Summary: Frequency of singletons – species represented by single individuals – is anomalously high in most large tropical arthropod surveys (average, 32%). We sampled 5965 adult spiders of 352 species (29% singletons) from 1 ha of lowland tropical moist forest in Guyana. Four common hypotheses (small body size, male‐biased sex ratio, cryptic habits, clumped distributions) failed to explain singleton frequency. Singletons are larger than other species, not gender‐biased, share no particular lifestyle, and are not clumped at 0·25–1 ha scales. Monte Carlo simulation of the best‐fit lognormal community shows that the observed data fit a random sample from a community of ~700 species and 1–2 million individuals, implying approximately 4% true singleton frequency. Undersampling causes systematic negative bias of species richness, and should be the default null hypothesis for singleton frequencies. Drastically greater sampling intensity in tropical arthropod inventory studies is required to yield realistic species richness estimates. The lognormal distribution deserves greater consideration as a richness estimator when undersampling bias is severe.

The concept of semantic tagging and its potential for semantic enhancements to taxonomic papers is outlined and illustrated by four exemplar papers published in

When parsimony ancestral character reconstruction is ambiguous, it is often resolved in favour of the more complex character state. Hence, secondary loss (secondary “absence”) of a complex feature is favoured over parallel gains of that feature as this preserves the stronger hypothesis of homology. We believe that such asymmetry in character state complexity is important information for understanding character evolution in general. However, we here point out an inappropriate link that is commonly made between this approach and the accelerated transformation (ACCTRAN) algorithm. In ACCTRAN, changes are assigned along branches of a phylogenetic tree as close to the root as possible. This has been taken to imply that ACCTRAN will minimize hypotheses of parallel origins of complex traits and thus that ACCTRAN is philosophically better justified than the alternatives, such as delayed transformation (DELTRAN), where changes are assigned along branches as close to the tips as possible. We provide simple examples to show that such views are mistaken and that neither ACCTRAN nor DELTRAN consistently minimize parallel gain of complex traits. We therefore do not see theoretical grounds for favouring the popular ACCTRAN algorithm.© The Willi Hennig Society 2008.