minA: A minimum area indicator of alpha-diversity patterns

Description of spatial diversity patterns is a crucial part of biogeography and ecology. Diversity patterns vary with scale and the definition of the appropriate scale for their observation and analysis is not always straightforward depending on the research question and studied taxon. Species richness patterns are affected by the sampling design, as sampling area is a complex parameter defined by size, shape and spatial arrangement of the sample. We introduce the minimum area (minA) method, which estimates the smallest area containing a specific number of species. This approach uses species richness as the sampling’s independent variable, thus establishing a direct reference to the functional and ecological characteristics of the studied taxon. We examined how different abundance distributions, spatial aggregation, and starting point locations affect minA size with simulated communities and linear mixed-effects models. We applied the minA method to empirical data of African reptiles (Sauria, Serpentes, Amphisbaenia, Testudines) to explore its ability to identify diversity patterns and hotspots. The minA size decreases with species evenness and increases with spatial aggregation. The impact of the starting point's location on minA size is less important. In African reptiles, minA aligns with richness hotspots, but the minA patterns change with increasing number of species. This indicates that the underlying processes are taxon- and scale-specific. At small scales, environmental conditions and biotic interactions are more likely to drive local diversity. Αt larger scales, biogeographic history becomes the most influential factor. minA could be an alternative tool for studying α-diversity patterns and identifying species-rich regions.