Philippa Kaur

1.O’Connor. Whale Watching Worldwide: Tourism Numbers, Expenditures and Expanding Economic Benefits. A special report from the International Fund for Animal Welfare Yarmouth, USA. Prepared by Economists at Large. www.ecolarge.com (2009). Accessed 15 Apr 2021.2.Cisneros-Montemayor, A. M., Sumaila, U. R., Kaschner, K. & Pauly, D. The global potential for whale watching. Mar. Policy 34, 1273–1278 (2010).Article 

Google Scholar 
3.Parsons, E. C. M. The negative impacts of whale-watching. J. Mar. Biol. 2012, 1–9 (2012).ADS 
Article 

Google Scholar 
4.Hoyt, E. & Hvenegaard, G. T. A review of whale-watching and whaling. Coast. Manag. 30, 381–399 (2002).Article 

Google Scholar 
5.Cunningham, P. A., Huijbens, E. H. & Wearing, S. L. From whaling to whale watching: Examining sustainability and cultural rhetoric. J. Sustain. Tour. 20, 143–161 (2012).Article 

Google Scholar 
6.Senigaglia, V. et al. Meta-analyses of whale-watching impact studies: Comparisons of cetacean responses to disturbance. Mar. Ecol. Prog. Ser. 542, 251–263 (2016).ADS 
CAS 
Article 

Google Scholar 
7.Bejder, L. et al. Decline in relative abundance of bottlenose dolphins exposed to long-term disturbance. Conserv. Biol. 20, 1791–1798 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
8.Lusseau, D., Slooten, L. & Currey, R. J. C. Unsustainable dolphin-watching tourism in Fiordland, New Zealand. Tour. Mar. Environ. 3, 173–178 (2006).Article 

Google Scholar 
9.Erbe, C. Underwater noise of whale-watching boats and potential effects on killer whales (Orcinus orca), based on an acoustic impact model. Mar. Mamm. Sci. 18, 394–418 (2002).Article 

Google Scholar 
10.Sprogis, K. R., Videsen, S. & Madsen, P. T. Vessel noise levels drive behavioural responses of humpback whales with implications for whale-watching. Elife 9, 1–17 (2020).Article 

Google Scholar 
11.Au, W. W. L. The Sonar of Dolphins (Springer, 1993).Book 

Google Scholar 
12.Tyack, P. L. & Clark, C. W. Communication and acoustic behavior of dolphins and whales. In Hearing by Whales and Dolphins (eds. Au, W. W. L., Fay, R. R. & Popper, A. N.) 156–224 (Springer, 2000). https://doi.org/10.1007/978-1-4612-1150-1_4.13.Lesage, V., Barrette, C., Kingsley, M. C. S. & Sjare, B. The effect of vessel noise on the vocal behavior of belugas in the St. Lawrence River estuary, Canada. Mar. Mamm. Sci. 15, 65–84 (1999).Article 

Google Scholar 
14.Jensen, F. H. et al. Vessel noise effects on delphinid communication. Mar. Ecol. Prog. Ser. 395, 161–175 (2009).ADS 
Article 

Google Scholar 
15.Pirotta, E. et al. Vessel noise affects beaked whale behavior: Results of a dedicated acoustic response study. PLoS One 7, e42535 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
16.Slabbekoorn, H. et al. A noisy spring: The impact of globally rising underwater sound levels on fish. Trends Ecol. Evol. 25, 419–427 (2010).PubMed 
Article 

Google Scholar 
17.Andrew, R. K., Howe, B. M. & Mercer, J. A. Long-time trends in ship traffic noise for four sites off the North American West Coast. J. Acoust. Soc. Am. 129, 642–651 (2011).ADS 
PubMed 
Article 

Google Scholar 
18.Miksis-Olds, J. L. & Nichols, S. M. Is low frequency ocean sound increasing globally?. J. Acoust. Soc. Am. 139, 501–511 (2016).ADS 
PubMed 
Article 

Google Scholar 
19.Payne, R. & Webb, D. Orientation by means of long range acoustic signaling in Baleen whales. Ann. N. Y. Acad. Sci. 188, 110–141 (1971).ADS 
CAS 
PubMed 
Article 

Google Scholar 
20.Melcón, M. L. et al. Blue whales respond to anthropogenic noise. PLoS One 7, e32681 (2012).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
21.Romagosa, M. et al. Underwater ambient noise in a baleen whale migratory habitat off the Azores. Front. Mar. Sci. 4, 1–14 (2017).Article 

Google Scholar 
22.Aguilar Soto, N. et al. Does intense ship noise disrupt foraging in deep-diving cuvier’s beaked whales (Ziphius cavirostris)?. Mar. Mamm. Sci. 22, 690–699 (2006).Article 

Google Scholar 
23.Wisniewska, D. M. et al. High rates of vessel noise disrupt foraging in wild harbour porpoises (Phocoena phocoena). Proc. R. Soc. B Biol. Sci. 285, 20172314 (2018).Article 

Google Scholar 
24.Hermannsen, L., Beedholm, K., Tougaard, J. & Madsen, P. T. High frequency components of ship noise in shallow water with a discussion of implications for harbor porpoises (Phocoena phocoena). J. Acoust. Soc. Am. 136, 1640–1653 (2014).ADS 
PubMed 
Article 

Google Scholar 
25.Wladichuk, J., Hannay, D. E., MacGillivray, A. O., Li, Z. & Thornton, S. J. Systematic source level measurements of whale watching vessels and other small boats. J. Ocean Technol. 14, 108–126 (2019).
Google Scholar 
26.Arranz, P., Aguilar de Soto, N., Madsen, P. T. & Sprogis, K. R. Whale-watch vessel noise levels with applications to whale-watching guidelines and conservation. Mar. Policy 134, 104776 (2021).Article 

Google Scholar 
27.Higham, J., Bejder, L. & Williams, R. Whale-Watching: Sustainable Tourism and Ecological Management (Cambridge University Press, 2014).Book 

Google Scholar 
28.Montero, R. & Arechavaleta, M. Distribution patterns: Relationships between depths, sea surface temperature, and habitat use of Short-finned pilot whales south-west of Tenerife. Eur. Res. Cetaceans 10, 193–198 (1996).
Google Scholar 
29.Servidio, A. et al. Site fidelity and movement patterns of short-finned pilot whales within the Canary Islands: Evidence for resident and transient populations. Aquat. Conserv. Mar. Freshw. Ecosyst. 29, 227–241 (2019).Article 

Google Scholar 
30.Würsig, B. Ethology and Behavioral Ecology of Odontocetes (Springer, 2019). https://doi.org/10.1007/978-3-030-16663-2_23.Book 

Google Scholar 
31.Sequeira, M. et al. Review of whalewatching activities in mainland Portugal, the Azores, Madeira and Canary archipelagos and the Strait of Gibraltar. J. Cetacean Res. Manag. SC61/WW11, 1–40 (2009).
32.IWC whale-watching handbook. https://wwhandbook.iwc.int/es/case-studies/canary-islands-spain#Accessed 15 Apr 2021.33.Hoyt, E. Tourism. In Encyclopedia of Marine Mammals 1010–1014 (2018). https://doi.org/10.1016/B978-0-12-804327-1.00262-4.
34.Kasuya, T. & Matsui, S. Age determination and growth of the short-finned pilot whale off the Pacific coast of Japan. Sci. Rep. Whales Res. Inst. 35, 57–91 (1984).
Google Scholar 
35.Reddy, M., Kamolnick, T., Skaar, D., Curry, C. & Ridgway, S. Bottlenose dolphins: Energy consumption during pregnancy, lactation, and growth. Int. Mar. Mammal Trainers Assoc. Conf. Proc. 30–37 (1991).36.Srinivasan, M., Swannack, T. M., Grant, W. E., Rajan, J. & Würsig, B. To feed or not to feed? Bioenergetic impacts of fear-driven behaviors in lactating dolphins. Ecol. Evol. 8, 1384–1398 (2018).PubMed 
Article 

Google Scholar 
37.Marsh, H. & Kasuya, T. Changes in the role of a female pilot whale with age. In Dolphin Societies (eds. Pryor, K. & Norris, K.S.) 281–286 (University of California Press, 1991).38.Augusto, J. F., Frasier, T. R. & Whitehead, H. Characterizing alloparental care in the pilot whale (Globicephala melas) population that summers off Cape Breton, Nova Scotia, Canada. Mar. Mamm. Sci. 33, 440–456 (2017).Article 

Google Scholar 
39.Quick, N., Scott-hayward, L., Sadykova, D., Nowacek, D. & Read, A. Effects of a scientific echo sounder on the behavior of short-finned pilot whales (Globicephala macrorhynchus). Can. J. Fish. Aquat. Sci. 74, 716–726 (2017).Article 

Google Scholar 
40.Würsig, B. & Jefferson, T. A. Methods of photo-identification for small cetaceans. Report of the International Whaling Commission (1990).41.Greenhow, D. R., Brodsky, M. C., Lingenfelser, R. G. & Mann, D. A. Hearing threshold measurements of five stranded short-finned pilot whales (Globicephala macrorhynchus). J. Acoust. Soc. Am. 135, 531–536 (2014).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
42.Tougaard, J. & Beedholm, K. Practical implementation of auditory time and frequency weighting in marine bioacoustics. Appl. Acoust. 145, 137–143 (2019).Article 

Google Scholar 
43.Pérez, J. M., Jensen, F. H., Rojano-Doñate, L. & Aguilar de Soto, N. Different modes of acoustic communication in deep-diving short-finned pilot whales (Globicephala macrorhynchus). Mar. Mamm. Sci. 33, 59–79 (2017).Article 

Google Scholar 
44.Pacini, A. F. et al. Audiogram of a formerly stranded long-finned pilot whale (Globicephala melas) measured using auditory evoked potentials. J. Exp. Biol. 213, 3138–3143 (2010).CAS 
PubMed 
Article 

Google Scholar 
45.Christiansen, F., Rojano-Doñate, L., Madsen, P. T. & Bejder, L. Noise levels of multi-rotor unmanned aerial vehicles with implications for potential underwater impacts on marine mammals. Front. Mar. Sci. 3, 1–9 (2016).Article 

Google Scholar 
46.Christiansen, F., Nielsen, M. L. K., Charlton, C., Bejder, L. & Madsen, P. T. Southern right whales show no behavioral response to low noise levels from a nearby unmanned aerial vehicle. Mar. Mamm. Sci. 36, 953–963 (2020).Article 

Google Scholar 
47.Giles, A. B. et al. Responses of bottlenose dolphins (Tursiops spp.) to small drones. Aquat. Conserv. Mar. Freshw. Ecosyst. 31, 677–684 (2021).Article 

Google Scholar 
48.Nielsen, M. L. K., Sprogis, K. R., Bejder, L., Madsen, P. T. & Christiansen, F. Behavioural development in southern right whale calves. Mar. Ecol. Prog. Ser. 629, 219–234 (2019).ADS 
Article 

Google Scholar 
49.Hofmann, B., Scheer, M. & Behr, I. P. Underwater behaviors of short-finned pilot whales (Globicephala macrorhynchus) off Tenerife. Mammalia 68, 221–224 (2004).Article 

Google Scholar 
50.Lockyer, C. All creatures great and smaller: A study in cetacean life history energetics. J. Mar. Biol. Assoc. U. K. 87, 1035–1045 (2007).Article 

Google Scholar 
51.Hin, V., Harwood, J. & de Roos, A. M. Bio-energetic modeling of medium-sized cetaceans shows high sensitivity to disturbance in seasons of low resource supply. Ecol. Appl. 29, 1–19 (2019).Article 

Google Scholar 
52.Christiansen, F., Rasmussen, M. H. & Lusseau, D. Inferring energy expenditure from respiration rates in minke whales to measure the effects of whale watching boat interactions. J. Exp. Mar. Biol. Ecol. 459, 96–104 (2014).Article 

Google Scholar 
53.Mann, J., Connor, R. C., Tyack, P. L. & Whitehead, H. Cetacean Societies: Field Studies of Dolphins and Whales (The University of Chicago Press, 2000).
Google Scholar 
54.Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).Article 

Google Scholar 
55.R Development Core Team. R: A Language and Environment for Statistical Computing. (2018).56.National Marine Fisheries Service. Technical guidance for assessing the effects of anthropogenic sound on marine mammal hearing underwater acoustic thresholds for onset of permanent and temporary threshold shifts. NOAA Technical Memorandum NMFS-OPR-55. (2016).57.Heimlich-Boran, J. R. Social Organisation of the Short-finned Pilot Whale, Globicephala macrorhynchus, with Special Reference to the Comparative Social Ecology of Delphinids (University of Cambridge, 1993).
Google Scholar 
58.Hastie, G. D., Wilson, B., Tufft, L. H. & Thompson, P. M. Bottlenose dolphins increase breathing synchrony in response to boat traffic. Mar. Mamm. Sci. 19, 74–084 (2003).Article 

Google Scholar 
59.Williams, R. & Noren, D. P. Swimming speed, respiration rate, and estimated cost of transport in adult killer whales. Mar. Mamm. Sci. 25, 327–350 (2009).Article 

Google Scholar 
60.Senigaglia, V. & Whitehead, H. Synchronous breathing by pilot whales. Mar. Mamm. Sci. 28, 213–219 (2012).Article 

Google Scholar 
61.Aguilar Soto, N. et al. Cheetahs of the deep sea: Deep foraging sprints in short-finned pilot whales off Tenerife (Canary Islands). J. Anim. Ecol. 77, 936–947 (2008).PubMed 
Article 

Google Scholar 
62.Ariza, A. et al. Vertical distribution, composition and migratory patterns of acoustic scattering layers in the Canary Islands. J. Mar. Syst. 157, 82–91 (2016).Article 

Google Scholar 
63.Owen, K., Andrews, R. D., Baird, R. W., Schorr, G. S. & Webster, D. L. Lunar cycles influence the diving behavior and habitat use of short-finned pilot whales around the main Hawaiian Islands. Mar. Ecol. Prog. Ser. 629, 193–206 (2019).ADS 
Article 

Google Scholar 
64.Kasuya, T. & Marsh, H. Life history and reproductive biology of the short-finned pilot whale, Globicephala macrorhynchus, off the Pacific coast of Japan. Rep. Int. Whal. Commun. Spec. Iss. 6, 259–310 (1984).
Google Scholar 
65.Barton, E. et al. The transition zone of the canary current upwelling region. Prog. Ocean. 41, 455–504 (1998).Article 

Google Scholar 
66.Olson, P. A. Pilot Whales: Globicephala melas and G. macrorhynchus. In Encyclopedia of Marine Mammals, 3rd ed (eds. Würsig, B., Thewissen, J. G. M. & Kovacs, K. M.) 701–705 (Academic Press, 2018). https://doi.org/10.1016/B978-0-12-804327-1.00194-1.67.Puig-Lozano, R. et al. Retrospective study of fishery interactions in stranded cetaceans, Canary Islands. Front. Vet. Sci. 7, 1–15 (2020).Article 

Google Scholar 
68.Almunia, J., Delponti, P. & Rosa, F. Using automatic identification system (AIS) data to estimate whale watching effort. Front. Mar. Sci. 8, 827 (2021).Article 

Google Scholar 
69.Schlundt, C. E. et al. Auditory evoked potentials in two short-finned pilot whales (Globicephala macrorhynchus). J. Acoust. Soc. Am. 129, 1111–1116 (2011).ADS 
PubMed 
Article 

Google Scholar 
70.Visser, F. et al. Risso’s dolphins alter daily resting pattern in response to whale watching at the Azores. Mar. Mamm. Sci. 27, 366–381 (2011).Article 

Google Scholar 
71.Constantine, R., Brunton, D. H. & Dennis, T. Dolphin-watching tour boats change bottlenose dolphin (Tursiops truncatus) behaviour. Biol. Conserv. 117, 299–307 (2004).Article 

Google Scholar 
72.Stensland, E. & Berggren, P. Behavioural changes in female Indo-Pacific bottlenose dolphins in response to boat-based tourism. Mar. Ecol. Prog. Ser. 332, 225–234 (2007).ADS 
Article 

Google Scholar 
73.Jensen, F. H., Perez, J. M., Johnson, M., Soto, N. A. & Madsen, P. T. Calling under pressure: Short-finned pilot whales make social calls during deep foraging dives. Proc. R. Soc. B Biol. Sci. 278, 3017–3025 (2011).Article 

Google Scholar 
74.Kiszka, J. J., Caputo, M., Méndez-Fernandez, P. & Fielding, R. Feeding ecology of elusive Caribbean killer whales inferred from bayesian stable isotope mixing models and whalers’ ecological knowledge. Front. Mar. Sci. 8, 1–11 (2021).Article 

Google Scholar 
75.Whitehead, H. Babysitting, dive synchrony, and indications of alloparental care in sperm whales. Behav. Ecol. Sociobiol. 38, 237–244 (1996).Article 

Google Scholar 
76.Konrad, C. M. Kinship in Sperm Whale Society: Effects on Association, Alloparental Care and Vocalization (Dalhousie University, 2017).
Google Scholar 
77.Leung, E. S., Vergara, V. & Barrett-Lennard, L. G. Allonursing in captive belugas (Delphinapterus leucas). Zoo Biol. 29, 633–637 (2010).PubMed 
Article 

Google Scholar 
78.Houston, A. I. & Carbone, C. The optimal allocation of time during the diving cycle. Behav. Ecol. 3, 255–265 (1992).Article 

Google Scholar 
79.Thompson, D. & Fedak, M. A. How long should a dive last? A simple model of foraging decisions by breath-hold divers in a patchy environment. Anim. Behav. 61, 287–296 (2001).Article 

Google Scholar 
80.Aoki, K., Sato, K., Isojunno, S., Narazaki, T. & Miller, P. J. O. High diving metabolic rate indicated by high-speed transit to depth in negatively buoyant long-finned pilot whales. J. Exp. Biol. 220, 3802–3811 (2017).PubMed 
Article 

Google Scholar 
81.New, L. F. et al. The modelling and assessment of whale-watching impacts. Ocean Coast. Manag. 115, 10–16 (2015).Article 

Google Scholar 
82.Parsons, M. J. G., Duncan, A. J., Parsons, S. K. & Erbe, C. Reducing vessel noise: An example of a solar-electric passenger ferry. J. Acoust. Soc. Am. 147, 3575–3583 (2020).ADS 
PubMed 
Article 

Google Scholar 
83.Dale, S. J., Hebner, R. E. & Sulligoi, G. Electric ship technologies. Proc. IEEE 103, 2225–2228 (2015).Article 

Google Scholar 
84.Anwar, S., Zia, M. Y. I., Rashid, M., De Rubens, G. Z. & Enevoldsen, P. Towards ferry electrification in the maritime sector. Energies 13, 1–22 (2020).Article 
CAS 

Google Scholar 
85.Filby, N. E., Christiansen, F., Scarpaci, C. & Stockin, K. A. Effects of swim-with-dolphin tourism on the behaviour of a threatened species, the Burrunan dolphin Tursiops Australis. Endanger. Species Res. 32, 479–490 (2017).Article 

Google Scholar 
86.Sprogis, K. R., Bejder, L., Hanf, D. & Christiansen, F. Behavioural responses of migrating humpback whales to swim-with-whale activities in the Ningaloo Marine Park, Western Australia. J. Exp. Mar. Bio. Ecol. 522, 151254 (2020).Article 

