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

Author:

Nitta Joel H.1ORCID,Laffan Shawn W.2ORCID,Mishler Brent D.3ORCID,Iwasaki Wataru145ORCID

Affiliation:

1. Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo Chiba Japan

2. Earth and Sustainability Science Research Centre, School of Biological, Earth and Environmental Sciences, The University of New South Wales Sydney NSW Australia

3. University and Jepson Herbaria, and Department of Integrative Biology, University of California Berkeley Berkeley CA USA

4. Department of Biological Sciences, Graduate School of Science, The University of Tokyo Tokyo Japan

5. Atmosphere and Ocean Research Institute, The University of Tokyo Chiba Japan

Abstract

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.

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

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