Package {mizer}

Title:	Dynamic Multi-Species Size Spectrum Modelling
Date:	2026-06-06
Type:	Package
Description:	A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.
Maintainer:	Gustav Delius <gustav.delius@york.ac.uk>
Version:	3.0.0
License:	GPL-3
Imports:	assertthat, deSolve, dplyr, ggplot2 (≥ 3.4.0), ggrepel, grid, lubridate, methods, plotly, plyr, progress, Rcpp, reshape2, rlang, lifecycle, pak
LinkingTo:	Rcpp
Depends:	R (≥ 3.5)
Suggests:	testthat (≥ 3.0.0), withr, vdiffr, diffviewer, roxygen2, knitr, rmarkdown, quarto, pkgdown, covr, spelling
Collate:	'age_mat.R' 'helpers.R' 'MizerParams-class.R' 'MizerSim-class.R' 'registerExtensions.R' 'ArraySpeciesBySize-class.R' 'ArrayTimeBySpecies-class.R' 'ArrayTimeBySpeciesBySize-class.R' 'generic_methods.R' 'background.R' 'reproduction.R' 'saveParams.R' 'species_params.R' 'getRequiredRDD.R' 'setColours.R' 'setInteraction.R' 'setPredKernel.R' 'setSearchVolume.R' 'setMaxIntakeRate.R' 'setMetabolicRate.R' 'setMetadata.R' 'setExtMort.R' 'setExtEncounter.R' 'diffusion.R' 'setExtDiffusion.R' 'setReproduction.R' 'setResource.R' 'setFishing.R' 'setInitialValues.R' 'setBevertonHolt.R' 'upgrade.R' 'selectivity_funcs.R' 'pred_kernel_funcs.R' 'resource_dynamics.R' 'resource_semichemostat.R' 'resource_logistic.R' 'numerical_methods.R' 'transport.R' 'project_n.R' 'project.R' 'mizer-package.R' 'project_methods.R' 'rate_functions.R' 'summary_methods.R' 'indicator_functions.R' 'plots.R' 'plotBiomassObservedVsModel.R' 'plotYieldObservedVsModel.R' 'animateSpectra.R' 'newMultispeciesParams.R' 'wrapper_functions.R' 'newSingleSpeciesParams.R' 'steady.R' 'extension.R' 'data.R' 'RcppExports.R' 'deprecated.R' 'get_initial_n.R' 'compareParams.R' 'customFunction.R' 'manipulate_species.R' 'calibrate.R' 'scaleRates.R' 'match.R' 'matchGrowth.R' 'steadySingleSpecies.R' 'defaults_edition.R' 'validSpeciesParams.R'
Encoding:	UTF-8
LazyData:	true
URL:	https://sizespectrum.org/mizer/, https://github.com/sizespectrum/mizer
BugReports:	https://github.com/sizespectrum/mizer/issues
Language:	en-GB
RdMacros:	lifecycle
VignetteBuilder:	knitr, quarto
Config/testthat/edition:	3
Config/roxygen2/version:	8.0.0
NeedsCompilation:	yes
Packaged:	2026-06-08 14:19:40 UTC; gustav
Author:	Gustav Delius [cre, aut, cph], Finlay Scott [aut, cph], Julia Blanchard [aut, cph], Ken Andersen [aut, cph], Richard Southwell [ctb, cph]
Repository:	CRAN
Date/Publication:	2026-06-08 14:50:02 UTC

mizer: Multi-species size-based modelling in R

Description

The mizer package implements multi-species size-based modelling in R. It has been designed for modelling marine ecosystems.

Details

Using mizer is relatively simple. There are three main stages:

1. Setting the model parameters. This is done by creating an object of class MizerParams. This includes model parameters such as the life history parameters of each species, and the range of the size spectrum. There are several setup functions that help to create a MizerParams objects for particular types of models:

   • newSingleSpeciesParams()

   • newCommunityParams()

   • newTraitParams()

   • newMultispeciesParams()

2. Running a simulation. This is done by calling the project() function with the model parameters. This produces an object of MizerSim that contains the results of the simulation.

3. Exploring results. After a simulation has been run, the results can be explored using a range of plotting_functions, summary_functions and indicator_functions.

See the mizer website for full details of the principles behind mizer and how the package can be used to perform size-based modelling.

Author(s)

Maintainer: Gustav Delius gustav.delius@york.ac.uk (ORCID) [copyright holder]

Authors:

• Gustav Delius gustav.delius@york.ac.uk (ORCID) [copyright holder]

• Finlay Scott drfinlayscott@gmail.com [copyright holder]

• Julia Blanchard julia.blanchard@utas.edu.au (ORCID) [copyright holder]

• Ken Andersen kha@aqua.dtu.dk (ORCID) [copyright holder]

Other contributors:

• Richard Southwell richard.southwell@york.ac.uk [contributor, copyright holder]

See Also

Useful links:

• https://sizespectrum.org/mizer/

• https://github.com/sizespectrum/mizer

• Report bugs at https://github.com/sizespectrum/mizer/issues

Check that a rate function returns the correct output dimensions

Description

Called by setRateFunction() to verify that a candidate rate function returns an array (or vector/list) of the correct dimensions for the requested rate.

Usage

.checkRateFunctionOutput(params, rate, fun)

Arguments

Value

Invisibly NULL. Called for its side-effect of stopping with an informative error if the output has the wrong shape.

S3 class for species x size rate arrays

Description

Many functions in mizer return two-dimensional arrays (species x size) holding rates like encounter rate, feeding level, growth rate, mortality etc. The ArraySpeciesBySize class wraps these arrays to provide convenient print(), summary(), plot(), and as.data.frame() methods.

Usage

ArraySpeciesBySize(x, value_name = NULL, units = NULL, params = NULL)

Arguments

Details

An ArraySpeciesBySize object behaves just like a regular matrix for arithmetic operations and subsetting. It carries two lightweight attributes:

• value_name – a human-readable name for the value (e.g. "Encounter rate").

• units – the units of the rate (e.g. "g/year").

Value

An ArraySpeciesBySize object (inherits from matrix and array).

See Also

print(), summary(), as.data.frame(), plot()

Examples

enc <- getEncounter(NS_params)
is.ArraySpeciesBySize(enc)
summary(enc)

S3 class for time x species arrays

Description

Some functions in mizer return two-dimensional arrays (time x species) holding quantities like biomass, abundance, or yield rate through time. The ArrayTimeBySpecies class wraps these arrays to provide convenient print(), summary(), plot(), and as.data.frame() methods.

Usage

ArrayTimeBySpecies(x, value_name = NULL, units = NULL, params = NULL)

Arguments

Details

An ArrayTimeBySpecies object behaves just like a regular matrix for arithmetic operations and subsetting. It carries these lightweight attributes:

• value_name – a human-readable name for the value (e.g. "Biomass").

• units – the units of the value (e.g. "g", "g/year").

• params – the MizerParams object that created the values.

Value

An ArrayTimeBySpecies object (inherits from matrix and array).

See Also

print(), summary(), as.data.frame(), plot()

Examples

bio <- getBiomass(NS_sim)
is.ArrayTimeBySpecies(bio)
summary(bio)

S3 class for time x species x size arrays

Description

Some functions in mizer return three-dimensional arrays (time x species x size) holding quantities like fishing mortality, feeding level, or predation mortality through time. The ArrayTimeBySpeciesBySize class wraps these arrays to provide convenient print(), summary(), plot(), animate(), and as.data.frame() methods.

Usage

ArrayTimeBySpeciesBySize(x, value_name = NULL, units = NULL, params = NULL)

Arguments

Details

An ArrayTimeBySpeciesBySize object behaves just like a regular array for arithmetic operations and subsetting. It carries these lightweight attributes:

• value_name – a human-readable name for the value (e.g. "Fishing mortality").

• units – the units of the value (e.g. "1/year").

• params – the MizerParams object that the value was computed from.

Value

An ArrayTimeBySpeciesBySize object (inherits from array).

See Also

print(), summary(), as.data.frame(), plot(), animateSpectra()

Examples

fmort <- getFMort(NS_sim)
is.ArrayTimeBySpeciesBySize(fmort)
summary(fmort)
plot(fmort, time = 2007)

Beverton Holt function to calculate density-dependent reproduction rate

Description

Takes the density-independent rates R_{di} of egg production (as calculated by getRDI()) and returns reduced, density-dependent reproduction rates R_{dd} given as

R_{dd} = R_{di} \frac{R_{max}}{R_{di} + R_{max}}

where R_{max} are the maximum possible reproduction rates that must be specified in a column in the species parameter dataframe. (All quantities in the above equation are species-specific but we dropped the species index for simplicity.)

Usage

BevertonHoltRDD(rdi, species_params, ...)

Arguments

Details

This is only one example of a density-dependence. You can write your own function based on this example, returning different density-dependent reproduction rates. Three other examples provided are RickerRDD(), SheperdRDD(), noRDD() and constantRDD(). For more explanation see setReproduction().

Value

Vector of density-dependent reproduction rates.

See Also

Other functions calculating density-dependent reproduction rate: RickerRDD(), SheperdRDD(), constantEggRDI(), constantRDD(), noRDD()

Alias for set_multispecies_model()

Description

An alias provided for backward compatibility with mizer version <= 1.0

Usage

MizerParams(
  species_params,
  interaction = matrix(1, nrow = nrow(species_params), ncol = nrow(species_params)),
  min_w_pp = 1e-10,
  min_w = 0.001,
  max_w = NULL,
  no_w = 100,
  n = 2/3,
  q = 0.8,
  f0 = 0.6,
  kappa = 1e+11,
  lambda = 2 + q - n,
  r_pp = 10,
  ...
)

Arguments

Details

If species_params contains a w_inf column then it is copied to w_max. If max_w is not supplied then it is set to 1.1 * max(species_params$w_max). The supplied min_w_pp is shifted up by one grid step before being passed to newMultispeciesParams() to compensate for the fact that newer mizer versions extend the full size grid below min_w_pp.

Missing legacy columns in species_params are filled as follows: gear = species, k = 0, alpha = 0.6, erepro = 1, sel_func = "knife_edge", knife_edge_size = w_mat if needed, catchability = 1, ks = h * 0.2, and m = 1. If h is missing it is calculated from k_vb, alpha, f0 and w_max. If gamma is missing it is calculated from f0, h, beta, sigma, lambda and kappa.

Value

A MizerParams object

A class to hold the parameters for a size based model.

Description

Although it is possible to build a MizerParams object by hand it is not recommended and several constructors are available. Dynamic simulations are performed using project() function on objects of this class. As a user you should never need to access the slots inside a MizerParams object directly.

Details

The MizerParams class is fairly complex with a large number of slots, many of which are multidimensional arrays. The dimensions of these arrays is strictly enforced so that MizerParams objects are consistent in terms of number of species and number of size classes.

The MizerParams class does not hold any dynamic information, e.g. abundances or harvest effort through time. These are held in MizerSim objects.

Slots

metadata

A list with metadata information. See setMetadata().

mizer_version

The package version of mizer (as returned by packageVersion("mizer")) that created or upgraded the model.

extensions

A named vector of strings describing the extension chain needed to run the model. The names are extension identifiers and S4 marker class names. The order is the S3 dispatch order, from outermost to innermost extension. The values are version strings, installation specifications, or NA_character_. Extension subclasses are marker classes only and must not add slots.

time_created

A POSIXct date-time object with the creation time.

time_modified

A POSIXct date-time object with the last modified time.

w

The size grid for the fish part of the spectrum. An increasing vector of weights (in grams) running from the smallest egg size to the largest maximum size.

dw

The widths (in grams) of the size bins

w_full

The size grid for the full size range including the resource spectrum. An increasing vector of weights (in grams) running from the smallest resource size to the largest maximum size of fish. The last entries of the vector have to be equal to the content of the w slot.

dw_full

The width of the size bins for the full spectrum. The last entries have to be equal to the content of the dw slot.

w_min_idx

A vector holding the index of the weight of the egg size of each species

maturity

An array (species x size) that holds the proportion of individuals of each species at size that are mature. This enters in the calculation of the spawning stock biomass with getSSB(). Set with setReproduction().

psi

An array (species x size) that holds the allocation to reproduction for each species at size, \psi_i(w). Changed with setReproduction().

intake_max

An array (species x size) that holds the maximum intake for each species at size. Changed with setMaxIntakeRate().

search_vol

An array (species x size) that holds the search volume for each species at size. Changed with setSearchVolume().

metab

An array (species x size) that holds the metabolism for each species at size. Changed with setMetabolicRate().

mu_b

An array (species x size) that holds the external mortality rate \mu_{ext.i}(w). Changed with setExtMort().

ext_encounter

An array (species x size) that holds the external encounter rate E_{ext.i}(w). Changed with setExtEncounter().

ext_diffusion

An array (species x size) that holds the external rate at which the abundance density is redistributed over body size due to mixing, beyond the deterministic growth dynamics. Changed with ext_diffusion().

pred_kernel

An array (species x predator size x prey size) that holds the predation coefficient of each predator at size on each prey size. If this is NA then the following two slots will be used. Changed with setPredKernel().

ft_pred_kernel_e

An array (species x log of predator/prey size ratio) that holds the Fourier transform of the feeding kernel in a form appropriate for evaluating the encounter rate integral. If this is NA then the pred_kernel will be used to calculate the available energy integral. Changed with setPredKernel().

ft_pred_kernel_p

An array (species x log of predator/prey size ratio) that holds the Fourier transform of the feeding kernel in a form appropriate for evaluating the predation mortality integral. If this is NA then the pred_kernel will be used to calculate the integral. Changed with setPredKernel().

rr_pp

A vector the same length as the w_full slot. The size specific growth rate of the resource spectrum.

cc_pp

A vector the same length as the w_full slot. The size specific carrying capacity of the resource spectrum.

resource_dynamics

Name of the function for projecting the resource abundance density by one timestep.

other_dynamics

A named list of functions for projecting the values of other dynamical components of the ecosystem that may be modelled by a mizer extensions you have installed. The names of the list entries are the names of those components.

other_encounter

A named list of functions for calculating the contribution to the encounter rate from each other dynamical component.

other_mort

A named list of functions for calculating the contribution to the mortality rate from each other dynamical components.

other_params

A list containing the parameters needed by any mizer extensions you may have installed to model other dynamical components of the ecosystem.

rates_funcs

A named list with the names of the functions that should be used to calculate the rates needed by project(). By default this will be set to the names of the built-in rate functions.

sc

The community abundance of the scaling community

species_params

A data.frame to hold the species specific parameters. See species_params() for details.

given_species_params

A data.frame to hold the species parameters that were given explicitly rather than obtained by default calculations.

gear_params

Data frame with parameters for gear selectivity. See setFishing() for details.

interaction

The species specific interaction matrix, \theta_{ij}. Changed with setInteraction().

selectivity

An array (gear x species x w) that holds the selectivity of each gear for species and size, S_{g,i,w}. Changed with setFishing().

catchability

An array (gear x species) that holds the catchability of each species by each gear, Q_{g,i}. Changed with setFishing().

initial_effort

A vector containing the initial fishing effort for each gear. Changed with setFishing().

initial_n

An array (species x size) that holds the initial abundance of each species at each weight.

initial_n_pp

A vector the same length as the w_full slot that describes the initial resource abundance at each weight.

initial_n_other

A list with the initial abundances of all other ecosystem components. Has length zero if there are no other components.

resource_params

List with parameters for resource.

