Cloern, J. E., Foster, S. Q. & Kleckner, A. E. Phytoplankton primary production in the world’s estuarine-coastal ecosystems. Biogeosciences 11, 2477–2501 (2014).
Google Scholar
Field, C. B., Behrenfeld, M. J., Randerson, J. T. & Falkowski, P. Primary production of the biosphere: Integrating terrestrial and oceanic components. Science (80-) 281, 237–240 (1998).
Google Scholar
Gervais, C. R., Champion, C. & Pecl, G. T. Species on the move around the Australian coastline: A continental scale review of climate-driven species redistribution in marine systems. Glob. Chang. Biol. 685, 171–181 (2021).
Scanes, E., Scanes, P. R. & Ross, P. M. Climate change rapidly warms and acidifies Australian estuaries. Nat. Commun. 11, 1–11 (2020).
Google Scholar
Rodrigues, J. G. et al. Marine and coastal cultural ecosystem services: knowledge gaps and research priorities. One Ecosyst. 2 (2017).
O’Brien, T. D., Lorenzoni, L., Isensee, K. & Valdés, L. What are marine ecological time series telling us about the ocean. A status report. IOC Tech. Ser. 129, 1–297 (2017).
Ajani, P. A., Davies, C. H., Eriksen, R. S. & Richardson, A. J. Global warming impacts micro-phytoplankton at a long-term Pacific Ocean Coastal Station. Front. Mar. Sci. 7, 878 (2020).
Google Scholar
Wiltshire, K. H. et al. Helgoland roads, North Sea: 45 years of change. Estuaries Coasts 33, 295–310 (2010).
Google Scholar
Benway, H. M. et al. Ocean time series observations of changing marine ecosystems: An era of integration, synthesis, and societal applications. Front. Mar. Sci. 6, 393 (2019).
Google Scholar
Wilson, J. M., Chamberlain, E. J., Erazo, N., Carter, M. L. & Bowman, J. S. Recurrent microbial community types driven by nearshore and seasonal processes in coastal Southern California. Environ. Microbiol. 23, 3225 (2021).
Google Scholar
Keeling, C. D. et al. Atmospheric carbon dioxide variations at Mauna Loa observatory, Hawaii. Tellus 28, 538–551 (1976).
Google Scholar
Doney, S. C., Fabry, V. J., Feely, R. A. & Kleypas, J. A. Ocean acidification: The other CO2 problem. Ann. Rev. Mar. Sci. 1, 169–192 (2009).
Google Scholar
Falkowski, P. G. Evolution of the nitrogen cycle and its influence on the biological sequestration of CO2 in the ocean. Nature 387, 272–275 (1997).
Google Scholar
Brown, M. V. et al. Systematic, continental scale temporal monitoring of marine pelagic microbiota by the Australian Marine Microbial Biodiversity Initiative. Sci. Data 5, 180130 (2018).
Google Scholar
Buttigieg, P. L. et al. Marine microbes in 4D—Using time series observation to assess the dynamics of the ocean microbiome and its links to ocean health. Curr. Opin. Microbiol. 43, 169–185 (2018).
Google Scholar
Chow, C.-E.T. et al. Temporal variability and coherence of euphotic zone bacterial communities over a decade in the southern California Bight. ISME J. 7, 2259–2273 (2013).
Google Scholar
Krabberød, A. K. et al. Long-term patterns of an interconnected core marine microbiota. bioRxiv 2021.03.18.435965. https://doi.org/10.1101/2021.03.18.435965 (2021).
Lambert, S. et al. Rhythmicity of coastal marine picoeukaryotes, bacteria and archaea despite irregular environmental perturbations. ISME J. 13, 388–401 (2019).
Google Scholar
Auladell, A. et al. Seasonal niche differentiation among closely related marine bacteria. ISME J. https://doi.org/10.1038/s41396-021-01053-2 (2021).
Google Scholar
Robicheau, B. M., Tolman, J., Bertrand, E. M. & LaRoche, J. Highly-resolved interannual phytoplankton community dynamics of the coastal Northwest Atlantic. ISME Commun. 2(1), 1–12 (2022).
Google Scholar
Legendre, L., Rivkin, R. B., Weinbauer, M. G., Guidi, L. & Uitz, J. The microbial carbon pump concept: Potential biogeochemical significance in the globally changing ocean. Prog. Oceanogr. 134, 432–450 (2015).
Google Scholar
Hutchins, D. A. & Fu, F. Microorganisms and ocean global change. Nat. Microbiol. 2, 1–11 (2017).
Google Scholar
Gross, T., Rudolf, L., Levin, S. A. & Dieckmann, U. Generalized models reveal stabilizing factors in food webs. Science (80-). 325, 747–750 (2009).
Google Scholar
Gilbert, J. A. et al. Defining seasonal marine microbial community dynamics. ISME J. 6, 298–308 (2012).
