Predicting the subspecific identity of invasive species using distribution models: Acacia saligna as an example
Acacia saligna, biological invasions, correlative models, Invasive species, niche conservatism, species distribution modelling, subspecies
Aim To explore whether the subspecific genetic entities of Acacia saligna occupy different bioclimatic niches in their native and introduced ranges and whether these niches are predictable using species distribution models (SDMs). Location Australia, South Africa and the Mediterranean Basin. Methods Species distribution models were developed in MAXENT using six climatic variables to calculate the climatic suitability of the ranges of A. saligna. We assessed (1) the subspecific niche differences identified by SDMs using measures of niche overlap and model performance; (2) the ability of SDMs to predict the most likely subspecific genetic entities present in South Africa based on comparisons to genetic data; and (3) the ability of SDMs to predict the most likely subspecific genetic entities present in the Mediterranean Basin. All model projections were assessed for sensitivity and modelled prevalence as indicators of model fit and predictability. Results The SDMs identified different subspecific bioclimatic niches in the native range. Sensitivity and modelled prevalence show that none of the models correctly predicted the full range of A. saligna in South Africa or the Mediterranean Basin. Models also show that the South African niche is different to that in the native range. Main conclusions Subspecies of A. saligna occupy quantifiably distinct bioclimatic niches in their native ranges, implying that they should occupy distinct niches in their invasive ranges. However, projections to the introduced range did not correspond with known occurrences. Our SDMs are unable to predict the full introduced niche of A. saligna at a species or subspecies level in either South Africa or the Mediterranean Basin. Range limits in the native and introduced ranges may be determined by additional factors not used in the SDMs developed in this study.