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. 2020 Nov 7;10(11):2064.
doi: 10.3390/ani10112064.

Environmental DNA Metabarcoding as a Means of Estimating Species Diversity in an Urban Aquatic Ecosystem

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Environmental DNA Metabarcoding as a Means of Estimating Species Diversity in an Urban Aquatic Ecosystem

Heather J Webster et al. Animals (Basel). .

Abstract

Adaptation to environments that are changing as a result of human activities is critical to species' survival. A large number of species are adapting to, and even thriving in, urban green spaces, but this diversity remains largely undocumented. In the current study, we explored the potential of environmental DNA (eDNA) to document species diversity in one of the largest green spaces in Johannesburg, South Africa. Using a novel metabarcoding approach that assembles short DNA fragments suitable for massively parallel sequencing platforms to the approximate standard ~710 bp COI barcoding fragment, we document the presence of 26 phyla, 52 classes, 134 orders, 289 families, 380 genera and 522 known species from the study site. Our results highlight the critical role that urban areas play in protecting the world's declining biodiversity.

Keywords: biodiversity monitoring; environmental DNA; metagenomics; species diversity.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Sampling localities within Delta Park, Johannesburg. The Braamfontein Spruit flows in a northerly direction. The three collection sites are indicated. Aerial photo taken from Google Earth.
Figure 2
Figure 2
A funnel graph showing the cumulative length distribution of the unfiltered assembled sequences. The Y axis represents the cumulative length of the scaffolds in base pair. The bottleneck in the figure reflects ~710 bp, the theoretical length of the target sequences. Less than 5% of sequences had a length exceeding 713 bp, and these were removed from the dataset.
Figure 3
Figure 3
A circular tree showing the different organisms found in the water and sediment samples in Delta Park, South Africa. This tree is based on the results from the BLASTN search results.

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