Google Scholar
Karl, D. M. & Church, M. J. Microbial oceanography and the Hawaii Ocean time-series programme. Nat. Rev. Microbiol. 12, 699–713 (2014).
Google Scholar
Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).
Google Scholar
Pachiadaki, M. G. et al. Charting the complexity of the marine microbiome through single-cell genomics. Cell 179, 1623–1635 (2019).
Google Scholar
Walsh, D. A. et al. Metagenome of a versatile chemolithoautotroph from expanding oceanic dead zones. Science (80-). 326, 578–582 (2009).
Google Scholar
Shan, S., Sheng, J., Thompson, K. R. & Greenberg, D. A. Simulating the three-dimensional circulation and hydrography of Halifax Harbour using a multi-nested coastal ocean circulation model. Ocean Dyn. 61, 951–976 (2011).
Google Scholar
Petrie, B. & Yeats, P. Simple models of the circulation, dissolved metals, suspended solids and nutrients in Halifax Harbour. Water Qual. Res. J. 25, 325–350 (1990).
Google Scholar
WK, W. L. The State of Phytoplankton and Bacterioplankton at the Compass Buoy Station: Bedford Basin Monitoring Program 1992–2013. (Fisheries and Oceans Canada = Pêches et Océans Canada, 2014).
Haas, S. et al. Physical mixing in coastal waters controls and decouples nitrification via biomass dilution. Proc. Natl. Acad. Sci. 118, e2004877118 (2021).
Google Scholar
Ibarbalz, F. M. et al. Global trends in marine plankton diversity across kingdoms of life. Cell 179, 1084-1097.e21 (2019).
Google Scholar
Mittelbach, G. G. et al. What is the observed relationship between species richness and productivity?. Ecology 82, 2381–2396 (2001).
Google Scholar
Pernthaler, J. Competition and niche separation of pelagic bacteria in freshwater habitats. Environ. Microbiol. 19, 2133–2150 (2017).
Google Scholar
Teeling, H. et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science (80-) 336, 608–611 (2012).
Google Scholar
Vallina, S. M. et al. Global relationship between phytoplankton diversity and productivity in the ocean. Nat. Commun. 5, 4299 (2014).
Google Scholar
Wietz, M. et al. The polar night shift: Annual dynamics and drivers of microbial community structure in the Arctic Ocean. bioRxiv 2021.04.08.436999. https://doi.org/10.1101/2021.04.08.436999 (2021).
Ladau, J. et al. Global marine bacterial diversity peaks at high latitudes in winter. ISME J. 7, 1669–1677 (2013).
Google Scholar
Sunagawa, S. et al. Structure and function of the global ocean microbiome. Science (80-). 348, 1261359 (2015).
Google Scholar
Brown, J. H. Why are there so many species in the tropics?. J. Biogeogr. 41, 8–22 (2014).
Google Scholar
Raes, E. J. et al. Oceanographic boundaries constrain microbial diversity gradients in the South Pacific Ocean. Proc. Natl. Acad. Sci. 115, E8266–E8275 (2018).
Google Scholar
Fuhrman, J. A. et al. A latitudinal diversity gradient in planktonic marine bacteria. Proc. Natl. Acad. Sci. 105, 7774–7778 (2008).
Google Scholar
Raes, E. J., Bodrossy, L., van de Kamp, J., Bissett, A. & Waite, A. M. Marine bacterial richness increases towards higher latitudes in the eastern Indian Ocean. Limnol. Oceanogr. Lett. 3, 10–19 (2018).
Google Scholar
Oksanen, J. et al. The vegan package. Commun. Ecol. Packag. 10, 719 (2007).
Mestre, M. et al. Sinking particles promote vertical connectivity in the ocean microbiome. Proc. Natl. Acad. Sci. 115, E6799–E6807 (2018).
Google Scholar
El-Swais, H., Dunn, K. A., Bielawski, J. P., Li, W. K. W. & Walsh, D. A. Seasonal assemblages and short-lived blooms in coastal north-west A tlantic O cean bacterioplankton. Environ. Microbiol. 17, 3642–3661 (2015).
Google Scholar
Raes, E. J. et al. Metabolic pathways inferred from a bacterial marker gene illuminate ecological changes across South Pacific frontal boundaries. Nat. Commun. 12, 2213 (2021).
Google Scholar
Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V. & Egozcue, J. J. Microbiome datasets are compositional: And this is not optional. Front. Microbiol. 8, 2224 (2017).
Google Scholar
Musat, N. et al. A single-cell view on the ecophysiology of anaerobic phototrophic bacteria. Proc. Natl. Acad. Sci. 105, 17861–17866 (2008).
Google Scholar
Wong, H. L., MacLeod, F. I., White, R. A., Visscher, P. T. & Burns, B. P. Microbial dark matter filling the niche in hypersaline microbial mats. Microbiome 8, 1–14 (2020).
