IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v481y2023ics0304380023000868.html
   My bibliography  Save this article

Modelling the spatial shifts of functional groups in the Barents Sea using a climate-driven spatial food web model

Author

Listed:
  • Nascimento, Marcela C.
  • Husson, Berengere
  • Guillet, Lilia
  • Pedersen, Torstein

Abstract

We built a dynamic, spatial food web model for the Barents Sea, developed with Ecospace by including species’ habitat requirements and ecological interactions. The model was used to test the spatial shifts of different functional groups due to warming. We compared model-predicted and field-surveyed biomass of functional groups (FGs) spatial distributions in relatively cold and warm years. The Ecospace model included habitat foraging capacities for environmental parameters such as water temperature and bottom depth for 74 FGs out of a total of 108 FGs. We created two plausible scenarios, one representing a relatively cold year (2004) and another representing a warm year (2013) with differences of ca. 0.3 °C in bottom temperature, 0.6 °C in surface temperature, and 7% less ice coverage between them. Comparison of centre of gravity, inertia, and spatial overlap of the modelled and surveyed spatial distributions in warm and cold years showed that the model represented the past distributions of the functional groups satisfactorily. We observed poleward shifts of 41 and 68 km for the modelled and observed distributions, respectively, in the average centre of gravity position for the 35 FGs with lowest sampling uncertainty. The model predicted that the whole community had shifted distribution towards the northeast at an average rate of 4.4 km year−1 and 67 km °C-1 between 2004 and 2013. We conclude that our Ecospace model represents past observed species distributions in the Barents Sea satisfactorily, and may predict the direction and magnitude of temperature-driven changes in spatial distributions. This ability may be useful for predicting the impact of climate changes on species and FG distributions in future scenarios.

