海洋eDNA的产生和损失机制

IF 3.4 2区 地球科学 Q1 OCEANOGRAPHY Journal of Geophysical Research-Oceans Pub Date : 2025-04-24 DOI:10.1029/2024JC021643
Elizabeth Brasseale, Nicolaus Adams, Elizabeth Andruszkiewicz Allan, Eiren K. Jacobson, Ryan P. Kelly, Owen R. Liu, Stephanie Moore, Megan Shaffer, Jilian Xiong, Kim Parsons
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引用次数: 0

摘要

环境DNA (eDNA)分析是一种在空气、水或土壤等环境中检测生物遗传物质的技术。由于生物和环境过程,观察到的eDNA浓度在空间和时间上发生变化。在这里,我们研究了eDNA产生和损失的可变性,通过在48小时的近小时时间尺度上采样非本地鲸类种群附近的水。我们使用不同的采样方法和建模方法来描述观察到的eDNA浓度的时间变异性,然后比较产生和损失机制的大小。我们在概念盒模型中分析了产量和损失率,并使用衰变实验和物理传输和扩散示踪剂模型比较了生物和物理损失率。然后,根据模型参数估计,我们沿着远离动物围栏的样带评估eDNA浓度。我们的结论是,eDNA的产生最好使用时变混合状态模型来概念化,并且相对于海洋环境中的物理损失,生物损失较小。由于物理损失是非定常和非线性的,示踪模型是准确估计物理损失的特别有用的工具。
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Marine eDNA Production and Loss Mechanisms

Environmental DNA (eDNA) analysis is a technique for detecting organisms based on genetic material in environments such as air, water, or soil. Observed eDNA concentrations vary in space and time due to biological and environmental processes. Here, we investigate variability in eDNA production and loss by sampling water adjacent to a managed population of non-native cetaceans on a near-hourly timescale for 48 hr. We used diverse sampling approaches and modeling methods to describe time variability in observed eDNA concentrations and then compare the magnitude of production and loss mechanisms. We parsed production and loss in a conceptual box model and compared biological and physical loss rates using a decay experiment and a physical transport-and-diffusion tracer model. We then evaluated eDNA concentrations along a transect away from the animal enclosure in light of model parameter estimates. We conclude that eDNA production is best conceptualized using a time-varying mixed-state model, and biological losses are small relative to physical losses in the marine environment. Because physical loss is unsteady and nonlinear, tracer models are especially helpful tools to estimate it accurately.

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来源期刊
Journal of Geophysical Research-Oceans
Journal of Geophysical Research-Oceans Earth and Planetary Sciences-Oceanography
CiteScore
7.00
自引率
13.90%
发文量
429
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