title: Performance of pairwise shape dissimilarity morphometrics on nonmammalian taxa (Insecta: Neuroptera: Mantispidae).
abstract: Morphometric dissimilarity metrics aim to quantify the variation between compared specimens such that inferences about their relatedness and alpha taxonomy can be made. Recently, the technique has developed metrics that purport to quantify shape dissimilarity between specimens-employing the use of least squares regression analysis. These metrics have been well applied by studies in the hominin fossil record with an arguably unsubstantiated backing for the technique. Originally postulated was the log10 sem metric which subsequently led to the standard error test of the null hypothesis metric. Following this, the standard deviation of logged ratios (SLR ) metric arose as a pairwise dissimilarity metric that constrains the regression to a zero-intercept, that is, a significant development in the robustness of the technique. This metric was tested on extant primates in order to evaluate its effectiveness alongside the two other metrics. It was shown to be the most reliable for comparisons between specimens of primates, but was unable to discriminate between heterospecific and conspecific comparisons. Arguably, an alternative model organism with which to compare the technique is lacking. This study considers shape dissimilarity metrics with respect to a group of nonmammalian organisms (mantidflies) and tests the metrics against three lines of evidence (morphology, CO1-DNA, and geographic distribution) that can delimit the species-level taxonomy for the group. It is shown that the metrics are unable to discriminate between pairwise comparisons of closely related species, resulting in biologically erroneous groupings, and contradicting the groupings derived from morphological, CO1-DNA, and distributional comparisons. It is thus asserted that the technique is unsuitable for use in alpha taxonomy as an additional line of evidence in mantidflies. It is further supposed that morphometrics in general should be employed with caution in studies of evolutionary history as phylogeny is not the only information contained within morphometric data.
authors.affiliation: Department of Zoology and Entomology, University of Pretoria, Hatfield, 0028, South Africa.
authors.forename: Deon K
authors.initials: DK
authors.lastname: Bakkes
authors.affiliation: Department of Zoology and Entomology, University of Pretoria, Hatfield, 0028, South Africa.
authors.forename: Louwtjie P
authors.initials: LP
authors.lastname: Snyman
authors.affiliation: Department of Zoology and Entomology, University of Pretoria, Hatfield, 0028, South Africa.
authors.forename: Christian W W
authors.initials: CW
authors.lastname: Pirk
authors.affiliation: Department of Zoology and Entomology, University of Pretoria, Hatfield, 0028, South Africa.
authors.forename: Catherine L
authors.initials: CL
authors.lastname: Sole
mesh_terms: D000465:Algorithms; D000818:Animals; D005580:Fossils / Q000033:anatomy & histology; D015186:Hominidae / Q000033:anatomy & histology; D007313:Insecta / Q000033:anatomy & histology*
keywords: DNA; log sem; mantispid; standard deviation of logged ratios; standard error test of the null hypothesis