High seed dispersal ability of Pinus canariensis in stands of contrasting density inferred from genotypic data

Aim of the study: Models that combine parentage analysis from molecular data with spatial information of seeds and seedlings provide a framework to describe and identify the factors involved in seed dispersal and recruitment of forest species. In the present study we used a spatially explicit method...

Full description

Bibliographic Details
Main Authors: Unai López de Heredia, Nikos Nanos, Eduardo García-del-Rey, Paula Guzmán, Rosana López, Martin Venturas, Pascual Gil Muñoz, Luis Gil
Format: Article
Language:English
Published: Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria 2015-04-01
Series:Forest Systems
Subjects:
Online Access:http://revistas.inia.es/index.php/fs/article/view/6351/2312
id doaj-72ee8f44c9914485a58358d9d3ce415e
record_format Article
spelling doaj-72ee8f44c9914485a58358d9d3ce415e2020-11-24T23:44:07ZengInstituto Nacional de Investigación y Tecnología Agraria y AlimentariaForest Systems2171-50682171-98452015-04-012401e01510.5424/fs/2015241-06351 High seed dispersal ability of Pinus canariensis in stands of contrasting density inferred from genotypic data Unai López de Heredia0Nikos Nanos1Eduardo García-del-Rey2Paula Guzmán3Rosana López4Martin Venturas5Pascual Gil Muñoz6Luis Gil7Forest Genetics and Ecophysiology Research Group. E.T.S. Forestry Engineering. Technical University of Madrid (UPM). Ciudad Universitaria s/n. 28040. Madrid, Spain Forest Genetics and Ecophysiology Research Group. E.T.S. Forestry Engineering. Technical University of Madrid (UPM). Ciudad Universitaria s/n. 28040. Madrid, Spain Departamento de Ecología, Facultad de Biología, Universidad de La Laguna, 38206 La Laguna, Tenerife, Canary Islands, SpainForest Genetics and Ecophysiology Research Group. E.T.S. Forestry Engineering. Technical University of Madrid (UPM). Ciudad Universitaria s/n. 28040. Madrid, Spain Forest Genetics and Ecophysiology Research Group. E.T.S. Forestry Engineering. Technical University of Madrid (UPM). Ciudad Universitaria s/n. 28040. Madrid, Spain Forest Genetics and Ecophysiology Research Group. E.T.S. Forestry Engineering. Technical University of Madrid (UPM). Ciudad Universitaria s/n. 28040. Madrid, Spain Sección de Montes, Medio Ambiente, Cabildo Insular de Tenerife, Santa Cruz de Tenerife 38200, Canary Islands, SpainForest Genetics and Ecophysiology Research Group. E.T.S. Forestry Engineering. Technical University of Madrid (UPM). Ciudad Universitaria s/n. 28040. Madrid, Spain Aim of the study: Models that combine parentage analysis from molecular data with spatial information of seeds and seedlings provide a framework to describe and identify the factors involved in seed dispersal and recruitment of forest species. In the present study we used a spatially explicit method (the gene shadow model) in order to assess primary and effective dispersal in Pinus canariensis. Area of study: Pinus canariensis is endemic to the Canary Islands (Spain). Sampling sites were a high density forest in southern slopes of Tenerife and a low density stand in South Gran Canaria. Materials and methods: We fitted models based on parentage analysis from seeds and seedlings collected in two sites with contrasting stand density, and then compared the resulting dispersal distributions. Main results: The results showed that: 1) P. canariensis has a remarkable dispersal ability compared to other pine species; 2) there is no discordance between primary and effective dispersals, suggesting limited secondary dispersal by animals and lack of Janzen-Connell effect; and 3) low stand densities enhance the extent of seed dispersal, which was higher in the low density stand. Research highlights: The efficient dispersal mechanism of P. canariensis by wind inferred by the gene shadow model is congruent with indirect measures of gene flow, and has utility in reconstructing past demographic events and in predicting future distribution ranges for the species. http://revistas.inia.es/index.php/fs/article/view/6351/2312Bayesian inferenceCanary Islandsgene shadow modelmicrosatellitesparentage analysis
collection DOAJ
