Ecology

1.McFall-Ngai, M. et al. Animals in a bacterial world, a new imperative for the life sciences. Proc. Natl Acad. Sci. USA 110, 3229–3236 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
2.Bang, C. et al. Metaorganisms in extreme environments: do microbes play a role in organismal adaptation? Zoology 127, 1–9 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
3.Mueller, U. G. & Sachs, J. L. Engineering microbiomes to improve plant and animal health. Trends Microbiol. 23, 606–617 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
4.Theis, K. R., Whittaker, D. J. & Rojas, C. A. A hologenomic approach to animal behavior. In Evolution in Action: Past, Present and Future 247–263 (Springer, 2020).5.Foster, K. R., Schluter, J., Coyte, K. Z. & Rakoff-Nahoum, S. The evolution of the host microbiome as an ecosystem on a leash. Nature 548, 43–51 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
6.Ziegler, M., Seneca, F. O., Yum, L. K., Palumbi, S. R. & Voolstra, C. R. Bacterial community dynamics are linked to patterns of coral heat tolerance. Nat. Commun. 8, 1–8 (2017).Article 
CAS 

Google Scholar 
7.Robbins, S. J. et al. A genomic view of the reef-building coral Porites lutea and its microbial symbionts. Nat. Microbiol. 4, 2090–2100 (2019).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
8.Berendsen, R. L., Pieterse, C. M. & Bakker, P. A. The rhizosphere microbiome and plant health. Trends Plant Sci. 17, 478–486 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Voolstra, C. R. & Ziegler, M. Adapting with microbial help: Microbiome flexibility facilitates rapid responses to environmental change. BioEssays 2, 2000004 (2020).Article 

Google Scholar 
10.Cárdenas, C. A., Bell, J. J., Davy, S. K., Hoggard, M. & Taylor, M. W. Influence of environmental variation on symbiotic bacterial communities of two temperate sponges. FEMS Microbiol. Ecol. 88, 516–527 (2014).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
11.Pantos, O., Bongaerts, P., Dennis, P. G., Tyson, G. W. & Hoegh-Guldberg, O. Habitat-specific environmental conditions primarily control the microbiomes of the coral Seriatopora hystrix. ISME J. 9, 1916–1927 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
12.Roder, C., Bayer, T., Aranda, M., Kruse, M. & Voolstra, C. R. Microbiome structure of the fungid coral Ctenactis echinata aligns with environmental differences. Mol. Ecol. 24, 3501–3511 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
13.Neave, M. J. et al. Differential specificity between closely related corals and abundant Endozoicomonas endosymbionts across global scales. ISME J. 11, 186–200 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Carrier, T. J. & Reitzel, A. M. Convergent shifts in host-associated microbial communities across environmentally elicited phenotypes. Nat. Commun. 9, 1–9 (2018).CAS 
Article 

Google Scholar 
15.Pollock, F. J. et al. Coral-associated bacteria demonstrate phylosymbiosis and cophylogeny. Nat. Commun. 9, 1–13 (2018).CAS 
Article 

Google Scholar 
16.Glasl, B., Smith, C. E., Bourne, D. G. & Webster, N. S. Disentangling the effect of host-genotype and environment on the microbiome of the coral Acropora tenuis. PeerJ 7, e6377 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
17.Macke, E., Callens, M., De Meester, L. & Decaestecker, E. Host-genotype dependent gut microbiota drives zooplankton tolerance to toxic cyanobacteria. Nat. Commun. 8, 1–13 (2017).CAS 
Article 

Google Scholar 
18.Casey, J. M., Connolly, S. R. & Ainsworth, T. D. Coral transplantation triggers shift in microbiome and promotion of coral disease associated potential pathogens. Sci. Rep. 5, 11903 (2015).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Ziegler, M. et al. Coral bacterial community structure responds to environmental change in a host-specific manner. Nat. Commun. 10, 1–11 (2019).ADS 
CAS 
Article 

Google Scholar 
20.Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
21.Spor, A., Koren, O. & Ley, R. Unravelling the effects of the environment and host genotype on the gut microbiome. Nat. Rev. Microbiol. 9, 279–290 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
22.Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
23.Jaspers, C. et al. Resolving structure and function of metaorganisms through a holistic framework combining reductionist and integrative approaches. Zoology 113, 81–87 (2019).Article 

Google Scholar 
24.Blackall, L. L., Wilson, B. & van Oppen, M. J. H. Coral—the world’s most diverse symbiotic ecosystem. Mol. Ecol. 24, 5330–5347 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
25.Hernandez-Agreda, A., Gates, R. D. & Ainsworth, T. D. Defining the core microbiome in corals’ microbial soup. Trends Microbiol. 25, 125–140 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
26.LaJeunesse, T. C. et al. Systematic revision of Symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570–2580 (2018).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
27.Rohwer, F., Seguritan, V., Azam, F. & Knowlton, N. Diversity and distribution of coral-associated bacteria. Mar. Ecol. Prog. Ser. 243, 1–10 (2002).ADS 
Article 

Google Scholar 
28.Rosenberg, E., Koren, O., Reshef, L., Efrony, R. & Zilber-Rosenberg, I. The role of microorganisms in coral health, disease and evolution. Nat. Rev. Microbiol. 5, 355–362 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
29.Bourne, D. G., Morrow, K. M. & Webster, N. S. Insights into the coral microbiome: underpinning the health and resilience of reef ecosystems. Annu. Rev. Microbiol. 70, 317–340 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
30.Muscatine, L., Porter, J. W. & Kaplan, I. R. Resource partitioning by reef corals as determined from stable isotope composition. Mar. Biol. 100, 185–193 (1989).Article 

