Pedology and plant provenance can improve predictions of species distributions of the Australian native flora: a calibrated and validated modelling exercise on 5,033 species

Species distribution models (SDMs) are valuable tools for assessing
species' responses to environmental factors and identifying areas
suitable for their survival. The careful selection of input variables is
critical, as their interactions, and correlations with other environmental
factors can affect model performance. This study evaluates the influence
of climate and soil variables on SDMs’ performance for 5,033 Australian
plant species, selected to represent the largest phylogenetic diversity of
native terrestrial vascular flora. Using an ensemble of correlative
models, we assessed the predictive performance of climate and soil
variables, individually and in combination, across four distinct
ecoregions: Desert (n = 640 species), Mediterranean (n = 1,246), Temperate
(n = 1,936), and Tropical (n = 1,211). Our results demonstrate that on a
continental scale, climate variables have a greater influence on plant
distributions than soil variables. Although incorporating soil and climate
variables enhanced model performance in some ecoregions, our results
indicate that relying solely on small-scale variables such as soil may
increase the likelihood of overfitting. In soil-only models, Clay content
(CLY), Nitrogen Total Organic (NTO), and Soil Organic Carbon (SOC) were
important across modelled species, with their relevance varying by
ecoregion. Our findings have significant implications for understanding
the interplay between climate, soil, and plant distribution within diverse
ecoregions. By highlighting the crucial role of climate in large-scale
models, this study serves as a foundation for developing more accurate
predictions of plant distributions, ultimately improving model accuracy
for biodiversity assessments.