Abstrac Background and aims: The genus Acacia has a pantropical distribution and currently consists in approximately 1.450 species throughout the world. In Argentina the species belong to two subgenera: Acacia and Aculeiferum. In this work the morphology of two species was studied, one belonging to the first subgenus, Acacia caven var. caven and Acacia bonariensis, corresponding to the second one. The aim of this study was to evalúate the interspecific and ¡ntraspecific variation based on 12 exomorphological traits. The hypothesis was that the selected traits were able to differentiate species and populations. M&M: The study was based on the Kruskal Wallis test and several analyses with multivariate methods. Results: The Kruskal Wallis test found that nine characters were able to differentiate the species and one the populations. From the multivariate analyses the result was that, except for one character, the remaining ones were significant for the interspecific differentiation. Conclusions: This showed a clear separation between species according to the taxonomic classification already established. However, no differences between reserves could be evidenced for either of the species with these methods. In conclusion, these analyses set a precedent for future studies including more natural populations and the genetic study of the differentiation at molecular level.

Abstract In order to elucidate the role of evolutionary forces in shaping the variation of quantitative traits in Senegalia gilliesii we evaluate seven phenotypic traits in three Argentinean populations, two of them sharing environmental and vegetation type conditions, and a third one ecologically differentiated from the former. The phenotypic traits were compared with molecular markers. Here, we search for signatures of selection by means of the comparison PST-FST. We assessed if the averages of the seven phenotypic traits were different among populations by means of ANOVA and we performed discriminant analysis of principal components (DAPC) for both morphological and molecular data. The ANOVA showed significant results only for two traits. For all foliar traits and two spine traits, the PST-FSTcomparison suggested the occurrence of stabilizing selection. The DAPC obtained from AFLP data showed three well defined groups of populations; when the same analysis was conducted with morphological data the scatterplot showed high overlapping among individuals and could not separate the populations. Overall, our findings suggest a prominent role of stabilizing selection in all foliar traits and stipular spine length. These results could be extrapolated to other tropical and subtropical acacias. Further studies are needed to analyse the mechanisms underlying genetic differentiation in natural populations of S. gilliesii, find its relationship with eco-geographical variables.

Background and aims: Acacia furcatispina belongs to the subgenus Aculeiferum. Currently, there are no studies in population genetics in this species. The aim of this work was to investigate the genetic diversity, population structure and spatial genetic structure at fne scale (SGS) in Argentinean sample sites by means of molecular markers. Materials and Metods: Two sample sites of A. furcatispina were studied with the AFLP technique. Three primer combinations were selected for this study. Results: The three primer combinations revealed a total of 121 AFLP bands. The percentage of polymorphic loci showed a mean value of 86.8 % and the mean heterozygocity was 0.33. The Bayesian analysis performed with software STRUCTURE detected three clusters (K= 3), corresponding one to Pasaje Pozo Zuni (PP) sample site and two for Cerro de la Gloria (CG) sample site, showing a subdivision of this last one (CG1 and CG2). The AMOVA showed that the great component of variability was represented within populations. The SGS detected significant structuration at short and middle distances in PP. Conclusions: Based on the results of the present work, we recommend to sample trees far apart 10 m to minimize the kinship between individuals. These results present the frst study in genetic diversity, population structure and spatial genetic structure at fne scale in A. furcatispina and all the analyses made here result of interest for management and conservation of this species.

Introduccion y objetivos: Acacia furcatispina, pertenece al subgénero Aculeiferum. Actualmente no hay estudios sobre la diversidad y estructura genética de esta especie. El objetivo de este trabajo fue estudiar la diversidad genética, estructura poblacional, y la estructura genética espacial a escala fna (SGS) en localidades argentinas de esta especie. Materiales y metodos: Se estudiaron dos localidades de la especie A. furcatispina mediante la técnica de AFLP. Se seleccionaron 3 combinaciones de cebadores. resultados: Con las combinaciones de cebadores seleccionadas, se revelaron un total de 121 bandas. El porcentaje de loci polimórficos presentó un valor medio de 86,8 % y la heterocigosis 0,33. El análisis bayesiano STRUCTURE mostró que los individuos analizados pertenecen a tres grupos genéticos (K= 3), uno correspondiente a la localidad Pasaje Pozo Zuni (PP) y dos, a Cerro de la Gloria (CG), subdividida en dos poblaciones (CG1 y CG2). El AMOVA indicó que la mayor parte de la variabilidad se encuentra contenida dentro de las poblaciones. El análisis SGS detectó estructuración local significativa a cortas y medianas distancias en la población PP. conclusiones: Basado en los resultados del presente trabajo, se recomienda muestrear árboles a más de 10 metros de distancia para minimizar el parentesco entre individuos. Estos resultados proveen el primer estudio acerca de la diversidad, estructura genética y estructura a escala espacial fna de Acacia furcatispina y todos los análisis realizados resultan de interés para el manejo y conservación de esta especie.

Bayesian clustering as implemented in STRUCTURE or GENELAND software is widely used to form genetic groups of populations or individuals. On the other hand, in order to satisfy the need for less computer-intensive approaches, multivariate analyses are specifically devoted to extracting information from large datasets. In this paper, we report the use of a dataset of AFLP markers belonging to 15 sampling sites of Acacia caven for studying the genetic structure and comparing the consistency of three methods: STRUCTURE, GENELAND and DAPC. Of these methods, DAPC was the fastest one and showed accuracy in inferring the K number of populations (K = 12 using the find.clusters option and K = 15 with a priori information of populations). GENELAND in turn, provides information on the area of membership probabilities for individuals or populations in the space, when coordinates are specified (K = 12). STRUCTURE also inferred the number of K populations and the membership probabilities of individuals based on ancestry, presenting the result K = 11 without prior information of populations and K = 15 using the LOCPRIOR option. Finally, in this work all three methods showed high consistency in estimating the population structure, inferring similar numbers of populations and the membership probabilities of individuals to each group, with a high correlation between each other.