西方池海 (Actinemys) 的形态物种划分:机器学习方法可以帮助识别神秘物种吗?
R W Burroughs1,2, J F Parham3, B L Stuart4
1Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794, USA.
Integrative organismal biology (Oxford, England)
|May 1, 2024
概括
几何形态测量和机器学习表明,石形状为Actinemys属内的两个神秘海物种提供了暂时的支持. 然而,与其他Emydidae海相比,Actinemys的整体胎盘变异较低.
科学领域:
- 进化生物学 进化生物学
- 形态测量法 形态测量法 形态测量法
- 计算生物学 计算生物学
背景情况:
- 神秘物种的发现正在增加,需要可靠的方法来进行形态诊断.
- 包括Actinemys marmorata和Actinemys pallida在内的Actinemys属,由于其分布和保护状况,具有显著的研究兴趣.
- 目前对Actinemys物种的形态诊断仍然不可靠.
研究的目的:
- 调查塑形状的几何形态数据是否可以区分两个假定的神秘海物种: Actinemys marmorata 和 Actinemys pallida.
- 评估机器学习方法 (MLMs) 在识别物种诊断细度变化的有效性.
- 为了验证该方法,使用了形态上不同的虫物种和亚种的数据集来验证该方法.
主要方法:
- 利用了乌胎盘的几何形态测量数据.
- 应用了五种监督机器学习方法 (MLM) 的组合.
- 验证了MLM在八个不同的emydid物种和两个Trachemys亚种的数据集上.
主要成果:
- 验证数据集实现了近乎完美的分类率,证实了塑形状在通过MLM区分emydid分类学群的有效性.
- 对于Actinemys神秘物种假设,MLM并没有产生很高的分类率.
- 两个假设稍微支持A. marmorata和A. pallida之间的两种分裂,提供了暂时的形态支持.
结论:
- 通过MLM分析的Plastron形状为Actinemys中的两种物种假设提供了暂时的形态支持.
- 与其他Emydidae海相比,Actinemys表现出较低的胎盘变异,目前尚不清楚这种保守的原因.
- 需要进一步的研究,以了解低形态变异,并最终诊断Actinemys物种.
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