Executing multi-taxa eDNA ecological assessment via traditional metrics and interactive networks.
Executing multi-taxa eDNA ecological assessment via traditional metrics and interactive networks.
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通过传统指标和交互式网络执行多分类单元 eDNA 生态评估。
DOI：
10.1016/j.scitotenv.2020.138801
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Seymour M
中科院分区：
文献类型：
--
作者：
Seymour M
目前的生态评估方法受到传统形态分类学方法的限制，无法满足日益增长的快速评估需求。高通量测序的进步现在可以使用环境DNA（eDNA）进行快速高分辨率的生态评估。在这里，我们测试的能力，使用基于eDNA的生态评估方法对传统的评估两个关键指标组（硅藻和大型无脊椎动物），并显示如何跨多个基因区域（COI，rbcL，12S和18S）的eDNA可以用来推断互动网络，链接到生态评估标准。我们比较了分类和基于eDNA的评估之间的结果，发现大型无脊椎动物（p< 0.001，R2= 0.645）和硅藻（p= 0.015，R2= 0.222）评估指标之间存在显著的正相关。我们进一步评估了基于eDNA的评估，以确定环境敏感的属的能力，并发现了一个数量级更大的潜力为18 S，COI或rbcL，以确定生态评估社区的环境过滤。最后，我们比较了传统指标的能力，对共生网络属性的18S，COI和rbcL指标属推断栖息地质量措施目前使用的管理人员。我们发现，传递性（网络连接），连接密度和凝聚力显着相关的栖息地修改分数（HMS），而网络属性是不一致的链接到栖息地质量分数（HQS）度量。多标记eDNA网络评估的结合开辟了一种手段，更精细的尺度生态评估，目前使用传统的方法有限。虽然建议使用基于eDNA的评估，但与传统方法进行直接比较是困难的，因为这些方法本质上是不同的，在未来的研究中应该这样对待。总的来说，我们的研究结果表明，eDNA可以用于有效的生态评估，同时提供了更广泛的范围和应用相比，传统的评估方法。
Current approaches to ecological assessment are limited by the traditional morpho-taxonomic methods presently employed and the inability to meet increasing demands for rapid assessments. Advancements in high throughput sequencing now enable rapid high-resolution ecological assessment using environmental DNA (eDNA). Here we test the ability of using eDNA-based ecological assessment methods against traditional assessment of two key indicator groups (diatoms and macroinvertebrates) and show how eDNA across multiple gene regions (COI, rbcL, 12S and 18S) can be used to infer interactive networks that link to ecological assessment criteria. We compared results between taxonomic and eDNA based assessments and found significant positive associations between macroinvertebrate (p< 0.001 R2= 0.645) and diatom (p= 0.015, R2= 0.222) assessment metrics. We further assessed the ability of eDNA based assessment to identify environmentally sensitive genera and found an order of magnitude greater potential for 18S, versus COI or rbcL, to determine environmental filtering of ecologically assessed communities. Lastly, we compared the ability of traditional metrics against co-occurrence network properties of our combined 18S, COI and rbcL indicator genera to infer habitat quality measures currently used by managers. We found that transitivity (network connectivity), linkage density and cohesion were significantly associated with habitat modification scores (HMS), whereas network properties were inconsistent with linking to the habitat quality score (HQS) metric. The incorporation of multi-marker eDNA network assessment opens up a means for finer scale ecological assessment, currently limited using traditional methods. While utilization of eDNA-based assessment is recommended, direct comparisons with traditional approaches are difficult as the methods are intrinsically different and should be treated as such with regards to future research. Overall, our findings show that eDNA can be used for effective ecological assessment while offering a wider range of scope and application compared to traditional assessment methods.
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