Making genetic biodiversity measurable

Measures of agro-ecosystems genetic variability are essential to sustain scientific-based actions and policies tending to protect the ecosystem services they provide. To build the genetic variability datum it is necessary to deal with a large number and different types of variables. Molecular mar...

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Publicado en:Revista de la Facultad de Ciencias Agrarias
Autores principales: Balzarini, Mónica, Bruno, Cecilia, Peña, Andrea, Teich, Ingrid
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Acceso en línea:https://bdigital.uncu.edu.ar/fichas.php?idobjeto=3936
descriptores_str_mv
Clustering
Córdoba (Argentina)
Estadísticas agrícolas
Multivariate association
Ordination
Spatial variability
Variabilidad espacial
Variación genética
todos_str_mv 3866
78
eng
UNC_FCA_CEB
UNC_FCA_CEB
UNC_FCA_CEB
UNC_FCA_CRyERAyN
autor_str_mv Balzarini, Mónica
Bruno, Cecilia
Peña, Andrea
Teich, Ingrid
disciplina_str_mv Ciencias agrarias
titulo_str_mv Cuantificando diversidad genética
Making genetic biodiversity measurable
description_str_mv Measures of agro-ecosystems genetic variability are essential to sustain scientific-based actions and policies tending to protect the ecosystem services they provide. To build the genetic variability datum it is necessary to deal with a large number and different types of variables. Molecular marker data is highly dimensional by nature, and frequently additional types of information are obtained, as morphological and physiological traits. This way, genetic variability studies are usually associated with the measurement of several traits on each entity. Multivariate methods are aimed at finding proximities between entities characterized by multiple traits by summarizing information in few synthetic variables. In this work we discuss and illustrate several multivariate methods used for different purposes to build the datum of genetic variability. We include methods applied in studies for exploring the spatial structure of genetic variability and the association of genetic data to other sources of information. Multivariate techniques allow the pursuit of the genetic variability datum, as a unifying notion that merges concepts of type, abundance and distribution of variability at gene level.
Obtener estimaciones confiables de la diversidad genética en los agroecosistemas es esencial para tomar decisiones basadas en el conocimiento científico que permitan proteger los servicios ecosistémicos que éstos brindan. Para construir el dato de variabilidad genética es necesario trabajar con gran cantidad de variables de distinta naturaleza. Los marcadores moleculares proveen datos multidimensionales que generalmente son complementados con otros tipos de información, por ejemplo datos morfológicos o fisiológicos. Así, los estudios sobre variabilidad genética están frecuentemente asociados a la medición de muchos caracteres en una misma entidad biológica. De especial interés son los métodos multivariados diseñados para analizar similitudes entre entidades caracterizadas por múltiples variables que permiten resumir la información en pocas variables sintéticas informativas de la variabilidad total. En este trabajo se discuten e ilustran distintos métodos multivariados utilizados en la construcción del dato de variabilidad genética. Se incluyen métodos aplicados a la exploración de la estructura espacial de la variabilidad genética y métodos para estudiar la asociación de los datos genéticos con otras fuentes de información. Las técnicas multivariadas en esta revisión permiten abordar el problema de construir al dato de variabilidad genética como un concepto donde convergen mediciones sobre tipo, abundancia y distribución de la variabilidad a nivel de genes.
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container_title Revista de la Facultad de Ciencias Agrarias
journal_title_str Revista de la Facultad de Ciencias Agrarias
journal_id_str r-78
container_issue Revista de la Facultad de Ciencias Agrarias
container_volume Vol. 43, no. 1
journal_issue_str Vol. 43, no. 1
tipo_str textuales
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title_full Making genetic biodiversity measurable
title_fullStr Making genetic biodiversity measurable
Making genetic biodiversity measurable
title_full_unstemmed Making genetic biodiversity measurable
Making genetic biodiversity measurable
description Measures of agro-ecosystems genetic variability are essential to sustain scientific-based actions and policies tending to protect the ecosystem services they provide. To build the genetic variability datum it is necessary to deal with a large number and different types of variables. Molecular marker data is highly dimensional by nature, and frequently additional types of information are obtained, as morphological and physiological traits. This way, genetic variability studies are usually associated with the measurement of several traits on each entity. Multivariate methods are aimed at finding proximities between entities characterized by multiple traits by summarizing information in few synthetic variables. In this work we discuss and illustrate several multivariate methods used for different purposes to build the datum of genetic variability. We include methods applied in studies for exploring the spatial structure of genetic variability and the association of genetic data to other sources of information. Multivariate techniques allow the pursuit of the genetic variability datum, as a unifying notion that merges concepts of type, abundance and distribution of variability at gene level.
dependencia_str_mv Facultad de Ciencias Agrarias
title Making genetic biodiversity measurable
spellingShingle Making genetic biodiversity measurable
Clustering
Córdoba (Argentina)
Estadísticas agrícolas
Multivariate association
Ordination
Spatial variability
Variabilidad espacial
Variación genética
Balzarini, Mónica
Bruno, Cecilia
Peña, Andrea
Teich, Ingrid
topic Clustering
Córdoba (Argentina)
Estadísticas agrícolas
Multivariate association
Ordination
Spatial variability
Variabilidad espacial
Variación genética
topic_facet Clustering
Córdoba (Argentina)
Estadísticas agrícolas
Multivariate association
Ordination
Spatial variability
Variabilidad espacial
Variación genética
author Balzarini, Mónica
Bruno, Cecilia
Peña, Andrea
Teich, Ingrid
author_facet Balzarini, Mónica
Bruno, Cecilia
Peña, Andrea
Teich, Ingrid
title_sort Making genetic biodiversity measurable
title_short Making genetic biodiversity measurable
url https://bdigital.uncu.edu.ar/fichas.php?idobjeto=3936
estado_str 3
building Biblioteca Digital
filtrotop_str Biblioteca Digital
collection Artículo de Revista
institution Sistema Integrado de Documentación
indexed_str 2023-04-25 00:38
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