A

Formerly used to flag background species via NA values. Replaced by the is_background column in species_params. Will be removed in a future version.

linecolour

A named vector of colour values, named by species. Used to give consistent colours in plots.

linetype

A named vector of linetypes, named by species. Used to give consistent line types in plots.

ft_mask

An array (species x w_full) with zeros for weights larger than the maximum weight of each species. Used to efficiently minimize wrap-around errors in Fourier transform calculations.

use_predation_diffusion

A logical flag controlling whether predation-induced diffusion is included when calculating rates with mizerDiffusion(). Defaults to FALSE to preserve the behaviour of previous mizer versions. Set to TRUE to enable the diffusion term from the jump-growth equation.

See Also

project() MizerSim() emptyParams() newMultispeciesParams() newCommunityParams() newTraitParams()

Constructor for the MizerSim class

Description

A constructor for the MizerSim class. This is used by project() to create MizerSim objects of the right dimensions. It is not necessary for users to use this constructor.

Usage

MizerSim(params, t_dimnames = NA, t_max = 100, t_save = 1)

Arguments

Value

An object of type MizerSim

A class to hold the results of a simulation

Description

A class that holds the results of projecting a MizerParams object through time using project().

Details

A new MizerSim object can be created with the MizerSim() constructor, but you will never have to do that because the object is created automatically by project() when needed.

As a user you should never have to access the slots of a MizerSim object directly. Instead there are a range of functions to extract the information. N() and NResource() return arrays with the saved abundances of the species and the resource population at size respectively. getEffort() returns the fishing effort of each gear through time. getTimes() returns the vector of times at which simulation results were stored and idxFinalT() returns the index with which to access specifically the value at the final time in the arrays returned by the other functions. getParams() extracts the ecosystem state as a MizerParams object with initial abundances set to values from the simulation; finalParams() and initialParams() are convenient shorthands for the final and initial time steps. There are also several summary_functions and plotting_functions available to explore the contents of a MizerSim object.

The arrays all have named dimensions. The names of the time dimension denote the time in years. The names of the w dimension are weights in grams rounded to three significant figures. The names of the sp dimension are the same as the species name in the order specified in the species_params data frame. The names of the gear dimension are the names of the gears, in the same order as specified when setting up the MizerParams object.

Extensions of mizer can use the n_other slot to store the abundances of other ecosystem components and these extensions should provide their own functions for accessing that information.

The MizerSim class has changed since previous versions of mizer. To use a MizerSim object created by a previous version, you need to upgrade it with validSim().

Slots

params

An object of type MizerParams. If this params object uses extensions, the MizerSim object uses the same extension chain via params@extensions; MizerSim has no separate extension slot.

n

Three-dimensional array (time x species x size) that stores the projected community number densities.

n_pp

An array (time x size) that stores the projected resource number densities.

n_other

A list array (time x component) that stores the projected values for other ecosystem components.

effort

An array (time x gear) that stores the fishing effort by time and gear.

sim_params

A named list of the parameters passed to project() or projectToSteady() to produce this simulation, such as method and dt.

Time series of size spectra

Description

Fetch the simulation results for the size spectra over time.

Usage

N(sim)

NResource(sim)

Arguments

Value

For N(): An ArrayTimeBySpeciesBySize object (time x species x size) with the number density of consumers.

For NResource(): An array (time x size) with the number density of resource

Examples

str(N(NS_sim))
str(NResource(NS_sim))

Time series of other components

Description

Fetch the simulation results for other components over time.

Usage

NOther(sim)

finalNOther(sim)

Arguments

Value

For NOther: A list array indexed by time and component that stores the projected values for other ecosystem components.

For finalNOther: A named list holding the values of other ecosystem components at the end of the simulation

See Also

Other extension tools: clearExtensionChain(), coerceToExtensionClass(), getRegisteredExtensions(), initialNOther<-(), registerExtension(), registerExtensions(), setComponent(), setRateFunction()

Example interaction matrix for the North Sea example

Description

The interaction coefficient between predator and prey species in the North Sea.

Usage

NS_interaction

Format

A 12 x 12 matrix.

Source

Blanchard et al.

Examples

params <- newMultispeciesParams(NS_species_params_gears,
                                interaction = NS_interaction)

Example MizerParams object for the North Sea example

Description

A MizerParams object created from the NS_species_params_gears species parameters and the inter interaction matrix together with an initial condition corresponding to the steady state obtained from fishing with an effort effort = c(Industrial = 0, Pelagic = 1, Beam = 0.5, Otter = 0.5).

Usage

NS_params

Format

A MizerParams object

Source

Blanchard et al.

See Also

Other example parameter objects: NS_sim

Examples

sim = project(NS_params, effort = c(Industrial = 0, Pelagic = 1, 
                                    Beam = 0.5, Otter = 0.5))
plot(sim)

Example MizerSim object for the North Sea example

Description

A MizerSim object containing a simulation with historical fishing mortalities from the North Sea, as created in the tutorial "A Multi-Species Model of the North Sea".

Usage

NS_sim

Format

A MizerSim object

Source

https://sizespectrum.org/mizer/articles/a_multispecies_model_of_the_north_sea.html

See Also

Other example parameter objects: NS_params

Examples

plotBiomass(NS_sim)

Example species parameter set based on the North Sea

Description

This data set is based on species in the North Sea (Blanchard et al.). It is a data.frame that contains all the necessary information to be used by the MizerParams() constructor. As there is no gear column, each species is assumed to be fished by a separate gear.

Usage

NS_species_params

Format

A data frame with 12 rows and 7 columns. Each row is a species.

species

Name of the species

w_max

Maximum size.

w_mat

Size at maturity

beta

Size preference ratio

sigma

Width of the size-preference

R_max

Maximum reproduction rate

k_vb

The von Bertalanffy k parameter

w_inf

The von Bertalanffy asymptotic size

Source

Blanchard et al.

Examples

params <- newMultispeciesParams(NS_species_params)

Example species parameter set based on the North Sea with different gears

Description

This data set is based on species in the North Sea (Blanchard et al.). It is similar to the data set NS_species_params except that this one has an additional column specifying the fishing gear that operates on each species.

Usage

NS_species_params_gears

Format

A data frame with 12 rows and 8 columns. Each row is a species.

species

Name of the species

w_max

Maximum size.

w_mat

Size at maturity

beta

Size preference ratio

sigma

Width of the size-preference

R_max

Maximum reproduction rate

k_vb

The von Bertalanffy k parameter

w_inf

The von Bertalanffy asymptotic size

gear

Name of the fishing gear

Source

Blanchard et al.

Examples

params <- MizerParams(NS_species_params_gears)

Ricker function to calculate density-dependent reproduction rate

Description

Takes the density-independent rates R_{di} of egg production and returns reduced, density-dependent rates R_{dd} given as

R_{dd} = R_{di} \exp(- b R_{di})

Usage

RickerRDD(rdi, species_params, ...)

Arguments

Value

Vector of density-dependent reproduction rates.

See Also

Other functions calculating density-dependent reproduction rate: BevertonHoltRDD(), SheperdRDD(), constantEggRDI(), constantRDD(), noRDD()

Sheperd function to calculate density-dependent reproduction rate

Description

Takes the density-independent rates R_{di} of egg production and returns reduced, density-dependent rates R_{dd} given as

R_{dd} = \frac{R_{di}}{1+(b\ R_{di})^c}

Usage

SheperdRDD(rdi, species_params, ...)

Arguments

Details

With b = 1/R_{max} and c = 1 this reduces to the Beverton-Holt reproduction rate, see BevertonHoltRDD().

Value

Vector of density-dependent reproduction rates.

See Also

Other functions calculating density-dependent reproduction rate: BevertonHoltRDD(), RickerRDD(), constantEggRDI(), constantRDD(), noRDD()

Add lines to an existing plot

Description

addPlot() adds another set of values to an existing ggplot. The first method supports adding an ArraySpeciesBySize object to a compatible plot, for example to compare the same rate before and after a model change. The method checks whether the existing plot uses a compatible x variable, and warns if the y variable or y-axis units appear to differ.

Usage

addPlot(
  plot,
  x,
  species = NULL,
  total = FALSE,
  background = TRUE,
  colour = NULL,
  linetype = "dashed",
  linewidth = 0.8,
  alpha = 1,
  ...
)

Arguments

Value

A ggplot2 object.

See Also

Other plotting functions: animate.ArrayTimeBySpeciesBySize(), plot, plot2(), plotBiomass(), plotCDF(), plotCDF2(), plotDiet(), plotFMort(), plotFeedingLevel(), plotGrowthCurves(), plotMizerParams, plotMizerSim, plotPredMort(), plotRelative(), plotSpectra(), plotSpectra2(), plotSpectraRelative(), plotYield(), plotYieldGear(), plotting_functions

Examples

p <- plot(getEncounter(NS_params), species = "Cod")
addPlot(p, getEncounter(NS_params), species = "Cod")

Add new species

Description

Takes a MizerParams object and adds additional species with given parameters to the ecosystem. It sets the initial values for these new species to their steady-state solution in the given initial state of the existing ecosystem. This will be close to the true steady state if the abundances of the new species are sufficiently low. Hence the abundances of the new species are set so that they are at most 1/100th of the resource power law. Their reproductive efficiencies are set so as to keep them at that low level.

Usage

addSpecies(
  params,
  species_params,
  gear_params = data.frame(),
  initial_effort,
  interaction,
  steady = TRUE,
  info_level = 3,
  ...
)

Arguments

Details

The resulting MizerParams object will use the same size grid where possible, but if one of the new species needs a larger range of w (either because a new species has an egg size smaller than those of existing species or a maximum size larger than those of existing species) then the grid will be expanded and all arrays will be enlarged accordingly.

If any of the rate arrays of the existing species had been set by the user to values other than those calculated as default from the species parameters, then these will be preserved. Only the rates for the new species will be calculated from their species parameters.

After adding the new species, the background species are not retuned and the system is not run to steady state. This could be done with steady(). The new species will have a reproduction level of 1/4, this can then be changed with setBevertonHolt()

Value

An object of type MizerParams

See Also

removeSpecies(), renameSpecies()

Examples

params <- newTraitParams()
species_params <- data.frame(
    species = "Mullet",
    w_max = 173,
    w_mat = 15,
    beta = 283,
    sigma = 1.8,
    h = 30,
    a = 0.0085,
    b = 3.11
)
params <- addSpecies(params, species_params)
plotSpectra(params)

Calculate age at maturity

Description

Uses the size-dependent growth rate and the size at maturity to calculate the age at maturity.

Usage

age_mat(params, ...)

Arguments

Details

Using that by definition of the growth rate g(w) = dw/dt we have that

\mathrm{age_{mat}} = \int_0^{w_{mat}.}\frac{dw}{g(w)}

In the implementation this integral is approximated on the model size grid by summing dw / g(w) over all size bins with w < w_mat.

Value

A named vector. The names are the species names and the values are the ages at maturity.

Examples

age_mat(NS_params)

Calculate age at maturity from von Bertalanffy growth parameters

Description

This is not a good way to determine the age at maturity because the von Bertalanffy growth curve is not reliable for larvae and juveniles. However this was used in previous versions of mizer and is supplied for backwards compatibility.

Usage

age_mat_vB(object, ...)

Arguments

Details

Uses the age at maturity that is implied by the von Bertalanffy growth curve specified by the w_inf, k_vb, t0, a and b parameters in the species_params data frame.

If any of k_vb is missing for a species, the function returns NA for that species. Default values of b = 3 and t0 = 0 are used if these are missing. If w_inf is missing, w_max is used instead.

Value

A named vector. The names are the species names and the values are the ages at maturity.

Animate size-dependent quantities through time

Description

Creates an interactive plotly animation in which a play button steps through time, drawing one line per species at each frame.

Usage

animate(
  x,
  species = NULL,
  log_x = TRUE,
  log_y = TRUE,
  log = NULL,
  wlim = c(NA, NA),
  llim = c(NA, NA),
  ylim = c(NA, NA),
  tlim = c(NA, NA),
  size_axis = c("w", "l"),
  total = FALSE,
  background = TRUE,
  frame_duration = 500,
  transition_duration = frame_duration,
  easing = "linear",
  ...
)

animateSpectra(sim, ...)

