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Metabolic flexibility allows bacterial habitat generalists to become dominant in a frequently disturbed ecosystem

  • 1.

    Wilson DS, Yoshimura J. On the coexistence of specialists and generalists. Am Nat. 1994;144:692–707.

    Article 

    Google Scholar 

  • 2.

    Slatyer RA, Hirst M, Sexton JP. Niche breadth predicts geographical range size: a general ecological pattern. Ecol Lett. 2013;16:1104–14.

    PubMed 
    Article 

    Google Scholar 

  • 3.

    Büchi L, Vuilleumier S. Coexistence of specialist and generalist species is shaped by dispersal and environmental factors. Am Nat. 2014;183:612–24.

    PubMed 
    Article 

    Google Scholar 

  • 4.

    Vellend M. Conceptual synthesis in community ecology. Q Rev Biol. 2010;85:183–206.

    PubMed 
    Article 

    Google Scholar 

  • 5.

    Kassen R. The experimental evolution of specialists, generalists, and the maintenance of diversity. J Evol Biol. 2002;15:173–90.

    Article 

    Google Scholar 

  • 6.

    Devictor V, Julliard R, Jiguet F. Distribution of specialist and generalist species along spatial gradients of habitat disturbance and fragmentation. Oikos. 2008;117:507–14.

    Article 

    Google Scholar 

  • 7.

    Clavel J, Julliard R, Devictor V. Worldwide decline of specialist species: toward a global functional homogenization? Front Ecol Environ. 2011;9:222–8.

    Article 

    Google Scholar 

  • 8.

    Marvier M, Kareiva P, Neubert MG. Habitat destruction, fragmentation, and disturbance promote invasion by habitat generalists in a multispecies metapopulation. Risk Anal Int J. 2004;24:869–78.

    Article 

    Google Scholar 

  • 9.

    Loehle C. Strategy space and the disturbance spectrum: a life-history model for tree species coexistence. Am Nat. 2000;156:14–33.

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 10.

    Székely AJ, Langenheder S. The importance of species sorting differs between habitat generalists and specialists in bacterial communities. FEMS Microbiol Ecol. 2014;87:102–12.

    PubMed 
    Article 
    CAS 

    Google Scholar 

  • 11.

    Mariadassou M, Pichon S, Ebert D. Microbial ecosystems are dominated by specialist taxa. Ecol Lett. 2015;18:974–82.

    PubMed 
    Article 

    Google Scholar 

  • 12.

    Carbonero F, Oakley BB, Purdy KJ. Metabolic flexibility as a major predictor of spatial distribution in microbial communities. PLoS ONE. 2014;9:e85105.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 13.

    Nemergut DR, Schmidt SK, Fukami T, O’Neill SP, Bilinski TM, Stanish LF, et al. Patterns and processes of microbial community assembly. Microbiol Mol Biol Rev. 2013;77:342–56.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 14.

    Wang J, Shen J, Wu Y, Tu C, Soininen J, Stegen JC, et al. Phylogenetic beta diversity in bacterial assemblages across ecosystems: Deterministic versus stochastic processes. ISME J. 2013;7:1310–21.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 15.

    Caruso T, Chan Y, Lacap DC, Lau MCY, McKay CP, Pointing SB. Stochastic and deterministic processes interact in the assembly of desert microbial communities on a global scale. ISME J. 2011;5:1406.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 16.

    Delgado-Baquerizo M, Oliverio AM, Brewer TE, Benavent-González A, Eldridge DJ, Bardgett RD, et al. A global atlas of the dominant bacteria found in soil. Science. 2018;359:320–5.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 17.

    Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, et al. Structure and function of the global ocean microbiome. Science. 2015;348:1261359.

    PubMed 
    Article 
    CAS 

    Google Scholar 

  • 18.

    Sriswasdi S, Yang C, Iwasaki W. Generalist species drive microbial dispersion and evolution. Nat Commun. 2017;8:1162.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 19.

