Ecology

1.Parmesan, C. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Syst. 37, 637–669 (2006).Article 

Google Scholar 
2.IPCC. Climate change 2014: Synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. (2014).3.Inouye, D. W., Barr, B., Armitage, K. B. & Inouye, B. D. Climate change is affecting altitudinal migrants and hibernating species. Proc. Natl. Acad. Sci. 97, 1630–1633 (2000).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
4.Adamík, P. & Král, M. Climate- and resource-driven long-term changes in dormice populations negatively affect hole-nesting songbirds. J. Zool. 275, 209–215 (2008).Article 

Google Scholar 
5.Ozgul, A. et al. Coupled dynamics of body mass and population growth in response to environmental change. Nature 466, 482–485 (2010).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
6.Moyes, K. et al. Advancing breeding phenology in response to environmental change in a wild red deer population. Glob. Chang. Biol. 17, 2455–2469 (2011).ADS 
Article 

Google Scholar 
7.Both, C., Van Asch, M., Bijlsma, R. G., Van Den Burg, A. B. & Visser, M. E. Climate change and unequal phenological changes across four trophic levels: Constraints or adaptations?. J. Anim. Ecol. 78, 73–83 (2009).PubMed 
Article 

Google Scholar 
8.Visser, M. E., Van Noordwijk, A. J., Tinbergen, J. M. & Lessells, C. M. Warmer springs lead to mistimed reproduction in great tits (Parus major). Proc. R. Soc. B Biol. Sci. 265, 1867–1870 (1998).Article 

Google Scholar 
9.Thackeray, S. J. et al. Trophic level asynchrony in rates of phenological change for marine, freshwater and terrestrial environments. Glob. Chang. Biol. 16, 3304–3313 (2010).ADS 
Article 

Google Scholar 
10.Spooner, F. E. B., Pearson, R. G. & Freeman, R. Rapid warming is associated with population decline among terrestrial birds and mammals globally. Glob. Chang. Biol. 24, 4521–4531 (2018).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
11.Sheriff, M. J., Boonstra, R., Palme, R., Loren Buck, C. & Barnes, B. M. Coping with differences in snow cover: The impact on the condition, physiology and fitness of an arctic hibernator. Conserv. Physiol. 5, 1–12 (2017).Article 

Google Scholar 
12.Easterling, D. R. et al. Climate extremes: Observations, modeling, and impacts. Science 289, 2068–2075 (2000).ADS 
CAS 
Article 

Google Scholar 
13.IPCC. Managing the risks of extreme events and disasters to advance climate change adaptation: Special report of the Intergovernmental Panel on Climate Change. (2012).14.Krause, J. S. et al. The effect of extreme spring weather on body condition and stress physiology in Lapland longspurs and white-crowned sparrows breeding in the Arctic. Gen. Comp. Endocrinol. 237, 10–18 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
15.Latimer, C. E. & Zuckerberg, B. How extreme is extreme? Demographic approaches inform the occurrence and ecological relevance of extreme events. Ecol. Monogr. 89, 1–15 (2019).Article 

Google Scholar 
16.Gutschick, V. P. & BassiriRad, H. Extreme events as shaping physiology, ecology, and evolution of plants: Toward a unified definition and evaluation of their consequences. New Phytol. 160, 21–42 (2003).PubMed 
Article 
PubMed Central 

Google Scholar 
17.Bailey, L. D. & van de Pol, M. Tackling extremes: Challenges for ecological and evolutionary research on extreme climatic events. J. Anim. Ecol. 85, 85–96 (2016).PubMed 
Article 
PubMed Central 

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

Google Scholar 
19.Boucek, R. E. & Rehage, J. S. Climate extremes drive changes in functional community structure. Glob. Chang. Biol. 20, 1821–1831 (2014).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
20.Hale, S. et al. Fire and climatic extremes shape mammal distributions in a fire-prone landscape. Divers. Distrib. 22, 1127–1138 (2016).Article 

Google Scholar 
21.Frederiksen, M., Daunt, F., Harris, M. P. & Wanless, S. The demographic impact of extreme events: Stochastic weather drives survival and population dynamics in a long-lived seabird. J. Anim. Ecol. 77, 1020–1029 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
22.Wingfield, J. C., Kelley, J. P. & Angelier, F. What are extreme environmental conditions and how do organisms cope with them?. Curr. Zool. 57, 363–374 (2011).Article 

Google Scholar 
23.Helm, B. et al. Annual rhythms that underlie phenology: Biological time-keeping meets environmental change. Proc. R. Soc. B Biol. Sci. 280, 1–10 (2013).
Google Scholar 
24.Sheriff, M. J., Richter, M. M., Buck, C. L. & Barnes, B. M. Changing seasonality and phenological responses of free-living male Arctic ground squirrels: The importance of sex. Philos. Trans. R. Soc. B Biol. Sci. 368, (2013).25.Michener, G. R. & Locklear, L. Differential costs of reproductive effort for male and female Richardson’s ground squirrels. Ecology 71, 855–868 (1990).Article 

Google Scholar 
26.Williams, C. T., Barnes, B. M., Kenagy, G. J. & Buck, C. L. Phenology of hibernation and reproduction in ground squirrels: Integration of environmental cues with endogenous programming. J. Zool. 292, 112–124 (2014).Article 

Google Scholar 
27.Michener, G. R. Age, sex, and species differences in the annual cycles of ground-dwelling sciurids: Implications for sociality. in The biology of ground-dwelling squirrels: annual cycles, behavioral ecology, and sociality (eds. Murie, J. O. & Michener, G. R.) 81–107 (University of Nebraska Press, Lincoln, 1984).28.Kenagy, G. J., Sharbaugh, S. M. & Nagy, K. A. Annual cycle of energy and time expenditure in a golden-mantled ground squirrel population. Oecologia 78, 269–282 (1989).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
29.Michener, G. R. Sexual Differences in over-winter torpor patterns of Richardson’s ground squirrels in natural hibernacula. Oecologia 89, 397–406 (1992).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
30.Michener, G. R. Effect of climatic conditions on the annual activity and hibernation cycle of Richardson’s ground squirrels and Columbian ground squirrels. Can. J. Zool. 55, 693–703 (1977).Article 

Google Scholar 
31.Michener, G. R. The circannual cycle of Richardson’s ground squirrels in southern Alberta. J. Mammal. 60, 760–768 (1979).Article 

Google Scholar 
32.Sheriff, M. J., Buck, C. L. & Barnes, B. M. Autumn conditions as a driver of spring phenology in a free-living arctic mammal. Clim. Chang. Responses 2, 1–7 (2015).Article 

Google Scholar 
33.Edic, M. N., Martin, J. G. A. & Blumstein, D. T. Heritable variation in the timing of emergence from hibernation. Evol. Ecol. 34, 763–776 (2020).Article 

Google Scholar 
34.Lane, J. E., Kruuk, L. E. B., Charmantier, A., Murie, J. O. & Dobson, F. S. Delayed phenology and reduced fitness associated with climate change in a wild hibernator. Nature 489, 554–557 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
35.Dobson, F. S., Lane, J. E., Low, M. & Murie, J. O. Fitness implications of seasonal climate variation in Columbian ground squirrels. Ecol. Evol. 6, 5614–5622 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
36.Armitage, K. B. Climate change and the conservation of marmots. Nat. Sci. 05, 36–43 (2013).
Google Scholar 
37.Neuhaus, P., Bennett, R. & Hubbs, A. Effects of a late snowstorm and rain on survival and reproductive success in Columbian ground squirrels (Spermophilus columbianus). Can. J. Zool. 77, 879–884 (1999).Article 

Google Scholar 
38.Williams, C. T. et al. Sex-dependent phenological plasticity in an arctic hibernator. Am. Nat. 190, 854–859 (2017).PubMed 
Article 

Google Scholar 
39.Barnes, B. M. Relationship between hibernation and reproduction in male ground squirrels. in Adaptations to the Cold: Tenth International Hibernation Symposium (eds. Geiser, F., Hulbert, A. J. & Nicol, S. C.) 71–80 (University of New England Press, 1996).40.Lee, T. M., Pelz, K., Licht, P. & Zucker, I. Testosterone influences hibernation in golden-mantled ground squirrels. Am. J. Physiol. Regul. Integr. Comput. Physiol. 259, 760–767 (1990).Article 

Google Scholar 
41.Richter, M. M., Barnes, B. M., Reilly, K. M. O., Fenn, A. M. & Buck, C. L. The influence of androgens on hibernation phenology of free-livingmale arctic ground squirrels. Horm. Behav. 89, 92–97 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
42.Michener, G. R. Spring emergence schedules and vernal behavior of Richardson’s ground squirrels: Why do males emerge from hibernation before females?. Behav. Ecol. Sociobiol. 14, 29–38 (1983).Article 

Google Scholar 
43.Wells, L. J. Seasonal sexual Rhythm and its experimental modification in the male of the thirteen-lined ground squirrel (Citellus tridecemlineatus). Anat. Rec. 62, 409–447 (1935).Article 

Google Scholar 
44.Michener, G. R. & Locklear, L. Over-winter weight loss by Richardson’s ground squirrels in relation to sexual differences in mating effort. J. Mammal. 71, 489–499 (1990).Article 

Google Scholar 
45.Poiani, A. Complexity of seminal fluid: A review. Behav. Ecol. Sociobiol. 60, 289–310 (2006).Article 

Google Scholar 
46.Michener, G. R. Estrous and gestation periods in Richardson’s ground squirrels. J. Mammal. 61, 531–534 (1980).Article 

Google Scholar 
47.Michener, G. R. Chronology of reproductive events for female Richardson’s ground aquirrels. J. Mammal. 66, 280–288 (1985).Article 

Google Scholar 
48.Michener, G. R. & McLean, I. G. Reproductive behaviour and operational sex ratio in Richardson’s ground squirrels. Anim. Behav. 52, 743–758 (1996).Article 

Google Scholar 
49.Hare, J. F., Todd, G. & Untereiner, W. A. Multiple mating results in multiple paternity in Richardson’s Ground Squirrels Spermophilus richardsonii. Can. Field Nat. 118, 90–94 (2004).Article 

Google Scholar 
50.Grumm, R., Arnott, J. & Halblaub, J. The epic eastern North American warm episode of March 2012. J. Oper. Meteorol. 2, 36–50 (2014).Article 

Google Scholar 
51.Environment and Climate Change Canada (ECCC). Top ten weather stories for 2012: story four—March’s meteorological mildness. (2017). Available at: https://www.ec.gc.ca/meteo-weather/default.asp?lang=En&n=70B4A3E9-1. (Accessed: 20th May 2020)52.Wilson, D. F. & Hare, J. F. Ground squirrel uses ultrasonic alarms. Nature 430, 523 (2004).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
53.Waterman, J. M., Macklin, G. F. & Enright, C. Sex-biased parasitism in Richardson’s ground squirrels (Urocitellus richardsonii) depends on the parasite examined. Can. J. Zool. 92, 73–79 (2014).Article 

Google Scholar 
54.Murie, J. O. & Harris, M. A. Annual variation of spring emergence and breeding in Columbian ground squirrels (Spermophilus columbianus). J. Mammal. 63, 431–439 (1982).Article 

Google Scholar 
55.Sikes, R. S. & Gannon, W. L. Guidelines of the American Society of Mammalogists for the use of wild mammals in research. J. Mammal. 92, 235–253 (2011).Article 

Google Scholar 
56.Gannon, W. L. & Sikes, R. S. Guidelines of the American society of mammalogists for the use of wild mammals in research. J. Mammal. 88, 809–823 (2007).Article 

Google Scholar 
57.Zucker, I. & Boshes, M. Circannual body weight rhythms of ground squirrels: Role of gonadal hormones. Am. J. Physiol. Regul. Int. Comput. Physiol. 12, 546–551 (1982).Article 

Google Scholar 
58.Boonstra, R., Hubbs, A. H., Lacey, E. A. & McColl, C. J. Seasonal changes in glucocorticoid and testosterone concentrations in free-living arctic ground squirrels from the boreal forest of the Yukon. Can. J. Zool. 79, 49–58 (2001).Article 

Google Scholar 
59.Bottini Luzardo, M., Centurion Castro, F., Alfaro Gamboa, M., Lopez, A. & Ake Lopez, A. Osmolarity of coconut water (Cocos nucifera) based diluents and their effect over viability of frozen boar semen. Am. J. Anim. Vet. Sci. 5, 187–191 (2010).Article 

Google Scholar 
60.Mollineau, W. M., Adogwa, A. O. & Garcia, G. W. Liquid and frozen storage of agouti (Dasyprocta leporina) semen extended with UHT milk, unpasteurized coconut water, and pasteurized coconut water. Vet. Med. Int. 2011, 1–5 (2011).Article 

Google Scholar 
61.Schulte-Hostedde, A. I., Millar, J. S. & Hickling, G. J. Evaluating body condition in small mammals. Can. J. Zool. 79, 1021–1029 (2001).Article 

Google Scholar 
62.Møller, A. P. & Birkhead, T. R. Copulation behaviour in mammals: Evidence that sperm competition is widespread. Biol. J. Linn. Soc. 38, 119–131 (1989).Article 

Google Scholar 
63.Sugg, D. W. & Chesser, R. K. Effective population sizes with multiple paternity. Genetics 137, 1147–1155 (1994).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
64.Murie, J. O. & Harris, M. A. Territoriality and dominance in male Columbian ground squirrels (Spermophilus columbianus). Can. J. Zool. 56, 2402–2412 (1978).Article 

Google Scholar 
65.Morton, M. L. & Gallup, J. S. Reproductive cycle of the Belding ground squirrel (Spermophilus beldingi beldingi): Seasonal and age differences. Gt. Basin Nat. 35, 427–433 (1975).
Google Scholar 
66.Barnes, B. M., Kretzmann, M., Licht, P. & Zucker, I. The influence of hibernation on testis growth and spermatogenesis in the golden-mantled ground squirrel Spermophilus lateralis. Biol. Reprod. 35, 1289–1297 (1986).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar  More

1.Eckstein, F. Phosphorothioation of DNA in bacteria. Nat. Chem. Biol. 3, 689–690 (2007).CAS 
PubMed 
Article 

Google Scholar 
2.Wang, L. et al. Phosphorothioation of DNA in bacteria by dnd genes. Nat. Chem. Biol. 3, 709–710 (2007).CAS 
PubMed 
Article 

Google Scholar 
3.Zhou, X. et al. A novel DNA modification by sulphur. Mol. Microbiol. 57, 1428–1438 (2005).CAS 
PubMed 
Article 

Google Scholar 
4.Chen, S., Wang, L. & Deng, Z. Twenty years hunting for sulfur in DNA. Protein cell 1, 14–21 (2010).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
5.Xu, T. et al. DNA phosphorothioation in Streptomyces lividans: mutational analysis of the dnd locus. BMC Microbiol. 9, 41 (2009).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
6.You, D., Wang, L., Yao, F., Zhou, X. & Deng, Z. A novel DNA modification by sulfur: DndA is a NifS-like cysteine desulfurase capable of assembling DndC as an iron-sulfur cluster protein in Streptomyces liVidans. Biochemistry 46, 6126–6133 (2007).CAS 
PubMed 
Article 

Google Scholar 
7.Chen, F. et al. Crystal structure of the cysteine desulfurase DndA from Streptomyces lividans which is involved in DNA phosphorothioation. PLoS ONE 7, e36635 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
8.An, X. et al. A novel target of IscS in Escherichia coli: participating in DNA phosphorothioation. PLoS ONE 7, e51265 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
9.Wang, L., Jiang, S., Deng, Z., Dedon, P. C. & Chen, S. DNA phosphorothioate modification-a new multi-functional epigenetic system in bacteria. FEMS Microbiol. Rev. 43, 109–122 (2019).CAS 
PubMed 
Article 

Google Scholar 
10.Yao, F., Xu, T., Zhou, X., Deng, Z. & You, D. Functional analysis of spfD gene involved in DNA phosphorothioation in Pseudomonas fluorescens Pf0-1. FEBS Lett. 583, 729–733 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
11.Hu, W. et al. Structural insights into DndE from Escherichia coli B7A involved in DNA phosphorothioation modification. Cell Res. 22, 1203–1206 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
12.Cheng, Q. et al. Regulation of DNA phosphorothioate modifications by the transcriptional regulator DptB in Salmonella. Mol. Microbiol. 97, 1186–1194 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
13.Xiong, W., Zhao, G., Yu, H. & He, X. Interactions of Dnd proteins involved in bacterial DNA phosphorothioate modification. Front. Microbiol. 6, 1139 (2015).PubMed 
PubMed Central 

