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Reply to ‘Dissimilarity measures affected by richness differences yield biased delimitations of biogeographic realms’

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  • Mark J. Costello

    (University of Auckland
    University of Auckland)

  • Peter Tsai

    (University of Auckland)

  • Alan Kwok Lun Cheung

    (University of Auckland)

  • Zeenatul Basher

    (University of Auckland)

  • Chhaya Chaudhary

    (University of Auckland)

Abstract

Recently, we classified the oceans into 30 biogeographic realms based on species’ endemicity. Castro-Insua et al. criticize the choices of dissimilarity coefficients and clustering approaches used in our paper, and reanalyse the data using alternative techniques. Here, we explain how the approaches used in our original paper yield results in line with existing biogeographical knowledge and are robust to alternative methods of analysis. We also repeat the analysis using several similarity coefficients and clustering algorithms, and a neural network theory method. Although each combination of methods produces outputs differing in detail, the overall pattern of realms is similar. The coarse nature of the present boundaries of the realms reflects the limited field data but may be improved with additional data and mapping to environmental variables.

Suggested Citation

  • Mark J. Costello & Peter Tsai & Alan Kwok Lun Cheung & Zeenatul Basher & Chhaya Chaudhary, 2018. "Reply to ‘Dissimilarity measures affected by richness differences yield biased delimitations of biogeographic realms’," Nature Communications, Nature, vol. 9(1), pages 1-4, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-07252-4
    DOI: 10.1038/s41467-018-07252-4
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