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Multi-marker DNA metabarcoding detects suites of environmental gradients from an urban harbour

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  • Breed, M. F. et al. The potential of genomics for restoring ecosystems and biodiversity. Nat. Rev. Genet. 20, 615–628 (2019).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Carpenter, S. R., Stanley, E. H. & Vander Zanden, M. J. State of the world’s freshwater ecosystems: Physical, chemical, and biological changes. Annu. Rev. Environ. Resour. 36, 75–99 (2011).

    Article 

    Google Scholar 

  • Geist, J. Integrative freshwater ecology and biodiversity conservation. Ecol. Indic. 11, 1507–1516 (2011).

    Article 

    Google Scholar 

  • Jeppesen, E., Søndergaard, M., Meerhoff, M., Lauridsen, T. L. & Jensen, J. P. Shallow lake restoration by nutrient loading reduction–some recent findings and challenges ahead. Hydrobiologia 584, 239–252 (2007).

    CAS 
    Article 

    Google Scholar 

  • Søndergaard, M. & Jeppesen, E. Anthropogenic impacts on lake and stream ecosystems, and approaches to restoration. J. Appl. Ecol. 44, 1089–1094 (2007).

    Article 

    Google Scholar 

  • Marburg, A. E., Turner, M. G. & Kratz, T. K. Natural and anthropogenic variation in coarse wood among and within lakes. J. Ecol. 94, 558–568 (2006).

    Article 

    Google Scholar 

  • Schindler, D. W. Recent advances in the understanding and management of eutrophication. Limnol. Oceanogr. 51, 356–363 (2006).

    ADS 
    Article 

    Google Scholar 

  • Lau, S. S. S. & Lane, S. N. Continuity and change in environmental systems: The case of shallow lake ecosystems. Prog. Phys. Geogr. Earth Environ. 25, 178–202 (2001).

    Article 

    Google Scholar 

  • Brinkhurst, R. O. Distribution and abundance of Tubificid (Oligochaeta) species in Toronto harbour, Lake Ontario. J. Fish. Res. Board Can. 27, 1961–1969 (1970).

    Article 

    Google Scholar 

  • Wood, L. W. & Chua, K. E. Glucose flux at the sediment-water interface of Toronto Harbour, Lake Ontario, with reference to pollution stress. Can. J. Microbiol. 19, 413–420 (1973).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Nriagu, J. O., Wong, H. K. T. & Snodgrass, W. J. Historical records of metal pollution in sediments of Toronto and Hamilton harbours. J. Gt. Lakes Res. 9(3), 365–373 (1983).

    CAS 
    Article 

    Google Scholar 

  • Toronto & Region Remedial Action Plan. Metro Toronto and Region Remedial Action Plan (1989).

  • Dahmer, S. C., Matos, L. & Morley, A. Restoring Toronto’s waters: Progress toward delisting the Toronto and Region area of concern. Aquat. Ecosyst. Health Manag. 21, 229–233 (2018).

    Article 

    Google Scholar 

  • Munawar, M., Norwood, W., McCarthy, L. & Mayfield, C. In situ bioassessment of dredging and disposal activities in a contaminated ecosystem: Toronto Harbour. Hydrobiologia https://doi.org/10.1007/978-94-009-1896-2_62 (1989).

    Article 

    Google Scholar 

  • Dahmer, S. C., Matos, L. & Jarvie, S. Assessment of the degradation of aesthetics beneficial use impairment in the Toronto and region area of concern. Aquat. Ecosyst. Health Manag. 21, 276–284 (2018).

    Article 

    Google Scholar 

  • Metro Toronto and Region Remedial Action Plan. Within Reach: 2015 Toronto an Region Remedial Action Plan Progress Report (2016).

  • Burniston, D. & Waltho, J. Report on Sediment Quality in the Toronto Inner Harbour 2007 (2011).

