School of Earth Sciences and Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, 210023, Jiangsu, China.
Department of Life Sciences, The Natural History Museum, Cromwell Road, London, SW7 5BD, UK.
BMC Ecol Evol. 2022 Apr 11;22(1):43. doi: 10.1186/s12862-022-01978-y.
The phylogenetic ecology of the Afro-Asian dragonfly genus Trithemis has been investigated previously by Damm et al. (in Mol Phylogenet Evol 54:870-882, 2010) and wing ecomorphology by Outomuro et al. (in J Evol Biol 26:1866-1874, 2013). However, the latter investigation employed a somewhat coarse sampling of forewing and hindwing outlines and reported results that were at odds in some ways with expectations given the mapping of landscape and water-body preference over the Trithemis cladogram produced by Damm et al. (in Mol Phylogenet Evol 54:870-882, 2010). To further explore the link between species-specific wing shape variation and habitat we studied a new sample of 27 Trithemis species employing a more robust statistical test for phylogenetic covariation, more comprehensive representations of Trithemis wing morphology and a wider range of morphometric data-analysis procedures.
Contrary to the Outomuro et al. (in J Evol Biol 26:1866-1874, 2013) report, our results indicate that no statistically significant pattern of phylogenetic covariation exists in our Trithemis forewing and hindwing data and that both male and female wing datasets exhibit substantial shape differences between species that inhabit open and forested landscapes and species that hunt over temporary/standing or running water bodies. Among the morphometric analyses performed, landmark data and geometric morphometric data-analysis methods yielded the worst performance in identifying ecomorphometric shape distinctions between Trithemis habitat guilds. Direct analysis of wing images using an embedded convolution (deep learning) neural network delivered the best performance. Bootstrap and jackknife tests of group separations and discriminant-function stability confirm that our results are not artifacts of overtrained discriminant systems or the "curse of dimensionality" despite the modest size of our sample.
Our results suggest that Trithemis wing morphology reflects the environment's "push" to a much greater extent than phylogeny's "pull". In addition, they indicate that close attention should be paid to the manner in which morphologies are sampled for morphometric analysis and, if no prior information is available to guide sampling strategy, the sample that most comprehensively represents the morphologies of interest should be obtained. In many cases this will be digital images (2D) or scans (3D) of the entire morphology or morphological feature rather than sparse sets of landmark/semilandmark point locations.
非洲-亚洲蜻蜓属特里赫米斯的系统发生生态已经被 Damm 等人（在 Mol Phylogenet Evol 54:870-882, 2010 中）和 Outomuro 等人（在 J Evol Biol 26:1866-1874, 2013 中）进行了研究。然而，后者的研究在一定程度上对前翅和后翅轮廓进行了粗略的抽样，并报告了一些与 Damm 等人（在 Mol Phylogenet Evol 54:870-882, 2010 中）产生的特里赫米斯系统发育枝上的景观和水体偏好映射不一致的结果。为了进一步探索物种特异性翼型变化与栖息地之间的联系，我们研究了一个新的 27 种特里赫米斯物种样本，使用更强大的系统发育共变统计检验、更全面的特里赫米斯翼形态代表和更广泛的形态数据分析程序。
与 Outomuro 等人（在 J Evol Biol 26:1866-1874, 2013 中）的报告相反，我们的结果表明，在我们的特里赫米斯前翅和后翅数据中，不存在统计上显著的系统发育共变模式，而且雄性和雌性翅膀数据集都显示出栖息在开阔和森林景观与栖息在临时/静止或流动水体的物种之间存在显著的形状差异。在所进行的形态计量分析中，地标数据和几何形态计量数据分析方法在识别特里赫米斯生境群体之间的生态形态差异方面表现最差。使用嵌入式卷积（深度学习）神经网络直接分析翅膀图像提供了最好的性能。分组分离和判别函数稳定性的自举和刀切检验证实，尽管我们的样本量较小，但我们的结果不是过度训练的判别系统或“维度诅咒”的人为产物。
我们的结果表明，特里赫米斯的翅膀形态在很大程度上反映了环境的“推动”，而不是系统发育的“拉动”。此外，它们表明，应该密切关注形态计量分析中形态采样的方式，如果没有先验信息来指导采样策略，那么应该获得最全面地代表感兴趣形态的样本。在许多情况下，这将是整个形态或形态特征的数字图像（2D）或扫描（3D），而不是稀疏的地标/半地标点位置集。
