Abstract
Objective: Develop a mathematical model to predict the loss of organic carbon in high Andean micro-watersheds of Sangay National Park. Method: The model is based on the analysis of soil physicochemical variables, such as carbon content and carbon/nitrogen ratio (C_N), which is an indicator of soil quality. Using multiple linear regression techniques, the model evaluates the impact of factors such as carbon and nitrogen content on COS loss, with predictions adjusted to two depths: 30 cm and 60 cm, complying with the requirements of normality, homoscedasticity and statistical independence, and explaining a high variability in the behavior of COS and the C_N ratio under different conditions. Results and Discussion: The results highlight the influence of key factors such as nitrogen percentage and relative density on carbon sequestration, and reveal that nutrient-rich soils show greater resistance to erosion, while soil compaction negatively affects the C_N ratio and reduces carbon storage capacity. Furthermore, the study suggests that COS in deep layers, such as at 60 cm, is more stable and less vulnerable to surface erosion. These findings strengthen the proposed model as a reliable quantitative predictive tool for the conservation of high Andean soils against water erosion and provide a comprehensive analysis of carbon dynamics in high mountain soils. Finally, this study provides a robust mathematical model for monitoring soil organic carbon (COS) dynamics in high Andean soils subject to water erosion. The physicochemical variables analyzed allow a comprehensive approach to accurately estimate COS loss and the carbon-nitrogen (C_N) ratio. In addition, these variables offer practical guidelines to anticipate and mitigate the effects of water erosion and promote sustainability in vulnerable high mountain ecosystems. Research Implications: The main complications of the current study were the climatic conditions of the study area, since at times it was extremely cold with temperatures below 0º. In addition, the cost of using the laboratory to obtain the results of the samples obtained in the field. Also, by including agricultural areas within our study area, there were complications related to the owners of the areas, however, we were able to reach an agreement through our own economic resources. Finally, limited time was an important constraint to obtain more robust results. Originality/Value: The originality of this article consists in the correct execution of a model based on the analysis of soil physicochemical variables and the obtaining of results in a study area with remote complexity with respect to its climatic conditions.
Published Version
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