Example application of MetaIPM to the Illinois River

Authors: Richard A. Erickson, James P. Peirce, Gregory J. Sandland, Hannah M. Thompson, Michael N. Fienen, and Charles J. Labuzzetta

Point of contact: Richard A. Erickson (rerickson@usgs.gov)

Repository Type: Jupyter Notebook supporting publication

Year of Origin: 2022 (original publication)

Year of Version: under review

Digital Object Identifier (DOI): https://doi.org/10.5066/P94CUS9A

USGS Information Product Data System (IPDS) no.: IP-154563 (internal agency tracking)

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Suggested Citation:

Erickson, RA, Peirce, JP, Sandland, GJ, Thompson, HM, Fienen, MN, and Labuzzetta, CJ. 2024. Example application of MetaIPM to the Illinois River. Version 2.0. U.S. Geological Survey software release. Reston, Va. https://doi.org/10.5066/P94CUS9A.

Authors' ORCID nos.:

• Richard A. Erickson, 0000-0003-4649-482X
• James P. Peirce, 0000-0002-7147-3695
• Gregory J. Sandland, 0000-0002-9716-0232
• Hannah M. Thompson, 0000-0001-8316-3232
• Michael N. Fienen, 0000-0002-7756-4651
• Charles J. Labuzzetta, 0000-0002-6027-0120

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This repository contains an example application of the Meta-IPM Python package (https://doi.org/10.5066/P9427H6M). The specific application focuses on the Illinois River using existing public data. The code for this project assumes the reader is familiar with Jupyter Notebooks, enough Conda and Python to install the Meta-IPM package, and population ecology. The example also assumes the user is familiar with the Meta-IPM package from the package's documentation.

Use notes/dependencies

• This respository requires version >2.0 of MetaIPM.
• This repository requires results from the "Analysis of carp demographic data" repository (https://doi.org/10.5066/P9Q6SUML)

Repository organization

• Files in the main-level of the repository
  • README.md, which is this file.
  • .gitignore is a Git ignore files for the repository.
  • LICENSE.md is the Official USGS License.
  • Contributing.md describes how to contribute to this project.
  • DISCLAIMER.md is the standard USGS disclaimer.
  • code.json is the required meta-data about the code in a machine readable file.
• output contains outputs figures.
• IL_example.ipynb contains the example application of the model to the Illinois River
• input_data contains model inputs as documented in the MetaIPM model.
  • Coulter_key.csv links the columns of psi_svcp_With_stay.csv to pools in the Illinois River
  • inputs.py reformat outputs from https://doi.org/10.5066/P9Q6SUML to work with MetaIPM
  • node.csv contains details about nodes for the example simulation.
  • psi_svcp_With_stay.csv contains movement probabilities between pools as used in the model. This includes the probability of staying within a pool.
  • reformat_coulter.R turns psi_svcp.csv into psi_svcp_With_stay.csv.
  • vonB_sigma.csv is an input for MetaIPM.
  • group_details.csv contains the group details for MetaIPM
  • network.csv contains the network details for MetaIPM
  • psi_svcp.csv are the raw movement probabilities from Coulter et al. (2022), saved with all chains in one csv file for easier use with models.

Programming background

This code assumes the user is familiar with basic Jupyter Notebooks and Python.

Code run time

The Juypter file takes less than 20 minutes to run on a standard 2020 laptop.

Acknowledgments

Funding for the coding portion of this study was provided by the USGS Biothreats Program and Great Lakes Restoration Initiative.

References

Coulter, A. A.; Brey, M. K.; Lubjeko, M.; Kalis, J. L.; Coulter, D. P.; Glover, D. C.; Whitledge, G. W.; and Garvey, J. E., "Movement Probabilities of Bigheaded Carps (Hypophthalmichthys spp.) in the Illinois River Estimated from Markov Chain Monte Carlo Methods" (2022). NRM Departmental Data Sets. 3. https://openprairie.sdstate.edu/nrm_datasets/3