Aim: The aim was to test whether species distribution models (SDMs) can reproduce major macroecological patterns in a species-rich, tropical region and provide recommendations for using SDMs in areas with sparse biotic inventory data. Location: North-east Brazil, including Minas Gerais. Time period: Present. Major taxa studied: Flowering ...
Aim: The aim was to test whether species distribution models (SDMs) can reproduce major macroecological patterns in a species-rich, tropical region and provide recommendations for using SDMs in areas with sparse biotic inventory data. Location: North-east Brazil, including Minas Gerais. Time period: Present. Major taxa studied: Flowering plants. Methods: Species composition estimates derived from stacked SDMs (s-SDMs) were compared with data from 1,506 inventories of 933 woody plant species from north-east Brazil. Both datasets were used in hierarchical clustering analyses to delimit floristic units that correspond to biomes. The ability of s-SDMs to predict the identity, functional composition and floristic composition of biomes was compared across geographical and environmental space. Results: The s-SDMs and inventory data both resolved four major biomes that largely corresponded in terms of their distribution, floristics and function. The s-SDMs proved excellent at identifying broad-scale biomes and their function, but misassigned many individual sites in complex savanna–forest mosaics. Main conclusions: Our results show that s-SDMs have a unique role to play in describing macroecological patterns in areas lacking inventory data and for poorly known taxa. s-SDMs accurately predict floristic and functional macroecological patterns but struggle in areas where non-climatic factors, such as fire or soil, play key roles in governing distributions.