The spatial representation of species’ data is needed in most areas of biodiversity related research. In fact, mapping the species’ continuum to guide the prioritization of areas for conservation was the main driver for PHYLIN development, but the possible application is far more vast.

            Spatial representation of distances between georeferenced samples is challenging. The PHYLIN input are distance matrices and a table of samples classified in groups (lineages, for instance) with locations. PHYLIN relates a matrix measuring a particular distance between samples (for example, a genetic distance) with a matrix representing spatial distance between the same samples. PHYLIN then applies a kriging interpolation: models the relation by means of a variogram and uses that information as weights to interpolate to other locations a probability of belonging to each of the groups

The latest version of PHYLIN adds the possibility of using multiple spatial distance metrics, opening an exciting avenue with different applications. In our recent paper in Molecular Ecology Resources, we showed how different mechanisms of genetic isolation can be represented in space by PHYLIN. The application of the method is not limited to that and we show here three other possible applications: using 3 dimensional distance (similarly to an ocean environment), climate change connectivity and species distributions/contact zone.

Pedro Tarroso, Guillermo Velo-Antón and Silvia Carvalho  

See the full paper here: https://onlinelibrary.wiley.com/doi/abs/10.1111/1755-0998.13010

A step by step tutorial can be found here: https://cran.r-project.org/web/packages/phylin/vignettes/phylin_tutorial.pdf