1300
Journal of Paleontology 91(6):1296–1305
Table 1. Numerical and categorical variables measured in Fusichonetes and Tethyochonetes (see Figure 4 for illustration of the chosen variables in a hypothetical rugosochonetid shell).
Score Numerical
Code No. Variables 1
Categorical
2 3 4 5 6 7 8 9
10 11 12 13
Costellae amount
Density of papillae in marginal area DP Lateral margin angle Shell length Shell width
Width/length ratio Costellae complexity Cardinal extremity Ear convexity
Ear ornamentation Ear size
Sulcus development
14 Umbonal region width 15
Valve convexity
Abbreviation Unit 0 CA
-
LMA SL
WLR CC CE EC EO ES SD
SW Transition of ear to visceral area TEV
URW VC
2016). Others, mainly those concerning the complexity of costellae and ears, represent morphological characters widely regarded as important for distinguishing chonetid genera and species (Brunton et al., 2000; Chen et al., 2000; Shen and Archbold, 2002). The quantitative values for all variables were collected from either complete ventral valves or complete dorsal valves. For body-size measurements (length, width) taken from the literature, they were measured from the published actual fossil illustrations with a digital caliper from the Foxit Reader to the nearest 0.1mm. According to Krause et al. (2007), size estimates of brachiopod fossil shells from photographed images correlate well with their real sizes and can therefore be used for studies of body size variations. For specimens from the Xinmin section, the width and length were measured from the actual specimens with a vernier caliper to the nearest 0.1mm. Four different approaches were applied to the dataset,
in order to test and visually demonstrate whether species of Fusichonetes and Tethyochonetes could be distinguished with rigor. First, we used simple bivariate plots and linear regression models to analyze and visually depict the relationships between certain pairs of key morphological variables (e.g., shell length versus width, density of costellae versus shell outline, shell shape [outline] versus shell length) (see online supporting data: Appendix 2). Second, the Kolmogorov-Smirnov test was used to analyze
differences in shell size and width/length ratio between the two previously recognized genera; this was carried out using the software PAST (Hammer et al., 2001). In this analysis, bra- chiopod shell size was approximated with the geometric mean of length and width, following Jablonski (1996). Third, owing to the fact that our dataset is comprised of a
mixture of both numerical and categorical variables (see online supporting data: Appendix 3), we performed a categorical princi- ple component analysis (CATPCA) to conduct a multivariate analysis of the dataset. This procedure simultaneously analyzes numerical and categorical variables while reducing the dimen- sionality of the original data. CATPCA has been used for similar taxonomic studies (Domínguez-Rodrigo et al., 2009; Claerhout et al., 2016). The CATPCA was performed with the software SPSS Statistics 22 (SPSS
Inc.Chicago, IL,USA). Tomaintain the category order in the quantifications on theoretical grounds,
/mm2 °
mm mm -
Simple pointed Flat
Smooth Small
Absent/weak
Moderate Flat
Slightly inflated Slightly costellate Medium
Moderately developed Broad
Slightly bifurcated Acutangular
Moderately developed
Well demarcated Not well demarcated from visceral region
Strongly
categorical variables were discretized and optimally scaled by ordinal transformation. Since we are interested only in the rela- tions between variables and objects, or between objects, rather than the relationships between the variables, numerical variables were scaled by numeric transformation. The discretizationmethod selectedwas symmetrical normalization, given that our aimwas to examine the differences or similarities between the objects. Finally, we employed cladistics to investigate the phylo-
genetic relationship of the 15 species that have hitherto been assigned to the two genera. For this analytical procedure, Neochonetes (Huangichonetes) substrophomenoides (Waagen, 1884) and N.(Sommeriella) strophomenoides (Huang, 1932) were selected as outgroups. The cladistic analysis was con- ducted in TNT (Goloboff et al., 2008), treating continuous characters (numerical variables) ‘as such’ (Goloboff et al., 2006). For each species, the total range of measured morpho- metric values was adopted in order to show data information on specimen level. All measured values were transformed by log (x+ 1) for standardization (Kitching et al., 1998) (online supporting data: Appendix 4).
Results
The bivariate plots of width versus length and the number of costellae versus width/length ratio of the two genera are shown in Figure 5 and Figure 6, respectively. Figure 5 suggests that the two genera have very similar shell size variation trends through ontogeny. Figure 6, on the other hand, shows two interesting features. First, taking the dataset for both genera as a whole, the number of costellae appears quite stable and changes little with the variation of the shell outline, expressed by the width/ length ratio. Second, based on this plot, the data points repre- senting Fusichonetes cannot be well separated from those of Tethyochonetes, although F. nanyongensis, the type species of this genus, appears to stand out quite clearly from the rest of the plot. Also of note from Figure 6 is that although F. nayongensis is more transverse than Tethyochonetes, they have a similar number of costellae. To test whether the visual differences observed in Figures 5
and 6 are of any statistical significance, we applied the Kolmogorov-Smirnov test. The result suggests, while there is no
Moderately bifurcated Obtuse
Large Distinctly developed 1 2
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