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优化环境 DNA 研究中的采样和分析方案。

Optimising sampling and analysis protocols in environmental DNA studies.

机构信息

Durrell Institute of Conservation and Ecology, School of Anthropology and Conservation, University of Kent, Marlowe Building, Canterbury, Kent, CT2 7NR, UK.

School of Mathematics, Statistics and Actuarial Science, University of Kent, Sibson Building, Canterbury, Kent, CT2 7FS, UK.

出版信息

Sci Rep. 2021 Jun 2;11(1):11637. doi: 10.1038/s41598-021-91166-7.

Abstract

Ecological surveys risk incurring false negative and false positive detections of the target species. With indirect survey methods, such as environmental DNA, such error can occur at two stages: sample collection and laboratory analysis. Here we analyse a large qPCR based eDNA data set using two occupancy models, one of which accounts for false positive error by Griffin et al. (J R Stat Soc Ser C Appl Stat 69: 377-392, 2020), and a second that assumes no false positive error by Stratton et al. (Methods Ecol Evol 11: 1113-1120, 2020). Additionally, we apply the Griffin et al. (2020) model to simulated data to determine optimal levels of replication at both sampling stages. The Stratton et al. (2020) model, which assumes no false positive results, consistently overestimated both overall and individual site occupancy compared to both the Griffin et al. (2020) model and to previous estimates of pond occupancy for the target species. The inclusion of replication at both stages of eDNA analysis (sample collection and in the laboratory) reduces both bias and credible interval width in estimates of both occupancy and detectability. Even the collection of > 1 sample from a site can improve parameter estimates more than having a high number of replicates only within the laboratory analysis.

摘要

生态调查有产生目标物种假阴性和假阳性检测结果的风险。对于间接调查方法,如环境 DNA,这种错误可能发生在两个阶段:样本采集和实验室分析。在这里,我们使用两种占有模型分析了一个大型基于 qPCR 的 eDNA 数据集,其中一个模型由 Griffin 等人(J R Stat Soc Ser C Appl Stat 69: 377-392, 2020)解释了假阳性错误,另一个模型假设 Stratton 等人(Methods Ecol Evol 11: 1113-1120, 2020)不存在假阳性错误。此外,我们将 Griffin 等人(2020)模型应用于模拟数据,以确定在采样阶段都要达到最佳的复制水平。Stratton 等人(2020)模型假设没有假阳性结果,与 Griffin 等人(2020)模型和目标物种池塘占有率的先前估计相比,该模型一致高估了总体和单个地点占有率。在 eDNA 分析的两个阶段(样本采集和实验室)都增加复制,减少了占有率和可检测性估计的偏差和置信区间宽度。即使从一个地点收集超过 1 个样本,也比只在实验室分析中进行多次复制更能改善参数估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a97/8172848/8900ec3ab376/41598_2021_91166_Fig1_HTML.jpg

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