Google Scholar 
14.Dai, D. et al. DNA phosphorothioate modification plays a role in peroxides resistance in Streptomyces lividans. Front. Microbiol. 7, 1380 (2016).PubMed 
PubMed Central 

Google Scholar 
15.Xie, X. et al. Phosphorothioate DNA as an antioxidant in bacteria. Nucleic Acids Res. 40, 9115–9124 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
16.Yang, Y. et al. DNA backbone sulfur-modification expands microbial growth range under multiple stresses by its anti-oxidation function. Sci. Rep. 7 (2017).17.Xu, T., Yao, F., Zhou, X., Deng, Z. & You, D. A novel host-specific restriction system associated with DNA backbone S-modification in Salmonella. Nucleic Acids Res. 38, 7133–7141 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
18.Liu, G. et al. Cleavage of phosphorothioated DNA and methylated DNA by the Type IV restriction endonuclease ScoMcrA. PLoS Genet. 6, e1001253 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Tong, T. et al. Occurrence, evolution, and functions of DNA phosphorothioate epigenetics in bacteria. Proc. Natl Acad. Sci. USA 115, E2988–E2996 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
20.Xiong, L. et al. A new type of DNA phosphorothioation-based antiviral system in archaea. Nat. Commun. 10 (2019).21.Xiong, X. et al. SspABCD-SspE is a phosphorothioation-sensing bacterial defence system with broad anti-phage activities. Nat. Microbiol. 5, 917–928 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
22.Dai, D., Pu, T., Liang, J., Wang, Z. & Tang, A. Regulation of dndB gene expression in Streptomyces lividans. Front. Microbiol. 9, 2387 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
23.Zhou, X., Deng, Z., Firmin, J. L., Hopwood, D. A. & Kieser, T. Site-specific degradation of Streptomyces lividans DNA during electrophoresis in buffers contaminated with ferrous iron. Nucleic Acids Res. 16, 4341–4352 (1988).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
24.Sun, Y. et al. DNA phosphorothioate modifications are widely distributed in the human microbiome. Biomolecules 10, 1175 (2020).CAS 
PubMed Central 
Article 

Google Scholar 
25.Khan, H. et al. DNA phosphorothioate modification facilitates the dissemination of mcr-1 and blaNDM-1 in drinking water supply systems. Environ. Pollut. 268, 115799 (2021).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
26.Wang, L. et al. DNA phosphorothioation is widespread and quantized in bacterial genomes. Proc. Natl Acad. Sci. USA 108, 2963–2968 (2011).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
27.Blow, M. J. et al. The epigenomic landscape of prokaryotes. PLoS Genet. 12, e1005854 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
28.Yang, X., Jian, H. & Wang, F. pSW2, a novel low-temperature-inducible gene expression vector based on a filamentous phage of the deep-sea bacterium Shewanella piezotolerans WP3. Appl. Environ. Microbiol. 81, 5519–5526 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
29.Cao, B. et al. Genomic mapping of phosphorothioates reveals partial modification of short consensus sequences. Nat. Commun. 5, 3951 (2014).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
30.Jian, H. et al. Multiple mechanisms are involved in repression of filamentous phage SW1 transcription by the DNA-binding protein FpsR. J. Mol. Biol. 431, 1113–1126 (2019).CAS 
PubMed 
Article 

Google Scholar 
31.Lai, C. et al. In vivo mutational characterization of DndE involved in DNA phosphorothioate modification. PLoS ONE 9, e107981 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
32.Schoemaker, J. M., Gayda, R. C. & Markovitz, A. Regulation of cell division in Escherichia coli: SOS induction and cellular location of the SulA protein, a key to lon-associated filamentation and death. J. Bacteriol. 158, 551–561 (1984).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
33.Jian, H., Xiong, L., Xu, G., Xiao, X. & Wang, F. Long 5′ untranslated regions regulate the RNA stability of the deep-sea filamentous phage SW1. Sci. Rep. 6, 21908 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
34.Chen, C. et al. Convergence of DNA methylation and phosphorothioation epigenetics in bacterial genomes. Proc. Natl Acad. Sci. USA 114, 4501–4506 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.Maleki, F., Khosravi, A., Nasser, A., Taghinejad, H. & Azizian, M. Bacterial heat shock protein activity. J. Clin. Diagnostic Res. 10, BE01–BE03 (2016).CAS 

Google Scholar 
36.Knoll, A. H. Paleobiological perspectives on early microbial evolution. Cold Spring Harb. Perspect. Biol. 7, a018093 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
37.Schirrmeister, B. E., Gugger, M. & Donoghue, P. C. Cyanobacteria and the great oxidation event: evidence from genes and fossils. Palaeontology 58, 769–785 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
38.Luo, G. et al. Rapid oxygenation of Earth’s atmosphere 2.33 billion years ago. Sci. Adv. 2, e1600134 (2016).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
39.Wacey, D., Kilburn, M. R., Saunders, M., Cliff, J. & Brasier, M. D. Microfossils of sulphur-metabolizing cells in 3.4-billion-year-old rocks of Western Australia. Nat. Geosci. 4, 698–702 (2011).ADS 
CAS 
Article 

Google Scholar 
40.Bontognali, T. R. R. et al. Sulfur isotopes of organic matter preserved in 3.45-billion-year-old stromatolites reveal microbial metabolism. Proc. Natl Acad. Sci. USA 109, 15146–15151 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
41.Schirrmeister, B. E., Vos, J. M. D., Antonelli, A. & Bagheri, H. C. Evolution of multicellularity coincided with increased diversification of cyanobacteria and the great oxidation event. Proc. Natl Acad. Sci. USA 110, 1791–1796 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
42.Pang, K. et al. Nitrogen-fixing heterocystous Cyanobacteria in the tonian period. Curr. Biol. 28, 616–622 (2018).CAS 
PubMed 
Article 

Google Scholar 
43.Demoulin, C. F. et al. Cyanobacteria evolution: Insight from the fossil record. Free Radic. Biol. Med. in press (2021).44.Soo, R. M., Hemp, J., Parks, D. H., Fischer, W. W. & Hugenholtz, P. On the origins of oxygenic photosynthesis and aerobic respiration in Cyanobacteria. Science 355, 1436–1440 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
45.Ou, H.-Y. et al. dndDB: a database focused on phosphorothioation of the DNA backbone. PLoS ONE 4, e5132 (2009).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
46.Janda, J. M. & Abbott, S. L. The genus Shewanella: from the briny depths below to human pathogen. Crit. Rev. Microbiol. 40, 293–312 (2014).PubMed 
Article 

Google Scholar 
47.Fredrickson, J. K. et al. Towards environmental systems biology of Shewanella. Nat. Rev. Microbiol. 6, 592–603 (2008).CAS 
PubMed 
Article 

Google Scholar 
48.Hau, H. H. & Gralnick, J. A. Ecology and biotechnology of the genus Shewanella. Annu. Rev. Microbiol. 61, 237–258 (2007).CAS 
PubMed 
Article 

Google Scholar 
49.Nealson, K. H. & Scott, J. Ecophysiology of the Genus Shewanella. Prokaryotes 6, 1133–1151 (2006).Article 

Google Scholar 
50.Roux, S. et al. Cryptic inoviruses revealed as pervasive in bacteria and archaea across Earth’s biomes. Nat. Microbiol. 4, 1895–1906 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
51.Hay, I. D. & Lithgow, T. Filamentous phages: masters of a microbial sharing economy. EMBO Rep. 20, e47427 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
52.Mai-Prochnow, A. et al. ‘Big things in small packages: the genetics of filamentous phage and effects on fitness of their host’. FEMS Microbiol. Rev. 39, 465–487 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
53.Middelboe, M., Glud, R. N. & Finster, K. Distribution of viruses and bacteria in relation to diagenetic activity in an estuarine sediment. Limnol. Oceanogr. 48, 1447–1456 (2003).ADS 
Article 

Google Scholar 
54.Engelhardt, T., Orsi, W. D. & Jørgensen, B. B. Viral activities and life cycles in deep subseafloor sediments. Environ. Microbiol. Rep. 7, 868–873 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
55.Dell’Anno, A., Corinaldesi, C. & Danovaro, R. Virus decomposition provides an important contribution to benthic deep-sea ecosystem functioning. Proc. Natl Acad. Sci. USA 112, E2014–E2019 (2015).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
56.Rakonjac, J. Filamentous Bacteriophages: Biology and Applications. eLS (2012).57.Güemes, A. G. C. et al. Viruses as winners in the game of life. Annu. Rev. Virol. 3, 197–214 (2016).Article 
CAS 

Google Scholar 
58.Breitbart, M. Marine viruses: truth or dare. Annu. Rev. Mar. Sci. 4, 425–448 (2012).ADS 
Article 

Google Scholar 
59.Danovaro, R. et al. Marine viruses and global climate change. FEMS Microbiol. Rev. 35, 993–1034 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
60.Rohwer, F. & Thurber, R. V. Viruses manipulate the marine environment. Nature 459, 207–212 (2009).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
61.Touchon, M., Bernheim, A. & Rocha, E. P. Genetic and life-history traits associated with the distribution of prophages in bacteria. ISME J. 10, 2744–2754 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
62.Harrison, E. & Brockhurst, M. A. Ecological and evolutionary benefits of temperate phage: what does or doesn’t kill you makes you stronger. Bioessays 39, 201700112 (2017).Article 

Google Scholar 
63.Paul, J. H. Prophages in marine bacteria: dangerous molecular time bombs or the key to survival in the seas? ISME J. 2, 579–589 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
64.Wu, X. et al. Epigenetic competition reveals density-dependent regulation and target site plasticity of phosphorothioate epigenetics in bacteria. PNAS 117, 14322–14330 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
65.Willbanks, A. et al. The evolution of epigenetics: from prokaryotes to humans and its biological consequences. Genet. Epigenet. 8, 25–36 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
66.Razin, A. & Cedar, H. DNA methylation and gene expression. Microbiol. Rev. 55, 451–458 (1991).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
67.Casadesús, J. & Low, D. Epigenetic gene regulation in the bacterial world. Microbiol. Mol. Biol. Rev. 70, 830–856 (2006).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
68.Iyer, L. M., Abhiman, S. & Aravind, L. Natural history of eukaryotic DNA methylation systems. Prog. Mol. Biol. Transl. Sci. 101, 25–104 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
69.Weiss, M. C. et al. The physiology and habitat of the last universal common ancestor. Nat. Microbiol. 1, 16116 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
70.Gan, R. et al. DNA phosphorothioate modifications influence the global transcriptional response and protect DNA from double-stranded breaks. Sci. Rep. 4, 6642 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
71.Chen, L. et al. Theoretical study on the relationship between Rp-phosphorothioation and base-step in S-DNA: based on energetic and structural analysis. J. Phys. Chem. B 119, 474–481 (2015).CAS 
PubMed 
Article 

Google Scholar 
72.Kellner, S. et al. Oxidation of phosphorothioate DNA modifications leads to lethal genomic instability. Nat. Chem. Biol. 13, 888–894 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
73.Ślesak, I., Kula, M., Ślesak, H., Miszalski, Z. & Strzałka, K. How to define obligatory anaerobiosis? An evolutionary view on the antioxidant response system and the early stages of the evolution of life on Earth. Free Radic. Biol. Med. 140, 61–73 (2019).PubMed 
Article 
CAS 

Google Scholar 
74.Brioukhanov, A. L., Thauer, R. K. & Netrusov, A. I. Catalase and superoxide dismutase in the cells of strictly anaerobic microorganisms. Microbiol. (Russ. Acad. Sci.) 71, 330–335 (2002).
Google Scholar 
75.Sebaihia, M. et al. The multidrug-resistant human pathogen Clostridium difficile has a highly mobile, mosaic genome. Nat. Genet. 38, 779–786 (2006).PubMed 
Article 
CAS 

Google Scholar 
76.Kanehisa, M. et al. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res. 42, D199–D205 (2014).CAS 
PubMed 
Article 

Google Scholar 
77.Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).CAS 
PubMed 
Article 

Google Scholar 
78.Kieft, K., Zhou, Z. & Anantharaman, K. VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences. Microbiome 8, 90 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
79.Gregory, A. C. et al. Marine DNA viral macro- and microdiversity from pole to pole. Cell 177, 1109–1123 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
80.Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
81.Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
82.Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
83.Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: a toolkit to classify genomes with the genome taxonomy database. Bioinformatics 36, 1925–1927 (2020).CAS 

Google Scholar 
84.Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2–approximately maximum-likelihood treesfor large alignments. PLoS ONE 5, e9490 (2010).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
85.Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
86.Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 47, W256–W259 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
87.Kwak, S. G. & Kim, J. H. Central limit theorem: the cornerstone of modern statistics. Korean J. Anesthesiol. 70, 144–156 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
88.Virtanen, P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat. Methods 17, 261–272 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
89.R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2013).90.Chok, N. S. Pearson’s versus Spearman’s and Kendall’s correlation coefficients for continuous data Master of Science thesis, University of Pittsburgh, (2010).91.Jian, H., Xu, G., Gai, Y., Xu, J. & Xiao, X. The histone-like nucleoid structuring protein (H-NS) is a negative regulator of the lateral flagellar system in the deep-sea bacterium Shewanella piezotolerans WP3. Appl. Environ. Microbiol. 82, 2388–2398 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
92.Wang, F. et al. Environmental adaptation: genomic analysis of the piezotolerant and psychrotolerant deep-sea iron reducing bacterium Shewanella piezotolerans WP3. PLoS ONE 3, e1937 (2008).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
93.Jian, H., Xu, J., Xiao, X. & Wang, F. Dynamic modulation of DNA replication and gene transcription in deep-sea filamentous phage SW1 in response to changes of host growth and temperature. PLoS ONE 7, e41578 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
94.Chin, C.-S. et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat. Methods 10, 563–569 (2016).Article 
CAS 

Google Scholar 
95.Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
96.Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
97.Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 12, 323 (2011).CAS 
Article 

Google Scholar 
98.Wang, L., Feng, Z., Wang, X., Wang, X. & Zhang, X. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 26, 136–138 (2010).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
99.Trapnell, C. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
100.Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
101.Gao, H. et al. Reduction of nitrate in Shewanella oneidensis depends on atypical NAP and NRF systems with NapB as a preferred electron transport protein from CymA to NapA. ISME J. 3, 966–976 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
102.Lenski, R. E., Rose, M. R., Simpson, S. C. & Tadler, S. C. Long-term experimental evolution in Escherichia coli. I. Adaptation and divergence during 2000 generations. Am. Naturalist 138, 1315–1341 (1991).Article 

Google Scholar  More

1.D’Costa, V. M. et al. Antibiotic resistance is ancient. Nature 477, 457–461 (2011). This study shows that different ARGs are present in 30,000-year-old permafrost.
Google Scholar 
2.Bhullar, K. et al. Antibiotic resistance is prevalent in an isolated cave microbiome. PLoS ONE 7, e34953 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
3.Lugli, G. A. et al. Ancient bacteria of the Ötzi’s microbiome: a genomic tale from the Copper Age. Microbiome 5, 5 (2017).PubMed 
PubMed Central 

Google Scholar 
4.Perry, J., Waglechner, N. & Wright, G. The prehistory of antibiotic resistance. Cold Spring Harb. Perspect. Med. 6, a025197 (2016).PubMed 
PubMed Central 

Google Scholar 
5.Davies, J. & Davies, D. Origins and evolution of antibiotic resistance. Microbiol. Mol. Biol. Rev. 74, 417–433 (2010). This authoritative and educational review discusses in an insightful way the evolution of resistance, including its origins and future implications.CAS 
PubMed 
PubMed Central 

Google Scholar 
6.Allen, H. K. et al. Call of the wild: antibiotic resistance genes in natural environments. Nat. Rev. Microbiol. 8, 251–259 (2010).CAS 
PubMed 

Google Scholar 
7.Martinez, J. L. The role of natural environments in the evolution of resistance traits in pathogenic bacteria. Proc. R. Soc. B Biol. Sci. 276, 2521–2530 (2009).
Google Scholar 
8.Alcock, B. P. et al. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res. https://doi.org/10.1093/nar/gkz935 (2019).Article 
PubMed Central 

Google Scholar 
9.Mackenzie, J. S. & Jeggo, M. The one health approach — why is it so important? Trop. Med. Infect. Dis. 4, 88 (2019).PubMed Central 

Google Scholar 
10.Buschhardt, T. et al. A one health glossary to support communication and information exchange between the human health, animal health and food safety sectors. One Health 13, 100263 (2021).PubMed 
PubMed Central 