Google Scholar 
31.Rädecker, N., Pogoreutz, C., Voolstra, C. R., Wiedenmann, J. & Wild, C. Nitrogen cycling in corals: the key to understanding holobiont functioning? Trends Microbiol. 23, 490–497 (2015).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
32.Wegley, L., Edwards, R., Rodriguez‐Brito, B., Liu, H. & Rohwer, F. Metagenomic analysis of the microbial community associated with the coral Porites astreoides. Environ. Microbiol. 9, 2707–2719 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
33.Raina, J. B., Tapiolas, D., Willis, B. L. & Bourne, D. G. Coral-associated bacteria and their role in the biogeochemical cycling of sulfur. Appl. Environ. Microbiol. 75, 3492–3501 (2009).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
34.Lema, K. A., Willis, B. L. & Bourne, D. G. Corals form characteristic associations with symbiotic nitrogen-fixing bacteria. Appl. Environ. Microbiol. 78, 3136–3144 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.Krediet, C. J., Ritchie, K. B., Paul, V. J. & Teplitski, M. Coral-associated micro-organisms and their roles in promoting coral health and thwarting diseases. Proc. R. Soc. B 280, 20122328 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
36.Glasl, B., Herndl, G. J. & Frade, P. R. The microbiome of coral surface mucus has a key role in mediating holobiont health and survival upon disturbance. ISME J. 10, 2280–2292 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
37.Boilard, A. et al. Defining coral bleaching as a microbial dysbiosis within the coral holobiont. Microorganisms 8, 1682 (2020).CAS 
PubMed Central 
Article 

Google Scholar 
38.Apprill, A., Weber, L. G. & Santoro, A. E. Distinguishing between microbial habitats unravels ecological complexity in coral microbiomes. mSystems 1, e00143–16 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
39.Glasl, E.B., B. et al. Microbial indicators of environmental perturbations in coral reef ecosystems. Microbiome 7, 1–13 (2019).Article 

Google Scholar 
40.Damjanovic, K., Blackall, L. L., Peplow, L. M. & van Oppen, M. J. H. Assessment of bacterial community composition within and among Acropora loripes colonies in the wild and in captivity. Coral Reefs 39, 1245–1255 (2020).Article 

Google Scholar 
41.Dubé, E. B. et al. Ecology, biology and genetics of Millepora hydrocorals on coral reefs. In Invertebrates – Ecophysiology and Management (eds. Ray, S., Diarte-Plata, G. &  Escamilla-Montes, R.), (IntechOpen, 2019).42.Rodríguez, L. et al. Genetic relationships of the hydrocoral Millepora alcicornis and its symbionts within and between locations across the Atlantic. Coral Reefs 38, 255–268 (2019).ADS 
Article 

Google Scholar 
43.Lewis, J. B. Biology and ecology of the hydrocoral Millepora on coral reefs. Adv. Mar. Biol. 50, 1–55 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
44.Arrigoni, R. et al. An integrated morpho-molecular approach to delineate species boundaries of Millepora from the Red Sea. Coral Reefs 37, 967–984 (2018).ADS 
Article 

Google Scholar 
45.Boissin, E., Leung, J. K., Denis, V., Bourmaud, C. A. & Gravier-Bonnet, N. Morpho-molecular delineation of structurally important reef species, the fire corals, Millepora spp., at Réunion Island, Southwestern Indian Ocean. Hydrobiologia 847, 1237–1255 (2020).Article 

Google Scholar 
46.Dubé, C. E., Boissin, E., Maynard, J. A. & Planes, S. Fire coral clones demonstrate phenotypic plasticity among reef habitats. Mol. Ecol. 26, 3860–3869 (2017).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
47.Schwartzman, J. A. & Ruby, E. G. Stress as a normal cue in the symbiotic environment. Trends Microbiol. 24, 414–424 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
48.van Oppen, M. J. H. et al. Adaptation to reef habitats through selection on the coral animal and its associated microbiome. Mol. Ecol. 27, 2956–2971 (2018).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
49.Sunagawa, S. et al. Structure and function of the global ocean microbiome. Science 348, 6237 (2015).Article 
CAS 

Google Scholar 
50.Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
51.Hernandez-Agreda, A., Leggat, W., Bongaerts, P., Herrera, C. & Ainsworth, T. D. Rethinking the coral microbiome: simplicity exists within a diverse microbial biosphere. MBio 9, e00812–18 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
52.Bongaerts, P. et al. Adaptive divergence in a scleractinian coral: physiological adaptation of Seriatopora hystrix to shallow and deep reef habitats. BMC Evol. Biol. 11, 303 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
53.Albright, R., Benthuysen, J., Cantin, N., Caldeira, K. & Anthony, K. Coral reef metabolism and carbon chemistry dynamics of a coral reef flat. Geophys. Res. Lett. 42, 3980–3988 (2015).ADS 
CAS 
Article 

