IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v220y2009i5p673-683.html
   My bibliography  Save this article

Network-based exploration and visualisation of ecological data

Author

Listed:
  • Raymond, Ben
  • Hosie, Graham

Abstract

Networks – structured graphs consisting of sets of nodes connected by edges – provide a rich framework for data visualisation and exploratory analyses. Although rarely used for the visualisation of ecological data, networks are well suited to this purpose, including data that one might not normally think of as a network. We present a simple method for transforming a data matrix into network format, and show how this can be used as the basis for interactive exploratory analyses of ecological data.The method is demonstrated using a database of marine zooplankton samples acquired in the Southern Ocean. The network analyses revealed zooplankton community structures that are in good agreement with previously published results. Variations in community structure were observed to be related to the temporal and spatial pattern of sampling, as well as to physical environmental factors such as sea ice cover. The analyses also revealed a number of errors in the data, including taxon identification errors and instrument failures.The method allows the analyst to generate networks from different combinations of variables in the data set, and to examine the effects of varying parameters such as the scales of spatial, temporal, and taxonomic aggregation. This flexibility allows the analyst to rapidly gain a number of perspectives on the data and provides a powerful mechanism for exploration.

Suggested Citation

  • Raymond, Ben & Hosie, Graham, 2009. "Network-based exploration and visualisation of ecological data," Ecological Modelling, Elsevier, vol. 220(5), pages 673-683.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:5:p:673-683
    DOI: 10.1016/j.ecolmodel.2008.12.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380008005863
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2008.12.011?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. Neil Rooney & Kevin McCann & Gabriel Gellner & John C. Moore, 2006. "Structural asymmetry and the stability of diverse food webs," Nature, Nature, vol. 442(7100), pages 265-269, July.
    2. J. C. Gower & G. J. S. Ross, 1969. "Minimum Spanning Trees and Single Linkage Cluster Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 18(1), pages 54-64, March.
    3. E. L. Berlow, 1999. "Strong effects of weak interactions in ecological communities," Nature, Nature, vol. 398(6725), pages 330-334, March.
    4. J. Kruskal, 1964. "Nonmetric multidimensional scaling: A numerical method," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 115-129, June.
    5. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    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. Muñoz-Mas, Rafael & Vezza, Paolo & Alcaraz-Hernández, Juan Diego & Martínez-Capel, Francisco, 2016. "Risk of invasion predicted with support vector machines: A case study on northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.)," Ecological Modelling, Elsevier, vol. 342(C), pages 123-134.
    2. Simensen, Trond & Halvorsen, Rune & Erikstad, Lars, 2018. "Methods for landscape characterisation and mapping: A systematic review," Land Use Policy, Elsevier, vol. 75(C), pages 557-569.
    3. Willem Heiser, 1991. "A generalized majorization method for least souares multidimensional scaling of pseudodistances that may be negative," Psychometrika, Springer;The Psychometric Society, vol. 56(1), pages 7-27, March.
    4. Luís Francisco Aguiar & Pedro C. Magalhães & Maria Joana Soares, 2010. "Synchronism in Electoral Cycles: How United are the United States?," NIPE Working Papers 17/2010, NIPE - Universidade do Minho.
    5. Kennen, Jonathan G. & Kauffman, Leon J. & Ayers, Mark A. & Wolock, David M. & Colarullo, Susan J., 2008. "Use of an integrated flow model to estimate ecologically relevant hydrologic characteristics at stream biomonitoring sites," Ecological Modelling, Elsevier, vol. 211(1), pages 57-76.
    6. Keith Poole, 1990. "Least squares metric, unidimensional scaling of multivariate linear models," Psychometrika, Springer;The Psychometric Society, vol. 55(1), pages 123-149, March.
    7. Berrie Zielman & Willem Heiser, 1993. "Analysis of asymmetry by a slide-vector," Psychometrika, Springer;The Psychometric Society, vol. 58(1), pages 101-114, March.
    8. Hansohm, Jürgen, 2007. "Algorithms and error estimations for monotone regression on partially preordered sets," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 1043-1050, May.
    9. Christian Genest & Johanna G. Nešlehová, 2014. "A Conversation with James O. Ramsay," International Statistical Review, International Statistical Institute, vol. 82(2), pages 161-183, August.
    10. Jerzy Grobelny & Rafal Michalski & Gerhard-Wilhelm Weber, 2021. "Modeling human thinking about similarities by neuromatrices in the perspective of fuzzy logic," WORking papers in Management Science (WORMS) WORMS/21/09, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    11. Monteiro, Carlos M.F. & Dibb, Sally & Almeida, Luis Tadeu, 2010. "Revealing doctors' prescribing choice dimensions with multivariate tools: A perceptual mapping approach," European Journal of Operational Research, Elsevier, vol. 201(3), pages 909-920, March.
    12. Peter Verboon & Ivo Lans, 1994. "Robust canonical discriminant analysis," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 485-507, December.
    13. Patrick Groenen & Bart-Jan Os & Jacqueline Meulman, 2000. "Optimal scaling by alternating length-constrained nonnegative least squares, with application to distance-based analysis," Psychometrika, Springer;The Psychometric Society, vol. 65(4), pages 511-524, December.
    14. Guerdjikova, Ani, 2008. "Case-based learning with different similarity functions," Games and Economic Behavior, Elsevier, vol. 63(1), pages 107-132, May.
    15. Giovanni De Luca & Paola Zuccolotto, 2011. "A tail dependence-based dissimilarity measure for financial time series clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 323-340, December.
    16. Hossein Safizadeh, M. & McKenna, David R., 1996. "Application of multidimensional scaling techniques to facilities layout," European Journal of Operational Research, Elsevier, vol. 92(1), pages 54-62, July.
    17. Guerdjikova, Ani, 2006. "Portfolio Choice and Asset Prices in an Economy Populated by Case-Based Decision Makers," Working Papers 06-13, Cornell University, Center for Analytic Economics.
    18. Phipps Arabie, 1991. "Was euclid an unnecessarily sophisticated psychologist?," Psychometrika, Springer;The Psychometric Society, vol. 56(4), pages 567-587, December.
    19. Verniest, Fabien & Greulich, Sabine, 2019. "Methods for assessing the effects of environmental parameters on biological communities in long-term ecological studies - A literature review," Ecological Modelling, Elsevier, vol. 414(C).
    20. Luís Aguiar-Conraria & Pedro Magalhães & Maria Soares, 2013. "The nationalization of electoral cycles in the United States: a wavelet analysis," Public Choice, Springer, vol. 156(3), pages 387-408, September.

    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:220:y:2009:i:5:p:673-683. 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.