Google Scholar  More

1.Drucker, P. Indians of the Northwest Coast (McGraw-Hill, 1955).Book 

Google Scholar 
2.Kroeber, A. Culture and natural areas of Native North America (University of California Press, 1939).
Google Scholar 
3.Introduction, S. W. In Handbook of North American Indians volume 7: Northwest Coast (ed. Suttles, W.) 1–15 (Smithsonian Institution, 1990).
Google Scholar 
4.Suttles, W. Coping with abundance: subsistence on the Northwest Coast. In Coast Salish Essays (ed. Suttles, W.) (Talon Books, 1987).
Google Scholar 
5.Barnett, H. G. The Coast Salish of British Columbia (University of Oregon Press, 1955).
Google Scholar 
6.Ames, K. The Northwest Coast: Complex hunter-gatherers, ecology, and social evolution. Annu. Rev. Anthropol. 23, 209–229 (1994).Article 

Google Scholar 
7.Carlson, R. L., Szpak, P. & Richards, M. The Pender Canal site and the beginnings of the Northwest Coast cultural system. Can. J. Archaeol. 41, 1–29 (2017).
Google Scholar 
8.Cannon, A. & Yang, D. Y. Early storage and sedentism on the Pacific Northwest Coast: ancient DNA analysis of salmon remains from Namu, British Columbia. Am. Antiquity 71, 123–140 (2006).Article 

Google Scholar 
9.Matson, R. G. The evolution of Northwest Coast subsistence. In Research in Economic Anthropology Supplement 6: Long-Term Subsistence Change in Prehistoric North America (eds Croes, D. et al.) 366–428 (JAI Press Inc., 1992).
Google Scholar 
10.Caldwell, M. et al. A bird’s eye view of northern Coast Salish intertidal resource management features, southern British Columbia. J. Island Coast. Archaeol. 7, 219–233 (2012).Article 

Google Scholar 
11.Caldwell, M. & Lepofsky, D. Indigenous marine resource management on the Northwest Coast of North America. Ecol. Process. 2(1), 12 (2013).
Google Scholar 
12.Croes, D. R. (ed.). The Qwu?gwes Archaeological Site and Fish Trap (45TN240), and Tested Homestead (45TN396), Eleven-year South Puget Sound Community College Summer Field School Investigations with the Squaxin Island Tribe—Final Report. Report on file, Washington State Department of Archaeology and Historic Preservation, Olympia (2013).13.Lepofsky, D. et al. Shellfish mariculture on the Northwest Coast of North America. Am. Antiq. 80, 236–259 (2015).Article 

Google Scholar 
14.Mathews, D. L. & Turner, N. J. Ocean cultures: northwest coast ecosystems and indigenous management systems. In Conservation for the Anthropocene Ocean: Interdisciplinary Science in Support of Nature and People (eds Levin, P. S. & Poe, M. R.) 169–201 (Academic Press, 2017).Chapter 

Google Scholar 
15.Williams, J. Clam gardens: aboriginal mariculture on Canada’s West Coast (New Star Books, 2006).
Google Scholar 
16.Campbell, S. & Butler, V. Archaeological evidence for resilience of Pacific Northwest salmon populations and the socioecological system over the last~7,500 years. Ecol. Soc. 15(1), 17 (2000).Article 

Google Scholar 
17.Thornton, T., Deur, D. & Kitka, H. Cultivation of salmon and other marine resources on the Northwest Coast of North America. Hum. Ecol. 43, 189–199 (2015).Article 

Google Scholar 
18.Thornton, T. The ideology and practice of Pacific Herring cultivation among the Tlingit and Haida. Hum. Ecol. 43, 213–223 (2015).Article 

Google Scholar 
19.Petersen, J. R. et al. Use of the traditional halibut hook of the Makah Tribe, the čibu⋅d, reduces bycatch in recreational halibut fisheries. PeerJ 8, e9288 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
20.Ritchie, M. & Angelbeck, B. “Coyote broke the dams”: Power, reciprocity, and conflict in fish weir narratives and implications for traditional and contemporary fisheries. Ethnohistory 67(2), 191–220 (2020).Article 

Google Scholar 
21.Royle, T. C. A. et al. An efficient and reliable DNA-based sex identification method for archaeological Pacific salmonid (Oncorhynchus spp.) remains. PLoS ONE 13(3), e0193212 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
22.Royle, T. C. A. et al. Investigating the sex-selectivity of a Middle Ontario Iroquoian Atlantic salmon (Salmo salar) and lake trout (Salvelinus namaycush) fishery through ancient DNA analysis. J. Archaeol. Sci. Rep. 31, 102301 (2020).
Google Scholar 
23.George, G. National Energy Board Hearing Order OH-001-2014. Trans Mountain Pipeline ULC. Trans Mountain Expansion Project. Volume 6 (2014).24.Morin, J. Tsleil-Waututh Nation’s History, Culture and Aboriginal Interests in Eastern Burrard Inlet. Report on file, Gowlings, Lafleur, Henderson LLP, Vancouver (2015).25.Suttles, W. Central Coast Salish. In Handbook of North American Indians Volume 7: Northwest Coast (ed. Suttles, W.) 453–475 (Smithsonian Institution, 1990).26.Hancock, M. J. & Marshall, D.E. Catalogue of Salmon Streams and Spawning Escapements of Statistical Area 28 Howe Sound-Burrard Inlet. Canadian Data Report of Fisheries and Aquatic Sciences No. 557 (1986).27.Harris, G. The salmon and trout streams of Vancouver. Waters J. Vanc. Aquar. 3, 4–23 (1978).
Google Scholar 
28.Ricker, W. E. Effects of the Fishery and of Obstacles to Migration on the Abundance of Fraser River Sockeye Salmon (Oncorhynchus nerka). Canadian Technical Report of Fisheries and Aquatic Sciences No. 1522 (1987).29.Charlton, A. S. The Belcarra Park Site. (Department of Archaeology, Simon Fraser University, 1980).30.Lepofsky, D., Trost, D. & Morin, J. Coast Salish interaction: a view from the inlets. Can. J. Archaeol. 31, 190–223 (2007).
Google Scholar 
31.Morin, J., Lepofsky, D., Ritchie, M., Porcic, M. & Edinborough, K. Assessing continuity in the ancestral territory of the Tsleil-Waututh-Coast Salish, southwest British Columbia, Canada. J. Anthropol. Archaeol. 51, 77–87 (2018).Article 

Google Scholar 
32.Morin, J., Muir, B., Ritchie, M. & Sellers, I. Tsleil-Waututh and Simon Fraser University Archaeological Investigations at Port Moody (Reed Point, Shoreline Park, Old Orchard Park, Slaughterhouse Creek, Carraholly Point, and Barnet Beach). Permit 2014–344. Report on file, British Columbia Archaeology Branch, Victoria (2020).33.Harris, C. Voices of disaster: smallpox around the Strait of Georgia in 1782. Ethnohistory 41, 591–626 (1994).Article 

Google Scholar 
34.Chisholm, B. S. Reconstructions of Prehistoric Diet in British Columbia Using Stable-Carbon Isotopic Analysis. PhD dissertation. (Simon Fraser University, 1986).35.Hanson, D. K. Late Prehistoric Subsistence in the Strait of Georgia Region of the Northwest Coast. Master’s thesis. (Simon Fraser University, 1991).36.Trost, T. Forgotten Waters: A Zooarchaeological Analysis of the Cove Cliff Site (DhRr 18), Indian Arm, British Columbia. Master’s thesis. (Simon Fraser University, 2005).37.Pierson, N. Bridging Troubled Waters: Zooarchaeology and Marine Conservation on Burrard Inlet, Southwest British Columbia. Master’s thesis. (Simon Fraser University, 2011).38.Morin, J. et al. DNA-based species identification of ancient salmonid remains provides new insight into pre-contact Coast Salish salmon fisheries in Burrard Inlet, British Columbia, Canada. J. Archaeol. Sci. Rep. 37, 102956 (2021).
Google Scholar 
39.Sproat, G. June 15, 1877. Copy of minute of decision, Joint Indian Reserve Commission. Signed by Dominion Commissioner Alex Anderson, Provincial Commissioner Arch. McKinley and Joint Commissioner G.M. Sproat. Federal set of JIRC’s Minutes and plans, surveyor’s copy. Aboriginal and Northern Affairs Canada, BC Regional Office Specific Claims Branch, Resource Library, Vancouver. AAND Lands and Trusts registration #15215. Also LAC, RG10, Volume 3612, File 3756-23, Reel C10106 (1877).40.Mortimer, H. & George, D. You Call Me Chief: Impressions of the Life of Dan George (Doubleday, 1981).
Google Scholar 
41.Talbot, M. Old Legends and Customs of the British Columbia Coast Indians. s.n., New Westminster (1952).42.Thornton, M. Indian Lives and Legends (Mitchell Press, 1966).
Google Scholar 
43.MacDonald, C., Drake, D., Doerksen, J. & Cotton, M. Between Forest and Sea: Memories of Belcarra (Belcarra Historical Group, 1998).
Google Scholar 
44.Romanoff, S. Fraser Lillooet Fishing. In A Complex Culture of the British Columbia Plateau, Vancouver (ed. Hayden, B.) 222–265 (University of British Columbia Press, 1992).
Google Scholar 
45.Kennedy, D. & Bouchard, R. Sliammon Life, Sliammon Lands (Talonbooks, 1983).
Google Scholar 
46.Mathisen, O. A. The effect of altered sex ratios on the spawning of red salmon. In Studies of Alaska Red Salmon (ed. Koo, T.) 137–246 (University of Washington Press, 1962).
Google Scholar 
47.Reed, W. J. Sex-selective harvesting of Pacific salmon: a theoretically optimal solution. Ecol. Model. 14, 261–271 (1982).Article 

Google Scholar 
48.Salo, E. O. Life history of chum salmon (Oncorhynchus keta). In Pacific Salmon Life Histories (eds Margolis Groot, C. & Margolis, L.) 231–310 (UBC Press, 1991).
Google Scholar 
49.Jenness, D. The Faith of a Coast Salish Indian (British Columbia Provincial Museum, 1955).50.Richling, B. (ed.) The W̲SÁNEĆ and Their Neighbours: Diamond Jenness on the Coast Salish of Vancouver Island, 1935 (Rock’s Mills Press, 2016).51.Dale, C. & Natcher, D. C. What is old is new again: the reintroduction of Indigenous fishing technologies in British Columbia. Local Environ. 20(11), 1309–1321 (2015).Article 

Google Scholar 
52.Ritchie, M. P. & Springer, C. Harrison River Chum Fishery: The Ethnographic and Archaeological Perspective. Report on file, Sts′ailes, Agassiz (2010).53.Simeone, W. E. & Valentine, E. M. Ahtna Knowledge of Long-Term Changes in Salmon runs in the Upper Copper River Drainage, Alaska (Alaska Department of Fish and Game, Division of Subsistence, 2007).54.Langdon, S. J. Traditional Knowledge and Harvesting of Salmon by Huna and Hinyaa Tlingit. (U.S. Fish and Wildlife Service, Office of Subsistence Management, Fisheries Resource Monitoring Program, 2006).55.Ratner, N. C. et al. Local Knowledge, Customary Practices, and Harvest of Sockeye salmon from the Klawock and Sarkar Rivers, Prince of Wales Island, Alaska (Alaska Department of Fish and Game, Division of Subsistence, 2006)56.Curtis, E. The North American Indian: being a series of volumes picturing and describing the Indians of the United States, the Dominion of Canada, and Alaska, Vol. 13 (Plimpton Press, 1924).
Google Scholar 
57.Kennedy, D. & Bouchard, R. Stl’atl’imx fishing. In A Complex Culture of the British Columbia Plateau (ed. Hayden, B.) 266–354 (UBC Press, 1992).
Google Scholar 
58.Yang, D. Y. & Watt, K. Contamination controls when preparing archaeological remains for ancient DNA analysis. J. Archaeol. Sci. 32(3), 331–336 (2005).Article 

Google Scholar 
59.Speller, C. F. et al. High potential for using DNA from ancient herring bones to inform modern fisheries management and conservation. PLoS ONE 7, e51122 (2012).CAS 
PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
60.Yang, D. Y., Eng, B., Waye, J. S., Dudar, J. C. & Saunders, S. R. Technical note: improved DNA extraction from ancient bones using silica-based spin columns. Am. J. Phys. Anthropol. 105(4), 539–543 (1998).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
61.Yang, D. Y., Liu, L., Chen, X. & Speller, C. F. Wild or domesticated: DNA analysis of ancient water buffalo remains from North China. J. Archaeol. Sci. 35(10), 2778–2785 (2008).Article 

Google Scholar 
62.Bertho, S. et al. The unusual rainbow trout sex determination gene hijacked the canonical vertebrate gonadal differentiation pathway. Proc. Natl. Acad. Sci. U.S.A. 115(50), 12781–12786 (2008).Article 
CAS 

Google Scholar 
63.Yano, A. et al. An immune-related gene evolved into the master sex-determining gene in rainbow trout, Oncorhynchus mykiss. Curr. Biol. 22(15), 1423–1428 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
64.Yano, A. et al. The sexually dimorphic on the Y-chromosome gene (sdY) is a conserved male-specific Y-chromosome sequence in many salmonids. Evol. Appl. 6(3), 486–496 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
65.Yang, D., Cannon, A. & Sanders, S. R. DNA species identification of archaeological salmon bone from the Pacific Northwest Coast of North America. J. Archaeol. Sci. 31, 619–631 (2004).Article 

Google Scholar 
66.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).67.Kim, K. et al. A real-time PCR-based amelogenin Y allele dropout assessment model in gender typing of degraded DNA samples. Int. J. Legal Med. 127, 55–61 (2013).PubMed 
Article 
PubMed Central 

Google Scholar 
68.Sinding, M. et al. Sex determination of baleen whale artefacts: Implications for ancient DNA use in zooarchaeology. J. Archaeol. Sci. Rep. 10, 345–349 (2016).
Google Scholar 
69.Cooper, A. & Poinar, H. Ancient DNA: do it right or not at all. Science 289(5482), 1139 (2000).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
70.McKechnie, I. Investigating the complexities of sustainable fishing at a prehistoric village on western Vancouver Island, British Columbia, Canada. J. Nat. Conserv. 15(3), 208–222 (2007).Article 

Google Scholar 
71.Cannon, A., Yang, D. Y. & Speller, C. Site-specific salmon fisheries on the central coast of British Columbia. In The Archaeology of North Pacific Fisheries (eds Moss, M. & Cannon, A.) 57–74 (University of Alaska Press, 2011).
Google Scholar 
72.McKechnie, I. & Moss, M. Meta-analysis in zooarchaeology expands perspectives on Indigenous fisheries of the Northwest Coast of North America. J. Archaeol. Sci. Rep. 8, 470–485 (2016).
Google Scholar 
73.Orchard, T. J. & Szpak, P. Zooarchaeological and isotopic insights into locally variable economic patterns: a case study from late Holocene southern Haida Gwaii, British Columbia. BC Stud. 187, 107–147 (2015).
Google Scholar 
74.Rodrigues, A. T., McKechnie, I. & Yang, D. Y. Ancient DNA analysis of indigenous rockfish use on the Pacific Coast: implications for marine conservation areas and fisheries management. PLoS ONE 13(2), e0192716 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
75.McGregor, D. Coming full circle: Indigenous knowledge, environment, and our future. Am. Indian Q. 28(3), 385–410 (2004).Article 

Google Scholar 
76.Suttles, W. Economic Life of the Coast Salish of Hario and Rosario Straits. PhD Dissertation. (University of Washington, 1951).77.Caldwell, M. E. Northern Coast Salish Marine Resource Management. PhD dissertation. (University of Alberta, 2015).78.Deur, D. Tending the garden, making the soil: Northwest Coast estuarine gardens as engineered environments. In Keeping It Living: Traditions of Plant Use and Cultivation on the Northwest Coast of North America (eds Deur, D. & Turner, N.) (UBC Press, 2005).
Google Scholar 
79.Hoffmann, T. et al. Engineered feature used to enhance gardening at a 3800-year-old site on the Pacific Northwest coast. Sci. Adv. 2(12), e1601282 (2016).PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
80.Lepofsky, D. et al. Documenting pre-contact plant management on the Northwest Coast: an example of prescribed burning in the Central and Upper Fraser Valley, British Columbia. In Keeping It Living: Traditions of Plant Use and Cultivation on the Northwest Coast of North America (eds Deur, D. & Turner, N.) 218–239 (UBC Press, 2005).
Google Scholar 
81.Turner, N. J., Deur, D. & Lepofsky, D. Plant management systems of British Columbia’s First Peoples. BC Stud. 179, 107–133 (2013).
Google Scholar 
82.Turner, N. J., Smith, R. & Jones, J. A fine line between two nations: ownership patterns for plant resources among Northwest Coast indigenous peoples. In Keeping It Living: Traditions of Plant Use and Cultivation on the Northwest Coast of North America (eds Deur, D. & Turner, N. J.) 151–180 (UBC Press, 2005).
Google Scholar 
83.Turner, N. J. & Peacock, S. Solving the perennial paradox: ethnobotanical evidence for plant resource management on the Northwest Coast. In Keeping It Living: Traditions of Plant Use and Cultivation on the Northwest Coast of North America (eds Deur, D. & Turner, N. J.) 101–151 (UBC Press, 2005).
Google Scholar 
84.Limburg, K. E., Walther, Y., Hong, B., Olson, C. & Stora, J. Prehistoric versus modern Baltic Sea cod fisheries: selectivity across the millennia. Proc. R. Soc. B 275, 2659–2665 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
85.Sanchez, G. Indigenous stewardship of marine and estuarine fisheries? Reconstructing the ancient size of Pacific herring through linear regression models. J. Archaeol. Sci. Rep. 29, 102061 (2020).
Google Scholar 
86.Slaney, T. L., Hyatt, K. D., Northcote, T. G. & Fielden, R. J. Status of anadromous salmon and trout in British Columbia and Yukon. Fisheries 21(10), 20–35 (1996).Article 

Google Scholar 
87.Kope, R. & Wainwright, T. Trends in the status of Pacific salmon populations in Washington, Oregon, California, and Idaho. N. Pac. Anadr. Fish Comm. Bull. 1, 1–12 (1998).
Google Scholar 
88.Gustafson, R. G. et al. Pacific salmon extinctions: Quantifying lost and remaining diversity. Conserv. Biol. 21(4), 1009–1020 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
89.Price, M. H., English, K. K., Rosenberger, A. G., MacDuffee, M. & Reynolds, J. D. Canada’s wild salmon policy: an assessment of conservation progress in British Columbia. Can. J. Fish. Aquat. Sci. 74(10), 1507–1518 (2017).Article 

Google Scholar 
90.Gayeski, N. J. et al. The failure of wild salmon management: need for a place-based conceptual foundation. Fisheries 43(7), 303–309 (2018).Article 

Google Scholar 
91.Morales, Q. E., Lepofsky, D. & Berkes, F. Ethnobiology and fisheries: Learning from the past for the present. J. Ethnobiol. 37(3), 369–379 (2017).Article 

Google Scholar 
92.Reid, A. J. et al. Two-eyed seeing: an Indigenous framework to transform fisheries research and management. Fish Fish. 00, 1–19 (2020).
Google Scholar 
93.Atlas, W. I. et al. Indigenous systems of management for culturally and ecologically resilient Pacific salmon (Oncorhynchus spp.) fisheries. Bioscience 71(2), 1–19 (2021).Article 

Google Scholar  More

1.Flemming H-C, Wingender J, Szewzyk U, Steinberg P, Rice SA, Kjelleberg S. Biofilms: an emergent form of bacterial life. Nat Rev Microbiol. 2016;14:563–75.CAS 
PubMed 
PubMed Central 

Google Scholar 
2.Nadell CD, Xavier JB, Foster KR. The sociobiology of biofilms. FEMS Microbiol Rev. 2009;33:206–24.CAS 
PubMed 

Google Scholar 
3.Rumbaugh KP, Sauer K. Biofilm dispersion. Nat Rev Microbiol. 2020;18:571–86.CAS 
PubMed 
PubMed Central 

