Stock {AMPLE}

R6 Class representing a stock

Description

A stock object has life history parameters, fields and methods for a biomass dynamic model.

Details

A stock has biomass, effort, catch and hcr_ip and hcr_op fields as well as the life history parameters. The population dynamics are a simple biomass dynamic model. The Stock class is used for the Shiny apps in the AMPLE package.

Public fields

biomass

Array of biomass

catch

Array of catches

effort

Array of fishing effort

hcr_ip

Array of HCR input signals

hcr_op

Array of HCR output signals

msy

MSY (default = 100).

r

Growth rate (default = 0.6). Set by the user in the app.

k

Carrying capacity (default = NULL - set by msy and r when object is initialised).

p

Shape of the production curve (default = 1).

q

Catchability (default = 1).

lrp

Limit reference point, expressed as depletion (default = 0.2).

trp

Target reference point, expressed as depletion (default = 0.5).

b0

Virgin biomass (default = NULL - set by msy and r when object is initialised).

current_corrnoise

Stores the current values of the correlated noise (by iteration).

biol_sigma

Standard deviation of biological variability (default = 0).

last_historical_timestep

The last historical timestep of catch and effort data.

Methods

Public methods

• Stock$new()

• Stock$reset()

• Stock$reactive()

• Stock$fill_history()

• Stock$fill_catch_history()

• Stock$fill_biomass()

• Stock$as_data_frame()

• Stock$project()

• Stock$relative_cpue()

• Stock$relative_effort()

• Stock$replicate_table()

• Stock$time_periods()

• Stock$performance_indicators()

• Stock$pi_table()

• Stock$clone()

Method new()

Create a new stock object, with fields of the right dimension and NA values (by calling the reset() method. See the reset() method for more details.

Usage

Stock$new(stock_params, mp_params, niters = 1)

Arguments

stock_params

A list of stock parameters with essential elements: r (growth rate, numeric), stock_history (string: "fully", "over", "under") initial_year (integer), last_historical_timestep (integer), nyears (integer), biol_sigma (numeric).

mp_params

A list of the MP parameters. Used to fill HCR ip and op.

niters

The number of iters in the stock (default = 1).

Returns

A new Stock object.

Method reset()

Resets an existing stock object, by remaking all fields (possibly with different dimensions for the array fields) . Fills up the catch, effort and biomass fields in the historical period based on the stock history and life history parameters in the stock_params argument. This is a reactive method which invalidates a reactive instance of this class after it is called.

Usage

Stock$reset(stock_params, mp_params, niters)

Arguments

stock_params

A list with essential elements: r (growth rate, numeric, default=6), stock_history (string: "fully", "over", "under", default="fully") initial_year (integer, default=2000), last_historical_timestep (integer, default=10), nyears (integer, default=30), biol_sigma (numeric, default = 0).

mp_params

A list of the MP parameters. Used to fill HCR ip and op.

niters

The number of iters in the stock (default = 1).

Returns

A new Stock object.

Method reactive()

Method to create a reactive instance of a Stock.

Usage

Stock$reactive()

Returns

a reactiveExpr.

Method fill_history()

Fills the historical period of the stock

Usage

Stock$fill_history(stock_params, mp_params)

Arguments

stock_params

Named list with last_historical_timestep and stock_history elements.

mp_params

A list of the MP parameters. Used to fill HCR ip and op.

Method fill_catch_history()

Fill up the historical period of catches with random values to simulate a catch history

Usage

Stock$fill_catch_history(stock_params)

Arguments

stock_params

A list with essential elements: r (growth rate, numeric), stock_history (string: "fully", "over", "under") initial_year (integer), last_historical_timestep (integer), nyears (integer).

stock_history

Character string of the exploitation history (default = "fully", alternatives are "under" or "over").

Method fill_biomass()

Fills the biomass in the next timestep based on current biomass and catches The surplus production model has the general form: Bt+1 = Bt + f(Bt) - Ct Where the production function f() is a Pella & Tomlinson model with shape f(Bt) = r/p Bt * (1 - (Bt/k)^p) Here p is fixed at 1 to give a Schaefer model cpue = Ct / Et = qBt

Usage

Stock$fill_biomass(ts, iters = 1:dim(self$biomass)[1])

Arguments

ts

The biomass time step to be filled (required catch etc in ts - 1).

iters

The iterations to calculate the biomass for (optional - default is all of them).

Method as_data_frame()

Produces a data.frame of some of the array-based fields, like biomass. Just used for testing purposes.

Usage

Stock$as_data_frame()

Method project()

Projects the stock over the time steps given and updates the biomass, HCR ip / op and catches It uses a simple biomass dynamic model where the catches or fishing effort are set every time step by the harvest control rule.

Usage

Stock$project(timesteps, mp_params, iters = 1:dim(self$biomass)[1])

Arguments

timesteps

The timesteps to project over. A vector of length 2 (start and end).

mp_params

A vector of management procedure parameters.

iters

A vector of iterations to be projected. Default is all the iterations in the stock

Returns

A stock object (a reactiveValues object with bits for the stock)

Method relative_cpue()

The catch per unit effort (CPUE, or catch rate) relative to the CPUE in the last historical period.

Usage

Stock$relative_cpue()

Returns

An array of same dims as the catch and effort fields.

Method relative_effort()

The effort relative to the effort in the last historical period.

Usage

Stock$relative_effort()

Returns

An array of same dims as the effort field.

Method replicate_table()

Summarises the final year of each iteration. Only used for the Measuring Performance app.

Usage

Stock$replicate_table(iters = 1, quantiles = c(0.05, 0.95))

Arguments

iters

The iterations to calculate the table values for (default is iteration 1).

quantiles

Numeric vector of the quantile range. Default values are 0.05 and 0.95.

Method time_periods()

Calculates the short, medium and long term periods to calculate the performance indicators over, based on the last historic year of data and the number of years in the projection.

Usage

Stock$time_periods()

Method performance_indicators()

Gets the performance indicators across all indicators, for three time periods. Used in the Measuring Performance and Comparing Performance apps.

Usage

Stock$performance_indicators(
  iters = 1:dim(self$biomass)[1],
  quantiles = c(0.05, 0.95)
)

Arguments

iters

The iterations to calculate the table values for (default is all of them).

quantiles

Numeric vector of the quantile range. Default values are 0.05 and 0.95.

Returns

A data.frame

Method pi_table()

Makes a table of the performance indicators.

Usage

Stock$pi_table(iters = 1:dim(self$biomass)[1], quantiles = c(0.05, 0.95))

Arguments

iters

The iterations to calculate the table values for (default is all of them).

quantiles

Numeric vector, length 2, of the low and high quantiles.

Method clone()

The objects of this class are cloneable with this method.

Usage

Stock$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.