Pomatoschistus, Gill, 1863

Cooper, David, Yamaguchi, Nobuyuki, Macdonald, David, Nanova, Olga, Yudin, Viktor, Dugmore, Andrew & Kitchener, Andrew, 2020, Identification of past and present gobies: distinguishing Gobius and Pomatoschistus (Teleostei: Gobioidei) species using characters of otoliths, meristics and body morphometry, Contributions to Zoology 89 (1), pp. 282-323 : 295-302

Species separation in Pomatoschistus

Otolith morphometry

Five otolith variables (out of 23) were successful in species separation when the complete dataset was used (N, 7 species; ANCOVA/ ANOVA; table 4a 1 ). The maximum classification success for a given species was 67%. OL/ OH and OP/OH were the best variables with respect to the number of species that could be discriminated; OL/OH separated all species except P. knerii , and OP/OH discriminated four species (table 4a 1 ). In total, all species could be separated from one another; P. marmoratus , P. microps and P. montenegrensis each by four variables, and the remainder by a single variable each (table 4a 1 ). When PC1–4 calculated from the otolith morphometric variables was analysed, the success in species separation declined in the case of P. microps (33% vs. 67% in the preceding analysis) and P. pictus (0vs.50%),but was improved in the case of P.montenegrensis (83% vs. 67%; table 4b 1 ).

When the reduced dataset (N, 5 species) was analysed in the same way, most of the otolith morphometric variables contributed to species separation (table 4a 2 ). Four variables achieved 100% separation success for a given species: SuEndV/OP for P. marmoratus and P. microps , and SuH/OL, SuH/SuTipV and SuP/SuTipV each for P. montenegrensis (table 4a 2 ). Overall, all species could be separated from ≥50% of their congeners, and 13–17 variables contributed in each case (table 4a 2 ). As observed in the complete dataset, the results of ANOVA on the basis of PC1–4 of the otolith morphometric variables discriminated the species less efficiently than when the individual otolith variables were used (compare table 4b 2 vs. 4a2).

Body morphometry

Each of the eight morphometric variables contributed to species separation and each species was separated from all others when the complete dataset was used (ANOVA; table 4d 1 ). 100% separation success was achieved by CP (for P. minutus ) and Ab (for P. montenegrensis ). The most efficient variables in relation to the number of species discriminated were Ab (all species), and D2b, D2C and SN/A (six species). Pomatoschistus quagga was the only species that could be separated by each morphometric variable from 50–83% of its congeners; the remaining species were separated by three to six variables from their congeners (table 4d 1 ). Furthermore, each species was separated when PC1–4 of the morphometric variables were analysed (ANOVA; table 4e 1 ). 100% separation success was obtained for P. montenegrensis and P. quagga (table 4e 1 ).

Overall, similar results were obtained with the reduced dataset, but some differences are noteworthy (table 4d 2 ). With the exception of SN/D2, every morphometric variable could be used to separate some species. The reason that SN/D2 was now disqualified lies in the exclusion of P. minutus (which had been separated by this variable) from the reduced dataset. Three variables (vs. one in the complete dataset) showed 100% separation success for at least one species: D2C (for P.marmoratus , P. microps ), B (for P. quagga ) and Ab (for P. montenegrensis ). Most effective concerning the number of species that could be separated were D2C (all species) and SN/A (four species) (table 4d 2 ). Apart from P. marmoratus (separated by a single variable), each of the included species could be discriminated by five or six variables from their congeners (table 4d 2 ). When ANOVA was done based on PC1–4 of the morphometric body variables, the separation success was generally similar to that of the previous analysis and all species could be separated (table 4e 2 ).

Meristic characters

Numbers of total and abdominal vertebrae contributed to species separation with moderate success (50–67%) when the complete dataset was employed (table 4f 1 ). Pomatoschistus microps , P. montenegrensis and P. pictus could be separated by either the total or the abdominal vertebrae count, while P. quagga was discriminated by both of these counts (table 4f 1 ). ANOVA using PC1–4 of the meristic counts showed improved results, as PC1 separated all species apart from P. pictus , with highest separation success (83%) for P. minutus , P. montenegrensis , and P. quagga (table 4g 1 ).

In the reduced dataset, seven meristic characters contributed to species separation (vs. two in the complete dataset), with an improved overall separation success (50–100% vs. 50–67%) (table 4f 2 ). The caudal and the abdominal vertebrae count separated P. montenegrensis and P. microps / P. quagga , respectively, from all other species. The latter was most efficient in relation to the number of species that could be separated (all five species) (table 4f 2 ). In total, all five species could be separated: P. knerii , P. montenegrensis and P. quagga by six, seven and five variables, respectively, and P. marmoratus and P. microps by one and three variables, respectively (table 4f 2 ). ANOVA using PC1–4 of the meristic values separated each species from 75–100% of its congeners, with 100% success for P. microps , P. montenegrensis and P.quagga (table 4g 2 ).

Discriminant analyses

As for Gobius , each LDA was based on the reduced dataset. The variables used as input were (i) PC1–4 of the otolith morphometric variables, (ii) PC1–14 of the Fourier descriptors, and (iii) PC1–4 of the body morphometric variables (table 5).

The first two functions of the LDA based on PC1–4 of the otolith morphometric variables explained 62.0% and 33.2% of the variation, respectively (fig. 2d). Overall classification success (jack-knifed) of the LDA was 71.1%. The highest classification success was achieved for P. montenegrensis (90%) and P. microps (87%), while the success rates were between 56 and 60% for P. knerii , P. marmoratus , and P. quagga (table 5a). The scatter plot depicts three groups (fig. 2d). The first consists of P. montenegrensis and is completely distinct. The second and third groups include P.microps / P.marmoratus and P.knerii / P.quagga ; the members of each group overlap with each other, but very little or not at all with the others (fig. 2d).

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The first two functions of the LDA based on PC1–14 of the Fourier descriptors captured 57.6% and 21.6% of the variance, respectively. Overall classification success (jack-knifed) was 96%, with 100% success for P.microps and P. quagga ,>90% success for the remainder (table 5b). The corresponding scatter plot depicts P. knerii , P. marmoratus , and P. montenegrensis as separate groups, while P. microps and P. quagga overlap (fig. 2e).

The first two functions of the LDA based on the body morphometric variables account for 71.7% and 23% of the variation, respectively. Overall classification success (jackknifed) was 75.9%, with 90% success for P.montenegrensis and P. quagga , and 67–70% success for the remainder (table 5c). The success in separation is also seen in the scatter plot, which reveals that each species is relatively well separated, although some overlap is seen (fig. 2f).