Reliability of environmental DNA surveys to detect pond occupancy by newts at a national scale.
Reliability of environmental DNA surveys to detect pond occupancy by newts at a national scale.
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DOI：
10.1038/s41598-022-05442-1
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发表时间：
2022-01-25
影响因子：
4.6
通讯作者：
Griffiths RA
中科院分区：
文献类型：
--
作者：
Buxton A;Diana A;Matechou E;Griffin J;Griffiths RA
物种分布评估和监测是进行可靠的环境影响评估和保护措施的关键。相当大的努力是针对调查和监测在英国大冠蝾螈（Triturus cristatus）。越来越多地使用间接方法进行调查，例如环境DNA （eDNA）。我们使用了一个大型数据集来估计全国池塘占用率，以及商业eDNA协议的假阴性和假阳性错误率。此外，我们还探索了一系列栖息地、景观和气候变量作为池塘占用的预测因子。在英格兰，估计有20%的池塘被大冠蝾螈占据。池塘样本采集错误率估计为假阴性5.2%，假阳性1.5%。当使用12个qPCR重复时，实验室误差表明假阴性率可以忽略不计。实验室假阳性误差估计为每个qPCR重复的2%，因此被高水平的实验室复制所夸大。在模型中加入简单的栖息地适宜性变量，揭示了鱼类、植物和阴影作为预测蝾螈存在的重要性。然而，传统上被认为对蝾螈存在很重要的变量，如果要在建模练习中用作可靠的预测因子，可能需要更精确和一致的测量。
The distribution assessment and monitoring of species is key to reliable environmental impact assessments and conservation interventions. Considerable effort is directed towards survey and monitoring of great crested newts (Triturus cristatus) in England. Surveys are increasingly undertaken using indirect methodologies, such as environmental DNA (eDNA). We used a large data set to estimate national pond occupancy rate, as well as false negative and false positive error rates, for commercial eDNA protocols. Additionally, we explored a range of habitat, landscape and climatic variables as predictors of pond occupancy. In England, 20% of ponds were estimated to be occupied by great crested newts. Pond sample collection error rates were estimated as 5.2% false negative and 1.5% false positive. Laboratory error indicated a negligible false negative rate when 12 qPCR replicates were used. Laboratory false positive error was estimated at 2% per qPCR replicate and is therefore exaggerated by high levels of laboratory replication. Including simple habitat suitability variables into the model revealed the importance of fish, plants and shading as predictors of newt presence. However, variables traditionally considered as important for newt presence may need more precise and consistent measurement if they are to be employed as reliable predictors in modelling exercises.
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