Ecology

1.
Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science 343, 1241484 (2014).
2.
Macdonald, E. A. et al. Conservation inequality and the charismatic cat: Felis felicis. Glob. Ecol. Conserv. 3, 851–866 (2015).
Article  Google Scholar 

3.
Carter, N. H. & Linnell, J. D. C. Co-adaptation is key to coexisting with large carnivores. Trends. Ecol. Evol. 31, 575–578 (2016).
PubMed  Article  Google Scholar 

4.
Inskip, C. & Zimmermann, A. Human-felid conflict: a review of patterns and priorities worldwide. Oryx 43, 18–34 (2009).
Article  Google Scholar 

5.
Macdonald, D. W., Mosser, A. & Gittleman, J. L. Felid society. In Biology and Conservation of Wild Felids (eds Macdonald, D. W. & Loveridge, A. J.) 125–160 (Oxford University Press, Oxford, 2010).
Google Scholar 

6.
Treves, A. & Karanth, K. U. Human-carnivore conflict and perspectives on carnivore management worldwide. Conserv. Biol. 17, 1491–1499 (2003).
Article  Google Scholar 

7.
Lute, M. L., Carter, N. H., López-Bao, J. V. & Linnell, J. D. C. Conservation professionals agree on challenges to coexisting with large carnivores but not on solutions. Biol. Conserv. 218, 223–232 (2018).
Article  Google Scholar 

8.
Chapron, G. et al. Recovery of large carnivores in Europe’s modern human-dominated landscapes. Science 346, 1517–1519 (2014).
ADS  CAS  PubMed  Article  Google Scholar 

9.
Van der Meer, E., Fritz, H., Blinston, P. & Rasmussen, G. S. A. Ecological trap in the buffer zone of a protected area: effects of indirect anthropogenic mortality on the African wild dog (Lycaon pictus). Oryx 48, 285–293 (2014).
Article  Google Scholar 

10.
Khorozyan, I., Ghoddousi, A., Soofi, M. & Waltert, M. Big cats kill more livestock when wild prey reaches a minimum threshold. Biol. Conserv. 192, 268–275 (2015).
Article  Google Scholar 

11.
Cozzi, G. et al. Anthropogenic food resources foster the coexistence of distinct life history strategies: year-round sedentary and migratory brown bears. J. Zool. 300, 142–150 (2016).
Article  Google Scholar 

12.
Schuette, P., Wagner, A. P., Wagner, M. E. & Creel, S. Occupancy patterns and niche partitioning within a diverse carnivore community exposed to anthropogenic pressures. Biol. Conserv. 158, 301–312 (2013).
Article  Google Scholar 

13.
Oriol-Cotterill, A., Macdonald, D. W., Valeix, M., Ekwanga, S. & Frank, L. G. Spatiotemporal patterns of lion space use in a human-dominated landscape. Anim. Behav. 101, 27–39 (2015).
Article  Google Scholar 

14.
Suraci, J. P. et al. Behavior-specific habitat selection by African lions may promote their persistence in a human-dominated landscape. Ecology 100, 1–11 (2019).
Article  Google Scholar 

15.
Kuijper, D. P. J. et al. Paws without claws? Ecological effects of large carnivores in anthropogenic landscapes. Proc. R. Soc. B Biol. Sci. 283, 20161625 (2016).
Article  Google Scholar 

16.
Carter, N. H., Shrestha, B. K., Karki, J. B., Pradhan, N. M. B. & Liu, J. Coexistence between wildlife and humans at fine spatial scales. Proc. Natl. Acad. Sci. 109, 15360–15365 (2012).
ADS  CAS  PubMed  Article  Google Scholar 

17.
Odden, M., Athreya, V., Rattan, S. & Linnell, J. D. C. Adaptable neighbours: Movement patterns of GPS-collared leopards in human dominated landscapes in India. PLoS ONE 9, .e112044. https://doi.org/10.1002/ecs2.1408 (2014).

18.
Wang, Y., Allen, M. L. & Wilmers, C. C. Mesopredator spatial and temporal responses to large predators and human development in the Santa Cruz Mountains of California. Biol. Conserv. 190, 23–33 (2015).
Article  Google Scholar 

19.
Wheat, R. E. & Wilmers, C. C. Habituation reverses fear-based ecological effects in brown bears (Ursus arctos). Ecosphere 7, (2016).

20.
Gaynor, K. M., Hojnowski, C. E., Carter, N. H. & Brashares, J. S. The influence of human disturbance on wildlife nocturnality. Science 360, 1232–1235 (2018).
ADS  CAS  PubMed  Article  Google Scholar 

21.
Valeix, M. et al. How key habitat features influence large terrestrial carnivore movements: waterholes and African lions in a semi-arid savanna of north-western Zimbabwe. Landsc. Ecol. 25, 337–351 (2010).
Article  Google Scholar 

22.
Dickson, B. G., Jenness, J. S. & Beier, P. Influence of vegetation, topography, and roads on cougar movement in southern California. J. Wildl. Manag. 69, 264–276 (2005).
Article  Google Scholar 

23.
Elliot, N. B., Cushman, S. A., Macdonald, D. W. & Loveridge, A. J. The devil is in the dispersers: predictions of landscape connectivity change with demography. J. Appl. Ecol. 51, 1169–1178 (2014).
Article  Google Scholar 

24.
Valeix, M., Hemson, G., Loveridge, A. J., Mills, G. & Macdonald, D. W. Behavioural adjustments of a large carnivore to access secondary prey in a human-dominated landscape. J. Appl. Ecol. 49, 73–81 (2012).
Article  Google Scholar 

25.
Farhadinia, M. S. et al. Vertical relief facilitates spatial segregation of a high density large carnivore population. Oikos 129, 346–355 (2020).
Article  Google Scholar 

26.
Grant, J., Hopcraft, C., Sinclair, A. R. E. & Packer, C. Planning for success: Serengeti lions seek prey accessibility rather than abundance. J. Anim. Ecol. 74, 559–566 (2005).
Article  Google Scholar 

27.
Laundré, J. W. & Hernández, L. Total energy budget and prey requirements of free-ranging coyotes in the Great Basin desert of the western United States. J. Arid. Environ. 55, 675–689 (2003).
ADS  Article  Google Scholar 

28.
Miller, J. R. B., Jhala, Y. V., Jena, J. & Schmitz, O. J. Landscape-scale accessibility of livestock to tigers: implications of spatial grain for modeling predation risk to mitigate human-carnivore conflict. Ecol. Evol. 5, 1354–1367 (2015).
PubMed  PubMed Central  Article  Google Scholar 

29.
Blake, L. W. & Gese, E. M. Resource selection by cougars: influence of behavioral state and season. J. Wildl. Manag. 80, 1205–1217 (2016).
Article  Google Scholar 

30.
Broekhuis, F., Grünewälder, S., McNutt, J. W. & Macdonald, D. W. Optimal hunting conditions drive circalunar behavior of a diurnal carnivore. Behav. Ecol. 25, 1268–1275 (2014).
Article  Google Scholar 

