University of Oxford, Department of Biology, OX1 3SZ, Oxford, United Kingdom.
University of Oxford, Department of Earth Sciences, OX1 3AN, Oxford, United Kingdom.
Sci Data. 2024 Sep 10;11(1):984. doi: 10.1038/s41597-024-03687-1.
Here we describe a dataset of freely available, readily processed, whole-body μCT-scans of 56 species (116 specimens) of Lake Malawi cichlid fishes that captures a considerable majority of the morphological variation present in this remarkable adaptive radiation. We contextualise the scanned specimens within a discussion of their respective ecomorphological groupings and suggest possible macroevolutionary studies that could be conducted with these data. In addition, we describe a methodology to efficiently μCT-scan (on average) 23 specimens per hour, limiting scanning time and alleviating the financial cost whilst maintaining high resolution. We demonstrate the utility of this method by reconstructing 3D models of multiple bones from multiple specimens within the dataset. We hope this dataset will enable further morphological study of this fascinating system and permit wider-scale comparisons with other cichlid adaptive radiations.
在这里，我们描述了一个数据集，其中包含 56 种（116 个标本）马拉维湖慈鲷鱼类的免费、易于处理的全身 μCT 扫描，这些扫描捕捉到了这个非凡的适应性辐射中存在的大量形态变异。我们将扫描标本置于对其各自生态形态分组的讨论中，并提出了可能使用这些数据进行的宏观进化研究。此外，我们描述了一种高效的 μCT 扫描方法（平均每小时扫描 23 个标本），可以限制扫描时间和减轻经济成本，同时保持高分辨率。我们通过从数据集中的多个标本重建多个骨骼的 3D 模型来证明该方法的实用性。我们希望这个数据集将能够促进对这个迷人系统的进一步形态学研究，并允许与其他慈鲷适应性辐射进行更广泛的比较。
