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Finding potential high-yield areas for Mexican maize under current and climate change conditions

  • C. URETA (a1), E. MARTÍNEZ-MEYER (a2), E. J. GONZÁLEZ (a3) and E. R. ÁLVAREZ-BUYLLA (a4)


Analyses of the geographic patterns of wild species abundance have been carried out in studies ranging from those interested in hot-spots for biodiversity and conservation to basic ecological analyses. Based on the methodological approaches used, the present study searched for areas of higher yield among native races of maize in Mexico, its centre of origin and diversification. Ecological theory suggests that population fitness, and thus abundance, is maximal at the centroid of the multi-dimensional ecological niche of a particular species, and decreases progressively as distance from it increases. In the present study, yield was used instead of abundance, assuming it to be higher under optimal environmental conditions. It was assessed whether nine Mexican maize races exhibited higher yields in areas that are ecologically closer to their niche centroid (NC), or a niche optimum (NO) that did not always coincide with the geometric centroid. Environmental and geographical clusters for each race were also created to identify additional NOs in widely distributed races. All races showed significant correlations between yield and distance, both to the NC or NOs, but in only six of them was the chosen model better than the null model. Three races and two sub-groups were selected for projection under climate change conditions: Celaya (R 2 = 0·288), Celaya 3 (R 2 = 0·774), Vandeño (R 2 = 0·277) and Vandeño 2 (R 2 = 0·466) and Tepecintle (R 2 = 0·537). The Celaya race improved with environmental clustering, while Vandeño improved under geographical clustering. Finally, Tepecintle was projected at a race level. Projections under climate change suggested some potential areas for high yields in the future. It was concluded that the approach used in the present paper, considering the distance to NC/NO as a predictor of maize landrace yield, may contribute important information to agro-ecological projects.


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