  • Elbrecht, V., Vamos, E. E., Meissner, K., Aroviita, J. & Leese, F. Assessing strengths and weaknesses of DNA metabarcoding-based macroinvertebrate identification for routine stream monitoring. Methods Ecol. Evol. 8, 1265–1275 (2017).

    Article 

    Google Scholar 

  • Emilson, C. E. et al. DNA metabarcoding and morphological macroinvertebrate metrics reveal the same changes in boreal watersheds across an environmental gradient. Sci. Rep. 7, 12777 (2017).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • Aylagas, E., Borja, Á., Muxika, I. & Rodríguez-Ezpeleta, N. Adapting metabarcoding-based benthic biomonitoring into routine marine ecological status assessment networks. Ecol. Indic. 95, 194–202 (2018).

    Article 

    Google Scholar 

  • Bush, A. et al. Studying ecosystems with DNA metabarcoding: Lessons from biomonitoring of aquatic macroinvertebrates. Front. Ecol. Evol. 7, 434 (2019).

    Article 

    Google Scholar 

  • Serrana, J. M., Miyake, Y., Gamboa, M. & Watanabe, K. Comparison of DNA metabarcoding and morphological identification for stream macroinvertebrate biodiversity assessment and monitoring. Ecol. Indic. 101, 963–972 (2019).

    Article 

    Google Scholar 

  • Fernández, S., Rodríguez-Martínez, S., Martínez, J. L., Garcia-Vazquez, E. & Ardura, A. How can eDNA contribute in riverine macroinvertebrate assessment? A metabarcoding approach in the Nalón River (Asturias, Northern Spain). Environ. DNA 1, 385–401 (2019).

    Article 

    Google Scholar 

  • Hajibabaei, M. et al. Watered-down biodiversity? A comparison of metabarcoding results from DNA extracted from matched water and bulk tissue biomonitoring samples. PLoS ONE 14, e0225409 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • Baird, D. J. & Hajibabaei, M. Biomonitoring 2.0: A new paradigm in ecosystem assessment made possible by next-generation DNA sequencing. Mol. Ecol. 21, 2039–2044 (2012).

    PubMed 
    Article 

    Google Scholar 

  • Hajibabaei, M., Baird, D. J., Fahner, N. A., Beiko, R. & Golding, G. B. A new way to contemplate Darwin’s tangled bank: How DNA barcodes are reconnecting biodiversity science and biomonitoring. Philos. Trans. R. Soc. B. Biol. Sci. 371, 20150330 (2016).

    Article 
    CAS 

    Google Scholar 

  • Beermann, A. J., Zizka, V. M. A., Elbrecht, V., Baranov, V. & Leese, F. DNA metabarcoding reveals the complex and hidden responses of chironomids to multiple stressors. Environ. Sci. Eur. 30, 26 (2018).

    Article 

    Google Scholar 

  • Bush, A. et al. DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness. Proc. Natl. Acad. Sci. 117, 8539–8545 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • Compson, Z. G. et al. Chapter Two—Linking DNA Metabarcoding and Text Mining to Create Network-Based Biomonitoring Tools: A Case Study on Boreal Wetland Macroinvertebrate Communities. In Advances in Ecological Research Vol. 59 (eds Bohan, D. A. et al.) 33–74 (Academic Press, 2018).

    Google Scholar 

  • Fernandes, K. et al. DNA metabarcoding—A new approach to fauna monitoring in mine site restoration. Restor. Ecol. 26, 1098–1107 (2018).

    Article 

    Google Scholar 

  • Fernandes, K. et al. Invertebrate DNA metabarcoding reveals changes in communities across mine site restoration chronosequences. Restor. Ecol. 27, 1177–1186 (2019).

