Wilber Mark Q, Weinstein Sara B, Briggs Cheryl J
Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA, United States.
Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA, United States.
Int J Parasitol. 2016 Jan;46(1):59-66. doi: 10.1016/j.ijpara.2015.08.009. Epub 2015 Oct 16.
Parasites can significantly impact animal populations by changing host behaviour, reproduction and survival. Detecting and quantifying these impacts is critical for understanding disease dynamics and managing wild animal populations. However, for wild hosts infected with macroparasites, it is notoriously difficult to quantify the fatal parasite load and number of animals that have died due to disease. When ethical or logistical constraints prohibit experimental determination of these values, examination of parasite intensity and distribution data may offer an alternative solution. In this study we introduce a novel method for using intensity data to detect and quantify parasite-induced mortality in wildlife populations. We use simulations to show that this method is more reliable than previously proposed methods while providing quantitative estimates of parasite-induced mortality from empirical data that are consistent with previously published qualitative estimates. However this method, and all techniques that estimate parasite-induced mortality from intensity data alone, have several important assumptions that must be scrutinised before applying those to real-world data. Given that these assumptions are met, our method is a new exploratory tool that can help inform more rigorous studies of parasite-induced host mortality.
寄生虫可通过改变宿主行为、繁殖和生存状况，对动物种群产生重大影响。检测和量化这些影响对于理解疾病动态和管理野生动物种群至关重要。然而，对于感染大型寄生虫的野生宿主而言，量化致命寄生虫负荷以及因病死亡的动物数量极为困难。当伦理或后勤限制禁止通过实验确定这些数值时，检查寄生虫强度和分布数据或许能提供一种替代解决方案。在本研究中，我们引入了一种利用强度数据检测和量化野生动物种群中寄生虫诱发死亡率的新方法。我们通过模拟表明，该方法比先前提出的方法更可靠，同时能根据经验数据对寄生虫诱发的死亡率进行定量估计，且与先前发表的定性估计结果一致。然而，此方法以及所有仅根据强度数据估算寄生虫诱发死亡率的技术，都有几个重要假设，在将其应用于实际数据之前必须仔细审查。鉴于这些假设成立，我们的方法是一种新的探索性工具，有助于为更严谨的寄生虫诱发宿主死亡率研究提供参考。