    Nicholls DG, Ferguson S. Bioenergetics. Academic Press; Cambridge, Massachusetts, USA; 2013.

  • 20.

    Jones SE, Lennon JT. Dormancy contributes to the maintenance of microbial diversity. Proc Natl Acad Sci USA. 2010;107:5881–6.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 21.

    Lennon JT, Jones SE. Microbial seed banks: the ecological and evolutionary implications of dormancy. Nat Rev Microbiol. 2011;9:119–30.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 22.

    Ji M, Greening C, Vanwonterghem I, Carere CR, Bay SK, Steen JA, et al. Atmospheric trace gases support primary production in Antarctic desert surface soil. Nature. 2017;552:400–3.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 23.

    Mußmann M, Pjevac P, Krüger K, Dyksma S. Genomic repertoire of the Woeseiaceae/JTB255, cosmopolitan and abundant core members of microbial communities in marine sediments. ISME J. 2017;11:1276.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 24.

    Tsementzi D, Wu J, Deutsch S, Nath S, Rodriguez-R LM, Burns AS, et al. SAR11 bacteria linked to ocean anoxia and nitrogen loss. Nature. 2016;536:179.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 25.

    Carere CR, Hards K, Houghton KM, Power JF, McDonald B, Collet C, et al. Mixotrophy drives niche expansion of verrucomicrobial methanotrophs. ISME J. 2017;11:2599–610.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 26.

    Greening C, Grinter R, Chiri E. Uncovering the metabolic strategies of the dormant microbial majority: towards integrative approaches. mSystems. 2019;4:e00107–19.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 27.

    Rodriguez-r LM, Overholt WA, Hagan C, Huettel M, Kostka JE, Konstantinidis KT. Microbial community successional patterns in beach sands impacted by the Deepwater Horizon oil spill. ISME J. 2015;9:1928–40.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 28.

    Herold M, Arbas SM, Narayanasamy S, Sheik AR, Kleine-Borgmann LAK, Lebrun LA, et al. Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance. Nat Commun. 2020;11:1–14.

    Article 
    CAS 

    Google Scholar 

  • 29.

    Muller EEL. Determining microbial niche breadth in the environment for better ecosystem fate predictions. mSystems. 2019;4:e00080–19.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 30.

    Huettel M, Berg P, Kostka JE. Benthic exchange and biogeochemical cycling in permeable sediments. Ann Rev Mar Sci. 2014;6:23–51.

    PubMed 
    Article 

    Google Scholar 

  • 31.

    Boudreau BP, Huettel M, Forster S, Jahnke RA, McLachlan A, Middelburg JJ, et al. Permeable marine sediments: overturning an old paradigm. EOS, Trans Am Geophys Union. 2001;82:133–6.

    Google Scholar 

  • 32.

    Devol AH. Denitrification, anammox, and N2 production in marine sediments. Ann Rev Mar Sci. 2015;7:403–23.

    PubMed 
    Article 

    Google Scholar 

  • 33.

    Reimers CE, Stecher HA III, Taghon GL, Fuller CM, Huettel M, Rusch A, et al. In situ measurements of advective solute transport in permeable shelf sands. Cont Shelf Res. 2004;24:183–201.

    Article 

    Google Scholar 

  • 34.

    Santos IR, Eyre BD, Huettel M. The driving forces of porewater and groundwater flow in permeable coastal sediments: a review. Estuar Coast Shelf Sci. 2012;98:1–15.

    Article 

    Google Scholar 

  • 35.

    Huettel M, Ziebis W, Forster S. Flow‐induced uptake of particulate matter in permeable sediments. Limnol Oceanogr. 1996;41:309–22.

    Article 

    Google Scholar 

  • 36.

    Cook PL, Frank W, Glud R, Felix J, Markus H. Benthic solute exchange and carbon mineralization in two shallow subtidal sandy sediments: Effect of advective pore‐water exchange. Limnol Oceanogr. 2007;52:1943–63.

