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ecosystemom

Ecosystem operating model. Generates data sets from ecosystem model scenarios for stock assessment models.

Installing ecosystemom

Install the most recent version of FIMSdiags using the following code:

install.packages("remotes")
remotes::install_github("NOAA-FIMS/ecosystemom")

or using {pak}

pak::pak("NOAA-FIMS/ecosystemom")

Why are we building {ecosystemom}?

  • Connect ecosystem model outputs to stock assessment simulation testing through a flexible operating model framework.
  • Support evaluation and comparison of FIMS and other assessment methods against ecosystem model outputs under realistic ecosystem dynamics.
  • Enable research on ecosystem-informed stock assessment approaches.
  • Foster collaboration between ecosystem modelers and stock assessment scientists.

🤝 Contributions and feedback are welcome! If you're interested in this project or its applications, please interact with this repository or contact Bai Li at [email protected]

Functions

The package includes functions below:

  • load_model() — import and standardize output from ecosystem operating models (OM). For example, this function can be used to read and standardize Ecopath with Ecosim (EwE) Ecosim outputs for downstream analyses within {ecosystemom}.
  • get_truth() — extract “true” population quantities from the OM, including annual or monthly biomass trajectories and biomass-at-age.
  • sample_*() — generate sampled observations from OM outputs that incorporate sampling and observation error for use in estimation models such as the Fisheries Integrated Modeling System (FIMS).
  • create_dsem_inputs() — prepare environmental covariates or diet composition data from the OM to support candidate model specifications for dynamic structural equation models (DSEMs) and related ecosystem-informed analyses.

Pkgdown site

The pkgdown site is temporarily being built from the add-a-demo branch and is currently under active development.

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Ecosystem operating model. Generates data sets from ecosystem model scenarios for stock assessment models.

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