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首页> 外文期刊>Journal of the Royal Society Interface >The well-tuned blues: the role of structural colours as optical signals in the species recognition of a local butterfly fauna (Lepidoptera: Lycaenidae: Polyommatinae)
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The well-tuned blues: the role of structural colours as optical signals in the species recognition of a local butterfly fauna (Lepidoptera: Lycaenidae: Polyommatinae)

机译:调好的蓝调:结构颜色作为光学信号在本地蝴蝶动物区系识别中的作用(鳞翅目:Lycaenidae:Polyommatinae)

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摘要

The photonic nanoarchitectures responsible for the blue colour of the males of nine polyomma-tine butterfly species living in the same site were investigated structurally by electron microscopy and spectrally by reflectance spectroscopy. Optical characterization was carried out on 110 exemplars. The structural data extracted by dedicated software and the spectral data extracted by standard software were inputted into an artificial neural network software to test the specificity of the structural and optical characteristics. It was found that both the structural and the spectral data allow species identification with an accuracy better than 90 per cent. The reflectance data were further analysed using a colour representation diagram built in a manner analogous to that of the human Commission Internationale de PEclairage diagram, but the additional blue visual pigment of lycaenid butterflies was taken into account. It was found that this butterfly-specific colour representation diagram yielded a much clearer distinction of the position of the investigated species compared with previous calculations using the human colour space. The specific colours of the investigated species were correlated with the 285 flight-period data points extracted from museum collections. The species with somewhat similar colours fly in distinct periods of the year such that the blue colours are well tuned for safe mate/competitor recognition. This allows for the creation of an effective pre-zygotic isolation mechanism for closely related synchronic and syntopic species.
机译:通过电子显微镜和反射光谱法研究了居住在同一地点的九种多蝶类蝴蝶的雄性蓝色的光子纳米结构。光学表征在110个样本上进行。通过专用软件提取的结构数据和通过标准软件提取的光谱数据被输入到人工神经网络软件中,以测试结构和光学特性的特异性。结果发现,结构和光谱数据都可以以超过90%的准确度进行物种鉴定。使用颜色表示图进一步分析反射率数据,该颜色表示图的构建方式类似于国际人体工程学委员会的图,但是考虑到了蝶形蓝蝶的其他蓝色视觉色素。已经发现,与先前使用人类色彩空间进行的计算相比,该特定于蝴蝶的颜色表示图对被调查物种的位置产生了更加清晰的区分。被调查物种的特定颜色与从博物馆收藏中提取的285个飞行周期数据点相关。颜色有些相似的物种会在一年中的不同时期飞翔,因此对蓝色进行了很好的调整,可以安全地识别配偶/竞争对手。这允许为紧密相关的共生和同位物种建立有效的合子前分离机制。

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