31.
Klaassen, B. & Broekhuis, F. Living on the edge: multiscale habitat selection by cheetahs in a human-wildlife landscape. Ecol. Evol. 8, 7611–7623 (2018).
PubMed  PubMed Central  Article  Google Scholar 

32.
Gese, E. M. et al. Cross-fostering as a conservation tool to augment endangered carnivore populations. J. Mammal. 99, 1033–1041 (2018).
Article  Google Scholar 

33.
Naha, D. et al. Ranging, activity and habitat use by tigers in the mangrove forests of the Sundarban. PLoS ONE 11, e0152119 (2016).
PubMed  PubMed Central  Article  CAS  Google Scholar 

34.
Karanth, K. K., Nichols, J. D., Hines, J. E., Karanth, K. U. & Christensen, N. L. Patterns and determinants of mammal species occurrence in India. J. Appl. Ecol. https://doi.org/10.1111/j.1365-2664.2009.01710.x (2009).
Article  Google Scholar 

35.
Athreya, V. et al. Spotted in the news: using media reports to examine leopard distribution, depredation, and management practices outside protected areas in Southern India. PLoS ONE 10, e0142647 (2015).
PubMed  PubMed Central  Article  CAS  Google Scholar 

36.
Naha, D., Sathyakumar, S. & Rawat, G. S. Understanding drivers of human-leopard conflicts in the Indian Himalayan region: spatio-temporal patterns of conflicts and perception of local communities towards conserving large carnivores. PLoS ONE 13, 1–19 (2018).
Article  CAS  Google Scholar 

37.
Jacobson, A. P. et al. Leopard (Panthera pardus) status, distribution, and the research efforts across its range. PeerJ, 4, 1–28 (2016).

38.
Naha, D. et al. Landscape predictors of human-leopard conflicts within multi-use areas of the Himalayan Region. Sci. Rep. 10, 11129. https://doi.org/10.1038/s41598-020-67980-w (2020).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

39.
Odden, M. & Wegge, P. Spacing and activity patterns of leopards (Panthera pardus) in the Royal Bardia National Park, Nepal. Wildl. Biol. 11, 145–152 (2005).
Article  Google Scholar 

40.
Farhadinia, M. S., Johnson, P. J., Macdonald, D. W. & Hunter, L. T. B. Anchoring and adjusting amidst humans: ranging behavior of Persian leopards along the Iran-Turkmenistan borderland. PLoS ONE 13, e0196602 (2018).
PubMed  PubMed Central  Article  CAS  Google Scholar 

41.
Miquelle, D. G. et al. Tigers and wolves in the Russian Far East: competitive exclusion, functional redundancy and conservation implications. In Large Carnivores and the Conservation of Biodiversity (eds Ray, J. C. et al.) 179–207 (Island Press, Washington, 2005).
Google Scholar 

42.
Powell, R. A. Animal home ranges and territories and home range estimators. In Boitani (ed. L. & Fuller, T.K. ) 65–110 (Research Techniques in Anim. Ecol. Controversies and Consequences, Columbia University Press, New York, 2000).
Google Scholar 

43.
Mizutani, F. & Jewell, P. A. Home-range and movements of leopards (Panthera pardus) on a livestock ranch in Kenya. J. Zool. 244, 269–286 (1998).
Article  Google Scholar 

44.
Ray-Brambach, R. R., Stommel, C. & Rödder, D. Home ranges, activity patterns and habitat preferences of leopards in Luambe National Park and adjacent Game Management Area in the Luangwa Valley, Zambia. Mamm. Biol. 92, 102–110 (2018).
Article  Google Scholar 

45.
Karelus, D. L. et al. Effects of environmental factors and landscape features on movement patterns of Florida black bears. J. Mammal. 98, 1463 (2017).
Article  Google Scholar 

46.
Athreya, V., Odden, M., Linnell, J. D. C., Krishnaswamy, J. & Karanth, K. U. A cat among the dogs: Leopard (Panthera pardus) diet in a human-dominated landscape in western Maharashtra, India. Oryx 50, 156–162 (2016).
Article  Google Scholar 

47.
Kshettry, A., Vaidyanathan, S. & Athreya, V. Diet selection of leopards (Panthera pardus) in a human-use landscape in North-Eastern India. Trop. Conserv. Sci. 11, 194008291876463 (2018).
Article  Google Scholar 

48.
Ciuti, S. et al. Effects of humans on behaviour of wildlife exceed those of natural predators in a landscape of fear. PLoS ONE 7(11), e50611. https://doi.org/10.1371/journal.pone.0050611 (2012).

49.
Tucker, M. A. et al. Moving in the anthropocene: global reductions in terrestrial mammalian movements. Science 359, 466 (2018).
ADS  CAS  PubMed  Article  Google Scholar 

50.
Broekhuis, F., Madsen, E. K. & Klaassen, B. Predators and pastoralists: how anthropogenic behavior inside wildlife areas influence carnivore space use and movement behavior. Anim. Conserv. https://doi.org/10.1111/acv.12483 (2019).
Article  Google Scholar 

51.
Filla, M. et al. Habitat selection by Eurasian lynx (Lynx lynx) is primarily driven by avoidance of human activity during day and prey availability during night. Ecol. Evol. 7, 6367–6381 (2017).
PubMed  PubMed Central  Article  Google Scholar 

52.
Du Preez, B., Hart, T., Loveridge, A. J. & Macdonald, D. W. Impact of risk on animal behaviour and habitat transition probabilities. Anim. Behav. 100, 22–37 (2015).
Article  Google Scholar 

53.
Van Cleave, E. K. et al. Diel patterns of movement activity and habitat use by leopards (Panthera pardus pardus) living in a human-dominated landscape in central Kenya. Biol. Conserv. 226, 224–237 (2018).
Article  Google Scholar 

54.
Durant, S. M. Living with the enemy: avoidance of hyenas and lions by cheetahs in the Serengeti. Behav. Ecol. 11, 624–632 (2000).
Article  Google Scholar 

55.
Broekhuis, F., Cozzi, G., Valeix, M., McNutt, J. W. & Macdonald, D. W. Risk avoidance in sympatric large carnivores: reactive or predictive?. J. Anim. Ecol. 82, 1098–1105 (2013).
PubMed  Article  Google Scholar 

56.
Packer, C., Swanson, A., Ikanda, D. & Kushnir, H. Fear of darkness, the full moon and the nocturnal ecology of African lions. PLoS ONE 6(7), e22285. https://doi.org/10.1371/journal.pone.0022285 (2011).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

57.
Schuette, P., Creel, S. & Christianson, D. (2013) Coexistence of African lions, livestock, and people in a landscape with variable human land use and seasonal movements. Biol. Conserv. 157, 148–154 (2013).
Article  Google Scholar 

58.
Acharya, K. P., Paudel, P. K., Neupane, P. R. & Köhl, M. Human–wildlife conflicts in Nepal: patterns of human fatalities and injuries caused by large mammals. PLoS ONE 11, e0161717 (2016).
PubMed  PubMed Central  Article  CAS  Google Scholar 

59.
Dhanwatey, H. S. et al. Large carnivore attacks on humans in Central India:aA case study from the Tadoba-Andheri Tiger Reserve. Oryx 47(2), 221–227. https://doi.org/10.1017/S0030605311001803 (2013).
Article  Google Scholar 

