Remote sensing techniques to identify and characterize forage communities in a livestock system in the hyper-arid desert of San Juan (Argentina)

Background and aims: The natural grasslands of arid zones cover 40% of the earth's surface and are a valuable source of forage for livestock. Inappropriate management and high livestock loads are among the factors responsible for their degradation. In this sense, a fast evaluation is essential...

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Autores principales: Tapia, Raúl E., Carmona Crocco, Julieta, Martinelli, Mariana
Formato: Artículo revista
Lenguaje:Español
Publicado: Sociedad Argentina de Botánica 2020
Materias:
Acceso en línea:https://revistas.unc.edu.ar/index.php/BSAB/article/view/29322
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record_format ojs
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-10
container_title_str Revistas de la UNC
language Español
format Artículo revista
topic vegetation cover
natural grassland
remote sensing
drylands
cobertura vegetal
pastizal natural
zonas áridas
spellingShingle vegetation cover
natural grassland
remote sensing
drylands
cobertura vegetal
pastizal natural
zonas áridas
Tapia, Raúl E.
Carmona Crocco, Julieta
Martinelli, Mariana
Remote sensing techniques to identify and characterize forage communities in a livestock system in the hyper-arid desert of San Juan (Argentina)
topic_facet vegetation cover
natural grassland
remote sensing
drylands
cobertura vegetal
pastizal natural
zonas áridas
author Tapia, Raúl E.
Carmona Crocco, Julieta
Martinelli, Mariana
author_facet Tapia, Raúl E.
Carmona Crocco, Julieta
Martinelli, Mariana
author_sort Tapia, Raúl E.
title Remote sensing techniques to identify and characterize forage communities in a livestock system in the hyper-arid desert of San Juan (Argentina)
title_short Remote sensing techniques to identify and characterize forage communities in a livestock system in the hyper-arid desert of San Juan (Argentina)
title_full Remote sensing techniques to identify and characterize forage communities in a livestock system in the hyper-arid desert of San Juan (Argentina)
title_fullStr Remote sensing techniques to identify and characterize forage communities in a livestock system in the hyper-arid desert of San Juan (Argentina)
title_full_unstemmed Remote sensing techniques to identify and characterize forage communities in a livestock system in the hyper-arid desert of San Juan (Argentina)
title_sort remote sensing techniques to identify and characterize forage communities in a livestock system in the hyper-arid desert of san juan (argentina)
description Background and aims: The natural grasslands of arid zones cover 40% of the earth's surface and are a valuable source of forage for livestock. Inappropriate management and high livestock loads are among the factors responsible for their degradation. In this sense, a fast evaluation is essential to correct its use and promote conservation. The objective of the study was to identify and characterize, through satellite image processing and fieldwork, forage plant communities in a rainfed livestock system of San Juan. M&M: Indicator variables of soil and vegetation were generated from a Landsat 8 OLI image. Subsequently, unsupervised kmeans classification was performed. On field, plant cover, mulch and percentage of bare soil were registered from linear transects. Finally, the livestock receptivity of the plant communities was estimated. Results: 3 types of coverage were identified: coverage higher than 50%; higher than 20% and less than 50% and less than 20%. Also, two forage communities were identified, Lamaral and Zampal. In Lamaral, Prosopis alpataco var lamaro obtained a coverage of 48%, a receptivity of 2.21 hectare/goat equivalent. In Zampal, a 35% coverage of Atriplex undulata was registered and the receptivity was 1.80 hectare/goat equivalent. Conclusions: The digital processing carried out was adequate for the purpose of the study and allowed recognizing, characterizing and mapping two forage communities. The richness of the species was low, with a predominance of shrubs and woody plants, limiting livestock in the area.
publisher Sociedad Argentina de Botánica
publishDate 2020
url https://revistas.unc.edu.ar/index.php/BSAB/article/view/29322
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