Philippa Kaur

Sampling and incubationFour rock samples were collected from the 3.7 km-deep Auka vent field in the Southern Pescadero Basin (23.956094N, 108.86192W)20,23. Sample NA091.008 was collected in 2017 on cruise NA091 with the Eexploration vessle Nautilus and incubated as described previously34. Samples 12,019 (S0200-R1), 11,719 (S0193-R2) and 11,868 (S0197-PC1), the latter representing a lithified nodule recovered from a sediment push core, were collected with Remotely operated vehicle SuBastian and Research vessel Falkor on cruise FK181031 in November 2018. These samples were processed shipboard and stored under anoxic conditions at 4 °C for subsequent incubation in the laboratory. In the laboratory, rock samples 12,019 and 11,719 were broken into smaller pieces under sterile conditions, immersed in N2-sparged sterilized artificial sea water and incubated under anoxic conditions with methane, as described previously for NA091.008 (ref. 34). Additional sampling information can be found in Supplementary Table 1. Mineralogical analysis by X-ray Powder Diffraction (XRD) identified barite in several of these samples, collected from two locations in the Auka vent field, including on the western side of the Matterhorn vent (11,719, NA091.008), and one oil-saturated sample (12,019) recovered from the sedimented flanks from the southern side of Z vent. Our analysis also includes metagenomic data from two sediment cores from the Auka vent field (DR750-PC67 and DR750-PC80) collected in April 2015 with the ROV Doc Ricketts and R/V Western Flyer (MBARI2015), previously published (ref. 23).Fluorescence in situ hybridizationSamples were fixed shipboard using freshly prepared paraformaldehyde (2 vol% in 3× Phosphate Buffer Solution (PBS), EMS15713) at 4 °C overnight, rinsed twice using 3× PBS, and stored in ethanol (50% in 1× PBS) at −20 °C until processing. Small pieces ( More

Authors and AffiliationsStatistics Division, Food and Agriculture Organization of the United Nations, Rome, ItalyFrancesco N. Tubiello, Giulia Conchedda, Leon Casse & Giorgia De SantisDigitization and Informatics Division, Food and Agriculture Organization of the United Nations, Rome, ItalyHao Pengyu & Chen ZhongxinInternational Institute for Applied Systems Analysis, Laxenburg, AustriaSteffen FritzGeospatial Unit, Land and Water Division, Food and Agriculture Organization of the United Nations, Rome, ItalyDouglas MuchoneyAuthorsFrancesco N. TubielloGiulia ConcheddaLeon CasseHao PengyuChen ZhongxinGiorgia De SantisSteffen FritzDouglas MuchoneyCorresponding authorCorrespondence to
Francesco N. Tubiello. More

Ehrlich PR, Raven PH. Butterflies and plants: a study in coevolution. Evolution. 1964;18:586–608.Article 

Google Scholar 
Marston MF, Pierciey FJ Jr, Shepard A, Gearin G, Qi J, Yandava C, et al. Rapid diversification of coevolving marine Synechococcus and a virus. Proc Natl Acad Sci USA. 2012;109:4544–9.Article 
CAS 

Google Scholar 
Hall AR, Scanlan PD, Buckling A. Bacteria-phage coevolution and the emergence of generalist pathogens. Am Nat. 2011;177:44–53.Article 

Google Scholar 
Badger MR, Andrews TJ, Whitney SM, Ludwig M, Yellowlees DC, Leggat W, et al. The diversity and coevolution of Rubisco, plastids, pyrenoids, and chloroplast-based CO2-concentrating mechanisms in algae. Can J Bot. 1998;76:1052–71.CAS 

Google Scholar 
Schluter D. The ecology of adaptive radiation. Oxford, UK: University Press; 2000.Buckling A, Maclean CR, Brockhurst MA, Colegrave N. The Beagle in a bottle. Nature. 2009;457:824–9.Article 
CAS 

Google Scholar 
Thompson JN. The coevolutionary process. Chicago, USA: University of Chicago Press; 1994.Vallina SM, Follows MJ, Dutkiewicz S, Montoya JM, Cermeno P, Loreau M. Global relationship between phytoplankton diversity and productivity in the ocean. Nat Commun. 2014;5:4299.Article 
CAS 

Google Scholar 
Jürgens K, Matz C. Predation as a shaping force for the phenotypic and genotypic composition of planktonic bacteria. Antonie Van Leeuwenhoek. 2002;81:413–34.Article 

Google Scholar 
Wildschutte H, Wolfe DM, Tamewitz A, Lawrence JG. Protozoan predation, diversifying selection, and the evolution of antigenic diversity in Salmonella. Proc Natl Acad Sci USA. 2004;101:10644–9.Article 
CAS 

Google Scholar 
Thompson JN. The geographic mosaic of coevolution. Chicago, USA: University of Chicago Press; 2005.Hahn MW, Höfle MG. Grazing of protozoa and its effect on populations of aquatic bacteria. FEMS Microbiol Ecol. 2001;35:113–21.Article 
CAS 

Google Scholar 
Fuhrman JA, Noble RT. Viruses and protists cause similar bacterial mortality in coastal seawater. Limnol Oceanogr. 1995;40:1236–42.Article 

Google Scholar 
Azam F, Fenchel T, Field JG, Gray JS, Meyer-Reil LA, Thingstad F. The ecological role of water-column microbes in the sea. Mar Ecol Prog Ser. 1983;10:257–63.Article 

Google Scholar 
Lankau RA, Strauss SY. Mutual feedbacks maintain both genetic and species diversity in a plant community. Science. 2007;317:1561–3.Article 
CAS 

Google Scholar 
Hogle SL, Hepolehto I, Ruokolainen L, Cairns J, Hiltunen T. Effects of phenotypic variation on consumer coexistence and prey community structure. Ecol Lett. 2022:25;307–19.Yoshida T, Jones LE, Ellner SP, Fussmann GF, Hairston NG Jr. Rapid evolution drives ecological dynamics in a predator-prey system. Nature. 2003;424:303–6.Article 
CAS 

Google Scholar 
McClean D, McNally L, Salzberg LI, Devine KM, Brown SP, Donohue I. Single gene locus changes perturb complex microbial communities as much as apex predator loss. Nat Commun. 2015;6:8235.Article 

Google Scholar 
Gómez P, Paterson S, De Meester L, Liu X, Lenzi L, Sharma MD, et al. Local adaptation of a bacterium is as important as its presence in structuring a natural microbial community. Nat Commun. 2016;7:12453.Article 

Google Scholar 
Middelboe M, Holmfeldt K, Riemann L, Nybroe O, Haaber J. Bacteriophages drive strain diversification in a marine Flavobacterium: Implications for phage resistance and physiological properties. Environ Microbiol. 2009;11:1971–82.Article 
CAS 

Google Scholar 
Lennon JT, Martiny JBH. Rapid evolution buffers ecosystem impacts of viruses in a microbial food web. Ecol Lett. 2008;11:1178–88.Article 

Google Scholar 
Cairns J, Jokela R, Hultman J, Tamminen M, Virta M, Hiltunen T. Construction and characterization of synthetic bacterial community for experimental ecology and evolution. Front Genet. 2018;9:312.Article 

Google Scholar 
Pascual-García A, Bell T. Community-level signatures of ecological succession in natural bacterial communities. Nat Commun. 2020;11:2386.Article 

Google Scholar 
Rivett DW, Bell T. Abundance determines the functional role of bacterial phylotypes in complex communities. Nat Microbiol. 2018;3:767–72.Article 
CAS 

Google Scholar 
Cairns J, Moerman F, Fronhofer EA, Altermatt F, Hiltunen T. Evolution in interacting species alters predator life-history traits, behaviour and morphology in experimental microbial communities. Proc Biol Sci. 2020;287:20200652.
Google Scholar 
Cooke DP, Wedge DC, Lunter G. A unified haplotype-based method for accurate and comprehensive variant calling. Nat Biotechnol. 2021;39:885–92.Article 
CAS 

Google Scholar 
Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012;6:80–92.Article 
CAS 

Google Scholar 
Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923–30.Article 
CAS 

Google Scholar 
Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ, von Mering C, et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-Mapper. Mol Biol Evol. 2017;34:2115–22.Article 
CAS 

Google Scholar 
Huerta-Cepas J, Szklarczyk D, Heller D, Hernández-Plaza A, Forslund SK, Cook H, et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 2019;47:D309–14.Article 
CAS 

Google Scholar 
Blin K, Shaw S, Steinke K, Villebro R, Ziemert N, Lee SY, et al. antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res. 2019;47:W81–7.Article 
CAS 

Google Scholar 
Good BH, McDonald MJ, Barrick JE, Lenski RE, Desai MM. The dynamics of molecular evolution over 60,000 generations. Nature. 2017;551:45–50.Article 