Google Scholar 
11.Berendonk, T. U. et al. Tackling antibiotic resistance: the environmental framework. Nat. Rev. Microbiol. 13, 310–317 (2015).CAS 
PubMed 

Google Scholar 
12.Wellington, E. M. et al. The role of the natural environment in the emergence of antibiotic resistance in gram-negative bacteria. Lancet Infect. Dis. 13, 155–165 (2013).CAS 
PubMed 

Google Scholar 
13.Bengtsson-Palme, J., Kristiansson, E. & Larsson, D. G. J. Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiol. Rev. https://doi.org/10.1093/femsre/fux053 (2017).Article 
PubMed Central 

Google Scholar 
14.Chow, L. K. M., Ghaly, T. M. & Gillings, M. R. A survey of sub-inhibitory concentrations of antibiotics in the environment. J. Environ. Sci. 99, 21–27 (2021).
Google Scholar 
15.Andersson, D. I. et al. Antibiotic resistance: turning evolutionary principles into clinical reality. FEMS Microbiol. Rev. 44, 171–188 (2020).CAS 
PubMed 

Google Scholar 
16.Singer, A. C., Shaw, H., Rhodes, V. & Hart, A. Review of antimicrobial resistance in the environment and its relevance to environmental regulators. Front. Microbiol. https://doi.org/10.3389/fmicb.2016.01728 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
17.United Nations Environment Programme. Frontiers 2017: emerging issues of environmental concern, https://www.unenvironment.org/resources/frontiers-2017-emerging-issues-environmental-concern (2017).18.Access to Medicines Foundation. 2020 antimicrobial resistance benchmark, https://accesstomedicinefoundation.org/publications/2020-antimicrobial-resistance-benchmark (2020).19.Review on Antimicrobial Resistance. Antimicrobials in agriculture and the environment: reducing unnecessary waste, https://amr-review.org/Publications.html (2015).20.European Parliament. Strategic approach to pharmaceuticals in the environment, https://www.europarl.europa.eu/doceo/document/TA-9-2020-0226_EN.pdf (2020).21.WHO. Technical brief on water, sanitation, hygiene (WASH) and wastewater management to prevent infections and reduce the spread of antimicrobial resistance (AMR)., https://www.who.int/water_sanitation_health/publications/wash-wastewater-management-to-prevent-infections-and-reduce-amr/en/ (2020).22.Graham, D. W. et al. Complexities in understanding antimicrobial resistance across domesticated animal, human, and environmental systems. Ann. N. Y. Acad. Sci. 1441, 17–30 (2019).PubMed 
PubMed Central 

Google Scholar 
23.Smalla, K., Cook, K., Djordjevic, S. P., Klümper, U. & Gillings, M. Environmental dimensions of antibiotic resistance: assessment of basic science gaps. FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fiy195 (2018).Article 
PubMed 

Google Scholar 
24.Rinke, C. et al. Insights into the phylogeny and coding potential of microbial dark matter. Nature 499, 431–437 (2013).CAS 
PubMed 

Google Scholar 
25.Schulz, F. et al. Towards a balanced view of the bacterial tree of life. Microbiome https://doi.org/10.1186/s40168-017-0360-9 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
26.Forsberg, K. J. et al. The shared antibiotic resistome of soil bacteria and human pathogens. Science 337, 1107–1111 (2012). This study demonstrates numerous identical resistance gene loci between multiresistant soil bacteria and diverse human pathogens, providing evidence for recent gene exchange across species and environments.CAS 
PubMed 
PubMed Central 

Google Scholar 
27.Berglund, F. et al. Identification of 76 novel B1 metallo-beta-lactamases through large-scale screening of genomic and metagenomic data. Microbiome 5, 134 (2017).PubMed 
PubMed Central 

Google Scholar 
28.Dantas, G., Sommer, M. O. A., Oluwasegun, R. D. & Church, G. M. Bacteria subsisting on antibiotics. Science 320, 100–103 (2008).CAS 
PubMed 

Google Scholar 
29.Berglund, F. et al. Comprehensive screening of genomic and metagenomic data reveals a large diversity of tetracycline resistance genes. Microb. Genomics https://doi.org/10.1099/mgen.0.000455 (2020).Article 

Google Scholar 
30.Pawlowski, A. C. et al. A diverse intrinsic antibiotic resistome from a cave bacterium. Nat. Commun. 7, 13803 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
31.Morar, M. & Wright, G. D. The genomic enzymology of antibiotic resistance. Annu. Rev. Genet. 44, 25–51 (2010).CAS 
PubMed 

Google Scholar 
32.Andersson, D. I., Jerlström-Hultqvist, J. & Näsvall, J. Evolution of new functions de novo and from preexisting genes. Cold Spring Harb. Perspect. Biol. 7, a017996 (2015).PubMed 
PubMed Central 

Google Scholar 
33.Razavi, M., Kristiansson, E., Flach, C.-F. & Larsson, D. G. J. The association between insertion sequences and antibiotic resistance genes. mSphere https://doi.org/10.1128/msphere.00418-20 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
34.Partridge, S. R., Kwong, S. M., Firth, N. & Jensen, S. O. Mobile genetic elements associated with antimicrobial resistance. Clin. Microbiol. Rev. https://doi.org/10.1128/cmr.00088-17 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
35.Gillings, M. et al. The evolution of class 1 integrons and the rise of antibiotic resistance. J. Bacteriol. 190, 5095–5100 (2008).CAS 
PubMed 
PubMed Central 

Google Scholar 
36.Razavi, M. et al. Discovery of the fourth mobile sulfonamide resistance gene. Microbiome https://doi.org/10.1186/s40168-017-0379-y (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
37.Flach, C.-F. et al. Does antifouling paint select for antibiotic resistance? Sci. Total Environ. 590–591, 461–468 (2017).PubMed 

Google Scholar 
38.Shintani, M. et al. Plant species-dependent increased abundance and diversity of IncP-1 plasmids in the rhizosphere: new insights into their role and ecology. Front. Microbiol. 11, 590776 (2020).PubMed 
PubMed Central 

Google Scholar 
39.Baquero, F., Coque, T. M., Martínez, J.-L., Aracil-Gisbert, S. & Lanza, V. F. Gene transmission in the one health microbiosphere and the channels of antimicrobial resistance. Front. Microbiol. https://doi.org/10.3389/fmicb.2019.02892 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
40.Vandecraen, J., Chandler, M., Aertsen, A. & Van Houdt, R. The impact of insertion sequences on bacterial genome plasticity and adaptability. Crit. Rev. Microbiol. 43, 709–730 (2017).CAS 
PubMed 

Google Scholar 
41.Depardieu, F., Podglajen, I., Leclercq, R., Collatz, E. & Courvalin, P. Modes and modulations of antibiotic resistance gene expression. Clin. Microbiol. Rev. 20, 79–114 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
42.Jutkina, J., Marathe, N. P., Flach, C. F. & Larsson, D. G. J. Antibiotics and common antibacterial biocides stimulate horizontal transfer of resistance at low concentrations. Sci. Total Environ. 616-617, 172–178 (2018).CAS 
PubMed 

Google Scholar 
43.Scornec, H., Bellanger, X., Guilloteau, H., Groshenry, G. & Merlin, C. Inducibility of Tn916 conjugative transfer in Enterococcus faecalis by subinhibitory concentrations of ribosome-targeting antibiotics. J. Antimicrob. Chemother. 72, 2722–2728 (2017).CAS 
PubMed 

Google Scholar 
44.Aminov, R. I. Horizontal gene exchange in environmental microbiota. Front. Microbiol. https://doi.org/10.3389/fmicb.2011.00158 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
45.Knöppel, A., Näsvall, J. & Andersson, D. I. Evolution of antibiotic resistance without antibiotic exposure. Antimicrob. Agents Chemother. https://doi.org/10.1128/aac.01495-17 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
46.Kimura, M. & Ohta, T. The average number of generations until fixation of a mutant gene in a finite population. Genetics 61, 763–771 (1969).CAS 
PubMed 
PubMed Central 

Google Scholar 
47.Letten, A. D., Hall, A. R. & Levine, J. M. Using ecological coexistence theory to understand antibiotic resistance and microbial competition. Nat. Ecol. Evol. 5, 431–441 (2021).PubMed 

Google Scholar 
48.Waglechner, N. & Wright, G. D. Antibiotic resistance: it’s bad, but why isn’t it worse? BMC Biol. https://doi.org/10.1186/s12915-017-0423-1 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
49.Ebmeyer, S., Erik, K. & Larsson, D. G. J. A framework for identifying the recent origins of mobile antibiotic resistance genes. Commun. Biol. https://doi.org/10.1038/s42003-020-01545-5 (2021). This study amends, summarizes and scrutinizes current evidence for proposed recent origin species for mobile ARGs.Article 
PubMed 
PubMed Central 

Google Scholar 
50.Andersson, D. I. & Hughes, D. Persistence of antibiotic resistance in bacterial populations. FEMS Microbiol. Rev. 35, 901–911 (2011).CAS 
PubMed 

Google Scholar 
51.Wang, J., Chu, L., Wojnárovits, L. & Takács, E. Occurrence and fate of antibiotics, antibiotic resistant genes (ARGs) and antibiotic resistant bacteria (ARB) in municipal wastewater treatment plant: an overview. Sci. Total. Environ. 744, 140997 (2020).CAS 
PubMed 

Google Scholar 
52.Tran, N. H., Reinhard, M. & Gin, K. Y.-H. Occurrence and fate of emerging contaminants in municipal wastewater treatment plants from different geographical regions-a review. Water Res. 133, 182–207 (2018).CAS 
PubMed 

Google Scholar 
53.Szymańska, U. et al. Presence of antibiotics in the aquatic environment in Europe and their analytical monitoring: recent trends and perspectives. Microchem. J. 147, 729–740 (2019).
Google Scholar 
54.Anwar, M., Iqbal, Q. & Saleem, F. Improper disposal of unused antibiotics: an often overlooked driver of antimicrobial resistance. Expert Rev. Antiinfect Ther. https://doi.org/10.1080/14787210.2020.1754797 (2020).Article 

Google Scholar 
55.Cabello, F. C. et al. Antimicrobial use in aquaculture re-examined: its relevance to antimicrobial resistance and to animal and human health. Environ. Microbiol. 15, 1917–1942 (2013).PubMed 

Google Scholar 
56.Cabello, F. C., Godfrey, H. P., Buschmann, A. H. & Dölz, H. J. Aquaculture as yet another environmental gateway to the development and globalisation of antimicrobial resistance. Lancet Infect. Dis. 16, e127–e133 (2016).PubMed 

Google Scholar 
57.Taylor, P. & Reeder, R. Antibiotic use on crops in low and middle-income countries based on recommendations made by agricultural advisors. CABI Agric. Biosci. https://doi.org/10.1186/s43170-020-00001-y (2020).Article 

Google Scholar 
58.Larsson, D. G. J. Pollution from drug manufacturing: review and perspectives. Philos. Trans. R. Soc. B Biol. Sci. 369, 20130571 (2014).
Google Scholar 
59.Larsson, D. G. J., De Pedro, C. & Paxeus, N. Effluent from drug manufactures contains extremely high levels of pharmaceuticals. J. Hazard. Mater. 148, 751–755 (2007).CAS 
PubMed 

Google Scholar 
60.Milaković, M. et al. Pollution from azithromycin-manufacturing promotes macrolide-resistance gene propagation and induces spatial and seasonal bacterial community shifts in receiving river sediments. Environ. Int. 123, 501–511 (2019).PubMed 

Google Scholar 
61.Bielen, A. et al. Negative environmental impacts of antibiotic-contaminated effluents from pharmaceutical industries. Water Res. 126, 79–87 (2017).CAS 
PubMed 

Google Scholar 
62.Fick, J. et al. Contamination of surface, ground, and drinking water from pharmaceutical production. Environ. Toxicol. Chem. 28, 2522–2527 (2009).CAS 
PubMed 

Google Scholar 
63.Bengtsson-Palme, J. & Larsson, D. G. J. Concentrations of antibiotics predicted to select for resistant bacteria: proposed limits for environmental regulation. Environ. Int. 86, 140–149 (2016). This study uses a simplified approach based on available MIC data for many species to predict concentrations of 111 antibiotics that are not likely to select for resistance.CAS 
PubMed 

Google Scholar 
64.Gullberg, E. et al. Selection of resistant bacteria at very low antibiotic concentrations. PLoS Pathog. 7, e1002158 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
65.Karkman, A., Pärnänen, K. & Larsson, D. G. J. Fecal pollution can explain antibiotic resistance gene abundances in anthropogenically impacted environments. Nat. Commun. https://doi.org/10.1038/s41467-018-07992-3 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
66.Yang, Y., Li, B., Zou, S., Fang, H. H. P. & Zhang, T. Fate of antibiotic resistance genes in sewage treatment plant revealed by metagenomic approach. Water Res. 62, 97–106 (2014).CAS 
PubMed 

Google Scholar 
67.Bengtsson-Palme, J. et al. Elucidating selection processes for antibiotic resistance in sewage treatment plants using metagenomics. Sci. Total Environ. 572, 697–712 (2016).CAS 
PubMed 

Google Scholar 
68.Manaia, C. M. et al. Antibiotic resistance in wastewater treatment plants: tackling the black box. Environ. Int. 115, 312–324 (2018).CAS 
PubMed 

Google Scholar 
69.Flach, C. F., Genheden, M., Fick, J. & Joakim Larsson, D. G. A comprehensive screening of Escherichia coli isolates from Scandinavia’s largest sewage treatment plant indicates no selection for antibiotic resistance. Environ. Sci. Technol. 52, 11419–11428 (2018).CAS 
PubMed 

Google Scholar 
70.Kraupner, N. et al. Evidence for selection of multi-resistant E. coli by hospital effluent. Environ. Int. 150, 106436 (2021).CAS 
PubMed 

Google Scholar 
71.Flach, C. F. et al. Isolation of novel IncA/C and IncN fluoroquinolone resistance plasmids from an antibiotic-polluted lake. J. Antimicrob. Chemother. 70, 2709–2717 (2015).CAS 
PubMed 

Google Scholar 
72.Bengtsson-Palme, J., Boulund, F., Fick, J., Kristiansson, E. & Larsson, D. G. J. Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Front. Microbiol. https://doi.org/10.3389/fmicb.2014.00648 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
73.Marathe, N. P. et al. Functional metagenomics reveals a novel carbapenem-hydrolyzing mobile beta-lactamase from Indian river sediments contaminated with antibiotic production waste. Environ. Int. 112, 279–286 (2018).CAS 
PubMed 

Google Scholar 
74.Thiele-Bruhn, S. Pharmaceutical antibiotic compounds in soils–a review. J. Plant Nutr. Soil Sci. 166, 145–167 (2003).CAS 

Google Scholar 
75.Li, W., Shi, Y., Gao, L., Liu, J. & Cai, Y. Occurrence, distribution and potential affecting factors of antibiotics in sewage sludge of wastewater treatment plants in China. Sci. Total. Environ. 445–446, 306–313 (2013).PubMed 

Google Scholar 
76.Reinthaler, F. F. et al. Resistance patterns of Escherichia coli isolated from sewage sludge in comparison with those isolated from human patients in 2000 and 2009. J. Water Health 11, 13–20 (2013).PubMed 

Google Scholar 
77.Rutgersson, C. et al. Long-term application of Swedish sewage sludge on farmland does not cause clear changes in the soil bacterial resistome. Environ. Int. 137, 105339 (2020).CAS 
PubMed 

Google Scholar 
78.Jechalke, S., Heuer, H., Siemens, J., Amelung, W. & Smalla, K. Fate and effects of veterinary antibiotics in soil. Trends Microbiol. 22, 536–545 (2014).CAS 
PubMed 

Google Scholar 
79.Boxall, A. B. et al. Pharmaceuticals and personal care products in the environment: what are the big questions? Environ. Health Perspect. 120, 1221–1229 (2012).PubMed 
PubMed Central 

Google Scholar 
80.Song, J., Rensing, C., Holm, P. E., Virta, M. & Brandt, K. K. Comparison of metals and tetracycline as selective agents for development of tetracycline resistant bacterial communities in agricultural soil. Environ. Sci. Technol. 51, 3040–3047 (2017).CAS 
PubMed 

Google Scholar 
81.Jechalke, S. et al. Plasmid-mediated fitness advantage of Acinetobacter baylyi in sulfadiazine-polluted soil. FEMS Microbiol. Lett. 348, 127–132 (2013). This study shows that a commonly used antibiotic in pig farming has the potential to select for a resistant Acinetobacter strain in manure-amended soils.CAS 
PubMed 

