Inferring Population Genetic Structure in Widely and Continuously Distributed Carnivores: The Stone Marten (Martes foina) as a Case Study

The stone marten is a widely distributed mustelid in the Palaearctic region that exhibits variable habitat preferences in different parts of its range. The species is a Holocene immigrant from southwest Asia which, according to fossil remains, followed the expansion of the Neolithic farming cultures into Europe and possibly colonized the Iberian Peninsula during the Early Neolithic (ca. 7,000 years BP). However, the population genetic structure and historical biogeography of this generalist carnivore remains essentially unknown. In this study we have combined mitochondrial DNA (mtDNA) sequencing (621 bp) and microsatellite genotyping (23 polymorphic markers) to infer the population genetic structure of the stone marten within the Iberian Peninsula. The mtDNA data revealed low haplotype and nucleotide diversities and a lack of phylogeographic structure, most likely due to a recent colonization of the Iberian Peninsula by a few mtDNA lineages during the Early Neolithic. The microsatellite data set was analysed with a) spatial and non-spatial Bayesian individual-based clustering (IBC) approaches (STRUCTURE, TESS, BAPS and GENELAND), and b) multivariate methods [discriminant analysis of principal components (DAPC) and spatial principal component analysis (sPCA)]. Additionally, because isolation by distance (IBD) is a common spatial genetic pattern in mobile and continuously distributed species and it may represent a challenge to the performance of the above methods, the microsatellite data set was tested for its presence. Overall, the genetic structure of the stone marten in the Iberian Peninsula was characterized by a NE-SW spatial pattern of IBD, and this may explain the observed disagreement between clustering solutions obtained by the different IBC methods. However, there was significant indication for contemporary genetic structuring, albeit weak, into at least three different subpopulations. The detected subdivision could be attributed to the influence of the rivers Ebro, Tagus and Guadiana, suggesting that main watercourses in the Iberian Peninsula may act as semi-permeable barriers to gene flow in stone martens. To our knowledge, this is the first phylogeographic and population genetic study of the species at a broad regional scale. We also wanted to make the case for the importance and benefits of using and comparing multiple different clustering and multivariate methods in spatial genetic analyses of mobile and continuously distributed species.

Análisis de los viveros de empresas en Galicia según su orientación tecnológica o generalista

[ES] El objetivo del presente trabajo consiste en analizar la contribución de los viveros de empresas a la economía gallega desglosando entre tecnológicos y generalistas, y si realmente los primeros contribuyen en mayor medida al desarrollo económico que los no tecnológicos. Para ello, se hará una revisión de la literatura que permita conceptualizar la innovación, innovación tecnológica y empresas de base tecnológica. Posteriormente se identificarán los criterios que permitan clasificar a los viveros en tecnológicos y generalistas, se analizarán sus características, propiedad, modelos de gestión, ubicaciones, requisitos de entrada, oferta de servicios, espacios ofertados, años de funcionamiento, así como se estudiarán los recursos económicos, ingresos propios y dependencia de fondos públicos, espacio físicos para los emprendedores, zonas comunes y los recursos humanos asociados por tipo de viveros. Otro apartado será analizar el perfil del emprendedor según el vivero, tipo de actividad desempeñada, género, edad, formación, dificultades para emprender. Finalmente se analizarán las contribuciones por tipo vivero a través de los indicadores de creación de empresas, generación de puestos de trabajo y sostenibilidad empresarial, usando el método de comparación de muestras independientes, con la prueba de Levene para la igualdad de varianzas, tratado con el paquete estadístico SPSS en su versión 22.0.0.0 Terminaremos con las principales conclusiones del presente trabajo.