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通过神经网络和遗传数据,通过连续的美国描述野猪的移动情况
Rachael M Giglio1, Courtney F Bowden1, Ryan K Brook2
1United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, Fort Collins, Colorado, USA.
Molecular ecology
|August 16, 2024
概括
野猪是一种具有破坏性的入侵物种. 使用深度神经网络的基因组分析显示,20%的采样野生猪被人类转移,通常超过1000公里,突出了人类介导的传播模式.
科学领域:
- 生态生态学 生态生态学
- 遗传学 遗传学是一种遗传学.
- 保护生物学 保护生物学
背景情况:
- 全球化促进了物种的入侵潜力.
- 野生猪 (Sus scrofa × domesticus) 是全球高度破坏性的入侵物种.
- 人为媒介的运动加快了美国野猪范围的扩张,造成了严重的生态和经济损害.
研究的目的:
- 使用基因组数据,在连续的美国地区识别转移的野猪.
- 描述人类介导的野猪运动模式.
- 为了验证深度神经网络对入侵物种传播分析的使用.
主要方法:
- 利用了一个庞大的基因组数据库 (18,789个样本,35,141个SNP).
- 使用深度神经网络来分类转移的个体.
- 利用网络分析来描述转移模式.
主要成果:
- 20% (3364/16,774) 的被采样野生猪被归类为转移的.
- 识别了广泛的人为媒介的移动,其中一些个体起源于距离采样地点>1000公里.
- 揭示了美国境内和加拿大的移动模式.
结论:
- 深度神经网络是识别迁移入侵物种的有效工具.
- 人类活动对野猪在自然分布之外的传播有很大影响.
- 了解转移模式对于管理像野猪这样的入侵物种至关重要.
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