Google Scholar 
4.Costerton JW, Stewart PS, Greenberg EP. Bacterial biofilms: a common cause of persistent infections. Science. 1999;284:1318–22.CAS 
PubMed 

Google Scholar 
5.Drenkard E, Ausubel FM. Pseudomonas biofilm formation and antibiotic resistance are linked to phenotypic variation. Nature. 2002;416:740–3.CAS 
PubMed 

Google Scholar 
6.de Carvalho CCCR. Marine biofilms: a successful microbial strategy with economic implications. Front Mar Sci. 2018;5:126.7.McDougald D, Rice SA, Barraud N, Steinberg PD, Kjelleberg S. Should we stay or should we go: mechanisms and ecological consequences for biofilm dispersal. Nat Rev Microbiol. 2012;10:39–50.CAS 

Google Scholar 
8.Nathan R, Getz WM, Revilla E, Holyoak M, Kadmon R, Saltz D, et al. A movement ecology paradigm for unifying organismal movement research. Proc Natl Acad Sci USA. 2008;105:19052–9.CAS 
PubMed 
PubMed Central 

Google Scholar 
9.Yan J, Monaco H, Xavier JB. The ultimate guide to bacterial swarming: an experimental model to study the evolution of cooperative behavior. Annu Rev Microbiol. 2019;73:293–312.CAS 
PubMed 
PubMed Central 

Google Scholar 
10.Gokhale S, Conwill A, Ranjan T, Gore J. Migration alters oscillatory dynamics and promotes survival in connected bacterial populations. Nat Commun. 2018;9:5273.CAS 
PubMed 
PubMed Central 

Google Scholar 
11.Hallatschek O, Fisher DS. Acceleration of evolutionary spread by long-range dispersal. Proc Natl Acad Sci USA. 2014;111:E4911–9.CAS 
PubMed 
PubMed Central 

Google Scholar 
12.Birzu G, Hallatschek O, Korolev KS. Fluctuations uncover a distinct class of traveling waves. Proc Natl Acad Sci USA. 2018;115:E3645–54.CAS 
PubMed 
PubMed Central 

Google Scholar 
13.Ping D, Wang T, Fraebel DT, Maslov S, Sneppen K, Kuehn S. Hitchhiking, collapse, and contingency in phage infections of migrating bacterial populations. ISME J. 2020;14:2007–18.PubMed 
PubMed Central 

Google Scholar 
14.Chen L, Noorbakhsh J, Adams RM, Samaniego-Evans J, Agollah G, Nevozhay D, et al. Two-dimensionality of yeast colony expansion accompanied by pattern formation. PLoS Comput Biol. 2014;10:e1003979.PubMed 
PubMed Central 

Google Scholar 
15.Patra P, Kissoon K, Cornejo I, Kaplan HB, Igoshin OA. Colony expansion of socially motile Myxococcus xanthus cells is driven by growth, motility, and exopolysaccharide production. PLoS Comput Biol. 2016;12:e1005010.PubMed 
PubMed Central 

Google Scholar 
16.Chapman BB, Brönmark C, Nilsson J-Å, Hansson L-A. The ecology and evolution of partial migration. Oikos. 2011;120:1764–75.
Google Scholar 
17.Lundberg P. Partial bird migration and evolutionarily stable strategies. J Theor Biol. 1987;125:351–60.
Google Scholar 
18.Kokko H. Directions in modelling partial migration: how adaptation can cause a population decline and why the rules of territory acquisition matter. Oikos. 2011;120:1826–37.
Google Scholar 
19.Singh NJ, Leonardsson K. Partial migration and transient coexistence of migrants and residents in animal populations. PloS One. 2014;9:e94750.PubMed 
PubMed Central 

Google Scholar 
20.Armbruster CE, Mobley HLT. Merging mythology and morphology: the multifaceted lifestyle of Proteus mirabilis. Nat Rev Microbiol. 2012;10:743.CAS 
PubMed 
PubMed Central 

Google Scholar 
21.Schaffer JN, Pearson MM. Proteus mirabilis and urinary tract infections. Microbiol Spectr. 2015;3. https://doi.org/10.1128/microbiolspec.UTI-0017-2013.22.Jones BV, Young R, Mahenthiralingam E, Stickler DJ. Ultrastructure of Proteus mirabilis swarmer cell rafts and role of swarming in catheter-associated urinary tract infection. Infect Immun. 2004;72:3941–50.CAS 
PubMed 
PubMed Central 

Google Scholar 
23.Li X, Zhao H, Lockatell CV, Drachenberg CB, Johnson DE, Mobley HL. Visualization of Proteus mirabilis within the matrix of urease-induced bladder stones during experimental urinary tract infection. Infect Immun. 2002;70:389–94.CAS 
PubMed 
PubMed Central 

Google Scholar 
24.Stickler DJ. Bacterial biofilms in patients with indwelling urinary catheters. Nat Clin Pr Urol. 2008;5:598–608.CAS 

Google Scholar 
25.Jacobsen SM, Stickler DJ, Mobley HLT, Shirtliff ME. Complicated catheter-associated urinary tract infections due to Escherichia coli and Proteus mirabilis. Clin Microbiol Rev. 2008;21:26–59.CAS 
PubMed 
PubMed Central 

Google Scholar 
26.Harshey RM. Bacterial motility on a surface: many ways to a common goal. Annu Rev Microbiol. 2003;57:249–73.CAS 
PubMed 

Google Scholar 
27.Verstraeten N, Braeken K, Debkumari B, Fauvart M, Fransaer J, Vermant J, et al. Living on a surface: swarming and biofilm formation. Trends Microbiol. 2008;16:496–506.CAS 
PubMed 
PubMed Central 

Google Scholar 
28.Kearns DB. A field guide to bacterial swarming motility. Nat Rev Microbiol. 2010;8:634–44.CAS 
PubMed 
PubMed Central 

Google Scholar 
29.Wu Y, Jiang Y, Kaiser AD, Alber M. Self-organization in bacterial swarming: lessons from myxobacteria. Phys Biol. 2011;8:055003.PubMed 

Google Scholar 
30.Howery KE, Şimşek E, Kim M, Rather PN. Positive autoregulation of the flhDC operon in Proteus mirabilis. Res Microbiol. 2018;169:199–204.CAS 
PubMed 

Google Scholar 
31.Little K, Austerman J, Zheng J, Gibbs KA. Cell shape and population migration are distinct steps of Proteus mirabilis swarming that are decoupled on high-percentage agar. J Bacteriol. 2019;201:e00726–18.CAS 
PubMed 
PubMed Central 

Google Scholar 
32.Furness RB, Fraser GM, Hay NA, Hughes C. Negative feedback from a Proteus class II flagellum export defect to the flhDC master operon controlling cell division and flagellum assembly. J Bacteriol. 1997;179:5585–8.CAS 
PubMed 
PubMed Central 

Google Scholar 
33.Claret L, Hughes C. Functions of the subunits in the FlhD(2)C(2) transcriptional master regulator of bacterial flagellum biogenesis and swarming. J Mol Biol. 2000;303:467–78.CAS 
PubMed 

Google Scholar 
34.Deegan RD, Bakajin O, Dupont TF, Huber G, Nagel SR, Witten TA. Capillary flow as the cause of ring stains from dried liquid drops. Nature. 1997;389:827–9.CAS 

Google Scholar 
35.Andac T, Weigmann P, Velu SKP, Pinçe E, Volpe G, Volpe G, et al. Active matter alters the growth dynamics of coffee rings. Soft Matter. 2019;15:1488–96.CAS 
PubMed 

Google Scholar 
36.Nellimoottil TT, Rao PN, Ghosh SS, Chattopadhyay A. Evaporation-induced patterns from droplets containing motile and nonmotile bacteria. Langmuir. 2007;23:8655–8.CAS 
PubMed 

Google Scholar 
37.Clemmer KM, Rather PN. Regulation of flhDC expression in Proteus mirabilis. Res Microbiol. 2007;158:295–302.CAS 
PubMed 

Google Scholar 
38.Howery KE, Clemmer KM, Rather PN. The Rcs regulon in Proteus mirabilis: implications for motility, biofilm formation, and virulence. Curr Genet. 2016;62:775–89.CAS 
PubMed 

Google Scholar 
39.Howery KE, Clemmer KM, Şimşek E, Kim M, Rather PN. Regulation of the min cell division inhibition complex by the Rcs phosphorelay in Proteus mirabilis. J Bacteriol. 2015;197:2499–507.CAS 
PubMed 
PubMed Central 

Google Scholar 
40.Wang Q, Zhao Y, McClelland M, Harshey RM. The RcsCDB signaling system and swarming motility in Salmonella enterica Serovar Typhimurium: dual regulation of flagellar and SPI-2 virulence genes. J Bacteriol. 2007;189:8447–57.CAS 
PubMed 
PubMed Central 

Google Scholar 
41.Samanta P, Clark ER, Knutson K, Horne SM, Prüß BM. OmpR and RcsB abolish temporal and spatial changes in expression of flhD in Escherichia coli biofilm. BMC Microbiol. 2013;13:182.CAS 
PubMed 
PubMed Central 

Google Scholar 
42.Girgis HS, Liu Y, Ryu WS, Tavazoie S. A comprehensive genetic characterization of bacterial motility. PLoS Genet. 2007;3:e154.PubMed Central 

Google Scholar 
43.Francez-Charlot A, Laugel B, Van Gemert A, Dubarry N, Wiorowski F, Castanié-Cornet MP, et al. RcsCDB His-Asp phosphorelay system negatively regulates the flhDC operon in Escherichia coli. Mol Microbiol. 2003;49:823–32.CAS 
PubMed 

Google Scholar 
44.Rieck VT, Palumbo SA, Witter LD. Glucose availability and the growth rate of colonies of Pseudomonas fluorescens. J Gen Microbiol. 1973;74:1–8.CAS 
PubMed 

Google Scholar 
45.Shao X, Mugler A, Kim J, Jeong HJ, Levin BR, Nemenman I. Growth of bacteria in 3-d colonies. PLoS Comput Biol. 2017;13:e1005679.PubMed 
PubMed Central 

Google Scholar 
46.Warren MR, Sun H, Yan Y, Cremer J, Li B, Hwa T. Spatiotemporal establishment of dense bacterial colonies growing on hard agar. Elife. 2019;8:e41093.PubMed 
PubMed Central 

Google Scholar 
47.Lavrentovich MO, Koschwanez JH, Nelson DR. Nutrient shielding in clusters of cells. Phys Rev E Stat Nonlin Soft Matter Phys. 2013;87:062703. -PubMed 
PubMed Central 

Google Scholar 
48.Dal Co A, van Vliet S, Ackermann M. Emergent microscale gradients give rise to metabolic cross-feeding and antibiotic tolerance in clonal bacterial populations. Philos Trans R Soc Lond B Biol Sci. 2019;374:20190080.CAS 
PubMed 
PubMed Central 

Google Scholar 
49.Huang YH, Ferrières L, Clarke DJ. The role of the Rcs phosphorelay in Enterobacteriaceae. Res Microbiol. 2006;157:206–12.CAS 
PubMed 

Google Scholar 
50.Majdalani N, Gottesman S. The Rcs phosphorelay: a complex signal transduction system. Annu Rev Microbiol. 2005;59:379–405.CAS 
PubMed 

Google Scholar 
51.Fraebel DT, Mickalide H, Schnitkey D, Merritt J, Kuhlman TE, Kuehn S. Environment determines evolutionary trajectory in a constrained phenotypic space. Elife. 2017;6:e24669.PubMed 
PubMed Central 

Google Scholar 
52.Yi X, Dean AM. Phenotypic plasticity as an adaptation to a functional trade-off. Elife. 2016;5:e19307.PubMed 
PubMed Central 

Google Scholar 
53.van Ditmarsch D, Boyle KE, Sakhtah H, Oyler JE, Nadell CD, Déziel É, et al. Convergent evolution of hyperswarming leads to impaired biofilm formation in pathogenic bacteria. Cell Rep. 2013;4:697–708.PubMed 
PubMed Central 

Google Scholar 
54.Auer GK, Oliver PM, Rajendram M, Lin T-Y, Yao Q, Jensen GJ, et al. Bacterial swarming reduces Proteus mirabilis and Vibrio parahaemolyticus cell stiffness and increases β-Lactam susceptibility. mBio. 2019;10:e00210–19.CAS 
PubMed 
PubMed Central 

Google Scholar 
55.Kaiser D. Bacterial swarming: a re-examination of cell-movement patterns. Curr Biol. 2007;17:R561–R70.CAS 
PubMed 

Google Scholar 
56.Inoue T, Shingaki R, Hirose S, Waki K, Mori H, Fukui K. Genome-wide screening of genes required for swarming motility in Escherichia coli K-12. J Bacteriol. 2007;189:950–7.CAS 
PubMed 

Google Scholar 
57.Dong T, Joyce C, Schellhorn H. The role of RpoS in bacterial adaptation. In: El-Sharoud W, editor. Bacterial physiology. Heidelberg: Springer, Berlin; 2008. pp 313-37.58.Phaiboun A, Zhang Y, Park B, Kim M. Survival kinetics of starving bacteria is biphasic and density-dependent. PLoS Comput Biol. 2015;11:e1004198.PubMed 
PubMed Central 

Google Scholar 
59.Majdalani N, Hernandez D, Gottesman S. Regulation and mode of action of the second small RNA activator of RpoS translation, RprA. Mol Microbiol. 2002;46:813–26.CAS 
PubMed 

Google Scholar 
60.Peterson CN, Carabetta VJ, Chowdhury T, Silhavy TJ. LrhA regulates rpoS translation in response to the Rcs phosphorelay system in Escherichia coli. J Bacteriol. 2006;188:3175–81.CAS 
PubMed 
PubMed Central 

Google Scholar 
61.Lok T, Overdijk O, Piersma T. The cost of migration: spoonbills suffer higher mortality during trans-Saharan spring migrations only. Biol Lett. 2015;11:20140944.PubMed 
PubMed Central 

Google Scholar 
62.Flack A, Fiedler W, Blas J, Pokrovsky I, Kaatz M, Mitropolsky M, et al. Costs of migratory decisions: a comparison across eight white stork populations. Sci Adv. 2016;2:e1500931.PubMed 
PubMed Central 

Google Scholar 
63.Rankin MA, Burchsted JCA. The cost of migration in insects. Annu Rev Entomol. 1992;37:533–59.
Google Scholar 
64.Ni B, Colin R, Link H, Endres RG, Sourjik V. Growth-rate dependent resource investment in bacterial motile behavior quantitatively follows potential benefit of chemotaxis. Proc Natl Acad Sci USA. 2020;117:595–601.CAS 
PubMed 

Google Scholar 
65.Amsler CD, Cho M, Matsumura P. Multiple factors underlying the maximum motility of Escherichia coli as cultures enter post-exponential growth. J Bacteriol. 1993;175:6238–44.CAS 
PubMed 
PubMed Central 

Google Scholar 
66.Yokota T, Gots JS. Requirement of adenosine 3’, 5’-cyclic phosphate for flagella formation in Escherichia coli and Salmonella typhimurium. J Bacteriol. 1970;103:513–6.CAS 
PubMed 
PubMed Central 

Google Scholar 
67.Soutourina O, Kolb A, Krin E, Laurent-Winter C, Rimsky S, Danchin A, et al. Multiple control of flagellum biosynthesis in Escherichia coli: role of H-NS protein and the cyclic AMP-catabolite activator protein complex in transcription of the flhDC master operon. J Bacteriol. 1999;181:7500–8.CAS 
PubMed 
PubMed Central 

Google Scholar 
68.Silverman M, Simon M. Characterization of Escherichia coli flagellar mutants that are insensitive to catabolite repression. J Bacteriol. 1974;120:1196–203.CAS 
PubMed 
PubMed Central 

Google Scholar 
69.Mitrophanov AY, Groisman EA. Positive feedback in cellular control systems. Bioessays. 2008;30:542–55.CAS 
PubMed 
PubMed Central 

Google Scholar 
70.Raj A, van Oudenaarden A. Nature, nurture, or chance: stochastic gene expression and its consequences. Cell. 2008;135:216–26.71.Ferrières L, Clarke DJ. The RcsC sensor kinase is required for normal biofilm formation in Escherichia coli K-12 and controls the expression of a regulon in response to growth on a solid surface. Mol Microbiol. 2003;50:1665–82.PubMed 

Google Scholar 
72.Guttenplan SB, Kearns DB. Regulation of flagellar motility during biofilm formation. FEMS Microbiol Rev. 2013;37:849–71.CAS 

Google Scholar  More

Agent-resource affiliation networksWe consider games involving populations of agents that extract from multiple common-pool sources (which term we use for nodes representing resources in accord with previous related work15,16). Agents’ access to sources is defined by bipartite networks, wherein a link between an agent and a source indicates that the agent can access that source. This access is determined by some exogenous factors and remains fixed in time. The set of agents affiliated with a particular source (s) is denoted as ({mathbf{A}}_{s}), while the set of sources affiliated with a particular agent (a) is denoted as ({mathbf{S}}_{a}). The degree of an agent (a) is denoted by (m(a)), and the degree of a source (s) by (n(s)).To explore the effects of network topology upon extraction dynamics and wealth distributions, we generate ensembles of ({10}^{3}) networks, each having (50) agents and (50) sources and sharing mean agent degree (langle mrangle =5) and mean source degree (langle nrangle =5). All networks thus share the same total numbers of agents, sources, and links, but differ in how these links are distributed among agents and sources. We generate 9 network ensembles, each generated to represent a particular combination of one of three types of degree heterogeneity in its source degree distribution (U: uniform-degree, L: low-heterogeneity, or H: high-heterogeneity) with one of three similar distributions of agent degree (u, l, or h39) (Supplementary Information S1.1). Degree histograms, averaged over each ensemble, provide a representative source degree distribution ({P}_{mathbf{S}}(n)) and agent degree distribution ({P}_{mathbf{A}}(m)) for each network type (Fig. 2a and b). It is worth noting that the results of the simulations depend primarily on the degree distributions of agents and sources rather than on the overall size of the networks used (Supplementary Information S3.1).Figure 2(a) Source degree distributions and (b) Agent degree distributions for 9 network ensembles, each representing a combination of a Uniform-degree (U), Low-heterogeneity (L), or High-heterogeneity (H) source degree distribution with a uniform-degree (u), low-heterogeneity (l), or high-heterogeneity (h) agent degree distribution. Ensemble mean time-averaged quantities from pure free adaptation dynamics: (c) Agent payoffs (f(a)) as a function of agent degree (m(a)); (d) Collective extraction (overrightarrow{q}(s)) as a function of source degree (n(s)); (e) Source quality (b(s)) as a function of source degree (n(s)); and (f) Period of oscillation (T(s)) as a function of source degree (n(s)). Means are computed from simulations on ({10}^{3}) networks of each type.Full size imageNetworked CPR extraction gameOn these networks, we simulate iterative games in which agents vary the extraction effort that they apply to their affiliated sources, altering the quality of these sources; in turn, these changes in source quality then influence how agents adapt their extraction levels in subsequent rounds. The extraction effort exerted by agent (a) upon its affiliated source (s) is denoted as (q(a,s)). The total effort exerted by an agent (a), its individual extraction, is denoted by (overleftarrow{q}left(aright)=sum_{sin {mathbf{S}}_{a}}q(a,s)). The total effort exerted upon source (s), or its collective extraction, is denoted by (overrightarrow{q}left(sright)=sum_{ain {mathbf{A}}_{s}}q(a,s)). The quality of a source (s) is quantified by the benefit (b(s)) per unit extraction effort applied that the source provides. The cost associated with extraction is given by a convex (quadratic) function of (overleftarrow{q}left(aright)), such that marginal costs increase with individual extraction15,16. In addition to modelling the increasing costs (i.e., diminishing returns) associated with the physical act of extraction itself, this could also reflect escalating, informal social penalties that result from increasing extraction (i.e., “graduated sanctions”1,40). The net payoff accumulated by an agent (a) in a game iteration is thus$$fleft( a right) = left[ {mathop sum limits_{{s in {mathbf{S}}_{a} }} qleft( {a,s} right) cdot bleft( s right)} right] – frac{gamma }{2}{ }mathop{q}limits^{leftarrow} left( a right)^{2} ,$$
(1)

