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Sexual dimorphism (SD) can contribute to local adaptation and evolutionary diversification, but species-wide comparisons are hindered by heterogeneous published datasets. We developed the Sexual Dimorphism Ternary Index (SDTI), coding each trait–sample comparison as −1 (significant female bias), 0 (no significant difference), or +1 (significant male bias), to integrate heterogeneous data on threespine stickleback, Gasterosteus aculeatus Linnaeus, 1758, into a comparative dataset. Correlation-guided hierarchical aggregation reduced 11 overlapping traits to four weakly correlated variables: standard length (SL), the head–posterior composite (HPC), body depth (BD1), and the dorsal-spine composite (DSs). PERMANOVA detected a significant ecotype effect, with the clearest contrast occurring between marine and freshwater populations; BD1 showed the clearest single-variable separation. Marine populations tended to exhibit more male-biased body-depth and dorsal-spine dimorphism, whereas SL was consistently female-biased across ecotypes. The framework also allowed the White Sea samples to be positioned relative to the major ecotypes: their mean profile was closest to the anadromous centroid, while their high signed mean SDTI reflected a net predominance of significant male-biased comparisons across the traits examined. Although SDTI does not measure effect magnitude and is sensitive to statistical power, it identifies patterns in direction and organization of sexual dimorphism.
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Lajus et al. (2026) studied this question.
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