Google Scholar 
Timonen J, Mannerström H, Vehtari A, Lähdesmäki H. lgpr: an interpretable nonparametric method for inferring covariate effects from longitudinal data. Bioinformatics. 2021;37:1860–7.Article 
CAS 

Google Scholar 
Willis AD, Martin BD. Estimating diversity in networked ecological communities. Biostatistics. 2022;23:207–22.Article 

Google Scholar 
Willis A, Bunge J, Whitman T. Improved detection of changes in species richness in high diversity microbial communities. J R Stat Soc C. 2017;66:963–77.Article 

Google Scholar 
Anderson MJ. A new method for non‐parametric multivariate analysis of variance. Austral Ecol. 2001:26;32–46.Anderson MJ. Distance-based tests for homogeneity of multivariate dispersions. Biometrics. 2006;62:245–53.Article 

Google Scholar 
Martin BD, Witten D, Willis AD. Modeling microbial abundances and dysbiosis with beta-binomial regression. Ann Appl Stat. 2020;14:94–115.Article 

Google Scholar 
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.Article 

Google Scholar 
Zhang Y, Thompson KN, Huttenhower C, Franzosa EA. Statistical approaches for differential expression analysis in metatranscriptomics. Bioinformatics. 2021;37:i34–41.Article 
CAS 

Google Scholar 
Abdi H, Williams LJ, Valentin D, Bennani-Dosse M. STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling. WIREs Comp Stat. 2012;4:124–67.Charrad M, Ghazzali N, Boiteau V, Niknafs A. NbClust: an R package for determining the relevant number of clusters in a data set. J Stat Softw. 2014;61:1–36.Article 

Google Scholar 
Zhu A, Ibrahim JG, Love MI. Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences. Bioinformatics. 2019;35:2084–92.Article 
CAS 

Google Scholar 
Yu G, Wang L-G, Han Y, He Q-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284–7.Article 
CAS 

Google Scholar 
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30.Article 
CAS 

Google Scholar 
Wichman HA, Badgett MR, Scott LA, Boulianne CM, Bull JJ. Different trajectories of parallel evolution during viral adaptation. Science. 1999;285:422–4.Article 
CAS 

Google Scholar 
Lieberman TD, Michel J-B, Aingaran M, Potter-Bynoe G, Roux D, Davis MR Jr, et al. Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes. Nat Genet. 2011;43:1275–80.Article 
CAS 

Google Scholar 
Lebeuf-Taylor E, McCloskey N, Bailey SF, Hinz A, Kassen R. The distribution of fitness effects among synonymous mutations in a gene under directional selection. Elife. 2019;8:e45952.Article 

Google Scholar 
Bailey SF, Hinz A, Kassen R. Adaptive synonymous mutations in an experimentally evolved Pseudomonas fluorescens population. Nat Commun. 2014;5:4076.Article 
CAS 

Google Scholar 
Mukherjee S, Jemielita M, Stergioula V, Tikhonov M, Bassler BL. Photosensing and quorum sensing are integrated to control Pseudomonas aeruginosa collective behaviors. PLoS Biol. 2019;17:e3000579.Article 
CAS 

Google Scholar 
Segura A, Hurtado A, Duque E, Ramos JL. Transcriptional phase variation at the flhB gene of Pseudomonas putida DOT-T1E is involved in response to environmental changes and suggests the participation of the flagellar export system in solvent tolerance. J Bacteriol. 2004;186:1905–9.Article 
CAS 

Google Scholar 
Lee X, Reimmann C, Greub G, Sufrin J, Croxatto A. The Pseudomonas aeruginosa toxin L-2-amino-4-methoxy-trans-3-butenoic acid inhibits growth and induces encystment in Acanthamoeba castellanii. Microbes Infect. 2012;14:268–72.Article 
CAS 

Google Scholar 
Montagnes DJS, Barbosa AB, Boenigk J, Davidson K, Jürgens K, Macek M, et al. Selective feeding behaviour of key free-living protists: avenues for continued study. Aquat Micro Ecol. 2008;53:83–98.Article 

Google Scholar 
Collins K, editor. Tetrahymena thermophila. New York: Academic Press, Elsevier; 2012.Ruehle MD, Orias E, Pearson CG. Tetrahymena as a unicellular model eukaryote: genetic and genomic tools. Genetics. 2016;203:649–65.Article 
CAS 

Google Scholar 
Plum K, Tarkington J, Zufall RA. Experimental evolution in Tetrahymena. Microorganisms. 2022;10:1–11.Heard E, Martienssen RA. Transgenerational epigenetic inheritance: myths and mechanisms. Cell. 2014;157:95–109.Article 
CAS 

Google Scholar 
Jones ML, Rivett DW, Pascual-García A, Bell T. Relationships between community composition, productivity and invasion resistance in semi-natural bacterial microcosms. Elife. 2021;10:1–25.Kertesz MA. Riding the sulfur cycle-metabolism of sulfonates and sulfate esters in gram-negative bacteria. FEMS Microbiol Rev. 2000;24:135–75.CAS 

Google Scholar 
Park C, Shin B, Park W. Protective role of bacterial alkanesulfonate monooxygenase under oxidative stress. Appl Environ Microbiol. 2020;86:1–14.Shatalin K, Shatalina E, Mironov A, Nudler E. H2S: a universal defense against antibiotics in bacteria. Science. 2011;334:986–90.Article 
CAS 

Google Scholar 
Ong C-LY, Beatson SA, Totsika M, Forestier C, McEwan AG, Schembri MA. Molecular analysis of type 3 fimbrial genes from Escherichia coli, Klebsiella and Citrobacter species. BMC Microbiol. 2010;10:183.Article 

Google Scholar 
McNally L, Brown SP. Building the microbiome in health and disease: niche construction and social conflict in bacteria. Philos Trans R Soc Lond B Biol Sci. 2015;370:1–8.Scheuerl T, Cairns J, Becks L, Hiltunen T. Predator coevolution and prey trait variability determine species coexistence. Proc Biol Sci. 2019;286:20190245.
Google Scholar 
Koskella B, Brockhurst MA. Bacteria-phage coevolution as a driver of ecological and evolutionary processes in microbial communities. FEMS Microbiol Rev. 2014;38:916–31.Article 
CAS 

Google Scholar 
Wilhelm Scherer H. Sulfur in soils. J Plant Nutr Soil Sci. 2009;172:326–35.Article 

Google Scholar 
Kaya K. Chemistry and biochemistry of taurolipids. Prog Lipid Res. 1992;31:87–108.Article 
CAS 

Google Scholar 
Fukami T. Historical contingency in community assembly: integrating niches, species pools, and priority effects. Annu Rev Ecol Evol Syst. 2015;46:1–23.Article 

Google Scholar 
Debray R, Herbert RA, Jaffe AL, Crits-Christoph A, Power ME, Koskella B. Priority effects in microbiome assembly. Nat Rev Microbiol. 2022;20:109–21.Article 
CAS 

Google Scholar 
Price TD, Qvarnström A, Irwin DE. The role of phenotypic plasticity in driving genetic evolution. Proc Biol Sci. 2003;270:1433–40.Article 

Google Scholar  More

Hou J, Sun J, Fang Q. A fluorinated low dielectric polymer at high frequency derived from allylphenol and benzocyclobutene by a facile route. Eur Polym J. 2022;163:110943–9.Article 
CAS 

Google Scholar 
Qiu Z, Wu S, Li Z, Zhang S, Xing W, Liu S. Sulfonated Poly(arylene-co-naphthalimide)s Synthesized by Copolymerization of Primarily Sulfonated Monomer and Fluorinated Naphthalimide Dichlorides as Novel Polymers for Proton Exchange Membranes. Macromolecules 2006;39:6425–32.Article 
CAS 

Google Scholar 
Schönberger F, Chromik A, Kerres J. Synthesis and characterization of novel (sulfonated) poly(arylene ether)s with pendent trifluoromethyl groups. Polymer 2009;50:2010–24.Article 

Google Scholar 
Chen JC, Liu YC, Ju JJ, Chiang CJ, Chern YT. Synthesis, characterization and hydrolysis of aromatic polyazomethines containing non-coplanar biphenyl structures. Polymer 2011;52:954–64.Article 
CAS 

Google Scholar 
Liaw DJ, Huang CC, Chen WH. Color lightness and highly organosoluble fluorinated polyamides, polyimides and poly(amide–imide)s based on noncoplanar 2,2’-dimethyl-4,4’-biphenylene units. Polymer 2006;47:2337–48.Article 
CAS 

Google Scholar 
Shohbuke E, Kobayashi Y, Okubayashi S. Effects of acrylate monomers containing alkyl groups on water and oil repellent treatments of polyester fabrics. Colloids. Surf. A: Physicochem Eng Asp. 2021;631:127632–9.Article 
CAS 