Google Scholar 
82.Pal, C. et al. Metal resistance and its association with antibiotic resistance. Adv. Microb. Physiol. 70, 261–313 (2017).CAS 
PubMed 

Google Scholar 
83.Wales, A. & Davies, R. Co-selection of resistance to antibiotics, biocides and heavy metals, and its relevance to foodborne pathogens. Antibiotics 4, 567–604 (2015).PubMed 
PubMed Central 

Google Scholar 
84.Pal, C., Bengtsson-Palme, J., Kristiansson, E. & Larsson, D. G. J. Co-occurrence of resistance genes to antibiotics, biocides and metals reveals novel insights into their co-selection potential. BMC Genomics https://doi.org/10.1186/s12864-015-2153-5 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
85.Klümper, U. et al. Metal stressors consistently modulate bacterial conjugal plasmid uptake potential in a phylogenetically conserved manner. ISME J. 11, 152–165 (2017).PubMed 

Google Scholar 
86.Jutkina, J., Rutgersson, C., Flach, C. F. & Joakim Larsson, D. G. An assay for determining minimal concentrations of antibiotics that drive horizontal transfer of resistance. Sci. Total. Environ. 548–549, 131–138 (2016).PubMed 

Google Scholar 
87.Wang, Y. et al. Non-antibiotic pharmaceuticals enhance the transmission of exogenous antibiotic resistance genes through bacterial transformation. ISME J. 14, 2179–2196 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
88.Klumper, U. et al. Broad host range plasmids can invade an unexpectedly diverse fraction of a soil bacterial community. ISME J. 9, 934–945 (2015). This study shows that plasmids that are common in pathogens can easily be taken up by diverse environmental bacteria, thereby providing pathways for the exchange of resistance genes.CAS 
PubMed 

Google Scholar 
89.Gillings, M. R., Paulsen, I. T. & Tetu, S. G. Genomics and the evolution of antibiotic resistance. Ann. N. Y. Acad. Sci. 1388, 92–107 (2017).PubMed 

Google Scholar 
90.Heuer, H. & Smalla, K. Plasmids foster diversification and adaptation of bacterial populations in soil. FEMS Microbiol. Rev. 36, 1083–1104 (2012).CAS 
PubMed 

Google Scholar 
91.Bengtsson-Palme, J. & Larsson, D. G. Antibiotic resistance genes in the environment: prioritizing risks. Nat. Rev. Microbiol. 13, 396 (2015).CAS 
PubMed 

Google Scholar 
92.Leonard, A. F. C. et al. Exposure to and colonisation by antibiotic-resistant E. coli in UK coastal water users: environmental surveillance, exposure assessment, and epidemiological study (Beach Bum Survey). Environ. Int. 114, 326–333 (2018). This is one of few studies showing that people more likely to ingest surface waters are also more prone to be carriers of resistant bacteria compared with matched controls.PubMed 

Google Scholar 
93.Manaia, C. M. Assessing the risk of antibiotic resistance transmission from the environment to humans: non-direct proportionality between abundance and risk. Trends Microbiol. 25, 173–181 (2017).CAS 
PubMed 

Google Scholar 
94.Schijven, J. F., Blaak, H., Schets, F. M. & De Roda Husman, A. M. Fate of extended-spectrum β-lactamase-producing Escherichia coli from faecal sources in surface water and probability of human exposure through swimming. Environ. Sci. Technol. 49, 11825–11833 (2015).CAS 
PubMed 

Google Scholar 
95.Collignon, P., Beggs, J. J., Walsh, T. R., Gandra, S. & Laxminarayan, R. Anthropological and socioeconomic factors contributing to global antimicrobial resistance: a univariate and multivariable analysis. Lancet Planet. Health 2, e398–e405 (2018).PubMed 

Google Scholar 
96.Dancer, S. J. Controlling hospital-acquired infection: focus on the role of the environment and new technologies for decontamination. Clin. Microbiol. Rev. 27, 665–690 (2014).PubMed 
PubMed Central 

Google Scholar 
97.Weber, D. J., Anderson, D. & Rutala, W. A. The role of the surface environment in healthcare-associated infections. Curr. Opin. Infect. Dis. 26, 338–344 (2013).PubMed 

Google Scholar 
98.Søraas, A., Sundsfjord, A., Sandven, I., Brunborg, C. & Jenum, P. A. Risk factors for community-acquired urinary tract infections caused by ESBL-producing Enterobacteriaceae –a case–control study in a low prevalence country. PLoS ONE 8, e69581 (2013).PubMed 
PubMed Central 

Google Scholar 
99.Zhou, S.-Y.-D. et al. Prevalence of antibiotic resistome in ready-to-eat salad. Front. Public Health https://doi.org/10.3389/fpubh.2020.00092 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
100.Uyttendaele, M. et al. Microbial hazards in irrigation water: standards, norms, and testing to manage use of water in fresh produce primary production. Compr. Rev. Food Sci. Food Saf. 14, 336–356 (2015).
Google Scholar 
101.Reid, C. J., Blau, K., Jechalke, S., Smalla, K. & Djordjevic, S. P. Whole genome sequencing of Escherichia coli from store-bought produce. Front. Microbiol. 10, 3050 (2020).PubMed 
PubMed Central 

Google Scholar 
102.Blau, K. et al. The transferable resistome of produce. mBio 9, e01300-18 (2018).PubMed 
PubMed Central 

Google Scholar 
103.Zhu, Y.-G. et al. Soil biota, antimicrobial resistance and planetary health. Environ. Int. 131, 105059 (2019).PubMed 

Google Scholar 
104.Pal, C., Bengtsson-Palme, J., Kristiansson, E. & Larsson, D. G. J. The structure and diversity of human, animal and environmental resistomes. Microbiome 4, 54 (2016).PubMed 
PubMed Central 

Google Scholar 
105.Kozajda, A., Jeżak, K. & Kapsa, A. Airborne Staphylococcus aureus in different environments — a review. Environ. Sci. Pollut. Res. 26, 34741–34753 (2019).CAS 

Google Scholar 
106.Ashbolt, N. J. et al. Human health risk assessment (HHRA) for environmental development and transfer of antibiotic resistance. Environ. Health Perspect. 121, 993–1001 (2013).PubMed 
PubMed Central 

Google Scholar 
107.Franz, E., Schijven, J., De Roda Husman, A. M. & Blaak, H. Meta-regression analysis of commensal and pathogenic Escherichia coli survival in soil and water. Environ. Sci. Technol. 48, 6763–6771 (2014).CAS 
PubMed 

Google Scholar 
108.Lewis, K. Platforms for antibiotic discovery. Nat. Rev. Drug. Discov. 12, 371–387 (2013).CAS 
PubMed 

Google Scholar 
109.Linton, K. B., Richmond, M. H., Bevan, R. & Gillespie, W. A. Antibiotic resistance and R factors in coliform bacilli isolated from hospital and domestic sewage. J. Med. Microbiol. 7, 91–103 (1974).CAS 
PubMed 

Google Scholar 
110.Huijbers, P., Joakim Larsson, D. G. & Flach, C. F. Surveillance of antibiotic resistant Escherichia coli in human populations through urban wastewater in ten European countries. Environ. Pollut. 261, 114200 (2020).CAS 
PubMed 

Google Scholar 
111.Hutinel, M. et al. Population-level surveillance of antibiotic resistance in Escherichia coli through sewage analysis. Euro Surveill. https://doi.org/10.2807/1560-7917.es.2019.24.37.1800497 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
112.Aarestrup, F. M. & Woolhouse, M. E. J. Using sewage for surveillance of antimicrobial resistance. Science 367, 630–632 (2020).CAS 
PubMed 

Google Scholar 
113.Kwak, Y. K. et al. Surveillance of antimicrobial resistance among Escherichia coli in wastewater in Stockholm during 1 year: does it reflect the resistance trends in the society? Int. J. Antimicrob. Agents 45, 25–32 (2015).CAS 
PubMed 

Google Scholar 
114.Parnanen, K. M. M. et al. Antibiotic resistance in European wastewater treatment plants mirrors the pattern of clinical antibiotic resistance prevalence. Sci. Adv. 5, eaau9124 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
115.Hendriksen, R. S. et al. Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage. Nat. Commun. 10, 1124 (2019). This is the most comprehensive survey of ARGs in sewage across the world to date, showing distinct differences between regions.PubMed 
PubMed Central 

Google Scholar 
116.Huijbers, P. M. C., Flach, C. F. & Larsson, D. G. J. A conceptual framework for the environmental surveillance of antibiotics and antibiotic resistance. Environ. Int. 130, 104880 (2019).CAS 
PubMed 

Google Scholar 
117.Böhm, M.-E., Razavi, M., Marathe, N. P., Flach, C.-F. & Larsson, D. G. J. Discovery of a novel integron-borne aminoglycoside resistance gene present in clinical pathogens by screening environmental bacterial communities. Microbiome https://doi.org/10.1186/s40168-020-00814-z (2020). Using a functional assay targeting mobile genes, this study explores environment communities and finds a completely novel resistance gene that had escaped discovery in clinics despite its presence in pathogens on different continents.Article 
PubMed 
PubMed Central 

Google Scholar 
118.Flach, C.-F., Hutinel, M., Razavi, M., Åhrén, C. & Larsson, D. G. J. Monitoring of hospital sewage shows both promise and limitations as an early-warning system for carbapenemase-producing Enterobacterales in a low-prevalence setting. Water Res. 200, 117261 (2021).CAS 
PubMed 

Google Scholar 
119.Karkman, A., Berglund, F., Flach, C.-F., Kristiansson, E. & Larsson, D. G. J. Predicting clinical resistance prevalence using sewage metagenomic data. Commun. Biol. https://doi.org/10.1038/s42003-020-01439-6 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
120.European Centre for Disease Prevention and Control. Surveillance of antimicrobial resistance in Europe 2017 (Stockholm, Sweden, 2018).121.Hovi, T. et al. Role of environmental poliovirus surveillance in global polio eradication and beyond. Epidemiol. Infect. 140, 1–13 (2012).CAS 
PubMed 

Google Scholar 
122.Agrawal, S., Orschler, L. & Lackner, S. Long-term monitoring of SARS-CoV-2 RNA in wastewater of the Frankfurt metropolitan area in southern Germany. Sci. Rep. https://doi.org/10.1038/s41598-021-84914-2 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
123.Medema, G., Heijnen, L., Elsinga, G., Italiaander, R. & Brouwer, A. Presence of SARS-coronavirus-2 RNA in sewage and correlation with reported COVID-19 prevalence in the early stage of the epidemic in the Netherlands. Environ. Sci. Technol. Lett. 7, 511–516 (2020).CAS 

Google Scholar 
124.Lundstrom, S. V. et al. Minimal selective concentrations of tetracycline in complex aquatic bacterial biofilms. Sci. Total Environ. 553, 587–595 (2016).PubMed 

Google Scholar 
125.McCann, C. M. et al. Understanding drivers of antibiotic resistance genes in High Arctic soil ecosystems. Environ. Int. 125, 497–504 (2019).CAS 
PubMed 

Google Scholar 
126.Pruden, A., Arabi, M. & Storteboom, H. N. Correlation between upstream human activities and riverine antibiotic resistance genes. Environ. Sci. Technol. 46, 11541–11549 (2012).CAS 
PubMed 

Google Scholar 
127.Zhu, Y.-G. et al. Continental-scale pollution of estuaries with antibiotic resistance genes. Nat. Microbiol. 2, 16270 (2017).CAS 
PubMed 

Google Scholar 
128.Zhu, Y.-G. et al. Diverse and abundant antibiotic resistance genes in Chinese swine farms. Proc. Natl Acad. Sci. USA 110, 3435–3440 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
129.Knapp, C. W., Dolfing, J., Ehlert, P. A. I. & Graham, D. W. Evidence of increasing antibiotic resistance gene abundances in archived soils since 1940. Environ. Sci. Technol. 44, 580–587 (2010).CAS 
PubMed 

Google Scholar 
130.Nesme, J. & Simonet, P. The soil resistome: a critical review on antibiotic resistance origins, ecology and dissemination potential in telluric bacteria. Environ. Microbiol. 17, 913–930 (2015).PubMed 

Google Scholar 
131.Finley, R. L. et al. The scourge of antibiotic resistance: the important role of the environment. Clin. Infect. Dis. 57, 704–710 (2013).PubMed 

Google Scholar 
132.Sjölund, M. et al. Dissemination of multidrug-resistant bacteria into the Arctic. Emerg. Infect. Dis. 14, 70–72 (2008).PubMed 
PubMed Central 

Google Scholar 
133.Zhu, G. et al. Air pollution could drive global dissemination of antibiotic resistance genes. ISME J. https://doi.org/10.1038/s41396-020-00780-2 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
134.Nichols, D. et al. Use of Ichip for high-throughput in situ cultivation of “Uncultivable” microbial species. Appl. Environ. Microbiol. 76, 2445–2450 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
135.Ashton, P. M. et al. MinION nanopore sequencing identifies the position and structure of a bacterial antibiotic resistance island. Nat. Biotechnol. 33, 296–300 (2015).CAS 
PubMed 

Google Scholar 
136.Spencer, S. J. et al. Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers. ISME J. 10, 427–436 (2016).CAS 
PubMed 

Google Scholar 
137.Rice, E. W., Wang, P., Smith, A. L. & Stadler, L. B. Determining hosts of antibiotic resistance genes: a review of methodological advances. Environ. Sci. Technol. Lett. 7, 282–291 (2020).CAS 

Google Scholar 
138.Sivalingam, P., Poté, J. & Prabakar, K. Extracellular DNA (eDNA): neglected and potential sources of antibiotic resistant genes (ARGs) in the aquatic environments. Pathogens 9, 874 (2020).CAS 
PubMed Central 

Google Scholar 
139.Bengtsson-Palme, J., Larsson, D. G. J. & Kristiansson, E. Using metagenomics to investigate human and environmental resistomes. J. Antimicrob. Chemother. 72, 2690–2703 (2017).CAS 
PubMed 

Google Scholar 
140.Karkman, A. et al. High-throughput quantification of antibiotic resistance genes from an urban wastewater treatment plant. FEMS Microbiol. Ecol. 92, https://doi.org/10.1093/femsec/fiw014 (2016).141.Gillings, M. R. et al. Using the class 1 integron-integrase gene as a proxy for anthropogenic pollution. ISME J. 9, 1269–1279 (2015).CAS 
PubMed 

Google Scholar 
142.Gaze, W. H., Abdouslam, N., Hawkey, P. M. & Wellington, E. M. H. Incidence of Class 1 integrons in a quaternary ammonium compound-polluted environment. Antimicrob. Agents Chemother. 49, 1802–1807 (2005).CAS 
PubMed 
PubMed Central 

Google Scholar 
143.Sommer, M. O. A., Munck, C., Toft-Kehler, R. V. & Andersson, D. I. Prediction of antibiotic resistance: time for a new preclinical paradigm? Nat. Rev. Microbiol. 15, 689–696 (2017). This article highlights the needs to consider the environmental gene reservoir and other factors influencing resistance evolution in the development process for new antibiotics.CAS 
PubMed 

Google Scholar 
144.Pehrsson, E. C., Forsberg, K. J., Gibson, M. K., Ahmadi, S. & Dantas, G. Novel resistance functions uncovered using functional metagenomic investigations of resistance reservoirs. Front. Microbiol. https://doi.org/10.3389/fmicb.2013.00145 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
145.Kim, C., Ryu, H.-D., Chung, E. G., Kim, Y. & Lee, J.-K. A review of analytical procedures for the simultaneous determination of medically important veterinary antibiotics in environmental water: sample preparation, liquid chromatography, and mass spectrometry. J. Environ. Manag. 217, 629–645 (2018).CAS 

Google Scholar 
146.Fahrenfeld, N. & Bisceglia, K. J. Emerging investigators series: sewer surveillance for monitoring antibiotic use and prevalence of antibiotic resistance: urban sewer epidemiology. Environ. Sci. Water Res. Technol. 2, 788–799 (2016).CAS 

Google Scholar 
147.Anliker, S. et al. Assessing emissions from pharmaceutical manufacturing based on temporal high-resolution mass spectrometry data. Environ. Sci. Technol. 54, 4110–4120 (2020). This recent study elegantly uses the erratic emission profiles of drugs from manufacturing plants to attribute a large portion of the pharmaceutical residues found in a Swiss river to industrial emissions, further showing that curbing such pollution is an ongoing, worldwide challenge.CAS 
PubMed 

Google Scholar 
148.Klümper, U. et al. Selection for antimicrobial resistance is reduced when embedded in a natural microbial community. ISME J. 13, 2927–2937 (2019).PubMed 
PubMed Central 

