通过距离采样估计野生动物密度:一种具有运动补偿的新技术
David G Morgan1, John R Gibbens1, Ed T Conway2
1School of Biosciences, University of Melbourne, Parkville, Australia.
PloS one
|October 16, 2024
概括
一种名为WildlifeDensity的新方法通过考虑观察者移动来改善野生动物种群密度估计. 这促进了远程采样,以更好地保护和管理难以捉摸的动物.
科学领域:
- 野生动物生态学野生动物生态学
- 生态建模 生态建模
- 保护科学 保护科学
背景情况:
- 人口密度估计对于野生动物保护至关重要.
- 传统的距离采样方法与流动人口作斗争,导致过高估计.
- 像Distance这样的现有软件对动态的动物群体有局限性.
研究的目的:
- 介绍野生动物密度,一种新的远距离采样方法和软件.
- 解决移动野生动物种群的现有方法的局限性.
- 提高估计保护人口密度的准确性.
主要方法:
- 开发了基于辐射或垂直距离的视觉检测的机械模型.
- 集成的运动补偿模型,以纠正人口-观察者相对运动.
- 在基准种群,移动歌鸟和森林鸟类上测试了野生动物密度.
主要成果:
- 野生动物密度为不移动的种群提供了与距离相似的估计.
- 野生动物密度的辐射距离分析显示,低流动性种群 (袋鼠) 略有改善.
- 运动补偿模型有效地消除了检测率中的观察者速度偏差.
- 野生动物密度为移动鸟类提供了可接受的密度估计,其中距离被高估.
结论:
- 野生动物密度通过补偿动物移动来扩大远距离采样能力.
- 该方法不需要在截面线上完全检测.
- 支持辐射距离,简化现场工作,提高野生动物密度估计的测量精度.
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