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Adding rigor to ecological network models by evaluating a set of pre-balance diagnostics: A plea for PREBAL

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  • Link, Jason S.

Abstract

The widespread use of ecological network models (e.g., Ecopath, Econetwrk, and related energy budget models) has been laudable for several reasons, chief of which is providing an easy-to-use set of modeling tools that can present an ecosystem context for improved understanding and management of living marine resources (LMR). Yet the ease-of-use of these models has led to two challenges. First, the veritable explosion of the use and application of these network models has resulted in recognition that the content and use of such models has spanned a range of quality. Second, as these models and their application have become more widespread, they are increasingly being used in a LMR management context. Thus review panels and other evaluators of these models would benefit from a set of rigorous and standard criteria from which the basis for all network models and related applications for any given system (i.e., the initial, static energy budget) can be evaluated. To this end, as one suggestion for improving network models in general, here I propose a series of pre-balance (PREBAL) diagnostics. These PREBAL diagnostics can be done, now, in simple spreadsheets before any balancing or tuning is executed. Examples of these PREBAL diagnostics include biomasses, biomass ratios, vital rates, vital rate ratios, total production, and total removals (and slopes thereof) across the taxa and trophic levels in any given energy budget. I assert that there are some general ecological and fishery principles that can be used in conjunction with PREBAL diagnostics to identify issues of model structure and data quality before balancing and dynamic applications are executed. I humbly present this PREBAL information as a simple yet general approach that could be easily implemented, could be considered for further incorporation into these model packages, and as such would ultimately result in a straightforward way to evaluate (and perhaps identify areas for improving) initial conditions in food web modeling efforts.

