Rangr: An R package for mechanistic, spatially explicit simulation of species range dynamics

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Abstract Global change driven by human activities is causing profound shifts in species distributions. Understanding the mechanisms that influence these dynamics is crucial for biodiversity management. Several mechanistic, spatially explicit models have been proposed to address this issue, but they do not cover the full range of potential functionalities. We present a new open‐source R package called rangr, which integrates population dynamics and dispersal into a mechanistic virtual species simulator. The package can be used to study the effects of environmental change on population growth and range shifts. It extends the capabilities of previously available simulators by allowing simple and straightforward definition of population dynamics (including positive density dependence), extensive possibilities for defining dispersal kernels and the ability to generate virtual ecologist data. We showcased rangr functionality by simulating the invasion of the collared dove (Streptopelia decaocto). First, we demonstrated how to set up a simulation with different dispersal kernels by investigating the role of long‐distance dispersal events on colonisation outcome. Second, we showed the use of rangr to assess the potential of an Allee effect to impede biological invasion. Finally, we used the virtual ecologist framework to determine the timeframe required to detect the spread of an invasive species. The rangr package, which comes with extensive documentation and vignettes, is easy to set up, flexible, fast, fully configurable and capable of emulating the observation process. These features make rangr particularly well suited to generating data that replicate existing wildlife monitoring programmes.