Arguments

Details

The function dispatches on the class of x:

• MizerSim — animates the community abundance spectra (number density or biomass density vs body size). Resource, background species, and a community total can be added via the resource, background, and total arguments. The power argument controls whether the y-axis shows number density (power = 0), biomass density (power = 1, default), or biomass density in logarithmic size bins (power = 2). Both axes are log10 by default and can each be switched to linear with log_x = FALSE or log_y = FALSE.

• ArrayTimeBySpeciesBySize — animates any per-species, size-resolved quantity returned by a MizerSim accessor, such as getFMort(), getFeedingLevel(), or getPredMort(). Both axes are log10 by default and can each be switched to linear with log_x = FALSE or log_y = FALSE. Background species and a species total can be added via the background and total arguments.

Species linecolours and linetypes follow params@linecolour and params@linetype.

animateSpectra() is retained as a backward-compatible alias.

Value

A plotly object with one animated line trace per plotted group. Use the play button or the slider to step through time.

See Also

Other plotting functions: addPlot(), plot, plot2(), plotBiomass(), plotCDF(), plotCDF2(), plotDiet(), plotFMort(), plotFeedingLevel(), plotGrowthCurves(), plotMizerParams, plotMizerSim, plotPredMort(), plotRelative(), plotSpectra(), plotSpectra2(), plotSpectraRelative(), plotYield(), plotYieldGear(), plotting_functions

Examples

# Animate biomass density spectra, showing only sizes above 0.1 g
animate(NS_sim, power = 2, wlim = c(0.1, NA), tlim = c(1997, 2007))

# Animate fishing mortality through time
animate(getFMort(NS_sim))

# Animate feeding level for two species only
animate(getFeedingLevel(NS_sim), species = c("Cod", "Herring"))

Convert mizer arrays to data frames

Description

The as.data.frame() methods for mizer array classes turn matrix- and array-like results into tidy long-form data frames, with one row per observed combination of species, size and/or time. The numeric result is always stored in a column called value.

Arguments

Details

The returned columns are:

• ArraySpeciesBySize: w, value, Species.

• ArrayTimeBySpecies: time, value, Species.

• ArrayTimeBySpeciesBySize: time, Species, w, value.

If the original object has non-numeric or missing dimension names, sequential indices are used for the time or w columns. Species names are taken from the row, column or dimension names of the original object.

Value

A data frame in long format.

See Also

print(), summary(), plot(), ArraySpeciesBySize(), ArrayTimeBySpecies(), ArrayTimeBySpeciesBySize()

Examples

enc <- getEncounter(NS_params)
head(as.data.frame(enc))

biomass <- getBiomass(NS_sim)
head(as.data.frame(biomass))

Assert that an object's extension chain is compatible with the session

Description

Stops with an informative error if the object's extension chain is not a suffix of the session's registered maximal chain, or (when check_class is TRUE) if the object does not inherit from the expected S4 marker class.

Usage

assertExtensionChain(
  object,
  extensions = objectExtensions(object),
  check_class = TRUE
)

Arguments

Value

Invisibly TRUE. Called for its side-effect of stopping on incompatibility.

Strip extension classes from a mizer object

Description

Coerces a MizerParams or MizerSim object back to its plain base class, removing any S4 extension marker classes. For MizerSim, also strips the extension class from the embedded params slot.

Usage

baseMizerClass(object)

Arguments

Value

The same object coerced to MizerParams or MizerSim.

Box predation kernel

Description

A predation kernel where the predator/prey mass ratio is uniformly distributed on an interval.

Usage

box_pred_kernel(ppmr, ppmr_min, ppmr_max)

Arguments

Details

Writing the predator mass as w and the prey mass as w_p, the feeding kernel is 1 if w/w_p is between ppmr_min and ppmr_max inclusive and zero otherwise. ppmr_min must be strictly smaller than ppmr_max. The parameters need to be given in the species parameter dataframe in the columns ppmr_min and ppmr_max.

Value

A vector giving the value of the predation kernel at each of the predator/prey mass ratios in the ppmr argument.

See Also

setPredKernel()

Other predation kernel: lognormal_pred_kernel(), power_law_pred_kernel(), truncated_lognormal_pred_kernel()

Examples

params <- NS_params
# Set all required paramters before changing kernel type
species_params(params)$ppmr_max <- 4000
species_params(params)$ppmr_min <- 200
species_params(params)$pred_kernel_type <- "box"
plot(w_full(params), getPredKernel(params)["Cod", 10, ], type="l", log="x")

Calculate selectivity from gear parameters

Description

This function calculates the selectivity for each gear, species and size from the gear parameters. It is called by setFishing() when the selectivity is not set by the user. The returned array is initialised to zero, so gear-species combinations that are not listed in gear_params(params) remain zero. For each listed combination the function named in sel_func is called with w = params@w, the corresponding species parameters, and the selectivity parameters from the matching row in gear_params(params).

Usage

calc_selectivity(params)

Arguments

Value

An array (gear x species x size) with the selectivity values

Examples

params <- NS_params
str(calc_selectivity(params))
calc_selectivity(params)["Pelagic", "Herring", ]

Calibrate the model scale to match total observed biomass

Description

Given a MizerParams object params for which biomass observations are available for at least some species via the biomass_observed column in the species_params data frame, this function returns an updated MizerParams object which is rescaled with scaleModel() so that the total biomass in the model agrees with the total observed biomass.

Usage

calibrateBiomass(params, ...)

Arguments

Details

Biomass observations usually only include individuals above a certain size. This size should be specified in a biomass_cutoff column of the species parameter data frame. If this is missing, it is assumed that all sizes are included in the observed biomass, i.e., it includes larval biomass.

After using this function the total biomass in the model will match the total biomass, summed over all species. However the biomasses of the individual species will not match observations yet, with some species having biomasses that are too high and others too low. So after this function you may want to use matchBiomasses(). This is described in the blog post at https://blog.mizer.sizespectrum.org/posts/2021-08-20-a-5-step-recipe-for-tuning-the-model-steady-state/.

If you have observations of the yearly yield instead of biomasses, you can use calibrateYield() instead of this function.

Value

A MizerParams object. If no non-missing observed biomass values are provided, the original object is returned unchanged.

Examples

params <- NS_params
species_params(params)$biomass_observed <- 
    c(0.8, 61, 12, 35, 1.6, 20, 10, 7.6, 135, 60, 30, 78)
species_params(params)$biomass_cutoff <- 10
params2 <- calibrateBiomass(params)
plotBiomassObservedVsModel(params2)

Calibrate the model scale to match total observed number

Description

Given a MizerParams object params for which number observations are available for at least some species via the number_observed column in the species_params data frame, this function returns an updated MizerParams object which is rescaled with scaleModel() so that the total number in the model agrees with the total observed number.

Usage

calibrateNumber(params, ...)

Arguments

Details

Number observations usually only include individuals above a certain size. This size should be specified in a number_cutoff column of the species parameter data frame. If this is missing, it is assumed that all sizes are included in the observed number, i.e., it includes larval number.

After using this function the total number in the model will match the total number, summed over all species. However the numbers of the individual species will not match observations yet, with some species having numbers that are too high and others too low. So after this function you may want to use matchNumbers(). This is described in the blog post at https://blog.mizer.sizespectrum.org/posts/2021-08-20-a-5-step-recipe-for-tuning-the-model-steady-state/.

If you have observations of the yearly yield instead of numbers, you can use calibrateYield() instead of this function.

Value

A MizerParams object. If no non-missing observed number values are provided, the original object is returned unchanged.

Examples

params <- NS_params
species_params(params)$number_observed <-
    c(0.8, 61, 12, 35, 1.6, 20, 10, 7.6, 135, 60, 30, 78)
species_params(params)$number_cutoff <- 10
params2 <- calibrateNumber(params)

Calibrate the model scale to match total observed yield

Description

Usage

calibrateYield(params, ...)

Arguments

Details

This function has been deprecated and will be removed in the future unless you have a use case for it. If you do have a use case for it, please let the developers know by creating an issue at https://github.com/sizespectrum/mizer/issues.

Given a MizerParams object params for which yield observations are available for at least some species via the yield_observed column in the species_params data frame, this function returns an updated MizerParams object which is rescaled with scaleModel() so that the total yield in the model agrees with the total observed yield.

After using this function the total yield in the model will match the total observed yield, summed over all species. However the yields of the individual species will not match observations yet, with some species having yields that are too high and others too low. So after this function you may want to use matchYields().

If you have observations of species biomasses instead of yields, you can use calibrateBiomass() instead of this function.

Value

A MizerParams object. If no non-missing observed yield values are provided, the original object is returned unchanged.

Examples

params <- NS_params
species_params(params)$yield_observed <-
    c(0.8, 61, 12, 35, 1.6, 20, 10, 7.6, 135, 60, 30, 78)
gear_params(params)$catchability <-
    c(1.3, 0.065, 0.31, 0.18, 0.98, 0.24, 0.37, 0.46, 0.18, 0.30, 0.27, 0.39)
params2 <- calibrateYield(params)
plotYieldObservedVsModel(params2)

Y-axis label for a cumulative-distribution plot

Description

Y-axis label for a cumulative-distribution plot

Usage

cdf_y_label(power, normalise)

Arguments

Value

A character string for the y-axis label.

Clear the registered extension chain

Description

Clears the session's extension registry. You can then create a new extension chain with registerExtensions().

Usage

clearExtensionChain()

Value

Invisibly, an empty character vector.

See Also

"Using mizer extension packages": vignette("using-extension-packages", package = "mizer")

Other extension tools: NOther(), coerceToExtensionClass(), getRegisteredExtensions(), initialNOther<-(), registerExtension(), registerExtensions(), setComponent(), setRateFunction()

Coerce a mizer object to its registered extension class

Description

Coerces a MizerParams or MizerSim object to the S4 marker class corresponding to the object's own extension chain. For MizerSim, the extension chain is read from sim@params@extensions.

Usage

coerceToExtensionClass(object, extensions = objectExtensions(object))

Arguments

Value

The same object coerced to the appropriate marker class, or to the base class for an empty extension chain.

See Also

"Creating a mizer extension package": vignette("creating-extension-packages", package = "mizer")

Other extension tools: NOther(), clearExtensionChain(), getRegisteredExtensions(), initialNOther<-(), registerExtension(), registerExtensions(), setComponent(), setRateFunction()

Compare two extension chains

Description

Compare two extension chains

Usage

compareExtensionChains(old, new)

Arguments

Value

One of "identical", "new_is_suffix", "old_is_suffix", or "incompatible".

Compare two MizerParams objects and print out differences

Description

Compare two MizerParams objects and print out differences

Usage

compareParams(params1, params2, ...)

Arguments

Value

Invisibly returns a character vector of difference messages, one element per difference. As a side effect, prints the differences in a human-readable format.

Examples

params1 <- NS_params
params2 <- params1
species_params(params2)$w_mat[1] <- 10
compareParams(params1, params2)

Alias for validSpeciesParams()

Description

An alias provided for backward compatibility with mizer version <= 2.5.2

Usage

completeSpeciesParams(species_params)

Arguments

Details

validGivenSpeciesParams() checks the validity of the given species parameters. It throws an error if

• the species column does not exist or contains duplicates

• the maximum size is not specified for all species

If a weight-based parameter is missing but the corresponding length-based parameter is given, as well as the a and b parameters for length-weight conversion, then the weight-based parameters are added. If both length and weight are given, then weight is used and an info_about_default condition is signalled if the two are inconsistent.

If a w_inf column is given but no w_max then the value from w_inf is used. This is for backwards compatibility. But note that the von Bertalanffy parameter w_inf is not the maximum size of the largest individual, but the asymptotic size of an average individual.

Some inconsistencies in the size parameters are resolved as follows:

• Any w_mat that is not smaller than w_max is set to w_max / 4.

• Any w_mat25 that is not smaller than w_mat is set to NA.

• Any w_min that is not smaller than w_mat is set to 0.001 or w_mat /10, whichever is smaller.

• Any w_repro_max that is not larger than w_mat is set to 4 * w_mat.

The row names of the returned data frame will be the species names. If species_params was provided as a tibble it is converted back to an ordinary data frame.

The function tests for some typical misspellings of parameter names, like wrong capitalisation or missing underscores and issues a warning if it detects such a name.

validSpeciesParams() first calls validGivenSpeciesParams() but then goes further by adding default values for species parameters that were not provided. The function sets default values if any of the following species parameters are missing or NA:

• w_repro_max is set to w_max

• w_mat is set to w_max/4

• w_min is set to 0.001

• alpha is set to 0.6

• interaction_resource is set to 1

• n is set to 3/4

• p is set to n

• z_ext is set to 0

• d is set to n - 1

• E_ext is set to 0

• D_ext is set to 0

Note that the species parameters returned by these functions are not guaranteed to produce a viable model. More checks of the parameters are performed by the individual rate-setting functions (see setParams() for the list of these functions).

Value

For validSpeciesParams(): A valid species parameter data frame with additional parameters with default values.

For validGivenSpeciesParams(): A valid species parameter data frame without additional parameters.

See Also

species_params(), validGearParams(), validParams(), validSim()

Choose egg production to keep egg density constant

Description

The new egg production is set to compensate for the loss of individuals from the smallest size class through growth and mortality. The result should not be modified by density dependence, so this should be used together with the noRDD() function, see example.

Usage

constantEggRDI(params, n, e_growth, mort, diffusion, ...)

