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resumen

Resumen
Ecological sites are a classification of local-land types based on differences in important environmental factors including soil properties, slope and landscape position within a geomorphologic and climatic zone. The concept is pivotal to conduct adaptative management in arid rangelands because it defines homogeneous areas over which specific soil-vegetation-disturbance dynamic occurs. Geomorphon is a computationally efficient method that uses Digital [ver mas...]
dc.contributor.authorCoria, Rubén Darío
dc.contributor.authorBrungard, Colby
dc.contributor.authorVizgarra, Lidia Amanda
dc.contributor.authorMoretti, Lucas Martin
dc.contributor.authorSchulz, Guillermo
dc.contributor.authorRodriguez, Dario Martin
dc.date.accessioned2024-09-25T11:45:52Z
dc.date.available2024-09-25T11:45:52Z
dc.date.issued2024-09-19
dc.identifier.issn0341-8162
dc.identifier.issn1872-6887
dc.identifier.otherhttps://doi.org/10.1016/j.catena.2024.108409
dc.identifier.urihttp://hdl.handle.net/20.500.12123/19538
dc.identifier.urihttps://www.sciencedirect.com/science/article/abs/pii/S0341816224006064
dc.description.abstractEcological sites are a classification of local-land types based on differences in important environmental factors including soil properties, slope and landscape position within a geomorphologic and climatic zone. The concept is pivotal to conduct adaptative management in arid rangelands because it defines homogeneous areas over which specific soil-vegetation-disturbance dynamic occurs. Geomorphon is a computationally efficient method that uses Digital Elevation Models (DEMs) for the classification of landforms at multiple scales. The objective of this study was to evaluate the accuracy of the geomorphon approach to map ecological sites in a 11,259-ha study area within the Dry Chaco region of Argentina, utilizing local topographic positions along soil catena as a predictor of broader ecological sites classes. We used two DEM pixel resolutions (12.5 m and 30 m) and optimized the flatness threshold (t) and search radius (L) geomorphon parameters. As “ground truth” we used legacy data of 62 soil profiles descriptions. The geomorphon elements detected were reclassified into the three main ecological sites of the study area: highlands, midlands and lowlands. We used the overall disagreement (D) as the main metric for evaluating the accuracy of ecological site classifications. We found that: i) the lowest t value (0.05◦) captured subtle topographical changes and thus more effectively reflected the soil-landscape relationship, and ii) larger L values paired with the lower pixel resolution (30 m) diminished the impact of minor landforms, improving the accuracy of ecological site detections. We determined that the geomorphon model with the pixel resolution of 30 m, t-value of 0.05◦, and L-value of 12 produced the ecological site classification map with the highest accuracy, achieving a moderate-high accuracy (D of 33.9 %). Our study suggests that the geomorphon approach shows potential for consistent, reproducible and easily updatable ecological site mapping over larger areas.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/es_AR
dc.sourceCatena 246 : 108409. (November 2024)es_AR
dc.subjectLandformseng
dc.subjectFormas del Terrenoes_AR
dc.subjectEcología
dc.subjectEcologyeng
dc.subject.otherRegión Chaqueña Semiáridaes_AR
dc.subject.otherEcological Siteseng
dc.subject.otherSitios Ecológicoses_AR
dc.subject.otherGeomorphoneng
dc.subject.otherGeomorfonaes_AR
dc.titleAccuracy assessment of the geomorphon approach to detect ecological sites in the Dry Chaco region of Argentinaes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)es_AR
dc.description.origenInstituto de Suelos
dc.description.filFil: Coria, Rubén D. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santiago del Estero; Argentinaes_AR
dc.description.filFil: Brungard, Colby. New Mexico State University; Estados Unidoses_AR
dc.description.filFil: Vizgarra, Lidia Amalia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santiago del Estero; Argentinaes_AR
dc.description.filFil: Moretti, Lucas Martín. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Cerro Azul; Argentinaes_AR
dc.description.filFil: Schulz, Guillermo Andrés. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentinaes_AR
dc.description.filFil: Rodríguez, Darío Martín. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentinaes_AR
dc.subtypecientifico


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