60.
Ngoprasert, D., Lynam, A. J. & Gale, G. A. Human disturbance affects habitat use and behaviour of Asiatic leopard (Panthera pardus) in Kaeng Krachan National Park, Thailand. Oryx 41, 343–351 (2007).
Article  Google Scholar 

61.
Carter, N., Jasny, M., Gurung, B. & Liu, J. Impacts of people and tigers on leopard spatiotemporal activity patterns in a global biodiversity hotspot. Glob. Ecol. Conserv. 3, 149–162 (2015).
Article  Google Scholar 

62.
Bhattacharjee, A. & Parthasarathy, N. Coexisting with large carnivores: a case study from Western Duars, India. Hum. Dimens. Wildl. 18, 20–31 (2013).
Article  Google Scholar 

63.
Naha, D., Sathyakumar, S., Dash, S., Chettri, A. & Rawat, G. S. Assessment and prediction of spatial patterns of human-elephant conflicts in changing land cover scenarios of a human-dominated landscape in North Bengal. PLoS ONE 14, 1–19 (2019).
Article  CAS  Google Scholar 

64.
Kreeger, T. K. Handbook of Wildlife Chemical immobilization. International Wildlife Vet. Services Inc. Post Box 37, Larammie, WY, USA, (1996).

65.
Calenge, C. The package “adehabitat” for the R software: a tool for the analysis of space and habitat use by animals. Ecol. Modell. 197, 516–519 (2006).
Article  Google Scholar 

66.
Kie, J. G., Terry-Bowyer, R., Nicholson, M. C., Boroski, B. B. & Loft, E. R. Landscape heterogeneity at differing scales: Effects on spatial distribution of mule deer. Ecology 83, 530–544 (2002).
Article  Google Scholar 

67.
Kie, J. G. et al. The home-range concept: are traditional estimators still relevant with modern telemetry technology?. Philos. Trans. R. Soc. B. Biol. Sci. 365, 2221–2231 (2010).
Article  Google Scholar 

68.
Michelot, T., Langrock, R. & Patterson, T. A. moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models. Methods Ecol Evol 7, 1308–1315 (2016).
Article  Google Scholar 

69.
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2019).
Google Scholar 

70.
Bates, D., Kliegl, R., Vasishth, S. & Baayen, H. Parsimonious Mixed Models. ArXiv150604967 Stat. http://arxiv.org/abs/1506.04967 (2015).

71.
Johnson, D. H. The comparison of usage and availability measurements for evaluating resource preference. Ecology 61, 65–71 (1980).
Article  Google Scholar 

72.
Pebesma, E. J. & Bivand, R. S. Classes and methods for spatial data in R. R News 5(2), 9–13 (2005).
Google Scholar 

73.
Esri Inc. ArcGIS Pro (Version 2.4.2). Esri Inc. https://www.esri.com/en-us/arcgis/products/arcgis-pro/ (2019).

74.
Dormann, C. F. et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 30, 609–628 (2007).
Article  Google Scholar 

75.
Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, Berlin, 2002).
Google Scholar  More

1.
Halpern, B. S. et al. A global map of human impact on marine ecosystems. Science 319, 948–952 (2008).
CAS  PubMed  Article  PubMed Central  Google Scholar 
2.
Conversi, A. et al. A holistic view of marine regime shifts. Philos. Trans. R. Soc. B Biol. Sci. 370, 20130279 (2015).
Article  Google Scholar 

3.
Möllmann, C., Folke, C., Edwards, M. & Conversi, A. Marine regime shifts around the globe: theory, drivers and impacts. Philos. Trans. R. Soc. B Biol. Sci. 370, 20130260 (2015).
Article  Google Scholar 

4.
Scheffer, M. & Carpenter, S. R. Catastrophic regime shifts in ecosystems: linking theory to observation. Trends Ecol. Evol. 18, 648–656 (2003).
Article  Google Scholar 

5.
Hastings, A. & Wysham, D. B. Regime shifts in ecological systems can occur with no warning. Ecol. Lett. 13, 464–472 (2010).
PubMed  Article  PubMed Central  Google Scholar 

6.
Rocha, J., Yletyinen, J., Biggs, R., Blenckner, T. & Peterson, G. Marine regime shifts: drivers and impacts on ecosystems services. Philos. Trans. R. Soc. B Biol. Sci. 370, 20130273 (2015).

7.
Suding, K. N., Gross, K. L. & Houseman, G. R. Alternative states and positive feedbacks in restoration ecology. Trends Ecol. Evol. 19, 46–53 (2004).
PubMed  Article  PubMed Central  Google Scholar 

8.
Jones, H. P. et al. Restoration and repair of Earth’s damaged ecosystems. Proc. R. Soc. B Biol. Sci. 285, 20172577 (2018).
Article  Google Scholar 

9.
Knowlton, N. Thresholds and multiple stable states in coral reef community dynamics. Am. Zool. 32, 674–682 (1992).
Article  Google Scholar 

10.
Moy, F. E. & Christie, H. Large-scale shift from sugar kelp (Saccharina latissima) to ephemeral algae along the south and west coast of Norway. Mar. Biol. Res. 8, 309–321 (2012).
Article  Google Scholar 

11.
Wernberg, T. et al. Climate-driven regime shift of a temperate marine ecosystem. Science 353, 169–172 (2016).
CAS  PubMed  Article  PubMed Central  Google Scholar 

12.
Airoldi, L. Roles of disturbance, sediment stress, and substratum retention on spatial dominance in algal turf. Ecology 79, 2759–2770 (1998).
Article  Google Scholar 

13.
Connell, S. D., Foster, M. S. & Airoldi, L. What are algal turfs? Towards a better description of turfs. Mar. Ecol. Prog. Ser. 495, 299–307 (2014).
Article  Google Scholar 

14.
Hughes, T. P. & Connell, J. H. Multiple stressors on coral reefs: a long-term perspective. Limnol. Oceanogr. 44, 932–940 (1999).
Article  Google Scholar 

15.
Strain, E. M. A., Thomson, R. J., Micheli, F., Mancuso, F. P. & Airoldi, L. Identifying the interacting roles of stressors in driving the global loss of canopy-forming to mat-forming algae in marine ecosystems. Glob. Change Biol. 20, 3300–3312 (2014).
Article  Google Scholar 

16.
O’Brien, J. & Scheibling, R. Turf wars: competition between foundation and turf-forming species on temperate and tropical reefs and its role in regime shifts. Mar. Ecol. Prog. Ser. 590, 1–17 (2018).
Article  Google Scholar 

17.
Rogers, A., Blanchard, J. L. & Mumby, P. J. Vulnerability of coral reef fisheries to a loss of structural complexity. Curr. Biol. 24, 1000–1005 (2014).
CAS  PubMed  Article  PubMed Central  Google Scholar 

18.
Kéfi, S., Holmgren, M. & Scheffer, M. When can positive interactions cause alternative stable states in ecosystems? Funct. Ecol. 30, 88–97 (2015).
Article  Google Scholar 

19.
May, R. M. Thresholds and breakpoints in ecosystems with a multiplicity of stable states. Nature 269, 471–477 (1977).
Article  Google Scholar 