Google Scholar 
54.Pootakham, W. et al. Dynamics of coral‐associated microbiomes during a thermal bleaching event. MicrobiologyOpen 7, e00604 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
55.Neave, M. J., Apprill, A., Ferrier-Pagès, C. & Voolstra, C. R. Diversity and function of prevalent symbiotic marine bacteria in the genus Endozoicomonas. Appl. Microbiol. Biotechnol. 100, 8315–8324 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
56.Meyer, J. L., Paul, V. J. & Teplitski, M. Community shifts in the surface microbiomes of the coral Porites astreoides with unusual lesions. PLoS ONE 9, e100316 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
57.Bayer, T. et al. The microbiome of the Red Sea coral Stylophora pistillata is dominated by tissue-associated Endozoicomonas bacteria. Appl. Environ. Microbiol. 79, 4759–4762 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
58.Jessen, C. et al. In-situ effects of eutrophication and overfishing on physiology and bacterial diversity of the Red Sea coral Acropora hemprichii. PLoS ONE 8, e62091 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
59.Morrow, K. M. et al. Natural volcanic CO2 seeps reveal future trajectories for host–microbial associations in corals and sponges. ISME J. 9, 894–908 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
60.Dubé, C. E., Ky, C. L. & Planes, S. Microbiome of the black-lipped pearl oyster Pinctada margaritifera, a multi-tissue description with functional profiling. Front. Microbiol. 10, 1548 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
61.Neave, M. J., Michell, C. T., Apprill, A. & Voolstra, C. R. Endozoicomonas genomes reveal functional adaptation and plasticity in bacterial strains symbiotically associated with diverse marine hosts. Sci. Rep. 7, 40579 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
62.Tandon, K. et al. Comparative genomics: dominant coral-bacterium Endozoicomonas acroporae metabolizes dimethylsulfoniopropionate (DMSP). ISME J. 14, 1290–1303 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
63.Ngugi, D. K., Ziegler, M., Duarte, C. M. & Voolstra, C. R. Genomic blueprint of glycine betaine metabolism in coral metaorganisms and their contribution to reef nitrogen budgets. iScience 23, 101120 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
64.González, J. M., Kiene, R. P. & Moran, M. A. Transformation of sulfur compounds by an abundant lineage of marine bacteria in the α-subclass of the class Proteobacteria. Appl. Environ. Microbiol. 65, 3810–3819 (1999).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
65.Curson, A. R. J., Rogers, R., Todd, J. D., Brearley, C. A. & Johnston, A. W. B. Molecular genetic analysis of a dimethylsulfoniopropionate lyase that liberates the climate-changing gas dimethylsulfide in several marine α-proteobacteria and Rhodobacter spharoides. Environ. Microbiol. 10, 757–767 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
66.Reisch, C. R., Moran, M. A. & Whitman, W. B. Bacterial catabolism of dimethylsulfoniopropionate (DMSP). Front. Microbiol. 2, 172 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
67.Thompson, J. R., Rivera, H. E., Closek, C. J. & Medina, M. Microbes in the coral holobiont: partners through evolution, development, and ecological interactions. Front. Cell. Infect. Microbiol. 4, 176 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
68.Durante, M. K., Baums, I. B., Williams, D. E., Vohsen, S. & Kemp, D. W. What drives phenotypic divergence among coral clonemates of Acropora palmata? Mol. Ecol. 28, 3208–3224 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
69.Wagner, M. R. et al. Host genotype and age shape the leaf and root microbiomes of a wild perennial plant. Nat. Commun. 7, 1–5 (2016).ADS 
CAS 
Article 

Google Scholar 
70.Fuerst, J. & Sagulenko, E. Beyond the bacterium: planctomycetes challenge our concepts of microbial structure and function. Nat. Rev. Microbiol. 9, 403–413 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
71.Forquin-Gomez, M. P. et al. The family Brevibacteriaceae. In Prokaryotes Actinobacteria. 4th edn., (eds. Rosenberg E. et al.), 141–153 (Springer, 2014).72.Baker, B. J., Lazar, C. S., Teske, A. P. & Dick, G. J. Genomic resolution of linkages in carbon, nitrogen, and sulfur cycling among widespread estuary sediment bacteria. Microbiome 3, 14 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
73.Tian, R. M. et al. Genomic analysis reveals versatile heterotrophic capacity of a potentially symbiotic sulfur‐oxidizing bacterium in sponge. Environ. Microbiol. 16, 3548–3561 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
74.Gauthier, M. E., Watson, J. R. & Degnan, S. M. Draft genomes shed light on the dual bacterial symbiosis that dominates the microbiome of the coral reef sponge Amphimedon queenslandica. Front. Mar. Sci. 3, 196 (2016).Article 

Google Scholar 
75.Dyksma, S. et al. Ubiquitous Gammaproteo-bacteria dominate dark carbon fixation in coastal sediments. ISME J. 8, 1939–1953 (2016).Article 
CAS 

Google Scholar 
76.Raina, J. B., Dinsdale, E. A., Willis, B. L. & Bourne, D. G. Do the organic sulfur compounds DMSP and DMS drive coral microbial associations? Trends Microbiol. 18, 101–108 (2010).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
77.Morrow, K. M., Moss, A. G., Chadwick, N. E. & Liles, M. R. Bacterial associates of two Caribbean coral species reveal species-specific distribution and geographic variability. Appl. Environ. Microbiol. 78, 6438–6449 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
78.Sabdono, A. & Radjasa, O. K. Phylogenetic diversity of organophosphorous pesticide-degrading coral bacteria from mid-west coast of Indonesia. Biotechnology 7, 694–701 (2008).CAS 
Article 

Google Scholar 
79.Kannapiran, E. & Ravindran, J. Dynamics and diversity of phosphate mineralizing bacteria in the coral reefs of Gulf of Mannar. J. Basic Microbiol. 52, 91–98 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
80.Mahmoud, H. M. & Kalendar, A. A. Coral-associated actinobacteria: diversity, abundance, and biotechnological potentials. Front. Microbiol. 7, 204 (2016).PubMed 
PubMed Central 

Google Scholar 
81.Probandt, D. et al. Permeability shapes bacterial communities in sublittoral surface sediments. Environ. Microbiol. 19, 1584–1599 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
82.Doolittle, W. F. & Booth, A. It’s the song, not the singer: an exploration of holobiosis and evolutionary theory. Biol. Philos. 32, 5–24 (2017).Article 