where (gamma) is a positive cost parameter.Bistable model of CPR depletion and remediationSources are bistable, meaning that at any time they can occupy one of two states: (1) a viable state, during which the source provides a benefit of magnitude (alpha) in return for each unit of extraction effort, and (2) a depleted state, during which this benefit is reduced by (beta) ((0 vec{q}_{{text{D}}} left( s right)} \ {0, } & {{text{if }} chi_{t – 1} left( s right) = 1{text{ and }}vec{q}_{t} left( s right) le vec{q}_{R} left( s right)} \ {chi_{t – 1} left( s right),} & {text{otherwise }} \ end{array} } right.$$
(3)
In the results that follow, we focus upon a uniform capacity scenario, wherein all sources share identical threshold values (vec{q}_{{text{D}}} left( s right) equiv vec{q}_{{text{D}}}) and (vec{q}_{{text{R}}} left( s right) equiv vec{q}_{{text{R}}} left( s right)). An alternative degree-proportional capacity scenario, in which threshold values increase with source degree, is discussed in the Supplementary Information (S3.4.2).Free adaptationUnder the free adaptation strategy, an agent updates its extraction levels independently at each of its affiliated sources depending on the state of each (Fig. 1b). As in the replicator rule often applied in networked evolutionary game models17,41,42, the rate at which an agent adapts its extraction levels within a time interval ({Delta }t) is proportional to the marginal payoff that the agent expects to attain thereby:$$frac{{{Delta }qleft( {a,s} right)}}{{{Delta }t}} = kfrac{partial fleft( a right)}{{partial qleft( {a,s} right)}},$$
(4)
where (k) is a rate constant. So, each extraction level (qleft( {a,s} right)) is updated according to$$q_{t + 1} left( {a,s} right) = q_{t} left( {a,s} right) + kleft[ {alpha – beta chi_{t} left( s right) – gamma {mathop{q}limits^{leftarrow}}_{t} left( a right)} right].$$
(5)
The higher an agent’s individual extraction (overleftarrow{q}(a)), the more slowly it will increase its extraction from viable sources, and the more rapidly it will reduce its extraction from depleted sources.Uniform adaptationWhen applying the uniform adaptation strategy, an agent adjusts each of its extraction levels by the same magnitude (Delta qleft(a,sright)equivDelta overleftarrow{q}(a)/mleft(aright)) (Fig. 1c). Assuming again that the rate at which an agent enacts this update is proportional to the associated marginal payoff, an agent adapts its extraction levels at all of its affiliated sources (s) by$$q_{t + 1} left( {a,s} right) = q_{t} left( {a,s} right) + kleft[ {alpha – beta overline{chi }left( a right) – gamma {mathop{q}limits^{leftarrow}}_{t} left( a right)} right],$$
(6)
where (overline{chi }left( a right) = left[ {mathop sum nolimits_{{s^{prime} in {mathbf{S}}_{a} }} chi left( {s^{prime}} right)} right]/mleft( a right)) is the mean state of the agent’s affiliated sources.ReallocationWhen practicing reallocation, an agent shifts an increment of extraction effort from a depleted source to a viable source such that its overall individual extraction (mathop{q}limits^{leftarrow} left( a right)) remains unchanged (Fig. 1d). The agent thus randomly selects one depleted source (s_{{text{D}}} in {mathbf{S}}_{a}) and one viable source (s_{{text{V}}} in {mathbf{S}}_{a}), if available. Since the marginal payoff per unit reallocated is (beta), updates its extraction levels such that$$q_{t + 1} left( {a,s} right) = left{ {begin{array}{*{20}c} {q_{t} left( {a,s} right) – kbeta , } & {{text{if}} s = s_{{text{D}}} } \ {q_{t} left( {a,s} right) + kbeta , } & {{text{if}} s = s_{{text{V}}} } \ {q_{t} left( {a,s} right),} & {text{otherwise }} \ end{array} } right.$$
(7)

When an agent’s affiliated sources all share the same quality value, no such reallocation is possible, and so the agent retains its present extraction levels: (q_{t + 1} left( {a,s} right) = q_{t} left( {a,s} right)) for all (s in {mathbf{S}}_{a}).Mixed strategiesAn agent’s adaptation strategy (({p}_{0},{p}_{updownarrow },{p}_{leftrightarrow })) comprises the probabilities that it will practice each of these update rules in any given round: its free adaptation propensity (({p}_{0})), its uniform adaptation propensity (({p}_{updownarrow })), and its reallocation propensity (({p}_{leftrightarrow })). An agent’s choice of a particular update rule is thus based only on its own innate inclinations, but the rate at which it enacts the selected rule is influenced by current resource conditions. We first simulate dynamics in which the same adaptation strategy is shared by all members of a population throughout the entire course of a simulation. We then consider games in which agents’ individual adaptation strategies are each allowed to independently evolve under generalized reinforcement learning38,43 (Supplementary Information S1.3.4). That is, after enacting a chosen update rule in an iteration (t), each agent (a) observes the payoff change (Delta {f}_{t}left(aright)={f}_{t}left(aright)-{f}_{t-1}(a)). If (Delta {f}_{t}left(aright) >0), then the agent’s relative propensity to practice this update rule in subsequent rounds is increased. If the agent’s payoffs decreased ((Delta {f}_{t}left(aright)0) or remediation threshold ({overrightarrow{q}}_{mathrm{R}}left(sright)). That is, all resource depletion events are assumed to be extreme enough to motivate agents to continuously “self-regulate” by remediating depleted sources (see Supplementary Information S5 for a more thorough discussion of these parameter settings).In simulations where reinforcement learning is applied, all agents are initialized with ({p}_{updownarrow }={p}_{leftrightarrow }=.333). For pure free adaptation simulations (({p}_{0}=1)), initial extraction levels were randomized (({q}_{t=0}left(a,sright)in [0,frac{{overrightarrow{q}}_{mathrm{D}}left(sright)}{nleft(sright)}])). All other simulations (({p}_{0} More

1.Muegge, B. D. et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science 6032(332), 970–974 (2011).ADS 
Article 
CAS 

Google Scholar 
2.McKenzie, V. J. et al. The effects of captivity on the mammalian gut microbiome. Integr. Comp. Biol. 57, 690–704 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
3.Flint, H. J., Scott, K. P., Duncan, S. H., Louis, P. & Forano, E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes 3, 289–306 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
4.Chen, T. et al. Fiber-utilizing capacity varies in Prevotella- versus Bacteroides-dominated gut microbiota. Sci. Rep. 7, 2594 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
5.Costello, E. K., Stagaman, K., Dethlefsen, L., Bohannan, B. J. M. & Relman, D. A. The application of ecological theory toward an understanding of the human microbiome. Science 6086(336), 1255–1262 (2012).ADS 
Article 
CAS 

Google Scholar 
6.Campbell, C. J., Fuentes, A., MacKinnon, K. C., Bearder, S. K. & Stumpf, R. Primates in Perspective (Oxford University Press, 2010).
Google Scholar 
7.Chivers, D. J. Functional anatomy of the gastrointestinal tract. Colobine Monkeys Ecol. Behav. Evol. 205–227 (1994).8.Davies, G. E. Colobine Monkeys: Their Ecology, Behaviour and Evolution (Cambridge University Press, 1994).
Google Scholar 
9.Neish, A. S. Microbes in gastrointestinal health and disease. Gastroenterology 136, 65–80 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
10.Hanya, G. & Chapman, C. A. Linking feeding ecology and population abundance: A review of food resource limitation on primates. Ecol. Res. 28, 183–190 (2013).Article 

Google Scholar 
11.Fan, P., Ni, Q., Sun, G., Huang, B. & Jiang, X. Gibbons under seasonal stress: the diet of the black crested gibbon (Nomascus concolor) on Mt. Wuliang, Central Yunnan, China. Primates 50, 37 (2009).PubMed 
Article 

Google Scholar 
12.Burrows, A. M. & Nash, L. T. The Evolution of Exudativory in Primates (Springer Science & Business Media, 2010).Book 

Google Scholar 
13.Amato, K. R. et al. Gut microbiome, diet, and conservation of endangered langurs in Sri Lanka. Biotropica 52, 981–990 (2020).Article 

Google Scholar 
14.Amato, K. R. et al. The gut microbiota appears to compensate for seasonal diet variation in the wild black howler monkey (Alouatta pigra). Microb. Ecol. 69, 434–443 (2015).CAS 
PubMed 
Article 

Google Scholar 
15.Amato, K. R. et al. Variable responses of human and non-human primate gut microbiomes to a Western diet. Microbiome 3, 53 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
16.Clayton, J. B. et al. Captivity humanizes the primate microbiome. Proc. Natl. Acad. Sci. U. S. A. 113, 10376–10381 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
17.Frankel, J. S., Mallott, E. K., Hopper, L. M., Ross, S. R. & Amato, K. R. The effect of captivity on the primate gut microbiome varies with host dietary niche. Am. J. Primatol. 81, 1–9 (2019).Article 

Google Scholar 
18.Lee, W., Hayakawa, T., Kiyono, M., Yamabata, N. & Hanya, G. Gut microbiota composition of Japanese macaques associates with extent of human encroachment. Am. J. Primatol. 81, 1–14 (2019).Article 

Google Scholar 
19.Amato, K. R. et al. Habitat degradation impacts black howler monkey (Alouatta pigra) gastrointestinal microbiomes. ISME J. 7, 1344–1353 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
20.Moeller, A. H. et al. Sympatric chimpanzees and gorillas harbor convergent gut microbial communities. Genome Res. 23, 1715–1720 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
21.Suzuki, T. A. & Worobey, M. Geographical variation of human gut microbial composition. Biol. Lett. 10, (2014).22.Sinha, A., Datta, A., Madhusudan, M. D. & Mishra, C. Macaca munzala: a new species from western Arunachal Pradesh, northeastern India. Int. J. Primatol. 26, 977–989 (2005).Article 

Google Scholar 
23.Sinha, A., Kumar, R. S., Gama, N., Madhusudan, M. D. & Mishra, C. Distribution and conservation status of the Arunachal macaque, Macaca munzala, in western Arunachal Pradesh, northeastern India. Primate Conserv. 2006, 145–148 (2006).Article 

Google Scholar 
24.Mendiratta, U., Kumar, A., Mishra, C. & Sinha, A. Winter ecology of the Arunachal macaque Macaca munzala in Pangchen Valley, western Arunachal Pradesh, northeastern India. Am. J. Primatol. 71, 939–947 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
25.Kumar, R. S., Mishra, C. & Sinha, A. Foraging ecology and time-activity budget of the Arunachal macaque Macaca munzala: A preliminary study. Curr. Sci. 93, 532–539 (2007).
Google Scholar 
26.Ghosh, A., Thakur, M., Singh, S. K., Sharma, L. K. & Chandra, K. Gut microbiota suggests dependency of Arunachal Macaque (Macaca munzala) on anthropogenic food in Western Arunachal Pradesh, Northeastern India: Preliminary findings. Glob. Ecol. Conserv. 22, e01030 (2020).Article 

Google Scholar 
27.Song, S. J., Amir, A., Metcalf, J. L. & Amato, K. R. Preservation methods differ in fecal microbiome stability, affecting suitability for field studies. mSystems 1, 1–12 (2016).Article 

Google Scholar 
28.Li, Q. & Zhang, Y. A molecular phylogeny of macaca based on mtochondrial corntrol region sequeryces. Zool. Res. 25, 385–390 (2004).
Google Scholar 
29.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 
30.Kanthaswamy, S. et al. Microsatellite markers for standardized genetic management of captive colonies of rhesus macaques (Macaca mulatta). Am. J. Primatol. Off. J. Am. Soc. Primatol. 68, 73–95 (2006).CAS 

Google Scholar 
31.Peakall, R. O. D. & 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 
32.Kalinowski, S. T., Wagner, A. P. & Taper, M. L. ML-RELATE: A computer program for maximum likelihood estimation of relatedness and relationship. Mol. Ecol. Notes 6, 576–579 (2006).CAS 
Article 

Google Scholar 
33.Takai, K. & Horikoshi, K. Rapid detection and quantification of members of the archaeal community by quantitative PCR using fluorogenic probes. Appl. Environ. Microbiol. 66, 5066–5072 (2000).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
34.Herlemann, D. P. R. et al. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 5, 1571–1579 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.Muyzer, G., De Waal, E. C. & Uitterlinden, A. G. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 59, 695–700 (1993).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
36.Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. U. S. A. 108, 4516–4522 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
37.Schloss, P. D. et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
38.Schloss, P. D. Reintroducing mothur: 10 years later. Appl. Environ. Microbiol. 86, 1–13 (2020).
Google Scholar 
39.Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
40.Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).CAS 
Article 

Google Scholar 
41.McMurdie, P. J. & Holmes, S. Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, (2013).42.Cao, Y. microbiomeMarker: microbiome biomarker analysis. R package version 0.0.1.9000 https://github.com/yiluheihei/microbiomeMarker (2020).43.Lozupone, C., Lladser, M. E., Knights, D., Stombaugh, J. & Knight, R. UniFrac: An effective distance metric for microbial community comparison. ISME J. 5, 169–172 (2011).PubMed 
Article 

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

Google Scholar 
45.Mao, S., Zhang, R., Wang, D. & Zhu, W. The diversity of the fecal bacterial community and its relationship with the concentration of volatile fatty acids in the feces during subacute rumen acidosis in dairy cows. BMC Vet. Res. 8, 1 (2012).CAS 
Article 

Google Scholar 
46.Wang, B., Yao, M., Lv, L., Ling, Z. & Li, L. The human microbiota in health and disease. Engineering 3, 71–82 (2017).Article 

Google Scholar 
47.Carding, S., Verbeke, K., Vipond, D. T., Corfe, B. M. & Owen, L. J. Dysbiosis of the gut microbiota in disease. Microb. Ecol. Health Dis. 26, 26191 (2015).PubMed 
PubMed Central 

Google Scholar 
48.Kumar, R. S., Gama, N., Raghunath, R., Sinha, A. & Mishra, C. In search of the munzala: distribution and conservation status of the newly-discovered Arunachal macaque Macaca munzala. Oryx 42, 360–366 (2008).Article 

Google Scholar 
49.Sarania, B., Devi, A., Kumar, A., Sarma, K. & Gupta, A. K. Predictive distribution modeling and population status of the endangered Macaca munzala in Arunachal Pradesh, India. Am. J. Primatol. 79, 2592 (2017).Article 

Google Scholar 
50.Aiyadurai, A., Singh, N. J. & Milner-Gulland, E. J. Wildlife hunting by indigenous tribes: A case study from Arunachal Pradesh, north-east India. Oryx 44, 564–572 (2010).Article 

Google Scholar 
51.Mishra, C., Madhusudan, M. D. & Datta, A. Mammals of the high altitudes of western Arunachal Pradesh, eastern Himalaya: an assessment of threats and conservation needs. Oryx 40, 29–35 (2006).Article 

Google Scholar  More

1.Reynolds, J. F. et al. Global desertification: building a science for dryland development. Science 316, 847–851 (2007).Article 

Google Scholar 
2.Berdugo, M., Kéfi, S., Soliveres, S. & Maestre, F. T. Plant spatial patterns identify alternative ecosystem multifunctionality states in global drylands. Nat. Ecol. Evol. 1, 0003 (2017).Article 

Google Scholar 
3.Ahlström, A. et al. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science 348, 895–899 (2015).Article 

Google Scholar 
4.Bestelmeyer, B. T. et al. Desertification, land use, and the transformation of global drylands. Front. Ecol. Environ. 13, 28–36 (2015).Article 

Google Scholar 
5.Huang, K. et al. Enhanced peak growth of global vegetation and its key mechanisms. Nat. Ecol. Evol. 2, 1897 (2018).Article 

Google Scholar 
6.Maestre, F. T. et al. Structure and functioning of dryland ecosystems in a changing world. Annu. Rev. Ecol. Evol. Syst. 47, 215–237 (2016).Article 

Google Scholar 
7.Costanza, R. et al. Changes in the global value of ecosystem services. Glob. Environ. Change 26, 152–158 (2014).Article 

Google Scholar 
8.Middleton, N. & Sternberg, T. Climate hazards in drylands: a review. Earth Sci. Rev. 126, 48–57 (2013).Article 

Google Scholar 
9.Park, C.-E. et al. Keeping global warming within 1.5 C constrains emergence of aridification. Nat. Clim. Change 8, 70–74 (2018).Article 

Google Scholar 
10.Pra˘va˘lie, R., Bandoc, G., Patriche, C. & Sternberg, T. Recent changes in global drylands: evidences from two major aridity databases. Catena 178, 209–231 (2019).Article 

Google Scholar 
11.Huang, J. et al. Declines in global ecological security under climate change. Ecol. Indic. 117, 106651 (2020).Article 

Google Scholar 
12.Delgado-Baquerizo, M. et al. Decoupling of soil nutrient cycles as a function of aridity in global drylands. Nature 502, 672–676 (2013).Article 

Google Scholar 
13.He, B., Wang, S., Guo, L. & Wu, X. Aridity change and its correlation with greening over drylands. Agric. For. Meteorol. 278, 107663 (2019).Article 

Google Scholar 
14.Zhang, C., Yang, Y., Yang, D. & Wu, X. Multidimensional assessment of global dryland changes under future warming in climate projections. J. Hydrol. 592, 125618 (2020).Article 

Google Scholar 
15.Pra˘va˘lie, R. Exploring the multiple land degradation pathways across the planet. Earth Sci. Rev. 220, 103689 (2021).Article 

Google Scholar 
16.Balvanera, P. et al. Linking biodiversity and ecosystem services: current uncertainties and the necessary next steps. Bioscience 64, 49–57 (2014).Article 

Google Scholar 
17.UNCCD. United Nations Convention to Combat Desertification — Global Land Outlook (UNCCD, 2017).18.Pra˘va˘lie, R. Drylands extent and environmental issues. A global approach. Earth Sci. Rev. 161, 259–278 (2016).Article 

Google Scholar 
19.Yang, X. et al. Quaternary environmental changes in the drylands of China — a critical review. Quat. Sci. Rev. 30, 3219–3233 (2011).Article 

Google Scholar 
20.Chen, X., Hu, R., Jiang, F., Wang, Y. & Zhang, J. Physical Geography in China’s Drylands (Science, 2015).21.Ci, L. & Yang, X. Desertification and its Control in China (Springer, 2010).22.Huang, J. et al. Dryland climate change: recent progress and challenges. Rev. Geophys. 55, 719–778 (2017).Article 

Google Scholar 
23.Smith, W. K. et al. Remote sensing of dryland ecosystem structure and function: progress, challenges, and opportunities. Remote Sens. Environ. 233, 111401 (2019).Article 

Google Scholar 
24.Fu, B. et al. Hydrogeomorphic ecosystem responses to natural and anthropogenic changes in the Loess Plateau of China. Annu. Rev. Earth Planet. Sci. 45, 223–243 (2017).Article 

Google Scholar 
25.D’Odorico, P., Porporato, A. & Runyan, C. W. Dryland Ecohydrology Vol. 9 (Springer, 2006).26.Brauman, K. A., Daily, G. C., Duarte, T. K. E. & Mooney, H. A. The nature and value of ecosystem services: an overview highlighting hydrologic services. Annu. Rev. Environ. Resour. 32, 67–98 (2007).Article 