Google Scholar 
Sun Y, Zhao X, Liu R, Chen G, Zhou X. Synthesis and characterization of fluorinated polyacrylate as water and oil repellent and soil release finishing agent for polyester fabric. Prog Org Coat. 2018;123:306–13.Article 
CAS 

Google Scholar 
Tang W, Huang Y, Qing FL. Synthesis and characterization of fluorinated polyacrylate graft copolymers capable as water and oil repellent finishing agents. J Appl Polym Sci. 2011;119:84–92.Article 
CAS 

Google Scholar 
Jiang J, Zhang G, Wang Q, Zhang Q, Zhan X, Chen F. Novel Fluorinated Polymers Containing Short Perfluorobutyl Side Chains and Their Super Wetting Performance on Diverse Substrates. ACS Appl Mater Interfaces. 2016;8:10513–23.Article 
CAS 

Google Scholar 
Honda K, Morita M, Otsuka H, Takahara A. Molecular Aggregation Structure and Surface Properties of Poly(fluoroalkyl acrylate) Thin Films. Macromolecules 2005;38:5699–705.Article 
CAS 

Google Scholar 
Shaver AT, Yin K, Borjigin H, Zhang W, Choudhury SR, Baer E, Mecham SJ, Riffle JS, McGrath JE. Fluorinated poly(arylene ether ketone)s for high temperature dielectrics. Polymer 2016;83:199–204.Article 
CAS 

Google Scholar 
Attwood TE, Dawson PC, Freeman JL, Hoy LRJ, Rose JB, Staniland PA. Synthesis and properties of polyaryletherketones. Polymer. 1981;22:1096–103.Article 
CAS 

Google Scholar 
Yonezawa N, Okamoto A. Synthesis of Wholly Aromatic Polyketones. Polym J. 2009;41:899–928.Article 
CAS 

Google Scholar 
Maeyama K, Ito S. Synthesis of aromatic poly(ether ketone)s bearing 9,9-dialkylfuorene-2,7-diyl units through nucleophilic aromatic substitution polymerization. Polym Bull.2018;75:5763–76.Article 
CAS 

Google Scholar 
Blundell DJ, Osborn BN. The morphology of poly(aryl-ether-ether ketone). Polymer 1983;24:953–8.Article 
CAS 

Google Scholar 
Maeyama K, Hikiji I, Ogura K, Okamoto A, Ogino K, Saito H, Yonezawa N. Synthesis of Optically Active Aromatic Poly(ether ketone)s via Nucleophilic Aromatic Substitution Polymerization. Polym J. 2005;37:707–10.Article 
CAS 

Google Scholar 
Liu Q, Zhang S, Wang Z, Chen Y, Jian X. Effect of pendent phenyl and bis-phthalazinone moieties on the properties of N-heterocyclic poly(aryl ether ketone ketone)s. Polymer 2020;198:122525–34.Article 
CAS 

Google Scholar 
Eaton PE, Carlson GR, Lee JT. Phosphorus Pentoxide-Methanesulfonic Acid. A Convenient Alternative to Polyphosphoric Acid. J Org Chem. 1973;38:4071–3.Article 
CAS 

Google Scholar 
Nowacki B, Iamazaki E, Cirpan A, Karasz F, Atvars TDZ, Akcelrud L. Highly efficient polymer blends from a polyfluorene derivative and PVK for LEDs. Polymer 2009;50:6057–64.Article 
CAS 

Google Scholar 
Wang TQ, Zhao SL, Zhang WM, Lin HX, Cui YM. Synthesis, X-ray crystal structure, and optical properties of novel 9,9-diethyl-1,2-diaryl-1,9-dihydrofluoreno[2,3-d]imidazoles. Monatsh Chem. 2016;147:1991–9.Article 
CAS 

Google Scholar 
Chen J, Onogi S, Hsieh YC, Hsiao CC, Higashibayashi S, Sakurai H, Wu YT. Palladium-Catalyzed Arylation of Methylene-Bridged Polyarenes: Synthesis and Structures of 9-Arylfluorene Derivatives. Adv Synth Catal. 2012;354:1551–8.Article 
CAS 

Google Scholar 
Manuel S, Anne S, Larissa AC, Stefan M. Uniform shape monodisperse single chain nanocrystals by living aqueous catalytic polymerization. Nat Commun.2019;10:2592.Article 

Google Scholar 
Lee KS, Lee JS. Synthesis of Highly Fluorinated Poly(arylene ether sulfide) for Polymeric Optical Waveguides. Chem Mater. 2006;18:4519–25.Article 
CAS 

Google Scholar 
Natarajan P, Vagicherla VD, Vijayan MT. A mild oxidation of deactivated naphthalenes and anthracenes to corresponding para-quinones by N-bromosuccinimide. Tetrahedron Lett. 2014;55:3511–5.Article 
CAS 

Google Scholar 
Faury T, Dumur F, Clair S, Abel M, Porte L, Gigmes D. Side functionalization of diboronic acid precursors for covalent organic frameworks. Cryst Eng Comm. 2013;15:2067–75.Article 
CAS 

Google Scholar 
Shaposhnikova VV, Tkachenko AS, Zvukova ND, Peregudov AS, Klemenkova ZS, Ponomarev AF, Il´yasov VK, Lachinov AN, Salazkin SN. New possibilities for the effective influence on the charge transport in poly(arylene ether ketones) without using phthalide-containing fragments in the polymer chains. Rus Chem Bull Int Ed. 2016;65:502–6.Article 
CAS 

Google Scholar 
Owens DK, Wendt RC. Estimation of the Surface Free Energy of Polymers. J Appl Polym Sci. 1969;13:1741–7.Article 
CAS 

Google Scholar 
Fox HW, Zisman WA. The spreading of liquids on low energy surfaces. I. Polytetrafluoroethylene. J Colloid Sci. 1950;5:514–31.Article 
CAS 

Google Scholar  More

Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014).Article 
ADS 
CAS 

Google Scholar 
Young, H. S., McCauley, D. J., Galetti, M. & Dirzo, R. Patterns, causes, and consequences of anthropocene defaunation. Annu. Rev. Ecol. Evol. Syst. 47, 333–358 (2016).Article 

Google Scholar 
Hoffmann, M. et al. The impact of conservation on the status of the world’s vertebrates. Science 330, 1503–1509 (2010).Article 
ADS 
CAS 

Google Scholar 
Ceballos, G. et al. Accelerated modern human–induced species losses: Entering the sixth mass extinction. Sci. Adv. 1, e1400253 (2015).Article 
ADS 

Google Scholar 
Ceballos, G., Ehrlich, P. R. & Dirzo, R. Biological annihilation via the ongoing sixth mass extinction signalled by vertebrate population losses and declines. PNAS 114, E6089–E6096 (2017).Article 
ADS 
CAS 

Google Scholar 
Almond, R. E. A. et al. (eds) Living Planet Report 2020—Bending the Curve of Biodiversity Loss (WWF, 2020).
Google Scholar 
Murali, G., de Oliveira Caetano, G. H., Barki, G., Meiri, S. & Roll, U. Emphasizing declining populations in the Living Planet Report. Nature 601, E20–E24 (2022).Article 
CAS 

Google Scholar 
Pianka, E. R., Vitt, L. J., Pelegrin, N., Fitzgerald, D. B. & Winemiller, K. O. Toward a periodic table of niches, for exploring the lizard niche hypervolume. Am. Nat. 190, 601–616 (2017).Article 

Google Scholar 
Cox, D. T. C., Gardner, A. S. & Gaston, K. J. Diel niche variation in mammals associated with expanded trait space. Nat. Commun. 12, 1753 (2021).Article 
ADS 
CAS 

Google Scholar 
Cox, D. T. C., Baker, D. J., Gardner, A. S. & Gaston, K. J. Global variation in unique and redundant mammal functional diversity across the daily cycle. J. Biogeogr. In PressChichorro, F., Juslén, A. & Cardoso, P. A review of the relation between species traits and extinction risk. Biol. Conserv. 237, 220–229 (2019).Article 

Google Scholar 
Cox, D. T. C., Gardner, A. S. & Gaston, K. J. Global and regional erosion of mammalian functional diversity across the diel cycle. Sci. Adv. 8, adb6008 (2022).Article 

Google Scholar 
Levy, O., Dayan, T., Porter, W. P. & Kronfeld-Schor, N. Time and ecological resilience: Can diurnal animals compensate for climate change by shifting to nocturnal activity?. Ecol. Monogr. 89, e01334 (2019).Article 

Google Scholar 
Bonebrake, T. C., Rezende, E. L. & Bozinovic, F. Climate change and thermoregulatory consequences of activity time in mammals. Am. Nat. 196, 45–56 (2020).Article 

