Each death event can be characterized by its associated microbes – a living community of bacteria composed of carcass, soil, and insect-introduced bacterial species – a necrobiome. With the possibility for close succession of these death events, it may be beneficial to characterize how the magnitude of an initial death event may impact the decomposition and necrobiomes of subsequent death events in close proximity. In this paper we hope to characterize the microbial communities associated with a proximate subsequent death event, and distinguish any changes within those communities based on the magnitude of an initial death event and the biomass of preexisting carcass (es) undergoing decomposition. For this experiment, 6 feral swine carcasses in containers were placed in the vicinity of preexisting and ongoing carcass decomposition at sites of three different scales of decomposing carcass biomass. Swab samples were collected from the skin and eye sockets of the container pigs and subjected to 16 s rRNA sequencing and OTU assignment. PERMANOVA analysis of the bacterial taxa showed that there was no significant difference in the bacterial communities based on initial mortality event biomass size, but we did see a change in the bacterial communities over time, and slight differences between the skin and ocular cavity communities. Even without soil input, necrobiome communities can change rapidly. Further characterization of the bacterial necrobiome included utilization of the Random Forest algorithm to identify the most important predictors for time of decomposition. Sample sets were also scanned for notable human and swine-associated pathogens. The applications from this study are many, ranging from establishing the environmental impacts of mass mortality events to understanding the importance of scavenger, and scavenger microbial community input on decomposition.

中文翻译：

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大规模死亡后继发性死亡事件的微生物演替

每个死亡事件都可以通过其相关的微生物来表征——由尸体、土壤和昆虫引入的细菌物种组成的活细菌群落——一个死生物群。由于这些死亡事件有可能连续发生，因此表征初始死亡事件的严重程度如何影响紧邻的后续死亡事件的分解和死灵生物群落可能是有益的。在本文中，我们希望表征与近期死亡事件相关的微生物群落，并根据初始死亡事件的严重程度和正在分解的预先存在的尸体的生物量来区分这些群落内的任何变化。对于这个实验，将容器中的 6 只野猪尸体放置在三个不同规模的尸体生物量分解位点的预先存在和正在进行的尸体分解附近。从容器猪的皮肤和眼窝中收集拭子样本，并进行 16 s rRNA 测序和 OTU 分配。细菌分类群的 PERMANOVA 分析表明，基于初始死亡事件生物量大小，细菌群落没有显着差异，但我们确实看到细菌群落随时间发生变化，皮肤和眼腔群落之间存在细微差异。即使没有土壤输入，死生物群落也会迅速变化。细菌坏死生物组的进一步表征包括利用随机森林算法来确定最重要的分解时间预测因子。还对样本集进行了显着的人类和猪相关病原体扫描。这项研究的应用范围很广，从确定大规模死亡事件的环境影响到了解清道夫的重要性，以及清道夫微生物群落对分解的投入。