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Article

Episodes 2023; 46(3): 341-359

Published online September 1, 2023

https://doi.org/10.18814/epiiugs/2022/022034

Copyright © International Union of Geological Sciences.

GIS-based methodology for mapping and modeling microbialite deposits in high mountain lakes and wetlands of Central Andes (Catamarca, Northwestern Argentina)

Patricio Guillermo Villafañe1,2*, Carlos Cónsole-Gonella2,†, María Eugenia Farías1, Luis Gabriel Ahumada3, Francisco Javier Ruiz Sánchez4

1Laboratorio de Investigaciones Microbiológicas de Lagunas Andinas (LIMLA), Planta Piloto de Procesos Industriales Microbiológicos (PROIMI), CONICET, Tucumán, Argentina
2Instituto Superior de Correlación Geológica (INSUGEO), CONICET- Universidad Nacional de Tucumán, Tucumán, Argentina
3Puna Argentina Foundation, Salta, Argentina
4Department of Botany and Geology, Universitat de València, València, España
Deceased

Correspondence to:*E-mail: pgvillafan@gmail.com

Received: January 27, 2022; Revised: August 11, 2022; Accepted: August 11, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Modern microbialites in Argentina’s Puna (Central Andes) are considered a reliable tool for understanding the evolution of early life on our planet and developing strategies for detecting life on Mars. The morphological, structural and geochemical variations in these deposits, together with their distribution and architecture, are some of the most important parameters for understanding and characterising them. However, the lack of appropriate cartography and/or the high price to access it, added to the complex geological and geomorphological context in this region, complicate a traditional mapping on a good scale of detail. This paper presents a GIS-based methodology for a detailed mapping and architectural modeling of Las Quínoas microbialitic deposit (Holocene). To meet this objective, the geoprocessing of the information obtained from drone surveys, fieldwork and laboratory work, is carried out using ArcGIS software. The result is a high-resolution reconstruction of the deposit architecture, together with several thematic maps that represent the variation of the morphological, structural and geochemical characteristics of the oncoids (microbialites) with respect to depth and their position in the water body. From an integral point of view, this work provides a new methodological approach for microbialites mapping and improves the survey strategies in Central Andes.

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