Arguments

Value

Vector with the value for each species

See Also

Other functions calculating density-dependent reproduction rate: BevertonHoltRDD(), RickerRDD(), SheperdRDD(), constantRDD(), noRDD()

Examples

# choose an example params object
params <- NS_params
# We set the reproduction rate functions
params <- setRateFunction(params, "RDI", "constantEggRDI")
params <- setRateFunction(params, "RDD", "noRDD")
# Now the egg density should stay fixed no matter how we fish
sim <- project(params, effort = 10, progress_bar = FALSE)
# To check that indeed the egg densities have not changed, we first construct
# the indices for addressing the egg densities
no_sp <- nrow(params@species_params)
idx <- (params@w_min_idx - 1) * no_sp + (1:no_sp)
# Now we can check equality between egg densities at the start and the end
all.equal(finalN(sim)[idx], initialN(params)[idx])

Give constant reproduction rate

Description

Simply returns the value from species_params$constant_reproduction.

Usage

constantRDD(rdi, species_params, ...)

Arguments

Value

Vector species_params$constant_reproduction

See Also

Other functions calculating density-dependent reproduction rate: BevertonHoltRDD(), RickerRDD(), SheperdRDD(), constantEggRDI(), noRDD()

Helper function to keep other components constant

Description

Helper function to keep other components constant

Usage

constant_other(params, n_other, component, ...)

Arguments

Value

The current value of the component

Convert plotting data from weight to length

Description

When size_axis = "l", adds a length column l computed from the weight column w using each species' weight-length relationship. For size_axis = "w" the data is returned unchanged.

Usage

convert_plot_size_axis(
  plot_dat,
  params,
  size_axis,
  species_col = "Species",
  drop_w = TRUE
)

Arguments

Value

The plotting data, with a length column l added (and w optionally dropped) when size_axis = "l".

Replace a mizer function with a custom version

Description

This function allows you to make arbitrary changes to how mizer works by allowing you to replace any mizer function with your own version. You should do this only as a last resort, when you find that you can not use the standard mizer extension mechanism to achieve your goal.

Usage

customFunction(name, fun)

Arguments

Details

If the function you need to overwrite is one of the mizer rate functions, then you should use setRateFunction() instead of this function. Similarly you should use ⁠resource_dynamics()<-⁠ to change the resource dynamics and setReproduction() to change the density-dependence in reproduction. You should also investigate whether you can achieve your goal by introducing additional ecosystem components with setComponent().

If you find that your goal really does require you to overwrite a mizer function, please also create an issue on the mizer issue tracker at https://github.com/sizespectrum/mizer/issues to describe your goal, because it will be interesting to the mizer community and may motivate future improvements to the mizer functionality.

Note that customFunction() only overwrites the function used by the mizer code. It does not overwrite the function that is exported by mizer. This will become clear when you run the code in the Examples section.

This function does not in any way check that your replacement function is compatible with mizer. Calling this function can totally break mizer. However you can always undo the effect by reloading mizer with

detach(package:mizer, unload = TRUE)
library(mizer)

Value

No return value, called for side effects

See Also

"Extending mizer": vignette("extending-mizer", package = "mizer")

Examples

## Not run: 
fake_project <- function(...) "Fake"
customFunction("project", fake_project)
mizer::project(NS_params) # This will print "Fake"
project(NS_params) # This will still use the old project() function
# To undo the effect:
customFunction("project", project)
mizer::project(NS_params) # This will again use the old project()

## End(Not run)

Set defaults for predation kernel parameters

Description

If the predation kernel type has not been specified for a species, then it is set to "lognormal" and the default values are set for the parameters beta and sigma.

Usage

default_pred_kernel_params(object)

Arguments

Value

The object with updated columns in the species params data frame.

Default editions

Description

Function to set and get which edition of default choices is being used.

Usage

defaults_edition(edition = NULL)

Arguments

Details

The mizer functions for creating new models make a lot of choices for default values for parameters that are not provided by the user. Sometimes we find better ways to choose the defaults and update mizer accordingly. When we do this, we will increase the edition number.

If you call defaults_edition() without an argument it returns the currently active edition. Otherwise it sets the active edition to the given value.

Users who want their existing code for creating models not to change behaviour when run with future versions of mizer should explicitly set the desired defaults edition at the top of their code.

The most recent edition is edition 2. It will become the default in the next release. The current default is edition 1. The following defaults are changed in edition 2:

• catchability = 0.3 instead of 1

• ⁠initial effort⁠ = 1 instead of 0

• gamma is set to ensure a feeding level of f0 for larvae with the current value of interaction_resource instead of interaction_resource = 1'.

• initial_n is set using get_steady_state_n() instead of the rather arbitrary old choice.

• In setReproduction(), psi is no longer forced to 1 above w_repro_max; its value is determined entirely by the maturity ogive and the reproductive proportion.

Value

If edition is NULL, the currently active edition number. If edition is supplied, the function sets the global mizer_defaults_edition option, emits a message, and returns the supplied value invisibly.

Define S4 marker classes for a set of dispatch extensions

Description

Creates a linear inheritance chain of S4 classes: the outermost extension extends the next, which extends the next, down to the base MizerParams / MizerSim class. Existing classes are checked for compatibility instead of being redefined.

Usage

defineExtensionClasses(extensions)

Arguments

Value

Invisibly, the named character vector of dispatch extensions.

Define an S4 class or verify it extends the expected parent

Description

If class does not yet exist, defines it as a virtual-free S4 class that contains parent, registered in .GlobalEnv. If class already exists, stops with an error unless it already extends parent.

Usage

defineOrCheckClass(class, parent)

Arguments

Value

Invisibly, class.

Check whether two objects are different

Description

Check whether two objects are numerically different, ignoring all attributes.

Usage

different(a, b)

Arguments

Details

We use this helper function in particular to see if a new value for a slot in MizerParams is different from the existing value in order to give the appropriate messages.

Value

TRUE or FALSE

Filter an extension vector to those that participate in S3/S4 dispatch

Description

An extension participates in dispatch if its requirement is NA_character_ (in-development) or if an S4 class with its name already exists.

Usage

dispatchExtensions(extensions)

Arguments

Value

A named character vector containing only the dispatch extensions, preserving order.

Measure distance between current and previous state in terms of RDI

Description

This function can be used in projectToSteady() to decide when sufficient convergence to steady state has been achieved.

Usage

distanceMaxRelRDI(params, current, previous)

Arguments

Value

The largest absolute relative change in rdi: max(abs((current_rdi - previous_rdi) / previous_rdi)). If any entry of previous_rdi is zero, the result can be infinite.

See Also

Other distance functions: distanceSSLogN()

Measure distance between current and previous state in terms of fish abundances

Description

Calculates the sum squared difference between log(N) in current and previous state. This function can be used in projectToSteady() to decide when sufficient convergence to steady state has been achieved.

Usage

distanceSSLogN(params, current, previous)

Arguments

Value

The sum of squares of the difference in the logs of the (nonzero) fish abundances n, ignoring entries where either state has zero abundance: sum((log(current$n) - log(previous$n))^2)

See Also

Other distance functions: distanceMaxRelRDI()

Length based double-sigmoid selectivity function

Description

A hump-shaped selectivity function with a sigmoidal rise and an independent sigmoidal drop-off. This drop-off is what distinguishes this from the function sigmoid_length() and it is intended to model the escape of large individuals from the fishing gear.

Usage

double_sigmoid_length(w, l25, l50, l50_right, l25_right, species_params, ...)

Arguments

Details

You would not usually call this function directly. Instead, set the sel_func column in gear_params() to "double_sigmoid_length" and provide the l25, l50, l50_right and l25_right values as additional columns. setFishing() will then call this function automatically when calculating the selectivity array.

The selectivity is obtained as the product of two sigmoidal curves, one rising and one dropping. The sigmoidal rise is based on the two parameters l25 and l50 which determine the length at which 25% and 50% of the stock is selected respectively. The sigmoidal drop-off is based on the two parameters l50_right and l25_right which determine the length at which the selectivity curve has dropped back to 50% and 25% respectively. The selectivity is given by the function

S(l) = \frac{1}{1 + \exp\left(\log(3)\frac{l50 -l}{l50 - l25}\right)}\frac{1}{1 + \exp\left(\log(3)\frac{l50_{right} -l}{l50_{right} - l25_{right}}\right)}

As the size-based model is weight based, and this selectivity function is length based, it uses the length-weight parameters a and b to convert between length and weight.

l = \left(\frac{w}{a}\right)^{1/b}

Value

Vector of selectivities at the given sizes. Requires ⁠l25 < l50 < l50_right < l25_right⁠.

See Also

gear_params() for setting the selectivity parameters.

Other selectivity functions: knife_edge(), sigmoid_length(), sigmoid_weight()

Examples

# Hump-shaped selectivity: rises from l25=10 to l50=15,
# then drops back to 50% at l50_right=40 and 25% at l25_right=50
sp <- list(a = 0.01, b = 3)
w <- c(1, 10, 100, 500, 1000)
double_sigmoid_length(w, l25 = 10, l50 = 15,
                      l50_right = 40, l25_right = 50,
                      species_params = sp)

Create empty MizerParams object of the right size

Description

An internal function. Sets up a valid MizerParams object with all the slots initialised and given dimension names, but with some slots left empty. This function is to be used by other functions to set up full parameter objects.

Usage

emptyParams(
  species_params,
  gear_params = data.frame(),
  no_w = 100,
  min_w = 0.001,
  max_w = NA,
  min_w_pp = 1e-12
)

Arguments

Value

An empty but valid MizerParams object

Size grid

A size grid is created so that the log-sizes are equally spaced. The spacing is chosen so that there will be no_w fish size bins, with the smallest starting at min_w and the largest starting at max_w. For the resource spectrum there is a larger set of bins containing additional bins below min_w, with the same log size. The number of extra bins is such that min_w_pp comes to lie within the smallest bin.

Changes to species params

The species_params slot of the returned MizerParams object may differ from the data frame supplied as argument to this function because default values are set for missing parameters.

See Also

See newMultispeciesParams() for a function that fills the slots left empty by this function.

Load (and optionally install) namespaces for all non-NA extensions

Description

For each extension whose requirement is not NA_character_, checks that the package is installed and up-to-date, installs or upgrades via pak::pkg_install() if install = TRUE, then calls loadNamespace().

Usage

ensureExtensionNamespaces(extensions, install = FALSE)

Arguments

Value

Invisibly TRUE.

Expand the size grid

Description

This function expands the size grid in a MizerParams object to the desired min and max size, preserving all existing species.

Usage

expandSizeGrid(params, ...)

## S3 method for class 'MizerParams'
expandSizeGrid(
  params,
  new_min_w = min(params@w),
  new_max_w = max(params@w),
  preserve_species = params@species_params$species,
  ...
)

Arguments

Value

A new MizerParams object with the updated size grid.

Filter plotting data to the requested length limits

Description

Filter plotting data to the requested length limits

Usage

filter_plot_length_limits(plot_dat, llim)

Arguments

Value

plot_dat filtered to the length limits, or unchanged if it has no l column.

Size spectra at end of simulation

Description

Size spectra at end of simulation

Usage

finalN(sim)

finalNResource(sim)

idxFinalT(sim)

Arguments

Value

For finalN(): An ArraySpeciesBySize object (species x size) holding the consumer number densities at the end of the simulation

For finalNResource(): A vector holding the resource number densities at the end of the simulation for all size classes

For idxFinalT(): An integer giving the index for extracting the results for the final time step

Examples

str(finalN(NS_sim))

# This could also be obtained using `N()` and `idxFinalT()`
identical(N(NS_sim)[idxFinalT(NS_sim), , ], finalN(NS_sim))
str(finalNResource(NS_sim))
idx <- idxFinalT(NS_sim)
idx
# This coincides with
length(getTimes(NS_sim))
# and corresponds to the final time
getTimes(NS_sim)[idx]
# We can use this index to extract the result at the final time
identical(N(NS_sim)[idx, , ], finalN(NS_sim))
identical(NResource(NS_sim)[idx, ], finalNResource(NS_sim))

Extract the final state from a simulation

Description

Returns the MizerParams object underlying the simulation with its initial abundances set to the abundances at the last saved time step of the simulation. This is a convenience wrapper around getParams() with no time_range argument (the default).

Usage

finalParams(sim)

Arguments

Value

A MizerParams object with initial values taken from the final time step of the simulation.

See Also

getParams(), initialParams()

Examples

sim <- project(NS_params, t_max = 20, effort = 0.5)
params_end <- finalParams(sim)

Assemble the flux matrix from growth, diffusion and recruitment rates

Description

Internal helper holding the arithmetic shared by getFlux.MizerParams and getFlux.MizerSim. Keeping it separate lets the MizerSim method resolve the rate functions once and reuse them across all saved time steps.

Usage

flux_from_rates(params, n, g, d, rdd, power = 0)

Arguments

Value

A plain species x size matrix of fluxes (no mizer array class).

Units string for the flux returned by getFlux()

Description

Units string for the flux returned by getFlux()

Usage

flux_units(power)

Arguments

Value

A character string with the units of the flux.

Format an extension chain as a human-readable string

Description

Format an extension chain as a human-readable string

Usage

formatExtensionChain(extensions)

Arguments

Value

A character string such as "mizerExtB -> mizerExtA", or "<empty>" for a zero-length chain.

Gear parameters

Description

These functions allow you to get or set the gear parameters stored in a MizerParams object. These are used by setFishing() to set up the selectivity and catchability and thus together with the fishing effort determine the fishing mortality.

Usage

gear_params(params)

gear_params(params) <- value

Arguments

Details

The gear_params data has one row for each gear-species pair and one column for each parameter that determines how that gear interacts with that species. The columns are:

• species The name of the species

• gear The name of the gear

• catchability A number specifying how strongly this gear selects this species.

• sel_func The name of the function that calculates the selectivity curve.

