Details of the model can be found in the following publications:
Hall et al. (2006). A length-based multispecies model for evaluating community responses to fishing. Can. J. Fish. Aquat. Sci. 63:1344-1359. doi: https://doi.org/10.1139/f06-039
Rochet et al. (2011). Does selective fishing conserve community biodiversity? Prediction from a length-based multispecies model. Can. J. Fish. Aquat. Sci. 68:469-486. doi: https://doi.org/10.1139/F10-159
Originally coded in MATLAB
Commments/questions/bugs should be documented at https://github.com/NOAA-EDAB/LeMANS/issues
Features
Each component of the model (M1, M2, F, suitability, size preference etc) has been modularized such that a users code block can be substitued.
original data files (used in Rochet et al. (2011)) are bundled with the package.
The code is substantially faster (~9 times) than the original MATLAB implementation
It serves as a framework for extending the model
Usage
Installation
# build the package from github with vignettes
remotes::install_github("NOAA-EDAB/LeMANS",build_vignettes = TRUE)If you don’t have remotes installed you will see an error “there is no package called ‘remotes’”; if that happens install devtools with install.packages("remotes").
If installation of LeMANS fails, it could be due to the Rcpp package. Try to install Rcpp first.
Help
# view the documentation on usage
browseVignettes("LeMANS")The code was developed with a similar structure to the MATLAB code. Supporting data files are lazily loaded and ready to use.
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rochet_GB_foodweb- Predator-prey matrix (binary). Predator (column), prey (row) -
rochet_GB_initialValues- number of individuals per tow for each species/sizeclass combination -
rochet_GB_parameterValues- carrying capacity (k), Maximum length (Linf) + for each species -
rochet_GB_species- lists common name, scientific name, and guild each species is a member of. -
rochet_GB_modelSetup- A list containing species independent parameter values (otherFood, Falpha, FL50)
To run the model with parameter values described in the Rochet et al paper simply type:
results <- key_run(Ffull=0.4, nYrs=50, rochet_GB_modelSetup, rochet_GB_parameterValues, rochet_GB_initialValues, rochet_GB_foodweb, rochet_GB_species)
To plot the catch output aggregated over sizeClass:
plot_key_run(results$catch/1E6, ylabel = "catch (millions individuals)", is.aggregated=T, speciesNames=rochet_GB_species, scale="free")
Contact
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Legal disclaimer
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