Google Scholar 
Cox, D. T. C., Maclean, I. M. D., Gardner, A. S. & Gaston, K. J. Global variation in diurnal asymmetry in temperature, cloud cover, specific humidity and precipitation and its association with leaf area index. Glob. Change Biol. 26, 7099–7111 (2020).Article 
ADS 

Google Scholar 
Fritts, T. H. & Rodda, G. H. The role of introduced species in the degradation of island ecosystems: A case history of Guam. Annu. Rev. Ecol. Evol. Syst. 29, 113–140 (1998).Article 

Google Scholar 
Su, J.-Q., Han, X. & Chen, B.-M. Do day and night warming exert different effects on growth and competitive interaction between invasive and native plants?. Biol. Invasions 23, 157–166 (2021).Article 

Google Scholar 
Peres, C. A. Synergistic effects of subsistence hunting and habitat fragmentation on Amazonian forest vertebrates. Conserv. Biol. 15, 1490–1505 (2001).Article 

Google Scholar 
Brook, B. W., Sodhi, N. S. & Bradshaw, C. J. A. Synergies among extinction drivers under global change. Trends Ecol. Evol. 23, 453–460 (2008).Article 

Google Scholar 
Brodie, J. F. Synergistic effects of climate change and agricultural land use on mammals. Front. Ecol. Environ. 14, 20–26 (2016).Article 

Google Scholar 
Brodie, J. F., Williams, S. & Garner, B. The decline of mammal functional and evolutionary diversity worldwide. PNAS https://doi.org/10.1073/pnas.1921849118 (2021).Article 

Google Scholar 
IUCN. The IUCN Red List of threatened species. Version 2021-3. https://www.iucnredlist.org. Downloaded on [21stt March 2022] (2021).Faurby, S. et al. PHYLACINE 1.2.1: The phylogenetic atlas of mammal macroecology. Ecology. 99, 2626–2626 (2018).Article 

Google Scholar 
Ripple, W. J. et al. Bushmeat hunting and extinction risk to the world’s mammals. R. Soc. Open Sci. 3, 160498 (2016).Article 
ADS 

Google Scholar 
Ripple, W. J. et al. Are we eating the world’s megafauna to extinction? Conserv. Lett. 12, e12627 (2019).Article 

Google Scholar 
Nasi, R., Taber, A. & Van Vliet, N. Empty forests, empty stomachs? Bushmeat and livelihoods in the Congo and Amazon Basins. Int. For. Rev. 13, 355–368 (2011).
Google Scholar 
Woinarski, J. C. Z., Burbidge, A. A. & Harrison, P. L. Ongoing unravelling of a continental fauna: decline and extinction of Australian mammals since European settlement. PNAS 112, 4531–4540 (2015).Article 
ADS 
CAS 

Google Scholar 
Welbergen, J. A., Klose, S. M., Markus, N. & Eby, P. Climate change and the effects of the temperature extremes on Australian flying-foxes. Proc. R. Soc. B. 275, 419–425 (2008).Article 

Google Scholar 
Ramesh, T., Kalle, R., Sankar, K. & Qureshi, Q. Role of body size in activity budget of mammals in the Western ghats of India. J. Trop. Biol. 31, 315–323 (2015).
Google Scholar 
Gaynor, K. M., Hojnowski, C. E., Carter, N. H. & Brashares, J. S. The influence of human disturbance on wildlife nocturnality. Science 360, 1232–1235 (2018).Article 
ADS 
CAS 

Google Scholar 
Bennie, J. J., Duffy, J. P., Inger, R. & Gaston, K. J. Biogeography of time partitioning in mammals. PNAS 111, 13727–13732 (2014).Article 
ADS 
CAS 

Google Scholar 
Forbes, B. C. et al. Sea ice, rain-on-snow and tundra reindeer nomadism in Arctic Russia. Biol. Lett. 12, 20160466 (2016).Article 

Google Scholar 
Safronov, V. M. Climate change and mammals of Yakutia. Biol. Bull Russ. Acad. Sci. 43, 1256–1270 (2016).Article 

Google Scholar 
Galán-Acedo, C. et al. The conservation value of human-modified landscapes for the world’s primates. Nat. Commun. 10, 152 (2019).Article 
ADS 

Google Scholar 
Gaston, K. J. Nighttime ecology: the “nocturnal problem” revisited. Am. Nat. 193, 481–502 (2019).Article 

Google Scholar 
Mittermeier, R., Rylands, A., Lacher, T. & Wilson, D. Handbook of the Mammals of the World Vol. 1–3 & 5–9 (Lynx Edicions, Cham, 2001-2019).
Google Scholar 
Ives, A. R. & Garland, T. Jr. Phylogenetic logistic regression for binary dependent variables. Syst. Biol. 59, 9–26 (2010).Article 

Google Scholar 
Ho, T. & Ané, C. A linear-time algorithm for Gaussian and non-Gaussian trait evolution models. Syst. Biol. 63, 397–408 (2014).Article 

Google Scholar 
Penone, C. et al. Imputation of missing data in life-history trait datasets: which approach performs the best? Methods Ecol. Evol. 5, 961–970 (2014).Article 

Google Scholar 
Brodzik, M. J., Billingsley, B., Haran, T., Raup, B. & Savoie, M. H. EASE-Grid 2.0: Incremental but significant improvements for earth-gridded data sets. ISPRS Int. J. Geo-Inf. 1, 32–45 (2012).Article 

Google Scholar  More

Mishra, A. K. & Singh, V. P. J. Hydrol. 391, 202–216 (2010).Article 

Google Scholar 
Jiao, W. et al. Nat. Commun. 12, 3777 (2021).Article 
CAS 

Google Scholar 
Gampe, D. et al. Nat. Clim. Change 11, 772–779 (2021).Article 

Google Scholar 
IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).Schwalm, C. R. et al. Nature 548, 202–205 (2017).Article 
CAS 

Google Scholar 
Li, Y. et al. Nat. Clim. Change https://doi.org/10.1038/s41558-022-01584-2 (2023).Fourth National Climate Assessment: Volume II—Impacts, Risks, and Adaptation in the United States (US Global Change Research Program, 2018).Daryanto, S., Wang, L. & Jacinthe, P. A. PLoS ONE 11, e0156362 (2016).Article 

Google Scholar 
Jiao, W. et al. J. Geophys. Res. Biogeosci. 127, e2021JG006431 (2022).Augspurger, C. K. Oecologia 156, 281–286 (2008).Article 

Google Scholar 
Lian, X. et al. Nat. Commun. 12, 983 (2021).Article 
CAS 

Google Scholar 
Buermann, W. et al. Nature 562, 110–114 (2018).Article 
CAS 

Google Scholar 
Lian, X. et al. Sci. Adv. 6, eaax0255 (2020).Article 

Google Scholar 
Jiao, W., Wang, L. & McCabe, M. F. Rem. Sens. Environ. 256, 112313 (2021).Article 

Google Scholar  More

Our main objective was to test the SJH (positing that adolescents living in “traditional”, non-industrial environments will more closely fulfil their “biological/natural” sleep requirements25,26) by comparing sleep deprivation among adolescents in rural and urban societies. The SJH argues that adolescent “biological/natural” sleep quotas and circadian cycles can be ascertained from free days, when sleep patterns are minimally shaped by social commitments5,37. Therefore, we predicted that sleep deprivation would be rare in the more rural agricultural settings of Puebla and Campeche but more frequent among participants in Mexico City. Likewise, we predicted that we would not see sleep deprivation on free days among any of the rural participants.Our predictions were not supported, instead, we found that short sleep quotas during school nights are common in both rural agricultural settings, with over 75% of adolescents in each group sleeping  More

Battin, T. J. et al. The boundless carbon cycle. Nat. Geosci. 2, 598–600 (2009).Article 
CAS 

Google Scholar 
Raymond, P. A. et al. Global carbon dioxide emissions from inland waters. Nature 503, 355–359 (2013).Article 
CAS 

Google Scholar 
Hotchkiss, E. R. et al. Sources of and processes controlling CO2 emissions change with the size of streams and rivers. Nat. Geosci. 8, 696–699 (2015). Important study conceptualizing (on the basis of a data synthesis) how the sources and magnitude of CO2 evasion flux change along a stream–river continuum.Ciais, P. et al. in Climate Change 2013 The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds Stocker, T. F. et al.) Ch. 6 (Cambridge Univ. Press, 2013).Friedlingstein, P. et al. Global carbon budget 2021. Earth Syst. Sci. Data 14, 1917–2005 (2022).Article 

Google Scholar 
Cole, J. J. et al. Plumbing the global carbon cycle: integrating inland waters into the terrestrial carbon budget. Ecosystems 10, 172–185 (2007). A pioneering study showing the role of inland waters for large-scale carbon fluxes and highlighting them as ‘reactors’ rather than ‘passive pipes’.Article 

