IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0196991.html
   My bibliography  Save this article

Disentangling the complexity of tropical small-scale fisheries dynamics using supervised Self-Organizing Maps

Author

Listed:
  • Manuel Mendoza-Carranza
  • Elisabet Ejarque
  • Leopold A J Nagelkerke

Abstract

Tropical small-scale fisheries are typical for providing complex multivariate data, due to their diversity in fishing techniques and highly diverse species composition. In this paper we used for the first time a supervised Self-Organizing Map (xyf-SOM), to recognize and understand the internal heterogeneity of a tropical marine small-scale fishery, using as model the fishery fleet of San Pedro port, Tabasco, Mexico. We used multivariate data from commercial logbooks, including the following four factors: fish species (47), gear types (bottom longline, vertical line+shark longline and vertical line), season (cold, warm), and inter-annual variation (2007–2012). The size of the xyf-SOM, a fundamental characteristic to improve its predictive quality, was optimized for the minimum distance between objects and the maximum prediction rate. The xyf-SOM successfully classified individual fishing trips in relation to the four factors included in the model. Prediction percentages were high (80–100%) for bottom longline and vertical line + shark longline, but lower prediction values were obtained for vertical line (51–74%) fishery. A confusion matrix indicated that classification errors occurred within the same fishing gear. Prediction rates were validated by generating confidence interval using bootstrap. The xyf-SOM showed that not all the fishing trips were targeting the most abundant species and the catch rates were not symmetrically distributed around the mean. Also, the species composition is not homogeneous among fishing trips. Despite the complexity of the data, the xyf-SOM proved to be an excellent tool to identify trends in complex scenarios, emphasizing the diverse and complex patterns that characterize tropical small scale-fishery fleets.

Suggested Citation

  • Manuel Mendoza-Carranza & Elisabet Ejarque & Leopold A J Nagelkerke, 2018. "Disentangling the complexity of tropical small-scale fisheries dynamics using supervised Self-Organizing Maps," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-28, May.
    • Handle: RePEc:plo:pone00:0196991
    DOI: 10.1371/journal.pone.0196991
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0196991
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0196991&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0196991?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
    ---><---

    References listed on IDEAS

    as
    1. Wehrens, Ron & Buydens, Lutgarde M. C., 2007. "Self- and Super-organizing Maps in R: The kohonen Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i05).
    2. Trevor A. Branch & Reg Watson & Elizabeth A. Fulton & Simon Jennings & Carey R. McGilliard & Grace T. Pablico & Daniel Ricard & Sean R. Tracey, 2010. "The trophic fingerprint of marine fisheries," Nature, Nature, vol. 468(7322), pages 431-435, November.
    3. Youen Vermard & Paul Marchal & Stéphanie Mahévas & Olivier Thébaud, 2008. "A dynamic model of the Bay of Biscay pelagic fleet simulating fishing trip choice: the response to the closure of the European anchovy (Engraulis encrasicolus) fishery in 2005," Post-Print hal-00368317, HAL.
    4. Zetina-Rejón, Manuel J. & Cabrera-Neri, Erika & López-Ibarra, Gladis A. & Arcos-Huitrón, N. Enrique & Christensen, Villy, 2015. "Trophic modeling of the continental shelf ecosystem outside of Tabasco, Mexico: A network and modularity analysis," Ecological Modelling, Elsevier, vol. 313(C), pages 314-324.
    5. Chih-hao Hsieh & Sarah M. Glaser & Andrew J. Lucas & George Sugihara, 2005. "Distinguishing random environmental fluctuations from ecological catastrophes for the North Pacific Ocean," Nature, Nature, vol. 435(7040), pages 336-340, May.
    6. Kampstra, Peter, 2008. "Beanplot: A Boxplot Alternative for Visual Comparison of Distributions," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(c01).
    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. Aiyshwariya Paulvannan Kanmani & Renee Obringer & Benjamin Rachunok & Roshanak Nateghi, 2020. "Assessing Global Environmental Sustainability Via an Unsupervised Clustering Framework," Sustainability, MDPI, vol. 12(2), pages 1-12, January.

