Land suitability levels for rainfed maize under current conditions and climate change projections in Mexico

Abstract

An assessment of land suitability classes for rainfed maize (spring–summer agricultural cycle) with current climate conditions (1950–2000) and projected climate change scenarios was carried out for Mexico. The method considered the most restrictive factors or agroclimatic requirements from different variables needed by rainfed maize. These factors were analyzed spatially in a geographic information systems (GIS) context, resulting in areas classified into four suitability levels: high, medium, low, and not suitable for maize. We considered two general circulation models (GCM): HADGEM2-ES and MPI-ESM-LR; one radiative forcing concentration representative concentration pathways (RCP) 8.5 Wm−2 and the far period (2075–2099). Results at a national-level analysis showed that under actual conditions, 57.5% of the area of Mexico presents some level of suitability for rainfed maize. The high suitability class is 11.4% of the country, while 20.7% and 25.3% had medium and low suitability levels, respectively. Other results showed that with the HADGEM2-ES and MPI-ESM-LR projections of climate change models, 50.4% and 46.7%, of Mexico’s continental area, respectively, present some level of suitability for the rainfed maize crop. In the first case, with respect to the present climate conditions, the HADGEM2-ES model presented an area decrease of −2.4% and the MPI-ESM-LR model of −5.5% in the high suitability level for the rainfed maize crop. Results at a state-level analysis showed there are five states (Jalisco, Campeche, Oaxaca, Chiapas, and Michoacán) in the interval of more than 50,000 km2 of surface with high and medium suitability levels, with a maximum extent change between the present to the projected climate conditions of −46% for the HADGEM2-ES and −57% for the MPI-ESM-LR. In general, the MPI-ESM-LR model showed the most adverse projected conditions for rainfed maize growth.

Changes in Climate Extremes and Their Effect on Maize (Zea mays L.) Suitability Over Southern Africa

“…For example, Ojara et al (2021) projected that area highly suitable for maize in Eastern Africa will decrease by more than 50% under the RCP8.5 scenario by the mid-century but if extreme indices were included, the decreases could be worse. Many studies have projected maize suitability changes without incorporating extreme variables (Holzkämper et al, 2013;Adisa et al, 2018;Lopez-Blanco et al, 2018;Kogo et al, 2019;Mumo et al, 2021;Yang et al, 2021), and the reported changes may need to be revisited in light of our findings.…”

Evaluating Risk and Possible Adaptations to Climate Change Under a Socio-Ecological System Approach

“…To overcome the climatic challenges for the agricultural sector in the north of Mexico, farmers have implemented irrigation management to grow animal feed crops such as sorghum and wheat, leaving staple foods production to the southern and central Mexico (Eakin et al, 2014b). The south seems prone to be affected not only by climate change (Monterroso et al, 2011;López-Blanco et al, 2018;Murray-Tortarolo et al, 2018) but also by socioeconomic constraints. Southern states of Mexico, like Chiapas, have lagged in investment (Fox and Haight, 2010), and the adoption of mechanization is impossible due to topography restrictions (Eakin et al, 2014c).…”

Geological Resource Planning and Environmental Impact Assessments Based on GIS

“…Bagherzadeh and Gholizadeh [11] Artificial neural network (ANN) Bagherzadeh et al [12] Fuzzy approach Danvi et al [13] Machine learning (ML) Lopez-Blanco et al [14] Fuzzy-based method + ML Raza et al [15] Fuzzy-based method Bhermama et al [16] GIS+ land suitability evaluation (LSE)…”