Google Scholar 
149.Kraupner, N. et al. Selective concentrations for trimethoprim resistance in aquatic environments. Environ. Int. 144, 106083 (2020).CAS 
PubMed 

Google Scholar 
150.Murray, A. K. et al. Novel insights into selection for antibiotic resistance in complex microbial communities. mBio https://doi.org/10.1128/mbio.00969-18 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
151.Government of India. Environment (Protection) Amendment Rules, 2020 – Inviting comments/suggestions on Environmental Standards for Bulk Drug and Formulation (Pharmaceutical) Industry, http://moef.gov.in/g-s-r-44-e-date-23-01-2020-environment-protection-amendment-rules-2020-inviting-commentssuggestions-on-environmental-standards-for-bulk-drug-and-formulation-pharmaceutical-indu/ (2020).152.Tell, J. et al. Science-based targets for antibiotics in receiving waters from pharmaceutical manufacturing operations. Integr. Environ. Assess. Manag. 15, 312–319 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
153.Greenfield, B. K. et al. Modeling the emergence of antibiotic resistance in the environment: an analytical solution for the minimum selection concentration. Antimicrob. Agents Chemother. https://doi.org/10.1128/aac.01686-17 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
154.Murray, A. K. et al. The ‘Selection end points in Communities of bacTeria’ (SELECT) method: a novel experimental assay to facilitate risk assessment of selection for antimicrobial resistance in the environment. Environ. Health Perspect. 128, 107007 (2020).PubMed 
PubMed Central 

Google Scholar 
155.Andersson, D. I. & Hughes, D. Antibiotic resistance and its cost: is it possible to reverse resistance? Nat. Rev. Microbiol. 8, 260–271 (2010).CAS 
PubMed 

Google Scholar 
156.Stanton, I. C., Murray, A. K., Zhang, L., Snape, J. & Gaze, W. H. Evolution of antibiotic resistance at low antibiotic concentrations including selection below the minimal selective concentration. Commun. Biol. https://doi.org/10.1038/s42003-020-01176-w (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
157.Nijsingh, N., Munthe, C. & Larsson, D. G. J. Managing pollution from antibiotics manufacturing: charting actors, incentives and disincentives. Environ. Health 18, 95 (2019).PubMed 
PubMed Central 

Google Scholar 
158.Sundin, G. W. & Wang, N. Antibiotic resistance in plant-pathogenic bacteria. Annu. Rev. Phytopathol. 56, 161–180 (2018).CAS 
PubMed 

Google Scholar 
159.Government of Sweden. Uppdrag angående försöksverksamhet för en miljöpremie i läkemedelsförmånssystemet, https://www.regeringen.se/499677/contentassets/36dcec65be904fd58e5e6b01c2f99709/uppdrag-angaende-forsoksverksamhet-for-en-miljopremie-i-lakemedelsformanssystemet-tlv.pdf (2021).160.Norwegian Hospital Procurement Trust. New environmental criteria for the procurement of pharmaceuticals, https://sykehusinnkjop.no/nyheter/new-environmental-criteria-for-the-procurement-of-pharmaceuticals (2019).161.Swedish Procurement Agency. Pharmaceuticals, https://www.upphandlingsmyndigheten.se/kriterier/sjukvard-och-omsorg/lakemedel/ (2021).162.G7. G7 Health Ministers’ Declaration, Oxford, 4 June 2021, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/992268/G7-health_ministers-communique-oxford-4-june-2021_5.pdf (2021).163.Årdal, C. et al. Supply chain transparency and the availability of essential medicines. Bull. World Health Organ. 99, 319–320 (2021).PubMed 
PubMed Central 

Google Scholar 
164.Graham, D., Giesen, M. & Bunce, J. Strategic approach for prioritising local and regional sanitation interventions for reducing global antibiotic resistance. Water 11, 27 (2018).
Google Scholar 
165.Margot, J. et al. Treatment of micropollutants in municipal wastewater: ozone or powdered activated carbon? Sci. Total. Environ. 461–462, 480–498 (2013).PubMed 

Google Scholar 
166.Larsson, D. G. J. et al. Critical knowledge gaps and research needs related to the environmental dimensions of antibiotic resistance. Environ. Int. 117, 132–138 (2018).PubMed 

Google Scholar 
167.Laxminarayan, R. et al. The Lancet Infectious Diseases Commission on antimicrobial resistance: 6 years later. Lancet Infect. Dis. 20, e51–e60 (2020).PubMed 

Google Scholar 
168.Ahammad, Z. S., Sreekrishnan, T. R., Hands, C. L., Knapp, C. W. & Graham, D. W. Increased waterborne blaNDM-1 resistance gene abundances associated with seasonal human pilgrimages to the upper Ganges River. Environ. Sci. Technol. 48, 3014–3020 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
169.Kookana, R. S. et al. Potential ecological footprints of active pharmaceutical ingredients: an examination of risk factors in low-, middle- and high-income countries. Philos. Trans. R. Soc. B Biol. Sci. 369, 20130586 (2014).
Google Scholar  More

1.Becoming #GenerationRestoration: Ecosystem Restoration for People, Nature and Climate (United Nations Environment Programme, 2021).2.Bongers, F. J. et al. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-021-01564-3 (2021).Article 

Google Scholar 
3.Reich, P. B. et al. Science 336, 589–592 (2012).CAS 
Article 

Google Scholar 
4.Guerrero-Ramírez, N. R. et al. Nat. Ecol. Evol. 1, 1639–1642 (2017).Article 

Google Scholar 
5.Fargione, J. et al. Proc. R. Soc. B 274, 871–876 (2007).Article 

Google Scholar 
6.Montagnini, F. & Piotto, D. In Silviculture in the Tropics (eds Günter, S. et al.) 501–511 (Springer-Verlag, 2011).7.Aerts, R. & Honnay, O. BMC Ecol. 11, 29 (2011).Article 

Google Scholar 
8.Messier, C. et al. Conserv. Lett. https://doi.org/gk82nr (2021).9.Sacco, A. D. et al. Global Change Biol. 27, 1328–1348 (2021).Article 

Google Scholar 
10.Coleman, E. A. et al. Nat. Sustain. https://doi.org/gzhx (2021).11.Forrester, D. I. For. Ecol. Manage. 312, 282–292 (2014).Article 

Google Scholar 
12.Eisenhauer, N., Reich, P. B. & Scheu, S. Basic Appl. Ecol. 13, 571–578 (2012).Article 

Google Scholar 
13.Zemp, D. C. et al. Agric. Ecosyst. Environ. 283, 106564 (2019).Article 

Google Scholar 
14.Laughlin, D. C. et al. Nat. Ecol. Evol. 5, 1123–1134 (2021).Article 

Google Scholar 
15.Rodrigues, R. R. et al. Práticas de restauração nos diferentes biomas brasileiros. in BPBES/IIS: Relatório Temático sobre Restauração de Paisagens e Ecossistemas (eds. Crouzeilles, R. et al.) (Editora Cubo, 2019). More

1.Global Assessment Report on Biodiversity and Ecosystem Services (IPBES, 2019).2.Bastin, J. F. et al. The global tree restoration potential. Science 366, 76–79 (2019).
Google Scholar 
3.Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
4.Zhang, J., Fu, B., Stafford-smith, M., Wang, S. & Zhao, W. Improve forest restoration initiatives to meet Sustainable Development Goal 15. Nat. Ecol. Evol. 5, 10–13 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
5.Holl, K. D. & Brancalion, P. H. S. Tree planting is not a simple solution. Science 368, 580–581 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
6.Lewis, S. L., Wheeler, C. E., Mitchard, E. T. A. & Koch, A. Restoring natural forests is the best way to remove atmospheric carbon. Nature 568, 25–28 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
7.Messier, C. et al. For the sake of resilience and multifunctionality, let’s diversify planted forests! Conserv. Lett. https://doi.org/10.1111/conl.12829 (2021).8.Baeten, L. et al. Identifying the tree species compositions that maximize ecosystem functioning in European forests. J. Appl. Ecol. 56, 733–744 (2019).
Google Scholar 
9.Schuldt, A. et al. Biodiversity across trophic levels drives multifunctionality in highly diverse forests. Nat. Commun. 9, 2989 (2018).PubMed 
PubMed Central 

Google Scholar 
10.Eisenhauer, N. et al. A multitrophic perspective on biodiversity–ecosystem functioning research. Adv. Ecol. Res. 61, 1–54 (2019).PubMed 
PubMed Central 

Google Scholar 
11.Isbell, F. et al. High plant diversity is needed to maintain ecosystem services. Nature 477, 199–202 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
12.Huang, Y. et al. Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362, 80–83 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
13.Liu, X. et al. Tree species richness increases ecosystem carbon storage in subtropical forests. Proc. R. Soc. B 285, 20181240 (2018).PubMed 
PubMed Central 

Google Scholar 
14.Tobner, C. M. et al. Functional identity is the main driver of diversity effects in young tree communities. Ecol. Lett. 19, 638–647 (2016).PubMed 
PubMed Central 

Google Scholar 
15.Van de Peer, T., Verheyen, K., Ponette, Q., Setiawan, N. N. & Muys, B. Overyielding in young tree plantations is driven by local complementarity and selection effects related to shade tolerance. J. Ecol. 106, 1096–1105 (2018).
Google Scholar 
16.Staples, T. L., Dwyer, J. M., England, J. R. & Mayfield, M. M. Productivity does not correlate with species and functional diversity in Australian reforestation plantings across a wide climate gradient. Glob. Ecol. Biogeogr. 28, 1417–1429 (2019).
Google Scholar 
17.Cheesman, A. W., Preece, N. D., van Oosterzee, P., Erskine, P. D. & Cernusak, L. A. The role of topography and plant functional traits in determining tropical reforestation success. J. Appl. Ecol. 55, 1029–1039 (2018).CAS 

Google Scholar 
18.Ma, L. et al. Species identity and composition effects on community productivity in a subtropical forest. Basic Appl. Ecol. 55, 87–97 (2021).
Google Scholar 
19.Gross, N. et al. Functional trait diversity maximizes ecosystem multifunctionality. Nat. Ecol. Evol. 1, 0132 (2017)..20.Violle, C. et al. The return of the variance: intraspecific variability in community ecology. Trends Ecol. Evol. 27, 244–252 (2012).PubMed 
PubMed Central 

Google Scholar 
21.Diaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
22.Diaz, S. et al. Incorporating plant functional diversity effects in ecosystem service assessments. Proc. Natl Acad. Sci. USA 104, 20684–20689 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
23.Bruelheide, H. et al. Global trait— environment relationships of plant communities. Nat. Ecol. Evol. 2, 1906–1917 (2018).PubMed 
PubMed Central 

Google Scholar 
24.van der Plas, F. et al. Plant traits alone are poor predictors of ecosystem properties and long-term ecosystem functioning. Nat. Ecol. Evol. 4, 1602–1611 (2020).PubMed 
PubMed Central 

Google Scholar 
25.Grime, J. P. Benefits of plant diversity to ecosystems: immediate, filter and founder effects. J. Ecol. 86, 902–910 (1998).
Google Scholar 
26.Chiang, J. M. et al. Functional composition drives ecosystem function through multiple mechanisms in a broadleaved subtropical forest. Oecologia 182, 829–840 (2016).PubMed 
PubMed Central 

Google Scholar 
27.Roscher, C. et al. Using plant functional traits to explain diversity–productivity relationships. PLoS ONE 7, e36760 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
28.Barry, K. E. et al. The future of complementarity: disentangling causes from consequences. Trends Ecol. Evol. 34, 167–180 (2019).PubMed 
PubMed Central 

Google Scholar 
29.Tilman, D., Lehman, C. L. & Thomson, K. T. Plant diversity and ecosystem productivity: theoretical considerations. Proc. Natl Acad. Sci. USA 94, 1857–1861 (1997).CAS 
PubMed 
PubMed Central 

Google Scholar 
30.Turnbull, L., Isbell, F., Purves, D. W., Loreau, M. & Hector, A. Understanding the value of plant diversity for ecosystem functioning through niche theory. Proc. R. Soc. B 283, 20160536 (2016).PubMed 
PubMed Central 

Google Scholar 
31.Salisbury, C. L. & Potvin, C. Does tree species composition affect productivity in a tropical planted forest? Biotropica 47, 559–568 (2015).
Google Scholar 
32.Bruelheide, H. et al. Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China. Methods Ecol. Evol. 5, 74–89 (2014).
Google Scholar 
33.Chen, Y. et al. Directed species loss reduces community productivity in a subtropical forest biodiversity experiment. Nat. Ecol. Evol. 4, 550–559 (2020).PubMed 
PubMed Central 

Google Scholar 
34.Laliberte, E. & Legendre, P. A distance-based framework for measuring functional diversity from multiple traits. Ecology 91, 299–305 (2010).PubMed 
PubMed Central 

Google Scholar 
35.Allan, E. et al. A comparison of the strength of biodiversity effects across multiple functions. Oecologia 173, 223–237 (2013).PubMed 
PubMed Central 

Google Scholar 
36.Luo, S. et al. Community-wide trait means and variations affect biomass in a biodiversity experiment with tree seedlings. Oikos 129, 799–810 (2020).
Google Scholar 
37.Lu, H., Mohren, G. M. J., den Ouden, J., Goudiaby, V. & Sterck, F. J. Overyielding of temperate mixed forests occurs in evergreen–deciduous but not in deciduous–deciduous species mixtures over time in the Netherlands. For. Ecol. Manag. 376, 321–332 (2016).
Google Scholar 
38.Toïgo, M. et al. Difference in shade tolerance drives the mixture effect on oak productivity. J. Ecol. 106, 1073–1082 (2018).
Google Scholar 
39.Forrester, D. I., Bauhus, J., Cowie, A. L. & Vanclay, J. K. Mixed-species plantations of Eucalyptus with nitrogen-fixing trees: a review. For. Ecol. Manag. 233, 211–230 (2006).
Google Scholar 
40.Montagnini, F. & Piotto, D. in Silviculture in the Tropics (eds Günter. S. et al.) 501–511 (Springer, 2011).41.Trogisch, S. et al. The significance of tree–tree interactions for forest ecosystem functioning. Basic Appl. Ecol. 55, 33–52 (2021).
Google Scholar 
42.Cardinale, B. J. et al. Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl Acad. Sci. USA 104, 18123–18128 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
43.Guerrero-Ramírez, N. R. et al. Diversity-dependent temporal divergence of ecosystem functioning in experimental ecosystems. Nat. Ecol. Evol. 1, 1639–1642 (2017).PubMed 
PubMed Central 

Google Scholar 
44.Kunz, M. et al. Neighbour species richness and local structural variability modulate aboveground allocation patterns and crown morphology of individual trees. Ecol. Lett. 22, 2130–2140 (2019).PubMed 
PubMed Central 

Google Scholar 
45.Reich, P. B. et al. Impacts of biodiversity loss escalate through time as redundancy fades. Science 336, 589–592 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
46.Martínez-Garza, C., Bongers, F. & Poorter, L. Are functional traits good predictors of species performance in restoration plantings in tropical abandoned pastures? For. Ecol. Manag. 303, 35–45 (2013).
Google Scholar 
47.Mayoral, C., van Breugel, M., Cerezo, A. & Hall, J. S. Survival and growth of five Neotropical timber species in monocultures and mixtures. For. Ecol. Manag. 403, 1–11 (2017).
Google Scholar 
48.Poorter, L. & Bongers, F. Leaf traits are good predictors of plant performance across 53 rain forest species. Ecology 87, 1733–1743 (2006).PubMed 
PubMed Central 

Google Scholar 
49.Ammer, C. Diversity and forest productivity in a changing climate. New Phytol. 221, 50–66 (2019).PubMed 
PubMed Central 

Google Scholar 
50.Brancalion, P. H. S. & Holl, K. D. Guidance for successful tree planting initiatives. J. Appl. Ecol. 57, 2349–2361 (2020).
Google Scholar 
51.Ruiz-Jaen, M. & Potvin, C. Can we predict carbon stocks in tropical ecosystems from tree diversity? Comparing species and functional diversity in a plantation and a natural forest. New Phytol. 189, 978–987 (2011).PubMed 
PubMed Central 

Google Scholar 
52.Grossman, J. J., Cavender-Bares, J., Hobbie, S. E., Reich, P. B. & Montgomery, R. A. Species richness and traits predict overyielding in stem growth in an early-successional tree diversity experiment. Ecology 98, 2601–2614 (2017).PubMed 
PubMed Central 