• One column for each selectivity parameter needed by the selectivity functions.

For the details see setFishing().

There can optionally also be a column yield_observed that allows you to specify for each gear and species the total annual fisheries yield.

The fishing effort, which is also needed to determine the fishing mortality exerted by a gear is not set via the gear_params data frame but is set with initial_effort() or is specified when calling project().

If you change a gear parameter, this will be used to recalculate the selectivity and catchability arrays by calling setFishing(), unless you have previously set these by hand.

⁠gear_params<-⁠ automatically sets the row names to contain the species name and the gear name, separated by a comma and a space. The last example below illustrates how this facilitates changing an individual gear parameter.

Value

Data frame with gear parameters

See Also

validGearParams()

Other functions for setting parameters: setExtDiffusion(), setExtEncounter(), setExtMort(), setFishing(), setInteraction(), setMaxIntakeRate(), setMetabolicRate(), setParams(), setPredKernel(), setReproduction(), setSearchVolume(), species_params(), use_predation_diffusion()

Examples

params <- NS_params

# gears set up in example
gear_params(params)

# setting totally different gears
gear_params(params) <- data.frame(
    gear = c("gear1", "gear2", "gear1"),
    species = c("Cod", "Cod", "Haddock"),
    catchability = c(0.5, 2, 1),
    sel_fun = c("sigmoid_weight", "knife_edge", "sigmoid_weight"),
    sigmoidal_weight = c(1000, NA, 800),
    sigmoidal_sigma = c(100, NA, 100),
    knife_edge_size = c(NA, 1000, NA)
    )
gear_params(params)

# changing an individual entry
gear_params(params)["Cod, gear1", "catchability"] <- 0.8

Calculate the total biomass of each species within a size range at each time step.

Description

Calculates the total biomass through time within user defined size limits. The default option is to use the size range starting at the size specified by the biomass_cutoff species parameter, if it is set, or else the full size range of each species. You can specify minimum and maximum weight or length range for the species. Lengths take precedence over weights (i.e. if both min_l and min_w are supplied, only min_l will be used).

Usage

getBiomass(object, use_cutoff = FALSE, ...)

Arguments

Details

When no size range arguments are provided, the function checks if the biomass_cutoff column exists in the species parameters. If it does, those values are used as the minimum weight for each species. For species with NA values in biomass_cutoff, the default minimum weight (smallest weight in the model) is used.

Value

If called with a MizerParams object, a named vector with the biomass in grams for each species in the model. If called with a MizerSim object, an ArrayTimeBySpecies object (time x species) containing the biomass in grams at each time step for all species.

See Also

Other summary functions: getDiet(), getGrowthCurves(), getN(), getSSB(), getTrophicLevel(), getTrophicLevelBySpecies(), getYield(), getYieldGear()

Examples

biomass <- getBiomass(NS_sim)
biomass["1972", "Herring"]
biomass <- getBiomass(NS_sim, min_w = 10, max_w = 1000)
biomass["1972", "Herring"]

# If species_params contains a `biomass_cutoff`` column, it can be used
# as the minimum weight when use_cutoff = TRUE
species_params(NS_sim@params)$biomass_cutoff <- 10
biomass <- getBiomass(NS_sim, use_cutoff = TRUE)  # Uses biomass_cutoff as min_w
biomass["1972", "Herring"]

Calculate the slope of the community abundance

Description

Calculates the slope of the community abundance by performing a linear regression on the logged total numerical abundance at weight and logged weights (natural logs, not log to base 10, are used). You can specify minimum and maximum weight or length range for the species. Lengths take precedence over weights (i.e. if both min_l and min_w are supplied, only min_l will be used). You can also specify the species to be used in the calculation.

Usage

getCommunitySlope(object, species = NULL, biomass = TRUE, ...)

Arguments

Value

A data.frame with columns slope, intercept and the coefficient of determination R^2 (and a time step column when called with a MizerSim object).

See Also

Other functions for calculating indicators: getMeanMaxWeight(), getMeanWeight(), getProportionOfLargeFish()

Examples

# Slope based on biomass, using all species and sizes
slope_biomass <- getCommunitySlope(NS_sim)
slope_biomass[1, ] # in 1976
slope_biomass[idxFinalT(NS_sim), ] # in 2010

# Slope based on numbers, using all species and sizes
slope_numbers <- getCommunitySlope(NS_sim, biomass = FALSE)
slope_numbers[1, ] # in 1976

# Slope based on biomass, using all species and sizes between 10g and 1000g
slope_biomass <- getCommunitySlope(NS_sim, min_w = 10, max_w = 1000)
slope_biomass[1, ] # in 1976

# Slope based on biomass, using only demersal species and
# sizes between 10g and 1000g
dem_species <- c("Dab","Whiting", "Sole", "Gurnard", "Plaice",
                 "Haddock", "Cod", "Saithe")
slope_biomass <- getCommunitySlope(NS_sim, species = dem_species,
                                   min_w = 10, max_w = 1000)
slope_biomass[1, ] # in 1976

getCommunitySlope(NS_params)

Get critical feeding level

Description

The critical feeding level is the feeding level at which the food intake is just high enough to cover the metabolic costs, with nothing left over for growth or reproduction.

Usage

getCriticalFeedingLevel(params)

Arguments

Value

An ArraySpeciesBySize object (species x size) with the critical feeding level

Examples

str(getFeedingLevel(NS_params))

Get diet of predator at size, resolved by prey species

Description

Calculates the rate at which a predator of a particular species and size consumes biomass of each prey species, resource, and other components of the ecosystem. Returns either the rates in grams/year or the proportion of the total consumption rate.

Usage

getDiet(
  params,
  n = initialN(params),
  n_pp = initialNResource(params),
  n_other = initialNOther(params),
  proportion = TRUE
)

Arguments

Details

The rates D_{ij}(w) at which a predator of species i and size w consumes biomass from prey species j are calculated from the predation kernel \phi_i(w, w_p), the search volume \gamma_i(w), the feeding level f_i(w), the species interaction matrix \theta_{ij} and the prey abundance density N_j(w_p):

D_{ij}(w, w_p) = (1-f_i(w)) \gamma_i(w) \theta_{ij} \int N_j(w_p) \phi_i(w, w_p) w_p dw_p.

The prey index j runs over all species and the resource.

Extra columns are added for the external encounter rate and for any extra ecosystem components in your model for which you have defined an encounter rate function. These encounter rates are multiplied by 1-f_i(w) to give the rate of consumption of biomass from these extra components.

This function performs the same integration as getEncounter() but does not aggregate over prey species, and multiplies by 1-f_i(w) to get the consumed biomass rather than the available biomass. Outside the range of sizes for a predator species the returned rate is zero.

Value

An array (predator species x predator size x (prey species + resource + other components). Dimnames are "prey", "w", and "predator".

See Also

plotDiet()

Other summary functions: getBiomass(), getGrowthCurves(), getN(), getSSB(), getTrophicLevel(), getTrophicLevelBySpecies(), getYield(), getYieldGear()

Examples

diet <- getDiet(NS_params)
str(diet)

Get diffusion rate from predation

Description

Calculates the diffusion rate D_i(w) (grams^2/year) for each species. This is the rate at which the abundance density is diffused along the size axis due to the variability in prey sizes. This is the diffusion term from the jump-growth equation.

Usage

getDiffusion(object, ...)

Arguments

Value

An array of dimensions species x size holding the diffusion rates.

References

Datta, S., Delius, G. W. and Law, R. (2010). A jump-growth model for predator-prey dynamics: derivation and application to marine ecosystems. Bulletin of Mathematical Biology, 72(6):1361–1382

See Also

Other rate functions: getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Get energy rate available for growth

Description

Calculates the energy rate g_i(w) (grams/year) available by species and size for growth after metabolism, movement and reproduction have been accounted for.

Usage

getEGrowth(object, ...)

Arguments

Details

The growth rate is calculated as the difference between the energy available for reproduction and growth (obtainable with getEReproAndGrowth()) and the energy used for reproduction (obtainable with getERepro()), but is set to 0 if the result would be negative.

Value

• MizerParams: An ArraySpeciesBySize object (species x size) with the somatic growth rates (grams/year).

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x species x size) with the growth rates at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own growth rate function

By default getEGrowth() calls mizerEGrowth(). However you can replace this with your own alternative growth rate function. If your function is called "myEGrowth" then you register it in a MizerParams object params with

params <- setRateFunction(params, "EGrowth", "myEGrowth")

Your function will then be called instead of mizerEGrowth(), with the same arguments.

See Also

getERepro(), getEReproAndGrowth()

Other rate functions: getDiffusion(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the energy at a particular time step
growth <- getEGrowth(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ], t = 15)
# Growth rate at this time for Sprat of size 2g
growth["Sprat", "2"]

Get energy rate available for reproduction

Description

Calculates the energy rate (grams/year) available for reproduction after growth and metabolism have been accounted for.

Usage

getERepro(object, ...)

Arguments

Value

• MizerParams: An ArraySpeciesBySize object (species x size) holding

  \psi_i(w)\max(0, E_{r.i}(w))

  where E_{r.i}(w) is the rate at which energy becomes available for growth and reproduction, calculated with getEReproAndGrowth(), and \psi_i(w) is the proportion of this energy that is used for reproduction. Negative values of E_{r.i}(w) are clipped to 0 before multiplying by \psi_i(w). This proportion is taken from the params object and is set with setReproduction().

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x species x size) with the energy for reproduction at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own reproduction rate function

By default getERepro() calls mizerERepro(). However you can replace this with your own alternative reproduction rate function. If your function is called "myERepro" then you register it in a MizerParams object params with

params <- setRateFunction(params, "ERepro", "myERepro")

Your function will then be called instead of mizerERepro(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the rate at a particular time step
erepro <- getERepro(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ], t = 15)
# Rate at this time for Sprat of size 2g
erepro["Sprat", "2"]

Get energy rate available for reproduction and growth

Description

Calculates the energy rate E_{r.i}(w) (grams/year) available for reproduction and growth after metabolism and movement have been accounted for.

Usage

getEReproAndGrowth(object, ...)

Arguments

Value

• MizerParams: An ArraySpeciesBySize object (species x size) with the energy rate E_{r.i}(w) available for growth and reproduction (grams/year).

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x species x size) with the energy rate at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own energy rate function

By default getEReproAndGrowth() calls mizerEReproAndGrowth(). However you can replace this with your own alternative energy rate function. If your function is called "myEReproAndGrowth" then you register it in a MizerParams object params with

params <- setRateFunction(params, "EReproAndGrowth", "myEReproAndGrowth")

Your function will then be called instead of mizerEReproAndGrowth(), with the same arguments.

See Also

The part of this energy rate that is invested into growth is calculated with getEGrowth() and the part that is invested into reproduction is calculated with getERepro().

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the energy at a particular time step
e <- getEReproAndGrowth(params, n = N(sim)[15, , ],
                        n_pp = NResource(sim)[15, ], t = 15)
# Rate at this time for Sprat of size 2g
e["Sprat", "2"]

Alias for getERepro()

Description

An alias provided for backward compatibility with mizer version <= 1.0

Usage

getESpawning(object, ...)

Arguments

Value

• MizerParams: An ArraySpeciesBySize object (species x size) holding

  \psi_i(w)\max(0, E_{r.i}(w))

  where E_{r.i}(w) is the rate at which energy becomes available for growth and reproduction, calculated with getEReproAndGrowth(), and \psi_i(w) is the proportion of this energy that is used for reproduction. Negative values of E_{r.i}(w) are clipped to 0 before multiplying by \psi_i(w). This proportion is taken from the params object and is set with setReproduction().

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x species x size) with the energy for reproduction at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own reproduction rate function

By default getERepro() calls mizerERepro(). However you can replace this with your own alternative reproduction rate function. If your function is called "myERepro" then you register it in a MizerParams object params with

params <- setRateFunction(params, "ERepro", "myERepro")

Your function will then be called instead of mizerERepro(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the rate at a particular time step
erepro <- getERepro(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ], t = 15)
# Rate at this time for Sprat of size 2g
erepro["Sprat", "2"]

Fishing effort used in simulation

Description

Note that the array returned may not be exactly the same as the effort argument that was passed in to project(). This is because only the saved effort is stored (the frequency of saving is determined by the argument t_save).

Usage

getEffort(sim)

Arguments

Value

An array (time x gear) that contains the fishing effort by time and gear.

Examples

str(getEffort(NS_sim))

Get encounter rate

Description

Returns the rate at which a predator of species i and weight w encounters food (grams/year).

Usage

getEncounter(object, ...)

Arguments

Value

• MizerParams: An ArraySpeciesBySize object (predator species x predator size) with the encounter rates.

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x predator species x predator size) with the encounter rates at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Predation encounter

The encounter rate E_i(w) at which a predator of species i and weight w encounters food has contributions from the encounter of fish prey and of resource. This is determined by summing over all prey species and the resource spectrum and then integrating over all prey sizes w_p, weighted by predation kernel \phi(w,w_p):

E_i(w) = \gamma_i(w) \int \left( \theta_{ip} N_R(w_p) + \sum_{j} \theta_{ij} N_j(w_p) \right) \phi_i(w,w_p) w_p \, dw_p.

Here N_j(w) is the abundance density of species j and N_R(w) is the abundance density of resource. The overall prefactor \gamma_i(w) determines the predation power of the predator. It could be interpreted as a search volume and is set with the setSearchVolume() function. The predation kernel \phi(w,w_p) is set with the setPredKernel() function. The species interaction matrix \theta_{ij} is set with setInteraction() and the resource interaction vector \theta_{ip} is taken from the interaction_resource column in params@species_params.

Details

The encounter rate is multiplied by 1-f_0 to obtain the consumption rate, where f_0 is the feeding level calculated with getFeedingLevel(). This is used by the project() function for performing simulations.