20.
Hughes, T. P. et al. Phase shifts, herbivory, and the resilience of coral reefs to climate change. Curr. Biol. 17, 360–365 (2007).
CAS  PubMed  Article  PubMed Central  Google Scholar 

21.
Filbee-Dexter, K. & Scheibling, R. E. Sea urchin barrens as alternative stable states of collapsed kelp ecosystems. Mar. Ecol. Prog. Ser. 495, 1–25 (2014).
Article  Google Scholar 

22.
Ling, S. D. et al. Global regime shift dynamics of catastrophic sea urchin overgrazing. Philos. Trans. R. Soc. B Biol. Sci. 370, 20130269 (2015).
Article  Google Scholar 

23.
Filbee-Dexter, K. & Wernberg, T. Rise of turfs: a new battlefront for globally declining kelp forests. BioScience 68, 64–76 (2018).
Article  Google Scholar 

24.
Biggs, R., Carpenter, S. R. & Brock, W. A. Turning back from the brink: detecting an impending regime shift in time to avert it. Proc. Natl Acad. Sci. USA 106, 826–831 (2009).
CAS  PubMed  Article  PubMed Central  Google Scholar 

25.
Bullock, J. M., Aronson, J., Newton, A. C., Pywell, R. F. & Rey-Benayas, J. M. Restoration of ecosystem services and biodiversity: conflicts and opportunities. Trends Ecol. Evol. 26, 541–549 (2011).
PubMed  Article  PubMed Central  Google Scholar 

26.
Kroeker, K. J., Micheli, F., Gambi, M. C. & Martz, T. R. Divergent ecosystem responses within a benthic marine community to ocean acidification. Proc. Natl Acad. Sci. USA 108, 14515–14520 (2011).
CAS  PubMed  Article  PubMed Central  Google Scholar 

27.
Vizzini, S. et al. Ocean acidification as a driver of community simplification via the collapse of higher-order and rise of lower-order consumers. Sci. Rep. 7, 4018 (2017).
CAS  PubMed  PubMed Central  Article  Google Scholar 

28.
Agostini, S. et al. Ocean acidification drives community shifts towards simplified non-calcified habitats in a subtropical-temperate transition zone. Sci. Rep. 8, 11354 (2018).
PubMed  PubMed Central  Article  CAS  Google Scholar 

29.
Connell, S. D. et al. The duality of ocean acidification as a resource and a stressor. Ecology 99, 1005–1010 (2018).
PubMed  Article  PubMed Central  Google Scholar 

30.
Connell, S. D., Kroeker, K. J., Fabricius, K. E., Kline, D. I. & Russell, B. D. The other ocean acidification problem: CO2 as a resource among competitors for ecosystem dominance. Philos. Trans. R. Soc. B Biol. Sci. 368, 20120442 (2013).
Article  CAS  Google Scholar 

31.
Cornwall, C. E. et al. Inorganic carbon physiology underpins macroalgal responses to elevated CO2. Sci. Rep. 7, 46297 (2017).
CAS  PubMed  PubMed Central  Article  Google Scholar 

32.
Harvey, B. P., Gwynn-Jones, D. & Moore, P. J. Meta-analysis reveals complex marine biological responses to the interactive effects of ocean acidification and warming. Ecol. Evol. 3, 1016–1030 (2013).
PubMed  PubMed Central  Article  Google Scholar 

33.
Kroeker, K. J. et al. Impacts of ocean acidification on marine organisms: quantifying sensitivities and interaction with warming. Glob. Change Biol. 19, 1884–1896 (2013).
Article  Google Scholar 

34.
Harvey, B. P., Agostini, S., Kon, K., Wada, S. & Hall-Spencer, J. M. Diatoms dominate and alter marine food-webs when CO2 rises. Diversity 11, 242 (2019).
CAS  Article  Google Scholar 

35.
Hall-Spencer, J. M. et al. Volcanic carbon dioxide vents show ecosystem effects of ocean acidification. Nature 454, 96–99 (2008).
CAS  PubMed  Article  PubMed Central  Google Scholar 

36.
Fabricius, K. E. et al. Losers and winners in coral reefs acclimatized to elevated carbon dioxide concentrations. Nat. Clim. Change 1, 165–169 (2011).
CAS  Article  Google Scholar 

37.
Enochs, I. C. et al. Shift from coral to macroalgae dominance on a volcanically acidified reef. Nat. Clim. Change 5, 1083–1088 (2015).
CAS  Article  Google Scholar 

38.
Hall-Spencer, J. M. & Harvey, B. P. Ocean acidification impacts on coastal ecosystem services due to habitat degradation. Emerg. Top. Life Sci. 3, 197–206 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

39.
Johnson, C. R. & Mann, K. H. Diversity, patterns of adaptation, and stability of Nova Scotian kelp beds. Ecol. Monogr. 58, 129–154 (1988).
Article  Google Scholar 

40.
McCook, L., Jompa, J. & Diaz-Pulido, G. Competition between corals and algae on coral reefs: a review of evidence and mechanisms. Coral Reefs 19, 400–417 (2001).
Article  Google Scholar 

41.
Ghedini, G., Russell, B. D. & Connell, S. D. Trophic compensation reinforces resistance: herbivory absorbs the increasing effects of multiple disturbances. Ecol. Lett. 18, 182–187 (2015).
PubMed  Article  PubMed Central  Google Scholar 

42.
Hoegh-Guldberg, O. et al. Coral reefs under rapid climate change and ocean acidification. Science 318, 1737–1742 (2007).
CAS  PubMed  Article  PubMed Central  Google Scholar 

43.
Anthony, K. R. et al. Ocean acidification and warming will lower coral reef resilience. Glob. Change Biol. 17, 1798–1808 (2011).
Article  Google Scholar 

44.
Diaz-Pulido, G., Gouezo, M., Tilbrook, B., Dove, S. & Anthony, K. R. N. High CO2 enhances the competitive strength of seaweeds over corals. Ecol. Lett. 14, 156–162 (2011).
PubMed  PubMed Central  Article  Google Scholar 

45.
Gorman, D. & Connell, S. D. Recovering subtidal forests in human-dominated landscapes. J. Appl. Ecol. 46, 1258–1265 (2009).
Article  Google Scholar 

46.
Bellgrove, A., McKenzie, P., McKenzie, J. & Sfiligoj, B. Restoration of the habitat-forming fucoid alga Hormosira banksii at effluent-affected sites: competitive exclusion by coralline turfs. Mar. Ecol. Prog. Ser. 419, 47–56 (2010).
Article  Google Scholar 

47.
Birrell, C. L., McCook, L. J. & Willis, B. L. Effects of algal turfs and sediment on coral settlement. Mar. Pollut. Bull. 51, 408–414 (2005).
CAS  PubMed  Article  PubMed Central  Google Scholar 

48.
Vermeij, M. J. A., Smith, J. E., Smith, C. M., Vega Thurber, R. & Sandin, S. A. Survival and settlement success of coral planulae: independent and synergistic effects of macroalgae and microbes. Oecologia 159, 325–336 (2009).
CAS  PubMed  Article  PubMed Central  Google Scholar 

