New regionally modelled soil layers improve prediction of vegetation type relative to that based on global soil models

Aim: High-resolution spatial soil data are crucial to species distribution modelling for fundamental research and conservation planning. Recent globally-modelled soil layers (e.g. SoilGrids) have transformed distribution modelling, but may fail to represent regional soil characteristics accurately. We hypothesize that in the Cape biodiversity hotspot of South Africa, the use of global soil layers has led to underestimation of the importance of edaphic factors as determinants of species’ and vegetation distributions. We present a series of new, regionally-modelled layers to address this deficiency.
Location: Greater Cape Floristic Region (GCFR, South Africa)
Methods: We georeferenced edaphic characteristics from literature and other sources and used boosted regression trees (BRT) to associate edaphic characteristics with spatially-explicit topographic, climatic, soil texture and biotic variables. Multinomial BRTs were used to predict mapped vegetation types from the collated edaphic a...