Mizer is an R package to run multi-species size-spectrum models of fish communities. The package has been developed to model marine ecosystems that are subject to fishing. However, it may also be appropriate for other ecosystems.

The package contains routines and functions to allow users to set up an ecosystem model, and then project it through time under different fishing strategies. Methods are included to explore the results, including plots and calculation of community indicators such as the slope of the size spectrum. Size-based models can be complicated so mizer contains many default options that can be easily changed by the user.

Mizer can also be used to create web apps that allow users to explore models without the need to install R. An example of such an app investigates the effect of switching to a gear with a T90 extension net to reduce the catches of undersize hake and red mullet

Mizer is still under active development, currently funded by the European Commission Horizon 2020 Research and Innovation Programme under Grant Agreement No. 634495 for the project MINOUW (http://minouw-project.eu/) and the Australian Research Council Discovery Project (“Rewiring Marine Food Webs”).

Does your project or publication use mizer? If so, we’d love to know. You can also join our Google Discussion group here: https://groups.google.com/forum/#!forum/size-spectrum-models

The package is on CRAN and therefore available from R’s build-it package manager.

# Install release version from CRAN
install.packages("mizer")

# Alternatively, install development version from GitHub
devtools::install_github("sizespectrum/mizer")

The following code loads the mizer package, loads some information about species in the North Sea that comes as an example with the package, sets up the parameters for the mizer model, and runs a simulation for 10 years.

library(mizer)
data(NS_species_params)
data(inter)
params <- set_multispecies_model(NS_species_params, inter)
sim <- project(params, t_max = 10, effort = 0)

The results of the simulation can then be analysed, for example via plots:

plot(sim)

See the accompanying Get started page for more details on how the package works, including detailed examples.