49.
Isæus, M., Malm, T., Persson, S. & Svensson, A. Effects of filamentous algae and sediment on recruitment and survival of Fucus serratus (Phaeophyceae) juveniles in the eutrophic Baltic Sea. Eur. J. Phycol. 39, 301–307 (2004).
Article  Google Scholar 

50.
Airoldi, L. The effects of sedimentation on rocky coast assemblages. Oceanogr. Mar. Biol. Annu. Rev. 41, 169–171 (2003).
Google Scholar 

51.
Decho, A. W. Microbial exopolymer secretions in ocean environments: their role(s) in food webs and marine processes. Oceanogr. Mar. Biol. Annu. Rev. 28, 9–16 (1990).
Google Scholar 

52.
Schiel, D. R., Wood, S. A., Dunmore, R. A. & Taylor, D. I. Sediment on rocky intertidal reefs: effects on early post-settlement stages of habitat-forming seaweeds. J. Exp. Mar. Biol. Ecol. 331, 158–172 (2006).
Article  Google Scholar 

53.
Chapman, A. S., Albrecht, A. S. & Fletcher, R. L. Differential effects of sediments on survival and growth of Fucus serratus embryos (Fucales, Phaeophyceae). J. Phycol. 38, 894–903 (2002).
Article  Google Scholar 

54.
Decho, A. W. Microbial biofilms in intertidal systems: an overview. Cont. Shelf Res. 20, 1257–1273 (2000).
Article  Google Scholar 

55.
Haas, A. F. et al. Organic matter release by coral reef associated benthic algae in the Northern Red Sea. J. Exp. Mar. Biol. Ecol. 389, 53–60 (2010).
CAS  Article  Google Scholar 

56.
Smith, J. E. et al. Indirect effects of algae on coral: algae-mediated, microbe-induced coral mortality. Ecol. Lett. 9, 835–845 (2006).
PubMed  Article  PubMed Central  Google Scholar 

57.
Haas, A. F. et al. Global microbialization of coral reefs. Nat. Microbiol. 1, 16042 (2016).
CAS  PubMed  Article  PubMed Central  Google Scholar 

58.
Haas, A. F. et al. Effects of coral reef benthic primary producers on dissolved organic carbon and microbial activity. PLoS ONE 6, e27973 (2011).
CAS  PubMed  PubMed Central  Article  Google Scholar 

59.
Barott, K. L. & Rohwer, F. L. Unseen players shape benthic competition on coral reefs. Trends Microbiol. 20, 621–628 (2012).
CAS  PubMed  Article  PubMed Central  Google Scholar 

60.
Dijkstra, J. A. et al. Invasive seaweeds transform habitat structure and increase biodiversity of associated species. J. Ecol. 105, 1668–1678 (2017).
Article  Google Scholar 

61.
Sieg, J. & Heard, R. W. Tanaidacea (Crustacea: Peracardia) of the Gulf of Mexico. III. On the Occurrence of Teleotanais gerlachi Lang, 1956 (Nototanaidae) in the Eastern Gulf. Gulf Caribb. Res. 7, 267–271 (1983).
Google Scholar 

62.
Allen, R., Foggo, A., Fabricius, K., Balistreri, A. & Hall-Spencer, J. M. Tropical CO2 seeps reveal the impact of ocean acidification on coral reef invertebrate recruitment. Mar. Pollut. Bull. 124, 607–613 (2017).
CAS  PubMed  Article  PubMed Central  Google Scholar 

63.
IPCC. Climate Change 2013 – The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the IPCC. p. 1535 (2013).

64.
Falkenberg, L. J., Connell, S. D. & Russell, B. D. Disrupting the effects of synergies between stressors: improved water quality dampens the effects of future CO2 on a marine habitat. J. Appl. Ecol. 50, 51–58 (2013).
CAS  Article  Google Scholar 

65.
Atalah, J., Hopkins, G. A. & Forrest, B. M. Augmentative biocontrol in natural marine habitats: persistence, spread and non-target effects of the sea urchin Evechinus chloroticus. PLoS ONE 8, e80365 (2013).
PubMed  PubMed Central  Article  CAS  Google Scholar 

66.
Conklin, E. J. & Smith, J. E. Abundance and spread of the invasive red algae, Kappaphycus spp., in Kane’ohe Bay, Hawai’i and an experimental assessment of management options. Biol. Invasions 7, 1029–1039 (2005).
Article  Google Scholar 

67.
Neilson, B. J., Wall, C. B., Mancini, F. T. & Gewecke, C. A. Herbivore biocontrol and manual removal successfully reduce invasive macroalgae on coral reefs. PeerJ 6, e5332 (2018).
PubMed  PubMed Central  Article  Google Scholar 

68.
Abràmoff, M. D., Magalhães, P. J. & Ram, S. J. Image processing with ImageJ. Biophoton. Int. 11, 36–42 (2004).
Google Scholar 

69.
R Development Core Team. R: A language and environment for statistical computing (2017).

70.
Pierrot, D., Lewis, E. & Wallace, D. W. R. MS Excel Program Developed for CO2System Calculations, ORNL/CDIAC-105 (2006).

71.
Mehrbach, C., Culberson, C. H., Hawley, J. E. & Pytkowicz, R. M. Measurement of the apparent dissociation constants of carbonic acid in seawater at atmospheric pressure. Limnol. Oceanogr. 18, 897–907 (1973).
CAS  Article  Google Scholar 

72.
Dickson, A. G. & Millero, F. J. A comparison of the equilibrium constants for the dissociation of carbonic acid in seawater media. Deep Sea Res. Part Oceanogr. Res. Pap. 34, 1733–1743 (1987).
CAS  Article  Google Scholar 

73.
Dickson, A. G. Thermodynamics of the dissociation of boric acid in potassium chloride solutions from 273.15 to 318.15 K. J. Chem. Eng. Data 35, 253–257 (1990).
CAS  Article  Google Scholar 

74.
Uppström, L. R. The boron/chlorinity ratio of deep-sea water from the Pacific Ocean. Deep Sea Res. Oceanogr. Abstr. 21, 161–162 (1974).
Article  Google Scholar 

75.
Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 18, 1403–1414 (2016).
CAS  PubMed  Article  PubMed Central  Google Scholar 

76.
Apprill, A., McNally, S., Parsons, R. & Weber, L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat. Microb. Ecol. 75, 129–137 (2015).
Article  Google Scholar 

77.
Griffith, J. C., Lee, W. G., Orlovich, D. A. & Summerfield, T. C. Contrasting bacterial communities in two indigenous Chionochloa (Poaceae) grassland soils in New Zealand. PLoS ONE 12, e0179652 (2017).
PubMed  PubMed Central  Article  CAS  Google Scholar 

78.
Callahan, B. J., Sankaran, K., Fukuyama, J. A., McMurdie, P. J. & Holmes, S. P. Bioconductor workflow for microbiome data analysis: from raw reads to community analyses. F1000Research 5, 1492 (2016).