Google Scholar 
Drake, T. W., Raymond, P. A. & Spencer, R. G. M. Terrestrial carbon inputs to inland waters: a current synthesis of estimates and uncertainty. Limnol. Oceanogr. Lett. 3, 132–142 (2018).Article 
CAS 

Google Scholar 
Odum, H. T. Primary production in flowing waters. Limnol. Oceanogr. 1, 102–117 (1956).Article 

Google Scholar 
Bernhardt, E. S. et al. The metabolic regimes of flowing waters. Limnol. Oceanogr. 63, 99–118 (2018). A synthesis of the predominant drivers and constraints on metabolic regimes of stream and river ecosystems.Article 

Google Scholar 
Barnes, A. D. et al. Energy flux: the link between multitrophic biodiversity and ecosystem functioning. Trends Ecol. Evol. 33, 186–197 (2018).Article 

Google Scholar 
Costanza, R. & Mageau, M. What is a healthy ecosystem? Aquat. Ecol. 33, 105–115 (1999).Article 

Google Scholar 
Blöschl, G. et al. Changing climate both increases and decreases European river floods. Nature 573, 108–111 (2019).Article 

Google Scholar 
Gudmundsson, L. et al. Globally observed trends in mean and extreme river flow attributed to climate change. Science 371, 1159–1162 (2021).Article 
CAS 

Google Scholar 
Yang, X., Pavelsky, T. M. & Allen, G. H. The past and future of global river ice. Nature 577, 69–73 (2020).Article 
CAS 

Google Scholar 
Grill, G. et al. Mapping the world’s free-flowing rivers. Nature 569, 215–221 (2019).Article 
CAS 

Google Scholar 
Belletti, B. et al. More than one million barriers fragment Europe’s rivers. Nature 588, 436–441 (2020).Article 
CAS 

Google Scholar 
Pekel, J.-F., Cottam, A., Gorelick, N. & Belward, A. S. High-resolution mapping of global surface water and its long-term changes. Nature 540, 418–422 (2016).Article 
CAS 

Google Scholar 
Cooley, S. W., Ryan, J. C. & Smith, L. C. Human alteration of global surface water storage variability. Nature 591, 78–81 (2021).Article 
CAS 

Google Scholar 
Jaramillo, F. & Destouni, G. Local flow regulation and irrigation raise global human water consumption and footprint. Science 350, 1248–1251 (2015).Article 
CAS 

Google Scholar 
Quinton, J. N., Govers, G., Oost, K. V. & Bardgett, R. D. The impact of agricultural soil erosion on biogeochemical cycling. Nat. Geosci. 3, 311–314 (2010).Article 
CAS 

Google Scholar 
Mekonnen, M. M. & Hoekstra, A. Y. Global anthropogenic phosphorus loads to freshwater and associated grey water footprints and water pollution levels: a high‐resolution global study. Water Resour. Res. 54, 345–358 (2018).Article 
CAS 

Google Scholar 
Regnier, P. et al. Anthropogenic perturbation of the carbon fluxes from land to ocean. Nat. Geosci. 6, 597–607 (2013). The first study showing the extent to which human activities have altered the magnitude of contemporary lateral carbon fluxes from land to ocean.Article 
CAS 

Google Scholar 
Rüegg, J. et al. Thinking like a consumer: linking aquatic basal metabolism and consumer dynamics. Limnol. Oceanogr. Lett. 6, 1–17 (2021).Article 

Google Scholar 
Fernández-Martínez, M. et al. Global trends in carbon sinks and their relationships with CO2 and temperature. Nat. Clim. Change 9, 73–79 (2019).Article 

Google Scholar 
Behrenfeld, M. J. et al. Climate-driven trends in contemporary ocean productivity. Nature 444, 752–755 (2006).Article 
CAS 

Google Scholar 
Phillips, J. S. Time‐varying responses of lake metabolism to light and temperature. Limnol. Oceanogr. 65, 652–666 (2020).Article 
CAS 

Google Scholar 
Uehlinger, U. Annual cycle and inter‐annual variability of gross primary production and ecosystem respiration in a floodprone river during a 15‐year period. Freshw. Biol. 51, 938–950 (2006).Article 
CAS 

Google Scholar 
Uehlinger, U. & Naegeli, M. W. Ecosystem metabolism, disturbance, and stability in a prealpine gravel bed river. J. North Am. Benthol. Soc. 17, 165–178 (1998).Article 

Google Scholar 
Mulholland, P. J. et al. Inter-biome comparison of factors controlling stream metabolism. Freshw. Biol. 46, 1503–1517 (2001).Article 
CAS 

Google Scholar 
Roberts, B. J., Mulholland, P. J. & Hill, W. R. Multiple scales of temporal variability in ecosystem metabolism rates: results from 2 years of continuous monitoring in a forested headwater stream. Ecosystems 10, 588–606 (2007).Article 
CAS 

Google Scholar 
Appling, A. P., Hall, R. O., Yackulic, C. B. & Arroita, M. Overcoming equifinality: leveraging long time series for stream metabolism estimation. J. Geophys. Res. Biogeosci. 123, 624–645 (2018).Article 
CAS 

Google Scholar 
Appling, A. P. et al. The metabolic regimes of 356 rivers in the United States. Sci. Data 5, 180292 (2018).Article 
CAS 

Google Scholar 
Canadell, M. B. et al. Regimes of primary production and their drivers in Alpine streams. Freshw. Biol. 66, 1449–1463 (2021).Article 

Google Scholar 
Myrstener, M., Gómez‐Gener, L., Rocher‐Ros, G., Giesler, R. & Sponseller, R. A. Nutrients influence seasonal metabolic patterns and total productivity of Arctic streams. Limnol. Oceanogr. 66, S182–S196 (2021).Article 
CAS 

Google Scholar 
Savoy, P. et al. Metabolic rhythms in flowing waters: an approach for classifying river productivity regimes. Limnol. Oceanogr. 64, 1835–1851 (2019).Article 

Google Scholar 
Kirk, L., Hensley, R. T., Savoy, P., Heffernan, J. B. & Cohen, M. J. Estimating benthic light regimes improves predictions of primary production and constrains light-use efficiency in streams and rivers. Ecosystems 24, 825–839 (2021).Article 

Google Scholar 
Bernhardt, E. S. et al. Light and flow regimes regulate the metabolism of rivers. Proc. Natl Acad. Sci. USA 119, e2121976119 (2022).Article 
CAS 

Google Scholar 
Savoy, P. & Harvey, J. W. Predicting light regime controls on primary productivity across CONUS river networks. Geophys. Res. Lett. 48, e2020GL092149 (2021).Article 

Google Scholar 
Julian, J. P., Stanley, E. H. & Doyle, M. W. Basin-scale consequences of agricultural land use on benthic light availability and primary production along a sixth-order temperate river. Ecosystems 11, 1091–1105 (2008).Article 

Google Scholar 
Hall, R. O. et al. Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon. Limnol. Oceanogr. 60, 512–526 (2015).Article 

Google Scholar 
Hosen, J. D. et al. Enhancement of primary production during drought in a temperate watershed is greater in larger rivers than headwater streams. Limnol. Oceanogr. 64, 1458–1472 (2019).Article 

Google Scholar 
Allen, A. P., Gillooly, J. F. & Brown, J. H. Linking the global carbon cycle to individual metabolism. Funct. Ecol. 19, 202–213 (2005).Article 

Google Scholar 
Demars, B. O. L. et al. Temperature and the metabolic balance of streams. Freshw. Biol. 56, 1106–1121 (2011).Article 

Google Scholar 
Song, C. et al. Continental-scale decrease in net primary productivity in streams due to climate warming. Nat. Geosci. 11, 415–420 (2018).Article 
CAS 

Google Scholar 
Hood, J. M. et al. Increased resource use efficiency amplifies positive response of aquatic primary production to experimental warming. Glob. Change Biol. 24, 1069–1084 (2018).Article 

Google Scholar 
Schindler, D. E., Carpenter, S. R., Cole, J. J., Kitchell, J. F. & Pace, M. L. Influence of food web structure on carbon exchange between lakes and the atmosphere. Science 277, 248–251 (1997).Article 
CAS 

Google Scholar 
Iannucci, F. M., Beneš, J., Medvedeff, A. & Bowden, W. B. Biogeochemical responses over 37 years to manipulation of phosphorus concentrations in an Arctic river: The Upper Kuparuk River Experiment. Hydrol. Process. 35, e14075 (2021).Article 
CAS 

Google Scholar 
Rosemond, A. D. et al. Experimental nutrient additions accelerate terrestrial carbon loss from stream ecosystems. Science 347, 1142–1145 (2015). A key study explaining how nutrient excess can accelerate terrestrial carbon loss from stream ecosystems.Article 
CAS 

