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Data for: Increasing information content and diagnosability in family-level classifications

<p>Higher-level classifications often must account for monotypic taxa representing depauperate evolutionary lineages and lacking synapomorphies of their better-known, well-defined sister clades. In a ranked (Linnean) or unranked (phylogenetic) classification system, discovering such a depauperate taxon does not necessarily invalidate the rank classification of sister clades. Named higher taxa must be monophyletic to be phylogenetically valid. Ranked taxa above the species level should also maximize information content, diagnosability, and utility (e.g., in biodiversity conservation). In spider classification, families are the highest rank that is systematically catalogued, and <em>incertae</em> <em>sedis</em> is not allowed. Consequently, it is important that family-level taxa be well-defined and informative. We revisit the classification problem of Orbipurae, an unranked suprafamilial clade containing the spider families Nephilidae, Phonognathidae, and Araneidae <em>sensu</em> <em>stricto</em>. We argue that, to maximize diagnosability, information content, conservation utility, and practical taxonomic considerations, this "splitting" scheme is superior to its recently proposed alternative, which lumps these families together as Araneidae <em>sensu</em> <em>lato</em>. We propose to redefine Araneidae and recognize a monogeneric spider family, Paraplectanoididae fam. nov. to accommodate the depauperate lineage <em>Paraplectanoides</em>. We present new subgenomic data to stabilize Orbipurae topology which also supports our proposed family-level classification. Our example from spiders demonstrates why classifications must be able to accommodate depauperate evolutionary lineages, e.g., <em>Paraplectanoides</em>. Finally, although clade age should not be a criterion to determine rank, other things being equal, comparable ages of similarly ranked taxa do benefit comparative biology.</p>

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36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
12
Access
12
Reuse readiness
0
Engagement
8

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