Hauger Amberly N, Hollis-Etter Karmen M, Etter Dwayne R, Roloff Gary J, Mahon Andrew R
Biology Department, University of Michigan-Flint, Flint, MI, United States of America.
Wildlife Division, Michigan Department of Natural Resources, East Lansing, MI, United States of America.
PeerJ. 2020 Jan 2;8:e8287. doi: 10.7717/peerj.8287. eCollection 2020.
Invasive feral swine can damage ecosystems, disrupt plant and animal populations, and transmit diseases. Monitoring of feral swine populations requires expensive and labor-intensive techniques such as aerial surveys, field surveys for sign, trail cameras, and verifying landowner reports. Environmental DNA (eDNA) provides an alternative method for locating feral swine. To aid in detection of this harmful invasive species, a novel assay was developed incorporating molecular methods. From August 2017 to April 2018, water samples and stream data were collected along 400 m transects in two different stream types where swine DNA was artificially introduced to investigate potential factors affecting detection. A generalized linear model (family binomial) was used to characterize environmental conditions affecting swine DNA detection; detection was the dependent variable and stream measurements included stream type, distance downstream, water temperature, velocity, turbidity, discharge, and pH as independent variables. Parameters from the generalized linear model were deemed significant if 95% confidence intervals did not overlap 0. Detection probability for swine DNA negatively related to water temperature ( = - 0.21, 95% CI [-0.35 to -0.09]), with the highest detection probability (0.80) at 0 °C and lowest detection probability (0.05) at 17.9 °C water temperature. Results indicate that sampling for swine eDNA in free-flowing stream systems should occur at lower water temperatures to maximize detection probability. This study provides a foundation for further development of field and sampling techniques for utilizing eDNA as a viable alternative to monitoring a terrestrial invasive species in northern regions of the United States.
入侵性野猪会破坏生态系统、扰乱动植物种群并传播疾病。监测野猪种群需要采用昂贵且耗费人力的技术,如空中调查、踪迹现场调查、追踪相机以及核实土地所有者报告等。环境DNA(eDNA)为定位野猪提供了一种替代方法。为了有助于检测这种有害的入侵物种,开发了一种结合分子方法的新型检测方法。2017年8月至2018年4月,在两种不同的溪流类型中沿着400米的样带收集了水样和溪流数据,在这些地方人工引入了猪的DNA,以调查影响检测的潜在因素。使用广义线性模型(二项分布族)来描述影响猪DNA检测的环境条件;检测为因变量,溪流测量值包括溪流类型、下游距离、水温、流速、浊度、流量和pH值作为自变量。如果95%的置信区间不与0重叠,则广义线性模型的参数被认为是显著的。猪DNA的检测概率与水温呈负相关(β = -0.21,95% CI [-0.35至-0.09]),在0°C时检测概率最高(0.80),在水温17.9°C时检测概率最低(0.05)。结果表明,在自由流动的溪流系统中采集猪eDNA样本应在较低水温下进行,以最大限度提高检测概率。本研究为进一步开发利用eDNA作为监测美国北部地区陆生入侵物种的可行替代方法的野外和采样技术奠定了基础。