Bark beetles are a natural part of coniferous forests. Dendroctonus mexicanus Hopkins is the most widely distributed and most destructive bark beetle in Mexico, colonizing more than 21 pine species. The objectives of this study were to generate ecological niche models for D. mexicanus and three of its most important host species, to evaluate the overlap of climate suitability of the association Dendroctonus–Pinus, and to determine the possible expansion of the bark beetle. We used meticulously cleaned species occurrence records, 15 bioclimatic variables and ‘kuenm’, an R package that uses Maxent as a modeling algorithm. The Dendroctonus–Pinus ecological niches were compared using ordination methods and the kernel density function. We generated 1392 candidate models; not all were statistically significant (α = 0.05). The response type was quadratic; there is a positive correlation between suitability and precipitation, and negative with temperature, the latter determining climatic suitability of the studied species. Indeed, a single variable (Bio 1) contributed 93.9% to the model (Pinus leiophylla Schl. & Cham). The overlap of suitable areas for Dendroctonus–Pinus is 74.95% (P. leiophylla) and on average of 46.66% in ecological niches. It is observed that D. mexicanus begins to expand towards climates not currently occupied by the studied pine species.

Agave lechuguilla Torr., of the family Agavaceae, is distributed from southwestern United States to southern Mexico and is one of the most representative species of arid and semiarid regions. Its fiber is extracted for multiple purposes. The objective of this study was to generate a robust model to predict dry fiber yield ( Dfw ) rapidly, simply, and inexpensively. We used a power model in its linear form and bioclimatic areas as dummy variables. Training, generation (80%) and validation (20%) of the model was performed using machine learning with the package ‘ caret’ of R. Using canonical correlation analysis (CCA), we evaluated the relationship of Dwf to bioclimatic variables. The principal components analysis (PCA) generated two bioclimatic zones, each with different A . lechuguilla productivities. We evaluated 499 individuals in four states of Mexico. The crown diameter ( Cd ) of this species adequately predicts its fiber dry weight (R 2 = 0.6327; p < 0.05). The intercept (β 0 ), slope [ lnCd (β 1 )], zone [( β 2 )] and interaction [ lnCd :Zona ( β 3 )] of the dummy model was statistically significant (p < 0.05), giving origin to an equation for each bioclimatic zone. The CCA indicates a positive correlation between minimum temperature of the coldest month (Bio 6) and Dwf (r = 0.84 and p < 0.05). In conclusion, because of the decrease in Bio 6 of more than 0.5°C by 2050, the species could be vulnerable to climate change, and A . lechuguilla fiber production could be affected gradually in the coming years.