Spectral prints in charcoals: reconstructing the eruptive history of Doña Juana volcano
Low-latitude volcanoes impose significant challenges for reconstructing their geological histories due to heavy precipitation and weathering, dense vegetation, complex topography and scarce outcrops, limiting traditional approaches and mapping techniques. Developing alternative tools to address thes...
- Autores:
-
Reinoso, Santiago
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2024
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/75931
- Acceso en línea:
- https://hdl.handle.net/1992/75931
- Palabra clave:
- Volcano
FTIR
Spectra
Doña Juana Volcanic complex
Biología
- Rights
- openAccess
- License
- Attribution 4.0 International
| Summary: | Low-latitude volcanoes impose significant challenges for reconstructing their geological histories due to heavy precipitation and weathering, dense vegetation, complex topography and scarce outcrops, limiting traditional approaches and mapping techniques. Developing alternative tools to address these challenges is critical for risk assessment and volcanic hazard in these regions. Organic materials, such as buried woods and ancient charcoal, frequently preserved in these environments, emerge as viable archives for understanding volcanic histories including flow and pyroclastic density currents (PDCs) temperatures, topography changes, and ages of eruptions. This study explores the application of Fourier Transform Infrared Spectroscopy (FTIR-IR) to reconstruct chemical changes of charcoal (n=40) collected from the Doña Juana Volcanic Complex (Nariño, Colombia) associated to different topographic settings and different eruption phases during the Holocene. Samples span diverse ages, altitude gradients, and locations, with a modern charcoal database aiding the identification of temperature-topography associations. Key chemical spectral patterns were analyzed using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA), revealing a model with ~60% predictive accuracy and robust confidence intervals. This accessible, low-cost approach demonstrates significant potential for regions with underdeveloped methodologies, offering a practical solution for refining sampling strategies and improving volcanic hazard assessments, with predictive power expected to increase as more data become available. |
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