Google Scholar 
83.Louca, S. et al. Function and functional redundancy in microbial systems. Nat. Ecol. Evol. 2, 936–943 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
84.Kelly, L. W. et al. Local genomic adaptation of coral reef-associated microbiomes to gradients of natural variability and anthropogenic stressors. Proc. Natl Acad. Sci. USA 111, 10227–10232 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
85.Peixoto, R. S., Rosado, P. M., Leite, D. C. D. A., Rosado, A. S. & Bourne, D. G. Beneficial microorganisms for corals (BMC): proposed mechanisms for coral health and resilience. Front. Microbiol. 8, 341 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
86.Peixoto, R. S. et al. Coral probiotics: premise, promise, prospects. Annu. Rev. Anim. Biosci. 9, 265–288 (2021).PubMed 
Article 
PubMed Central 

Google Scholar 
87.Voolstra, C. R. et al. Extending the natural adaptive capacity of coral holobionts. Nat Rev Earth Environ. 1–16 (2021). https://doi.org/10.1038/s43017-021-00214-3.88.Santoro, E. P. et al. Coral microbiome manipulation elicits metabolic and genetic restructuring to mitigate heat stress and evade mortality. Sci Adv. 7 (2021). https://doi.org/10.1126/sciadv.abg3088.89.Adam, T. C. et al. Landscape‐scale patterns of nutrient enrichment in a coral reef ecosystem: implications for coral to algae phase shifts. Ecol. Appl. 31, e2227 (2021).PubMed 
Article 
PubMed Central 

Google Scholar 
90.Buckling, A., Kassen, R., Bell, G. & Rainey, P. B. Disturbance and diversity in experimental microcosms. Nature 408, 961–964 (2000).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
91.Berga, M., Szekely, A. J. & Langenheder, S. Effects of disturbance intensity and frequency on bacterial community composition and function. PLoS ONE 7, e36959 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
92.Neulinger, S. C., Järnegren, J., Ludvigsen, M., Lochte, K. & Dullo, W. C. Phenotype-specific bacterial communities in the cold-water coral Lophelia pertusa (Scleractinia) and their implications for the coral’s nutrition, health, and distribution. Appl. Environ. Microbiol. 74, 7272–7285 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
93.Kanukollu, S. et al. Distinct compositions of free-living, particle-associated and benthic communities of the Roseobacter group in the North Sea. FEMS Microbiol. Ecol. 92, 1 (2016).Article 
CAS 

Google Scholar 
94.Santos, H. F. et al. Climate change affects key nitrogen-fixing bacterial populations on coral reefs. ISME J. 8, 2272–2279 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
95.Sorokin, D. Y., Tourova, T. P. & Muyzer, G. Citreicella thiooxidans gen. nov., sp. nov., a novel lithoheterotrophic sulfur-oxidizing bacterium from the Black Sea. Syst. Appl. Microbiol. 28, 679–687 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
96.Chen, Y. J. et al. Metabolic flexibility allows generalist bacteria to become dominant in a frequently disturbed ecosystem. bioRxiv (2020). Preprint at https://doi.org/10.1101/2020.02.12.94522097.Spring, S., Scheuner, C., Göker, M. & Klenk, H. P. A taxonomic framework for emerging groups of ecologically important marine gammaproteobacteria based on the reconstruction of evolutionary relationships using genome-scale data. Front. Microbiol. 9, 281 (2015).
Google Scholar 
98.Preston, G. M. Metropolitan microbes: type III secretion in multi-host symbionts. Cell Host Microbe 2, 291–294 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
99.Lutz, A., Raina, J.-B., Motti, C. A., Miller, D. J. & van Oppen, M. J. H. Host coenzyme Q redox state is an early biomarker of thermal stress in the coral Acropora millepora. PLoS ONE 10, e0139290 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
100.Smith, D. J., Suggett, D. J. & Baker, N. R. Is photoinhibition of zooxanthellae photosynthesis the primary cause of thermal bleaching in corals? Glob. Chang. Biol. 11, 1–11 (2005).ADS 
Article 

Google Scholar 
101.Gardner, S. G. et al. A multi-trait systems approach reveals a response cascade to bleaching in corals. BMC Biol. 15, 1–14 (2017).Article 
CAS 

Google Scholar 
102.Lema, K. A., Bourne, D. G. & Willis, B. L. Onset and establishment of diazotrophs and other bacterial associates in the early life history stages of the coral Acropora millepora. Mol. Ecol. 23, 4682–4695 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
103.Pogoreutz, C. et al. Nitrogen fixation aligns with nifH abundance and expression in two coral trophic functional groups. Front. Microbiol. 8, 1187 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
104.Marangoni, L. F. et al. Peroxynitrite generation and increased heterotrophic capacity are linked to the disruption of the coral–dinoflagellate symbiosis in a scleractinian and hydrocoral species. Microorganisms 7, 426 (2019).PubMed Central 
Article 
CAS 

Google Scholar 
105.Quigley, K. M., Alvarez Roa, C., Torda, G., Bourne, D. G. & Willis, B. L. Co‐dynamics of Symbiodiniaceae and bacterial populations during the first year of symbiosis with Acropora tenuis juveniles. MicrobiologyOpen 9, e959 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
106.Dubé, C. E., Mercière, A., Vermeij, M. J. A. & Planes, S. Population structure of the hydrocoral Millepora platyphylla in habitats experiencing different flow regimes in Moorea, French Polynesia. PLoS ONE 12, e0173513 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
107.Agostini, S. et al. Biological and chemical characteristics of the coral gastric cavity. Coral Reefs 31, 147–156 (2012).ADS 
Article 

Google Scholar 
108.Williams, A. D., Brown, B. E., Putchim, L. & Sweet, M. J. Age-related shifts in bacterial diversity in a reef coral. PLoS ONE 10, e0144902 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
109.Sweet, M. J., Brown, B. E., Dunne, R. P., Singleton, I. & Bulling, M. Evidence for rapid, tide-related shifts in the microbiome of the coral Coelastrea aspera. Coral Reefs 36, 815–828 (2017).ADS 
Article 