Suggested Citation

  • Link, Jason S., 2010. "Adding rigor to ecological network models by evaluating a set of pre-balance diagnostics: A plea for PREBAL," Ecological Modelling, Elsevier, vol. 221(12), pages 1580-1591.
  • Handle: RePEc:eee:ecomod:v:221:y:2010:i:12:p:1580-1591
    DOI: 10.1016/j.ecolmodel.2010.03.012
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    1. Link, Jason & Col, Laurel & Guida, Vincent & Dow, David & O’Reilly, John & Green, Jack & Overholtz, William & Palka, Debra & Legault, Chris & Vitaliano, Joseph & Griswold, Carolyn & Fogarty, Michael &, 2009. "Response of balanced network models to large-scale perturbation: Implications for evaluating the role of small pelagics in the Gulf of Maine," Ecological Modelling, Elsevier, vol. 220(3), pages 351-369.
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    1. Nuttall, M.A. & Jordaan, A. & Cerrato, R.M. & Frisk, M.G., 2011. "Identifying 120 years of decline in ecosystem structure and maturity of Great South Bay, New York using the Ecopath modelling approach," Ecological Modelling, Elsevier, vol. 222(18), pages 3335-3345.
    2. Alva-Basurto, Jorge Christian & Arias-González, Jesús Ernesto, 2014. "Modelling the effects of climate change on a Caribbean coral reef food web," Ecological Modelling, Elsevier, vol. 289(C), pages 1-14.
    3. Sagarese, Skyler R. & Lauretta, Matthew V. & Walter, John F., 2017. "Progress towards a next-generation fisheries ecosystem model for the northern Gulf of Mexico," Ecological Modelling, Elsevier, vol. 345(C), pages 75-98.
    4. Kearney, Kelly A. & Stock, Charles & Aydin, Kerim & Sarmiento, Jorge L., 2012. "Coupling planktonic ecosystem and fisheries food web models for a pelagic ecosystem: Description and validation for the subarctic Pacific," Ecological Modelling, Elsevier, vol. 237, pages 43-62.
    5. Booth, Shawn & Walters, William J & Steenbeek, Jeroen & Christensen, Villy & Charmasson, Sabine, 2020. "An Ecopath with Ecosim model for the Pacific coast of eastern Japan: Describing the marine environment and its fisheries prior to the Great East Japan earthquake," Ecological Modelling, Elsevier, vol. 428(C).
    6. Lassalle, Géraldine & Bourdaud, Pierre & Saint-Béat, Blanche & Rochette, Sébastien & Niquil, Nathalie, 2014. "A toolbox to evaluate data reliability for whole-ecosystem models: Application on the Bay of Biscay continental shelf food-web model," Ecological Modelling, Elsevier, vol. 285(C), pages 13-21.
    7. Lercari, Diego & Defeo, Omar & Ortega, Leonardo & Orlando, Luis & Gianelli, Ignacio & Celentano, Eleonora, 2018. "Long-term structural and functional changes driven by climate variability and fishery regimes in a sandy beach ecosystem," Ecological Modelling, Elsevier, vol. 368(C), pages 41-51.
    8. Zetina-Rejón, Manuel J. & Cabrera-Neri, Erika & López-Ibarra, Gladis A. & Arcos-Huitrón, N. Enrique & Christensen, Villy, 2015. "Trophic modeling of the continental shelf ecosystem outside of Tabasco, Mexico: A network and modularity analysis," Ecological Modelling, Elsevier, vol. 313(C), pages 314-324.
    9. Ricci, P. & Sion, L. & Capezzuto, F. & Cipriano, G. & D'Onghia, G. & Libralato, S. & Maiorano, P. & Tursi, A. & Carlucci, R., 2021. "Modelling the trophic roles of the demersal Chondrichthyes in the Northern Ionian Sea (Central Mediterranean Sea)," Ecological Modelling, Elsevier, vol. 444(C).
    10. Perryman, Holly A. & Tarnecki, Joseph H. & Grüss, Arnaud & Babcock, Elizabeth A. & Sagarese, Skyler R. & Ainsworth, Cameron H. & Gray DiLeone, Alisha M., 2020. "A revised diet matrix to improve the parameterization of a West Florida Shelf Ecopath model for understanding harmful algal bloom impacts," Ecological Modelling, Elsevier, vol. 416(C).
    11. Eddy, Tyler D. & Pitcher, Tony J. & MacDiarmid, Alison B. & Byfield, Tamsen T. & Tam, Jamie C. & Jones, Timothy T. & Bell, James J. & Gardner, Jonathan P.A., 2014. "Lobsters as keystone: Only in unfished ecosystems?," Ecological Modelling, Elsevier, vol. 275(C), pages 48-72.
    12. Yang Yuan & Jie Feng & Weiwei Xian & Hui Zhang, 2022. "Analysis of the Ecosystem Characteristics and Ecological Carrying Capacity of the Main Commercial Fish in the Artificial Reef Ecosystem in Laizhou Bay Using the Ecopath Model," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    13. Bentley, Jacob W. & Serpetti, Natalia & Heymans, Johanna Jacomina, 2017. "Investigating the potential impacts of ocean warming on the Norwegian and Barents Seas ecosystem using a time-dynamic food-web model," Ecological Modelling, Elsevier, vol. 360(C), pages 94-107.
    14. Larsen, Lars-Henrik & Sagerup, Kjetil & Ramsvatn, Silje, 2016. "The mussel path – Using the contaminant tracer, Ecotracer, in Ecopath to model the spread of pollutants in an Arctic marine food web," Ecological Modelling, Elsevier, vol. 331(C), pages 77-85.
    15. Tomczak, M.T. & Niiranen, S. & Hjerne, O. & Blenckner, T., 2012. "Ecosystem flow dynamics in the Baltic Proper—Using a multi-trophic dataset as a basis for food–web modelling," Ecological Modelling, Elsevier, vol. 230(C), pages 123-147.
    16. Ofir, E. & Gal, G. & Goren, M. & Shapiro, J. & Spanier, E., 2016. "Detecting changes to the functioning of a lake ecosystem following a regime shift based on static food-web models," Ecological Modelling, Elsevier, vol. 320(C), pages 145-157.
    17. 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.
    18. Byron, Carrie & Link, Jason & Costa-Pierce, Barry & Bengtson, David, 2011. "Calculating ecological carrying capacity of shellfish aquaculture using mass-balance modeling: Narragansett Bay, Rhode Island," Ecological Modelling, Elsevier, vol. 222(10), pages 1743-1755.
    19. Fourriére, Manon & Alvarado, Juan José & Cortés, Jorge & Taylor, Marc H. & Ayala-Bocos, Arturo & Azofeifa-Solano, Juan Carlos & Arauz, Randall & Heidemeyer, Maike & López-Garro, Andrés & Zanella, Ilen, 2019. "Energy flow structure and role of keystone groups in shallow water environments in Isla del Coco, Costa Rica, Eastern Tropical Pacific," Ecological Modelling, Elsevier, vol. 396(C), pages 74-85.
    20. Gray DiLeone, A.M. & Ainsworth, C.H., 2019. "Effects of Karenia brevis harmful algal blooms on fish community structure on the West Florida Shelf," Ecological Modelling, Elsevier, vol. 392(C), pages 250-267.
    21. Bueno-Pardo, Juan & García-Seoane, Eva & Sousa, Ana I. & Coelho, João P. & Morgado, Mariana & Frankenbach, Silja & Ezequiel, João & Vaz, Nuno & Quintino, Victor & Rodrigues, Ana M. & Leandro, Sérgio &, 2018. "Trophic web structure and ecosystem attributes of a temperate coastal lagoon (Ria de Aveiro, Portugal)," Ecological Modelling, Elsevier, vol. 378(C), pages 13-25.
    22. Natugonza, Vianny & Ogutu-Ohwayo, Richard & Musinguzi, Laban & Kashindye, Benedicto & Jónsson, Steingrímur & Valtysson, Hreidar Thor, 2016. "Exploring the structural and functional properties of the Lake Victoria food web, and the role of fisheries, using a mass balance model," Ecological Modelling, Elsevier, vol. 342(C), pages 161-174.
    23. Buchheister, Andre & Wilberg, Michael J. & Miller, Thomas J. & Latour, Robert J., 2015. "Simulating bottom-up effects on predator productivity and consequences for the rebuilding timeline of a depleted population," Ecological Modelling, Elsevier, vol. 311(C), pages 48-62.

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