Google Scholar 
27.Wang, X., Chen, F., Hasi, E. & Li, J. Desertification in China: an assessment. Earth Sci. Rev. 88, 188–206 (2008).Article 

Google Scholar 
28.Stringer, L. C. et al. Climate change impacts on water security in global drylands. One Earth 4, 851–864 (2021).Article 

Google Scholar 
29.Qi, J., Chen, J., Wan, S. & Ai, L. Understanding the coupled natural and human systems in dryland East Asia. Environ. Res. Lett. 7, 015202 (2012).Article 

Google Scholar 
30.Chi, W., Zhao, Y., Kuang, W. & He, H. Impacts of anthropogenic land use/cover changes on soil wind erosion in China. Sci. Total Environ. 668, 204–215 (2019).Article 

Google Scholar 
31.Shi, P., Yan, P., Yuan, Y. & Nearing, M. A. Wind erosion research in China: past, present and future. Prog. Phys. Geogr. 28, 366–386 (2004).Article 

Google Scholar 
32.Cheng, L. et al. Estimation of the costs of desertification in China: a critical review. Land. Degrad. Dev. 29, 975–983 (2018).Article 

Google Scholar 
33.Bryan, B. A. et al. China’s response to a national land-system sustainability emergency. Nature 559, 193 (2018).Article 

Google Scholar 
34.Scott, R. L., Jenerette, G. D., Potts, D. L. & Huxman, T. E. Effects of seasonal drought on net carbon dioxide exchange from a woody-plant-encroached semiarid grassland. J. Geophys. Res. Biogeosci. 114, G4 (2009).Article 

Google Scholar 
35.Scott, R. L. et al. When vegetation change alters ecosystem water availability. Glob. Change Biol. 20, 2198–2210 (2014).Article 

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

Google Scholar 
37.Wang, T. et al. Permafrost thawing puts the frozen carbon at risk over the Tibetan Plateau. Sci. Adv. 6, eaaz3513 (2020).Article 

Google Scholar 
38.Arndt, S. K. et al. Contrasting patterns of leaf solute accumulation and salt adaptation in four phreatophytic desert plants in a hyperarid desert with saline groundwater. J. Arid. Environ. 59, 259–270 (2004).Article 

Google Scholar 
39.Deng, L., Shangguan, Z.-P., Wu, G.-L. & Chang, X.-F. Effects of grazing exclusion on carbon sequestration in China’s grassland. Earth Sci. Rev. 173, 84–95 (2017).Article 

Google Scholar 
40.Dai, A. Drought under global warming: a review. Wiley Interdiscip. Rev. Clim. Change 2, 45–65 (2011).Article 

Google Scholar 
41.Fu, C., Jiang, Z., Guan, Z., He, J. & Xu, Z. F. Regional Climate Studies of China (Springer Science & Business Media, 2008).42.Zhao, J., Zhang, Q., Zhu, X., Shen, Z. & Yu, H. Drought risk assessment in China: evaluation framework and influencing factors. Geogr. Sustain. 1, 220–228 (2020).
Google Scholar 
43.Huang, J., Xie, Y., Guan, X., Li, D. & Ji, F. The dynamics of the warming hiatus over the northern hemisphere. Clim. Dyn. 48, 429–446 (2017).Article 

Google Scholar 
44.Poulter, B. et al. Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 509, 600–603 (2014).Article 

Google Scholar 
45.Liu, M., Shen, Y., Qi, Y., Wang, Y. & Geng, X. Changes in precipitation and drought extremes over the past half century in China. Atmosphere 10, 203 (2019).Article 

Google Scholar 
46.Seneviratne, S. I. et al. Investigating soil moisture–climate interactions in a changing climate: a review. Earth Sci. Rev. 99, 125–161 (2010).Article 

Google Scholar 
47.Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 1–12 (2018).Article 

Google Scholar 
48.Li, Y., Huang, J., Ji, M. & Ran, J. Dryland expansion in northern China from 1948 to 2008. Adv. Atmos. Sci. 32, 870–876 (2015).Article 

Google Scholar 
49.Lian, X. et al. Multifaceted characteristics of dryland aridity changes in a warming world. Nat. Rev. Earth Environ. 2, 232–250 (2021).Article 

Google Scholar 
50.Posner, S. M., McKenzie, E. & Ricketts, T. H. Policy impacts of ecosystem services knowledge. Proc. Natl Acad. Sci. USA 113, 1760–1765 (2016).Article 

Google Scholar 
51.Costanza, R. et al. Twenty years of ecosystem services: how far have we come and how far do we still need to go? Ecosyst. Serv. 28, 1–16 (2017).Article 

Google Scholar 
52.Ouyang, Z. et al. Improvements in ecosystem services from investments in natural capital. Science 352, 1455–1459 (2016).Article 

Google Scholar 
53.Cao, S. Why large-scale afforestation efforts in China have failed to solve the desertification problem. Environ. Sci. Technol. 42, 1826–1831 (2008).Article 

Google Scholar 
54.Liu, J., Li, S., Ouyang, Z., Tam, C. & Chen, X. Ecological and socioeconomic effects of China’s policies for ecosystem services. Proc. Natl Acad. Sci. USA 105, 9477–9482 (2008).Article 

Google Scholar 
55.Wang, X., Zhang, C., Hasi, E. & Dong, Z. Has the Three Norths Forest Shelterbelt Program solved the desertification and dust storm problems in arid and semiarid China? J. Arid. Environ. 74, 13–22 (2010).Article 

Google Scholar 
56.Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).Article 

Google Scholar 
57.Chen, L., Wei, W., Fu, B. & Lü, Y. Soil and water conservation on the Loess Plateau in China: review and perspective. Prog. Phys. Geogr. 31, 389–403 (2007).Article 

Google Scholar 
58.Lü, Y. et al. A policy-driven large scale ecological restoration: quantifying ecosystem services changes in the Loess Plateau of China. PLoS ONE 7, e31782 (2012).Article 

Google Scholar 
59.McVicar, T. R. et al. Parsimoniously modelling perennial vegetation suitability and identifying priority areas to support China’s re-vegetation program in the Loess Plateau: matching model complexity to data availability. For. Ecol. Manag. 259, 1277–1290 (2010).Article 

Google Scholar 
60.Chen, Y. et al. Balancing green and grain trade. Nat. Geosci. 8, 739–741 (2015).Article 

Google Scholar 
61.Xiao, J. et al. Responses of four dominant dryland plant species to climate change in the Junggar Basin, northwest China. Ecol. Evol. 9, 13596–13607 (2019).Article 

Google Scholar 
62.Zastrow, M. China’s tree-planting drive could falter in a warming world. Nature 573, 474–476 (2019).Article 

Google Scholar 
63.Feng, X. et al. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nat. Clim. Change 6, 1019–1022 (2016).Article 

Google Scholar 
64.Berdugo, M. et al. Global ecosystem thresholds driven by aridity. Science 367, 787–790 (2020).Article 

Google Scholar 
65.Chappell, A., Baldock, J. & Sanderman, J. The global significance of omitting soil erosion from soil organic carbon cycling schemes. Nat. Clim. Change 6, 187 (2016).Article 

Google Scholar 
66.Yue, Y. et al. Lateral transport of soil carbon and land-atmosphere CO2 flux induced by water erosion in China. Proc. Natl Acad. Sci. USA 113, 6617–6622 (2016).Article 

Google Scholar 
67.Peng, S. et al. Asymmetric effects of daytime and night-time warming on northern hemisphere vegetation. Nature 501, 88–92 (2013).Article 

Google Scholar 
68.Cao, S. et al. Excessive reliance on afforestation in China’s arid and semi-arid regions: lessons in ecological restoration. Earth Sci. Rev. 104, 240–245 (2011).Article 

Google Scholar 
69.Wang, G., Innes, J. L., Lei, J., Dai, S. & Wu, S. China’s forestry reforms. Science 318, 1556 (2007).Article 

Google Scholar 
70.Li, M. M. et al. An overview of the “Three-North” Shelterbelt project in China. Forestry Stud. China 14, 70–79 (2012).Article 

Google Scholar 
71.Wang, Y., Shao, M. A., Zhu, Y. & Liu, Z. Impacts of land use and plant characteristics on dried soil layers in different climatic regions on the Loess Plateau of China. Agric. For. Meteorol. 151, 437–448 (2011).Article 

Google Scholar 
72.Wang, S. et al. Reduced sediment transport in the Yellow River due to anthropogenic changes. Nat. Geosci. 9, 38–41 (2016).Article 

Google Scholar 
73.Zhao, G., Mu, X., Wen, Z., Wang, F. & Gao, P. Soil erosion, conservation, and eco-environment changes in the Loess Plateau of China. Land Degrad. Dev. 24, 499–510 (2013).Article 

Google Scholar 
74.Fu, B. et al. Assessing the soil erosion control service of ecosystems change in the Loess Plateau of China. Ecol. Complex. 8, 284–293 (2011).Article 

Google Scholar 
75.Huang, L. & Shao, M. Advances and perspectives on soil water research in China’s Loess Plateau. Earth Sci. Rev. 199, 102962 (2019).Article 

Google Scholar 
76.Wang, L. & D’Odorico, P. Water limitations to large-scale desert agroforestry projects for carbon sequestration. Proc. Natl Acad. Sci. USA 116, 24925–24926 (2019).Article 

Google Scholar 
77.Bai, Y., Han, X., Wu, J., Chen, Z. & Li, L. Ecosystem stability and compensatory effects in the Inner Mongolia grassland. Nature 431, 181–184 (2004).Article 

Google Scholar 
78.Wu, Z., Dijkstra, P., Koch, G. W., Peñuelas, J. & Hungate, B. A. Responses of terrestrial ecosystems to temperature and precipitation change: a meta-analysis of experimental manipulation. Glob. Change Biol. 17, 927–942 (2011).Article 

Google Scholar 
79.Zhenghu, D., Honglang, X., Xinrong, L., Zhibao, D. & Gang, W. Evolution of soil properties on stabilized sands in the Tengger Desert, China. Geomorphology 59, 237–246 (2004).Article 

Google Scholar 
80.Wang, Y., Shao, M. A. & Shao, H. A preliminary investigation of the dynamic characteristics of dried soil layers on the Loess Plateau of China. J. Hydrol. 381, 9–17 (2010).Article 

Google Scholar 
81.Huang, J., Wang, T., Wang, W., Li, Z. & Yan, H. Climate effects of dust aerosols over East Asian arid and semiarid regions. J. Geophys. Res. Atmos. 119, 11–398 (2014).Article 

Google Scholar 
82.Cheng, S., Guan, X., Huang, J., Ji, F. & Guo, R. Long-term trend and variability of soil moisture over East Asia. J. Geophys. Res. Atmos. 120, 8658–8670 (2015).Article 

Google Scholar 
83.Wang, S., Fu, B., Chen, H. & Liu, Y. Regional development boundary of China’s Loess Plateau: water limit and land shortage. Land Use Policy 74, 130–136 (2018).Article 

Google Scholar 
84.Zhang, S. et al. Excessive afforestation and soil drying on China’s Loess Plateau. J. Geophys. Res. Biogeosci. 123, 923–935 (2018).Article 

Google Scholar 
85.Jia, X., Shao, M., Yu, D., Zhang, Y. & Binley, A. Spatial variations in soil-water carrying capacity of three typical revegetation species on the Loess Plateau, China. Agric. Ecosyst. Environ. 273, 25–35 (2019).Article 

Google Scholar 
86.Piao, S., Fang, J., Liu, H. & Zhu, B. NDVI-indicated decline in desertification in China in the past two decades. Geophys. Res. Lett. 32, L06402 (2005).Article 

Google Scholar 
87.Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Envir. 1, 14–27 (2020).Article 

Google Scholar 
88.Zhu, Z. et al. Greening of the Earth and its drivers. Nat. Clim. Change 6, 791–795 (2016).Article 

Google Scholar 
89.D’Odorico, P., Bhattachan, A., Davis, K. F., Ravi, S. & Runyan, C. W. Global desertification: drivers and feedbacks. Adv. Water Resour. 51, 326–344 (2013).Article 

Google Scholar 
90.Xue, Y. in Dryland Ecohydrology 139–169 (Springer, 2019).91.Peng, S.-S. et al. Afforestation in China cools local land surface temperature. Proc. Natl Acad. Sci. USA 111, 2915–2919 (2014).Article 

Google Scholar 
92.Li, S. G. et al. Micrometeorological changes following establishment of artificially established artemisia vegetation on desertified sandy land in the Horqin sandy land, China and their implication on regional environmental change. J. Arid. Environ. 52, 101–119 (2002).Article 

Google Scholar 
93.Li, Y. et al. Divergent hydrological response to large-scale afforestation and vegetation greening in China. Sci. Adv. 4, eaar4182 (2018).Article 

Google Scholar 
94.Xue, Y. The impact of desertification in the Mongolian and the Inner Mongolian grassland on the regional climate. J. Clim. 9, 2173–2189 (1996).Article 

Google Scholar 
95.Chen, L., Ma, Z. & Zhao, T. Modeling and analysis of the potential impacts on regional climate due to vegetation degradation over arid and semi-arid regions of China. Clim. Change 144, 461–473 (2017).Article 

Google Scholar 
96.Peng, D. et al. The influences of drought and land-cover conversion on inter-annual variation of NPP in the Three-North Shelterbelt Program zone of China based on MODIS data. PLoS ONE 11, e0158173 (2016).Article 

Google Scholar 
97.Wang, F., Pan, X., Wang, D., Shen, C. & Lu, Q. Combating desertification in China: past, present and future. Land Use Policy 31, 311–313 (2013).Article 

Google Scholar 
98.Chen, C. et al. China and India lead in greening of the world through land-use management. Nat. Sustain. 2, 122–129 (2019).Article 

Google Scholar 
99.Tong, X. et al. Increased vegetation growth and carbon stock in China karst via ecological engineering. Nat. Sustain. 1, 44–50 (2018).Article 

Google Scholar 
100.Lu, F. et al. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010. Proc. Natl Acad. Sci. USA 115, 4039–4044 (2018).Article 

Google Scholar 
101.Deng, L., Liu, G. & Shangguan, Z. Land-use conversion and changing soil carbon stocks in China’s ‘Grain-for-Green’ Program: a synthesis. Glob. Change Biol. 20, 3544–3556 (2014).Article 

Google Scholar 
102.Zhao, Y., Wu, J., He, C. & Ding, G. Linking wind erosion to ecosystem services in drylands: a landscape ecological approach. Landsc. Ecol. 32, 2399–2417 (2017).Article 

Google Scholar 
103.Gao, Y., Dang, P., Zhao, Q., Liu, J. & Liu, J. Effects of vegetation rehabilitation on soil organic and inorganic carbon stocks in the Mu Us Desert, northwest China. Land Degrad. Dev. 29, 1031–1040 (2018).Article 

Google Scholar 
104.Xu, J., Chen, J., Liu, Y. & Fan, F. Identification of the geographical factors influencing the relationships between ecosystem services in the Belt and Road region from 2010 to 2030. J. Clean. Prod. 275, 124153 (2020).Article 

Google Scholar 
105.Viña, A., McConnell, W. J., Yang, H., Xu, Z. & Liu, J. Effects of conservation policy on China’s forest recovery. Sci. Adv. 2, e1500965 (2016).Article 

Google Scholar 
106.Xu, W. et al. Strengthening protected areas for biodiversity and ecosystem services in China. Proc. Natl Acad. Sci. USA 114, 1601–1606 (2017).Article 

Google Scholar 
107.Xu, J. China’s new forests aren’t as green as they seem. Nature 477, 371–371 (2011).Article 

Google Scholar 
108.Hua, F. et al. Opportunities for biodiversity gains under the world’s largest reforestation programme. Nat. Commun. 7, 1–11 (2016).
Google Scholar 
109.Kong, Z.-H., Stringer, L. C., Paavola, J. & Lu, Q. Situating China in the global effort to combat desertification. Land 10, 702 (2021).Article 

Google Scholar 
110.Cao, S. et al. Greening China naturally. Ambio 40, 828–831 (2011).Article 

Google Scholar 
111.Chen, H., Shao, M. & Li, Y. Soil desiccation in the Loess Plateau of China. Geoderma 143, 91–100 (2008).Article 

Google Scholar 
112.Chu, X., Zhan, J., Li, Z., Zhang, F. & Qi, W. Assessment on forest carbon sequestration in the Three-North Shelterbelt Program region, China. J. Clean. Prod. 215, 382–389 (2019).Article 

Google Scholar 
113.Yang, H., Huang, Q., Zhang, J., Songer, M. & Liu, J. Range-wide assessment of the impact of China’s nature reserves on giant panda habitat quality. Sci. Total. Environ. 769, 145081 (2021).Article 

Google Scholar 
114.Feng, C. et al. Which management measures lead to better performance of China’s protected areas in reducing forest loss? Sci. Total Environ. 764, 142895 (2021).Article 

Google Scholar 
115.Bastin, J.-F. et al. The global tree restoration potential. Science 365, 76–79 (2019).Article 

Google Scholar 
116.Luedeling, E. et al. Forest restoration: overlooked constraints. Science 366, 315–315 (2019).Article 

Google Scholar 
117.Stenzel, F., Gerten, D., Werner, C. & Jägermeyr, J. Freshwater requirements of large-scale bioenergy plantations for limiting global warming to 1.5 °C. Environ. Res. Lett. 14, 084001 (2019).Article 

Google Scholar 
118.Morton, S. et al. A fresh framework for the ecology of arid Australia. J. Arid. Environ. 75, 313–329 (2011).Article 

Google Scholar 
119.Sankaran, M. et al. Determinants of woody cover in African savannas. Nature 438, 846–849 (2005).Article 

Google Scholar 
120.Kotiaho, J. S. & Halme, P. The IPBES Assessment Report on Land Degradation and Restoration (Univ. of Jyväskylä, 2018).121.Bhattachan, A., D’Odorico, P., Dintwe, K., Okin, G. S. & Collins, S. L. Resilience and recovery potential of duneland vegetation in the southern Kalahari. Ecosphere 5, 1–14 (2014).Article 

Google Scholar 
122.Huang, J., Yu, H., Guan, X., Wang, G. & Guo, R. Accelerated dryland expansion under climate change. Nat. Clim. Change 6, 166 (2016).Article 

Google Scholar 
123.Yu, G. et al. Construction and progress of Chinese terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation. J. Geogr. Sci. 26, 803–826 (2016).Article 

Google Scholar 
124.Fu, B. et al. Chinese ecosystem research network: progress and perspectives. Ecol. Complex. 7, 225–233 (2010).Article 

Google Scholar 
125.Wang, C. et al. Aridity threshold in controlling ecosystem nitrogen cycling in arid and semi-arid grasslands. Nat. Commun. 5, 4799 (2014).Article 

Google Scholar 
126.Fu, B. et al. The Global-DEP conceptual framework — research on dryland ecosystems to promote sustainability. Curr. Opin. Environ. Sustain. 48, 17–28 (2021).Article 

Google Scholar 
127.Assessment, M. E. Ecosystems and Human Well-Being Vol. 5 (Island, 2005).128.Zhu, Q., Castellano, M. J. & Yang, G. Coupling soil water processes and the nitrogen cycle across spatial scales: potentials, bottlenecks and solutions. Earth Sci. Rev. 187, 248–258 (2018).Article 

Google Scholar 
129.Fu, B. Promoting geography for sustainability. Geogr. Sustain. 1, 1–7 (2020).
Google Scholar 
130.Fu, B. et al. The research priorities of resources and environmental sciences. Geogr. Sustain. 2, 87–94 (2021).
Google Scholar 
131.Li, C., Zhang, C., Luo, G. & Chen, X. Modeling the carbon dynamics of the dryland ecosystems in Xinjiang, China from 1981 to 2007 — the spatiotemporal patterns and climate controls. Ecol. Model. 267, 148–157 (2013).Article 

