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An area of endemism is defined by the spatial congruence among two or more species with distributions that are limited by barriers. In this study, we explored and discussed the use of the network analysis method (NAM) and neighbor-joining (NJ) to analyze the areas of endemism of Quercus sect. Lobatae (red oak species) in Mexico and Central America. We compared the NAM and NJ with other methods commonly used in biogeographic studies to show the advantages of these new approaches and to identify the shortcomings of other approaches. The NAM used in this study is based on notions of centrality measures, such as betweenness. We incorporated the strength of the ties within the internal networks through p-cores and aggregate constraints in iterative analyses. The NAM based on betweenness is ideal for recognizing completely allopatric areas of endemism. The iterative NAMs increase the number of possible areas of endemism because they minimize the effect of minimal overlap, and the p-core is efficient at identifying the closest relationships among species in the cases in which betweenness is not informative. The number of areas of endemism increases when the sympatry matrix minimizes the dispersal effect and the sample effort is maximized, allowing the identification of the greatest number of these areas. The NJ method supports the idea that areas diverge among themselves in a differential way; the long branches correspond to zones with high speciation rates and complex histories (biotic and tectonic), and the short branches correspond to zones with low speciation rates and simple histories. In a classification scheme, NJ was capable of identifying the areas that are considered biotically complex because of their high speciation rates. The results obtained with the NAM and NJ showed that the physiographic regions of Mexico are not natural units and that many of them are composed of at least two different biotic components. [ABSTRACT FROM AUTHOR]

Geometric morphometric techniques allow for the direct quantification and analysis of variation in biological shape and have been used in studies in systematic biology. However, these techniques have not been used for species discrimination in the gastropod genus Conus, a major taxon of significant tropical reef predators recognized for their peptide-based toxins. Here, we used landmark digitization and analysis to show that five species commonly studied for their conotoxins - Conus consors, Conus miles, Conus stercusmuscarum, Conus striatus, and Conus textile - can be effectively distinguished from each other by their shape, as manifested in the results of a principal components analysis (PCA) and the generated thin-plate splines. Two piscivorous species, C. stercusmuscarum and C. striatus, show clear overlaps in the PCA plot, although each taxon clusters within itself, as does each of the others. The loadings on the first two principal components show that the forms of the shells' aperture and spire are particularly important for discrimination. Phylogenetic analysis using neighbour-joining methods shows that group separations are comparable with published phylogenetic schemes based on molecular data and feeding mode (i.e. piscivory, vermivory, molluscivory). The results of this study establish the utility of geometric morphometric methods in capturing the interspecific differences in shell form in the genus Conus. This may lead to the utilization of these methods on other gastropod taxa and the creation of species-recognition programs based on shell shape. © 2012 The Linnean Society of London, Zoological Journal of the Linnean Society, 2012, 165, 296-310. [ABSTRACT FROM AUTHOR]

There are many examples of groups (such as birds, bees, mammals, multicellular animals, and flowering plants) that have undergone a rapid radiation. In such cases, where there is a combination of short internal and long external branches, correctly estimating and rooting phylogenetic trees is known to be a difficult problem. In this simulation study, we tested the performances of different phylogenetic methods at estimating a tree that models a rapid radiation. We found that maximum likelihood, corrected and uncorrected neighbor-joining, and corrected and uncorrected parsimony, all suffer from biases toward specific tree topologies. In addition, we found that using a single-taxon outgroup to root a tree frequently disrupts an otherwise correct ingroup phylogeny. Moreover, for uncorrected parsimony, we found cases where several individual trees (in which the outgroup was placed incorrectly) were selected more frequently than the correct tree. Even for parameter settings where the correct tree was selected most frequently when using extremely long sequences, for sequences of up to 60,000 nucleotides the incorrectly rooted trees were each selected more frequently than the correct tree. For all the cases tested here, tree estimation using a two taxon outgroup was more accurate than when using a single-taxon outgroup. However, the ingroup was most accurately recovered when no outgroup was used. [ABSTRACT FROM PUBLISHER]