Google Scholar 
Arroita, M., Elosegi, A. & Hall, R. O. Jr Twenty years of daily metabolism show riverine recovery following sewage abatement. Limnol. Oceanogr. 64, 77–92 (2019).Article 

Google Scholar 
Battin, T. J. et al. Biophysical controls on organic carbon fluxes in fluvial networks. Nat. Geosci. 1, 95–100 (2008). An important article conceptualizing how physical and biological processes combine to shape metabolic dynamics and carbon fluxes in fluvial networks.Article 
CAS 

Google Scholar 
Hoellein, T. J., Bruesewitz, D. A. & Richardson, D. C. Revisiting Odum (1956): a synthesis of aquatic ecosystem metabolism. Limnol. Oceanogr. 58, 2089–2100 (2013).Article 
CAS 

Google Scholar 
Marzolf, N. S. & Ardón, M. Ecosystem metabolism in tropical streams and rivers: a review and synthesis. Limnol. Oceanogr. 66, 1627–1638 (2021).Article 

Google Scholar 
Gounand, I., Little, C. J., Harvey, E. & Altermatt, F. Cross-ecosystem carbon flows connecting ecosystems worldwide. Nat. Commun. 9, 4825 (2018).Article 

Google Scholar 
Ciais, P. et al. Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration. Natl Sci. Rev. 8, nwaa145 (2020).Article 

Google Scholar 
Bauer, J. E. et al. The changing carbon cycle of the coastal ocean. Nature 504, 61–70 (2013). Important review on the sources, exchange and fates of carbon in the coastal ocean and how human activities have altered the coastal carbon cycle.Article 
CAS 

Google Scholar 
Reichert, P., Uehlinger, U. & Acuña, V. Estimating stream metabolism from oxygen concentrations: effect of spatial heterogeneity. J. Geophys. Res. Biogeosci. 114, G03016 (2009).Article 

Google Scholar 
Koenig, L. E. et al. Emergent productivity regimes of river networks. Limnol. Oceanogr. Lett. 4, 173–181 (2019).Article 

Google Scholar 
Rodríguez-Castillo, T., Estévez, E., González-Ferreras, A. M. & Barquín, J. Estimating ecosystem metabolism to entire river networks. Ecosystems 22, 892–911 (2019).Article 

Google Scholar 
Segatto, P. L., Battin, T. J. & Bertuzzo, E. The metabolic regimes at the scale of an entire stream network unveiled through sensor data and machine learning. Ecosystems 24, 1792–1809 (2021).Article 
CAS 

Google Scholar 
Loreau, M., Mouquet, N. & Holt, R. D. Meta‐ecosystems: a theoretical framework for a spatial ecosystem ecology. Ecol. Lett. 6, 673–679 (2003).Article 

Google Scholar 
Mastrandrea, M. D. et al. Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties (Intergovernmental Panel on Climate Change (IPCC), 2010).Tank, S. E., Fellman, J. B., Hood, E. & Kritzberg, E. S. Beyond respiration: controls on lateral carbon fluxes across the terrestrial‐aquatic interface. Limnol. Oceanogr. Lett. 3, 76–88 (2018). Important synthesis on the mechanisms and controls of organic and inorganic carbon flows across terrestrial–aquatic interfaces.Article 

Google Scholar 
Aitkenhead, J. A. & McDowell, W. H. Soil C:N ratio as a predictor of annual riverine DOC flux at local and global scales. Global Biogeochem. Cycles 14, 127–138 (2000).Article 
CAS 

Google Scholar 
Regnier, P., Resplandy, L., Najjar, R. G. & Ciais, P. The land-to-ocean loops of the global carbon cycle. Nature 603, 401–410 (2022).Article 
CAS 

Google Scholar 
van Hoek, W. J. et al. Exploring spatially explicit changes in carbon budgets of global river basins during the 20th century. Environ. Sci. Technol. 55, 16757–16769 (2021). A global quantitative assessment of river carbon fluxes in the twentieth century, highlighting the combined influence of environmental and anthropogenic controls on the long-term patterns of global carbon export.Article 

Google Scholar 
Abril, G. & Borges, A. V. Ideas and perspectives: carbon leaks from flooded land: do we need to replumb the inland water active pipe? Biogeosciences 16, 769–784 (2019). Important review emphasizing the role of flooding for inland water carbon cycling at the global scale.Article 
CAS 

Google Scholar 
Lauerwald, R., Regnier, P., Guenet, B., Friedlingstein, P. & Ciais, P. How simulations of the land carbon sink are biased by ignoring fluvial carbon transfers: a case study for the Amazon Basin. One Earth 3, 226–236 (2020).Article 

Google Scholar 
Raymond, P. A., Saiers, J. E. & Sobczak, W. V. Hydrological and biogeochemical controls on watershed dissolved organic matter transport: pulse‐shunt concept. Ecology 97, 5–16 (2016).Article 

Google Scholar 
Catalán, N., Marcé, R., Kothawala, D. N. & Tranvik, L. J. Organic carbon decomposition rates controlled by water retention time across inland waters. Nat. Geosci. 9, 501–504 (2016).Article 

Google Scholar 
Maavara, T., Lauerwald, R., Regnier, P. & Cappellen, P. V. Global perturbation of organic carbon cycling by river damming. Nat. Commun. 8, 15347 (2017).Article 
CAS 

Google Scholar 
Mendonça, R. et al. Organic carbon burial in global lakes and reservoirs. Nat. Commun. 8, 1694–1697 (2017).Article 

Google Scholar 
Downing, J. A. et al. Sediment organic carbon burial in agriculturally eutrophic impoundments over the last century. Global Biogeochem. Cycles 22, GB1018 (2008).Article 

Google Scholar 
Deemer, B. R. et al. Greenhouse gas emissions from reservoir water surfaces: a new global synthesis. Bioscience 66, 949–964 (2016).Article 

Google Scholar 
Abril, G. et al. Amazon River carbon dioxide outgassing fuelled by wetlands. Nature 505, 395–398 (2014).Article 
CAS 

Google Scholar 
Dodds, W. K. et al. Abiotic controls and temporal variability of river metabolism: multiyear analyses of Mississippi and Chattahoochee River data. Freshw. Sci. 32, 1073–1087 (2013).Article 

Google Scholar 
Ros, G. R., Sponseller, R. A., Bergström, A. K., Myrstener, M. & Giesler, R. Stream metabolism controls diel patterns and evasion of CO2 in Arctic streams. Glob. Change Biol. 26, 1400–1413 (2020).Article 

Google Scholar 
Rasilo, T., Hutchins, R. H. S., Ruiz-González, C. & Del Giorgio, P. A. Transport and transformation of soil-derived CO2, CH4 and DOC sustain CO2 supersaturation in small boreal streams. Sci. Total Environ. 579, 902–912 (2017).Article 
CAS 

Google Scholar 
Aho, K. S., Hosen, J. D., Logozzo, L. A., McGillis, W. R. & Raymond, P. A. Highest rates of gross primary productivity maintained despite CO2 depletion in a temperate river network. Limnol. Oceanogr. Lett. 6, 200–206 (2021).Article 
CAS 

Google Scholar 
Wehrli, B. Conduits of the carbon cycle. Nature 503, 346–347 (2013).Article 
CAS 

Google Scholar 
Sarmiento, J. L. & Sundquist, E. T. Revised budget for the oceanic uptake of anthropogenic carbon dioxide. Nature 356, 589–593 (1992).Article 
CAS 

Google Scholar 
Lacroix, F., Ilyina, T., Laruelle, G. G. & Regnier, P. Reconstructing the preindustrial coastal carbon cycle through a global ocean circulation model: was the global continental shelf already both autotrophic and a CO2 sink? Glob. Biogeochem. Cycles 35, e2020GB006603 (2021).Article 
CAS 

Google Scholar 
Jacobson, A. R., Fletcher, S. E. M., Gruber, N., Sarmiento, J. L. & Gloor, M. A joint atmosphere‐ocean inversion for surface fluxes of carbon dioxide: 1. Methods and global‐scale fluxes. Global Biogeochem. Cycles 21, GB1019 (2007).
Google Scholar 
Resplandy, L. et al. Revision of global carbon fluxes based on a reassessment of oceanic and riverine carbon transport. Nat. Geosci. 11, 504–509 (2018).Article 
CAS 

Google Scholar 
Lee, L.-C. et al. Unusual roles of discharge, slope and SOC in DOC transport in small mountainous rivers, Taiwan. Sci. Rep. 9, 1574 (2019).Article 

Google Scholar 
Reddy, S. K. K. et al. Export of particulate organic carbon by the mountainous tropical rivers of Western Ghats, India: variations and controls. Sci. Total Environ. 751, 142115 (2021).Article 
CAS 

Google Scholar 
Zhang, X., Tarpley, D. & Sullivan, J. T. Diverse responses of vegetation phenology to a warming climate. Geophys. Res. Lett. 34, L19405 (2007).Article 