language English
format Article
sources DOAJ
author Unai López de Heredia
Nikos Nanos
Eduardo García-del-Rey
Paula Guzmán
Rosana López
Martin Venturas
Pascual Gil Muñoz
Luis Gil
spellingShingle Unai López de Heredia
Nikos Nanos
Eduardo García-del-Rey
Paula Guzmán
Rosana López
Martin Venturas
Pascual Gil Muñoz
Luis Gil
High seed dispersal ability of Pinus canariensis in stands of contrasting density inferred from genotypic data
Forest Systems
Bayesian inference
Canary Islands
gene shadow model
microsatellites
parentage analysis
author_facet Unai López de Heredia
Nikos Nanos
Eduardo García-del-Rey
Paula Guzmán
Rosana López
Martin Venturas
Pascual Gil Muñoz
Luis Gil
author_sort Unai López de Heredia
title High seed dispersal ability of Pinus canariensis in stands of contrasting density inferred from genotypic data
title_short High seed dispersal ability of Pinus canariensis in stands of contrasting density inferred from genotypic data
title_full High seed dispersal ability of Pinus canariensis in stands of contrasting density inferred from genotypic data
title_fullStr High seed dispersal ability of Pinus canariensis in stands of contrasting density inferred from genotypic data
title_full_unstemmed High seed dispersal ability of Pinus canariensis in stands of contrasting density inferred from genotypic data
title_sort high seed dispersal ability of pinus canariensis in stands of contrasting density inferred from genotypic data
publisher Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria
series Forest Systems
issn 2171-5068
2171-9845
publishDate 2015-04-01
description Aim of the study: Models that combine parentage analysis from molecular data with spatial information of seeds and seedlings provide a framework to describe and identify the factors involved in seed dispersal and recruitment of forest species. In the present study we used a spatially explicit method (the gene shadow model) in order to assess primary and effective dispersal in Pinus canariensis. Area of study: Pinus canariensis is endemic to the Canary Islands (Spain). Sampling sites were a high density forest in southern slopes of Tenerife and a low density stand in South Gran Canaria. Materials and methods: We fitted models based on parentage analysis from seeds and seedlings collected in two sites with contrasting stand density, and then compared the resulting dispersal distributions. Main results: The results showed that: 1) P. canariensis has a remarkable dispersal ability compared to other pine species; 2) there is no discordance between primary and effective dispersals, suggesting limited secondary dispersal by animals and lack of Janzen-Connell effect; and 3) low stand densities enhance the extent of seed dispersal, which was higher in the low density stand. Research highlights: The efficient dispersal mechanism of P. canariensis by wind inferred by the gene shadow model is congruent with indirect measures of gene flow, and has utility in reconstructing past demographic events and in predicting future distribution ranges for the species.
topic Bayesian inference
Canary Islands
gene shadow model
microsatellites
parentage analysis
url http://revistas.inia.es/index.php/fs/article/view/6351/2312
work_keys_str_mv AT unailopezdeheredia highseeddispersalabilityofpinuscanariensisinstandsofcontrastingdensityinferredfromgenotypicdata
AT nikosnanos highseeddispersalabilityofpinuscanariensisinstandsofcontrastingdensityinferredfromgenotypicdata
AT eduardogarciadelrey highseeddispersalabilityofpinuscanariensisinstandsofcontrastingdensityinferredfromgenotypicdata
AT paulaguzman highseeddispersalabilityofpinuscanariensisinstandsofcontrastingdensityinferredfromgenotypicdata
AT rosanalopez highseeddispersalabilityofpinuscanariensisinstandsofcontrastingdensityinferredfromgenotypicdata
AT martinventuras highseeddispersalabilityofpinuscanariensisinstandsofcontrastingdensityinferredfromgenotypicdata
AT pascualgilmunoz highseeddispersalabilityofpinuscanariensisinstandsofcontrastingdensityinferredfromgenotypicdata
AT luisgil highseeddispersalabilityofpinuscanariensisinstandsofcontrastingdensityinferredfromgenotypicdata
_version_ 1725499991858872320