Google Scholar
De Cáceres, M. How to use the indicspecies package (ver. 1.7.1). R Proj. 2, 29 (2013).
Hood, R. R. et al. Pelagic functional group modeling: Progress, challenges and prospects. Deep Sea Res. Part II Top. Stud. Oceanogr. 53, 459–512 (2006).
Google Scholar
Sun, S., Jones, R. B. & Fodor, A. A. Inference-based accuracy of metagenome prediction tools varies across sample types and functional categories. Microbiome 8, 1–9 (2020).
Google Scholar
Lynam, C. P. et al. Interaction between top-down and bottom-up control in marine food webs. Proc. Natl. Acad. Sci. 114, 1952–1957 (2017).
Google Scholar
Zhou, Z. et al. Gammaproteobacteria mediating utilization of methyl-, sulfur- and petroleum organic compounds in deep ocean hydrothermal plumes. ISME J. 14, 3136–3148 (2020).
Google Scholar
Dede, B. et al. Niche differentiation of sulfur-oxidizing bacteria (SUP05) in submarine hydrothermal plumes. ISME J. 16(6), 1479–1490 (2022).
Google Scholar
Lavik, G. et al. Detoxification of sulphidic African shelf waters by blooming chemolithotrophs. Nature 457, 581–584 (2009).
Google Scholar
Swan, B. K. et al. Potential for chemolithoautotrophy among ubiquitous bacteria lineages in the dark ocean. Science (80-) 333, 1296–1300 (2011).
Google Scholar
Taguchi, S. & Platt, T. Assimilation of 14CO2 in the dark compared to phytoplankton production in a small coastal inlet. Estuar. Coast. Mar. Sci. 5, 679–684 (1977).
Google Scholar
Platt, T. & Irwin, B. Phytoplankton Production and Nutrients in Bedford Basin, 1969–1970. (1971).
Vega, S. et al. Morphological plasticity in a sulfur-oxidizing marine bacterium from the SUP05 clade enhances dark carbon fixation. MBio 10, e00216-e219 (2021).
Mattes, T. E., Ingalls, A. E., Burke, S. & Morris, R. M. Metabolic flexibility of SUP05 under low DO growth conditions. Environ. Microbiol. 23, 2823 (2020).
Google Scholar
Brown, M. V. et al. Global biogeography of SAR11 marine bacteria. Mol. Syst. Biol. 8, 595 (2012).
Google Scholar
Martiny, A. C., Coleman, M. L. & Chisholm, S. W. Phosphate acquisition genes in Prochlorococcus ecotypes: Evidence for genome-wide adaptation. Proc. Natl. Acad. Sci. 103, 12552–12557 (2006).
Zorz, J. et al. Drivers of regional bacterial community structure and diversity in the Northwest Atlantic Ocean. Front. Microbiol. 10, 281 (2019).
Google Scholar
Comeau, A. M., Douglas, G. M. & Langille, M. G. I. Microbiome helper: A custom and streamlined workflow for microbiome research. MSystems 2, e00127 (2017).
Google Scholar
Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: Assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 18, 1403–1414 (2016).
Google Scholar
Walters, W. et al. Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1, e00009-15 (2016).
Google Scholar
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10 (2011).
Google Scholar
Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: A fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30, 614–620 (2014).
Google Scholar
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).
Google Scholar
Amir, A. et al. Deblur rapidly resolves single-nucleotide community sequence patterns. MSystems 2, 191–16 (2017).
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).
Google Scholar
Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).
Google Scholar
Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).
Google Scholar
Langille, M. G. I. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821 (2013).
Google Scholar
McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).
Google Scholar
Lahti L. & Shetty, S.A. Tools for Microbiome Analysis in R. Microbiome Package Version 1.7.21. R/Bioconductor http://microbiome.github.com/microbiome. (2017).
Team, R. C. R: A Language and Environment for Statistical Computing. (2013).
Wickham, H. ggplot2. Wiley Interdiscip. Rev. Comput. Stat. 3, 180–185 (2011).
Google Scholar
Schlitzer, R. Ocean Data View. 2018. Available odv. awi. (2015).
Hijmans, R. J., Williams, E., Vennes, C. & Hijmans, M. R. J. Package ‘geosphere’. in Spherical Trigonometry. Vol. 1 (2017).
Wickham, H. The split-apply-combine strategy for data analysis. J. Stat. Softw. 40, 1–29 (2011).
Groemping, U. & Matthias, L. Package ‘relaimpo’. (2021).
Clarke, K. R. & Gorley, R. N. Primer. Prim. Plymouth (2006).
Chytrý, M., Tichý, L., Holt, J. & Botta-Dukát, Z. Determination of diagnostic species with statistical fidelity measures. J. Veg. Sci. 13, 79–90 (2002).
Google Scholar
Tichy, L. & Chytry, M. Statistical determination of diagnostic species for site groups of unequal size. J. Veg. Sci. 17, 809–818 (2006).
Google Scholar
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