IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v492y2024ics0304380024000929.html
   My bibliography  Save this article

Exploring ecosystem effects of underwater noise in the nordic seas, using the NoBa-Atlantis E2E model

Author

Listed:
  • Skartsæterhagen, Maria
  • Hansen, Cecilie
  • Fulton, Elizabeth A.

Abstract

Underwater noise generated by human activities, such as shipping and seismic surveys, has emerged as a growing concern. Despite the mounting evidence that noise negatively impacts marine mammals, fish, and invertebrates, end-to-end ecosystem models often overlook noise as a stressor. This omission is due to the complexity of studying noise’s influence on entire populations and ecosystems, making it difficult to gauge the potential total effects accurately. In this study, we implemented potential effects of underwater noise in the Atlantis ecosystem modeling framework. Noise effects on organisms were simulated through reduced growth and consumption rates, increased mortality and movement away from noisy areas. The noise module was tested by a Morris sensitivity analysis on most of the fish, mammal and invertebrate species in the model. The species were aggregated into 12 groups perturbed with six different noise levels, with the spatial dimension taken into account by repeating the analysis under varying spatial configurations. The results revealed substantial systemic effects from increased vulnerability to noise from zooplankton, while marine mammal noise vulnerability had relatively little impact, in line with earlier Atlantis studies. Additionally, the coastal area exhibited significantly higher biomass variability, indicating a need for more research in this region where noise is expected to increase the most. These results provide an initial estimation of the potential effects of noise at the ecosystem level in the Nordic and Barents Seas. However, for improved realism of the noise module in future studies, we emphasize the need to develop response functions for each species’ sensitivity to noise. Understanding such species-specific sensitivities will be crucial in devising effective strategies to mitigate the detrimental consequences of underwater noise on marine ecosystems.

