避免在人口规模估计中的偏差,用于转移管理
Katherine T Bickerton1,2, John G Ewen1, Stefano Canessa3
1Institute of Zoology, Zoological Society of London, London, UK.
概括
使用Jolly-Seber (JS) 模型的标记回收调查可以高估转移的种群. 本研究引入了对已知初始尺寸进行校正的JS模型,改进了保护估计.
科学领域:
- 生态生态学 生态生态学
- 保护生物学 保护生物学
- 人口动态 人口动态
背景情况:
- 标记回收调查对于监测转移的野生动物种群至关重要.
- 乔利-塞伯 (JS) 模型是估计诸如丰富和生存等人口参数的标准.
- 在转移中已知的初始种群大小经常被忽视,可能会对JS模型估计产生偏见.
研究的目的:
- 开发和验证一个修改的Jolly-Seber (JS) 模型,该模型包含已知转移物种的初始种群大小.
- 评估标准JS模型中的偏差以及纠正模型在改善人口估计中的有效性.
主要方法:
- 开发了JS模型的最大概率估计框架,其中包括转移个体的特定概率组件.
- 利用模拟数据和一个案例研究,涉及一个受到威胁的物种,捕获概率低.
- 将不受约束的JS模型中的参数估计与新受约束的模型进行比较.
主要成果:
- 当检测概率低 (<0.3) 时,不受约束的JS模型可以将转移的种群大小高估78130%.
- 约束模型显著降低了高估值 (18.9%) 并减少了所有参数估计中的误差.
- 修正后的模型可以防止边界估计,并提高了案例研究的整体稳定性.
结论:
- 在JS模型中考虑已知的初始种群大小对于准确监测转移种群至关重要.
- 修正后的JS模型为保护决策提供了更可靠的数据,例如人口增强.
- 实施这种精细的方法提高了野生动物转移计划的成功率.
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