The function returns values also for sizes outside the size-range of the species. These values should not be used, as they are meaningless.

If your model contains additional components that you added with setComponent() and for which you specified an encounter_fun function then the encounters of these components will be included in the returned value.

Extension hook

projectEncounter() is the S3 generic used by extension-aware projections. Extension packages can add methods for their marker classes and call NextMethod() to compose encounter-rate changes. The MizerParams method contains the standard mizer calculation and is also exported as mizerEncounter() for compatibility.

Your own encounter function

By default getEncounter() calls mizerEncounter() on models without extensions. However you can replace this with your own alternative encounter function. If your function is called "myEncounter" then you register it in a MizerParams object params with

params <- setRateFunction(params, "Encounter", "myEncounter")

Your function will then be called instead of mizerEncounter(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

encounter <- getEncounter(NS_params)
str(encounter)

Get the total fishing mortality rate from all fishing gears by time, species and size.

Description

Calculates the total fishing mortality (in units 1/year) from all gears by species and size and possibly time. See setFishing() for details of how fishing gears are set up.

Usage

getFMort(object, ...)

Arguments

Details

The total fishing mortality is just the sum of the fishing mortalities imposed by each gear, F_i(w)=\sum_g F_{g,i,w}. The fishing mortality for each gear is obtained as catchability x selectivity x effort.

Value

• MizerParams with vector effort: An ArraySpeciesBySize object (species x size) with the fishing mortality rates.

• MizerParams with time-dimensioned effort or MizerSim: An ArrayTimeBySpeciesBySize object (time x species x size).

The effort argument is only used if a MizerParams object is passed in. The effort argument can be a two dimensional array (time x gear), a vector of length equal to the number of gears (each gear has a different effort that is constant in time), or a single numeric value (each gear has the same effort that is constant in time). The order of gears in the effort argument must be the same as in the MizerParams object.

If the object argument is of class MizerSim then the effort slot of the MizerSim object is used and the effort argument is not used.

Your own fishing mortality function

By default getFMort() calls mizerFMort(). However you can replace this with your own alternative fishing mortality function. If your function is called "myFMort" then you register it in a MizerParams object params with

params <- setRateFunction(params, "FMort", "myFMort")

Your function will then be called instead of mizerFMort(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Get the total fishing mortality in the initial state
F <- getFMort(params, effort = 1)
str(F)
# Get the initial total fishing mortality when effort is different
# between the four gears:
F <- getFMort(params, effort = c(0.5,1,1.5,0.75))
# Get the total fishing mortality when effort is different
# between the four gears and changes with time:
effort <- array(NA, dim = c(20,4))
effort[, 1] <- seq(from = 0, to = 1, length = 20)
effort[, 2] <- seq(from = 1, to = 0.5, length = 20)
effort[, 3] <- seq(from = 1, to = 2, length = 20)
effort[, 4] <- seq(from = 2, to = 1, length = 20)
F <- getFMort(params, effort = effort)
str(F)
# Get the total fishing mortality using the effort already held in a
# MizerSim object.
sim <- project(params, t_max = 20, effort = 0.5)
F <- getFMort(sim)
F <- getFMort(sim, time_range = c(10, 20))

Get the fishing mortality by time, gear, species and size

Description

Calculates the fishing mortality rate F_{g,i,w} by gear, species and size and possibly time (in units 1/year).

Usage

getFMortGear(object, ...)

Arguments

Value

An array. If the effort argument has a time dimension, or a MizerSim is passed in, the output array has four dimensions (time x gear x species x size). If the effort argument does not have a time dimension (i.e. it is a vector or a single numeric), the output array has three dimensions (gear x species x size).

Note

Here: fishing mortality = catchability x selectivity x effort.

The effort argument is only used if a MizerParams object is passed in. The effort argument can be a two dimensional array (time x gear), a vector of length equal to the number of gears (each gear has a different effort that is constant in time), or a single numeric value (each gear has the same effort that is constant in time). The order of gears in the effort argument must be the same the same as in the MizerParams object. If the effort argument is not supplied, its value is taken from the ⁠@initial_effort⁠ slot in the params object.

If the object argument is of class MizerSim then the effort slot of the MizerSim object is used and the effort argument is not used.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <-NS_params
# Get the fishing mortality in initial state
F <- getFMortGear(params, effort = 1)
str(F)
# Get the initial fishing mortality when effort is different
# between the four gears:
F <- getFMortGear(params, effort = c(0.5, 1, 1.5, 0.75))
# Get the fishing mortality when effort is different
# between the four gears and changes with time:
effort <- array(NA, dim = c(20, 4))
effort[, 1] <- seq(from=0, to = 1, length = 20)
effort[, 2] <- seq(from=1, to = 0.5, length = 20)
effort[, 3] <- seq(from=1, to = 2, length = 20)
effort[, 4] <- seq(from=2, to = 1, length = 20)
F <- getFMortGear(params, effort = effort)
str(F)
# Get the fishing mortality using the effort already held in a MizerSim object.
sim <- project(params, t_max = 20, effort = 0.5)
F <- getFMortGear(sim)
F <- getFMortGear(sim, time_range = c(10, 20))

Get feeding level

Description

Returns the feeding level. By default this function uses mizerFeedingLevel() to calculate the feeding level, but this can be overruled via setRateFunction().

Usage

getFeedingLevel(object, ...)

Arguments

Value

• MizerParams: An ArraySpeciesBySize object (predator species x predator size) with the feeding level.

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x predator species x predator size) with the feeding level at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Feeding level

The feeding level f_i(w) is the proportion of its maximum intake rate at which the predator is actually taking in fish. It is calculated from the encounter rate E_i and the maximum intake rate h_i(w) as

f_i(w) = \frac{E_i(w)}{E_i(w)+h_i(w)}.

The encounter rate E_i is passed as an argument or calculated with getEncounter(). The maximum intake rate h_i(w) is taken from the params object, and is set with setMaxIntakeRate(). As a consequence of the above expression for the feeding level, 1-f_i(w) is the proportion of the food available to it that the predator actually consumes.

Your own feeding level function

By default getFeedingLevel() calls mizerFeedingLevel(). However you can replace this with your own alternative feeding level function. If your function is called "myFeedingLevel" then you register it in a MizerParams object params with

params <- setRateFunction(params, "FeedingLevel", "myFeedingLevel")

Your function will then be called instead of mizerFeedingLevel(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Get initial feeding level
fl <- getFeedingLevel(params)
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the feeding level at all saved time steps
fl <- getFeedingLevel(sim)
# Get the feeding level for years 15 - 20
fl <- getFeedingLevel(sim, time_range = c(15, 20))

Get flux into size bins

Description

Calculates the flux J_i(w) (numbers/year) entering each size class from the one below it. This is composed of an advective flux from somatic growth and a diffusive flux from the redistribution of individuals.

Usage

getFlux(object, ..., power = 0)

Arguments

Details

At the recruitment size, the flux is simply the recruitment rate R_{dd,i} (see getRDD()). For sizes below the recruitment size the flux is zero.

The flux at weight w is multiplied by w raised to the power given by the power argument, similar to the power argument of plotSpectra(). The default power = 0 returns the flux of individuals (numbers/year). With power = 1 the result is the flux of biomass (grams/year).

Value

• MizerParams: An ArraySpeciesBySize object (species x size) with the flux entering each size class. The units are numbers/year when power = 0 and g^power/year otherwise.

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x species x size) with the flux at every time step. If drop = TRUE then dimensions of length 1 will be removed.

See Also

getEGrowth(), getRDD()

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the flux at a particular time step
flux <- getFlux(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ], t = 15)
# Flux for Sprat of size 2g
flux["Sprat", "2"]

Get growth curves giving weight as a function of age

Description

Get growth curves giving weight as a function of age

Usage

getGrowthCurves(object, species = NULL, max_age = 20, percentage = FALSE)

Arguments

Value

An array (species x age) containing the weight in grams.

See Also

Other summary functions: getBiomass(), getDiet(), getN(), getSSB(), getTrophicLevel(), getTrophicLevelBySpecies(), getYield(), getYieldGear()

Examples

growth_curves <- getGrowthCurves(NS_params, species = c("Cod", "Haddock"))
str(growth_curves)

library(ggplot2)
ggplot(melt(growth_curves)) +
  geom_line(aes(Age, value)) +
  facet_wrap(~ Species, scales = "free") +
  ylab("Size[g]") + xlab("Age[years]")

Deprecated function to get interaction matrix

Description

You should now use interaction_matrix() instead.

Usage

getInteraction(params)

Arguments

Alias for getPredMort()

Description

An alias provided for backward compatibility with mizer version <= 1.0

Usage

getM2(object, ...)

Arguments

Value

• MizerParams: An ArraySpeciesBySize object (prey species x prey size) with the predation mortality rates.

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x prey species x prey size) with the predation mortality at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own predation mortality function

By default getPredMort() calls mizerPredMort(). However you can replace this with your own alternative predation mortality function. If your function is called "myPredMort" then you register it in a MizerParams object params with

params <- setRateFunction(params, "PredMort", "myPredMort")

Your function will then be called instead of mizerPredMort(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Predation mortality in initial state
M2 <- getPredMort(params)
str(M2)
# With constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get predation mortality at one time step
M2 <- getPredMort(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ])
# Get predation mortality at all saved time steps
M2 <- getPredMort(sim)
str(M2)
# Get predation mortality over the years 15 - 20
M2 <- getPredMort(sim, time_range = c(15, 20))

Alias for getResourceMort()

Description

An alias provided for backward compatibility with mizer version <= 1.0

Usage

getM2Background(
  params,
  n = initialN(params),
  n_pp = initialNResource(params),
  n_other = initialNOther(params),
  t = 0,
  ...
)

Arguments

Value

A vector of mortality rate by resource size.

Your own resource mortality function

By default getResourceMort() calls mizerResourceMort(). However you can replace this with your own alternative resource mortality function. If your function is called "myResourceMort" then you register it in a MizerParams object params with

params <- setRateFunction(params, "ResourceMort", "myResourceMort")

Your function will then be called instead of mizerResourceMort(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates()

Examples

params <- NS_params
# With constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get resource mortality at one time step
getResourceMort(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ])

Calculate the mean maximum weight of the community

Description

Calculates the mean maximum weight of the community. This can be calculated by numbers or biomass. The calculation is the sum of the w_max * abundance of each species, divided by the total abundance community, where abundance is either in biomass or numbers. You can specify minimum and maximum weight or length range for the species. Lengths take precedence over weights (i.e. if both min_l and min_w are supplied, only min_l will be used). You can also specify the species to be used in the calculation.

Usage

getMeanMaxWeight(object, species = NULL, measure = "both", ...)

Arguments

Value

Depends on the measure argument. If measure = “both” then you get a matrix with two columns, one with values by numbers, the other with values by biomass at each saved time step (or a named vector with two entries for MizerParams). If measure = “numbers” or “biomass” you get a vector of the respective values at each saved time step (or a single value for MizerParams).

See Also

Other functions for calculating indicators: getCommunitySlope(), getMeanWeight(), getProportionOfLargeFish()

Examples

mmw <- getMeanMaxWeight(NS_sim)
years <- c("1967", "2010")
mmw[years, ]
getMeanMaxWeight(NS_sim, species=c("Herring","Sprat","N.pout"))[years, ]
getMeanMaxWeight(NS_sim, min_w = 10, max_w = 5000)[years, ]
getMeanMaxWeight(NS_params)

Calculate the mean weight of the community

Description

Calculates the mean weight of the community. This is simply the total biomass of the community divided by the abundance in numbers. You can specify minimum and maximum weight or length range for the species. Lengths take precedence over weights (i.e. if both min_l and min_w are supplied, only min_l will be used). You can also specify the species to be used in the calculation.

Usage

getMeanWeight(object, species = NULL, ...)

Arguments

Value

A vector containing the mean weight of the community through time, or a single value if called with a MizerParams object.

See Also

Other functions for calculating indicators: getCommunitySlope(), getMeanMaxWeight(), getProportionOfLargeFish()

Examples

mean_weight <- getMeanWeight(NS_sim)
years <- c("1967", "2010")
mean_weight[years]
getMeanWeight(NS_sim, species = c("Herring", "Sprat", "N.pout"))[years]
getMeanWeight(NS_sim, min_w = 10, max_w = 5000)[years]
getMeanWeight(NS_params)

Get total mortality rate

Description

Calculates the total mortality rate \mu_i(w) (in units 1/year) on each species by size from predation mortality, background mortality and fishing mortality for a single time step.

Usage

getMort(object, ...)

Arguments

Details

If your model contains additional components that you added with setComponent() and for which you specified a mort_fun function then the mortality inflicted by these components will be included in the returned value.

Value

• MizerParams: An ArraySpeciesBySize object (species x size) with the total mortality rates.

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x species x size) with the total mortality rates at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own mortality function

By default getMort() calls mizerMort(). However you can replace this with your own alternative mortality function. If your function is called "myMort" then you register it in a MizerParams object params with

params <- setRateFunction(params, "Mort", "myMort")

Your function will then be called instead of mizerMort(), with the same arguments.

See Also

getPredMort(), getFMort()

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the total mortality at a particular time step
mort <- getMort(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ],
                t = 15, effort = 0.5)
# Mortality rate at this time for Sprat of size 2g
mort["Sprat", "2"]

Calculate the number of individuals within a size range

Description

Calculates the number of individuals within user-defined size limits. The default option is to use the whole size range. You can specify minimum and maximum weight or lengths for the species. Lengths take precedence over weights (i.e. if both min_l and min_w are supplied, only min_l will be used)

Usage

getN(object, ...)

Arguments

Value

If called with a MizerParams object, a named vector with the numbers for each species in the model. If called with a MizerSim object, a ArrayTimeBySpecies object (time x species) containing the numbers at each time step for all species.