Google Scholar 
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).Article 
CAS 

Google Scholar 
Heathcote, A. J., Anderson, N. J., Prairie, Y. T., Engstrom, D. R. & del Giorgio, P. A. Large increases in carbon burial in northern lakes during the Anthropocene. Nat. Commun. 6, 10016 (2015).Article 
CAS 

Google Scholar 
Guillemette, F., Berggren, M., Giorgio, P. Adel. & Lapierre, J.-F. Increases in terrestrially derived carbon stimulate organic carbon processing and CO2 emissions in boreal aquatic ecosystems. Nat. Commun. 4, 2972 (2013).Article 

Google Scholar 
Hastie, A., Lauerwald, R., Ciais, P., Papa, F. & Regnier, P. Historical and future contributions of inland waters to the Congo Basin carbon balance. Earth Syst. Dyn. 12, 37–62 (2020).Article 

Google Scholar 
Nakhavali, M. et al. Leaching of dissolved organic carbon from mineral soils plays a significant role in the terrestrial carbon balance. Glob. Change Biol. 27, 1083–1096 (2021).Article 
CAS 

Google Scholar 
Tian, H. et al. Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models: current status and future directions. Global Biogeochem. Cycles 29, 775–792 (2015).Article 
CAS 

Google Scholar 
Öquist, M. G. et al. The full annual carbon balance of boreal forests is highly sensitive to precipitation. Environ. Sci. Technol. Lett. 1, 315–319 (2014).Article 

Google Scholar 
Jones, J. B.Jr, Stanley, E. H. & Mulholland, P. J. Long‐term decline in carbon dioxide supersaturation in rivers across the contiguous United States. Geophys. Res. Lett. 30, 1495 (2003).Article 

Google Scholar 
Raymond, P. A. & Oh, N.-H. Long term changes of chemical weathering products in rivers heavily impacted from acid mine drainage: insights on the impact of coal mining on regional and global carbon and sulfur budgets. Earth Planet. Sci. Lett. 284, 50–56 (2009).Article 
CAS 

Google Scholar 
Ran, L. et al. Substantial decrease in CO2 emissions from Chinese inland waters due to global change. Nat. Commun. 12, 1730 (2021).Article 
CAS 

Google Scholar 
Zarnetske, J. P., Bouda, M., Geophysical, B. A., Saiers, J. & Raymond, P. Generality of hydrologic transport limitation of watershed organic carbon flux across ecoregions of the United States. Geophys. Res. Lett. 45, 11,702–11,711 (2018).Article 
CAS 

Google Scholar 
Liu, S. et al. The importance of hydrology in routing terrestrial carbon to the atmosphere via global streams and rivers. Proc. Natl Acad. Sci. USA 119, e2106322119 (2022).Article 
CAS 

Google Scholar 
Nydahl, A. C., Wallin, M. B. & Weyhenmeyer, G. A. No long‐term trends in pCO2 despite increasing organic carbon concentrations in boreal lakes, streams, and rivers. Global Biogeochem. Cycles 31, 985–995 (2017).Article 
CAS 

Google Scholar 
Raymond, P. A. & Hamilton, S. K. Anthropogenic influences on riverine fluxes of dissolved inorganic carbon to the oceans. Limnol. Oceanogr. Lett. 3, 143–155 (2018).Article 
CAS 

Google Scholar 
Ulseth, A. J., Bertuzzo, E., Singer, G. A., Schelker, J. & Battin, T. J. Climate-induced changes in spring snowmelt impact ecosystem metabolism and carbon fluxes in an Alpine stream network. Ecosystems 21, 373–390 (2018).Article 
CAS 

Google Scholar 
Berghuijs, W. R., Woods, R. A. & Hrachowitz, M. A precipitation shift from snow towards rain leads to a decrease in streamflow. Nat. Clim. Change 4, 583–586 (2014).Article 

Google Scholar 
Drake, T. W. et al. Mobilization of aged and biolabile soil carbon by tropical deforestation. Nat. Geosci. 12, 541–546 (2019).Article 
CAS 

Google Scholar 
Wit, F. et al. The impact of disturbed peatlands on river outgassing in Southeast Asia. Nat. Commun. 6, 10155 (2015).Article 
CAS 

Google Scholar 
Moore, S., Gauci, V., Evans, C. D. & Page, S. E. Fluvial organic carbon losses from a Bornean blackwater river. Biogeosciences 8, 901–909 (2011).Article 
CAS 

Google Scholar 
Masese, F. O., Salcedo-Borda, J. S., Gettel, G. M., Irvine, K. & McClain, M. E. Influence of catchment land use and seasonality on dissolved organic matter composition and ecosystem metabolism in headwater streams of a Kenyan river. Biogeochemistry 132, 1–22 (2017).Article 
CAS 

Google Scholar 
Bernot, M. J. et al. Inter‐regional comparison of land‐use effects on stream metabolism. Freshw. Biol. 55, 1874–1890 (2010). Among the first studies showing how land use alters ecosystem metabolism across geographic regions.Article 

Google Scholar 
Griffiths, N. A. et al. Agricultural land use alters the seasonality and magnitude of stream metabolism. Limnol. Oceanogr. 58, 1513–1529 (2013).Article 
CAS 

Google Scholar 
Sweeney, B. W. et al. Riparian deforestation, stream narrowing, and loss of stream ecosystem services. Proc. Natl Acad. Sci. 101, 14132–14137 (2004).Article 
CAS 

Google Scholar 
Roley, S. S., Tank, J. L., Griffiths, N. A., Hall, R. O. Jr & Davis, R. T. The influence of floodplain restoration on whole-stream metabolism in an agricultural stream: insights from a 5-year continuous data set. Freshw. Sci. 33, 1043–1059 (2014).Article 

Google Scholar 
Crawford, J. T., Stanley, E. H., Dornblaser, M. M. & Striegl, R. G. CO2 time series patterns in contrasting headwater streams of North America. Aquat. Sci. 79, 473–486 (2016).Article 

Google Scholar 
Blackburn, S. R. & Stanley, E. H. Floods increase carbon dioxide and methane fluxes in agricultural streams. Freshw. Biol. 66, 62–77 (2021).Article 
CAS 

Google Scholar 
Robertson, G. P., Paul, E. A. & Harwood, R. R. Greenhouse gases in intensive agriculture: contributions of individual gases to the radiative forcing of the atmosphere. Science 289, 1922–1925 (2000).Article 
CAS 

Google Scholar 
Min, S.-K., Zhang, X., Zwiers, F. W. & Hegerl, G. C. Human contribution to more-intense precipitation extremes. Nature 470, 378–381 (2011).Article 
CAS 

Google Scholar 
Yin, J. et al. Large increase in global storm runoff extremes driven by climate and anthropogenic changes. Nat. Commun. 9, 4389 (2018).Article 
CAS 

Google Scholar 
Myhre, G. et al. Sensible heat has significantly affected the global hydrological cycle over the historical period. Nat. Commun. 9, 1922 (2018).Article 
CAS 

Google Scholar 
Messager, M. L. et al. Global prevalence of non-perennial rivers and streams. Nature 594, 391–397 (2021).Article 
CAS 

Google Scholar 
Ward, A. S., Wondzell, S. M., Schmadel, N. M. & Herzog, S. P. Climate change causes river network contraction and disconnection in the H.J. Andrews Experimental Forest, Oregon, USA. Front. Water 2, 7 (2020).Article 

Google Scholar 
Sabater, S., Timoner, X., Borrego, C. & Acuña, V. Stream biofilm responses to flow intermittency: from cells to ecosystems. Front. Environ. Sci. 4, 14 (2016).Article 

Google Scholar 
Gómez-Gener, L., Lupon, A., Laudon, H. & Sponseller, R. A. Drought alters the biogeochemistry of boreal stream networks. Nat. Commun. 11, 1795 (2020).Article 

Google Scholar 
Marcé, R. et al. Emissions from dry inland waters are a blind spot in the global carbon cycle. Earth Sci. Rev. 188, 240–248 (2019).Article 

Google Scholar 
Blaszczak, J. R., Delesantro, J. M., Urban, D. L., Doyle, M. W. & Bernhardt, E. S. Scoured or suffocated: urban stream ecosystems oscillate between hydrologic and dissolved oxygen extremes. Limnol. Oceanogr. 64, 877–894 (2019).Article 
CAS 

Google Scholar 
Reisinger, A. J. et al. Recovery and resilience of urban stream metabolism following Superstorm Sandy and other floods. Ecosphere 8, e01776 (2017).Article 

Google Scholar 
O’Donnell, B. & Hotchkiss, E. R. Coupling concentration‐ and process‐discharge relationships integrates water chemistry and metabolism in streams. Water Resour. Res. 55, 10179–10190 (2019).Article 

