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      Environmental DNA allows upscaling spatial patterns of biodiversity in freshwater ecosystems

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          Abstract

          The alarming declines of freshwater biodiversity call for efficient biomonitoring at fine spatiotemporal scales, such that conservation measures be grounded upon accurate biodiversity data. Here, we show that combining environmental DNA (eDNA) extracted from stream water samples with models based on hydrological first principles allows upscaling biodiversity estimates for aquatic insects at very high spatial resolution. Our model decouples the diverse upstream contributions to the eDNA data, enabling the reconstruction of taxa distribution patterns. Across a 740-km 2 basin, we obtain a space-filling biodiversity prediction at a grain size resolution of 1-km long stream sections. The model’s accuracy in matching direct observations of aquatic insects’ local occurrence ranges between 57–100%. Our results demonstrate how eDNA can be used for high-resolution biodiversity assessments in rivers with minimal prior knowledge of the system. Our approach allows identification of biodiversity hotspots that could be otherwise overlooked, enabling implementation of focused conservation strategies.

          Abstract

          Biomonitoring via environmental DNA (eDNA) is an important conservation tool for freshwater ecosystems, but this is complicated by eDNA movement downstream. Here, Carraro et al. develop and test an approach to reconstruct high-resolution spatial biodiversity patterns from freshwater eDNA.

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          Environmental DNA metabarcoding: Transforming how we survey animal and plant communities

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            ITS as an environmental DNA barcode for fungi: an in silico approach reveals potential PCR biases

            Background During the last 15 years the internal transcribed spacer (ITS) of nuclear DNA has been used as a target for analyzing fungal diversity in environmental samples, and has recently been selected as the standard marker for fungal DNA barcoding. In this study we explored the potential amplification biases that various commonly utilized ITS primers might introduce during amplification of different parts of the ITS region in samples containing mixed templates ('environmental barcoding'). We performed in silico PCR analyses with commonly used primer combinations using various ITS datasets obtained from public databases as templates. Results Some of the ITS primers, such as ITS1-F, were hampered with a high proportion of mismatches relative to the target sequences, and most of them appeared to introduce taxonomic biases during PCR. Some primers, e.g. ITS1-F, ITS1 and ITS5, were biased towards amplification of basidiomycetes, whereas others, e.g. ITS2, ITS3 and ITS4, were biased towards ascomycetes. The assumed basidiomycete-specific primer ITS4-B only amplified a minor proportion of basidiomycete ITS sequences, even under relaxed PCR conditions. Due to systematic length differences in the ITS2 region as well as the entire ITS, we found that ascomycetes will more easily amplify than basidiomycetes using these regions as targets. This bias can be avoided by using primers amplifying ITS1 only, but this would imply preferential amplification of 'non-dikarya' fungi. Conclusions We conclude that ITS primers have to be selected carefully, especially when used for high-throughput sequencing of environmental samples. We suggest that different primer combinations or different parts of the ITS region should be analyzed in parallel, or that alternative ITS primers should be searched for.
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              The extraction of drainage networks from digital elevation data

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                Author and article information

                Contributors
                luca.carraro@eawag.ch
                florian.altermatt@ieu.uzh.ch
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                17 July 2020
                17 July 2020
                2020
                : 11
                : 3585
                Affiliations
                [1 ]ISNI 0000 0004 1937 0650, GRID grid.7400.3, Department of Evolutionary Biology and Environmental Studies, , University of Zurich, ; Winterthurerstr. 190, CH-8057 Zürich, Switzerland
                [2 ]ISNI 0000 0001 1551 0562, GRID grid.418656.8, Department of Aquatic Ecology, , Eawag, Swiss Federal Institute of Aquatic Science and Technology, ; Überlandstrasse 133, CH-8600 Dübendorf, Switzerland
                [3 ]gutwasser GmbH, Geerenweg 2, CH-8048 Zürich, Switzerland
                [4 ]ISNI 0000 0004 1937 0650, GRID grid.7400.3, University Research Priority Programme (URPP) on Global Change and Biodiversity, University of Zurich, ; Winterthurerstr. 190, CH-8057 Zürich, Switzerland
                Author information
                http://orcid.org/0000-0002-3933-1144
                http://orcid.org/0000-0002-4831-6958
                Article
                17337
                10.1038/s41467-020-17337-8
                7367889
                32680984
                863ea86b-2e57-46c1-af5e-cf9ccc16cd6b
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 December 2019
                : 25 June 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation);
                Award ID: PP00P3_179089
                Award ID: 31003A_173074
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                conservation biology,freshwater ecology,molecular ecology,hydrology
                Uncategorized
                conservation biology, freshwater ecology, molecular ecology, hydrology

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