    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. Moolenaar, Hanneke E. & Grasman, Johan & Selten, Frank M. & de Gee, Maarten, 2007. "Testing a method for analyzing the effect of parameter change in climate driven ecological systems," Ecological Modelling, Elsevier, vol. 205(3), pages 289-300.
    2. Andreas Karpf, 2014. "Expectation Formation and Social Influence," Documents de travail du Centre d'Economie de la Sorbonne 14005, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. Jach Agnieszka E & Marín Juan M, 2010. "Classification of Genomic Sequences via Wavelet Variance and a Self-Organizing Map with an Application to Mitochondrial DNA," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-14, July.
    4. Markus Demary, 2017. "Yield curve responses to market sentiments and monetary policy," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 309-344, July.
    5. Miroslav Sirota & Marie Juanchich, 2015. "A direct and comprehensive test of two postulates of politeness theory applied to uncertainty communication," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(3), pages 232-240, May.
    6. Barrios Ramos, Iris & Espinoza Tenorio, Alejandro & Mesa Jurado, M. Azahara & Tovilla Hernández, Cristian & Mendoza Carranza, Manuel, 2021. "Percepción social de la salinización del agua para uso doméstico en Puerto Madero, Chiapas, México," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 21(01), June.
    7. Preetam Debasish Saha Roy & Prabhat Kumar Tiwari, 2019. "Knowledge discovery and predictive accuracy comparison of different classification algorithms for mould level fluctuation phenomenon in thin slab caster," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 241-254, January.
    8. Grasman, Johan & van Nes, Egbert H. & Kersting, Kees, 2009. "Data-directed modelling of Daphnia dynamics in a long-term micro-ecosystem experiment," Ecological Modelling, Elsevier, vol. 220(3), pages 343-350.
    9. Andreas M Neophytou & Elizabeth M Noth & Sa Liu & Sadie Costello & S Katharine Hammond & Mark R Cullen & Ellen A Eisen, 2016. "Ischemic Heart Disease Incidence in Relation to Fine versus Total Particulate Matter Exposure in a U.S. Aluminum Industry Cohort," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-13, June.
    10. Ali Kharrazi & Brian D. Fath & Harald Katzmair, 2016. "Advancing Empirical Approaches to the Concept of Resilience: A Critical Examination of Panarchy, Ecological Information, and Statistical Evidence," Sustainability, MDPI, vol. 8(9), pages 1-17, September.
    11. Joanna F Dipnall & Julie A Pasco & Michael Berk & Lana J Williams & Seetal Dodd & Felice N Jacka & Denny Meyer, 2016. "Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-19, December.
    12. Cabral, Reniel B. & Geronimo, Rollan C. & Lim, May T. & Aliño, Porfirio M., 2010. "Effect of variable fishing strategy on fisheries under changing effort and pressure: An agent-based model application," Ecological Modelling, Elsevier, vol. 221(2), pages 362-369.
    13. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    14. Michael C. Thrun & Alfred Ultsch, 2021. "Using Projection-Based Clustering to Find Distance- and Density-Based Clusters in High-Dimensional Data," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 280-312, July.
    15. Michael J Malick & Sean P Cox, 2016. "Regional-Scale Declines in Productivity of Pink and Chum Salmon Stocks in Western North America," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-23, January.
    16. Alberto Arcagni & Elisa Barbiano di Belgiojoso & Marco Fattore & Stefania M. L. Rimoldi, 2019. "Multidimensional Analysis of Deprivation and Fragility Patterns of Migrants in Lombardy, Using Partially Ordered Sets and Self-Organizing Maps," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(2), pages 551-579, January.
    17. Grafton, R. Quentin & Akter, Sonia & Kompas, Tom, 2009. "Guide to the Ex-Ante Socio-Economic Evaluation of Marine Protected Areas," Research Reports 94827, Australian National University, Environmental Economics Research Hub.
    18. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    19. Vermard, Youen & Rivot, Etienne & Mahévas, Stéphanie & Marchal, Paul & Gascuel, Didier, 2010. "Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models," Ecological Modelling, Elsevier, vol. 221(15), pages 1757-1769.
    20. Heymans, Johanna Jacomina & Coll, Marta & Link, Jason S. & Mackinson, Steven & Steenbeek, Jeroen & Walters, Carl & Christensen, Villy, 2016. "Best practice in Ecopath with Ecosim food-web models for ecosystem-based management," Ecological Modelling, Elsevier, vol. 331(C), pages 173-184.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0196991. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.