Google Scholar 
132.Maestre, F. T. et al. Plant species richness and ecosystem multifunctionality in global drylands. Science 335, 214–218 (2012).Article 

Google Scholar 
133.Zhang, Y., Zhao, R., Liu, Y., Huang, K. & Zhu, J. Sustainable wildlife protection on the Qingzang Plateau. Geogr. Sustain. 2, 40–47 (2021).
Google Scholar 
134.Wang, X., Chen, F. & Dong, Z. The relative role of climatic and human factors in desertification in semiarid China. Glob. Environ. Change 16, 48–57 (2006).Article 

Google Scholar 
135.An, S. et al. Soil quality degradation processes along a deforestation chronosequence in the Ziwuling area, China. Catena 75, 248–256 (2008).Article 

Google Scholar 
136.Huang, J. et al. Global desertification vulnerability to climate change and human activities. Land Degrad. Dev. 31, 1380–1391 (2020).Article 

Google Scholar 
137.Sun, D. et al. The effects of land use change on soil infiltration capacity in China: a meta-analysis. Sci. Total Environ. 626, 1394–1401 (2018).Article 

Google Scholar 
138.Ren, C. et al. Linkages of C:N:P stoichiometry and bacterial community in soil following afforestation of former farmland. For. Ecol. Manag. 376, 59–66 (2016).Article 

Google Scholar 
139.Fu, Q. & Feng, S. Responses of terrestrial aridity to global warming. J. Geophys. Res. Atmos. 119, 7863–7875 (2014).Article 

Google Scholar 
140.Feng, S. & Fu, Q. Expansion of global drylands under a warming climate. Atmos. Chem. Phys. 13, 10081–10094 (2013).Article 

Google Scholar 
141.Huang, J., Yu, H., Dai, A., Wei, Y. & Kang, L. Drylands face potential threat under 2 °C global warming target. Nat. Clim. Change 7, 417–422 (2017).Article 

Google Scholar  More

1.Rothschild, L. J. & Mancinelli, R. L. Life in extreme environments. Nature 409, 1092–1101 (2001).CAS 
PubMed 

Google Scholar 
2.Schmid, A. K., Allers, T. & DiRuggiero, J. Snapshot: microbial extremophiles. Cell 180, 818–818.e1 (2020).CAS 
PubMed 

Google Scholar 
3.Denef, V. J., Mueller, R. S. & Banfield, J. F. AMD biofilms: using model communities to study microbial evolution and ecological complexity in nature. ISME J. 4, 599–610 (2010).PubMed 

Google Scholar 
4.Inskeep, W. P. et al. The YNP metagenome project: environmental parameters responsible for microbial distribution in the Yellowstone geothermal ecosystem. Front. Microbiol. 4, 67 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
5.Oren, A. Halophilic microbial communities and their environments. Curr. Opin. Microbiol. 33, 119–124 (2015).CAS 

Google Scholar 
6.Reysenbach, A. L., Wickham, G. S. & Pace, N. R. Phylogenetic analysis of the hyperthermophilic pink filament community in Octopus Spring, Yellowstone National Park. Appl. Environ. Microbiol. 60, 2113–2119 (1994).CAS 
PubMed 
PubMed Central 

Google Scholar 
7.Bond, P. L., Smriga, S. P. & Banfield, J. F. Phylogeny of microorganisms populating a thick, subaerial, predominantly lithotrophic biofilm at an extreme acid mine drainage site. Appl. Environ. Microbiol. 66, 3842–3849 (2000).CAS 
PubMed 
PubMed Central 

Google Scholar 
8.Huber, J. A. et al. Microbial population structures in the deep marine biosphere. Science 318, 97–100 (2007).CAS 
PubMed 

Google Scholar 
9.Kuang, J. L. et al. Contemporary environmental variation determines microbial diversity patterns in acid mine drainage. ISME J. 7, 1038–1050 (2013).CAS 
PubMed 

Google Scholar 
10.Power, J. F. et al. Microbial biogeography of 925 geothermal springs in New Zealand. Nat. Commun. 9, 2876 (2018). Extensive sampling and high-throughput 16S rRNA gene sequencing have provided deeper insights into the patterns and ecological drivers of microbial communities inhabiting geothermal springs.PubMed 
PubMed Central 

Google Scholar 
11.Podell, S. et al. Seasonal fluctuations in ionic concentrations drive microbial succession in a hypersaline lake community. ISME J. 8, 979–990 (2014).CAS 
PubMed 

Google Scholar 
12.Chen, L. X. et al. Comparative metagenomic and metatranscriptomic analyses of microbial communities in acid mine drainage. ISME J. 9, 1579–1592 (2015).PubMed 

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

Google Scholar 
14.Brown, C. T. et al. Unusual biology across a group comprising more than 15% of domain Bacteria. Nature 523, 208–211 (2015).CAS 
PubMed 

Google Scholar 
15.Castelle, C. J. et al. Genomic expansion of domain archaea highlights roles for organisms from new phyla in anaerobic carbon cycling. Curr. Biol. 25, 690–701 (2015). The cultivation-independent reconstruction of the first complete genomes for members of the DPANN archaea allowed confident prediction of incomplete or absent pathways for these enigmatic organisms.CAS 
PubMed 

Google Scholar 
16.Sharp, C. E. et al. Humboldt’s spa: microbial diversity is controlled by temperature in geothermal environments. ISME J. 8, 1166–1174 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
17.Hedlund, B. P. et al. Uncultivated thermophiles: current status and spotlight on ‘Aigarchaeota’. Curr. Opin. Microbiol. 25, 136–145 (2015).CAS 
PubMed 

Google Scholar 
18.Hua, Z. S. et al. Ecological roles of dominant and rare prokaryotes in acid mine drainage revealed by metagenomics and metatranscriptomics. ISME J. 9, 1280–1294 (2015).CAS 
PubMed 

Google Scholar 
19.Tyson, G. W. et al. Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature 428, 37–43 (2004). This is the first shotgun metagenomic sequencing study that enabled reconstruction of near-complete microbial genomes directly (without cultivation) from a natural community.CAS 
PubMed 

Google Scholar 
20.Castelle, C. J. & Banfield, J. F. Major new microbial groups expand diversity and alter our understanding of the tree of life. Cell 172, 1181–1197 (2018).CAS 
PubMed 

Google Scholar 
21.Chen, L. X. et al. Metabolic versatility of small archaea Micrarchaeota and Parvarchaeota. ISME J. 12, 756–775 (2018).CAS 
PubMed 

Google Scholar 
22.Baker, B. J. et al. Enigmatic, ultrasmall, uncultivated Archaea. Proc. Natl Acad. Sci. USA 107, 8806–8811 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
23.Narasingarao, P. et al. De novo metagenomic assembly reveals abundant novel major lineage of Archaea in hypersaline microbial communities. ISME J. 6, 81–93 (2012).CAS 
PubMed 

Google Scholar 
24.Brock, T. D. Life at high temperatures. Science 158, 1012–1019 (1967).CAS 
PubMed 

Google Scholar 
25.Cole, J. K. et al. Sediment microbial communities in Great Boiling Spring are controlled by temperature and distinct from water communities. ISME J. 7, 718–729 (2013).CAS 
PubMed 

Google Scholar 
26.Colman, D. R. et al. Ecological differentiation in planktonic and sediment-associated chemotrophic microbial populations in Yellowstone hot springs. FEMS Microbiol. Ecol. 92, fiw137 (2016).PubMed 

Google Scholar 
27.Ward, D. M. et al. 16S rRNA sequences reveal numerous uncultured microorganisms in a natural community. Nature 345, 63–65 (1990).CAS 
PubMed 

Google Scholar 
28.Miller, S. R. et al. Bar-coded pyrosequencing reveals shared bacterial community properties along the temperature gradients of two alkaline hot springs in Yellowstone National Park. Appl. Environ. Microbiol. 75, 4565–4572 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
29.Ward, L. et al. Microbial community dynamics in Inferno Crater Lake, a thermally fluctuating geothermal spring. ISME J. 11, 1158–1167 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
30.Barns, S. M., Fundyga, R. E., Jeffries, M. W. & Pace, N. R. Remarkable archaeal diversity detected in a Yellowstone National Park hot spring environment. Proc. Natl Acad. Sci. USA 91, 1609–1613 (1994).CAS 
PubMed 
PubMed Central 

Google Scholar 
31.Takai, K. & Yoshihiko, S. A molecular view of archaeal diversity in marine and terrestrial hot water environments. FEMS Microbiol. Ecol. 28, 177–188 (1999).CAS 

Google Scholar 
32.Elkins, J. G. et al. A korarchaeal genome reveals insights into the evolution of the Archaea. Proc. Natl Acad. Sci. USA 105, 8102–8107 (2008).CAS 
PubMed 
PubMed Central 

Google Scholar 
33.Dombrowski, N., Teske, A. P. & Baker, B. J. Expansive microbial metabolic versatility and biodiversity in dynamic Guaymas Basin hydrothermal sediments. Nat. Commun. 9, 4999 (2018).PubMed 
PubMed Central 

Google Scholar 
34.Nunoura, T. et al. Genetic and functional properties of uncultivated thermophilic crenarchaeotes from a subsurface gold mine as revealed by analysis of genome fragments. Environ. Microbiol. 7, 1967–1984 (2005).CAS 
PubMed 

Google Scholar 
35.Nunoura, T. et al. Insights into the evolution of Archaea and eukaryotic protein modifier systems revealed by the genome of a novel archaeal group. Nucleic Acids Res. 39, 3204–3223 (2011).CAS 
PubMed 

Google Scholar 
36.Beam, J. P. et al. Ecophysiology of an uncultivated lineage of Aigarchaeota from an oxic, hot spring filamentous ‘streamer’ community. ISME J. 10, 210–224 (2016).CAS 
PubMed 

Google Scholar 
37.Hua, Z. S. et al. Genomic inference of the metabolism and evolution of the archaeal phylum Aigarchaeota. Nat. Commun. 9, 2832 (2018).PubMed 
PubMed Central 

Google Scholar 
38.Takami, H. et al. A deeply branching thermophilic bacterium with an ancient acetyl-CoA pathway dominates a subsurface ecosystem. PLoS ONE 7, e30559 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
39.Colman, D. R. et al. Novel, deep-branching heterotrophic bacterial populations recovered from thermal spring metagenomes. Front. Microbiol. 7, 304 (2016).PubMed 
PubMed Central 

Google Scholar 
40.Nobu, M. et al. Phylogeny and physiology of candidate phylum ‘Atribacteria’ (OP9/JS1) inferred from cultivation-independent genomics. ISME J. 10, 273–286 (2016).CAS 
PubMed 

Google Scholar 
41.Hugenholtz, P., Pitulle, C., Hershberger, K. L. & Pace, N. R. Novel division level bacterial diversity in a Yellowstone hot spring. J. Bacteriol. 180, 366–376 (1998).CAS 
PubMed 
PubMed Central 

Google Scholar 
42.Orcutt, B. N., Sylvan, J. B., Knab, N. J. & Edwards, K. J. Microbial ecology of the dark ocean above, at, and below the seafloor. Microbiol. Mol. Biol. Rev. 75, 361–422 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
43.Eloe-Fadrosh, E. A. et al. Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs. Nat. Commun. 7, 10476 (2016). This is a good example of how analysis of the increasing wealth of metagenomic data collected from diverse environments may lead to the discovery of novel major lineages.CAS 
PubMed 
PubMed Central 

Google Scholar 
44.Kelley, D. S., Baross, J. A. & Delaney, J. R. Volcanoes, fluids, and life at Mid-Ocean Ridge spreading centers. Annu. Rev. Earth Planet. Sci. 30, 385–491 (2002).CAS 

Google Scholar 
45.Perner, M. et al. In situ chemistry and microbial community compositions in five deep-sea hydrothermal fluid samples from Irina II in the Logatchev field. Environ. Microbiol. 15, 1551–1560 (2013).CAS 
PubMed 

Google Scholar 
46.Flores, G. E. et al. Microbial community structure of hydrothermal deposits from geochemically different vent fields along the Mid-Atlantic Ridge. Environ. Microbiol. 13, 2158–2171 (2011).CAS 
PubMed 

Google Scholar 
47.Dick, G. J. et al. The microbiomes of deep-sea hydrothermal vents: distributed globally, shaped locally. Nat. Rev. Microbiol. 17, 271–283 (2019).CAS 
PubMed 

Google Scholar 
48.Campbell, B. J., Summers Engel, A., Porter, M. L. & Takai, K. The versatile ε-proteobacteria: key players in sulphidic habitats. Nat. Rev. Microbiol. 4, 458–468 (2006).CAS 
PubMed 

Google Scholar 
49.Reysenbach, A. L., Longnecker, K. & Kirshtein, J. Novel bacterial and archaeal lineages from an in situ growth chamber deployed at a Mid-Atlantic Ridge hydrothermal vent. Appl. Environ. Microbiol. 66, 3798–3806 (2000).CAS 
PubMed 
PubMed Central 

Google Scholar 
50.Takai, K., Komatsu, T., Inagaki, F. & Horikoshi, K. Distribution of archaea in a black smoker chimney structure. Appl. Environ. Microbiol. 67, 3618–3629 (2001).CAS 
PubMed 
PubMed Central 

Google Scholar 
51.Schrenk, M. O., Kelley, D. S., Bolton, S. A. & Baross, J. A. Low archaeal diversity linked to subseafloor geochemical processes at the Lost City Hydrothermal Field, Mid-Atlantic Ridge. Environ. Microbiol. 6, 1086–1095 (2004).CAS 
PubMed 

Google Scholar 
52.Brazelton, W. J., Schrenk, M. O., Kelley, D. S. & Baross, J. A. Methane- and sulfur-metabolizing microbial communities dominate the Lost City Hydrothermal Field ecosystem. Appl. Environ. Microbiol. 72, 6257–6270 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
53.Reveillaud, J. et al. Subseafloor microbial communities in hydrogen-rich vent fluids from hydrothermal systems along the Mid-Cayman Rise. Environ. Microbiol. 18, 1970–1987 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
54.Brazelton, W. J. et al. Archaea and bacteria with surprising micro-diversity show shifts in dominance over 1000-year time scales in hydrothermal chimneys. Proc. Natl Acad. Sci. USA 107, 1612–1617 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
55.Huber, H. et al. A new phylum of Archaea represented by a nanosized hyperthermophilic symbiont. Nature 417, 63–67 (2002).CAS 
PubMed 

Google Scholar 
56.Waters, E. et al. The genome of Nanoarchaeum equitans: insights into early archaeal evolution and derived parasitism. Proc. Natl Acad. Sci. USA 100, 12984–12988 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
57.Casanueva, A. et al. Nanoarchaeal 16S rRNA gene sequences are widely dispersed in hyperthermophilic and mesophilic halophilic environments. Extremophiles 12, 651–656 (2008).CAS 
PubMed 

Google Scholar 
58.Wurch, L. et al. Genomics-informed isolation and characterization of a symbiotic Nanoarchaeota system from a terrestrial geothermal environment. Nat. Commun. 7, 12115 (2016). This is an interesting study demonstrating that insights from genomic studies may help develop effective cultivation strategies for the isolation of novel microbial species.CAS 
PubMed 
PubMed Central 

Google Scholar 
59.Spang, A. et al. Complex archaea that bridge the gap between prokaryotes and eukaryotes. Nature 521, 173–179 (2015). The discovery and genomic characterization of Lokiarchaeota have unveiled insights into eukaryogenesis.CAS 
PubMed 
PubMed Central 

Google Scholar 
60.Seitz, K. W., Lazar, C. S., Hinrichs, K. U., Teske, A. P. & Baker, B. J. Genomic reconstruction of a novel, deeply branched sediment archaeal phylum with pathways for acetogenesis and sulfur reduction. ISME J. 10, 1696–1705 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
61.Zaremba-Niedzwiedzka, K. et al. Asgard archaea illuminate the origin of eukaryotic cellular complexity. Nature 541, 353–358 (2017).CAS 
PubMed 

Google Scholar 
62.Imachi, H. et al. Isolation of an archaeon at the prokaryote-eukaryote interface. Nature 577, 519–525 (2020). This study reports the isolation of the first member of the superphylum Asgard, confirming the existence of these archaea and their close phylogenetic relatedness to eukaryotes.CAS 
PubMed 
PubMed Central 

Google Scholar 
63.Margesin, R. & Collins, T. Microbial ecology of the cryosphere (glacial and permafrost habitats): current knowledge. Appl. Microbiol. Biotechnol. 103, 2537–2549 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
64.Boetius, A., Anesio, A. M., Deming, J. W., Mikucki, J. A. & Rapp, J. Z. Microbial ecology of the cryosphere: sea ice and glacial habitats. Nat. Rev. Microbiol. 13, 677–690 (2015).CAS 
PubMed 

Google Scholar 
65.Hoham, R. W. & Duval, B. in Snow Ecology (eds Jones, H. et al.) 168–228 (Cambridge Univ. Press, 2001).66.Edwards, A. et al. Coupled cryoconite ecosystem structure-function relationships are revealed by comparing bacterial communities in alpine and Arctic glaciers. FEMS Microbiol. Ecol. 89, 222–237 (2014).CAS 
PubMed 

Google Scholar 
67.Jungblut, A. D., Lovejoy, C. & Vincent, W. F. Global distribution of cyanobacterial ecotypes in the cold biosphere. ISME J. 4, 191–202 (2010).CAS 
PubMed 

Google Scholar 
68.Franzetti, A. et al. Temporal variability of bacterial communities in cryoconite on an alpine glacier. Environ. Microbiol. Rep. 9, 71–78 (2017).CAS 
PubMed 

Google Scholar 
69.Anesio, A. M., Hodson, A. J., Fritz, A., Psenner, R. & Sattler, B. High microbial activity on glaciers: importance to the global carbon cycle. Glob. Chang. Biol. 15, 955–960 (2009).
Google Scholar 
70.Christner, B. C. et al. A microbial ecosystem beneath the West Antarctic ice sheet. Nature 512, 310–313 (2014).CAS 
PubMed 

Google Scholar 
71.Hultman, J. et al. Multi-omics of permafrost, active layer and thermokarst bog soil microbiomes. Nature 521, 208–212 (2015).CAS 
PubMed 

Google Scholar 
72.Mackelprang, R. et al. Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw. Nature 480, 368–371 (2011).CAS 
PubMed 

Google Scholar 
73.Frey, B. et al. Microbial diversity in European alpine permafrost and active layers. FEMS Microbiol. Ecol. 92, fiw018 (2016).PubMed 

Google Scholar 
74.Fernández, A. B. et al. Prokaryotic taxonomic and metabolic diversity of an intermediate salinity hypersaline habitat assessed by metagenomics. FEMS Microbiol. Ecol. 88, 623–635 (2014).PubMed 

Google Scholar 
75.Ventosa, A. et al. Microbial diversity of hypersaline environments: a metagenomic approach. Curr. Opin. Microbiol. 25, 80–87 (2015).CAS 
PubMed 

Google Scholar 
76.Emerson, J. B. et al. Virus-host and CRISPR dynamics in Archaea-dominated hypersaline Lake Tyrrell, Victoria, Australia. Archaea 2013, 370871 (2013).PubMed 
PubMed Central 

Google Scholar 
77.Ley, R. E. et al. Unexpected diversity and complexity of the Guerrero Negro hypersaline microbial mat. Appl. Environ. Microbiol. 72, 3685–3695 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
78.Harris, J. K. et al. Phylogenetic stratigraphy in the Guerrero Negro hypersaline microbial mat. ISME J. 7, 50–60 (2013). This study retrieves an unprecedented number of nearly full length 16S rRNA gene sequences from the microbial mats of the Guerrero Negro hypersaline environment, Mexico, demonstrating them to be among the most diverse, complex and novel microbial ecosystems known.PubMed 

