使用深度学习对多样性依赖的生物地理速率的族群遗传学估计
bioRxiv : the preprint server for biology
|February 27, 2026
概括
当地的物种丰富性影响了物种化和灭绝率,创造了承载能力. 我们的新模型DDGeoSSE使用深度学习来分析这些多样性依赖于多样化动态的影响.
科学领域:
- 生态生态学 生态生态学
- 进化生物学 进化生物学
- 生物地理学是生物地理学.
背景情况:
- 生态理论认为,当地物种丰富程度会影响物种化,灭绝和分散率.
- 高物种密度可能导致当地物种丰富的承载能力由于增加的竞争和灭绝.
研究的目的:
- 介绍DDGeoSSE,这是一个植物遗传多样化模型,结合了对生物地理速率的多样性依赖效应.
- 测试替代多样化场景,包括正面,负面和中性物种相互作用.
- 研究当地物种丰富在塑造多样化动态中的作用.
主要方法:
- 开发了一个完全生成的,基于事件的族系遗传多样化模型 (DDGeoSSE).
- 导出模型的数学和统计属性,包括平衡时的承载能力.
- 由于复杂的概率函数,使用phyddle进行参数推断和模型选择.
主要成果:
- 通过模拟验证了模型的承载能力预测.
- 将DDGeoSSE应用于加勒比海的Anolis和云林Viburnum植物.
- 发现了大量证据表明,当地物种丰富程度影响了两种研究类型的多样化动态.
结论:
- 当地的物种丰富是塑造分类多样化的重要因素.
- DDGeoSSE模型为研究依赖于多样性的物种和灭绝提供了一个强大的框架.
- 深度学习有助于分析复杂的遗传学多样化模型.
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