See Also

Other summary functions: getBiomass(), getDiet(), getGrowthCurves(), getSSB(), getTrophicLevel(), getTrophicLevelBySpecies(), getYield(), getYieldGear()

Examples

numbers <- getN(NS_sim)
numbers["1972", "Herring"]
# The above gave a huge number, because that included all the larvae.
# The number of Herrings between 10g and 1kg is much smaller.
numbers <- getN(NS_sim, min_w = 10, max_w = 1000)
numbers["1972", "Herring"]

Extract the model state from a simulation

Description

A MizerParams object describes the state of the ecosystem: its species parameters, size grid, rate functions, and the current abundances stored in the initial_n, initial_n_pp, initial_n_other, and initial_effort slots. getParams() extracts that state from a MizerSim object, averaged over a chosen time range (or at a single time point).

Usage

getParams(sim, time_range, geometric_mean = FALSE)

Arguments

Details

When no time_range is given, the state at the final time step is returned. Use initialParams() or finalParams() as convenient shorthand for the state at the initial and final time respectively.

The abundances set in the returned MizerParams object are averages over the selected time range. By default this is an arithmetic mean; set geometric_mean = TRUE to use a geometric mean instead (this does not affect the effort or other components, which are always averaged arithmetically).

Value

A MizerParams object with initial_n, initial_n_pp, initial_n_other, and initial_effort set to the (averaged) values from the simulation.

See Also

initialParams(), finalParams()

Examples

sim <- project(NS_params, t_max = 20, effort = 0.5)
# Extract state at a specific time
params_2010 <- getParams(sim, time_range = 10)
# Extract state averaged over the last 10 years
params_avg <- getParams(sim, time_range = c(10, 20))

Get available energy

Description

This is deprecated and is no longer used by the mizer project() method. Calculates the amount E_{a,i}(w) of food exposed to each predator as a function of predator size.

Usage

getPhiPrey(object, n, n_pp, ...)

Arguments

Value

A two dimensional array (predator species x predator size) equal to getEncounter(object, n, n_pp) / getSearchVolume(object).

See Also

project()

Get total predation mortality rate

Description

Calculates the total predation mortality rate \mu_{p,i}(w_p) (in units of 1/year) on each prey species by prey size:

\mu_{p.i}(w_p) = \sum_j {\tt pred\_rate}_j(w_p)\, \theta_{ji}.

The predation rate pred_rate is returned by getPredRate().

Usage

getPredMort(object, ...)

Arguments

Value

• MizerParams: An ArraySpeciesBySize object (prey species x prey size) with the predation mortality rates.

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x prey species x prey size) with the predation mortality at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own predation mortality function

By default getPredMort() calls mizerPredMort(). However you can replace this with your own alternative predation mortality function. If your function is called "myPredMort" then you register it in a MizerParams object params with

params <- setRateFunction(params, "PredMort", "myPredMort")

Your function will then be called instead of mizerPredMort(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Predation mortality in initial state
M2 <- getPredMort(params)
str(M2)
# With constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get predation mortality at one time step
M2 <- getPredMort(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ])
# Get predation mortality at all saved time steps
M2 <- getPredMort(sim)
str(M2)
# Get predation mortality over the years 15 - 20
M2 <- getPredMort(sim, time_range = c(15, 20))

Get predation rate

Description

Calculates the potential rate (in units 1/year) at which a prey individual of a given size w is killed by predators from species j. In formulas

{\tt pred\_rate}_j(w_p) = \int \phi_j(w,w_p) (1-f_j(w)) \gamma_j(w) N_j(w) \, dw.

This potential rate is used in getPredMort() to calculate the realised predation mortality rate on the prey individual.

Usage

getPredRate(object, ...)

Arguments

Value

• MizerParams: An ArraySpeciesBySize object (predator species x prey size), where the prey size runs over fish community plus resource spectrum.

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x predator species x prey size) with the predation rates at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own predation rate function

By default getPredRate() calls mizerPredRate(). However you can replace this with your own alternative predation rate function. If your function is called "myPredRate" then you register it in a MizerParams object params with

params <- setRateFunction(params, "PredRate", "myPredRate")

Your function will then be called instead of mizerPredRate(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Predation rate in initial state
pred_rate <- getPredRate(params)
str(pred_rate)
# With constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the feeding level at one time step
pred_rate <- getPredRate(params, n = N(sim)[15, , ],
                         n_pp = NResource(sim)[15, ], t = 15)

Calculate the proportion of large fish

Description

Calculates the proportion of large fish in a MizerSim or MizerParams object within user defined size limits. The default option is to use the whole size range. You can specify minimum and maximum size ranges for the species and also the threshold size for large fish. Sizes can be expressed as weight or length. Lengths take precedence over weights (i.e. if both min_l and min_w are supplied, only min_l will be used, and if threshold_l is supplied it takes precedence over threshold_w). You can also specify the species to be used in the calculation. This function can be used to calculate the Large Fish Index. The proportion is based on either abundance or biomass.

Usage

getProportionOfLargeFish(
  object,
  species = NULL,
  threshold_w = 100,
  threshold_l = NULL,
  biomass_proportion = TRUE,
  ...
)

Arguments

Value

A vector containing the proportion of large fish through time, or a single value if called with a MizerParams object.

See Also

Other functions for calculating indicators: getCommunitySlope(), getMeanMaxWeight(), getMeanWeight()

Examples

lfi <- getProportionOfLargeFish(NS_sim, min_w = 10, max_w = 5000,
                                threshold_w = 500)
years <- c("1972", "2010")
lfi[years]
getProportionOfLargeFish(NS_sim)[years]
getProportionOfLargeFish(NS_sim, species=c("Herring","Sprat","N.pout"))[years]
getProportionOfLargeFish(NS_sim, min_w = 10, max_w = 5000)[years]
getProportionOfLargeFish(NS_sim, min_w = 10, max_w = 5000,
    threshold_w = 500, biomass_proportion = FALSE)[years]
getProportionOfLargeFish(NS_params)

Get density dependent reproduction rate

Description

Calculates the density dependent rate of egg production R_i (units 1/year) for each species. This is the flux entering the smallest size class of each species. The density dependent rate is the density independent rate obtained with getRDI() after it has been put through the density dependence function. This is the Beverton-Holt function BevertonHoltRDD() by default, but this can be changed. See setReproduction() for more details.

Usage

getRDD(object, ...)

Arguments

Value

• MizerParams: A numeric vector the length of the number of species.

• MizerSim: An ArrayTimeBySpecies object (time x species).

See Also

getRDI()

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the rate at a particular time step
getRDD(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ], t = 15)

Get density independent rate of egg production

Description

Calculates the density-independent rate of total egg production R_{di} (units 1/year) before density dependence, by species.

Usage

getRDI(object, ...)

Arguments

Details

This rate is obtained by taking the per capita rate E_r(w)\psi(w) at which energy is invested in reproduction, as calculated by getERepro(), multiplying it by the number of individualsN(w) and integrating over all sizes w and then multiplying by the reproductive efficiency \epsilon and dividing by the egg size w_min, and by a factor of two to account for the two sexes:

R_{di} = \frac{\epsilon}{2 w_{min}} \int N(w) E_r(w) \psi(w) \, dw

Used by getRDD() to calculate the actual, density dependent rate. See setReproduction() for more details.

Value

• MizerParams: A numeric vector the length of the number of species.

• MizerSim: An ArrayTimeBySpecies object (time x species).

Your own reproduction function

By default getRDI() calls mizerRDI(). However you can replace this with your own alternative reproduction function. If your function is called "myRDI" then you register it in a MizerParams object params with

params <- setRateFunction(params, "RDI", "myRDI")

Your function will then be called instead of mizerRDI(), with the same arguments. For an example of an alternative reproduction function see constantEggRDI().

See Also

getRDD()

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the density-independent reproduction rate at a particular time step
getRDI(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ], t = 15)

Get all rates

Description

Calls other rate functions in sequence and collects the results in a list. The rates returned are encounter, feeding level, energy for growth and reproduction, predation rate, predation mortality, and resource mortality. The purpose of this function is to provide a convenient way to get all the rates at once, and to ensure that they are all calculated at the same time step with the same inputs. The rates are returned in a list with the same names as the rate functions that calculate them, so for example the encounter rate is returned in the list element named "encounter" and is calculated with the getEncounter() function.

Usage

getRates(
  params,
  n = initialN(params),
  n_pp = initialNResource(params),
  n_other = initialNOther(params),
  effort,
  t = 0,
  ...
)

Arguments

Details

When mizer needs to calculate the rates during a simulation it does not use this function but instead the faster projectRates().

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getResourceMort()

Examples

rates <- getRates(NS_params)
names(rates)
identical(rates$encounter, getEncounter(NS_params))

Get the registered mizer extension chain

Description

Get the registered mizer extension chain

Usage

getRegisteredExtensions()

Value

A named character vector giving the maximal extension chain registered for this R session.

See Also

"Using mizer extension packages": vignette("using-extension-packages", package = "mizer")

Other extension tools: NOther(), clearExtensionChain(), coerceToExtensionClass(), initialNOther<-(), registerExtension(), registerExtensions(), setComponent(), setRateFunction()

Get reproduction level

Description

The reproduction level is the ratio between the density-dependent reproduction rate and the maximal reproduction rate.

Usage

getReproductionLevel(params)

Arguments

Value

A named vector with the reproduction level for each species.

Examples

getReproductionLevel(NS_params)

# The reproduction level can be changed without changing the steady state:
params <- setBevertonHolt(NS_params, reproduction_level = 0.9)
getReproductionLevel(params)

# The result is the ratio of RDD and R_max
identical(getRDD(params) / species_params(params)$R_max,
          getReproductionLevel(params))

Determine reproduction rate needed for initial egg abundance

Description

Determine reproduction rate needed for initial egg abundance

Usage

getRequiredRDD(params)

Arguments

Value

A vector of reproduction rates for all species

Deprecated functions for getting resource parameters

Description

Use resource_dynamics(), resource_level(), resource_rate() and resource_capacity() instead.

Usage

getResourceDynamics(params)

getResourceLevel(params)

getResourceRate(params)

getResourceCapacity(params)

Arguments

Value

Name of the function that determines the resource dynamics

Get predation mortality rate for resource

Description

Calculates the predation mortality rate \mu_p(w) on the resource spectrum by resource size (in units 1/year).

Usage

getResourceMort(
  params,
  n = initialN(params),
  n_pp = initialNResource(params),
  n_other = initialNOther(params),
  t = 0,
  ...
)

Arguments

Value

A vector of mortality rate by resource size.

Your own resource mortality function

By default getResourceMort() calls mizerResourceMort(). However you can replace this with your own alternative resource mortality function. If your function is called "myResourceMort" then you register it in a MizerParams object params with

params <- setRateFunction(params, "ResourceMort", "myResourceMort")

Your function will then be called instead of mizerResourceMort(), with the same arguments.

See Also

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getMort(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates()

Examples

params <- NS_params
# With constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get resource mortality at one time step
getResourceMort(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ])

Calculate the SSB of species

Description

Calculates the spawning stock biomass (SSB) for each species. For a MizerSim object this is returned for every saved time; for a MizerParams object it is calculated from the initial state. SSB is the total mass of all mature individuals.

Usage

getSSB(object)

Arguments

Value

If called with a MizerParams object, a named vector with the SSB in grams for each species in the model. If called with a MizerSim object, a ArrayTimeBySpecies object (time x species) containing the SSB in grams at each time step for all species.

See Also

Other summary functions: getBiomass(), getDiet(), getGrowthCurves(), getN(), getTrophicLevel(), getTrophicLevelBySpecies(), getYield(), getYieldGear()

Examples

ssb <- getSSB(NS_sim)
ssb[c("1972", "2010"), c("Herring", "Cod")]

Extract the projection parameters used to produce a simulation

Description

Returns the named list of arguments passed to project() or projectToSteady() when producing this MizerSim object, such as method and dt. Returns an empty list for simulations produced by older versions of mizer.

Usage

getSimParams(sim)

Arguments

Value

A named list of projection parameters.

Examples

sim <- project(NS_params, t_max = 0.1, dt = 0.05, method = "predictor-corrector")
getSimParams(sim)

Times for which simulation results are available

Description

Times for which simulation results are available

Usage

getTimes(sim)

Arguments

Value

A numeric vector of the times (in years) at which simulation results have been stored in the MizerSim object.

Examples

getTimes(NS_sim)

Get trophic level of individuals at size

Description

Calculates the trophic level of individuals of each species at each size, assuming the system is in a steady state. The trophic level of an individual is defined as 1 more than the consumption-rate-weighted average trophic level of all the prey it has consumed during its lifetime up to the current size. The trophic level of the primary resource is set to 0.

Usage

getTrophicLevel(
  params,
  n = initialN(params),
  n_pp = initialNResource(params),
  n_other = initialNOther(params),
  ...
)

Arguments

Details

In the traditional non-size-resolved approach, all individuals of a species have the same diet composition D_{ij}, defined as the proportion of total biomass intake of species i that comes from species j. The trophic levels then satisfy

T_i = 1 + \sum_j D_{ij}\,T_j,

which is solved as a linear system (I - D)\,\mathbf{T} = \mathbf{1}.

