Breed, M. F. et al. The potential of genomics for restoring ecosystems and biodiversity. Nat. Rev. Genet. 20, 615–628 (2019).
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).
Google Scholar
Geist, J. Integrative freshwater ecology and biodiversity conservation. Ecol. Indic. 11, 1507–1516 (2011).
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).
Google Scholar
Søndergaard, M. & Jeppesen, E. Anthropogenic impacts on lake and stream ecosystems, and approaches to restoration. J. Appl. Ecol. 44, 1089–1094 (2007).
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).
Google Scholar
Schindler, D. W. Recent advances in the understanding and management of eutrophication. Limnol. Oceanogr. 51, 356–363 (2006).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Google Scholar
Bush, A. et al. Studying ecosystems with DNA metabarcoding: Lessons from biomonitoring of aquatic macroinvertebrates. Front. Ecol. Evol. 7, 434 (2019).
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).
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).
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).
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).
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).
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).
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).
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).
Fernandes, K. et al. DNA metabarcoding—A new approach to fauna monitoring in mine site restoration. Restor. Ecol. 26, 1098–1107 (2018).
Google Scholar
Fernandes, K. et al. Invertebrate DNA metabarcoding reveals changes in communities across mine site restoration chronosequences. Restor. Ecol. 27, 1177–1186 (2019).
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).
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).
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).
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.
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).
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).
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).
Google Scholar
Rosling, A. et al. Archaeorhizomycetes: Unearthing an ancient class of ubiquitous soil fungi. Science 333, 876–879 (2011).
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).
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).
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).
Google Scholar
Luiza-Andrade, A., Montag, L. F. A. & Juen, L. Functional diversity in studies of aquatic macroinvertebrates community. Scientometrics 111, 1643–1656 (2017).
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).
Google Scholar
Pastorino, P. et al. Macrobenthic invertebrates as tracers of rare earth elements in freshwater watercourses. Sci. Total Environ. 698, 134282 (2020).
Google Scholar
Kulaš, A. et al. Ciliates (Alveolata, Ciliophora) as bioindicators of environmental pressure: A karstic river case. Ecol. Indic. 124, 107430 (2021).
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).
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).
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).
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).
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).
Google Scholar
Gibson, J. F. et al. Large-scale biomonitoring of remote and threatened ecosystems via high-throughput sequencing. PLoS ONE 10, e0138432 (2015).
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).
Google Scholar
Köster, J. & Rahmann, S. Snakemake—a scalable bioinformatics workflow engine. Bioinformatics 28, 2520–2522 (2012).
Google Scholar
Anon. Conda. (2016).
Porter, T. M. & Hajibabaei, M. Automated high throughput animal CO1 metabarcode classification. Sci. Rep. 8, 4226 (2018).
Google Scholar
Porter, T. M. Eukaryote CO1 Reference set for the RDP Classifier (Zenodo, 2017) https://doi.org/10.5281/zenodo.4741447.
Google Scholar
Porter, T. M. SILVA 18S Reference Set for the RDP Classifier(Zenodo, 2018) https://doi.org/10.5281/zenodo.4741433.
Google Scholar
R Core Team. R: A Language and Environment for Statistical Computing (R Core Team, 2020).
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2009). https://doi.org/10.1007/978-0-387-98141-3.
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).
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).
Google Scholar
Source: Ecology - nature.com