Google Scholar 
53.Kambach, S. et al. How do trees respond to species mixing in experimental compared to observational studies? Ecol. Evol. 9, 11254–11265 (2019).PubMed 
PubMed Central 

Google Scholar 
54.Finegan, B. et al. Does functional trait diversity predict above-ground biomass and productivity of tropical forests? Testing three alternative hypotheses. J. Ecol. 103, 191–201 (2015).
Google Scholar 
55.Piston, N. et al. Multidimensional ecological analyses demonstrate how interactions between functional traits shape fitness and life history strategies. J. Ecol. 107, 2317–2328 (2019).
Google Scholar 
56.McDowell, N. et al. Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought? New Phytol. 178, 719–739 (2008).PubMed 
PubMed Central 

Google Scholar 
57.O’Brien, M. J. et al. A synthesis of tree functional traits related to drought-induced mortality in forests across climatic zones. J. Appl. Ecol. 54, 1669–1686 (2017).
Google Scholar 
58.Freschet, G. T. et al. Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs. New Phytol. https://doi.org/10.1111/nph.17072 (2020).59.Jucker, T. et al. Good things take time—diversity effects on tree growth shift from negative to positive during stand development in boreal forests. J. Ecol. 108, 2198–2211 (2020).
Google Scholar 
60.McGill, B. J., Enquist, B. J., Weiher, E. & Westoby, M. Rebuilding community ecology from functional traits. Trends Ecol. Evol. 21, 178–185 (2006).PubMed 
PubMed Central 

Google Scholar 
61.Laughlin, D. C. The intrinsic dimensionality of plant traits and its relevance to community assembly. J. Ecol. 102, 186–193 (2014).
Google Scholar 
62.Fiedler, S., Perring, M. P. & Tietjen, B. Integrating trait-based empirical and modeling research to improve ecological restoration. Ecol. Evol. 8, 6369–6380 (2018).PubMed 
PubMed Central 

Google Scholar 
63.Zhang, Y., Chen, H. Y. H. & Reich, P. B. Forest productivity increases with evenness, species richness and trait variation: a global meta-analysis. J. Ecol. 100, 742–749 (2012).
Google Scholar 
64.Schnabel, F. et al. Drivers of productivity and its temporal stability in a tropical tree diversity experiment. Glob. Change Biol. 25, 4257–4272 (2019).
Google Scholar 
65.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).66.Krober, W., Zhang, S., Ehmig, M. & Bruelheide, H. Linking xylem hydraulic conductivity and vulnerability to the leaf economics spectrum—a cross-species study of 39 evergreen and deciduous broadleaved subtropical tree species. PLoS ONE 9, e109211 (2014).67.Eichenberg, D., Purschke, O., Ristok, C., Wessjohann, L. & Bruelheide, H. Trade-offs between physical and chemical carbon-based leaf defence: of intraspecific variation and trait evolution. J. Ecol. 103, 1667–1679 (2015).CAS 

Google Scholar 
68.Krober, W., Heklau, H. & Bruelheide, H. Leaf morphology of 40 evergreen and deciduous broadleaved subtropical tree species and relationships to functional ecophysiological traits. Plant Biol. 17, 373–383 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
69.Sokal, R. R. & Rohlf, F. J. Biometry (W.H. Freeman and Company, 1995).70.Schmid, B., Baruffol, M., Wang, Z. & Niklaus, P. A. A guide to analyzing biodiversity experiments. J. Plant Ecol. 10, 91–110 (2017).
Google Scholar  More

Etymology‘Candidatus Celerinatantimonas neptuna’ (nep.tu’na L. fem. n.), pertaining to Neptunus (L. masc. n. Neptune), the Roman god of the seas and the Neptune grass, Posidonia oceanica.SamplingA P. oceanica meadow at 8 m water depth and nearby sandy sediments in Fetovaia Bay, Elba, Italy13 were sampled between June 2014 and September 2019; individual sampling months and years are indicated in the sections below and/or in the figures and tables. In May 2017, a P. oceanica meadow at the island of Pianosa, Italy was also sampled. All of the samples were obtained via SCUBA diving.Complete plants of P. oceanica were carefully separated from the meadow by hand and stored in seawater-filled containers until arrival at the shore-based laboratory. Sediment for use in the laboratory-based aquaria was scooped into containers from nearby sandy patches. Seawater was pumped through a hose (placed at about 0.5 m above the P. oceanica meadow) into several 50 l barrels onboard the boat and was later used in the laboratory for the aquarium and the incubation experiments.The sediment within the seagrass meadow was sampled with stainless steel core tubes (length, 50 cm), which were drilled into the sediment by divers, and the cores were briefly stored at 22 °C (ambient temperature, September 2019) in a seawater-filled barrel until further processing at the shore-based laboratory.Porewater nutrient samples were obtained using stainless steel lances41 at intervals of around 10 cm. Water column nutrient samples were obtained from above the seagrass meadow at the start or end of sampling. Nutrient samples were collected in 15 ml or 50 ml centrifuge tubes and were stored in a cooler box until further processing.Nutrient measurementsWater column nutrients were measured during several sampling campaigns as indicated in Extended Data Table 1a. Ammonium (NH4+) concentrations were measured fluorometrically42 in the nearby shore-based laboratory, and the remaining water was frozen (−20 °C) for later analyses of nitrate (NO3−), nitrite (NO2−), phosphate (PO43−) and silicate (SiO44−) using an autoanalyser (QuAAtro, Seal Analytical). Porewater samples were obtained in June 2019 and were processed the same as the water column nutrient samples with the exception that ammonium was not measured on site but at the home laboratory at the same time as the other nutrients. Dissolved inorganic nitrogen (ammonium plus NOx−) concentrations in the porewater were averaged for the upper 20 cm (Extended Data Table 1b).Net primary production measurements using the EC methodNet carbon dioxide (CO2) fluxes were calculated on the basis of oxygen (O2) fluxes determined using the aquatic eddy covariance (EC) method. In this non-invasive approach, turbulence-induced transport is resolved using high-frequency current meters combined with fast O2 microsensors. Under the assumption of stationarity, the instantaneous turbulent flux contributions are calculated by correlating vertical current fluctuations to oxygen fluctuations. Our EC system was equipped with an acoustic Doppler velocimeter (ADV, Nortek) and ultra-fast responding optode microsensors with a tip diameter of 430 µm (t90  More

1.Enquist, B. J., Abraham, A. J., Harfoot, M. B. J., Malhi, Y. & Doughty, C. E. The megabiota are disproportionately important for biosphere functioning. Nat. Commun. 11, 699 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
2.Doughty, C. E. et al. Global nutrient transport in a world of giants. Proc. Natl Acad. Sci. USA 113, 868–873 (2016).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
3.Roman, J. & McCarthy, J. J. The whale pump: marine mammals enhance primary productivity in a coastal basin. PLoS ONE 5, e13255 (2010).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
4.Barlow, J., Kahru, M. & Mitchell, B. G. Cetacean biomass, prey consumption, and primary production requirements in the California Current ecosystem. Mar. Ecol. Prog. Ser. 371, 285–295 (2008).ADS 
Article 

Google Scholar 
5.Fortune, S. M. E., Trites, A. W., Mayo, C. A., Rosen, D. A. S. & Hamilton, P. K. Energetic requirements of North Atlantic right whales and the implications for species recovery. Mar. Ecol. Prog. Ser. 478, 253–272 (2013).ADS 
Article 

Google Scholar 
6.Trites, A. W., Christensen, V. & Pauly, D. Competition between fisheries and marine mammals for prey and primary production in the Pacific Ocean. J. Northwest Atl. Fish. Sci. 22, 173–187 (1997).Article 

Google Scholar 
7.Lavery, T. J. et al. Whales sustain fisheries: blue whales stimulate primary production in the Southern Ocean. Mar. Mammal Sci. 30, 888–904 (2014).CAS 
Article 

Google Scholar 
8.Croll, D. A., Kudela, R. & Tershy, B. R. in Whales, Whaling, and Ocean Ecosystems (eds. Estes, J. A. et al.) 202–214 (Univ. California Press, 2006).9.Smith, L. A., Link, J. S., Cadrin, S. X. & Palka, D. L. Consumption by marine mammals on the Northeast U.S. continental shelf. Ecol. Appl. 25, 373–389 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
10.Atkinson, A., Siegel, V., Pakhomov, E. A., Jessopp, M. J. & Loeb, V. A re-appraisal of the total biomass and annual production of Antarctic krill. Deep. Res. Part I Oceanogr. Res. Pap. 56, 727–740 (2009).ADS 
Article 

Google Scholar 
11.Pauly, D. & Zeller, D. Catch reconstructions reveal that global marine fisheries catches are higher than reported and declining. Nat. Commun. 7, 10244 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
12.Estes, J. A., Heithaus, M., McCauley, D. J., Rasher, D. B. & Worm, B. Megafaunal Impacts on Structure and Function of Ocean Ecosystems. Annu. Rev. Environ. Resour. 41, 83–116 (2016).Article 

Google Scholar 
13.Smetacek, V. in Impacts of Global Warming on Polar Ecosystems (ed. Duarte, C. M.) 46–80 (Fundacion BBVA, 2008).14.Wing, S. et al. Seabirds and marine mammals redistribute bioavailable iron in the Southern Ocean. Mar. Ecol. Prog. Ser. 510, 1–13 (2014).ADS 
Article 
CAS 

Google Scholar 
15.Nicol, S. et al. Southern Ocean iron fertilization by baleen whales and Antarctic krill. Fish Fish. 11, 203–209 (2010).Article 

Google Scholar 
16.Ripple, W. J., Wolf, C., Newsome, T. M., Hoffmann, M. & Wirsing, A. J. Extinction risk is most acute for the world’s largest and smallest vertebrates. Proc. Natl Acad. Sci. USA 114, 10678–10683 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
17.McCauley, D. J. et al. Marine defaunation: animal loss in the global ocean. Science 347, 1255641 (2015).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
18.Goldbogen, J. A. et al. How baleen whales feed: the biomechanics of engulfment and filtration. Ann. Rev. Mar. Sci. 9, 367–386 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
19.Kleiber, M. The Fire of Life: An Introduction to Animal Energetics (Krieger, 1975).20.Nagy, K. A. Field metabolic rate and body size. J. Exp. Biol. 208, 1621–1625 (2005).PubMed 
Article 
PubMed Central 

Google Scholar 
21.Roman, J. et al. Whales as marine ecosystem engineers. Front. Ecol. Environ. 12, 377–385 (2014).Article 

Google Scholar 
22.Atkinson, A., Siegel, V., Pakhomov, E. & Rothery, P. Long-term decline in krill stock and increase in salps within the Southern Ocean. Nature 432, 100–103 (2004).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
23.Lee, C. I. L., Pakhomov, E., Atkinson, A. & Siegel, V. Long-term relationships between the marine environment, krill and salps in the Southern Ocean. J. Mar. Biol. 2010, 410129 (2010).Article 

Google Scholar 
24.Kahane-Rapport, S. R. & Goldbogen, J. A. Allometric scaling of morphology and engulfment capacity in rorqual whales. J. Morphol. 279, 1256–1268 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
25.Goldbogen, J. A. et al. Why whales are big but not bigger: physiological drivers and ecological limits in the age of ocean giants. Science 366, 1367–1372 (2019).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
26.Nickels, C. F., Sala, L. M. & Ohman, M. D. The morphology of euphausiid mandibles used to assess selective predation by blue whales in the southern sector of the California Current System. J. Crustac. Biol. 38, 563–573 (2018).Article 

Google Scholar 
27.Croll, D. A., Kudela, R. & Tershy, B. R. in Whales, Whaling, and Ocean Ecosystems (eds. Estes, J. A. et al.) 202–214 (Univ. California Press, 2006).28.Fleming, A. H., Clark, C. T., Calambokidis, J. & Barlow, J. Humpback whale diets respond to variance in ocean climate and ecosystem conditions in the California Current. Glob. Chang. Biol. 22, 1214–1224 (2015).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
29.Katija, K. Biogenic inputs to ocean mixing. J. Exp. Biol. 215, 1040–1049 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
30.Katija, K., Sherlock, R. E., Sherman, A. D. & Robison, B. H. New technology reveals the role of giant larvaceans in oceanic carbon cycling. Sci. Adv. 3, e1602374 (2017).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
31.Riisgård, H. U. On measurement of filtration rates in bivalves — the stony road to reliable data: review and interpretation. Mar. Ecol. Prog. Ser. 211, 275–291 (2001).ADS 
Article 

Google Scholar 
32.Drenner, R. W., Mummert, J. R. & O’Brien, W. J. Filter-feeding rates of gizzard shad. Trans. Am. Fish. Soc. 111, 210–215 (1982).Article 

Google Scholar 
33.Rocha, R. C. Jr, Clapham, P. J. & Ivashchenko, Y. V. Emptying the oceans: a summary of industrial whaling catches in the 20th century. Mar. Fish. Rev. 76, 37–48 (2014).Article 

Google Scholar 
34.Christensen, L. B. Marine mammal populations: reconstructing historical abundances at the global scale. Fish. Cent. Res. Reports 14, 167 (2006).
Google Scholar 
35.Laws, R. M. Seals and whales of the Southern Ocean. Philos. Trans. R. Soc. B Biol. Sci. 279, 81–96 (1977).ADS 

Google Scholar 
36.Myers, R. A. & Worm, B. Rapid worldwide depletion of predatory fish communities. Nature 423, 280–283 (2003).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
37.Trathan, P. N., Ratcliffe, N. & Masden, E. A. Ecological drivers of change at South Georgia: the krill surplus, or climate variability. Ecography 35, 983–993 (2012).Article 

Google Scholar 
38.Dunn, M. J. et al. Population size and decadal trends of three penguin species nesting at Signy Island, South Orkney Islands. PLoS ONE 11, e0164025 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
39.Falkowski, P. G., Barber, R. T. & Smetacek, V. Biogeochemical controls and feedbacks on ocean primary production. Science 281, 200–206 (1998).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
40.Ratnarajah, L. et al. A preliminary model of iron fertilisation by baleen whales and Antarctic krill in the Southern Ocean: sensitivity of primary productivity estimates to parameter uncertainty. Ecol. Modell. 320, 203–212 (2016).Article 

Google Scholar 
41.Willis, J. Whales maintained a high abundance of krill; both are ecosystem engineers in the Southern Ocean. Mar. Ecol. Prog. Ser. 513, 51–69 (2014).ADS 
Article 

Google Scholar 
42.Gerber, L. R., Morissette, L., Kaschner, K. & Pauly, D. Should whales be culled to increase fishery yield? Science 323, 880–881 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
43.Ruzicka, J. J., Steele, J. H., Ballerini, T., Gaichas, S. K. & Ainley, D. G. Dividing up the pie: whales, fish, and humans as competitors. Prog. Oceanogr. 116, 207–219 (2013).ADS 
Article 

Google Scholar 
44.Arrigo, K. R., van Dijken, G. L. & Bushinsky, S. Primary production in the Southern Ocean, 1997-2006. J. Geophys. Res. Ocean. 113, C08004 (2008).ADS 
Article 
CAS 

Google Scholar 
45.Geremia, C. et al. Migrating bison engineer the green wave. Proc. Natl Acad. Sci. USA 116, 25707–25713 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
46.Abrahms, B. et al. Memory and resource tracking drive blue whale migrations. Proc. Natl Acad. Sci. USA 116, 5582–5587 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
47.Bar-on, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
48.Pallin, L. J. et al. High pregnancy rates in humpback whales (Megaptera novaeangliae) around the Western Antarctic Peninsula, evidence of a rapidly growing population. R. Soc. Open Sci. 5, 180017 (2018).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
49.Aksnes, D. L. & Ohman, M. D. Multi-decadal shoaling of the euphotic zone in the southern sector of the California Current System. Limnol. Oceanogr. 54, 1272–1281 (2009).ADS 
Article 

Google Scholar 
50.Krough, A. The physiology of the blue whale. Nature 133, 635–637 (1934).ADS 
Article 

Google Scholar 
51.Lockyer, C. in Mammals in the Seas: Large Cetaceans (eds. Clarke, J. G., Goodman, J. & Soave, G. A.) 379–487 (FAO, 1981).52.Tamura, T. & Ohsumi, S. Regional assessments of prey consumption by marine cetaceans in the world. International Whaling Comission Scientific Report (2000); https://doi.org/10.1079/9780851996332.014353.Leaper, R. & Lavigne, D. How much do large whales eat? J. Cetacean Res. Manag. 9, 179–188 (2007).
Google Scholar 
54.Klumov, S. K. Food and helminth fauna of whalebone whales (Mystacoceti) in the main whaling regions of the world ocean. Tr. Instituta Okeanol. 71, 94–194 (1963).
Google Scholar 
55.Sigurjónsson, J. & Víkingsson, G. A. Estimation of food consumption by cetaceans in Icelandic and adjacent waters. J. Northw. Atl. Fish. Sci 22, 271–287 (1997).Article 

