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Conducting reproducible ecosystem modeling using the open source mass balance model Rpath

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  • Lucey, Sean M.
  • Gaichas, Sarah K.
  • Aydin, Kerim Y.

Abstract

Ecosystem models are important tools for conducting ecosystem-based management. A particularly useful method of characterizing the flow of energy through an ecosystem and the subsequent direct and indirect implications of management actions is mass balance modeling. Here we outline the equations as utilized in Rpath, an R implementation of the mass balance algorithms popularized by Ecopath with Ecosim that are designed to work with fisheries data sources. We believe that common practices in R will aid in the reproducibility of conducting analysis using a mass balance model as all of the code is contained within a single script file. This includes the built-in statistical and graphical functions of R. In addition to added reproducibility, R is a coding language with which ecologists are familiar. This familiarity offers greater flexibility for practitioners to tailor the model to their needs. We have made the code available on an open software development platform which should aid in continuous community development of the tool.

Suggested Citation

  • Lucey, Sean M. & Gaichas, Sarah K. & Aydin, Kerim Y., 2020. "Conducting reproducible ecosystem modeling using the open source mass balance model Rpath," Ecological Modelling, Elsevier, vol. 427(C).
    • Handle: RePEc:eee:ecomod:v:427:y:2020:i:c:s0304380020301290
    DOI: 10.1016/j.ecolmodel.2020.109057
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    References listed on IDEAS

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    1. Heymans, Johanna Jacomina & Coll, Marta & Link, Jason S. & Mackinson, Steven & Steenbeek, Jeroen & Walters, Carl & Christensen, Villy, 2016. "Best practice in Ecopath with Ecosim food-web models for ecosystem-based management," Ecological Modelling, Elsevier, vol. 331(C), pages 173-184.
    2. Eddelbuettel, Dirk & Francois, Romain, 2011. "Rcpp: Seamless R and C++ Integration," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i08).
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    Cited by:

    1. Whitehouse, George A. & Aydin, Kerim Y., 2020. "Assessing the sensitivity of three Alaska marine food webs to perturbations: an example of Ecosim simulations using Rpath," Ecological Modelling, Elsevier, vol. 429(C).
    2. Calhoun-Grosch, Stacy & Ruzicka, Jim J. & Robinson, Kelly L. & Wang, Verena H. & Sutton, Tracey & Ainsworth, Cameron & Hernandez, Frank, 2024. "Simulating productivity changes of epipelagic, mesopelagic, and bathypelagic taxa using a depth-resolved, end-to-end food web model for the oceanic Gulf of Mexico," Ecological Modelling, Elsevier, vol. 489(C).
    3. Heinichen, Margaret & McManus, M. Conor & Lucey, Sean M. & Aydin, Kerim & Humphries, Austin & Innes-Gold, Anne & Collie, Jeremy, 2022. "Incorporating temperature-dependent fish bioenergetics into a Narragansett Bay food web model," Ecological Modelling, Elsevier, vol. 466(C).

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