Scleromystax barbatus, (Quoy & Gaimard, 1824) (Quoy & Gaimard, 1824)

Dalcin, Roger Henrique & Abilhoa, Vinícius, 2024, Discriminating Scleromystax barbatus (Siluriformes: Callichthyidae) populations from Atlantic Rainforest streams employing otolith shape, Neotropical Ichthyology (e 230129) 22 (1), pp. 1-15 : 6

publication ID

https://doi.org/10.1590/1982-0224-2023-0129

DOI

https://doi.org/10.5281/zenodo.15528237

persistent identifier

https://treatment.plazi.org/id/0E7687EC-8E1F-FFA5-FE29-FDD7BAADFAF2

treatment provided by

Felipe

scientific name

Scleromystax barbatus
status

 

The lapillus otoliths of

S. barbatus View in CoL

display an elongation in the superior-inferior axis, with uneven wavy bottom edges, while the gibbus maculae is large, prominent, occupying much of the surface of the otolith and the sulcus is short, wide and contours the inner gibbus maculae region ( Fig. 2 View FIGURE 2 ). The ANOVA-like permutation test for the Fourier/Wavelet coefficients indicated significant differences between otoliths of males of Scleromystax barbatus from southern and southeastern areas in the Atlantic Rainforest biome, and also between otoliths of males from southeastern areas and females of southern areas of the Atlantic Rainforest biome ( Tab. 2 View TABLE 2 ).

The Fourier and Wavelet reconstructions showed differences among the mean otolith outlines between the southern and southeastern areas ( Fig. 3 View FIGURE 3 ). The highest variation was observed for the extremum anterior, the posterior region and medial regions of the sulcus. Otoliths from the southeastern areas are more elongated in these portions, mainly in the Wavelet reconstruction. Conversely, high overlaps in the lateral sulcus and in the lateral and medial gibbus maculae regions were observed.

The CAP assessments indicated that otolith shape was not homogeneous among the southern and southeastern regions, for both coefficients (ANOVA-like, P <0.01). The first two principal coordinates axes explained 94.4% of the total Fourier coefficient variation and 94.3% of the Wavelet coefficient variation ( Fig. 4 View FIGURE 4 ).

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