79.
Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581 (2016).
CAS  PubMed  PubMed Central  Article  Google Scholar 

80.
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 

81.
Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naïve bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261 (2007).
CAS  PubMed  PubMed Central  Article  Google Scholar 

82.
McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).
CAS  PubMed  PubMed Central  Article  Google Scholar 

83.
Oksanen, J. et al. The vegan package. Vegan Community Ecol. Package R Package Version 25-5 Httpscranr-Proj (2019).

84.
Kassambara, A. rstatix: Pipe-Friendly Framework for Basic Statistical Tests (2020).

85.
Wickham, H. et al. Welcome to the tidyverse. J. Open Source Softw. 4, 1686 (2019).
Article  Google Scholar 

86.
Kassambara, A. ggpubr:“ggplot2” based publication ready plots. R Package Version 024 (2019).

87.
Harvey, B. P. et al. ‘Feedback mechanisms stabilise degraded turf algal systems at a CO2seep site’ – Associated Raw Data for Figures https://doi.org/10.6084/m9.figshare.13289588.v1 (2020). More

For millions of years the Southern Ocean has been one of the most thermally constant of Earth’s environments, but is now undergoing multiple, complex, interacting physical changes1. This region includes a major centre of considerable, recent warming in the shallows, and this is forecast to be sustained1. It will likely drive varied and considerable biological change, which remains little investigated in situ. Most existing knowledge is for responses of individual species, in isolation2, but cumulative responses at assemblage and community levels, though poorly studied, will likely have greater consequences3. There is now a wide literature on indirect impacts of warming on biota (e.g., snow and ice retreat, freshening, and sedimentation from glaciers, among others4,5,6,7) but few field studies on specifically direct thermal effects. To date, warming impacts have been predicted to change species success4,8 and the first polar assemblage level data demonstrated increased growth9. However, this only occurred in a few species at moderately increased temperature. If sessile animals become larger (owing to increased growth) this is more likely to make space a limiting resource and increase the incidence, and importance, of spatial competition.
In the current study, we investigated how in situ warming impacts physical ‘fighting’ for space (so called contest competitive interactions), between species in assemblages. This is where the boundaries of colonies/individuals meet others, which leads to either a cessation and redirection of growth by both competitors (a tie or draw) or overgrowth of one (a loser) by the other (winner). To our knowledge, the impact of climate-forcing on spatial competition has not been considered in polar seas. Yet, for species unchanging in growth performance (and even some of those which do increase growth) competitive encounter frequency might be easier to detect and therefore be an earlier measure of response to environmental change. This is because snapshots of the extent of spatial competition can be obtained using still photographs either by SCUBA or Remotely Operated Vehicles. In comparison, growth has to be monitored over long periods of time and compared within species across years. Bryozoans and other encrusting cryptofauna have proved strong model taxa for investigating spatial competition and artificial substrata, in the form of settlement panels, are good experimental surfaces to investigate such encounter dynamics7,9,10,11,12,13. To investigate responses to global physical change, the next step is to be able to manipulate one aspect of artificial substrata in situ whilst not altering any others.
Heat controllable settlement panels9 allow exploration of predicted mid or end-century shallow sea temperature levels in situ, which is enhanced by including several warming regimes (year-round and summer only) and levels (0, +1, and +2 °C). Different levels of warming treatments aid prediction of future responses, but are also useful because warming is geographically highly variable, even around the West Antarctic Peninsula (WAP). Using this apparatus, Ashton et al.9 found that growth (and per cent cover change) responses varied considerably between warming levels in the six most common recruit species9. In particular, a 1 °C temperature rise led to one bryozoan species, Fenestrulina rugula, monopolising most space (~60%), despite being a weak spatial competitor (it is out competed and overgrown in physical encounters with most other species it meets)7. What does this mean for assemblage dynamics and intra- and interspecific competition for space? Other factors being equal, more-occupied space should increase the incidence and importance of spatial competition. Thus Ashton et al.’s9 findings led us to hypothesise that (1) competitive encounters per unit area, and the probability of a given individual, or colony, being involved in spatial competition would increase with moderate (1 °C) warming, but less so, if at all, with 2 °C warming. The reasoning behind increased competition with 1 °C but not 2 °C warming was that Ashton et al.9 found increased growth with 1 °C but not 2 °C warming—making it more likely that the boundaries of species should come into contact. Our hypothesis (2) was that the spatial dominance of F. rugula would lead to more competition involving this species and fewer interactions involving other species (less complexity). Typically, investigation of the impacts of treatments such as warming, compares changes in species composition across treatments14. We, however, compared competitive pairings between species (across treatments). We predicted that the similarity of competitor pairings would provide a stronger response signal to warming than mere species composition, as the number of potential competitive interactions between species is the factorial of presence/absence.
We found that panels that were warmed to 1 °C above ambient (either throughout the year or just summer only) increased the probability of spatial competition among encrusting nearshore Antarctic fauna. This level of warming also increased the density and complexity of spatial competitive interactions. In contrast, warming to 2 °C above ambient increased variance (rather than mean) in the probability and density of competition, but competition did not significantly differ from ambient (control) levels. Thus biological responses, in terms of spatial competition, to warming change alter with both level and (seasonal) timing of warming. We found evidence that changes in competitive structure may be detected before changes in species composition, thus panels may be a powerful tool for monitoring early community responses to stressors such as climate change. More

