IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v335y2016icp87-100.html
   My bibliography  Save this article

Developing a high taxonomic resolution food web model to assess the functional role of forage fish in the California Current ecosystem

Author

Listed:
  • Koehn, Laura E.
  • Essington, Timothy E.
  • Marshall, Kristin N.
  • Kaplan, Isaac C.
  • Sydeman, William J.
  • Szoboszlai, Amber I.
  • Thayer, Julie A.

Abstract

Understanding the role of forage fish in marine food webs is an important part of ecosystem-based fisheries management. Food web models are a common tool used to account for important characteristics of forage fish and their trophodynamics. One primary limitation of many existing food web models is that the taxonomic resolution of forage fish and their predators is overly simplified. Here, we developed a food web model with high taxonomic resolution of forage fish and their predators in the California Current to more comprehensively describe trophic linkages involving forage fish and examine the ecological role of forage fish in this system. We parameterized a mass-balanced food web model (Ecopath) with 92 living functional groups, and used this to quantify diet dependency on forage fish, determine the main predators of forage fish, identify the topological position of forage fish in the food web, and calculate an index that identifies forage species or species aggregations that have key ecological roles (Supportive Role to Fishery ecosystem, SURF). Throughout, we characterized parameter uncertainty using a Monte Carlo approach. Though diets revealed some predators had high diet dependencies on individual forage fish species, most predators consumed multiple forage fish and also had notable diet overlap with forage fish. Consequently, no single forage fish appeared to act as a vital nexus species that is characteristic of “wasp-waisted” food webs in other upwelling regions. Additionally, no single forage fish was identified as “key” by the SURF index, but if predators and fisheries view certain pairs of forage fish as functionally equivalent, some plausible pairs would be identified as key assemblages. Specifically, sardine & anchovy (Sardinops sagax &Engraulis mordax) and herring & anchovy (Clupea pallasii &E. mordax) are key when predator populations depend on the aggregate availability of these species. This food web model can be used to support generalized equilibrium trade-off analysis or dynamic modeling to identify specific predators that would be of conservation concern under conditions of future forage fish depletion.

