Reply to 'Dissimilarity measures affected by richness differences yield biased delimitations of biogeographic realms'.

Journal: Nature communications
Published Date:

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.

Authors

  • Mark J Costello
    Institute of Marine Science, University of Auckland, Auckland, 1142, New Zealand. m.costello@auckland.ac.nz.
  • Peter Tsai
    Bioinformatics Institute, University of Auckland, Auckland, 1142, New Zealand.
  • Alan Kwok Lun Cheung
    School of Environment, University of Auckland, Auckland, 1142, New Zealand.
  • Zeenatul Basher
    Institute of Marine Science, University of Auckland, Auckland, 1142, New Zealand.
  • Chhaya Chaudhary
    Institute of Marine Science, University of Auckland, Auckland, 1142, New Zealand.