Google Scholar 
110.Dubé, C. E., Boissin, E., Mercière, A. & Planes, S. Parentage analyses identify local dispersal events and sibling aggregations in a natural population of Millepora hydrocorals, a free‐spawning marine invertebrate. Mol. Ecol. 29, 1508–1522 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
111.Abràmoff, M. D., Magalhães, P. J. & Ram, S. J. Image processing with ImageJ. Biophotonics Int. 11, 36–42 (2004).
Google Scholar 
112.Dubé, C. E., Planes, S., Zhou, Y., Berteaux-Lecellier, V. & Boissin, E. Genetic diversity and differentiation in reef-building Millepora species, as revealed by cross-species amplification of fifteen novel microsatellite loci. PeerJ 5, e2936 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
113.Arnaud-Haond, S. & Belkhir, K. GENCLONE: A computer pro- gram to analyze genotypic data, test for clonality and describe spatial clonal organization. Mol. Ecol. Notes 7, 15–17 (2007).CAS 
Article 

Google Scholar 
114.Peakall, R. & Smouse, P. E. GENALEX 6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295 (2006).Article 

Google Scholar 
115.Wickham, H. ggplot2: Elegant Graphics for Data Analysis. (Springer, 2016).116.R Development Core Team. R: A language and environment for statistical computing (ISBN 3-900051-07-0, http://www.R-project.org/ (R Foundation for Statistical Computing, 2020).117.Andersson, A. F. et al. Comparative analysis of human gut microbiota by barcoded pyrosequencing. PloS ONE 3, e2836 (2008).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
118.Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
119.Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
120.Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79, 5112–5120 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
121.Pedregosa, F. et al. Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).MathSciNet 
MATH 

Google Scholar 
122.Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 1–17 (2018).Article 

Google Scholar 
123.Yilmaz, P. et al. The SILVA and “All-species Living Tree Project (LTP)” taxonomic frameworks. Nucl. Acids Res. 42, D643–D648 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
124.Oksanen, J. et al. vegan: Community Ecology Package (2018).125.Weerdt, W. H. Transplantation experiments with Caribbean Millepora species (Hydrozoa, Coelenterata), including some ecological observations on growth forms. Bijdr. Dierkd. 51, 1–19 (1981).Article 

Google Scholar 
126.Cáceres, M. D. & Legendre, P. Associations between species and groups of sites: indices and statistical inference. Ecology 90, 3566–3574 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
127.Langille, M. G. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
128.Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60 (2011).PubMed 
PubMed Central 
Article 

Google Scholar  More

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

One of the striking features of the Anthropocene is a rapid degradation of natural ecosystems1,2, and an alarming decline of many species, which ultimately may lead to extinctions3,4,5. Whereas conserving ecosystem functions is increasingly recognised as a vital need for humans6,7,8, the interspecific interactions underpinning these functions are poorly understood9,10. However, conserving such interactions can be particularly important when taxa providing high-value ecosystem services are involved10,11.Ground beetles (Coleoptera: Carabidae) have been long known for their benefits in agroecosystems12,13. They play an important role in suppressing pests14, but several carabid species also consume seeds of herbaceous plants, making them a valuable asset for weed control as well15.Fungi are also of vital significance in most of the world’s terrestrial ecosystems16. Mycorrhizal fungi improve nutrient uptake by a large range of plant species through intimate and specialised associations17, other fungi play a crucial role in decomposition18, and yet others are pathogens of both crops and pests in agroecosystems19. Fungal parasitism is one of the crucial agents of evolution20.Fungi and carabids often co-occur, and they can potentially interact in many ways. The soil environment carabids often inhabit is a reservoir of fungal propagules where the beetles can feed on spores, hyphae or fruiting bodies21. They may also be responsible for dispersal of spores of certain fungi22. Several parasitic or entomopathogenic fungi are in an obligatory relationship with their beetle hosts23, therefore, the population decline of a ground beetle species could potentially lead to overlooked extinction cascades24. However, our knowledge of the fungal-carabid interactions is still limited concerning the frequency of these interactions and on how their exact nature affect the parties involved. Indeed, we do not even have a catalogue of the carabid-fungi interactions, and they have not yet been organized into a comprehensive database. Such a database would be of particular importance from an integrated pest management point of view because both fungi and carabids can deliver ecosystem services, but how their interactions, and potential synergies or antagonisms, influence the delivery of these services is poorly understood.In order to have a detailed overview of the interactions between Carabidae and the fungal kingdom, we collated a database containing previously reported associations between these taxa. Carabid and fungal species involved in the interaction, the type of the interaction (e. g. parasitic, pathogenic, mutualistic, or trophic interactions), the location (country) the interaction was reported from, and the publication source combined with detailed notes to each questionable entry comprised one record. Publications available in printed formats only were either digitized and data were extracted using semi-automatic text-mining processes, or they were manually screened. We aimed at possible completeness, using a wide range of databases and search engines and several languages to cover most of the published literature.Both ground beetle and fungal names were validated and their higher taxonomical classifications were also extracted. When it was possible, historical localities were converted to their current country names. The full bibliographical details were also stored in the database.The database covers a time-period from 1793 to 2020, spans over all geographic sub-regions defined by the United Nations (“UNSD — Methodology”, unstats.un.org. Retrieved 2020–10–11) with recorded associations from 129 countries. Our effort yielded 3,378 unique associations in 5,564 records between 1,776 carabid and 676 fungal species. Although rapidly developing molecular methods have largely facilitated the mapping of complex interaction networks in ecological studies25,26,27, due to the historic nature of our dataset, most of the records rely on traditional taxonomical identification. Yet, 16 records were based purely on metabarcoding studies; comments linked to these associations clearly identify them.Whilst we found relatively few pathogenic interactions, a great diversity between ectoparasitic Laboulbeniales fungi and carabids was revealed (Fig. 1). Soft bodied, cave-dwelling members of the Trechinae subfamily were particularly prone to these parasitic infections. Little information was available on mutualistic relationships but the presence of Yarrowia yeast reported from the gut of several carabid species28 is probably beneficial for both parties. The data show two distinct peaks in publications registering new associations, in the early 19th century and in the late 20th century (Fig. 2a) but the steady increase in the cumulative number of associations (Fig. 2b) suggests that further research is required to fully resolve this association network. Although we believe that most of the data published so far were collected, data submission will remain open to researchers wishing to contribute.Fig. 1The number of unique associations between Carabidae subfamilies and fungal classes. Side bar plots show the number of species in each subfamily/class recorded in our dataset.Full size imageFig. 2The number of recorded unique associations over time. Changes in the number of new records (a) and in the cumulative number (b) per year. Dark green lines indicate smoothed trends.Full size image More

