Alexander Zizka | Search bioRxiv

bioRxiv2015

speciesgeocodeR: An R package for linking species occurrences, user-defined regions and phylogenetic trees for biogeography, ecology and evolution

1. Large-scale species occurrence data from geo-referenced observations and collected specimens are crucial for analyses in ecology, evolution and biogeography. Despite the rapidly growing availability of such data, their use in evolutionary analyses is often hampered by tedious manual classification of point occurrences into operational areas, leading to a lack of reproducibility and concerns regarding data quality.\n\n2. Here we present speciesgeocodeR, a user-friendly R-package for data cleaning, data exploration and data visualization of species point occurrences using discrete operational areas, and linking them to analyses invoking phylogenetic trees.\n\n3. The three core functions of the package are 1) automated and reproducible data cleaning, 2) rapid and reproducible classification of point occurrences into discrete operational areas in an adequate format for subsequent biogeographic analyses, and 3) a comprehensive summary and visualization of species distributions to explore large datasets and ensure data quality. In addition, speciesgeocodeR facilitates the access and analysis of publicly available species occurrence data, widely used operational areas and elevation ranges. Other functionalities include the implementation of minimum occurrence thresholds and the visualization of coexistence patterns and range sizes. SpeciesgeocodeR accompanies a richly illustrated and easy-to-follow tutorial and help functions.

Evolutionary Biology↗

bioRxiv2014

SpeciesGeoCoder: Fast categorisation of species occurrences for analyses of biodiversity, biogeography, ecology and evolution

Understanding the patterns and processes underlying the uneven distribution of biodiversity across space and time constitutes a major scientific challenge in evolutionary biology. With rapidly accumulating species occurrence data, there is an increasing need for making the process of coding species into operational units for biogeographic and evolutionary analyses faster, automated, transparent and reproducible. Here we present SpeciesGeoCoder, a free software package written in Python and R, that allows for easy coding of species into user-defined areas. These areas may be of any size and be purely geographical (i.e., polygons) such as political units, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include altitudinal ranges. This flexibility allows scoring species into complex categories, such as those encountered in topographically and ecologically heterogeneous landscapes. In addition, SpeciesGeoCoder can be used to facilitate sorting and cleaning of occurrence data. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and NEXUS files that can be directly used in many phylogeny-based applications for ancestral state reconstruction, investigations on biome evolution, and diversification rate analyses. Our simulations indicate that even datasets containing hundreds of millions of records can be analysed in relatively short time using a regular desktop computer. We exemplify the use of our program through two contrasting examples: i) inferring historical dispersal of birds across the Isthmus of Panama, separating lowland vs. montane species and optimising the results onto a species-level, dated phylogeny; and ii) exploring seasonal variations in the occurrence of 10 GPS-tracked individuals of moose (Alces alces) over one year in northern Sweden. These analyses show that SpeciesGeoCoder allows an easy, flexible and fast categorisation of species distribution data for various analyses in ecology and evolution, with potential use at different spatial, taxonomic and temporal scales.

Evolutionary Biology↗