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

• 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: Bayesian inference; Canary Islands; gene shadow model; microsatellites; parentage analysis
• Online Access: http://revistas.inia.es/index.php/fs/article/view/6351/2312
• ISSN: 2171-5068; 2171-9845

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.