IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v265y2013icp14-25.html
   My bibliography  Save this article

Assessment of Atlantic salmon (Salmo salar) habitat quality and its uncertainty using a multiple-expert fuzzy model applied to the Romaine River (Canada)

Author

Listed:
  • Mocq, J.
  • St-Hilaire, A.
  • Cunjak, R.A.

Abstract

Many tools have been developed to evaluate environmental flows, including physical microhabitat models like PHASBIM and HABSCORE, which require habitat suitability curves. Unfortunately, the models and curves are often used in stream-specific applications and are rarely easily exportable. With the aim to address this shortcoming, we developed several habitat suitability indices sets for three Atlantic salmon (Salmo salar) life stages (young-of-the-year (YOY), parr, spawning adults) with the help of fuzzy logic modeling. Using the knowledge of twenty-seven experts, from both sides of the Atlantic Ocean, we defined fuzzy sets of four variables (depth, substrate size, velocity and Habitat Suitability Index, or HSI) and associated fuzzy rules. When applied to the Romaine River (Canada), median curves of standardized Weighted Usable Area (WUA) were calculated and a confidence interval was obtained by bootstrap resampling. Despite the large range of WUA covered by the expert WUA curves, confidence intervals were relatively narrow: an average width of 0.095 (on a scale of 0 to 1) for spawning habitat, 0.155 for parr rearing habitat and 0.160 for YOY rearing habitat. In addition, Student's t-test showed significant differences in predicted HSI between presence and absence, for parr and YOY, and RM_ANOVA showed significant differences for parr only. When considering an environmental flow value corresponding to 90% of the maximum reached by WUA curve, results seem acceptable for the Romaine River. Generally, this proposed fuzzy logic method seems suitable to model habitat availability for the three life stages, while also providing an estimate of uncertainty in salmon preferences.

Suggested Citation

  • Mocq, J. & St-Hilaire, A. & Cunjak, R.A., 2013. "Assessment of Atlantic salmon (Salmo salar) habitat quality and its uncertainty using a multiple-expert fuzzy model applied to the Romaine River (Canada)," Ecological Modelling, Elsevier, vol. 265(C), pages 14-25.
  • Handle: RePEc:eee:ecomod:v:265:y:2013:i:c:p:14-25
    DOI: 10.1016/j.ecolmodel.2013.05.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380013002834
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2013.05.020?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. Mouton, Ans M. & Schneider, Matthias & Peter, Armin & Holzer, Georg & Müller, Rudolf & Goethals, Peter L.M. & De Pauw, Niels, 2008. "Optimisation of a fuzzy physical habitat model for spawning European grayling (Thymallus thymallus L.) in the Aare river (Thun, Switzerland)," Ecological Modelling, Elsevier, vol. 215(1), pages 122-132.
    2. Fukuda, Shinji, 2009. "Consideration of fuzziness: Is it necessary in modelling fish habitat preference of Japanese medaka (Oryzias latipes)?," Ecological Modelling, Elsevier, vol. 220(21), pages 2877-2884.
    3. Fukuda, Shinji & Hiramatsu, Kazuaki, 2008. "Prediction ability and sensitivity of artificial intelligence-based habitat preference models for predicting spatial distribution of Japanese medaka (Oryzias latipes)," Ecological Modelling, Elsevier, vol. 215(4), pages 301-313.
    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. Schwamborn, R. & Mildenberger, T.K. & Taylor, M.H., 2019. "Assessing sources of uncertainty in length-based estimates of body growth in populations of fishes and macroinvertebrates with bootstrapped ELEFAN," Ecological Modelling, Elsevier, vol. 393(C), pages 37-51.
    2. Castanho, M.J.P. & Mateus, R.P. & Hein, K.D., 2014. "Fuzzy model of Drosophila mediopunctata population dynamics," Ecological Modelling, Elsevier, vol. 287(C), pages 9-15.
    3. Hughes, Conchúr & King, Jonathan W., 2023. "Habitat suitability modelling for an integrated multi-trophic aquaculture (IMTA) system along Europe's Atlantic coast," Ecological Modelling, Elsevier, vol. 484(C).
    4. Yi, Yujun & Cheng, Xi & Yang, Zhifeng & Wieprecht, Silke & Zhang, Shanghong & Wu, Yingjie, 2017. "Evaluating the ecological influence of hydraulic projects: A review of aquatic habitat suitability models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 748-762.
    5. Dubos, Véronique & St-Hilaire, André & Bergeron, Normand E., 2023. "Fuzzy logic modelling of anadromous Arctic char spawning habitat from Nunavik Inuit knowledge," Ecological Modelling, Elsevier, vol. 477(C).
    6. Boudreault, Jeremie & Bergeron, Normand E & St-Hilaire, Andre & Chebana, Fateh, 2022. "A new look at habitat suitability curves through functional data analysis," Ecological Modelling, Elsevier, vol. 467(C).

