Abstract
To develop a dynamic and stochastic model that incorporates verified bio-spheric interactions, in order to calculate allometric equations for the total volumetric growth of Abies religiosa (Kunth) Schltdl. and Cham. and to determine the cumulative distribution of its biomass. This model will be applied to populations of the species in six Mexican states: Mexico, Guerrero, Hidalgo, Michoacán, Oaxaca and Puebla. The study took into account the effects of climate change on these variables. The methodological approach integrated various tools and data sources: SiBiFor numerical databases were used, incorporating NASA Power climate data and applying Ordinary Least Squares statistical models. The Random Forest package was used for predictive analysis and the Ridge Model was implemented with regression techniques, developing algorithms using the R programming language. For volumetric estimation, Newton's equations were applied. The results of the study yielded several important conclusions: allometric equations were developed to estimate the total tree volume in 2023. Linear regression models proved to be particularly relevant in this process. The validity and usefulness of the variables selected for the study were confirmed. The study highlights the importance of understanding and assessing the carbon al-storage capacity of forests, especially in the context of climate change. It also highlights the usefulness of linear regression models and variable validation for estimating carbon sequestration in forests of Abies religiosa (Kunth) Schltdl. and Cham.
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