megaSDM: integrating dispersal and time?step analyses into species distribution models

Understanding how species ranges shift as climates rapidly change informs us to effectively conserve vulnerable species. Species distribution models (SDMs) are an important method for examining these range shifts. The tools performing SDMs ever improving. Here, we present the megaSDM R package. This package facilitates realistic spatiotemporal SDM analyses by incorporating dispersal probabilities, creating time-step maps of dynamics and efficiently handling large datasets computationally intensive environmental subsampling techniques. Provided a list data, synthesizes GIS processing, methods, MaxEnt modelling, rate restrictions additional statistical create variety outputs each species, time period climate scenario requested. For these, generates series visual representations data. offers several advantages over other commonly used tools. First, many functions in natively implement parallelization, enabling handle amounts data without need coding. also implements occurrences, making technique broadly available way that was not possible before due computational considerations. Uniquely, showing expansion contraction across all considered periods (time-maps), constrains both presence/absence continuous suitability according species-specific constraints. user can then directly compare non-dispersal dispersal-limited predictions. paper discusses unique features highlights megaSDM, describes structure demonstrates package's model flow through examples.