論文

査読有り 本文へのリンクあり 国際誌
2023年7月18日

canaper: Categorical analysis of neo‐ and paleo‐endemism in R

Ecography
  • Joel H. Nitta
  • ,
  • Shawn W. Laffan
  • ,
  • Brent D. Mishler
  • ,
  • Wataru Iwasaki

記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1111/ecog.06638
出版者・発行元
Wiley

Biodiversity has typically been quantified using species richness, but this ignores evolutionary history. Due to the increasing availability of robust phylogenies, methods have been developed that incorporate phylogenetic relationships into quantification of biodiversity. CANAPE (categorical analysis of neo‐ and paleo‐endemism) is one such method that can provide insight into the evolutionary processes generating biodiversity. The only currently available software implementing CANAPE is Biodiverse, which is written in Perl and can be used either through a graphical user interface (GUI) or user‐developed scripts. However, many researchers, particularly in the fields of ecology and evolutionary biology, use the R programming language to conduct their analyses. Here, we present canaper, a new R package (www.r‐project.org) that provides functions to conduct CANAPE in R. canaper implements methods for efficient computation, including parallelization and encoding of community data as sparse matrices. The interface is designed for maximum simplicity and reproducibility; CANAPE can be conducted with two functions, and parallel computing can be enabled with one line of code. Our case study shows that canaper produces equivalent results to Biodiverse and can complete computations on moderately sized datasets quickly (<10 min to reproduce a canonical study). canaper allows researchers to conduct all analyses from data import and cleaning through CANAPE within R, thereby obviating the need to manually import and export data and analysis results between programs. We anticipate canaper will become a part of the toolkit for analyzing biodiversity in R.

リンク情報
DOI
https://doi.org/10.1111/ecog.06638 本文へのリンクあり
URL
https://onlinelibrary.wiley.com/doi/pdf/10.1111/ecog.06638
ID情報
  • DOI : 10.1111/ecog.06638
  • ISSN : 0906-7590
  • eISSN : 1600-0587
  • ORCIDのPut Code : 120381106

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