Reconciling hierarchical taxonomy with molecular phylogenies.

Taxonomy has a history dating back to Aristotle (350BC)andhas facilitatedawide rangeofdevelopments in the biological sciences. Linnaeus’ Systema Naturae assumed that organisms were static creations of God and formulated the hierarchical framework of classification that we currently use. Today we know that organisms continuously evolve and it is generally accepted that these hierarchies are arbitrary constructs (Coyne and Orr 2004). The arbitrary nature of these higher taxonomic ranks does not prevent their practical use with regards to cataloguing, and communicating about, biological diversity, provided such arbitrary decisions are made on a consistent basis. However, current taxonomic hierarchies are suggested to be inconsistent, both between and within major clades (Avise and Liu 2011), reflecting the work of systematists with diverging views regarding the constitution of higher taxonomic ranks. In this study, we present a comprehensive analysis of the overall levels of consistency within current higher taxonomic ranks using dated phylogenies for all bird and mammal species. Building on work by Hennig (1966), and proposed by Avise and Johns (1999), “temporal banding” provides an opportunity to assess the consistency of ancestral relationships within and among higher taxonomic ranks, as well as a practical solution to these temporal inconsistencies. Temporal banding standardizes taxonomic ranks by “cutting” dated phylogenies at specified points in time and applying this concept requires comprehensive dated phylogenies, which has so far limited the application of the approach. Here, we apply temporal banding to two vertebrate classes (birds and mammals) and produce standardized error metrics to compare the consistency of existing taxonomic rankswithin and between the two classes.We discuss the implications of error within the phylogenies used, aswell as the practicalities of the temporal banding approach. Taxonomic inconsistencies have implications for our viewon the uniqueness of organisms. Studies of ecology, evolution, and conservation often attempt to cover a particular hierarchical rank (for some examples, see Jonsson et al. 2010; Derryberry et al. 2011; Condamine et al. 2012; Holt et al. 2013). These approaches all implicitly assume that hierarchical ranks are to some extent comparable across taxa and some studies even make the assumption explicit by using these categories as units of study (e.g., Lagomarcino and Miller 2012; Rueda et al. 2013). Although the extensive use of current taxonomic rankings demonstrates both their practical benefits and scientific importance, the fact that no attempt has been made to delimit higher rankings consistently is cause for concern (Hennig 1966; de Queiroz and Gauthier 1992; Avise and Liu 2011). We intuitively assume that hierarchical ranks reflect similar temporal evolutionary histories across different taxa, but this is commonly not the case. For example, the age of orders may vary by more than 400 myr between vertebrates and invertebrates (Avise and Liu 2011). Heated debates have proved that it is not a trivial task to produce taxonomies that convey information about the evolutionary history of organisms on Earth (Hennig 1966; Mayr 1974; de Queiroz and Cantino 2001). These debates have centered on the evolutionary theory that should underpin the assignment of taxonomic ranks, with the two main competing views focusing on either the identification of lineages entering new adaptive zones or the identification of clades (Mayr 1974). Although both of these views represent a valid approach to rank taxonomic delimitation in theory, the practical application of these concepts requires relevant data for the focal organisms, as well as an analytical approach that can use such data to delimit taxonomies in a systematic manner. In the absence of such an objective analytical approach, higher taxonomic ranks cannot be expected to represent comparable biological units. Taxonomic inconsistencies have the potential to bias the results of scientific studies, as well as adversely influencing scientific prioritization and comparisons across studies. Consequently, new opportunities to