    Article 

    Google Scholar 

  • Poikane, S. et al. Benthic macroinvertebrates in lake ecological assessment: A review of methods, intercalibration and practical recommendations. Sci. Total Environ. 543, 123–134 (2016).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Macher, J.-N. et al. Comparison of environmental DNA and bulk-sample metabarcoding using highly degenerate cytochrome c oxidase I primers. Mol. Ecol. Resour. 18, 1456–1468 (2018).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Marshall, N. T. & Stepien, C. A. Macroinvertebrate community diversity and habitat quality relationships along a large river from targeted eDNA metabarcode assays. Environ. DNA 2, 572–586 (2020).

    Article 

    Google Scholar 

  • Metro Toronto and Region Remedial Action Plan. Updates on Actions 2013–2014. (2013).

  • López-López, E. & Sedeño-Díaz, J. E. Biological indicators of water quality: The role of fish and macroinvertebrates as indicators of water quality. In Environmental Indicators (eds Armon, R. H. & Hänninen, O.) 643–661 (Springer Netherlands, 2015). https://doi.org/10.1007/978-94-017-9499-2_37.

    Chapter 

    Google Scholar 

  • Berry, O. et al. A Comparison of Morphological and DNA Metabarcoding Analysis of Diets in Exploited Marine Fishes (2015).

  • Sweeney, B. W., Battle, J. M., Jackson, J. K. & Dapkey, T. Can DNA barcodes of stream macroinvertebrates improve descriptions of community structure and water quality?. J. N. Am. Benthol. Soc. 30, 195–216 (2011).

    Article 

    Google Scholar 

  • Banerji, A. et al. Spatial and temporal dynamics of a freshwater eukaryotic plankton community revealed via 18S rRNA gene metabarcoding. Hydrobiologia 818, 71–86 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • Porter, T. M. et al. Widespread occurrence and phylogenetic placement of a soil clone group adds a prominent new branch to the fungal tree of life. Mol. Phylogenet. Evol. 46, 635–644 (2008).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Rosling, A. et al. Archaeorhizomycetes: Unearthing an ancient class of ubiquitous soil fungi. Science 333, 876–879 (2011).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Mandaville, S. M. Benthic Macroinvertebrates in Freshwaters—Taxa Tolerance Values, Metrics, and Protocols, vol. 128. http://lakes.chebucto.org/H-1/tolerance.pdf (2002).

  • Trzcinski, M. K. et al. The effects of food web structure on ecosystem function exceeds those of precipitation. J. Anim. Ecol. 85, 1147–1160 (2016).

    PubMed 
    Article 

    Google Scholar 

  • Liu, X. & Wang, H. Contrasting patterns and drivers in taxonomic versus functional diversity, and community assembly of aquatic plants in subtropical lakes. Biodivers. Conserv. 27(12), 3103–3118 (2018).

    Article 

    Google Scholar 

  • Kovalenko, K. E., Brady, V. J., Ciborowski, J. J. H., Ilyushkin, S. & Johnson, L. B. Functional changes in littoral macroinvertebrate communities in response to watershed-level anthropogenic stress. PLoS ONE 9, e101499 (2014).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • Luiza-Andrade, A., Montag, L. F. A. & Juen, L. Functional diversity in studies of aquatic macroinvertebrates community. Scientometrics 111, 1643–1656 (2017).

    Article 

    Google Scholar 

  • MacMillan, G. A., Chételat, J., Heath, J. P., Mickpegak, R. & Amyot, M. Rare earth elements in freshwater, marine, and terrestrial ecosystems in the eastern Canadian Arctic. Environ. Sci. Process. Impacts 19, 1336–1345 (2017).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Pastorino, P. et al. Macrobenthic invertebrates as tracers of rare earth elements in freshwater watercourses. Sci. Total Environ. 698, 134282 (2020).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Kulaš, A. et al. Ciliates (Alveolata, Ciliophora) as bioindicators of environmental pressure: A karstic river case. Ecol. Indic. 124, 107430 (2021).

    Article 

    Google Scholar 

  • Persaud, D., Lomas, T., Boyd, D. & Mathai, S. Historical Development and Quality of the Toronto Waterfront Sediments (1985).

