在野生动物群体中检测大规模死亡事件
Jesse L Brunner1, Justin M Calabrese2,3,4
1School of Biological Sciences, Washington State University, Pullman, Washington, USA.
概括
由于采样问题,许多动物大规模死亡事件 (MME) 没有被发现. 这项研究提出了一种改善MME检测概率的模型,这对于了解野生动物健康和设计监测计划至关重要.
科学领域:
- 生态与野生动物健康
- 保护生物学
- 流行病学
背景情况:
- 越来越多的不同类型的群体死亡事件 (MME) 报告.
- 由于检测偏差而显著低估了MME (例如,采样不频繁,神秘物种,尸体快速腐烂).
- 评估MME的时间和空间趋势的挑战.
研究的目的:
- 开发一个建模框架,以了解影响MME检测概率的因素.
- 为监测提供最佳采样频率和检测能力动态的见解.
- 在一个特定的危群体中估计MME的频率.
主要方法:
- 开发了一个概率模型,将MME检测概率与观测频率和检测性衰减率联系起来.
- 应用该框架对35个临灭绝的子亚种种群进行Ranavirus相关的MMEs分析.
- 评估了采样频率和检测能力对观察MME的可能性的影响.
主要成果:
- 在研究的种群中检测MME的概率低于50%.
- 系统中MME的实际频率可能高于单个观察到的事件.
- 模型表明,更高的峰值检测能力,更慢的衰变率和更高的观察频率提高了MME检测的概率.
结论:
- 目前的监测可能低估了MME的真实发病率,特别是对于神秘的物种或快速衰变的物种.
- 开发的框架有助于设计更有效的野生动物疾病监测计划.
- 需要进一步的研究来解决限制,例如定期,同等努力调查的假设.
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