Google Scholar 
79.Vavourakis, C. D. et al. Metagenomic insights into the uncultured diversity and physiology of microbes in four hypersaline soda lake brines. Front. Microbiol. 7, 211 (2016).PubMed 
PubMed Central 

Google Scholar 
80.Hamm, J. N. et al. Unexpected host dependency of Antarctic Nanohaloarchaeota. Proc. Natl Acad. Sci. USA. 116, 14661–14670 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
81.Nigro, L. M., Hyde, A. S., MacGregor, B. J. & Teske, A. Phylogeography, salinity adaptations and metabolic potential of the candidate division KB1 bacteria based on a partial single cell genome. Front. Microbiol. 7, 1266 (2016).PubMed 
PubMed Central 

Google Scholar 
82.Vavourakis, C. D. et al. A metagenomics roadmap to the uncultured genome diversity in hypersaline soda lake sediments. Microbiome 6, 168 (2018).PubMed 
PubMed Central 

Google Scholar 
83.Edwards, K. J., Becker, K. & Colwell, F. The deep, dark energy biosphere: intraterrestrial life on Earth. Annu. Rev. Earth Planet. Sci. 40, 551–568 (2012).CAS 

Google Scholar 
84.Parkes, R. J. et al. A review of prokaryotic populations and processes in sub-seafloor sediments, including biosphere: geosphere interactions. Mar. Geol. 352, 409–425 (2014).CAS 

Google Scholar 
85.Starnawski, P. et al. Microbial community assembly and evolution in subseafloor sediment. Proc. Natl Acad. Sci. USA 114, 2940–2945 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
86.Ciobanu, M. C. et al. Microorganisms persist at record depths in the subseafloor of the Canterbury Basin. ISME J. 8, 1370–1380 (2014).PubMed 
PubMed Central 

Google Scholar 
87.Inagaki, F. et al. Exploring deep microbial life in coal-bearing sediment down to ~2.5 km below the ocean floor. Science 349, 420–424 (2015).CAS 
PubMed 

Google Scholar 
88.D’Hondt, S., Pockalny, R., Fulfer, V. M. & Spivack, A. J. Subseafloor life and its biogeochemical impacts. Nat. Commun. 10, 3519 (2019).PubMed 
PubMed Central 

Google Scholar 
89.Petro, C., Starnawski, P., Schramm, A. & Kjeldsen, K. U. Microbial community assembly in marine sediments. Aquat. Microb. Ecol. 79, 177–195 (2017).
Google Scholar 
90.Teske, A. & Sørensen, K. B. Uncultured archaea in deep marine subsurface sediments: have we caught them all? ISME J. 2, 3–18 (2008).CAS 
PubMed 

Google Scholar 
91.Orsi, W. D. Ecology and evolution of seafloor and subseafloor microbial communities. Nat. Rev. Microbiol. 16, 671–683 (2018).CAS 
PubMed 

Google Scholar 
92.Sørensen, K. B. & Teske, A. Stratified communities of active Archaea in deep marine subsurface sediments. Appl. Environ. Microbiol. 72, 4596–4603 (2006).PubMed 
PubMed Central 

Google Scholar 
93.Walsh, E. A. et al. Relationship of bacterial richness to organic degradation rate and sediment age in subseafloor sediment. Appl. Environ. Microbiol. 82, 4994–4999 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
94.Petro, C. et al. Marine deep biosphere microbial communities assemble in near-surface sediments in Aarhus Bay. Front. Microbiol. 10, 758 (2019).PubMed 
PubMed Central 

Google Scholar 
95.Jorgensen, S. L. et al. Correlating microbial community profiles with geochemical data in highly stratified sediments from the Arctic Mid-Ocean Ridge. Proc. Natl Acad. Sci. USA 109, E2846–E2855 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
96.Edwards, K. J., Wheat, C. G. & Sylvan, J. B. Under the sea: microbial life in volcanic oceanic crust. Nat. Rev. Microbiol. 9, 703–712 (2011).CAS 
PubMed 

Google Scholar 
97.Li, J. et al. Recycling and metabolic flexibility dictate life in the lower oceanic crust. Nature 579, 250–255 (2020). This is a multiple-approach exploration to provide the first insights into the ultralow-biomass microbial assemblages inhabiting the lithified lower oceanic crust.CAS 
PubMed 

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

Google Scholar 
99.Nyyssönen, M. et al. Taxonomically and functionally diverse microbial communities in deep crystalline rocks of the Fennoscandian shield. ISME J. 8, 126–138 (2014).PubMed 

Google Scholar 
100.Lin, X., Kennedy, D., Fredrickson, J., Bjornstad, B. & Konopka, A. Vertical stratification of subsurface microbial community composition across geological formations at the Hanford Site. Environ. Microbiol. 14, 414–425 (2012).CAS 
PubMed 

Google Scholar 
101.Osburn, M. R. et al. Chemolithotrophy in the continental deep subsurface: Sanford Underground Research Facility (SURF), USA. Front. Microbiol. 5, 610 (2014).PubMed 
PubMed Central 

Google Scholar 
102.Magnabosco, C. et al. The biomass and biodiversity of the continental subsurface. Nat. Geosci. 11, 707–717 (2018).CAS 

Google Scholar 
103.Navarro-Noya, Y. E. et al. Pyrosequencing analysis of the bacterial community in drinking water wells. Microb. Ecol. 66, 19–29 (2013).PubMed 

Google Scholar 
104.Wrighton, K. C. et al. Fermentation, hydrogen, and sulfur metabolism in multiple uncultivated bacterial phyla. Science 337, 1661–1665 (2012).CAS 
PubMed 

Google Scholar 
105.Bagnoud, A. et al. Reconstructing a hydrogen driven microbial metabolic network in Opalinus Clay rock. Nat. Commun. 7, 12770 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
106.Magnabosco, C. et al. A metagenomic window into carbon metabolism at 3 km depth in Precambrian continental crust. ISME J. 10, 730–741 (2016).CAS 
PubMed 

Google Scholar 
107.Hernsdorf, A. W. et al. Potential for microbial H2 and metal transformations associated with novel bacteria and archaea in deep terrestrial subsurface sediments. ISME J. 11, 1915–1929 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
108.Anantharaman, K. et al. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat. Commun. 7, 13219 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
109.Kantor, R. S. et al. Small genomes and sparse metabolisms of sediment-associated bacteria from four candidate phyla. mBio 4, e00708–e00713 (2013).PubMed 
PubMed Central 

Google Scholar 
110.Wrighton, K. C. et al. Metabolic interdependencies between phylogenetically novel fermenters and respiratory organisms in an unconfined aquifer. ISME J. 8, 1452–1463 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
111.Hallberg, K. B., Coupland, K., Kimura, S. & Johnson, D. B. Macroscopic streamer growths in acidic, metal-rich mine waters in north Wales consist of novel and remarkably simple bacterial communities. Appl. Environ. Microbiol. 72, 2022–2030 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
112.Belnap, C. P. et al. Quantitative proteomic analyses of the response of acidophilic microbial communities to different pH conditions. ISME J. 5, 1152–1161 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
113.Edwards, K. J. et al. Seasonal variations in microbial populations and environmental conditions in an extreme acid mine drainage environment. Appl. Environ. Microbiol. 65, 3627–3632 (1999).CAS 
PubMed 
PubMed Central 

Google Scholar 
114.Liu, J. et al. Correlating microbial diversity patterns with geochemistry in an extreme and heterogeneous environment of mine tailings. Appl. Environ. Microbiol. 80, 3677–3686 (2014).PubMed 
PubMed Central 

Google Scholar 
115.Golyshina, O. V. et al. ‘ARMAN’ archaea depend on association with euryarchaeal host in culture and in situ. Nat. Commun. 8, 60 (2017).PubMed 
PubMed Central 

Google Scholar 
116.Antony, C. P. et al. Microbiology of Lonar Lake and other soda lakes. ISME J. 7, 468–476 (2013).PubMed 

Google Scholar 
117.Sorokin, D. Y. et al. Microbial diversity and biogeochemical cycling in soda lakes. Extremophiles 18, 791–809 (2014).CAS 
PubMed 
PubMed Central 

Google Scholar 
118.Reynolds, J. F. et al. Global desertification: building a science for dryland development. Science 316, 847–851 (2007).CAS 
PubMed 

Google Scholar 
119.Maestre, F. T. et al. Increasing aridity reduces soil microbial diversity and abundance in global drylands. Proc. Natl Acad. Sci. USA. 112, 15684–15689 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
120.Makhalanyane, T. P. et al. Microbial ecology of hot desert edaphic systems. FEMS Microbiol. Rev. 39, 203–221 (2015).CAS 
PubMed 

Google Scholar 
121.Reinthaler, T. et al. Prokaryotic respiration and production in the meso- and bathypelagic realm of the eastern and western North Atlantic basin. Limnol. Oceanogr. 51, 1262–1273 (2006).CAS 

Google Scholar 
122.Hewson, I., Steele, J. A., Capone, D. G. & Fuhrman, J. A. Remarkable heterogeneity in meso- and bathypelagic bacterioplankton assemblage composition. Limnol. Oceanogr. 51, 1274–1283 (2006).
Google Scholar 
123.DeLong, E. F. et al. Community genomics among stratified microbial assemblages in the ocean’s interior. Science 311, 496–503 (2006).CAS 
PubMed 

Google Scholar 
124.Pham, V. D., Konstantinidis, K. T., Palden, T. & DeLong, E. F. Phylogenetic analyses of ribosomal DNA-containing bacterioplankton genome fragments from a 4000 m vertical profile in the North Pacific Subtropical Gyre. Environ. Microbiol. 10, 2313–2330 (2008).CAS 
PubMed 

Google Scholar 
125.Karner, M. B., DeLong, E. F. & Karl, D. M. Archaeal dominance in the mesopelagic zone of the Pacific Ocean. Nature 409, 507–510 (2001).CAS 
PubMed 

Google Scholar 
126.Ziegler, S. et al. Oxygen-dependent niche formation of a pyrite-dependent acidophilic consortium built by archaea and bacteria. ISME J. 7, 1725–1737 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
127.Méndez-García, C. et al. Microbial stratification in low pH oxic and suboxic macroscopic growths along an acid mine drainage. ISME J. 8, 1259–1274 (2014).PubMed 
PubMed Central 

Google Scholar 
128.Klatt, C. G. et al. Temporal metatranscriptomic patterning in phototrophic Chloroflexi inhabiting a microbial mat in a geothermal spring. ISME J. 7, 1775–1789 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
129.Klatt, C. G. et al. Community structure and function of high-temperature chlorophototrophic microbial mats inhabiting diverse geothermal environments. Front. Microbiol. 4, 106 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
130.Inskeep, W. P. et al. Metagenomes from high-temperature chemotrophic systems reveal geochemical controls on microbial community structure and function. PLoS ONE 5, e9773 (2010).PubMed 
PubMed Central 

Google Scholar 
131.Swingley, W. D. et al. Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem. PLoS ONE 7, e38108 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
132.Liu, Z. et al. Metatranscriptomic analyses of chlorophototrophs of a hot-spring microbial mat. ISME J. 5, 1279–1290 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
133.Woodcroft, B. J. et al. Genome-centric view of carbon processing in thawing permafrost. Nature 560, 49–54 (2018).CAS 
PubMed 

Google Scholar 
134.Ghai, R. et al. New abundant microbial groups in aquatic hypersaline environments. Sci. Rep. 1, 135 (2011).PubMed 
PubMed Central 

Google Scholar 
135.Uritskiy, G. et al. Halophilic microbial community compositional shift after a rare rainfall in the Atacama Desert. ISME J. 13, 2737–2749 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
136.Uritskiy, G. et al. Cellular life from the three domains and viruses are transcriptionally active in a hypersaline desert community. Environ. Microbiol. 23, 3401–3417 (2021).CAS 
PubMed 

Google Scholar 
137.Herrmann, M. et al. Large fractions of CO2-fixing microorganisms in pristine limestone aquifers appear to be involved in the oxidation of reduced sulfur and nitrogen compounds. Appl. Environ. Microbiol. 81, 2384–2394 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
138.Probst, A. J. et al. Differential depth distribution of microbial function and putative symbionts through sediment-hosted aquifers in the deep terrestrial subsurface. Nat. Microbiol. 3, 328–336 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
139.Mueller, R. S. et al. Ecological distribution and population physiology defined by proteomics in a natural microbial community. Mol. Syst. Biol. 6, 374 (2010).PubMed 
PubMed Central 

Google Scholar 
140.Chen, L. X. et al. Shifts in microbial community composition and function in the acidification of a lead/zinc mine tailings. Environ. Microbiol. 15, 2431–2444 (2013).CAS 
PubMed 

Google Scholar 
141.Mueller, R. S. et al. Proteome changes in the initial bacterial colonist during ecological succession in an acid mine drainage biofilm community. Environ. Microbiol. 13, 2279–2292 (2011).CAS 
PubMed 

Google Scholar 
142.Mosier, A. C. et al. Elevated temperature alters proteomic responses of individual organisms within a biofilm community. ISME J. 9, 180–194 (2015).CAS 
PubMed 

Google Scholar 
143.Papke, R. T., Koenig, J. E., Rodriguez-Valera, F. & Doolittle, W. F. Frequent recombination in a saltern population of Halorubrum. Science 306, 1928–1929 (2004).CAS 
PubMed 

Google Scholar 
144.Whitaker, R. J., Grogan, D. W. & Taylor, J. W. Recombination shapes the natural population structure of the hyperthermophilic archaeon Sulfolobus islandicus. Mol. Biol. Evol. 22, 2354–2361 (2005).CAS 
PubMed 

Google Scholar 
145.Naor, A., Lapierre, P., Mevarech, M., Papke, R. T. & Gophna, U. Low species barriers in halophilic archaea and the formation of recombinant hybrids. Curr. Biol. 22, 1444–1448 (2012).CAS 
PubMed 

Google Scholar 
146.Reno, M. L., Held, N. L., Fields, C. J., Burke, P. V. & Whitaker, R. J. Biogeography of the Sulfolobus islandicus pan-genome. Proc. Natl Acad. Sci. USA 106, 8605–8610 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
147.Mongodin, E. F. et al. The genome of Salinibacter Ruber: convergence and gene exchange among hyperhalophilic bacteria and archaea. Proc. Natl Acad. Sci. USA 102, 18147–18152 (2005).CAS 
PubMed 
PubMed Central 

Google Scholar 
148.Nelson-Sathi, S. et al. Acquisition of 1,000 eubacterial genes physiologically transformed a methanogen at the origin of Haloarchaea. Proc. Natl Acad. Sci. USA 109, 20537–20542 (2012). Comparative genomics provides evidence that massive amounts of gene influx from bacterial sources may have led to the drastic change in lifestyle in the extremely salt tolerant Haloarchaea.CAS 
PubMed 
PubMed Central 

Google Scholar 
149.Wolf, Y. I., Makarova, K. S., Yutin, N. & Koonin, E. V. Updated clusters of orthologous genes for Archaea: a complex ancestor of the Archaea and the byways of horizontal gene transfer. Biol. Direct 7, 46 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
150.Nelson-Sathi, S. et al. Origins of major archaeal clades correspond to gene acquisitions from bacteria. Nature 517, 77–80 (2015).CAS 
PubMed 

Google Scholar 
151.Simmons, S. L. et al. Population genomic analysis of strain variation in Leptospirillum group II bacteria involved in acid mine drainage formation. PLoS Biol. 6, e177 (2008).PubMed 
PubMed Central 

Google Scholar 
152.Lo, I. et al. Strain-resolved community proteomics reveals recombining genomes of acidophilic bacteria. Nature 446, 537–541 (2007).CAS 
PubMed 

Google Scholar 
153.Denef, V. J. et al. Proteomics-inferred genome typing (PIGT) demonstrates inter-population recombination as a strategy for environmental adaptation. Environ. Microbiol. 11, 313–325 (2009).CAS 
PubMed 

Google Scholar 
154.Denef, V. J. et al. Proteogenomic basis for ecological divergence of closely related bacteria in natural acidophilic microbial communities. Proc. Natl Acad. Sci. USA 107, 2383–2390 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
155.Denef, V. J. & Banfield, J. F. In situ evolutionary rate measurements show ecological success of recently emerged bacterial hybrids. Science 336, 462–466 (2012). This study provides a time-series population metagenomic analysis of microorganisms in exceptionally low diversity AMD biofilms, allowing for the first time measurement of evolutionary rates for wild populations.CAS 
PubMed 

Google Scholar 
156.Brochier-Armanet, C., Boussau, B., Gribaldo, S. & Forterre, P. Mesophilic Crenarchaeota: proposal for a third archaeal phylum, the Thaumarchaeota. Nat. Rev. Microbiol. 6, 245–252 (2008).CAS 
PubMed 

Google Scholar 
157.Kelly, S., Wickstead, B. & Gull, K. Archaeal phylogenomics provides evidence in support of a methanogenic origin of the Archaea and a thaumarchaeal origin for the eukaryotes. Proc. Biol. Sci. 278, 1009–1018 (2011).CAS 
PubMed 

Google Scholar 
158.Sorokin, D. Y. et al. Discovery of extremely halophilic, methyl-reducing euryarchaea provides insights into the evolutionary origin of methanogenesis. Nat. Microbiol. 2, 17081 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
159.Baker, B. J. et al. Diversity, ecology and evolution of archaea. Nat. Microbiol. 5, 887–900 (2020).CAS 
PubMed 

Google Scholar 
160.Paul, B. G. et al. Targeted diversity generation by intraterrestrial archaea and archaeal viruses. Nat. Commun. 6, 6585 (2015).CAS 
PubMed 

Google Scholar 
161.Paul, B. G. et al. Retroelement-guided protein diversification abounds in vast lineages of Bacteria and Archaea. Nat. Microbiol. 2, 17045 (2017).CAS 
PubMed 
PubMed Central 

Google Scholar 
162.Burstein, D. et al. New CRISPR-Cas systems from uncultivated microbes. Nature 542, 237–241 (2017).CAS 
PubMed 

Google Scholar 
163.Anderson, R. E. et al. Genomic variation in microbial populations inhabiting the marine subseafloor at deep-sea hydrothermal vents. Nat. Commun. 8, 1114 (2017).PubMed 
PubMed Central 

Google Scholar 
164.Brazelton, W. J. & Baross, J. A. Abundant transposases encoded by the metagenome of a hydrothermal chimney biofilm. ISME J. 3, 1420–1424 (2009).CAS 
PubMed 

Google Scholar 
165.Jansson, J. K. & Taş, N. The microbial ecology of permafrost. Nat. Rev. Microbiol. 12, 414–425 (2014).CAS 
PubMed 

Google Scholar 
166.Kuang, J. et al. Predicting taxonomic and functional structure of microbial communities in acid mine drainage. ISME J. 10, 1527–1539 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
167.Clark, D. R. et al. Biogeography at the limits of life: do extremophilic microbial communities show biogeographical regionalization? Glob. Ecol. Biogeogr. 26, 1435–1446 (2017).
Google Scholar 
168.Atanasova, N. S., Roine, E., Oren, A., Bamford, D. H. & Oksanen, H. M. Global network of specific virus-host interactions in hypersaline environments. Environ. Microbiol. 14, 426–440 (2012).CAS 
PubMed 

Google Scholar 
169.Wilkins, D. et al. Key microbial drivers in Antarctic aquatic environments. FEMS Microbiol. Rev. 37, 303–335 (2013).CAS 
PubMed 