Suggested Citation

  • Nascimento, Marcela C. & Husson, Berengere & Guillet, Lilia & Pedersen, Torstein, 2023. "Modelling the spatial shifts of functional groups in the Barents Sea using a climate-driven spatial food web model," Ecological Modelling, Elsevier, vol. 481(C).
  • Handle: RePEc:eee:ecomod:v:481:y:2023:i:c:s0304380023000868
    DOI: 10.1016/j.ecolmodel.2023.110358
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380023000868
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2023.110358?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. Coll, M. & Pennino, M. Grazia & Steenbeek, J. & Sole, J. & Bellido, J.M., 2019. "Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches," Ecological Modelling, Elsevier, vol. 405(C), pages 86-101.
    2. Cribari-Neto, Francisco & Zeileis, Achim, 2010. "Beta Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i02).
    3. Püts, Miriam & Taylor, Marc & Núñez-Riboni, Ismael & Steenbeek, Jeroen & Stäbler, Moritz & Möllmann, Christian & Kempf, Alexander, 2020. "Insights on integrating habitat preferences in process-oriented ecological models – a case study of the southern North Sea," Ecological Modelling, Elsevier, vol. 431(C).
    4. Maria Fossheim & Raul Primicerio & Edda Johannesen & Randi B. Ingvaldsen & Michaela M. Aschan & Andrey V. Dolgov, 2015. "Recent warming leads to a rapid borealization of fish communities in the Arctic," Nature Climate Change, Nature, vol. 5(7), pages 673-677, July.
    5. Marie Laure Delignette-Muller & Christophe Dutang, 2015. "fitdistrplus : An R Package for Fitting Distributions," Post-Print hal-01616147, HAL.
    6. Romagnoni, Giovanni & Mackinson, Steven & Hong, Jiang & Eikeset, Anne Maria, 2015. "The Ecospace model applied to the North Sea: Evaluating spatial predictions with fish biomass and fishing effort data," Ecological Modelling, Elsevier, vol. 300(C), pages 50-60.
    7. Delignette-Muller, Marie Laure & Dutang, Christophe, 2015. "fitdistrplus: An R Package for Fitting Distributions," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i04).
    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. Schulte, Benedikt & Sachs, Anna-Lena, 2020. "The price-setting newsvendor with Poisson demand," European Journal of Operational Research, Elsevier, vol. 283(1), pages 125-137.
    2. Chen, Shang & He, Liang & Cao, Yinxuan & Wang, Runhong & Wu, Lianhai & Wang, Zhao & Zou, Yufeng & Siddique, Kadambot H.M. & Xiong, Wei & Liu, Manshuang & Feng, Hao & Yu, Qiang & Wang, Xiaoming & He, J, 2021. "Comparisons among four different upscaling strategies for cultivar genetic parameters in rainfed spring wheat phenology simulations with the DSSAT-CERES-Wheat model," Agricultural Water Management, Elsevier, vol. 258(C).
    3. Riva-Palacio, Alan & Leisen, Fabrizio, 2021. "Compound vectors of subordinators and their associated positive Lévy copulas," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    4. Minji Lee & Sun Ju Chung & Youngjo Lee & Sera Park & Jun-Gun Kwon & Dai Jin Kim & Donghwan Lee & Jung-Seok Choi, 2020. "Investigation of Correlated Internet and Smartphone Addiction in Adolescents: Copula Regression Analysis," IJERPH, MDPI, vol. 17(16), pages 1-12, August.
    5. Phillip M. Gurman & Tom Ross & Andreas Kiermeier, 2018. "Quantitative Microbial Risk Assessment of Salmonellosis from the Consumption of Australian Pork: Minced Meat from Retail to Burgers Prepared and Consumed at Home," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2625-2645, December.
    6. Sarra Ghaddab & Manel Kacem & Christian Peretti & Lotfi Belkacem, 2023. "Extreme severity modeling using a GLM-GPD combination: application to an excess of loss reinsurance treaty," Empirical Economics, Springer, vol. 65(3), pages 1105-1127, September.
    7. Kalanka P. Jayalath, 2021. "Fiducial Inference on the Right Censored Birnbaum–Saunders Data via Gibbs Sampler," Stats, MDPI, vol. 4(2), pages 1-15, May.
    8. Zubillaga, María & Skewes, Oscar & Soto, Nicolás & Rabinovich, Jorge E., 2018. "How density-dependence and climate affect guanaco population dynamics," Ecological Modelling, Elsevier, vol. 385(C), pages 189-196.
    9. Nielsen, J.K. & Mueter, F.J. & Adkison, M.D. & Loher, T. & McDermott, S.F. & Seitz, A.C., 2019. "Effect of study area bathymetric heterogeneity on parameterization and performance of a depth-based geolocation model for demersal fishes," Ecological Modelling, Elsevier, vol. 402(C), pages 18-34.
    10. Antonello Maruotti & Antonio Punzo, 2021. "Initialization of Hidden Markov and Semi‐Markov Models: A Critical Evaluation of Several Strategies," International Statistical Review, International Statistical Institute, vol. 89(3), pages 447-480, December.
    11. Taleb-Berrouane, Mohammed & Khan, Faisal & Amyotte, Paul, 2020. "Bayesian Stochastic Petri Nets (BSPN) - A new modelling tool for dynamic safety and reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    12. Fezzi, Carlo & Menapace, Luisa & Raffaelli, Roberta, 2021. "Estimating risk preferences integrating insurance choices with subjective beliefs," European Economic Review, Elsevier, vol. 135(C).
    13. Pongnumkul, Suchit & Motohashi, Kazuyuki, 2018. "A bipartite fitness model for online music streaming services," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1125-1137.
    14. Püts, Miriam & Taylor, Marc & Núñez-Riboni, Ismael & Steenbeek, Jeroen & Stäbler, Moritz & Möllmann, Christian & Kempf, Alexander, 2020. "Insights on integrating habitat preferences in process-oriented ecological models – a case study of the southern North Sea," Ecological Modelling, Elsevier, vol. 431(C).
    15. Gzara, Fatma & Elhedhli, Samir & Yildiz, Burak C., 2020. "The Pallet Loading Problem: Three-dimensional bin packing with practical constraints," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1062-1074.
    16. Lehtomaa, Jaakko & Resnick, Sidney I., 2020. "Asymptotic independence and support detection techniques for heavy-tailed multivariate data," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 262-277.
    17. Xing Zheng Wu & Chen Zhe Ma & Rui-kai Wang & Wei Chao Li, 2023. "Development of environmental contours from rainfall intensity and duration data for slopes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(1), pages 1001-1027, March.
    18. Yasin Khadem Charvadeh & Grace Y. Yi & Yuan Bian & Wenqing He, 2022. "Is 14-Days a Sensible Quarantine Length for COVID-19? Examinations of Some Associated Issues with a Case Study of COVID-19 Incubation Times," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(1), pages 175-190, April.
    19. Andrea Ferrantelli & Helena Kuivjõgi & Jarek Kurnitski & Martin Thalfeldt, 2020. "Office Building Tenants’ Electricity Use Model for Building Performance Simulations," Energies, MDPI, vol. 13(21), pages 1-19, October.
    20. Oluwatobi Aiyelokun & Quoc Bao Pham & Oluwafunbi Aiyelokun & Anurag Malik & S. Adarsh & Babak Mohammadi & Nguyen Thi Thuy Linh & Mohammad Zakwan, 2021. "Credibility of design rainfall estimates for drainage infrastructures: extent of disregard in Nigeria and proposed framework for practice," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(2), pages 1557-1588, November.

    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:481:y:2023:i:c:s0304380023000868. 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.