Google Scholar 
Thellman, A. et al. The ecology of river ice. J. Geophys. Res. Biogeosci. 126, e2021JG006275 (2021).Article 

Google Scholar 
Maavara, T. et al. River dam impacts on biogeochemical cycling. Nat. Rev. Earth Environ. 1, 103–116 (2020).Article 

Google Scholar 
Rosentreter, J. A. et al. Half of global methane emissions come from highly variable aquatic ecosystem sources. Nat. Geosci. 14, 225–230 (2021).Article 
CAS 

Google Scholar 
Barros, N. et al. Carbon emission from hydroelectric reservoirs linked to reservoir age and latitude. Nat. Geosci. 4, 593–596 (2011).Article 
CAS 

Google Scholar 
Keller, P. S., Marcé, R., Obrador, B. & Koschorreck, M. Global carbon budget of reservoirs is overturned by the quantification of drawdown areas. Nat. Geosci. 14, 402–408 (2021).Article 
CAS 

Google Scholar 
Calamita, E. et al. Unaccounted CO2 leaks downstream of a large tropical hydroelectric reservoir. Proc. Natl Acad. Sci. USA 118, e2026004118 (2021).Article 
CAS 

Google Scholar 
Park, J.-H. et al. Reviews and syntheses: anthropogenic perturbations to carbon fluxes in Asian river systems – concepts, emerging trends, and research challenges. Biogeosciences 15, 3049–3069 (2018).Article 
CAS 

Google Scholar 
Rosamond, M. S., Thuss, S. J. & Schiff, S. L. Dependence of riverine nitrous oxide emissions on dissolved oxygen levels. Nat. Geosci. 5, 715–718 (2012).Article 
CAS 

Google Scholar 
Stanley, E. H. et al. The ecology of methane in streams and rivers: patterns, controls, and global significance. Ecol. Monogr. 86, 146–171 (2016). Key paper highlighting the role of streams and rivers for methane production and emissions and developing a conceptual framework on the environmental drivers of methane dynamics in fluvial ecosystems.Article 

Google Scholar 
Breitburg, D. et al. Declining oxygen in the global ocean and coastal waters. Science 359, eaam7240 (2018).Article 

Google Scholar 
Jane, S. F. et al. Widespread deoxygenation of temperate lakes. Nature 594, 66–70 (2021).Article 
CAS 

Google Scholar 
Triska, F. J., Kennedy, V. C., Avanzino, R. J., Zellweger, G. W. & Bencala, K. E. Retention and transport of nutrients in a third‐order stream in northwestern California: hyporheic processes. Ecology 70, 1893–1905 (1989).Article 

Google Scholar 
Carter, A. M., Blaszczak, J. R., Heffernan, J. B. & Bernhardt, E. S. Hypoxia dynamics and spatial distribution in a low gradient river. Limnol. Oceanogr. 66, 2251–2265 (2021).Article 

Google Scholar 
Kadygrov, N. et al. On the potential of the ICOS atmospheric CO2 measurement network for estimating the biogenic CO2 budget of Europe. Atmos. Chem. Phys. 15, 12765–12787 (2015).Article 
CAS 

Google Scholar 
Hanson, P. C., Weathers, K. C. & Kratz, T. K. Networked lake science: how the Global Lake Ecological Observatory Network (GLEON) works to understand, predict, and communicate lake ecosystem response to global change. Inland Waters 6, 543–554 (2018).Article 

Google Scholar 
Claustre, H., Johnson, K. S. & Takeshita, Y. Observing the global ocean with biogeochemical-Argo. Annu. Rev. Mar. Sci. 12, 23–48 (2019).Article 

Google Scholar 
Jankowski, K. J., Mejia, F. H., Blaszczak, J. R. & Holtgrieve, G. W. Aquatic ecosystem metabolism as a tool in environmental management. Wiley Interdiscip. Rev. Water 8, e1521 (2021).Article 

Google Scholar 
Mao, F. et al. Moving beyond the technology: a socio-technical roadmap for low-cost water sensor network applications. Environ. Sci. Technol. 54, 9145–9158 (2020).Article 
CAS 

Google Scholar 
Park, J., Kim, K. T. & Lee, W. H. Recent advances in information and communications technology (ICT) and sensor technology for monitoring water quality. Water 12, 510 (2020).Article 
CAS 

Google Scholar 
Yamazaki, D. et al. MERIT Hydro: a high‐resolution global hydrography map based on latest topography dataset. Water Resour. Res. 55, 5053–5073 (2019).Article 

Google Scholar 
Lin, P., Pan, M., Wood, E. F., Yamazaki, D. & Allen, G. H. A new vector-based global river network dataset accounting for variable drainage density. Sci. Data 8, 28 (2021).Article 

Google Scholar 
Allen, G. H. & Pavelsky, T. M. Global extent of rivers and streams. Science 361, 585–587 (2018).Article 
CAS 
MATH 

Google Scholar 
Durand, M. et al. An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope. Water Resour. Res. 52, 4527–4549 (2016).Article 

Google Scholar 
Frasson, R. P. M. et al. Exploring the factors controlling the error characteristics of the surface water and ocean topography mission discharge estimates. Water Resour. Res. 57, e2020WR028519 (2021).Article 

Google Scholar 
Dethier, E. N., Renshaw, C. E. & Magilligan, F. J. Rapid changes to global river suspended sediment flux by humans. Science 376, 1447–1452 (2022).Article 
CAS 

Google Scholar 
Campbell, A. D. et al. A review of carbon monitoring in wet carbon systems using remote sensing. Environ. Res. Lett. 17, 025009 (2022).Article 

Google Scholar 
Allen, G. H. et al. Similarity of stream width distributions across headwater systems. Nat. Commun. 9, 610 (2018).Article 

Google Scholar 
Rodriguez-Iturbe, I. & Rinaldo, A. Fractal River Basins: Chance and Self-organization (Cambridge Univ. Press, 2001). Game-changing oeuvre formalizing the structure and function of river networks.Bertuzzo, E., Helton, A. M., Hall, Robert, O. & Battin, T. J. Scaling of dissolved organic carbon removal in river networks. Adv. Water Resour. 110, 136–146 (2017).Article 
CAS 

Google Scholar 
Marzadri, A., Dee, M. M., Tonina, D., Bellin, A. & Tank, J. L. Role of surface and subsurface processes in scaling N2O emissions along riverine networks. Proc. Natl Acad. Sci. USA 114, 4330–4335 (2017).Article 
CAS 

Google Scholar 
Marzadri, A. et al. Global riverine nitrous oxide emissions: the role of small streams and large rivers. Sci. Total Environ. 776, 145148 (2021).Article 
CAS 

Google Scholar 
Botter, G. & Durighetto, N. The stream length duration curve: a tool for characterizing the time variability of the flowing stream length. Water Resour. Res. 56, e2020WR027282 (2020).Article 
CAS 

Google Scholar 
Wollheim, W. M. et al. River network saturation concept: factors influencing the balance of biogeochemical supply and demand of river networks. Biogeochemistry 141, 503–521 (2018).Article 
CAS 

Google Scholar 
Durighetto, N., Vingiani, F., Bertassello, L. E., Camporese, M. & Botter, G. Intraseasonal drainage network dynamics in a headwater catchment of the Italian Alps. Water Resour. Res. 56, e2019WR02556 (2020).Article 

Google Scholar 
Montgomery, D. R. & Dietrich, W. E. Source areas, drainage density, and channel initiation. Water Resour. Res. 25, 1907–1918 (1989).Article 

Google Scholar 
Fatichi, S., Ivanov, V. Y. & Caporali, E. A mechanistic ecohydrological model to investigate complex interactions in cold and warm water‐controlled environments: 1. Theoretical framework and plot‐scale analysis. J. Adv. Model. Earth. Syst. 4, M05002 (2012).
Google Scholar 
Ulseth, A. J. et al. Distinct air–water gas exchange regimes in low- and high-energy streams. Nat. Geosci. 12, 259–263 (2019).Article 
CAS 

Google Scholar 
Hall, R. O. in Streams and Ecosystems in a Changing Environment (eds. Jones, J. J. & Stanley, E. H.) 151–180 (Academic, 2016).Butman, D. & Raymond, P. A. Significant efflux of carbon dioxide from streams and rivers in the United States. Nat. Geosci. 4, 839–842 (2011).Article 
CAS 

Google Scholar 
Duvert, C., Butman, D. E., Marx, A., Ribolzi, O. & Hutley, L. B. CO2 evasion along streams driven by groundwater inputs and geomorphic controls. Nat. Geosci. 11, 813–818 (2018).Article 
CAS 

Google Scholar 
Zhang, L. et al. Significant methane ebullition from alpine permafrost rivers on the East Qinghai–Tibet Plateau. Nat. Geosci. 13, 349–354 (2020).Article 

Google Scholar  More