1.Christie, K. S., Gilbert, S. L., Brown, C. L., Hatfield, M. & Hanson, L. Unmanned aircraft systems in wildlife research: Current and future applications of a transformative technology. Front. Ecol. Environ. 14, 241–251 (2016).Article 

Google Scholar 
2.Anderson, K. & Gaston, K. J. Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Front. Ecol. Environ. 11, 138–146 (2013).Article 

Google Scholar 
3.Chabot, D. & Bird, D. M. Wildlife research and management methods in the 21st century: Where do unmanned aircraft fit in?. J. Unmanned Veh. Syst. 3, 137–155 (2015).Article 

Google Scholar 
4.Sasse, D. B. Job-related mortality of wildlife workers in the United States, 1937–2000. Wildl. Soc. Bull. 4, 1015–1020 (2003).
Google Scholar 
5.Wiegmann, D. A. & Taneja, N. Analysis of injuries among pilots involved in fatal general aviation airplane accidents. Accid. Anal. Prev. 35, 571–577 (2003).PubMed 
Article 
PubMed Central 

Google Scholar 
6.Vas, E., Lescroël, A., Duriez, O., Boguszewski, G. & Grémillet, D. Approaching birds with drones: first experiments and ethical guidelines. Biol. Lett. 11, 20140754 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
7.Hodgson, J. C., Baylis, S. M., Mott, R., Herrod, A. & Clarke, R. H. Precision wildlife monitoring using unmanned aerial vehicles. Sci. Rep. 6, 22574. https://doi.org/10.1038/srep22574 (2016).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
8.Egan, C. C., Blackwell, B. F., Fernández-Juricic, E. & Klug, P. E. Testing a key assumption of using drones as frightening devices: Do birds perceive drones as risky?. The Condor 122, 1–15. https://doi.org/10.1093/condor/duaa014 (2020).Article 

Google Scholar 
9.Hahn, N. et al. Unmanned aerial vehicles mitigate human–elephant conflict on the borders of Tanzanian Parks: A case study. Oryx 51, 513–516 (2017).Article 

Google Scholar 
10.FAA. Protocol for the Conduct and Review of Wildlife Hazard Site Visits, Wildlife Hazard Assessments, and Wildlife Hazard Management Plan. (2018).11.Dolbeer, R. A., Begier, M. J., Miller, P. R., Weller, J. R. & Anderson, A. L. Wildlife strikes to civil aircraft in the United States 1990–2019. 124 (Federal Aviation Administration, Washington, D.C., USA, 2021).12.Bivings, A. in Bird Strike Committee Europe. 481–487.13.Wandrie, L. J., Klug, P. E. & Clark, M. E. Evaluation of two unmanned aircraft systems as tools for protecting crops from blackbird damage. Crop Prot. 117, 15–19 (2019).Article 

Google Scholar 
14.Ydenberg, R. C. & Dill, L. M. The economics of fleeing from predators. Adv. Study Behav. 16, 229–249 (1986).Article 

Google Scholar 
15.Cooper, W. E., Samia, D. S. & Blumstein, D. T. Chapter five-FEAR, spontaneity, and artifact in economic escape theory: A review and prospectus. Adv. Study Behav. 47, 147–179 (2015).Article 

Google Scholar 
16.Lima, S. L., Blackwell, B. F., DeVault, T. L. & Fernandez-Juricic, E. Animal reactions to oncoming vehicles: A conceptual review. Biol. Rev. Camb. Philos. Soc. 90, 60–76. https://doi.org/10.1111/brv.12093 (2015).Article 
PubMed 

Google Scholar 
17.Bernhardt, G. E., Blackwell, B. F., DeVault, T. L. & Kutschbach-Brohl, L. Fatal injuries to birds from collisions with aircraft reveal anti-predator behaviours. Ibis https://doi.org/10.1111/j.1474-919X.2010.01043.x (2010).Article 

Google Scholar 
18.McEvoy, J. F., Hall, G. P. & McDonald, P. G. Evaluation of unmanned aerial vehicle shape, flight path and camera type for waterfowl surveys: Disturbance effects and species recognition. PeerJ 4, e1831 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
19.Mulero-Pázmány, M. et al. Unmanned aircraft systems as a new source of disturbance for wildlife: A systematic review. PLoS ONE 12, e0178448 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
20.Tinbergen, N. Social releasers and the experimental method required for their study. Wilson Bull., 6–51 (1948).21.Kirk, D. A. & Mossman, M. J. in Bird of the World (ed Cornell Lab of Ornithology) (Poole, A.F.,Gill, F.B., Ithaca, NY, USA, 2020).22.FAA. Wildlife Strike Database, wildlife.faa.gov (2020).23.DeVault, T. L. et al. Estimating interspecific economic risk of bird strikes with aircraft. Wildl. Soc. Bull. 42, 94–101 (2018).Article 