Soil freeze–thaw characteristics in different landscapes
In this study, the FT characteristics exhibited certain differences among the three landscapes. AS land had the largest frost depth and the longest freeze duration, followed by LT grassland, and then farmland (Fig. 3). These differences may be attributed to the differences in dependent soil physical properties, soil surface covers and initial soil water contents of the landscape17,18. The denser soil structure of the AS land quickened the more spread of the cold from the upper soils to the lower soils than LT land and farmland during freezing. Furthermore, AS land had the lowest snow cover and no residue, which promotes heat transport at the soil–atmosphere interface19. Therefore, the soil temperature decreased rapidly with the air temperature, resulting in a significant increase in the frost depth and freezing rate of AS land. These was in accordance with the conclusions of Iwata et al. (2010)20, who clearly demonstrated that the reduction in a snow cover deposition could cause a dramatic increase in the frost depth, as well as those of Fu et al. (2018)2 who reported that the decrease in snow cover strengthened the actions of soil temperature on freezing front. In addition, the higher SWC in the LT grassland (0.21 cm3/cm3) and AS land (0.32 cm3/cm3) would slow down soil temperature changes21, because more heat release from the soil when soil freezes, or more heat is needed when soil thaws. Consequently, the wetter conditions in the LT grassland and AS land would postpone the freeze–thaw processes, as indicated by other researches17. Similar results were obtained in the study of Yi et al. (2014) on soil freeze–thaw characteristics of different landscapes in the Heihe River Basin, Gansu, China22.
Influence of freeze–thaw process on the soil water content (SWC)
In this study, the freezing process led to an upward enrichment in soil water within different landscapes in the study area (Fig. 5). One possible reason for this phenomenon was that the soil temperature gradient drove the upward flux of water towards the frozen layers, and water finally accumulated in the frozen layers23,24. However, during the spring thawing, soil water in the upper soil layer and the deeper soil layers decreased and increased, respectively (Table 2). This was because soils thawed bi–directionally, the water above the frozen layer moved upwards and ultimately intensively evaporated away, whereas the water below the frozen infiltrated into the deeper layers. These results agreed with the findings of Zhang and Wang (2001)12, Wang et al. (2009)14 and Bing et al. (2015)4. Furthermore, this freeze-induced soil water enrichment in the frozen zone can facilitate to soil water conservation by reducing evaporation and seepage, thus maintaining a high water content1,3,22, which can be helpful to farming and plant germination in the following spring. However, in this study there were obvious differences in profiled water redistributions upon freezing in different landscapes. The SWC in the AS land at a depth of 0–5 cm decreased during freezing and increased during thawing. This may be attributed to fierce regional winds, no plant residue on the surface, lack of snow cover and frequent heat exchanges between the surface soil and air during winter in the study area. Furthermore, because of the higher initial moisture content, the greater frost depth and intensity in the AS land, the water in the frozen layer continuously replenished the surface soil, and even produced internal runoff during spring thawing, despite an intensification of evaporation. This occurrence thereby increased the surface SWC, which proved the conclusions of Iwata et al. (2010)20, Nagare et al. (2012)25 and Wu et al. (2019)21. In addition, the profiled soil water migration rates in the farmland, LT grassland and AS land were substantially different during the FT processes. It was the highest in the LT grassland, whereas the lowest in the farmland. This is because the LT grassland was less salinised than the AS land and surface soil of the former had the highest organic matter content (0–25 cm, 2.50%) (Table 1), which resulted in a good soil structure that facilitated a better movement of soil water compared to the AS land. Therefore, more water migrated in the LT grassland than that in AS land during the FT processes. However, for the farmland, the lower initial moisture content (0.11 cm3/cm3) and soil compaction caused by farming activity over many years inhibited soil water migration. Furthermore, the FT affect soil physical properties, such as soil structure, soil cracking, soil thermal properties and heat flux, which were also an important reason explaining the difference of water migration in soil profiles of different landscapes. For example, frozen soils are divided into layered and reticulate structures by ice, resulting in a higher soil water permeability coefficient; thus, water can be quickly discharged from cracking during soil thawing23,24,26. Additionally, the groundwater table declined during freezing and rose during thawing, thus suggesting that a mutual transport occurred between the soil water and groundwater in deeper soil.
Influence of freeze-thaw process on the soil salinity and alkalinity
According to the data obtained from this study, the profiled soil salinity distributions were characterised by an accumulation of soil salt towards the frozen layer with soil water during the freezing. Consequently, the salt content obviously increased throughout the entire frozen layer, which experimentally verified the findings of Stahli and Stadler (1997)27 and Wang et al. (2009)14. A possible explanation for these results was that the soil salt along with water in the deeper unfrozen layer and groundwater both moved upward towards the frozen layer because of temperature gradient between the frozen and unfrozen layer. In fact, the freeze-induced soil salt migration was exceedingly complex and could not be solely attributed to the temperature gradient. Instead, this dynamic represented the integrated result of many factors, such as land use, initial soil water, soil salinisation, soil temperature, groundwater level. Furthermore, our results also showed that the salinised ratio in the upper soil profile was substantially higher than that in the deeper soil profile during freezing. This behavior may be attributed to the liquid water occurring in the frost layer and temperature gradient forcing the liquid water to carry the salt upwards. Some researchers have observed that it is possible for liquid water to exist as membrane water, wherein its thickness gradually becomes thinner from the deep soil to the upper soil, thereby causing salt to move upwards along with water28.
Furthermore, our study showed that the salification layer moved upwards and expanded, and the surface soil exhibited the significant salt accumulations in the LT grassland and AS land during spring thawing. This appears to experimentally explain the phenomenon of topsoil salt explosive increases that resemble an ‘eruption’ during spring thawing12,14. The results were in accordance with Han et al. (2010)29, who pointed out that the surface soil salinity increased rapidly in spring because of strong evaporation, more FT cycles and longer freezing durations. This is because the quantity of evaporation is five times higher than the amount of rainfall in the western Songnen Plain; thus, this intense soil evaporation induces a redistribution of the accumulated salt in the frozen layer, and transports a large quantity of salt upwards to the surface. More importantly, these findings revealed that FT processes were mainly responsible for the obvious soil salinisation in our study, which aligns with the analysis of Bing et al. (2015)4, who determined that FT processes are the main driving force of soil water and salt movement and are responsible for soil salinisation during the spring in cold and arid regions. However, these results slightly contradicted the findings of Wang. (1993)8, who noted that the surface soil salt ‘eruption’ in spring was controlled by ‘the critical depth of ground water’ rather than FT actions, yet which contradicted the local practical condition of using phreatic water as the only water source influencing the soil salinisation in this study area. The water exchanges were blocked by the frozen layers between the soil surface and underground water; therefore, soil salinisation during the spring was not related to groundwater5,12. However, their findings slightly contradicted with the results observed in our study that suggested that bi-directional thawing also possibly caused the salt under the freezing layer to accumulate in the middle soil profile. This was because the thawed water carrying salt infiltrated towards the deeper soil into the groundwater, which implied that the profiled salt distributions had a relationship with the groundwater. Moreover, the results from our study also revealed that landscapes affected the salification of the soil surface and the desalinisation of the subsurface soil, with the trend being AS land  > LT grassland  > farmland. This discrepancy may be interpreted by four aspects. Firstly, the initial soil salt content of AS land was 19.3 times higher than that of the LT grassland, consequently causing a higher accumulation ratio of soil salt, as indicated by Wan et al. (2019)6, who observed that the salt crystallisation increased the salt migration during the freezing process, and that salt migration was positively correlated with the salt content. Secondly, LT grassland had a larger coverage area and a higher litter amount reduced the quantity of ground evaporation and avoided surface salt accumulation. Thirdly, the improved soil structure of the LT grassland, with its larger root system and higher organic content was beneficial to increase infiltration and promote the downward movement of salt from the upper soil layers30. Finally, the soil of AS land started to thaw earliest because of its lowest freezing point resulted from its highest salt content at corresponding depths, which accelerated the consumption of soil water by evaporation. Additionally, the salinised ratio of the farmland was weaker than that of AS land and LT grassland, which was attributed to its lower initial salt content (64.73 mg/kg), initial water content (0.11 cm3/cm3), lower frost depth and intensity in farmland21,25.
The soil SAR and ESP have been recommended the sensitive indicators of soil alkalisation for a soil alkalisation assessment in the Songnen grassland31. In this study, FT cycles induced the increases in the SAR and ESP in the upper soil layers for all three landscapes (Fig. 8 and Table 5), which implied that the FT processes not only contributed to soil salinisation but also to soil alkalisation. As indicated in Table 6, the soil salinisation within the frozen soil layer shows a significantly positive correlation with the soil alkalisation, which was similar to the findings observed by Yu et al. (2018)31. This occurrence may be mainly attributed to the fact that the salts migrating towards the frozen layer had a prevalence of NaHCO3 and Na2CO313. Wang et al. (2009)14 also reported that soil FT were one of the most important causes of soil salinisation and alkalisation in the western Songnen Plain and further proved that the influence of groundwater could not be ignored. Groundwater in the study area comprises a weak mineralised water of NaHCO3 type, where Na+, CO32− and HCO3−contents can be up to 853.55 mg/L, the salinity is as high as 1.21 g/L and the SAR can reach 88.65. Accordingly, groundwater migrating upwards due to soil freezing induced soil both salinisation and alkalisation, which accelerated soil degradation13. Conversely, some studies have reported that FT cycles had no significant effects on soil CEC or exchangeable Ca2+ and Mg2+ but significantly decreased the exchangeable K+32 that indicated that FT cycles can possibly reduce the soil alkalisation, which was different from our results. The cause of this difference is not clear that is the integrated result of various factors, such as soil types, vegetation types, microbial activity, ground level, and so on. The experimental conditions in this study were different from Hinman (1970)32 in which soils were fumigated and sterilize without groundwater exchange and vegetation. Furthermore, the influences of soil FT on soil alkalisation varied with soil types and soil depths. In this study, the FT-induced soil alkalisation in the AS land was more pronounced than that in the farmland and LT grassland (Table 4). This may be a comprehensive consequence of land use, groundwater levels, topography, soil-human activities, and so on.
Hypothetical mechanism of freeze–thaw influences on soil salinity and alkalinity
The FT process caused variations in profiled soil water and salt distributions12, yet the internal mechanism still stayed at an exploration stage. During freezing, the potential head gradients between the frozen and unfrozen zones created by the temperature gradient exerted a certain driving force behind an upward flux of water towards the upper zones3,25. Salt, using water as the carrier, also rose towards the upper layer and was finally enriched in the frozen layer, which thereby increased the salinity. The enriched salts in the frozen layer were driven by intense surface evaporation to move towards soil surface and then accumulated, which been characterized as ‘eruptions’ during the spring. Therefore, the intensity of freezing during the winter and the strength of surface evaporation during the spring determined the extent of surface soil salinity-alkalinity.
Moreover, there was sufficient evidence to prove that soil salt migration was related to land use and vegetation. Soil colloidal particles were dispersed most widely in the AS land because of the highest Na+ contents, and most dispersed fine clay particles moved downward through the subsoil to act as a dense water barrier. Additionally, the poor soil structure of the AS land directly slowed down the soil water and salt migration rate on the unfrozen layer and the upward migration of groundwater toward the frozen layer. The relatively superior soil structure in the LT grassland promoted soil water and salt removal. Furthermore, various types of vegetation have differentially improved the soil physical, chemical and biological properties31,33, and these differential reactions may contribute to the response to FT actions. The vegetation coverages and the sizes of their root networks influenced evapotranspiration and soil water percolation, which consequently further influenced the upward water and salt migrations during FT. Maize vegetation has been found to have a greater impact than grass vegetation on repairing saline-sodic soils in the study area, and were both found to have superior soil physical properties compared to non-vegetated AS land28. Therefore, the FT processes, as associated with different landscapes and vegetation coverage, controlled soil water and salt migration during the winter and spring, which were mainly responsible for the variations in the soil salinity and alkalinity in the study area. More