    CAS 
    Article 

    Google Scholar 

  • 37.

    Glud RN. Oxygen dynamics of marine sediments. Mar Biol Res. 2008;4:243–89.

    Article 

    Google Scholar 

  • 38.

    Gobet A, Böer SI, Huse SM, Van Beusekom JEE, Quince C, Sogin ML, et al. Diversity and dynamics of rare and of resident bacterial populations in coastal sands. ISME J. 2012;6:542.

    PubMed 
    Article 

    Google Scholar 

  • 39.

    Böer SI, Arnosti C, Van Beusekom JEE, Boetius A. Temporal variations in microbial activities and carbon turnover in subtidal sandy sediments. Biogeosciences. 2009;6:1149–65.

    Article 

    Google Scholar 

  • 40.

    Hunter EM, Mills HJ, Kostka JE. Microbial community diversity associated with carbon and nitrogen cycling in permeable shelf sediments. Appl Environ Microbiol. 2006;72:5689–701.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 41.

    Probandt D, Knittel K, Tegetmeyer HE, Ahmerkamp S, Holtappels M, Amann R. Permeability shapes bacterial communities in sublittoral surface sediments. Environ Microbiol. 2017;19:1584–99.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 42.

    Probandt D, Eickhorst T, Ellrott A, Amann R, Knittel K. Microbial life on a sand grain: from bulk sediment to single grains. ISME J. 2017;12:623–33.

  • 43.

    Kessler AJ, Chen Y-J, Waite DW, Hutchinson T, Koh S, Popa ME, et al. Bacterial fermentation and respiration processes are uncoupled in permeable sediments. Nat Microbiol. 2019;4:1014–23.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 44.

    Dyksma S, Pjevac P, Ovanesov K, Mussmann M. Evidence for H2 consumption by uncultured Desulfobacterales in coastal sediments. Environ Microbiol. 2018;20:450–61.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 45.

    Bourke MF, Marriott PJ, Glud RN, Hasler-Sheetal H, Kamalanathan M, Beardall J, et al. Metabolism in anoxic permeable sediments is dominated by eukaryotic dark fermentation. Nat Geosci. 2017;10:30–35.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 46.

    Canfield D, Kristensen E, Thamdrup B. Aquatic geomicrobiology. Academic Press; Cambridge, Massachusetts, USA; 2005.

  • 47.

    Bell TH, Bell T. Many roads to bacterial generalism. FEMS Microbiol Ecol. 2021; 97: fiaa240.

  • 48.

    Devictor V, Clavel J, Julliard R, Lavergne S, Mouillot D, Thuiller W, et al. Defining and measuring ecological specialization. J Appl Ecol. 2010;47:15–25.

    Article 

    Google Scholar 

  • 49.

    Lowe MK, Kennedy DM. Stability of artificial beaches in Port Phillip Bay, Victoria, Australia. J Coast Res. 2016;75:253–7.

  • 50.

    Paulin MM, Nicolaisen MH, Jacobsen CS, Gimsing AL, Sørensen J, Bælum J. Improving Griffith’s protocol for co-extraction of microbial DNA and RNA in adsorptive soils. Soil Biol Biochem. 2013;63:37–49.

    CAS 
    Article 

    Google Scholar 

  • 51.

    Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA. 2011;108:4516–22.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 52.

    Rognes T, Flouri T, Nichols B, Quince C, Mahé F. VSEARCH: a versatile open source tool for metagenomics. PeerJ. 2016;4:2584.

    Article 

    Google Scholar 

  • 53.

    Amir A, Daniel M, Navas-Molina JA, Kopylova E, Morton JT, Xu ZZ, et al. Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems. 2017;2:e00191–16.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 54.

    Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 55.

    Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome. 2018;6:226.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 56.