    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. Fukuda, Shinji & De Baets, Bernard & Mouton, Ans M. & Waegeman, Willem & Nakajima, Jun & Mukai, Takahiko & Hiramatsu, Kazuaki & Onikura, Norio, 2011. "Effect of model formulation on the optimization of a genetic Takagi–Sugeno fuzzy system for fish habitat suitability evaluation," Ecological Modelling, Elsevier, vol. 222(8), pages 1401-1413.
    2. Yi, Yujun & Cheng, Xi & Yang, Zhifeng & Wieprecht, Silke & Zhang, Shanghong & Wu, Yingjie, 2017. "Evaluating the ecological influence of hydraulic projects: A review of aquatic habitat suitability models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 748-762.
    3. Yi, Yujun & Wang, Zhaoyin & Yang, Zhifeng, 2010. "Two-dimensional habitat modeling of Chinese sturgeon spawning sites," Ecological Modelling, Elsevier, vol. 221(5), pages 864-875.
    4. Fukuda, Shinji, 2009. "Consideration of fuzziness: Is it necessary in modelling fish habitat preference of Japanese medaka (Oryzias latipes)?," Ecological Modelling, Elsevier, vol. 220(21), pages 2877-2884.
    5. Gobeyn, Sacha & Mouton, Ans M. & Cord, Anna F. & Kaim, Andrea & Volk, Martin & Goethals, Peter L.M., 2019. "Evolutionary algorithms for species distribution modelling: A review in the context of machine learning," Ecological Modelling, Elsevier, vol. 392(C), pages 179-195.
    6. Mouton, Ans M. & De Baets, Bernard & Goethals, Peter L.M., 2010. "Ecological relevance of performance criteria for species distribution models," Ecological Modelling, Elsevier, vol. 221(16), pages 1995-2002.
    7. Mouton, Ans M. & De Baets, Bernard & Van Broekhoven, Ester & Goethals, Peter L.M., 2009. "Prevalence-adjusted optimisation of fuzzy models for species distribution," Ecological Modelling, Elsevier, vol. 220(15), pages 1776-1786.
    8. Mouton, A.M. & Dillen, A. & Van den Neucker, T. & Buysse, D. & Stevens, M. & Coeck, J., 2012. "Impact of sampling efficiency on the performance of data-driven fish habitat models," Ecological Modelling, Elsevier, vol. 245(C), pages 94-102.
    9. Febrina, Rina & Sekine, Masahiko & Noguchi, Hiroyuki & Yamamoto, Koichi & Kanno, Ariyo & Higuchi, Takaya & Imai, Tsuyoshi, 2015. "Modeling the preference of ayu (Plecoglossus altivelis) for underwater sounds to determine the migration path in a river," Ecological Modelling, Elsevier, vol. 299(C), pages 102-113.
    10. Muñoz-Mas, Rafael & Marcos-Garcia, Patricia & Lopez-Nicolas, Antonio & Martínez-García, Francisco J. & Pulido-Velazquez, Manuel & Martínez-Capel, Francisco, 2018. "Combining literature-based and data-driven fuzzy models to predict brown trout (Salmo trutta L.) spawning habitat degradation induced by climate change," Ecological Modelling, Elsevier, vol. 386(C), pages 98-114.
    11. Dubos, Véronique & St-Hilaire, André & Bergeron, Normand E., 2023. "Fuzzy logic modelling of anadromous Arctic char spawning habitat from Nunavik Inuit knowledge," Ecological Modelling, Elsevier, vol. 477(C).
    12. Aude Zingraff-Hamed & Markus Noack & Sabine Greulich & Kordula Schwarzwälder & Karl Matthias Wantzen & Stephan Pauleit, 2018. "Model-Based Evaluation of Urban River Restoration: Conflicts between Sensitive Fish Species and Recreational Users," Sustainability, MDPI, vol. 10(6), pages 1-27, May.

    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:265:y:2013:i:c:p:14-25. 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.