Reply to ‘Dissimilarity measures affected by richness differences yield biased delimitations of biogeographic realms’
| Autor: | Alan Kwok Lun Cheung, Mark J. Costello, Zeenatul Basher, Peter Tsai, Chhaya Chaudhary |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
0301 basic medicine Theory method Yield (finance) Field data Science General Physics and Astronomy 010603 evolutionary biology 01 natural sciences General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Similarity (network science) Statistics Correspondence Cluster Analysis Cluster analysis lcsh:Science Mathematics Alternative methods Multidisciplinary Artificial neural network General Chemistry 030104 developmental biology lcsh:Q Species richness Neural Networks Computer Algorithms |
| Zdroj: | Nature Communications Nature Communications, Vol 9, Iss 1, Pp 1-4 (2018) |
| ISSN: | 2041-1723 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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