Modelación de Nichos Ecológicos bajo dos escenarios de cambio Climático para Maíz Chulpi (zea mays) en la Provincia de Cotopaxi, en el periodo 2019-2020. - Chimborazo Taipicaña, Erika Alexandra (2020)
The main aim of this research project was to model the current and future potential distribution of the chulpi corn kind (Zea mays) in the Cotopaxi Province, with the help of the MaxEnt program, it was possible to determine the areas with probabilities of adaptation of the species. For this, the maximum entropy distribution modeling method (MaxEnt) version 3.4.1 was used, it was worked with 44 records of the presence of chulpi corn and bioclimatic variables downloaded from the WorldClim platform of these variables, eight were chosen by performing the Pearson correlation In the SPSS statistical program, for the future projection bioclimatic variables were used in two time horizons: year 2050 and 2080 using the global circulation models CCCMA-cgcm3_1t47 and CSIRO-mk3_5 under scenarios A2 and B1. What was obtained models of current and future potential distribution with an appropriate reliability index of AUC (area under the curve) of 0.970, 10 replications were made using the Bootstrap type of execution with a random test of 25% and with 500 interactions, which also could determine the variables with the greatest contribution to the model for the determination of the adaptation of the species which were: Bio2 the temperature range and Bio15 precipitation seasonality. In this way, it was identified that the areas with the greatest probability that the species adapts to environmental conditions are in the rural areas of the Mulalo, Joseguango Bajo, Tanicuchi and Guaytacama parishes, it was also determined that the Pujilí and Sigchos Cantons have very low adaptation probabilities. The results of this model will help with adaptation strategies against climate change for chulpi corn in rural areas of the Cotopaxi Province, in such a way as to seek strategies and good agricultural practices that contribute to reducing the impacts of climate change on production.