    Parks DH, Chuvochina M, Waite DW, Rinke C, Skarshewski A, Chaumeil P-A, et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat Biotechnol. 2018;36:996–1004.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 57.

    McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8:e61217.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 58.

    Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, et al. Vegan: community ecology package. R Packag Version. 2018;2:4–6.

    Google Scholar 

  • 59.

    Wickham H. ggplot2. WIREs Comp Stats. 2011;3:180–5.

  • 60.

    Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 2011;5:169.

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 61.

    Latombe G, Hui C, McGeoch MA. Multi‐site generalised dissimilarity modelling: using zeta diversity to differentiate drivers of turnover in rare and widespread species. Methods Ecol Evol. 2017;8:431–42.

    Article 

    Google Scholar 

  • 62.

    Lorenzen CJ. Determination of chlorophyll and pheo‐pigments: spectrophotometric equations 1. Limnol Oceanogr. 1967;12:343–6.

    CAS 
    Article 

    Google Scholar 

  • 63.

    Li DH, Luo RB, Liu CM, Leung CM, Ting HF, Sadakane K, et al. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods. 2016;102:3–11.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 64.

    Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 65.

    Alneberg J, Bjarnason BS, De Bruijn I, Schirmer M, Quick J, Ijaz UZ, et al. Binning metagenomic contigs by coverage and composition. Nat Methods. 2014;11:1144.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 66.

    Wu Y-W, Simmons BA, Singer SW. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics. 2015;32:605–7.

    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 

  • 67.

    Kang D, Li F, Kirton ES, Thomas A, Egan RS, An H, et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ. 2019;7:e7359.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 68.

    Sieber CMK, Probst AJ, Sharrar A, Thomas BC, Hess M, Tringe SG, et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nat Microbiol. 2018;3:836–43.

  • 69.

    Olm MR, Brown CT, Brooks B, Banfield JF. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 2017;11:2864.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 70.

    Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 71.

    Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy TBK, et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol. 2017;35:725–31.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 72.

    Hyatt D, Chen G-L, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinforma. 2010;11:119.

    Article 
    CAS 

    Google Scholar 

  • 73.

    Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2014;12:59.

    PubMed 
    Article 
    CAS 

    Google Scholar 

  • 74.

    Greening C, Geier R, Wang C, Woods LC, Morales SE, McDonald MJ, et al. Diverse hydrogen production and consumption pathways influence methane production in ruminants. ISME J. 2019;13:2617–32.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 75.

    Søndergaard D, Pedersen CNS, Greening C. HydDB: a web tool for hydrogenase classification and analysis. Sci Rep. 2016;6:34212.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 76.

    Cordero PRF, Bayly K, Leung PM, Huang C, Islam ZF, Schittenhelm RB, et al. Atmospheric carbon monoxide oxidation is a widespread mechanism supporting microbial survival. ISME J. 2019;13:2868–81.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 77.

    Darling AE, Jospin G, Lowe E, Matsen FA IV, Bik HM, Eisen JA. PhyloSift: phylogenetic analysis of genomes and metagenomes. PeerJ. 2014;2:e243.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 78.

    Zhou Z, Tran P, Liu Y, Kieft K, Anantharaman K. METABOLIC: a scalable high-throughput metabolic and biogeochemical functional trait profiler based on microbial genomes. bioRxiv. 2019; 761643. https://www.biorxiv.org/content/10.1101/761643v2.

  • 79.

    Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al. Clustal W and Clustal X version 2.0. Bioinformatics. 2007;23:2947–8.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 80.

    Kumar S, Stecher G, Tamura K. MEGA7: molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33:1870–4.

  • 81.

    Islam ZF, Cordero PRF, Feng J, Chen Y-J, Bay SK, Gleadow RM, et al. Two Chloroflexi classes independently evolved the ability to persist on atmospheric hydrogen and carbon monoxide. ISME J. 2019;13:1801–13.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 82.

