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Modelling European small pelagic fish distribution: Methodological insights

Author

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  • Schickele, Alexandre
  • Leroy, Boris
  • Beaugrand, Gregory
  • Goberville, Eric
  • Hattab, Tarek
  • Francour, Patrice
  • Raybaud, Virginie

Abstract

The distribution of marine organisms is strongly influenced by climatic gradients worldwide. The ecological niche (sensu Hutchinson) of a species, i.e. the combination of environmental tolerances and resources required by an organism, interacts with the environment to determine its geographical range. This duality between niche and distribution allows climate change biologists to model potential species’ distributions from past to future conditions. While species distribution models (SDMs) have been intensively used over the last years, no consensual framework to parametrise, calibrate and evaluate models has emerged. Here, to model the contemporary (1990–2017) spatial distribution of seven highly harvested European small pelagic fish species, we implemented a comprehensive and replicable numerical procedure based on 8 SDMs (7 from the Biomod2 framework plus the NPPEN model). This procedure considers critical issues in species distribution modelling such as sampling bias, pseudo-absence selection, model evaluation and uncertainty quantification respectively through (i) an environmental filtration of observation data, (ii) a convex hull based pseudo-absence selection, (iii) a multi-criteria evaluation of model outputs and (iv) an ensemble modelling approach. By mitigating environmental sampling bias in observation data and by identifying the most ecologically relevant predictors, our framework helps to improve the modelling of fish species’ environmental suitability. Not only average temperature, but also temperature variability appears as major factors driving small pelagic fish distribution, and areas of highest environmental suitability were found along the north-western Mediterranean coasts, the Bay of Biscay and the North Sea. We demonstrate in this study that the use of appropriate data pre-processing techniques, an often-overlooked step in modelling, increase model predictive performance, strengthening our confidence in the reliability of predictions.

Suggested Citation

  • Schickele, Alexandre & Leroy, Boris & Beaugrand, Gregory & Goberville, Eric & Hattab, Tarek & Francour, Patrice & Raybaud, Virginie, 2020. "Modelling European small pelagic fish distribution: Methodological insights," Ecological Modelling, Elsevier, vol. 416(C).
    • Handle: RePEc:eee:ecomod:v:416:y:2020:i:c:s0304380019304107
    DOI: 10.1016/j.ecolmodel.2019.108902
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    1. Chaalali, Aurélie & Beaugrand, Grégory & Raybaud, Virginie & Lassalle, Géraldine & Saint-Béat, Blanche & Le Loc’h, François & Bopp, Laurent & Tecchio, Samuele & Safi, Georges & Chifflet, Marina & Lobr, 2016. "From species distributions to ecosystem structure and function: A methodological perspective," Ecological Modelling, Elsevier, vol. 334(C), pages 78-90.
    2. Hengl, Tomislav & Sierdsema, Henk & Radović, Andreja & Dilo, Arta, 2009. "Spatial prediction of species’ distributions from occurrence-only records: combining point pattern analysis, ENFA and regression-kriging," Ecological Modelling, Elsevier, vol. 220(24), pages 3499-3511.
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    1. De Cubber, Lola & Trenkel, Verena M. & Diez, Guzman & Gil-Herrera, Juan & Novoa Pabon, Ana Maria & Eme, David & Lorance, Pascal, 2023. "Robust identification of potential habitats of a rare demersal species (blackspot seabream) in the Northeast Atlantic," Ecological Modelling, Elsevier, vol. 477(C).
    2. Farahmand, Shekoofeh & Hilmi, Nathalie & Cinar, Mine & Safa, Alain & Lam, Vicky W.Y. & Djoundourian, Salpie & Shahin, Wassim & Ben Lamine, Emna & Schickele, Alexandre & Guidetti, Paolo & Allemand, Den, 2023. "Climate change impacts on Mediterranean fisheries: A sensitivity and vulnerability analysis for main commercial species," Ecological Economics, Elsevier, vol. 211(C).
    3. Moullec, Fabien & Barrier, Nicolas & Drira, Sabrine & Guilhaumon, François & Hattab, Tarek & Peck, Myron A. & Shin, Yunne-Jai, 2022. "Using species distribution models only may underestimate climate change impacts on future marine biodiversity," Ecological Modelling, Elsevier, vol. 464(C).

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