IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v443y2021ics0304380021000314.html
   My bibliography  Save this article

A simple modelling tool for assessing interaction with host and local infestation of sea lice from salmonid farms on wild salmonids based on processes operating at multiple scales in space and time

Author

Listed:
  • Murray, Alexander G
  • Moriarty, Meadhbh

Abstract

Sea lice are marine ectoparasitic crustacea which limit the potential for sustainable salmon aquaculture due to risks of impacts on iconic wild salmon and sea trout. Control of the parasite on farms costs an estimated 9% of farm revenue. Sea lice develop through planktonic nauplii to copepodid stages which attach to, and mature on, salmonid hosts until females become ovigerous (egg laying) Impacts of lice on wild fish depend on their exposure to planktonic larval lice transported from salmon farms, which consists of (A) production of larval lice from ovigerous female lice on salmon farms, (B) local concentrations of planktonic larval lice infectious copepodids in adjacent waters, (C) rates of infestation of wild fish given these concentrations, and (D) impact on fish given this level of interaction. A model of this local exposure around salmon farms was developed. Production rates for nauplii as a function of the numbers of adult lice on salmon farms and maturation to copepodids (A) is well studied, as are impacts of infestation (D), with >0.75 lice per gram of host fish considered to present a high risk of mortality. Using existing assessments of infectious copepodid production (A) we develop a model of copepodid concentration (B) based on a simple kernel of copepodid distribution around farms; within this kernel the copepodids are assumed either to disperse evenly or to be transported in a concentrated plume, allowing comparison of the range of different concentration distributions. These distributions combine with a model of infestation (C) based on small-scale movements of copepodids in the immediate vicinity of a swimming fish. Fish swimming at intermediate velocities are most susceptible to infestation, as slow fish exhaust lice in their immediate vicinity while fast fish move on before lice copepodids can approach. These models are combined to create an assessment of the risk that concentrations can result in infestation of fish at levels considered to cause mortalities (D). The results can be used in combination with empirical assessments as a tool to link potential impacts on wild salmonids to aquaculture biomass and on-farm lice management in different environments in support of strategic aquaculture planning. Our modelling demonstrates the, often neglected, importance of fine-scale processes in sea lice infestation of salmonids.

Suggested Citation

  • Murray, Alexander G & Moriarty, Meadhbh, 2021. "A simple modelling tool for assessing interaction with host and local infestation of sea lice from salmonid farms on wild salmonids based on processes operating at multiple scales in space and time," Ecological Modelling, Elsevier, vol. 443(C).
    • Handle: RePEc:eee:ecomod:v:443:y:2021:i:c:s0304380021000314
    DOI: 10.1016/j.ecolmodel.2021.109459
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380021000314
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2021.109459?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. Friederike Ziegler & Ulf Winther & Erik Skontorp Hognes & Andreas Emanuelsson & Veronica Sund & Harald Ellingsen, 2013. "The Carbon Footprint of Norwegian Seafood Products on the Global Seafood Market," Journal of Industrial Ecology, Yale University, vol. 17(1), pages 103-116, February.
    2. Murray, Alexander G. & Salama, Nabeil K.G., 2016. "A simple model of the role of area management in the control of sea lice," Ecological Modelling, Elsevier, vol. 337(C), pages 39-47.
    3. Jay Abolofia & Frank Asche & James E. Wilen, 2017. "The Cost of Lice: Quantifying the Impacts of Parasitic Sea Lice on Farmed Salmon," Marine Resource Economics, University of Chicago Press, vol. 32(3), pages 329-349.
    Full references (including those not matched with items on IDEAS)

