1.Over 60 claylicks were reported, with over 90% occurring in the western Amazon in Peru and Ecuador. 2.The modelling program determined that the highest likelihood of encountering claylicks is associated with the edges of the Amazon, with highest likelihood on the east slopes of the Andes mountains (Fig. 2). 3.All claylicks were found in tropical broadleaf forest and significantly more are found in younger geological age zones and basins. 4.Claylicks with large surface-areas and furthest from the east coast oceans had the highest species richness. 5.Parrots with large ranges and with broader habitat breadth use a larger proportion of claylicks. Parrots claylick distribution in South America: Do patterns of where help answer the question why? Lee, A.T.K 1,4, Kumar, S. 2, Marsden, S.J. 1, and Brightsmith, D.J. 3 1 Manchester Metropolitan University; 2 Colorado State University; 3 Texas A&M University 4 (corresponding author) Introduction Methods Results Conclusions References Geophagy, the intentional consumption of soil, is observed on all continents of the world except Antarctica by a host of taxa from butterflies to elephants. In South America up to 20 species of parrots are commonly observed eating clay from claylicks on riverbanks 1 (Fig. 1). Common theories include adsorption of dietary toxins 2 and nutrient supplementation, especially sodium 3. Recent studies have struggled to separate these benefits as the variables are strongly correlated 4. We aimed to map the extent of this phenomenon to: 1.determine the range of claylick distribution and the reasons for this distribution in South America 2.determine claylick characteristics that increase species richness 3.determine parrot characteristics that predetermine a species likelihood of engaging in geophagy 1.Location data and parrot use of claylicks was obtained through an online survey and from relevant publications. 2.A predictive modelling program MAXENT 5 was used to determine the extent of parrot geophagy using 24 environmental layers e.g. rainfall, temperature, and satellite maps of vegetation. 3.Claylick positions were mapped using GIS software to determine vegetation and geology associations. 4.Claylick height, width, area, distance from ocean and distance to a calculated centre of gravity were correlated with parrot species richness. 5.Parrot diet, habitat breadth, range, abundance, IUCN ranking and size were correlated with proportion of licks used 1.Geological origins are important for creating the right conditions for claylicks within tropical forests. Very few claylicks are found in the Brazilian and Guianan shields in central and northern South America. 2.The modelling program Maxent provides a useful visual interpretation of clay lick distribution based on relatively few locations and suggests further potential areas of claylick occurrence in unexplored regions e.g. Bolivia. 3.Local claylick conditions play an important role in determining the range and number of visiting parrot species. 4.Common species that have broader habitat tolerance are more commonly observed on claylicks. 5.The need for sodium could explain why this ornithological phenomenon is associated with basins in western Amazonia but not in eastern Amazonia. Figure 1: Macaws feeding on a claylick in southeastern Peru Figure 2: Map of South America with probability of claylick occurrence based on positional data from 52 locations and 24 environmental layers. Probability of occurrence < – – – – – – – – – Brightsmith, D. J Effects of weather on parrot geophagy in Tambopata, Peru. Wilson Bulletin 116: Gilardi, J. D., S. S. Duffey, C. A. Munn, and L. A. Tell Biochemical functions of geophagy in parrots: Detoxification of dietary toxins and cytoprotective effects. Journal of Chemical Ecology 25: Brightsmith, D. J., and R. Aramburu Munoz-Najar Avian geophagy and soil characteristics in southeastern Peru. Biotropica 36: Brightsmith, D. J., J. Taylor, and T. D. Phillips. in press. The roles of soil characteristics and toxin adsorption in avian geophagy. Biotropica 5.Phillips, S. J., R. P. Anderson, and R. E. Schapire Maximum entropy modeling of species geographic distributions. Ecological Modelling 190:231–259