Suggested Citation

  • Koehn, Laura E. & Essington, Timothy E. & Marshall, Kristin N. & Kaplan, Isaac C. & Sydeman, William J. & Szoboszlai, Amber I. & Thayer, Julie A., 2016. "Developing a high taxonomic resolution food web model to assess the functional role of forage fish in the California Current ecosystem," Ecological Modelling, Elsevier, vol. 335(C), pages 87-100.
    • Handle: RePEc:eee:ecomod:v:335:y:2016:i:c:p:87-100
    DOI: 10.1016/j.ecolmodel.2016.05.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380016301909
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2016.05.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Elizabeth A Fulton & Anthony D M Smith & David C Smith & Penelope Johnson, 2014. "An Integrated Approach Is Needed for Ecosystem Based Fisheries Management: Insights from Ecosystem-Level Management Strategy Evaluation," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-16, January.
    2. B. A. Block & I. D. Jonsen & S. J. Jorgensen & A. J. Winship & S. A. Shaffer & S. J. Bograd & E. L. Hazen & D. G. Foley & G. A. Breed & A.-L. Harrison & J. E. Ganong & A. Swithenbank & M. Castleton & , 2011. "Tracking apex marine predator movements in a dynamic ocean," Nature, Nature, vol. 475(7354), pages 86-90, July.
    3. S. Lewis & T. N. Sherratt & K. C. Hamer & S. Wanless, 2001. "Evidence of intra-specific competition for food in a pelagic seabird," Nature, Nature, vol. 412(6849), pages 816-819, August.
    4. Martin, Andrew D. & Quinn, Kevin M. & Park, Jong Hee, 2011. "MCMCpack: Markov Chain Monte Carlo in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i09).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Walters, Carl & Christensen, Villy, 2019. "Effect of non-additivity in mortality rates on predictions of potential yield of forage fishes," Ecological Modelling, Elsevier, vol. 410(C), pages 1-1.
    2. 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).
    3. 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).
    4. Punt, André E. & MacCall, Alec D. & Essington, Timothy E. & Francis, Tessa B. & Hurtado-Ferro, Felipe & Johnson, Kelli F. & Kaplan, Isaac C. & Koehn, Laura E. & Levin, Phillip S. & Sydeman, William J., 2016. "Exploring the implications of the harvest control rule for Pacific sardine, accounting for predator dynamics: A MICE model," Ecological Modelling, Elsevier, vol. 337(C), pages 79-95.
    5. Goedegebuure, Merel & Melbourne-Thomas, Jessica & Corney, Stuart P. & Hindell, Mark A. & Constable, Andrew J., 2017. "Beyond big fish: The case for more detailed representations of top predators in marine ecosystem models," Ecological Modelling, Elsevier, vol. 359(C), pages 182-192.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hengtao Zhang & Guosheng Yin, 2021. "Response‐adaptive rerandomization," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1281-1298, November.
    2. Andrew Gelman & Daniel Lee & Jiqiang Guo, 2015. "Stan," Journal of Educational and Behavioral Statistics, , vol. 40(5), pages 530-543, October.
    3. Brias, Antoine & Munch, Stephan B., 2021. "Ecosystem based multi-species management using Empirical Dynamic Programming," Ecological Modelling, Elsevier, vol. 441(C).
    4. Zuoxian Gan & Tao Feng & Min Yang, 2018. "Exploring the Effects of Car Ownership and Commuting on Subjective Well-Being: A Nationwide Questionnaire Study," Sustainability, MDPI, vol. 11(1), pages 1-20, December.
    5. Crow White & Christopher Costello, 2014. "Close the High Seas to Fishing?," PLOS Biology, Public Library of Science, vol. 12(3), pages 1-5, March.
    6. Antonio Parisi & B. Liseo, 2018. "Objective Bayesian analysis for the multivariate skew-t model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 277-295, June.
    7. Bakar, Khandoker Shuvo & Sahu, Sujit K., 2015. "spTimer: Spatio-Temporal Bayesian Modeling Using R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i15).
    8. Baştürk, Nalan & Grassi, Stefano & Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2017. "The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i01).
    9. White, Robin R. & Brady, Michael, 2014. "Can consumers’ willingness to pay incentivize adoption of environmental impact reducing technologies in meat animal production?," Food Policy, Elsevier, vol. 49(P1), pages 41-49.
    10. Xin Fang & Bo Fang & Chunfang Wang & Tian Xia & Matteo Bottai & Fang Fang & Yang Cao, 2019. "Comparison of Frequentist and Bayesian Generalized Additive Models for Assessing the Association between Daily Exposure to Fine Particles and Respiratory Mortality: A Simulation Study," IJERPH, MDPI, vol. 16(5), pages 1-20, March.
    11. Ji, Yonggang & Lin, Nan & Zhang, Baoxue, 2012. "Model selection in binary and tobit quantile regression using the Gibbs sampler," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 827-839.
    12. Schaarschmidt, Frank & Gerhard, Daniel & Vogel, Charlotte, 2017. "Simultaneous confidence intervals for comparisons of several multinomial samples," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 65-76.
    13. Eijffinger, Sylvester & Mahieu, Ronald & Raes, Louis, 2018. "Inferring hawks and doves from voting records," European Journal of Political Economy, Elsevier, vol. 51(C), pages 107-120.
    14. Camilo Duque Londono & Seth F. Cones & Jue Deng & Jingjing Wu & Hyunwoo Yuk & David E. Guza & T. Aran Mooney & Xuanhe Zhao, 2024. "Bioadhesive interface for marine sensors on diverse soft fragile species," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    15. Rujia Bi & Can Zhou & Yan Jiao, 2020. "Detection of fish movement patterns across management unit boundaries using age-structured Bayesian hierarchical models with tag-recovery data," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-21, December.
    16. Martin Hernani Merino & Enver Gerald Tarazona Vargas & Antonieta Hamann Pastorino & José Afonso Mazzon, 2014. "Validation of Sustainable Development Practices Scale Using the Bayesian Approach to Item Response Theory," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 26(2), pages 147-162.
    17. repec:jss:jstsof:39:i12 is not listed on IDEAS
    18. Emmanuel Mensaklo & Chukiat Chaiboonsri & Kanchana Chokethaworn & Songsak Sriboonchitta, 2023. "Comparing Classical and Bayesian Panel Kink Regression Frameworks in Estimating the Impact of Economic Freedom on Economic Growth," Economies, MDPI, vol. 11(10), pages 1-24, October.
    19. Daniel W. Hill Jr., 2016. "Avoiding Obligation," Journal of Conflict Resolution, Peace Science Society (International), vol. 60(6), pages 1129-1158, September.
    20. Marisol Valencia Cárdenas & Juan Gabriel Vanegas López & Juan Carlos Correa Morales & Jorge Aníbal Restrepo Morales, 2017. "Comparing forecasts for tourism dynamics in Medellín, Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 199-230, Enero - J.
    21. Mason Dyana P., 2017. "Measuring Latent Constructs in Nonprofit Surveys with Item Response Theory: The Example of Political Ideology," Nonprofit Policy Forum, De Gruyter, vol. 8(1), pages 91-110, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:335:y:2016:i:c:p:87-100. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.