Habitat Suitability of Fig (Ficus carica L.) in Mexico under Current and Future Climates

Abstract

Emerging or alternative crops are those that have been recently introduced in response to new demands and commercial opportunities. The fig has been introduced as an alternative fruit crop in Mexico due to its high nutritional, nutraceutical, and antioxidant capacity. A total of 644 points of presence were downloaded and filtered according to climatic ranges and agricultural areas, leaving 68 records. The MaxEnt algorithm was used to develop the habitat suitability models for current and future climate. The bioclimatic variables of the global circulation models, Hadley Centre Global Environment Model version 2-EarthSystem (HADGEM2-ES) and Max Planck Institute for Meteorology-Earth System Model Low Resolution (MPI-ESM-LR), were used under scenarios 2.6 and 8.5. The changes in the fig area for Mexico were analyzed based on the generated models. Under the current climate, 359,575.76 km2 were estimated for 2050, and a loss of area for the excellent category was estimated for both models and scenarios; however, for the MPI-ESM-LR model projected to 2070, an increase of 5.51% and 0.39% was estimated for scenarios 2.6 and 8.5, respectively. The effect of climate change on agronomic species such as figs will be expressed in variations in climatic ranges and areas suitable for their development. The results of this study reveal the negative and positive effects of climate change on fig habitat suitability in Mexico. The dynamics of changes in surface area will be reflected mainly in northern and central Mexico.

Potential global distribution of Setaria italica, an important species for dryland agriculture in the context of climate change

“…These models play an increasingly critical role in predicting species distribution by considering changes in various environmental factors [6,12]. Over ten distinct models, including Bioclim (Bioclimatic Envelope Models), Domain (Domain Models), GARP (Genetic Algorithm for Rule-set Production), MaxEnt (Maximum Entropy Model), etc., have been applied in different fields such as plant protection, utilization, and pest invasion [12][13][14][15][16][17][18]. Notably, the MaxEnt model has several advantages over its counterparts: (1) it requires only a single distribution record during modeling, (2) it accommodates both continuous and discrete variables, (3) it is simple to operate and does not require complex format conversions of species distribution and environmental data, (4) a minimal sample of species "presence" data yields highly effective simulations, and (5) its theoretical foundations are closely related to ecological principles, enhancing understanding of species suitability [1,3,19,20].…”