Google Scholar 
24.DeVault, T. L., Blackwell, B. F., Seamans, T. W. & Belant, J. L. Identification of off airport interspecific avian hazards to aircraft. J. Wildl. Manag. 80, 746–752 (2016).Article 

Google Scholar 
25.Kluever, B. M., Pfeiffer, M. B., Barras, S. C., Dunlap, B. G. & Humberg, L. A. Black vulture conflict and management in the United States: Damage trends, management overview, and research needs. Hum. Wildl. Interact. 14, 8 (2020).
Google Scholar 
26.Walters, J. R. Anti-predatory behavior of lapwings: field evidence of discriminative abilities. Wilson Bull., 49–70 (1990).27.Septon, G. Peregrine falcon strikes turkey vulture. Passenger Pigeon 53, 192 (1991).
Google Scholar 
28.Coleman, J. S. & Fraser, J. D. Predation on black and Turkey vultures. Wilson Bull. 98, 600–601 (1986).
Google Scholar 
29.Rush, G. P., Clarke, L. E., Stone, M. & Wood, M. J. Can drones count gulls? Minimal disturbance and semiautomated image processing with an unmanned aerial vehicle for colony-nesting seabirds. Ecol. Evol. 8, 12322–12334 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
30.Bennitt, E., Bartlam-Brooks, H. L. A., Hubel, T. Y. & Wilson, A. M. Terrestrial mammalian wildlife responses to unmanned aerial systems approaches. Sci. Rep. 9, 2142. https://doi.org/10.1038/s41598-019-38610-x (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
31.Weston, M. A., O’Brien, C., Kostoglou, K. N. & Symonds, M. R. Escape responses of terrestrial and aquatic birds to drones: Towards a code of practice to minimize disturbance. J. Appl. Ecol. 57, 777–785 (2020).Article 

Google Scholar 
32.Belant, J. L., Seamans, T. W., Gabrey, S. W. & Dolbeer, R. A. Abundance of gulls and other birds at landfills in northern Ohio. Am. Midl. Nat. 134, 30–40 (1995).Article 

Google Scholar 
33.Barnas, A. F. et al. A standardized protocol for reporting methods when using drones for wildlife research. J. Unmanned Veh. Syst. 8, 89–98 (2020).Article 

Google Scholar 
34.DeVault, T. L., Blackwell, B. F., Seamans, T. W., Lima, S. L. & Fernández-Juricic, E. Effects of vehicle speed on flight initiation by turkey vultures: implications for bird-vehicle collisions. PLoS ONE 9, e87944 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
35.Doppler, M. S., Blackwell, B. F., DeVault, T. L. & Fernández-Juricic, E. Cowbird responses to aircraft with lights tuned to their eyes: Implications for bird–aircraft collisions. The Condor 117, 165–177 (2015).Article 

Google Scholar 
36.Blackwell, B. F., Fernandez-Juricic, E., Seamans, T. W. & Dolan, T. Avian visual system configuration and behavioural response to object approach. Anim. Behav. 77, 673–684 (2009).Article 

Google Scholar 
37.DeVault, T. L., Reinhart, B. D., Brisbin, I. L., Rhodes, O. E. & Bechard. Flight Behavior of Black and Turkey Vultures: Implications for reducing bird–aircraft collisions. J. Wildl. Manag. 69, 601–608. https://doi.org/10.2193/0022-541X(2005)069[0601:FBOBAT]2.0.CO;2 (2005).38.Runyan, A. M. & Blumstein, D. T. Do individual differences influence flight initiation distance?. J. Wildl. Manag. 68, 1124–1129 (2004).Article 

Google Scholar 
39.Rebolo-Ifrán, N., Grilli, M. G. & Lambertucci, S. A. Drones as a threat to wildlife: YouTube complements science in providing evidence about their effect. Environ. Conserv. 46, 205–210 (2019).Article 

Google Scholar 
40.Fernández-Juricic, E., Deisher, M., Stark, A. C. & Randolet, J. Predator detection is limited in microhabitats with high light intensity: An experiment with Brown-headed Cowbirds. Ethology 118, 341–350 (2012).Article 

Google Scholar 
41.Koch, D. D. Glare and contrast sensitivity testing in cataract patients. J. Cataract Refract. Surg. 15, 158–164 (1989).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
42.Vorobyev, M. & Osorio, D. Receptor noise as a determinant of colour thresholds. Proc. Royal Soc. B. 265, 351–358 (1998).CAS 
Article 

Google Scholar 
43.Ödeen, A. & Håstad, O. The phylogenetic distribution of ultraviolet sensitivity in birds. BMC Evol. Biol. 13, 36 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
44.Hill, G. E., Hill, G. E., McGraw, K. J. & Kevin, J. Bird coloration: mechanisms and measurements. Vol. 1 (Harvard University Press, 2006).45.Maia, R., Eliason, C. M., Bitton, P. P., Doucet, S. M. & Shawkey, M. D. pavo: Asn R package for the analysis, visualization and organization of spectral data. Methods Ecol. Evol. 4, 906–913 (2013).
Google Scholar 
46.Lakens, D. Sample Size Justification. (2021).47.Nakagawa, S. & Cuthill, I. C. Effect size, confidence interval and statistical significance: a practical guide for biologists. Biol. Rev. 82, 591–605 (2007).PubMed 
PubMed Central 
Article 

Google Scholar 
48.Hurlbert, S. H. Pseudoreplication and the design of ecological field experiments. Ecol. Monogr. 54, 187–211. https://doi.org/10.2307/1942661 (1984).Article 