Google Scholar 
56.Tamura, T. & Konishi, K. Food habit and prey consumption of Antarctic minke whale Balaenoptera bonaerensis in JARPA research area. Inst. Cetacean Res. Rep. SC/D06/J18 (2006).57.Kenney, R. D., Scott, G. P., Thompson, T. J. & Winn, H. E. Estimates of prey consumption and trophic impacts of cetaceans in the USA northeast continental shelf ecosystem. J. Northwest Atl. Fish. Sci. 22, 155–171 (1997).Article 

Google Scholar 
58.Innes, B. Y. S., Lavigne, D. M., Earle, W. M. & Kovacs, K. M. Feeding rates of seals and whales. J. Anim. Ecol. 56, 115–130 (1987).Article 

Google Scholar 
59.Tamura, T. & Konishi, K. Prey composition and consumption rate by Antarctic minke whales based on JARPA and JARPAII data. Inst. Cetacean Res. Rep. SC/F14/J15 (2014).60.Tamura, T. Preliminary analyses on prey consumption by fin whales based on JARPAII data. Inst. Cetacean Res. Rep. SC/F14/J16 (2014).61.Tamura, T., Konishi, K. & Isoda, T. Updated estimation of prey consumption by common minke, Bryde’s and sei whales in the western North Pacific. Inst. Cetacean Res. Rep. SC/F16/JR15 (2016).62.Lockyer, C. All creatures great and smaller: a study in cetacean life history energetics. J. Mar. Biol. Assoc. UK 87, 1035–1045 (2007).Article 

Google Scholar 
63.Víkingsson, G. A. Feeding of fin whales (Balaenoptera physalus) off Iceland – diurnal and seasonal variation and possible rates. J. Northwest Atl. Fish. Sci. 22, 77–89 (1997).Article 

Google Scholar 
64.Ichii, T. & Kato, H. Food and daily food consumption of southern minke whales in the Antarctic (Balaenoptera acutorostrata). Polar Biol. 11, 479–487 (1991).Article 

Google Scholar 
65.Tamura, T. & Konishi, K. Feeding habits and prey consumption of Antarctic minke whale (Balaenoptera bonaerensis) in the Southern Ocean. J. Northwest Atl. Fish. Sci. 42, 13–25 (2009).Article 

Google Scholar 
66.Lockyer, C. Body fat condition in northeast Atlantic fin whales, Balaenoptera physalus, and its relationship with reproduction and food resource. Can. J. Fish. Aquat. Sci. 43, 142–147 (1986).Article 

Google Scholar 
67.Goldbogen, J. A. et al. Using digital tags with integrated video and inertial sensors to study moving morphology and associated function in large aquatic vertebrates. Anat. Rec. 300, 1935–1941 (2017).CAS 
Article 

Google Scholar 
68.Sumich, J. L. Swimming velocities, breathing patterns, and estimated costs of locomotion in migrating gray whales, Eschrichtius robustus. Can. J. Zool. 61, 647–652 (1983).Article 

Google Scholar 
69.Pauly, D., Trites, A. W., Capuli, E. & Christensen, V. Diet composition and trophic levels of marine mammals. ICES J. Mar. Sci. 55, 467–481 (1998).Article 

Google Scholar 
70.White, C. R. & Kearney, M. R. Metabolic scaling in animals: methods, empirical results, and theoretical explanations. Compr. Physiol. 4, 231–256 (2014).PubMed 
Article 
PubMed Central 

Google Scholar 
71.Schmitz, O. J. & Lavigne, D. M. Intrinsic rate of increase, body size, and specific metabolic rate in marine mammals. Oecologia 62, 305–309 (1984).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
72.Nagy, K. A., Girard, I. A. & Brown, T. K. Energetics of free-ranging mammals, reptiles, and birds. Annu. Rev. Nutr. 19, 247–277 (1999).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
73.Rivero, J.-L. L. Locomotor muscle fibre heterogeneity and metabolism in the fastest large-bodied rorqual: the fin whale (Balaenoptera physalus). J. Exp. Biol. 221, jeb177758 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
74.Friedlaender, A. S. et al. The advantages of diving deep: Fin whales quadruple their energy intake when targeting deep krill patches. Funct. Ecol. 34, 497–506 (2019).Article 

Google Scholar 
75.Calambokidis, J. et al. Differential vulnerability to ship strikes between day and night for blue, fin, and humpback whales based on dive and movement data from medium duration archival tags. Front. Mar. Sci. 6, 543 (2019).Article 

Google Scholar 
76.Cade, D. E., Friedlaender, A. S., Calambokidis, J. & Goldbogen, J. A. Kinematic diversity in rorqual whale feeding mechanisms. Curr. Biol. 26, 2617–2624 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
77.Gough, W. T. et al. Scaling of swimming performance in baleen whales. J. Exp. Biol. 222, jeb204172 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
78.Parks, S. E., Warren, J. D., Stamieszkin, K., Mayo, C. A. & Wiley, D. Dangerous dining: Surface foraging of North Atlantic right whales increases risk of vessel collisions. Biol. Lett. 8, 57–60 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
79.Nowacek, D. P. et al. Buoyant balaenids: the ups and downs of buoyancy in right whales. Proc. R. Soc. B Biol. Sci. 268, 1811–1816 (2001).CAS 
Article 

Google Scholar 
80.Johnson, M. P. & Tyack, P. L. A digital acoustic recording tag for measuring the response of wild marine mammals to sound. IEEE J. Ocean. Eng. 28, 3–12 (2003).ADS 
Article 

Google Scholar 
81.Cade, D. E., Barr, K. R., Calambokidis, J., Friedlaender, A. S. & Goldbogen, J. A. Determining forward speed from accelerometer jiggle in aquatic environments. J. Exp. Biol. 221, 170449 (2018).
Google Scholar 
82.Goldbogen, J. A. et al. Integrative approaches to the study of baleen whale diving behavior, feeding performance, and foraging ecology. Bioscience 63, 90–100 (2013).Article 

Google Scholar 
83.Hazen, E. L., Friedlaender, A. S. & Goldbogen, J. A. Blue whales (Balaenoptera musculus) optimize foraging efficiency by balancing oxygen use and energy gain as a function of prey density. Sci. Adv. 1, e1500469 (2015).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
84.Cade, D. E. et al. Predator-scale spatial analysis of intra-patch prey distribution reveals the energetic drivers of rorqual whale super group formation. Fucntional Ecol. 35, 894–908 (2021).Article 

Google Scholar 
85.Nowacek, D. P. et al. Super-aggregations of krill and humpback whales in Wilhelmina bay, Antarctic Peninsula. PLoS ONE 6, 2–6 (2011).Article 
CAS 

Google Scholar 
86.Goldbogen, J. A. et al. Prey density and distribution drive the three-dimensional foraging strategies of the largest filter feeder. Funct. Ecol. 29, 951–961 (2015).Article 

Google Scholar 
87.Cade, D. E., Carey, N., Domenici, P., Potvin, J. & Goldbogen, J. A. Predator-informed looming stimulus experiments reveal how large filter feeding whales capture highly maneuverable forage fish. Proc. Natl Acad. Sci. USA 117, 472–478 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
88.Goldbogen, J. A. et al. Mechanics, hydrodynamics and energetics of blue whale lunge feeding: efficiency dependence on krill density. J. Exp. Biol. 214, 131–146 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
89.Hamner, W. M. Aspects of schooling in Euphausia superba. J. Crustac. Biol. 4, 67–74 (1984).Article 

Google Scholar 
90.Potvin, J., Goldbogen, J. A. & Shadwick, R. E. Passive versus active engulfment: verdict from trajectory simulations of lunge-feeding fin whales Balaenoptera physalus. J. R. Soc. Interface 6, 1005–1025 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
91.Potvin, J., Goldbogen, J. A. & Shadwick, R. E. Scaling of lunge feeding in rorqual whales: an integrated model of engulfment duration. J. Theor. Biol. 267, 437–453 (2010).ADS 
MathSciNet 
CAS 
PubMed 
MATH 
Article 
PubMed Central 

Google Scholar 
92.Goldbogen, J. A. et al. Underwater acrobatics by the world’s largest predator: 360° rolling manoeuvres by lunge-feeding blue whales. Biol. Lett. 9, 20120986 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
93.Rodriguez-Romero, J., Palacios-Salgado, D. S., Lopez-Martinez, J., Vazquez, S. H. & Velazquez-Abunader, J. I. The length – weight relationship parameters of demersal fish species off the western coast of Baja California Sur, Mexico. J. Appl. Ichthology 25, 114–116 (2009).Article 

Google Scholar 
94.Pitcher, T. J. & Partridge, B. L. Fish school density and volume. Mar. Biol. 394, 383–394 (1979).Article 

Google Scholar 
95.Laidre, K. L., Heide-Jørgensen, M. P. & Nielsen, T. G. Role of the bowhead whale as a predator in West Greenland. Mar. Ecol. Prog. Ser. 346, 285–297 (2007).ADS 
Article 

Google Scholar 
96.Simon, M., Johnson, M., Tyack, P. & Madsen, P. T. Behaviour and kinematics of continuous ram filtration in bowhead whales (Balaena mysticetus). Proc. R. Soc. B Biol. Sci. 276, 3819–3828 (2009).Article 

Google Scholar 
97.Baumgartner, M. F. & Mate, B. R. Summertime foraging ecology of North Atlantic right whales. Mar. Ecol. Prog. Ser. 264, 123–135 (2003).ADS 
Article 

Google Scholar 
98.van der Hoop, J. M. et al. Foraging rates of ram‐filtering North Atlantic right whales. Funct. Ecol. 33, 1290–1306 (2019).Article 

Google Scholar 
99.Burnett, J. D. et al. Estimating morphometric attributes of baleen whales with photogrammetry from small UASs: a case study with blue and gray whales. Mar. Mammal Sci. 35, 108–139 (2019).Article 

Google Scholar 
100.Torres, W. I. & Bierlich, K. C. MorphoMetriX: a photogrammetric measurement GUI for morphometric analysis of megafauna. J. Open Source Softw. 5, 1825 (2020).ADS 
Article 

Google Scholar 
101.Johnston, D. W. Unoccupied aircraft systems in marine science and conservation. Ann. Rev. Mar. Sci. 11, 439–463 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
102.Durban, J. W. et al. Photogrammetry of blue whales with an unmanned hexacopter. Mar. Mammal Sci. 32, 1510–1515 (2016).Article 

Google Scholar 
103.Kelley, D. & Richards, C. oce: Analysis of Oceanographic Data R Package v. 1.1 (2019).104.Dubreuil, J. & Petitgas, P. Energy density of anchovy Engraulis encrasicolus in the Bay of Biscay. J. Fish Biol. 74, 521–534 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
105.Chenowith, E. M. Bioenergetic and Economic Impacts of Humpback Whale Depredation at Salmon Hatchery Release Sites. PhD thesis, Univ. Alaska (2018).106.Werth, A. J. Models of hydrodynamic flow in the bowhead whale filter feeding apparatus. J. Exp. Biol. 207, 3569–3580 (2004).PubMed 
Article 
PubMed Central 

Google Scholar 
107.Werth, A. in Feeding: Form, Function, and Evolution in Tetrapod Vertebrates (ed. Schwenk, K.) 487–526 (Academic, 2000).108.Mckinstry, C. A. E., Westgate, A. J. & Koopman, H. N. Annual variation in the nutritional value of stage V Calanus finmarchicus: implications for right whales and other copepod predators. Endang. Species Res. 20, 195–204 (2013).Article 

Google Scholar 
109.Folkow, L. P., Haug, T., Nilssen, K. T. & Nordy, E. S. Estimated food consumption of minke whales Balaenoptera acutorostrata in Northeast Atlantic waters in 1992-1995. NAMMCO Sci. Publ. 2, 65–80 (2000).Article 

Google Scholar 
110.Brodie, P. F. Cetacean energetics, an overview of intraspecific size variation. Ecology 56, 152–161 (1975).ADS 
Article 

Google Scholar 
111.Hill, S. L. et al. Is current management of the antarctic krill fishery in the atlantic sector of the southern ocean precautionary? CCAMLR Sci. 23, 31–51 (2016).
Google Scholar 
112.Atkinson, A. et al. Oceanic circumpolar habitats of Antarctic krill. Mar. Ecol. Prog. Ser. 362, 1–23 (2008).ADS 
CAS 
Article 

Google Scholar 
113.Ratnarajah, L., Bowie, A. R., Lannuzel, D., Meiners, K. M. & Nicol, S. The biogeochemical role of baleen whales and krill in Southern Ocean nutrient cycling. PLoS ONE 9, e114067 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
114.Rose, C., Parker, A., Jefferson, B. & Cartmell, E. The characterization of feces and urine: a review of the literature to inform advanced treatment technology. Crit. Rev. Environ. Sci. Technol. 45, 1827–1879 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
115.Candela, E., Camacho, M. V. & Perdomo, J. Iron absorption by humans and swine from Fe (III)-EDTA. Further studies. J. Nutr. 114, 2204–2211 (1984).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
116.Ratnarajah, L. et al. A preliminary model of iron fertilisation by baleen whales and Antarctic krill in the Southern Ocean: sensitivity of primary productivity estimates to parameter uncertainty. Ecol. Modell. 320, 203–212 (2016).Article 

Google Scholar 
117.Twining, B. S., Baines, S. B. & Fisher, N. S. Element stoichiometries of individual plankton cells collected during the Southern Ocean Iron Experiment (SOFeX). Limnol. Oceanogr. 49, 2115–2128 (2004).ADS 
CAS 
Article 

Google Scholar 
118.Strzepek, R. F., Maldonado, M. T., Hunter, K. A., Frew, R. D. & Boyd, P. W. Adaptive strategies by Southern Ocean phytoplankton to lessen iron limitation: uptake of organically complexed iron and reduced cellular iron requirements. Limnol. Oceanogr. 56, 1983–2002 (2011).ADS 
CAS 
Article 

Google Scholar 
119.Quigg, A. et al. The evolutionary inheritance of elemental stoichiometry in marine phytoplankton. Nature 425, 291–294 (2003).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
120.Wickham, H. ggplot2: Elegant Graphics for Data Analysis 2nd edn (Springer, 2016).121.Lockyer, C. Body weights of some species of large whales. ICES J. Mar. Sci. 36, 259–273 (1976).Article 

Google Scholar 
122.Blix, A. S. & Folkow, L. P. Daily energy expenditure in free living minke whales (Balaenoptera acutorostrata). Acta Physiol. Scand. 153, 61–66 (1995).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
123.Nordoy, E. S., Folkow, L. P., Martensson, P. & Blix, A. S. Food requirements of Northeast Atlantic minke whales. Dev. Mar. Biol. 4, 307–317 (1995).Article 

Google Scholar 
124.Murase, H., Tamura, T., Matsuoka, K. & Hakamada, T. First attempt of estimation of feeding impact on krill standing stock by three baleen whale species (Antarctic minke, humpback and fin whales) in Areas IV and V using JARPA dat. Inst. Cetacean Res. Rep. SC/D06/J22 (2006).125.Southall, B. L. et al. Behavioral responses of individual blue whales (Balaenoptera musculus) to mid-frequency military sonar. J. Exp. Biol. 222, jeb190637 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
126.Goldbogen, J. A. et al. Blue whales respond to simulated mid-frequency military sonar. Proc. R. Soc. B 280, 20130657 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
127.Stimpert, A. K. et al. Sound production and associated behavior of tagged fin whales (Balaenoptera physalus) in the Southern California Bight. Anim. Biotelemetry 3, 1–12 (2015).Article 

Google Scholar 
128.Goldbogen, J. A. et al. Foraging behavior of humpback whales: kinematic and respiratory patterns suggest a high cost for a lunge. J. Exp. Biol. 211, 3712–3719 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
129.Wiley, D. et al. Underwater components of humpback whale bubble-net feeding behaviour. Behaviour 148, 575–602 (2011).Article 

Google Scholar 
130.Friedlaender, A. S., Tyson, R. B., Stimpert, A. K., Read, A. J. & Nowacek, D. P. Extreme diel variation in the feeding behavior of humpback whales along the western Antarctic Peninsula during autumn. Mar. Ecol. Prog. Ser. 494, 281–289 (2013).ADS 
Article 