Google Scholar 
170.Cavicchioli, R. Microbial ecology of Antarctic aquatic systems. Nat. Rev. Microbiol. 13, 691–706 (2015).CAS 
PubMed 

Google Scholar 
171.López-Bueno, A. et al. High diversity of the viral community from an Antarctic lake. Science 326, 858–861 (2009).PubMed 

Google Scholar 
172.Aguirre de Cárcer, D., López-Bueno, A., Pearce, D. A. & Alcamí, A. Biodiversity and distribution of polar freshwater DNA viruses. Sci. Adv. 1, e1400127 (2015).PubMed 
PubMed Central 

Google Scholar 
173.Yau, S. et al. Virophage control of Antarctic algal host–virus dynamics. Proc. Natl Acad. Sci. USA 108, 6163–6168 (2011). This is the first study to reveal the important ecological roles of virophages and their regulation of host–virus interactions.CAS 
PubMed 
PubMed Central 

Google Scholar 
174.Al-Shayeb, B. et al. Clades of huge phages from across Earth’s ecosystems. Nature 578, 425–431 (2020). Analysis of massive metagenomic datasets revealed clades of huge phages from diverse habitats, including extreme environments.CAS 
PubMed 
PubMed Central 

Google Scholar 
175.Tschitschko, B. et al. Antarctic archaea-virus interactions: metaproteome-led analysis of invasion, evasion and adaptation. ISME J. 9, 2094–2107 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
176.Mosier, A. C. et al. Fungi contribute critical but spatially varying roles in nitrogen and carbon cycling in acid mine drainage. Front. Microbiol. 7, 238 (2016).PubMed 
PubMed Central 

Google Scholar 
177.Quemener, M. et al. Meta-omics highlights the diversity, activity and adaptations of fungi in deep oceanic crust. Environ. Microbiol. 22, 3950–3967 (2020).CAS 
PubMed 

Google Scholar 
178.Fredrickson, J. K. Ecological communities by design. Science 348, 1425–1427 (2015).CAS 
PubMed 

Google Scholar 
179.Fuhrman, J. A. et al. Annually reoccurring bacterial communities are predictable from ocean conditions. Proc. Natl Acad. Sci. USA 103, 13104–13109 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
180.Sunagawa, S. et al. Structure and function of the global ocean microbiome. Science 348, 1261359 (2015).PubMed 

Google Scholar 
181.Lozupone, C. A. & Knight, R. Global patterns in bacterial diversity. Proc. Natl Acad. Sci. USA 104, 11436–11440 (2007).CAS 
PubMed 
PubMed Central 

Google Scholar 
182.Fierer, N. & Jackson, R. B. The diversity and biogeography of soil bacterial communities. Proc. Natl Acad. Sci. USA 103, 626–631 (2006).CAS 
PubMed 
PubMed Central 

Google Scholar 
183.López-Pérez, M., Haro-Moreno, J. M., Coutinho, F. H., Martinez-Garcia, M. & Rodriguez-Valera, F. The evolutionary success of the marine bacterium SAR11 analyzed through a metagenomic perspective. mSystems 5, e00605-20 (2020).PubMed 
PubMed Central 

Google Scholar 
184.Altshuler, I., Goordial, J. & Whyte, L. G. in Psychrophiles: From Biodiversity to Biotechnology (ed. Margesin, R.) 153–180 (Springer International Publishing, 2017).185.Huang, L. N., Kuang, J. L. & Shu, W. S. Microbial ecology and evolution in the acid mine drainage model system. Trends Microbiol. 24, 581–593 (2016).CAS 
PubMed 

Google Scholar 
186.Klatt, C. G. et al. Community ecology of hot spring cyanobacterial mats: predominant populations and their functional potential. ISME J. 5, 1262–1278 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
187.Menzel, P. et al. Comparative metagenomics of eight geographically remote terrestrial hot springs. Microb. Ecol. 70, 411–424 (2015).PubMed 

Google Scholar 
188.Stokke, R. et al. Functional interactions among filamentous Epsilonproteobacteria and Bacteroidetes in a deep-sea hydrothermal vent biofilm. Environ. Microbiol. 17, 4063–4077 (2015).CAS 
PubMed 

Google Scholar 
189.Zeng, Y. et al. Potential rhodopsin- and bacteriochlorophyll-based dual phototrophy in a High Arctic glacier. mBio 11, e02641–20 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
190.Simon, C., Wiezer, A., Strittmatter, A. W. & Daniel, R. Phylogenetic diversity and metabolic potential revealed in a glacier ice metagenome. Appl. Environ. Microbiol. 75, 7519–7526 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
191.Lipson, D. A. et al. Metagenomic insights into anaerobic metabolism along an Arctic peat soil profile. PLoS ONE 8, e64659 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
192.Podell, S. et al. Assembly-driven community genomics of a hypersaline microbial ecosystem. PLoS ONE 8, e61692 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
193.DeMaere, M. Z. et al. High level of intergenera gene exchange shapes the evolution of haloarchaea in an isolated Antarctic lake. Proc. Natl Acad. Sci. USA. 110, 16939–16944 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
194.Smith, A. R. et al. Carbon fixation and energy metabolisms of a subseafloor olivine biofilm. ISME J. 13, 1737–1749 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
195.Zhao, R. et al. Geochemical transition zone powering microbial growth in subsurface sediments. Proc. Natl Acad. Sci. USA. 117, 32617–32626 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
196.Luo, Z. H. et al. Diversity and genomic characterization of a novel Parvarchaeota family in acid mine drainage sediments. Front. Microbiol. 11, 612257 (2020).PubMed 
PubMed Central 

Google Scholar 
197.Lewin, A., Wentzel, A. & Valla, S. Metagenomics of microbial life in extreme temperature environments. Curr. Opin. Biotechnol. 24, 516–525 (2013).CAS 
PubMed 

Google Scholar 
198.Schlesinger, M. J. Heat-shock proteins. J. Biol. Chem. 265, 12111–12114 (1990).CAS 
PubMed 

Google Scholar 
199.D’Amico, S., Collins, T., Marx, J.-C., Feller, G. & Gerday, C. Psychrophilic microorganisms: challenges for life. EMBO Rep. 7, 385–389 (2006).PubMed 
PubMed Central 

Google Scholar 
200.Bakermans, C., Bergholz, P. W., Ayala-del-Río, H. & Tiedje, J. in Permafrost Soils (ed. Margesin, R.) 159–168 (Springer, 2009).201.Gunde-Cimerman, N., Plemenitaš, A. & Oren, A. Strategies of adaptation of microorganisms of the three domains of life to high salt concentrations. FEMS Microbiol. Rev. 42, 353–375 (2018).CAS 
PubMed 

Google Scholar 
202.Baker-Austin, C. & Dopson, M. Life in acid: pH homeostasis in acidophiles. Trends Microbiol. 15, 165–171 (2007).CAS 
PubMed 

Google Scholar 
203.Dopson, M., Baker-Austin, C., Koppineedi, P. R. & Bond, P. L. Growth in sulfidic mineral environments: metal resistance mechanisms in acidophilic micro-organisms. Microbiology 149, 1959–1970 (2003).CAS 
PubMed 

Google Scholar 
204.Dopson, M., Ossandon, F. J., Lövgren, L. & Holmes, D. S. Metal resistance or tolerance? Acidophiles confront high metal loads via both abiotic and biotic mechanisms. Front. Microbiol. 5, 157 (2014).PubMed 
PubMed Central 

Google Scholar 
205.Allen, E. E. & Banfield, J. F. Community genomics in microbial ecology and evolution. Nat. Rev. Microbiol. 3, 489–498 (2005).CAS 
PubMed 

Google Scholar 
206.Sakowski, E. et al. Current state of and future opportunities for prediction in microbiome research: report from the Mid-Atlantic Microbiome Meet-up in Baltimore on 9 January 2019. mSystems 4, e00392–19 (2019).PubMed 
PubMed Central 

Google Scholar 
207.Lima-Mendez, G. et al. Determinants of community structure in the global plankton interactome. Science 348, 1262073 (2015).PubMed 

Google Scholar  More

1.Sims, D. W., Queiroz, N., Doyle, T. K., Houghton, J. D. R. & Hays, G. C. Satellite tracking of the world’s largest bony fish, the ocean sunfish (Mola mola L.) in the North East Atlantic. J. Exp. Mar. Biol. Ecol. 370, 127–133 (2009a)2.Sims, D. W., Queiroz, N., Humphries, N. E., Lima, F. P. & Hays, G. C. Long-term GPS tracking of ocean sunfish Mola mola offers a new direction in fish monitoring. PLoS ONE 4, e7351 (2009b).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
3.Dewar, H. et al. Satellite tracking the world’s largest jelly predator, the ocean sunfish, Mola mola, in the Western Pacific. J. Exp. Mar. Biol. Ecol. 393, 32–42 (2010).Article 

Google Scholar 
4.Thys, T. M. et al. Ecology of the ocean sunfish, Mola mola, in the southern California current system. J. Exp. Mar. Biol. Ecol. 471, 64–76 (2015).Article 

Google Scholar 
5.Sousa, L. L., Queiroz, N., Mucientes, G., Humphries, N. E. & Sims, D. W. Environmental influence on the seasonal movements of satellite-tracked ocean sunfish Mola mola in the north-east Atlantic. Anim. Biotelemetry 4, 7 (2016a).Article 

Google Scholar 
6.Sousa, L. L. et al. Integrated monitoring of Mola mola behaviour in space and time. PLoS ONE 11, e0160404 (2016b).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
7.Chang, C. T. et al. Horizontal and vertical movement patterns of sunfish off eastern Taiwan. Deep-Sea Res. Part II Top. Stud. Oceanogr. 175, 104683 (2020).8.Sawai, E., Yamanoue, Y., Yoshita, Y., Sakai, Y. & Hashimoto, H. Seasonal occurrence patterns of Mola sunfishes (Mola spp. A and B; Molidae) in waters off the Sanriku region, eastern Japan. Japan. J. Ichthyol. 58, 181–187 (2011).
Google Scholar 
9.Thys, T. M., Ryan, J. P., Weng, K. C., Erdmann, M. & Tresnati, J. Tracking a marine ecotourism star: Movements of the short ocean sunfish Mola ramsayi in Nusa Penida, Bali, Indonesia. J. Mar. Biol. 2016, 8750193 (2016).Article 

Google Scholar 
10.Thys, T. M., Hearn, A. R., Weng, K. C., Ryan, J. P. & Peñaherrera-Palma, C. Satellite tracking and site fidelity of short ocean sunfish, Mola ramsayi, in the Galapagos Islands. J. Mar. Biol. 2017, 7097965 (2017).Article 

Google Scholar 
11.Aspillaga, E. et al. Thermal stratification drives movement of a coastal apex predator. Sci. Rep. 7, 526 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
12.Gaube, P. et al. Mesoscale eddies influence the movements of mature female white sharks in the Gulf Stream and Sargasso Sea. Sci. Rep. 8, 7363 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
13.Nakamura, I., Goto, Y. & Sato, K. Ocean sunfish rewarm at the surface at the surface after deep excursion to forage for siphonophores. J. Anim. Ecol. 84, 590–603 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Tolotti, M. et al. Fine-scale vertical movements of oceanic whitetip sharks (Carcharhinus longimanus). Fish. Bull. 115, 380–395 (2017).Article 

Google Scholar 
15.Musyl, M. K. et al. Postrelease survival, vertical and horizontal movements, and thermal habitats of five species of pelagic sharks in the central Pacific Ocean. Fish. Bull. 109, 341–368 (2011).
Google Scholar 
16.Furukawa, S. et al. Vertical movements of Pacific bluefin tuna (Thunnus orientalis) and dolphinfish (Coryphaena hippurus) relative to the thermocline in the northern East China Sea. Fish. Res. 149, 86–91 (2014).Article 

Google Scholar 
17.Gaube, P. et al. The use of mesoscale eddies by juvenile loggerhead sea turtles (Caretta caretta) in the southwestern Atlantic. PloS ONE 12, e0172839 (2017).18.Braun, C. D., Gaube, P., Sinclair-Taylor, T. H., Skomal, G. B. & Thorrold, S. R. Mesoscale eddies release pelagic sharks from thermal constraints to foraging in the ocean twilight zone. PNAS 116, 17187–17192 (2019).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Sawai, E., Yamanoue, Y., Nyegaard, M. & Sakai, Y. Redescription of the bump-head sunfish Mola alexandrini (Ranzani 1839), senior synonym of Mola ramsayi (Giglioli 1883), with designation of a neotype for Mola mola (Linnaeus 1758) (Tetraodontiformes: Molidae). Ichthyol. Res. 65, 142–160 (2018).Article 

Google Scholar 
20.Sawai, E. & Yamada, M. Bump-head sunfish Mola alexandrini photographed in the north-west Pacific Ocean mesopelagic zone. J. Fish Biol. 96, 278–280 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
21.Kiyofuji, H. et al. Northward migration dynamics of skipjack tuna (Katsuwonus pelamis) associated with the lower thermal limit in the western Pacific Ocean. Progr. Oceanogr. 175, 55–67 (2019).ADS 
Article 

Google Scholar 
22.Fujioka, K. et al. Spatial and temporal variability in the trans-Pacific migration of Pacific bluefin tuna (Thunnus orientalis) revealed by archival tags. Progr. Oceanogr. 162, 52–65 (2018).23.Kobari, T. et al. Variability in taxonomic composition, standing stock, and productivity of the plankton community in the Kuroshio and its neighboring waters in Kuroshio Current: Physical, Biogeochemical, and Ecosystem Dynamics (ed. Nagai, T., Saito, H., Suzuki, K., Takahashi, M.) 223–243 (Hoboken, 2019).24.Queiroz, N., Humphries, N. E., Noble, L. R., Santos, A. M. & Sims, D. W. Short-term movements and diving behaviour of satellite-tracked blue sharks Prionace glauca in the northeastern Atlantic Ocean. Mar. Ecol. Progress Ser. 406, 265–279 (2010).ADS 
Article 

Google Scholar 
25.McMahon, C. R. & Hays, G. C. Thermal niche, large-scale movements and implications of climate change for a critically endangered marine vertebrate. Glob. Change Biol. 12, 1330–1338 (2006).ADS 
Article 

Google Scholar 
26.Nakatsubo, T., Kawachi, M., Mano, N. & Hirose, H. Spawning period of ocean sunfish Mola mola in waters of the eastern Kanto region, Japan. Aquacult. Sci. 55, 613–618 (2007).
Google Scholar 
27.Ashida, H., Suzuki, N., Tanabe, T., Suzuki, N. & Aonuma, Y. Reproductive condition, batch fecundity, and spawning fraction of large Pacific bluefin tuna Thunnus orientalis landed at Ishigaki Island, Okinawa, Japan. Environ. Biol. Fish. 98, 1173–1183 (2015).Article 

Google Scholar 
28.Watai, M. et al. Comparative analysis of the early growth history of Pacific bluefin tuna Thunnus orientalis from different spawning grounds. Mar. Ecol. Progress Ser. 607, 207–220 (2018).ADS 
Article 

Google Scholar 
29.Stevens, J. D., Bradford, R. W. & West, G. J. Satellite tagging of blue sharks (Prionace glauca) and other pelagic sharks off eastern Australia: Depth behaviour, temperature experience and movements. Mar. Biol. 157, 575–591 (2010).Article 

Google Scholar 
30.Musyl, M. K. et al. Vertical movements of bigeye tuna (Thunnus obesus) associated with islands, buoys, and seamounts near the main Hawaiian Islands from archival tagging data. Fish. Oceanogr. 12, 152–169 (2003).Article 

Google Scholar 
31.Lin, S. J. et al. Vertical and horizontal movements of bigeye tuna (Thunnus obesus) in southeastern Taiwan. Mar. Freshw. Behav. Physiol. 54, 1–21 (2021).Article 

Google Scholar 
32.Yasuda, I. & Kitagawa, D. Locations of early fishing grounds of saury in the northwestern Pacific. Fish. Oceanogr. 5, 63–69 (1996).Article 

Google Scholar 
33.Godø, O. R. et al. Mesoscale eddies are oases for higher trophic marine life. PloS ONE 7, e30161 (2012). 34.Polovina, J. J. et al. Forage and migration habitat of loggerhead (Caretta caretta) and olive ridley (Lepidochelys olivacea) sea turtles in the central North Pacific Ocean. Fish. Oceanogr. 13, 36–51 (2004).Article 

Google Scholar 
35.Sbragaglia, V. et al. Annual rhythms of temporal niche partitioning in the Sparidae family are correlated to different environmental variables. Sci. Rep. 9, 1708 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
36.Nakamura, I., Mastumoto, R. & Sato, K. Body temperature stability in the whale shark, the world’s largest fish. J. Exp. Biol. 223, jeb210286 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
37.Brill, R. W., Bigelow, K. A., Musyl, M. K., Fritsches, K. A. & Warrant, E. J. Bigeye tuna (Thunnus obesus) behavior and physiology and their relevance to stock assessments and fishery biology. Col. Vol. Sci. Pap. ICCAT 57, 142–161 (2005).
Google Scholar 
38.Stramma, L. et al. Expansion of oxygen minimum zones may reduce available habitat for tropical pelagic fishes. Nat. Clim. Change 2, 33–37 (2012).ADS 
CAS 
Article 

Google Scholar 
39.Brill, R. W. A review of temperature and oxygen tolerance studies of tunas pertinent to fisheries oceanography, movement models and stock assessments. Fish. Oceanogr. 3, 204–216 (1994).Article 

Google Scholar 
40.Lam, C. H., Kiefer, D. A. & Domeier, M. L. Habitat characterization for striped marlin in the Pacific Ocean. Fish. Res. 166, 80–91 (2015).Article 

Google Scholar 
41.Carlisle, A. B. et al. Influence of temperature and oxygen on the distribution of blue marlin (Makaira nigricans) in the Central Pacific. Fish. Oceanogr. 26, 34–48 (2017).Article 

Google Scholar 
42.Madigan D. J. et al. Water column structure defines vertical habitat of twelve pelagic predators in the South Atlantic. ICES J. Mar. Sci. 78, 867–883 (2021).Article 

Google Scholar 
43.Schlitzer, R. Export production in the equatorial and North Pacific derived from dissolved oxygen, nutrient and carbon data. J. Oceanogr. 60, 53–62 (2004).CAS 
Article 

Google Scholar 
44.Thomsen, S. et al. The formation of a subsurface anticyclonic eddy in the Peru-Chile Undercurrent and its impact on the near-coastal salinity, oxygen, and nutrient distributions. J. Geophys. Res. 121, 476–501 (2016).ADS 
Article 

Google Scholar 
45.Nakamura, I. & Sato, K. Ontogenetic shift in foraging habit of ocean sunfish Mola mola from dietary and behavioral studies. Mar. Biol. 161, 1263–1273 (2014).Article 

Google Scholar 
46.QGIS Development Team. Quantum GIS geographic information system. Open Source Geospatial Foundation Project. http://www.qgis.org/en/site/ (2016).47.Chelton, D. B., Gaube, P., Schlax, M. G., Early, J. J. & Samelson, R. M. The influence of nonlinear mesoscale eddies on near-surface oceanic chlorophyll. Science 334, 328–332 (2011).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
48.Fiedler, P. C. Comparison of objective descriptions of the thermocline. Limnol. Oceanogr. Methods 8, 313–325 (2010).Article 

Google Scholar 
49.Zar, J. H. Biostatistical Analysis 4th edn. (Prentice Hall, 1999).
Google Scholar 
50.Clarke, K. R., & Gorley, R. N. PRIMER v6: User manual/tutorial. PRIMER-E, Plymouth.51.Wood, S. N. On p-values for smooth components of an extended generalized additive model. Biometrika 100, 221–228 (2013).MathSciNet 
MATH 
Article 

Google Scholar  More