In mizer, diet composition changes as an individual grows, so we must integrate over the individual's lifetime. Assuming a steady state so that the growth rate g_i(w) and prey densities depend only on size and not on time, we can replace the integral over time since birth by an integral over weight using dt = dw / g_i(w). The trophic level T_i(w) of an individual of species i at weight w is then

T_i(w) = 1 + \frac{ \int_{w_0}^{w} \frac{1}{g_i(w')} \sum_j \int r_{ij}(w', w_p)\, T_j(w_p)\, dw_p\, dw' }{ \int_{w_0}^{w} \frac{1}{g_i(w')} \sum_j \int r_{ij}(w', w_p)\, dw_p\, dw' },

where w_0 is the egg size and r_{ij}(w, w_p) is the rate at which a predator of species i at weight w consumes biomass from prey species j at weight w_p:

r_{ij}(w, w_p) = \theta_{ij}\,\gamma_i(w)\,(1 - f_i(w))\,\phi_i(w/w_p)\, N_j(w_p)\,w_p.

The sum over j runs over all species. The resource is excluded from the numerator because its trophic level is 0, but is included in the denominator (which equals the total biomass consumed over the predator's lifetime from egg size to current weight w).

This equation can be viewed as a linear system (I - D)\,\mathbf{T} = \mathbf{1} in which the entries of \mathbf{T} are indexed by (i, w) and the matrix D encodes the lifetime-integrated diet composition. The system is solved iteratively from small to large sizes, exploiting the fact that prey are typically much smaller than the predator (large predator-to-prey mass ratio), so that the trophic levels of all relevant prey sizes are already known when computing T_i(w).

Value

An ArraySpeciesBySize object (species x size) with the trophic level of individuals at each size. Entries below the egg size of each species are NA.

See Also

getTrophicLevelBySpecies()

Other summary functions: getBiomass(), getDiet(), getGrowthCurves(), getN(), getSSB(), getTrophicLevelBySpecies(), getYield(), getYieldGear()

Examples

tl <- getTrophicLevel(NS_params)
plot(tl)

Get mean trophic level of each species

Description

Calculates the consumption-rate-weighted mean trophic level of each species, defined as

T_i = \frac{\int r_i(w)\,N_i(w)\,T_i(w)\,dw} {\int r_i(w)\,N_i(w)\,dw},

where r_i(w) = (1 - f_i(w))\,E_i(w) is the consumption rate of an individual of species i at weight w, N_i(w) is the abundance density, and T_i(w) is the size-resolved trophic level from getTrophicLevel().

Usage

getTrophicLevelBySpecies(
  params,
  n = initialN(params),
  n_pp = initialNResource(params),
  n_other = initialNOther(params),
  ...
)

Arguments

Value

A named vector with the mean trophic level for each species.

See Also

getTrophicLevel()

Other summary functions: getBiomass(), getDiet(), getGrowthCurves(), getN(), getSSB(), getTrophicLevel(), getYield(), getYieldGear()

Examples

getTrophicLevelBySpecies(NS_params)

Calculate the rate at which biomass of each species is fished

Description

This yield rate is given in grams per year. It is calculated at each time step saved in the MizerSim object.

Usage

getYield(object)

Arguments

Details

The yield rate y_i(t) for species i at time t is defined as

y_i(t)=\int\mu_{f.i}(w, t)N_i(w, t)w dw

where \mu_{f.i}(w, t) is the fishing mortality of an individual of species i and weight w at time t and N_i(w, t) is the abundance density of such individuals. The factor of w converts the abundance density into a biomass density and the integral aggregates the contribution from all sizes.

The total catch in a time period from t_1 to t_2 is the integral of the yield rate over that period:

C = \int_{t_1}^{t2}y_i(t)dt

In practice, as the yield rate is only available at the saved times, one can only approximate this integral by averaging over the available yield rates during the time period and multiplying by the time period. The less the yield changes between the saved values, the more accurate this approximation is. So the approximation can be improved by saving simulation results at smaller intervals, using the t_save argument to project(). But this is only a concern if abundances change quickly during the time period of interest.

Value

If called with a MizerParams object, a named numeric vector with the yield rate in grams per year for each species in the model. If called with a MizerSim object, an ArrayTimeBySpecies object (time x species) containing the yield rate in grams per year at each saved time step.

See Also

getYieldGear()

Other summary functions: getBiomass(), getDiet(), getGrowthCurves(), getN(), getSSB(), getTrophicLevel(), getTrophicLevelBySpecies(), getYieldGear()

Examples

yield <- getYield(NS_sim)
yield[c("1972", "2010"), c("Herring", "Cod")]

# Running simulation for another year, saving intermediate time steps
params <- finalParams(NS_sim)
sim <- project(params, t_save = 0.1, t_max = 1,
               t_start = 2010, progress_bar = FALSE)
# The yield rate for Herring decreases during the year
getYield(sim)[, "Herring"]
# We approximate the total catch in the year by averaging over the year
sum(getYield(sim)[1:10, "Herring"] / 10)

Calculate the rate at which biomass of each species is fished by each gear

Description

This yield rate is given in grams per year. It is calculated at each time step saved in the MizerSim object.

Usage

getYieldGear(object)

Arguments

Details

For details of how the yield rate is defined see the help page of getYield().

Value

If called with a MizerParams object, an array (gear x species) with the yield rate in grams per year from each gear for each species in the model. If called with a MizerSim object, an array (time x gear x species) containing the yield rate at each time step.

See Also

getYield()

Other summary functions: getBiomass(), getDiet(), getGrowthCurves(), getN(), getSSB(), getTrophicLevel(), getTrophicLevelBySpecies(), getYield()

Examples

yield <- getYieldGear(NS_sim)
dim(yield)
yield["1972", , "Herring"]

Alias for getMort()

Description

An alias provided for backward compatibility with mizer version <= 1.0

Usage

getZ(object, ...)

Arguments

Details

If your model contains additional components that you added with setComponent() and for which you specified a mort_fun function then the mortality inflicted by these components will be included in the returned value.

Value

• MizerParams: An ArraySpeciesBySize object (species x size) with the total mortality rates.

• MizerSim: An ArrayTimeBySpeciesBySize object (time step x species x size) with the total mortality rates at every time step. If drop = TRUE then dimensions of length 1 will be removed.

Your own mortality function

By default getMort() calls mizerMort(). However you can replace this with your own alternative mortality function. If your function is called "myMort" then you register it in a MizerParams object params with

params <- setRateFunction(params, "Mort", "myMort")

Your function will then be called instead of mizerMort(), with the same arguments.

See Also

getPredMort(), getFMort()

Other rate functions: getDiffusion(), getEGrowth(), getERepro(), getEReproAndGrowth(), getEncounter(), getFMort(), getFMortGear(), getFeedingLevel(), getFlux(), getPredMort(), getPredRate(), getRDD(), getRDI(), getRates(), getResourceMort()

Examples

params <- NS_params
# Project with constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# Get the total mortality at a particular time step
mort <- getMort(params, n = N(sim)[15, , ], n_pp = NResource(sim)[15, ],
                t = 15, effort = 0.5)
# Mortality rate at this time for Sprat of size 2g
mort["Sprat", "2"]

Get the size grid for an ArraySpeciesBySize object

Description

Internal helper that returns the consumer size grid params@w or the full prey/resource size grid params@w_full, depending on the number of columns in the array.

Usage

get_ArraySpeciesBySize_w(x)

Arguments

Value

A numeric vector giving the size represented by each column.

Get default value for f0

Description

Fills in any missing values for f0 so that if the prey abundance was described by the power law \kappa w^{-\lambda} then the encounter rate coming from the given gamma parameter would lead to the feeding level f_0. This is thus doing the inverse of get_gamma_default(). Only for internal use.

Usage

get_f0_default(params)

Arguments

Details

For species for which no value for gamma is specified in the species parameter data frame, the f0 values is kept as provided in the species parameter data frame or it is set to 0.6 if it is not provided.

Value

A vector with the values of f0 for all species

See Also

Other functions calculating defaults: get_gamma_default(), get_h_default(), get_ks_default()

Get default value for gamma

Description

Fills in any missing values for gamma so that fish feeding on a resource spectrum described by the power law \kappa w^{-\lambda} achieve a feeding level f_0. Only for internal use.

Usage

get_gamma_default(params)

Arguments

Value

A vector with the values of gamma for all species

See Also

Other functions calculating defaults: get_f0_default(), get_h_default(), get_ks_default()

Get default value for h

Description

Sets h so that the species reaches maturity size w_mat at the maturity age age_mat if it feeds at feeding level f0.

Usage

get_h_default(params)

Arguments

Details

If age_mat is missing in the species parameter data frame, then it is calculated from the von Bertalanffy growth curve parameters k_vb and (optionally t0) taken from the species parameter data frame. This is not reliable and a warning is issued.

If no growth information is given at all for a species, the default is set to h = 30.

Value

A vector with the values of h for all species

See Also

Other functions calculating defaults: get_f0_default(), get_gamma_default(), get_ks_default()

Calculate initial population abundances

Description

This function uses the model parameters and other parameters to calculate initial values for the species number densities. These initial abundances are currently quite arbitrary and not close to the steady state. We intend to improve this in the future.

Usage

get_initial_n(params, n0_mult = NULL, a = 0.35)

Arguments

Value

An ArraySpeciesBySize object (species x size) of population abundances.

Examples

init_n <- get_initial_n(NS_params)

Get default value for ks

Description

Fills in any missing values for ks so that the critical feeding level needed to sustain the species is as specified in the fc column in the species parameter data frame. If that column is not provided the default critical feeding level f_c = 0.2 is used.

Usage

get_ks_default(params)

Arguments

Value

A vector with the values of ks for all species

See Also

Other functions calculating defaults: get_f0_default(), get_gamma_default(), get_h_default()

Get values from feeding kernel function

Description

This involves finding the feeding kernel function for each species, using the pred_kernel_type parameter in the species_params data frame, checking that it is valid and all its arguments are contained in the species_params data frame, and then calling this function with the ppmr vector.

Usage

get_phi(species_params, ppmr)

Arguments

Value

An array (species x ppmr) with the values of the predation kernel function

Extract one saved simulation state for a rate calculation

Description

Internal helper used by MizerSim rate methods to rebuild the single-time inputs expected by MizerParams rate methods.

Usage

get_sim_rate_slice(sim, time_idx)

Arguments

Value

A list with entries n, n_pp, n_other, effort, and t.

Get selected saved time steps for a simulation rate

Description

Internal helper used by MizerSim rate methods. If time_range is missing, all saved simulation times are selected; otherwise the request is delegated to get_time_elements().

Usage

get_sim_rate_time_elements(sim, time_range)

Arguments

Value

A named logical vector indicating the selected saved time steps.

Get size range array

Description

Helper function that returns an array (species x size) of logical values indicating whether that size bin is within the size limits specified by the arguments. Either the size limits can be the same for all species or they can be specified as vectors with one value for each species in the model.

Usage

get_size_range_array(
  params,
  min_w = min(params@w),
  max_w = max(params@w),
  min_l = NULL,
  max_l = NULL,
  ...
)

Arguments

Value

A logical array (species x size), with dimnames sp and w.

Length to weight conversion

If min_l is specified there is no need to specify min_w and so on. However, if a length is specified (minimum or maximum) then it is necessary for the species parameter data.frame to include the parameters a and b that determine the relation between length l and weight w by

w = a l^b.

It is possible to mix length and weight constraints, e.g. by supplying a minimum weight and a maximum length, but this must be done the same for all species. The default values are the minimum and maximum weights of the spectrum, i.e., the full range of the size spectrum is used.

Apply a species-by-size rate function over saved simulation times

Description

Internal helper used by MizerSim rate methods whose one-time result is an ArraySpeciesBySize. The helper applies the supplied rate function to each selected time slice, stacks the results, and restores the appropriate mizer array class when dimensions have not been dropped.

Usage

get_species_size_rate_from_sim(
  sim,
  time_range,
  drop,
  rate_fun,
  value_name,
  units = NULL
)

Arguments

Value

A time x species x size array, possibly with dimensions dropped.

Apply a species rate function over saved simulation times

Description

Internal helper used by MizerSim rate methods whose one-time result is a named vector with one value for each species.

Usage

get_species_time_rate_from_sim(
  sim,
  time_range,
  rate_fun,
  value_name,
  units = NULL
)

Arguments

Value

An ArrayTimeBySpecies object with dimensions time x species.

Calculate steady state abundance

Description

This function calculates the steady state abundance by solving the transport equation with given growth and mortality rates. It sets up a tri-diagonal system and solves it.

Usage

get_steady_state_n(params, g, mu, D, N0)

Arguments

Value

A matrix with the steady state abundance

Get array indices for a time range in a MizerSim object

Description

Internal helper to select the saved time points whose times lie between the smallest and largest values in time_range, inclusive.

Usage

get_time_elements(sim, time_range, slot_name = "n")

Arguments

Value

A named logical vector, with one entry for each saved time in sim, indicating whether that time lies in the requested range.

Description of indicator functions

Description

Mizer provides a range of functions to calculate indicators from a MizerSim or MizerParams object.

Details

When called with a MizerSim object, these functions return a time series of values. When called with a MizerParams object, they return a single value calculated from the initial abundances stored in the params object.

A list of available indicator functions is given in the table below

See Also

summary_functions, plotting_functions

Initial values for fish spectra

Description

Values used as starting values for simulations with project().

Usage

initialN(params) <- value

initialN(object)

Arguments

Value

An ArraySpeciesBySize object with dimensions species x size holding the initial number densities for the fish spectra.

See Also

initialNResource(), initialNOther()

Examples

# Doubling abundance of Cod in the initial state of the North Sea model
params <- NS_params
initialN(params)["Cod", ] <- 2 * initialN(params)["Cod", ]

Initial values for other ecosystem components

Description

Values used as starting values for simulations with project().

Usage

initialNOther(params) <- value

initialNOther(object)

Arguments

Value

A named list with the initial values of other ecosystem components

See Also

initialNResource(), initialN()

Other extension tools: NOther(), clearExtensionChain(), coerceToExtensionClass(), getRegisteredExtensions(), registerExtension(), registerExtensions(), setComponent(), setRateFunction()