Networks are widely used for modelling landscape connectivity and have many ecological and conservation applications. The nodes in these models describe geographic locations (such as habitat patches or protected areas) and links describe the potential for organisms (or their propagules) to move among nodes. We present the r package grainscape which facilitates working with these networks within a spatially explicit framework. Package analyses are based on the minimum planar graph, a class of network where links among nodes are influenced by the spatial characteristics of features across the entire landscape. Modelling outputs are compatible with downstream packages including igraph for network analysis and ggplot2 for visualization. Tools for analysis (e.g. finding corridors) and scaling networks (e.g. grains of connectivity) are also provided. Models can be exported for visualization and analysis in Geographic Information System (GIS) or network software. This package provides a computationally‐efficient programmatic toolbox for many landscape connectivity research questions, enabling researchers to easily customize models, work at large geographic extents, generate their own network metrics, conduct sensitivity analyses and seamlessly employ r statistical functions to test models using biological data. A detailed guide, provided as an Appendix, illustrates common analysis and model variants with accompanying r code.

No abstract