Schrodinger's phenotypes: Herbarium specimens show two-dimensional images are both good and (not so) bad sources of morphological data
Schrodinger's phenotypes: Herbarium specimens show two-dimensional images are both good and (not so) bad sources of morphological data
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DOI：
10.1111/2041-210x.13450
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发表时间：
2020-08-20
影响因子：
6.6
通讯作者：
Izbicki, Rafael
中科院分区：
文献类型：
--
作者：
Borges, Leonardo M.;Reis, Victor Candido;Izbicki, Rafael
博物馆标本是生物形态特征信息的主要来源。虽然这些信息通常仅限于能够访问收藏品的研究人员，但由于博物馆标本的数字化，现在可以免费获得。有了这些图像，我们将能够共同构建大规模的形态数据集，但只有在这种方法的局限性众所周知的情况下，这些数据集才会有用。为了建立这些限制，我们使用植物标本的二维图像来测试基于图像的数据和分析的精度和准确性。为了测试测量的精度和准确性，我们比较了叶片测量标本和相同标本的图像。然后，我们使用传统的形态测量数据集来建立样本和图像之间的数据集质量和多变量分析的差异。为此，我们将基于原始遗留数据的多变量空间与使用模拟基于图像的数据的数据集构建的空间进行了比较。我们发现，从图像中获得的特征测量与直接从标本中获得的特征测量一样精确，但随着特征尺寸的减小，准确性也会下降。然而，这种准确性的降低对数据集和分析质量的影响非常小。基于图像的数据集的主要问题来自于由于图像分辨率或器官重叠而导致的观测缺失。缺失数据降低了数据集和多变量分析的准确性。虽然这种影响并不强烈，但这种准确性的下降表明，在设计依赖于数字化标本的形态学研究时需要谨慎。正如植物标本的图像所强调的那样，2D图像是可靠的测量来源，即使分辨率会降低小性状的准确性。与此同时，无法观察到特定特征影响了基于图像的数据集的质量，从而影响了衍生分析的质量。尽管存在这些问题，但从二维图像中收集表型数据是有效的，可以支持对多种生物的形态和进化进行大规模研究。
Museum specimens are the main source of information on organisms' morphological features. Although access to this information was commonly limited to researchers able to visit collections, it is now becoming freely available thanks to the digitization of museum specimens. With these images, we will be able to collectively build large-scale morphological datasets, but these will only be useful if the limits to this approach are well-known. To establish these limits, we used two-dimensional images of plant specimens to test the precision and accuracy of image-based data and analyses. To test measurement precision and accuracy, we compared leaf measurements taken from specimens and images of the same specimens. Then, we used legacy morphometric datasets to establish differences in the quality of datasets and multivariate analyses between specimens and images. To do so, we compared the multivariate space based on original legacy data to spaces built with datasets simulating image-based data. We found that trait measurements made from images are as precise as those obtained directly from specimens, but as traits diminish in size, the accuracy drops as well. This decrease in accuracy, however, has a very low impact on dataset and analysis quality. The main problem with image-based datasets comes from missing observations due to image resolution or organ overlapping. Missing data lowers the accuracy of datasets and multivariate analyses. Although the effect is not strong, this decrease in accuracy suggests caution is needed when designing morphological research that will rely on digitized specimens. As highlighted by images of plant specimens, 2D images are reliable measurement sources, even though resolution issues lower accuracy for small traits. At the same time, the impossibility of observing particular traits affects the quality of image-based datasets and, thus, of derived analyses. Despite these issues, gathering phenotypic data from two-dimensional images is valid and may support large-scale studies on the morphology and evolution of a wide diversity of organisms.