Biological taxon names are descriptive names.

The so-called 'type method' widely employed in biological taxonomy is often seen as conforming to the causal-historical theory of reference. In this paper, I argue for an alternative account of reference for biological nomenclature in which taxon names are understood as descriptive names (the 'DN account'). A descriptive name, as the concept came to be known from the work of Gareth Evans, is a referring expression introduced by a definite description. There are three main differences between the DN and the causal account. First, according to the DN account, rather than fixing a name to a referent, the assignment of a type specimen to serve as the name-bearer for a taxon should be seen as performatively establishing a synonymy between a name and a definite description of the form "the taxon whose type is t". Each taxon name is therefore associated with a criterion of application, a semantic rule that establishes the connection between the name and the descriptive content. This is the second major difference from the causal account: taxon names do have some descriptive content associated with them. The final locus of dissent concerns the strength of the modality resulting from the usage of taxon names. In order to address this point, I use the DN account to focus on the debate between Matt Haber and Joeri Witteveen concerning misidentification of type specimens, misapplication of names, and the truth conditions of Joseph LaPorte's de dicto necessary sentence "Necessarily, any species with a type specimen contains its type specimen". Using a pragmatic variant of the distinction between attributive and referential uses of descriptions, I argue that a metalinguistic version of the de dicto sentence is in fact falsified, as previously argued by Haber.

Comparison of complex networks and tree-based methods of phylogenetic analysis and proposal of a bootstrap method.

Complex networks have been successfully applied to the characterization and modeling of complex systems in several distinct areas of Biological Sciences. Nevertheless, their utilization in phylogenetic analysis still needs to be widely tested, using different molecular data sets and taxonomic groups, and, also, by comparing complex networks approach to current methods in phylogenetic analysis. In this work, we compare all the four main methods of phylogenetic analysis (distance, maximum parsimony, maximum likelihood, and Bayesian) with a complex networks method that has been used to provide a phylogenetic classification based on a large number of protein sequences as those related to the chitin metabolic pathway and ATP-synthase subunits. In order to perform a close comparison to these methods, we selected Basidiomycota fungi as the taxonomic group and used a high-quality, manually curated and characterized database of chitin synthase sequences. This enzymatic protein plays a key role in the synthesis of one of the exclusive features of the fungal cell wall: the presence of chitin. The communities (modules) detected by the complex network method corresponded exactly to the groups retrieved by the phylogenetic inference methods. Additionally, we propose a bootstrap method for the complex network approach. The statistical results we have obtained with this method were also close to those obtained using traditional bootstrap methods.