    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. Gaspard Philis & Friederike Ziegler & Mona Dverdal Jansen & Lars Christian Gansel & Sara Hornborg & Grete Hansen Aas & Anne Stene, 2022. "Quantifying environmental impacts of cleaner fish used as sea lice treatments in salmon aquaculture with life cycle assessment," Journal of Industrial Ecology, Yale University, vol. 26(6), pages 1992-2005, December.
    2. Teea Kortetmäki & Markku Oksanen, 2021. "Is there a convincing case for climate veganism?," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(3), pages 729-740, September.
    3. Jesse Sherry & Jennifer Koester, 2020. "Life Cycle Assessment of Aquaculture Stewardship Council Certified Atlantic Salmon ( Salmo salar )," Sustainability, MDPI, vol. 12(15), pages 1-15, July.
    4. Vázquez-Rowe, Ian & Villanueva-Rey, Pedro & Moreira, Mª Teresa & Feijoo, Gumersindo, 2013. "The role of consumer purchase and post-purchase decision-making in sustainable seafood consumption. A Spanish case study using carbon footprinting," Food Policy, Elsevier, vol. 41(C), pages 94-102.
    5. Gaspard Philis & Friederike Ziegler & Lars Christian Gansel & Mona Dverdal Jansen & Erik Olav Gracey & Anne Stene, 2019. "Comparing Life Cycle Assessment (LCA) of Salmonid Aquaculture Production Systems: Status and Perspectives," Sustainability, MDPI, vol. 11(9), pages 1-27, April.
    6. Giovanni Codotto & Massimo Pizzol & Troels J. Hegland & Niels Madsen, 2024. "Model uncertainty versus variability in the life cycle assessment of commercial fisheries," Journal of Industrial Ecology, Yale University, vol. 28(1), pages 160-172, February.
    7. McGarraghy, Seán & Olafsdottir, Gudrun & Kazakov, Rossen & Huber, Élise & Loveluck, William & Gudbrandsdottir, Ingunn Y. & Čechura, Lukáš & Esposito, Gianandrea & Samoggia, Antonella & Aubert, Pierre-, 2022. "Conceptual system dynamics and agent-based modelling simulation of interorganisational fairness in food value chains: Research agenda and case studies," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 12(2).
    8. Chen, Xianwen & Alfnes , Frode & Rickertsen , Kyrre, 2015. "Labeling Farmed Seafood," Working Paper Series 10-2015, Norwegian University of Life Sciences, School of Economics and Business.
    9. Bronnmann, Julia & Asche, Frank, 2017. "Sustainable Seafood From Aquaculture and Wild Fisheries: Insights From a Discrete Choice Experiment in Germany," Ecological Economics, Elsevier, vol. 142(C), pages 113-119.
    10. Seán McGarraghy & Gudrun Olafsdottir & Rossen Kazakov & Élise Huber & William Loveluck & Ingunn Y. Gudbrandsdottir & Lukáš Čechura & Gianandrea Esposito & Antonella Samoggia & Pierre-Marie Aubert & Da, 2022. "Conceptual System Dynamics and Agent-Based Modelling Simulation of Interorganisational Fairness in Food Value Chains: Research Agenda and Case Studies," Agriculture, MDPI, vol. 12(2), pages 1-30, February.
    11. Oglend, Atle & Asche, Frank & Straume, Hans-Martin, 2024. "Rent formation and distortions due to quotas in biological production processes," Resource and Energy Economics, Elsevier, vol. 77(C).
    12. Ingunn Y. Gudbrandsdottir & Nína M. Saviolidis & Gudrun Olafsdottir & Gudmundur V. Oddsson & Hlynur Stefansson & Sigurdur G. Bogason, 2021. "Transition Pathways for the Farmed Salmon Value Chain: Industry Perspectives and Sustainability Implications," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    13. Haarstad, Aleksander H. & Lavrutich, Maria & Strypet, Kristian & Strøm, Eivind, 2022. "Multi-commodity price risk hedging in the Atlantic salmon farming industry," Journal of Commodity Markets, Elsevier, vol. 25(C).
    14. Antonio Cortés & Sara González‐García & Amaya Franco‐Uría & Maria Teresa Moreira & Gumersindo Feijoo, 2022. "Evaluation of the environmental sustainability of the inshore great scallop (Pecten maximus) fishery in Galicia," Journal of Industrial Ecology, Yale University, vol. 26(6), pages 1920-1933, December.
    15. Asche, Frank & Smith, Martin D., 2018. "Viewpoint: Induced Innovation in Fisheries and Aquaculture," Food Policy, Elsevier, vol. 76(C), pages 1-7.
    16. Botterell, Zara L.R. & Lindeque, Penelope K. & Thompson, Richard C. & Beaumont, Nicola J., 2023. "An assessment of the ecosystem services of marine zooplankton and the key threats to their provision," Ecosystem Services, Elsevier, vol. 63(C).
    17. Friederike Ziegler & Sepideh Jafarzadeh & Erik Skontorp Hognes & Ulf Winther, 2022. "Greenhouse gas emissions of Norwegian seafoods: From comprehensive to simplified assessment," Journal of Industrial Ecology, Yale University, vol. 26(6), pages 1908-1919, December.
    18. Standal, Dag & Annie Sønvisen, Signe, 2015. "Gear liberalization in the Northeast Arctic cod fisheries – Implications for sustainability, efficiency and legitimacy," Marine Policy, Elsevier, vol. 53(C), pages 141-148.
    19. Onozaka, Yuko & Honkanen, Pirjo & Altintzoglou, Themistoklis, 2023. "Sustainability, perceived quality and country of origin of farmed salmon: Impact on consumer choices in the USA, France and Japan," Food Policy, Elsevier, vol. 117(C).
    20. Aldrin, M. & Huseby, R.B. & Stien, A. & Grøntvedt, R.N. & Viljugrein, H. & Jansen, P.A., 2017. "A stage-structured Bayesian hierarchical model for salmon lice populations at individual salmon farms – Estimated from multiple farm data sets," Ecological Modelling, Elsevier, vol. 359(C), pages 333-348.

    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:443:y:2021:i:c:s0304380021000314. 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.