Google Scholar 
49.Garamszegi, L. Z. A simple statistical guide for the analysis of behaviour when data are constrained due to practical or ethical reasons. Anim. Behav. 120, 223–234 (2016).Article 

Google Scholar 
50.Burnham, K. P. & Anderson, D. R. Model selection and multimodel inference: a practical information-theoretic approach. (Springer Science & Business Media, 2002).51.Nauman, L. E. Spatial distribution in a turkey vulture roost, The Ohio State University, (1965).52.Bertram, B. C. Living in groups: predators and prey. Behavioural ecology: an evolutionary approach, 221–248 (1978).53.Blackwell, B. F. et al. Social information affects Canada goose alert and escape responses to vehicle approach: Implications for animal–vehicle collisions. PeerJ 7, e8164. https://doi.org/10.7717/peerj.8164 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
54.Blackwell, B. F., Seamans, T. W., Fernández-Juricic, E., Devault, T. L. & Outward, R. J. Avian responses to aircraft in an airport environment. J. Wildl. Manag. 83, 893–901 (2019).Article 

Google Scholar 
55.Beauchamp, G. Social predation: how group living benefits predators and prey. (Elsevier, 2013).56.Fox, J., Friendly, M. & Weisberg, S. Hypothesis tests for multivariate linear models using the car package. The R Journal 5, 39–52 (2013).Article 

Google Scholar 
57.Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. arXiv preprint arXiv:1406.5823(2014).58.DeVault, T. L., Blackwell, B. F., Seamans, T. W., Lima, S. L. & Fernandez-Juricic, E. Speed kills: Ineffective avian escape responses to oncoming vehicles. Proc. R. Soc. B. 282, 20142188. https://doi.org/10.1098/rspb.2014.2188 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
59.DeVault, T. L. et al. Can experience reduce collisions between birds and vehicles?. J. Zool. 301, 17–22. https://doi.org/10.1111/jzo.12385 (2016).Article 

Google Scholar 
60.Rhoades, E. & Blumstein, D. T. Predicted fitness consequences of threat-sensitive hiding behavior. Behav. Ecol. 18, 937–943 (2007).Article 

Google Scholar 
61.Cooper Jr, W. E. Factors affecting risk and cost of escape by the broad-headed skink (Eumeces laticeps): predator speed, directness of approach, and female presence. Herpetologica, 464–474 (1997).62.Cooper, W. E. Jr., Hawlena, D. & Pérez-Mellado, V. Interactive effect of starting distance and approach speed on escape behavior challenges theory. Behav. Ecol. 20, 542–546 (2009).Article 

Google Scholar 
63.Fernández-Juricic, E., Jimenez, M. D. & Lucas, E. Alert distance as an alternative measure of bird tolerance to human disturbance: Implications for park design. Environ. Conserv. 28, 263–269. https://doi.org/10.1017/S0376892901000273 (2001).Article 

Google Scholar 
64.Dill, L. M. The escape response of the zebra danio (Brachydanio rerio) I. The stimulus for escape. Anim. Behav. 22, 711–722 (1974).Article 

Google Scholar 
65.Sun, H. & Frost, B. J. Computation of different optical variables of looming objects in pigeon nucleus rotundus neurons. Nat. Neurosci. 1, 296–303 (1998).CAS 
PubMed 
Article 

Google Scholar 
66.Pfeiffer, M. B., Iglay, R. B., Seamans, T. W., Blackwell, B. F. & DeVault, T. L. Deciphering interactions between white-tailed deer and approaching vehicles. Transp. Res. D Transp. Environ. 79, 102251. https://doi.org/10.1016/j.trd.2020.102251 (2020).Article 

Google Scholar 
67.Collins, S. A., Giffin, G. J. & Strong, W. T. Using flight initiation distance to evaluate responses of colonial-nesting Great Egrets to the approach of an unmanned aerial vehicle. J. Field. Ornithol. 90, 382–390 (2019).Article 

Google Scholar 
68.Kane, S. A., Fulton, A. H. & Rosenthal, L. J. When hawks attack: Animal-borne video studies of goshawk pursuit and prey-evasion strategies. J. Exp. Biol. 218, 212–222 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
69.Frid, A. & Dill, L. Human-caused disturbance stimuli as a form of predation risk. Conserv. Ecol. 6 (2002).70.Lambertucci, S. A., Shepard, E. L. & Wilson, R. P. Human-wildlife conflicts in a crowded airspace. Science 348, 502–504 (2015).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
71.Ballejo, F., Plaza, P., Speziale, K. L., Lambertucci, A. P. & Lambertucci, S. A. Plastic ingestion and dispersion by vultures may produce plastic islands in natural areas. Sci. Total Environ. 755, 142421. https://doi.org/10.1016/j.scitotenv.2020.142421 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
72.Conover, M. R. Resolving human-wildlife conflicts: the science of wildlife damage management. (CRC press, 2001).73.Pfeiffer, M. B., Blackwell, B. F. & DeVault, T. L. Collective effect of landfills and landscape composition on bird–aircraft collisions. Hum.–Wildl. Interact. 14, 43–54 (2020).74.Dolbeer, R. A. Aerodrome bird hazard prevention: case study at John F. Kennedy International Airport. (1999).75.Blackwell, B. F. et al. Exploiting avian vision with aircraft lighting to reduce bird strikes. J. Appl. Ecol. 49, 758–766 (2012).Article 

Google Scholar 
76.Goller, B., Blackwell, B. F., DeVault, T. L., Baumhardt, P. E. & Fernández-Juricic, E. Assessing bird avoidance of high-contrast lights using a choice test approach: Implications for reducing human-induced avian mortality. PeerJ 6, e5404 (2018).PubMed 
PubMed Central 
Article 

Google Scholar  More