Bibliographic citations
Llanos, G., (2024). Dinámica del stock del carbono orgánico del suelo en los ecosistemas del área de conservación privada Tilacancha, Amazonas, Perú [Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/6469
Llanos, G., Dinámica del stock del carbono orgánico del suelo en los ecosistemas del área de conservación privada Tilacancha, Amazonas, Perú []. PE: Universidad Nacional Agraria La Molina; 2024. https://hdl.handle.net/20.500.12996/6469
@misc{renati/247875,
title = "Dinámica del stock del carbono orgánico del suelo en los ecosistemas del área de conservación privada Tilacancha, Amazonas, Perú",
author = "Llanos Sánchez, Grecia Ximena",
publisher = "Universidad Nacional Agraria La Molina",
year = "2024"
}
Soil organic carbon (SOC) is decisive in the productivity of ecosystems since it impacts fertility and the ability to sequester atmospheric carbon in the soil. At the same time, soil carbon dynamics and sequestration are subject to the interaction of biological, chemical, and physical factors, with anthropic activity being one of the main changes significantly affecting soil organic carbon content. Therefore, in the last decade, research on soil carbon dynamics has focused more on the analysis of active carbon fractions in various ecosystems. Tilacancha Private Conservation Area preserves Amazon's ecosystems that provide valuable ecosystem services. Evaluating the dynamics of soil carbon stocks is vital to studying the carbon sequestration service. Thus, the variations in soil carbon stocks over time were assessed in Tilacancha Private Conservation Area's ecosystems. The methodology consisted of extracting georeferenced soil samples in the ecosystems of the Tilacancha Conservation Area to analyze the content of total organic carbon, active carbon, and bulk density, thereby calculating the stock of total and active soil carbon. In parallel, information on the reflectance of the earth's surface was extracted from the Landsat 8 satellite for the years 2013 to 2021. The randomforest model was used to relate carbon stocks to satellite images from sampling years. The model was applied on data from 2013 to 2020 to predict carbon stocks and thereby graph the dynamics. The result shows that the dynamics of total and active organic carbon stocks are constant between the years of study. To enhance carbon storage, it is recommended to adopt soil conservation and management practices.
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