For centuries, humans occupying arid regions of North America have maintained an intricate relationship with Agave (Agavoideae, Asparagaceae). Today Agave cultivation, primarily for beverage production, provides an economic engine for rural communities throughout Mexico. Among known dryland-farming methods, the use of rock piles and cattle-grazed areas stand out as promising approaches for Agave cultivation. Identifying new cultivation areas to apply these approaches in Arizona, USA and Sonora, Mexico warrants a geographic assessment of areas outside the known ranges of rock piles and grasslands. The objective of this study was to predict areas for dryland-farming of Agave and develop models to identify potential areas for Agave cultivation. We used maximum entropy (MaxEnt) ecological-niche-modeling algorithms to predict suitable areas for Agave dryland farming. The model was parameterized using occurrence records of Hohokam rock piles in Arizona and grassland fields cultivated with Agave in Sonora. Ten environmental-predictor variables were used in the model, downloaded from the WorldClim 2 climate database. The model identified potential locations for using rock piles as dryland-farming methods from south-central Arizona to northwestern Sonora. The Agave-grassland model indicated that regions from central to southern Sonora have the highest potential for cultivation of Agave, particularly for the species Agave angustifolia. Results suggest that there are many suitable areas where rock piles can be used to cultivate Agave in the Sonoran Desert, particularly in the border of southeastern Arizona and northwest Sonora. Likewise, cattle-grazing grasslands provide a viable environment for cultivating Agave in southern Sonora, where the expanding bacanora-beverage industry continues to grow and where different Agave products (e.g., syrups, fructans, saponins, and medicinal compounds) can potentially strengthen local economies.
Copyright: © 2023 Ortiz Cano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.