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Towards standardized operating procedures for eDNA-based monitoring of marine coastal ecosystems
Rubel, V. (2022). Towards standardized operating procedures for eDNA-based monitoring of marine coastal ecosystems. PhD Thesis. Technische Universität Kaiserslautern: Kaiserslautern. 281 pp.

Keyword
    Marine/Coastal

Author  Top 
  • Rubel, V.

Abstract
    Marine coastal ecosystems are exposed to a variety of anthropogenic impacts, which often manifest themselves in the pollution of the surrounding ecosystem. Especially on densely populated coasts or in regions heavily used for aquaculture, changes in the natural marine habitat can be observed. In order to protect nature and thus its ecosystem services for humans, more and more environmental protection laws are coming into force. Exemplary, operators of facilities known to contribute to pollution are obliged to regularly monitor the condition of the surrounding environment. The purpose of such so-called compliance monitoring is to determine whether the prescribed regulations are being followed. The traditional routine involves sampling by ship, during which sediment samples are taken from the seabed below the aquaculture cages and all macrofauna organisms found, such as mussels or worms, are taxonomically determined and quantified by experts. Based on the community of organisms the ecological status of the sample can then be inferred. Since this method is very labor- and time-consuming, a reorientation of the scientific community towards alternative monitoring methods is currently taking place. A bacteria-based eDNA (environmental DNA) metabarcoding system in particular has proven to be a suitable monitoring tool. With this molecular method, the composition of the benthic bacterial community is determined using high-throughput sequencing. The great advantage of this method is that bacteria, due to their short generation times, react rapidly to various environmental influences. The composition of this community can then be used to infer the ecological status of the sample under investigation via sequencing without the need for laborious enumeration and identification of organisms. Additionally, sequencing costs are more and more decreasing, proposing eDNA metabarcoding-based monitoring as a faster and cheaper alternative to traditional monitoring. In order to implement the method in legislation in the long term, standard protocols need to be developed. Once these are sufficiently validated, the novel methodology can be incorporated into regulations to support or even replace traditional monitoring. However, some steps of the eDNA metabarcoding method, from sampling to ecosystem assessment, are not yet sufficiently standardized, which is why the development of this work was necessary. Since there is no consensus in the scientific community on (i) the preservation of environmental samples during transport, (ii) the reproducibility of ecosystem assessment among different laboratories, (iii) the most appropriate bioinformatic method for ecosystem assessment, and (iv) the minimum sequencing depth required to determine ecosystem status, these sub-steps were investigated. It was found that the most common methods currently used to preserve samples during transport had no discernible effect on the final ecosystem assessment. Furthermore, sample processing in independent laboratories allowed the same ecological interpretations based on the bacterial community, which resulted in concordant ecosystem assessments among laboratories. This indicates the overall reproducibility of the eDNA metabarcoding-based method, thus enabling its implementation in standard protocols. Furthermore, it was shown that corresponding ecosystem assessments can be obtained with the currently used methods for determining ecological status based on eDNA data. Critical to predictive accuracy is not the method itself, but a sufficient number of samples that accounts for the natural spatial and temporal variability of bacterial communities. It was demonstrated that a very shallow sequencing depth per sample can be sufficient to use machine learning to prediction the ecological status of the environmental sample. The quality of this classifications did not depend on the sequencing depth as assumed but was determined by the separability of individual categories. The results and recommendations of this work contribute directly to the standardization of ecological assessment of nearshore marine ecosystems. By establishing these standard protocols, it will be possible to integrate the eDNA metabarcoding-based method for monitoring compliance of coastal marine ecosystems into legislative regulations in the future.

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