  • Milani, D. & Grapentine, L. Assessment of Sediment Quality in the Bay of Quinte Area Of Concern (2000).

  • Reynoldson, T. B., Bailey, R. C., Day, K. E. & Norris, R. H. Biological guidelines for freshwater sediment based on BEnthic Assessment of SedimenT (the BEAST) using a multivariate approach for predicting biological state. Aust. J. Ecol. 20(1), 198–219 (1995).

    Article 

    Google Scholar 

  • Geller, J., Meyer, C., Parker, M. & Hawk, H. Redesign of PCR primers for mitochondrial cytochrome c oxidase subunit I for marine invertebrates and application in all-taxa biotic surveys. Mol. Ecol. Resour. 13, 851–861 (2013).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • Leray, M. et al. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: Application for characterizing coral reef fish gut contents. Front. Zool. 10, 34 (2013).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • Zhan, A. et al. High sensitivity of 454 pyrosequencing for detection of rare species in aquatic communities. Methods Ecol. Evol. 4, 558–565 (2013).

    Article 

    Google Scholar 

  • Gibson, J. et al. Simultaneous assessment of the macrobiome and microbiome in a bulk sample of tropical arthropods through DNA metasystematics. Proc. Natl. Acad. Sci. 111, 8007–8012 (2014).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • Gibson, J. F. et al. Large-scale biomonitoring of remote and threatened ecosystems via high-throughput sequencing. PLoS ONE 10, e0138432 (2015).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • Porter, T. M. & Hajibabaei, M. METAWORKS: A flexible, scalable bioinformatic pipeline for multi-marker biodiversity assessments. bioRxiv https://doi.org/10.1101/2020.07.14.202960 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Köster, J. & Rahmann, S. Snakemake—a scalable bioinformatics workflow engine. Bioinformatics 28, 2520–2522 (2012).

    PubMed 
    Article 
    CAS 

    Google Scholar 

  • Anon. Conda. (2016).

  • Porter, T. M. & Hajibabaei, M. Automated high throughput animal CO1 metabarcode classification. Sci. Rep. 8, 4226 (2018).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • Porter, T. M. Eukaryote CO1 Reference set for the RDP Classifier (Zenodo, 2017) https://doi.org/10.5281/zenodo.4741447.

    Book 

    Google Scholar 

  • Porter, T. M. SILVA 18S Reference Set for the RDP Classifier(Zenodo, 2018) https://doi.org/10.5281/zenodo.4741433.

    Book 

    Google Scholar 

  • R Core Team. R: A Language and Environment for Statistical Computing (R Core Team, 2020).

    Google Scholar 

  • Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2009). https://doi.org/10.1007/978-0-387-98141-3.

    Book 
    MATH 

    Google Scholar 

  • Oksanen, J. et al. vegan: Community Ecology Package (2020).

  • Komsta, L. & Novomestky, F. moments: Moments, cumulants, skewness, kurtosis and related tests (2015).

  • U.S. Environmental Protection Agency. Freshwater Biological Traits Database (Final Report) EPA/600/R-11/038F. (2012)

  • U.S. Environmental Protection Agency. Freshwater Biological Traits Database (2012).

  • Schmidt-Kloiber, A. & Hering, D. An online tool that unifies, standardises and codifies more than 20,000 European freshwater organisms and their ecological preferences. Ecol. Indic. 53, 271–282 (2015).

    Article 

    Google Scholar 

  • Moog, O. Fauna Aquatica Austriaca – Catalogue for autecological Classification of Austrian Aquatic Organisms (1995).

  • Tachet, H., Bournaud, M., Richoux, P., Usseglio-Polatera, P. Invertébrés d’eau douce – systématique, biologie, écologie (2010).

  • Nally, R. M. & Walsh, C. J. Hierarchical partitioning public-domain software. Biodivers. Conserv. https://doi.org/10.1023/B:BIOC.0000009515.11717.0b (2004).

    Article 

    Google Scholar 


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