Suggested Citation

  • Skartsæterhagen, Maria & Hansen, Cecilie & Fulton, Elizabeth A., 2024. "Exploring ecosystem effects of underwater noise in the nordic seas, using the NoBa-Atlantis E2E model," Ecological Modelling, Elsevier, vol. 492(C).
  • Handle: RePEc:eee:ecomod:v:492:y:2024:i:c:s0304380024000929
    DOI: 10.1016/j.ecolmodel.2024.110704
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380024000929
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2024.110704?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. Ortega-Cisneros, Kelly & Cochrane, Kevern & Fulton, Elizabeth A., 2017. "An Atlantis model of the southern Benguela upwelling system: Validation, sensitivity analysis and insights into ecosystem functioning," Ecological Modelling, Elsevier, vol. 355(C), pages 49-63.
    2. Ihde, Thomas F. & Townsend, Howard M., 2017. "Accounting for multiple stressors influencing living marine resources in a complex estuarine ecosystem using an Atlantis model," Ecological Modelling, Elsevier, vol. 365(C), pages 1-9.
    3. Bracis, Chloe & Lehuta, Sigrid & Savina-Rolland, Marie & Travers-Trolet, Morgane & Girardin, Raphaël, 2020. "Improving confidence in complex ecosystem models: The sensitivity analysis of an Atlantis ecosystem model," Ecological Modelling, Elsevier, vol. 431(C).
    4. Nye, Janet A. & Gamble, Robert J. & Link, Jason S., 2013. "The relative impact of warming and removing top predators on the Northeast US large marine biotic community," Ecological Modelling, Elsevier, vol. 264(C), pages 157-168.
    5. Travers, M. & Shin, Y.-J. & Jennings, S. & Machu, E. & Huggett, J.A. & Field, J.G. & Cury, P.M., 2009. "Two-way coupling versus one-way forcing of plankton and fish models to predict ecosystem changes in the Benguela," Ecological Modelling, Elsevier, vol. 220(21), pages 3089-3099.
    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. Bracis, Chloe & Lehuta, Sigrid & Savina-Rolland, Marie & Travers-Trolet, Morgane & Girardin, Raphaël, 2020. "Improving confidence in complex ecosystem models: The sensitivity analysis of an Atlantis ecosystem model," Ecological Modelling, Elsevier, vol. 431(C).
    2. Lopez de Gamiz-Zearra, A. & Hansen, C. & Corrales, X. & Andonegi, E., 2024. "Increasing the reliability of the Bay of Biscay Atlantis model: A sensitivity analysis to parameters perturbations using a Morris screening approach," Ecological Modelling, Elsevier, vol. 488(C).
    3. Caracappa, Joseph C. & Beet, Andrew & Gaichas, Sarah & Gamble, Robert J. & Hyde, Kimberly J.W. & Large, Scott I. & Morse, Ryan E. & Stock, Charles A. & Saba, Vincent S., 2022. "A northeast United States Atlantis marine ecosystem model with ocean reanalysis and ocean color forcing," Ecological Modelling, Elsevier, vol. 471(C).
    4. Perryman, Holly A. & Kaplan, Isaac C. & Blanchard, Julia L. & Fay, Gavin & Gaichas, Sarah K. & McGregor, Vidette L. & Morzaria-Luna, Hem Nalini & Porobic, Javier & Townsend, Howard & Fulton, Elizabeth, 2023. "Atlantis Ecosystem Model Summit 2022: Report from a workshop," Ecological Modelling, Elsevier, vol. 483(C).
    5. Xing, Lei & Zhang, Chongliang & Chen, Yong & Shin, Yunne-Jai & Verley, Philippe & Yu, Haiqing & Ren, Yiping, 2017. "An individual-based model for simulating the ecosystem dynamics of Jiaozhou Bay, China," Ecological Modelling, Elsevier, vol. 360(C), pages 120-131.
    6. Maar, Marie & Butenschön, Momme & Daewel, Ute & Eggert, Anja & Fan, Wei & Hjøllo, Solfrid S. & Hufnagl, Marc & Huret, Martin & Ji, Rubao & Lacroix, Geneviève & Peck, Myron A. & Radtke, Hagen & Sailley, 2018. "Responses of summer phytoplankton biomass to changes in top-down forcing: Insights from comparative modelling," Ecological Modelling, Elsevier, vol. 376(C), pages 54-67.
    7. Libralato, Simone & Solidoro, Cosimo, 2009. "Bridging biogeochemical and food web models for an End-to-End representation of marine ecosystem dynamics: The Venice lagoon case study," Ecological Modelling, Elsevier, vol. 220(21), pages 2960-2971.
    8. Travers-Trolet, Morgane & Coppin, Franck & Cresson, Pierre & Cugier, Philippe & Oliveros-Ramos, Ricardo & Verley, Philippe, 2019. "Emergence of negative trophic level-size relationships from a size-based, individual-based multispecies fish model," Ecological Modelling, Elsevier, vol. 410(C), pages 1-1.
    9. Fay, Gavin & Link, Jason S. & Hare, Jonathan A., 2017. "Assessing the effects of ocean acidification in the Northeast US using an end-to-end marine ecosystem model," Ecological Modelling, Elsevier, vol. 347(C), pages 1-10.
    10. Fu, Caihong & Travers-Trolet, Morgane & Velez, Laure & Grüss, Arnaud & Bundy, Alida & Shannon, Lynne J. & Fulton, Elizabeth A. & Akoglu, Ekin & Houle, Jennifer E. & Coll, Marta & Verley, Philippe & He, 2018. "Risky business: The combined effects of fishing and changes in primary productivity on fish communities," Ecological Modelling, Elsevier, vol. 368(C), pages 265-276.
    11. Duboz, Raphaël & Versmisse, David & Travers, Morgane & Ramat, Eric & Shin, Yunne-Jai, 2010. "Application of an evolutionary algorithm to the inverse parameter estimation of an individual-based model," Ecological Modelling, Elsevier, vol. 221(5), pages 840-849.
    12. Kumar, Vijay & Kumari, Beena, 2015. "Mathematical modelling of the seasonal variability of plankton and forage fish in the Gulf of Kachchh," Ecological Modelling, Elsevier, vol. 313(C), pages 237-250.
    13. Hood, Raleigh R. & Shenk, Gary W. & Dixon, Rachel L. & Smith, Sean M.C. & Ball, William P. & Bash, Jesse O. & Batiuk, Rich & Boomer, Kathy & Brady, Damian C. & Cerco, Carl & Claggett, Peter & de Mutse, 2021. "The Chesapeake Bay program modeling system: Overview and recommendations for future development," Ecological Modelling, Elsevier, vol. 456(C).
    14. Grüss, Arnaud & Palomares, Maria L.D. & Poelen, Jorrit H. & Barile, Josephine R. & Aldemita, Casey D. & Ortiz, Shelumiel R. & Barrier, Nicolas & Shin, Yunne-Jai & Simons, James & Pauly, Daniel, 2019. "Building bridges between global information systems on marine organisms and ecosystem models," Ecological Modelling, Elsevier, vol. 398(C), pages 1-19.
    15. Oladayo Amed Idris & Prosper Opute & Israel Ropo Orimoloye & Mark Steve Maboeta, 2022. "Climate Change in Africa and Vegetation Response: A Bibliometric and Spatially Based Information Assessment," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    16. Diaz, Frédéric & Bănaru, Daniela & Verley, Philippe & Shin, Yunne-Jai, 2019. "Implementation of an end-to-end model of the Gulf of Lions ecosystem (NW Mediterranean Sea). II. Investigating the effects of high trophic levels on nutrients and plankton dynamics and associated feed," Ecological Modelling, Elsevier, vol. 405(C), pages 51-68.
    17. Bănaru, Daniela & Diaz, Fréderic & Verley, Philippe & Campbell, Rose & Navarro, Jonathan & Yohia, Christophe & Oliveros-Ramos, Ricardo & Mellon-Duval, Capucine & Shin, Yunne-Jai, 2019. "Implementation of an end-to-end model of the Gulf of Lions ecosystem (NW Mediterranean Sea). I. Parameterization, calibration and evaluation," Ecological Modelling, Elsevier, vol. 401(C), pages 1-19.
    18. Planque, Benjamin & Aarflot, Johanna M. & Buttay, Lucie & Carroll, JoLynn & Fransner, Filippa & Hansen, Cecilie & Husson, Bérengère & Langangen, Øystein & Lindstrøm, Ulf & Pedersen, Torstein & Primice, 2022. "A standard protocol for describing the evaluation of ecological models," Ecological Modelling, Elsevier, vol. 471(C).
    19. Hill Cruz, Mariana & Frenger, Ivy & Getzlaff, Julia & Kriest, Iris & Xue, Tianfei & Shin, Yunne-Jai, 2022. "Understanding the drivers of fish variability in an end-to-end model of the Northern Humboldt Current System," Ecological Modelling, Elsevier, vol. 472(C).
    20. Halouani, Ghassen & Ben Rais Lasram, Frida & Shin, Yunne-Jai & Velez, Laure & Verley, Philippe & Hattab, Tarek & Oliveros-Ramos, Ricardo & Diaz, Frédéric & Ménard, Frédéric & Baklouti, Melika & Guyenn, 2016. "Modelling food web structure using an end-to-end approach in the coastal ecosystem of the Gulf of Gabes (Tunisia)," Ecological Modelling, Elsevier, vol. 339(C), pages 45-57.

    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:492:y:2024:i:c:s0304380024000929. 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.