    Fonselius S, Dyrssen D, Yhlen B. Determination of hydrogen sulphide. Methods of Seawater Analysis. Wiley-VCH; Weinheim, Germany. Third Ed 2007. p. 91–100.

  • 83.

    Hui C, McGeoch MA. Zeta diversity as a concept and metric that unifies incidence-based biodiversity patterns. Am Nat. 2014;184:684–94.

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 84.

    Bay SK, McGeoch MA, Gillor O, Wieler N, Palmer DJ, Baker DJ, et al. Soil bacterial communities exhibit strong biogeographic patterns at fine taxonomic resolution. mSystems. 2020;5:e00540–20.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 85.

    Büchi L, Vuilleumier S. Ecological strategies in stable and disturbed environments depend on species specialisation. Oikos. 2016;125:1408–20.

  • 86.

    Walters W, Hyde ER, Berg-Lyons D, Ackermann G, Humphrey G, Parada A, et al. Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems. 2016;1:e00009–15.

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 87.

    Lencina AM, Ding Z, Schurig-Briccio LA, Gennis RB. Characterization of the type III sulfide: quinone oxidoreductase from Caldivirga maquilingensis and its membrane binding. Biochim Biophys Acta (BBA)-Bioenerg. 2013;1827:266–75.

    CAS 
    Article 

    Google Scholar 

  • 88.

    Han Y, Perner M. Sulfide consumption in Sulfurimonas denitrificans and heterologous expression of its three sulfide-quinone reductase homologs. J Bacteriol. 2016;198:1260–7.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 89.

    Ramel F, Amrani A, Pieulle L, Lamrabet O, Voordouw G, Seddiki N, et al. Membrane-bound oxygen reductases of the anaerobic sulfate-reducing Desulfovibrio vulgaris Hildenborough: roles in oxygen defence and electron link with periplasmic hydrogen oxidation. Microbiology. 2013;159:2663–73.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 90.

    Ramel F, Brasseur G, Pieulle L, Valette O, Hirschler-Réa A, Fardeau ML, et al. Growth of the obligate anaerobe Desulfovibrio vulgaris Hildenborough under continuous low oxygen concentration sparging: impact of the membrane-bound oxygen reductases. PLoS ONE. 2015;10:e0123455.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 91.

    Shibl AA, Isaac A, Ochsenkühn MA, Cárdenas A, Fei C, Behringer G, et al. Diatom modulation of select bacteria through use of two unique secondary metabolites. Proc Natl Acad Sci. 2020;117:27445–55.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 92.

    Yurkov VV, Beatty JT. Aerobic anoxygenic phototrophic bacteria. Microbiol Mol Biol Rev. 1998;62:695–724.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 93.

    Kamp A, de Beer D, Nitsch JL, Lavik G, Stief P. Diatoms respire nitrate to survive dark and anoxic conditions. Proc Natl Acad Sci USA. 2011;108:5649–54.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 94.

    Pianka ER. On r-and K-selection. Am Nat. 1970;104:592–7.

    Article 

    Google Scholar 

  • 95.

    Andrews JH, Harris RF. r-and K-selection and microbial ecology. Advances in microbial ecology. Springer; Berlin, Germany; 1986. p. 99–147.

  • 96.

    Shade A, Dunn RR, Blowes SA, Keil P, Bohannan BJM, Herrmann M, et al. Macroecology to unite all life, large and small. Trends Ecol Evol. 2018;33:731–44.

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 97.

    Algar CK, Vallino JJ. Predicting microbial nitrate reduction pathways in coastal sediments. Aquat Micro Ecol. 2014;71:223–38.

    Article 

    Google Scholar 

  • 98.

    Graham EB, Knelman JE, Schindlbacher A, Siciliano S, Breulmann M, Yannarell A, et al. Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes? Front Microbiol. 2016;7:214.

    PubMed 
    PubMed Central 

    Google Scholar 


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