficient of variation in depletion over time t. Vector nsim long. Positive real numbers

`Ref`

A reference management level (eg a catch limit). Single value. Positive real number

`Ref_type`

Type of reference management level (eg 2009 catch limit). Single value. Character string

`Log`

A record of events. Single value. Character string

`params`

A place to store estimated parameters. An object. R list

`PosMPs`

The methods that can be applied to these data. Vector. Character strings

`TAC`

The calculated catch limits (function TAC). An array with dimensions PosMPs x replicate TAC samples x nsim. Positive real numbers

`Sense`

The results of the sensitivity analysis (function Sense). An array with dimensions PosMPs x sensitivity increments. Positive real numbers

`MPs`

The methods that were applied to these data. Vector. Character strings

`OM`

A table of operating model conditions. R table object of nsim rows. Real numbers

`Obs`

A table of observation model conditions. R table object of nsim rows. Real numbers

`Misc`

Other information for MPs. An object. R list

Objects can be created by calls of the form
`new('Data', stock)`

T. Carruthers and A. Hordyk

newdata<-new('Data')