Google Scholar 
131.Kahane-Rapport, S. R. et al. Lunge filter feeding biomechanics constrain rorqual foraging ecology across scale. J. Exp. Biol. 223, jeb224196 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
132.Friedlaender, A. S. et al. Feeding rates and under-ice foraging strategies of the smallest lunge filter feeder, the Antarctic minke whale (Balaenoptera bonaerensis). J. Exp. Biol. 217, 2851–2854 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
133.Domenici, P., Batty, R. S. & Similä, T. Spacing of wild schooling herring while encircled by killer whales. J. Fish Biol. 57, 831–836 (2000).Article 

Google Scholar 
134.Tamura, T. et al. Some examinations of uncertainties in the prey consumption estimates of common minke, sei and Bryde’s whales in the western North Pacific. (2009).135.Innes, S., Lavigne, D. M., Earle, W. M. & Kovacs, K. M. Estimating feeding rates of marine mammals from heart mass to body mass ratios. Mar. Mammal Sci. 2, 227–229 (1986).Article 

Google Scholar 
136.Armstrong, A. J. & Siegfried, W. R. Consumption of Antarctic krill by minke whales (Balaenoptera acutorostrata). Antarct. Sci. 3(1)13-18. 1991. 3, 13–18 (1991).
Google Scholar 
137.Reilly, S. et al. Biomass and energy transfer to baleen whales in the South Atlantic sector of the Southern Ocean. Deep. Res. Part II Top. Stud. Oceanogr. 51, 1397–1409 (2004).ADS 
Article 

Google Scholar 
138.Read, A. J. & Brownstein, C. R. Considering other consumers: Fisheries, predators, and Atlantic herring in the Gulf of Maine. Conserv. Ecol. 7 (2003).139.Nagy, K. Food requirements of wild animals: predictive equations for free-living mammals, reptiles, and birds. Nutr. Abstr. Rev. Ser. B 71, 21R–31R (2001).
Google Scholar 
140.Stevick, P. T. et al. Trophic relationships and oceanography on and around a small offshore bank. Mar. Ecol. Prog. Ser. 363, 15–28 (2008).ADS 
Article 

Google Scholar  More

1.Hayes, T. B., Falso, P., Gallipeau, S. & Stice, M. The cause of global amphibian declines: A developmental endocrinologist’s perspective. J. Exp. Biol. 213, 921–933. https://doi.org/10.1242/jeb.040865 (2010).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
2.IPBES. The IPBES Regional Assessment Report on Biodiversity and Ecosystem Services for Europe and Central Asia (eds Rounsevell, M. et al.) (IPBES, 2018).
Google Scholar 
3.Eigenbrod, F., Hecnar, S. J. & Fahrig, L. Accessible habitat: An improved measure of the effects of habitat loss and roads on wildlife populations. Landsc. Ecol. 23, 159–168. https://doi.org/10.1007/s10980-007-9174-7 (2008).Article 

Google Scholar 
4.Cushman, S. A. Effects of habitat loss and fragmentation on amphibians: A review and prospectus. Biol. Conserv. 128, 231–240. https://doi.org/10.1016/j.biocon.2005.09.031 (2006).Article 

Google Scholar 
5.Pittman, S. E., Osbourn, M. S. & Semlitsch, R. D. Movement ecology of amphibians: A missing component for understanding population declines. Biol. Conserv. 169, 44–53. https://doi.org/10.1016/j.biocon.2013.10.020 (2014).Article 

Google Scholar 
6.Heigl, F., Horvath, K., Laaha, G. & Zaller, J. G. Amphibian and reptile road-kills on tertiary roads in relation to landscape structure: Using a citizen science approach with open-access land cover data. BMC Ecol. 17, 1–11. https://doi.org/10.1186/s12898-017-0134-z (2017).Article 

Google Scholar 
7.Heigl, F. & Zaller, J. G. Using a citizen science approach in higher education: A case study reporting roadkills in Austria. Hum. Comput. https://doi.org/10.15346/hc.v1i2.7 (2014).Article 

Google Scholar 
8.Kyek, M., Kaufmann, P. H. & Lindner, R. Differing long term trends for two common amphibian species (Bufo bufo and Rana temporaria) in alpine landscapes of Salzburg, Austria. PLoS ONE 12, e0187148. https://doi.org/10.1371/journal.pone.0187148 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
9.Klepsch, R. et al. Amphibienschutz an Straßen. Leitbilder zu temporären und permanenten Schutzeinrichtungen. ÖGH-Aktuell, Mitteilungen der Österreichischen Gesellschaft für Herpetologie (2011).10.Kropfberger, J. Naturschützer als Amphibientaxi. Amphibienschutzprojekte des naturschutzbund Oberösterreich. natur&land 103, 12–13 (2017).
Google Scholar 
11.Gross, M. Amphibienschutz an Niederösterreichs Straßen. natur&land 103, 16–18 (2017).
Google Scholar 
12.Kordges, T. & Weddeling, K. Immer früher? Langzeitmonitoring (1979–2013) zum Laichbeginn des Grasfrosches (Rana temporaria) im Felderbachtal in Hattingen (NRW). Zeitschrift für Feldherpetologie 24, 211–222 (2015).
Google Scholar 
13.Arnfield, H., Grant, R., Monk, C. & Uller, T. Factors influencing the timing of spring migration in common toads (Bufo bufo). J. Zool. 288, 112–118. https://doi.org/10.1111/j.1469-7998.2012.00933.x (2012).Article 

Google Scholar 
14.Timm, B. C., McGarigal, K. & Compton, B. W. Timing of large movement events of pond-breeding amphibians in Western Massachusetts USA. Biol. Conserv. 136, 442–454. https://doi.org/10.1016/j.biocon.2006.12.015 (2007).Article 

Google Scholar 
15.Dervo, B. K., Bærum, K. M., Skurdal, J. & Museth, J. Effects of temperature and precipitation on breeding migrations of amphibian species in southeastern Norway. Scientifica 2016, 3174316. https://doi.org/10.1155/2016/3174316 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
16.Loman, J. Breeding phenology in Rana temporaria. Local variation is due to pond temperature and population size. Ecol. Evolut. 6, 6202–6209. https://doi.org/10.1002/ece3.2356 (2016).Article 

Google Scholar 
17.Hofrichter, R. Amphibien: Evolution, Anatomie, Physiologie, Ökologie und Verbreitung, Verhalten, Bedrohung und Gefährdung (Naturbuch-Verl., 1998).
Google Scholar 
18.Hartel, T., Sas, I., Pernetta, A. P. & Geltsch, I. C. The reproductive dynamic of temperate amphibians: A review. North-Western J. Zool. 3, 127–145 (2007).
Google Scholar 
19.Becker, C. G., Fonseca, C. R., Haddad, C. F. B., Batista, R. F. & Prado, P. I. Habitat split and the global decline of amphibians. Science 318, 1775–1777. https://doi.org/10.1126/science.1149374 (2007).CAS 
Article 
PubMed 
ADS 

Google Scholar 
20.Reading, C. J. The effect of winter temperatures on the timing of breeding activity in the common toad Bufo bufo. Oecologia 117, 469–475. https://doi.org/10.1007/s004420050682 (1998).CAS 
Article 
PubMed 
ADS 

Google Scholar 
21.Tryjanowski, P., Rybacki, M. & Sparks, T. Changes in the first spawning dates of common frogs and common toads in western Poland in 1978–2002. Ann. Zool. Fennici 10, 459–464 (2003).
Google Scholar 
22.Mazgajska, J. & Mazgajski, T. D. Two amphibian species in the urban environment: Changes in the occurrence, spawning phenology and adult condition of common and green toads. Eur. Zool. J. 87, 170–179. https://doi.org/10.1080/24750263.2020.1744743 (2020).Article 

Google Scholar 
23.Scott, W. A., Pithart, D. & Adamson, J. K. Long-term United Kingdom trends in the breeding phenology of the common frog, Rana temporaria. hpet 42, 89–96. https://doi.org/10.1670/07-022.1 (2008).Article 

Google Scholar 
24.Ficetola, G. F. & Maiorano, L. Contrasting effects of temperature and precipitation change on amphibian phenology, abundance and performance. Oecologia 181, 683–693. https://doi.org/10.1007/s00442-016-3610-9 (2016).Article 
PubMed 
ADS 

Google Scholar 
25.Delpierre, N. et al. Temperate and boreal forest tree phenology: From organ-scale processes to terrestrial ecosystem models. Ann. For. Sci. 73, 5–25. https://doi.org/10.1007/s13595-015-0477-6 (2016).Article 

Google Scholar 
26.Basler, D. & Körner, C. Photoperiod sensitivity of bud burst in 14 temperate forest tree species. Agric. For. Meteorol. 165, 73–81. https://doi.org/10.1016/j.agrformet.2012.06.001 (2012).Article 
ADS 

Google Scholar 
27.Vitasse, Y. & Basler, D. What role for photoperiod in the bud burst phenology of European beech. Eur. J. For. Res. 132, 1–8. https://doi.org/10.1007/s10342-012-0661-2 (2013).Article 

Google Scholar 
28.Piao, S. et al. Plant phenology and global climate change: Current progresses and challenges. Glob. Change Biol. 25, 1922–1940. https://doi.org/10.1111/gcb.14619 (2019).Article 
ADS 

Google Scholar 
29.ZAMG. PhenoWatch—ZAMG Phänologie. http://www.phenowatch.at/ (2020).30.Naturschutzbund Österreich. naturbeobachtung.at: der Treffpunkt für Naturbeobachtung in Österreich (2020).31.Citizen Science Working Group. Project roadkill. https://roadkill.at/ (2020).32.Naturhistorisches Museum Wien. Naturhistorisches Museum Wien—Herpetofaunistische Datenbank. https://www.nhm-wien.ac.at/forschung/1_zoologie_wirbeltiere/herpetologische_sammlung/datenbank (2021).33.Münch, D. Populationsentwicklung und klimatisch veränderte Frühjahrsaktivität von Erdkröte, Teichmolch, Bergmolch nd Kammolch an der Höfkerstraße (am NSG Hallerey in Dortmund 1981–1997). Dortmunder Beitr. Landeskde. Naturwiss. Mitt 32, 98–106 (1998).
Google Scholar 
34.Chmielewski, F.-M. & Rötzer, T. Response of tree phenology to climate change across Europe. Agric. For. Meteorol. 108, 101–112. https://doi.org/10.1016/S0168-1923(01)00233-7 (2001).Article 
ADS 

Google Scholar 
35.Menzel, A. Phenology: Its importance to the global change community. Clim. Change 54, 379–385 (2002).Article 

Google Scholar 
36.Menzel, A., Sparks, T. H., Estrella, N. & Roy, D. B. Altered geographic and temporal variability in phenology in response to climate change. Glob Ecol. Biogeogr. 15, 498–504. https://doi.org/10.1111/j.1466-822X.2006.00247.x (2006).Article 

Google Scholar 
37.Crimmins, M. A. & Crimmins, T. M. Does an early spring indicate an early summer? Relationships between intraseasonal growing degree day thresholds. J. Geophys. Res. Biogeosci. 124, 2628–2641. https://doi.org/10.1029/2019JG005297 (2019).Article 

Google Scholar 
38.Zentralanstalt für Meteorologie und Geodynamik. Beobachtungsanleitung für die Phänologie (2013).39.Meier, U. (ed.) Growth stages of mono- and dicotyledonous plants. BBCH monograph = Entwicklungsstadien mono- und dikotyler Pflanzen (Blackwell-Wiss.-Verl., 1997).
Google Scholar 
40.Phillimore, A. B., Hadfield, J. D., Jones, O. R. & Smithers, R. J. Differences in spawning date between populations of common frog reveal local adaptation. Proc. Natl. Acad. Sci. 107, 8292–8297. https://doi.org/10.1073/pnas.0913792107 (2010).Article 
PubMed 
PubMed Central 
ADS 

Google Scholar 
41.Auer, I. et al. HISTALP—Historical instrumental climatological surface time series of the Greater Alpine Region. Int. J. Climatol. 27, 17–46. https://doi.org/10.1002/joc.1377 (2007).Article 

Google Scholar 
42.Hiebl, J. et al. A high-resolution 1961–1990 monthly temperature climatology for the greater Alpine region. metz 18, 507–530. https://doi.org/10.1127/0941-2948/2009/0403 (2009).Article 

Google Scholar 
43.BMVIT—Bundesministerium für Verkehr, Innovation und Technologie. Gesamtverkehrsplan für Österreich. https://www.bmk.gv.at/dam/jcr:dfd82842-234b-41c7-a267-0dc7ac76eb6b/gvp_gesamt.pdf (2012).44.European Environment Agency. Landscape fragmentation pressure and trends in Europe. https://www.eea.europa.eu/data-and-maps/indicators/mobility-and-urbanisation-pressure-on-ecosystems-2/assessment (2020).45.Grillmayer, R., Banko, G., Leitner, H. & Leissing, D. Wie zerschnitten ist unsere Landschaft? natur&land, 30–31 (2015).46.Weißmair, W. Monitoring ausgewählter Amphibienwanderstrecken—Endbericht 2010 Amt der Oö (Landesregierung, Abteilung Naturschutz, 2011).
Google Scholar 
47.Dick, G. & Sackl, P. Angaben zur Laichwanderung von Erdkröte, Bufo b. bufo (LINNAEUS; 1758), und Grasfrosch, Rana t. temporaria LINNAEUS, 1758, einiger Populationen im Waldviertel (Niederösterreich) sowie zu praktischen Schutzmaßnahmen. Herpetozoa 1, 13–22 (1988).
Google Scholar 
48.Wolf, M. J., Smole-Wiener, A. K. & Kleewein, A. Lebensraum- und Populationsanalyse am Beispiel der Amphibienwanderstrecke 37 Wernberg, Kärnten. Carinthia II 125, 741 (2015).
Google Scholar 
49.Kapeller, H. Amphibienschutz im Sellraintal. natur&land 103, 15 (2017).
Google Scholar 
50.Templ, B. et al. Pan European phenological database (PEP725): A single point of access for European data. Int. J. Biometeorol. 62, 1109–1113. https://doi.org/10.1007/s00484-018-1512-8 (2018).Article 
PubMed 
ADS 

Google Scholar 
51.Menzel, A. et al. Climate change fingerprints in recent European plant phenology. Glob. Change Biol. 26, 2599–2612. https://doi.org/10.1111/gcb.15000 (2020).Article 
ADS 

Google Scholar 
52.Lanner, J., Huchler, K., Pachinger, B., Sedivy, C. & Meimberg, H. Dispersal patterns of an introduced wild bee, Megachile sculpturalis Smith, 1853 (Hymenoptera: Megachilidae) in European alpine countries. PLoS ONE 15, e0236042. https://doi.org/10.1371/journal.pone.0236042 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
53.Schweiger, S., Grillitsch, H., Hill, J. & Mayer, W. Die Mauereidechse, Podarcis muralis (Laurenti, 1768) in Österreich: Phylogeographie, Verbreitung, Lebensräume und Schutz. In Verbreitung, Biologie und Schutz der Mauereidechse Podarcis muralis (Laurenti, 1768) (eds Laufer, H. & Schulte, U.) 44–55 (Deutsche Gesellschaft für Herpetologie und Terrarienkunde (DGHT) e.V, 2015).
Google Scholar 
54.Maletzky, A. & Schweiger, S. Zur Situation der Erdkröte, Bufo bufo in Österreich—Verbreitung, Phänologie, Gefährdung und Schutz. In Verbreitung, Biologie und Schutz der Erdkröte Bufo bufo (LINNAEUS, 1758) mit besonderer Berücksichtigung des Amphibienschutzes an Straßen (eds Maletzky, A. et al.) 58–66 (Deutsche Gesellschaft für Herpetologie und Terrarienkunde, 2016).
Google Scholar 
55.Cabela, A., Grillitsch, H. & Tiedemann, F. Atlas zur Verbreitung und Ökologie der Amphibien und Reptilien in Österreich. Auswertung der herpetofaunistischen Datenbank der herpetologischen Sammlung des Naturhistorischen Museums in Wien (Naturhistorisches Museum, 2001).
Google Scholar 
56.Brunken, G. Amphibienwanderungen. Zwischen Land und Wasser. Merkblatt NVN/BSH 1–4 (2004).57.Hiebl, J., Reisenhofer, S., Auer, I., Böhm, R. & Schöner, W. Multi-methodical realisation of Austrian climate maps for 1971–2000. Adv. Sci. Res. 6, 19–26. https://doi.org/10.5194/asr-6-19-2011 (2011).Article 

Google Scholar 
58.RStudio. RStudio—Take control of your R code. https://rstudio.com/products/rstudio/ (2020). More