Using plant distributions to predict the current and future range of a rare lizard
Correspondence: S. Delean, The Environment Institute and School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005, Australia.
To investigate the use of bioclimatic envelope models for predicting distributions of species that have experienced severe human-induced geographical range contractions. Bioclimatic envelope model predictions of current and future distributions were contrasted with those from models that used biotic indicators of suitable habitat as predictors rather than climate.
Temperate grassy woodlands of South Australia.
We modelled the distribution of two native grassland plant species, key habitat indicators of the endangered and geographically restricted pygmy bluetongue lizard (Tiliqua adelaidensis), using climate and landscape variables with aggregated boosted regression trees. We forecast annual changes in the plant species distributions from 2000 to 2100 under a no-climate-policy ‘Reference’ scenario (high global greenhouse gas emissions) and a climate stabilization ‘Policy’ scenario. We compared current and future predicted distributions of the lizard estimated directly using bioclimatic envelope models with those derived indirectly from climate-driven changes in habitat suitability of the grassland plant species with which the lizard has a strong association (termed plant-habitat models).
Both coupled plant-habitat models and bioclimatic envelope models described the current distribution of the pygmy bluetongue lizard almost equally well; however, future projections of changes in the species range were markedly more pessimistic (i.e. greater range contraction) for bioclimatic envelope models. Further, bioclimatic envelope models that included interactions among variables projected rapid increases in area of occupancy that are unlikely to be attainable given dispersal constraints, but no such increases were projected from plant-habitat models.
Capturing species–environment relationships for threatened and range-restricted species using surrogate biotic variables that represent resource requirements of the focal species – which themselves respond to environmental variation and are in stable equilibrium – allows more confident and ecologically realistic forecasts of potential range changes for species most susceptible to climate change.