Abstract
Existing models for assigning species, subspecies, or no taxonomic rank to populations which are geographically separated from one another were analyzed. This was done by subjecting over 3,000 pairwise comparisons of vocal or biometric data based on birds to a variety of statistical tests that have been proposed as measures of differentiation. One current model which aims to test diagnosability (Isler et al. 1998) is highly conservative, applying a hard cut-off, which excludes from consideration differentiation below diagnosis. It also includes non-overlap as a requirement, a measure which penalizes increases to sample size. The “species scoring” model of Tobias et al. (2010) involves less drastic cut-offs, but unlike Isler et al. (1998), does not control adequately for sample size and attributes scores in many cases to differentiation which is not statistically significant. Four different models of assessing effect sizes were analyzed: using both pooled and unpooled standard deviations and controlling for sample size using t-distributions or omitting to do so. Pooled standard deviations produced more conservative effect sizes when uncontrolled for sample size but less conservative effect sizes when so controlled. Pooled models require assumptions to be made that are typically elusive or unsupported for taxonomic studies. Modifications to improving these frameworks are proposed, including: (i) introducing statistical significance as a gateway to attributing any weighting to findings of differentiation; (ii) abandoning non-overlap as a test; (iii) recalibrating Tobias et al. (2010) scores based on effect sizes controlled for sample size using t-distributions. A new universal method is proposed for measuring differentiation in taxonomy using continuous variables and a formula is proposed for ranking allopatric populations. This is based first on calculating effect sizes using unpooled standard deviations, controlled for sample size using t-distributions, for a series of different variables. All non-significant results are excluded by scoring them as zero. Distance between any two populations is calculated using Euclidian summation of non-zeroed effect size scores. If the score of an allopatric pair exceeds that of a related sympatric pair, then the allopatric population can be ranked as species and, if not, then at most subspecies rank should be assigned. A spreadsheet has been programmed and is being made available which allows this and other tests of differentiation and rank studied in this paper to be rapidly analyzed.
Highlights
This paper aims to help address the “allopatric problem” when determining species rank in taxonomic science
Results for effect sizes divided into buckets of 2d are set out in Tables 10–11 for each of the four effect size measures used in the study, in each case for both voice and biometrics
The dataset studied here exhibits comparable overall levels of variation to Tobias et al (2010)’s data set. The latter was developed using sympatric species pairs on a global basis. This data set involves comparisons of many populations that are currently recognized as subspecies and several of which are unnamed (Table 1)
Summary
As defined by Ray (1686): “no matter what variations occur in the individuals or the species, if they spring from the seed of one and the same plant, they are accidental variations and not such as to distinguish a species. Animals likewise that differ preserve their distinct species permanently; one species never springs from the seed of another nor vice versa.”. Sympatric species, which occur together in the same place during the breeding season but do not successfully interbreed to any material extent, are demonstrably real. With enough data and persistence, it is usually possible to determine whether or not sympatric populations interbreed regularly and whether they produce fertile offspring (Mayr 1940) and whether or not the two populations are reproductively isolated. Where hybridization is rare or occurs in narrow zones, this can cause difficulties in delimiting species and may need judgment to be applied
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