1.
Li, B. et al. The contribution of China’s emissions to global climate forcing. Nature 531, 357–361 (2016).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 
2.
Yang, Q. et al. Hybrid life-cycle assessment for energy consumption and greenhouse gas emissions of a typical biomass gasification power plant in China. J. Clean Prod. 205, 661–671 (2018).
Article  Google Scholar 

3.
Amiri, S., Henning, D. & Karlsson, B. G. Simulation and introduction of a CHP plant in a Swedish biogas system. Renew. Energ. 49, 242–249 (2013).
Article  Google Scholar 

4.
NDRC. National Development and Reform Committee of China, 2016. The “13th Five-year Plan” of Biomass Energy, Beijing (2016) [In Chinese].

5.
Serra, P., Giuntoli, J., Agostini, A., Colauzzi, M. & Amaducci, S. Coupling sorghum biomass and wheat straw to minimise the environmental impact of bioenergy production. J. Clean. Prod. 154, 242–254 (2017).
CAS  Article  Google Scholar 

6.
Benoist, A., Dron, D. & Zoughaib, A. Origins of the debate on the life-cycle greenhouse gas emissions and energy consumption of first-generation biofuels: A sensitivity analysis approach. Biomass. Bioenerg. 40, 133–142 (2012).
CAS  Article  Google Scholar 

7.
Klimiuk, E., Pokoj, T., Budzynski, W. & Dubis, B. Theoretical and observed biogas production from plant biomass of different fibre contents. Biosour. Technol. 101, 9527–9535 (2010).
CAS  Article  Google Scholar 

8.
Mela, G. & Canali, G. How distorting policies can affect energy efficiency and sustainability: the case of biogas production in the Po Valley. AgBio Forum 16, 194–206 (2014) ([In Chinese]).
Google Scholar 

9.
International Energy Agency. World energy outlook 2011 (International Energy Agency, Paris, 2011).
Google Scholar 

10.
Gerbens-Leenes, P. W., Hoekstra, A. Y. & van der Meer, T. The water footprint of energy from biomass: A quantitative assessment and consequences of an increasing share of bio-energy in energy supply. Ecol. Econ. 68, 1052–1060 (2009).
Article  Google Scholar 

11.
Lijó, L. et al. Life Cycle Assessment of electricity production in Italy from anaerobic co-digestion of pig slurry and energy crops. Renew. Energ. 68, 625–635 (2014).
Article  CAS  Google Scholar 

12.
Zheng, Y., Zhao, J., Xu, F. & Li, Y. Pretreatment of lignocellulosic biomass for enhanced biogas production. Prog Energ Combust 42, 35–53 (2014).
Article  Google Scholar 

13.
Cuellar, M. C. & Straathof, A. J. Biochemical conversion: biofuels by industrial fermentation. Biomass as a Sustainable Energy Source for the Future: Fundamentals of Conversion Processes. (Eds Wiley, J. et al.) 403 (New Jersey, USA. Press, 2015).

14.
Schittenhelm, S. Chemical composition and methane yield of maize hybrids with contrasting maturity. Eur. J. Agron. 29, 72–79 (2008).
CAS  Article  Google Scholar 

15.
Ertem, F. C., Neubauer, P. & Junne, S. Environmental life cycle assessment of biogas production from marine macroalgal feedstock for the substitution of energy crops. J. Clean. Prod. 140, 977–985 (2017).
CAS  Article  Google Scholar 

16.
Rathor, D., Nizami, A.-S., Singh, A. & Pant, D. Key issues in estimating energy and greenhouse gas savings of biofuels: Challenges and perspectives. Biofuel Res. J. 3, 380–393 (2016).
Article  Google Scholar 

17.
Lemus, R. & Lal, R. Bioenergy Crops and Carbon Sequestration. Crit Rev Plant Sci 24, 1–21 (2005).
CAS  Article  Google Scholar 

18.
Lewandowski, I., Scurlock, J. M. O., Lindvall, E. & Christou, M. The development and current status of perennial rhizomatous grasses as energy crops in the US and Europe. Biomass Bioenerg. 25, 335–361 (2003).
Article  Google Scholar 

19.
Amon, T. et al. Methane production through anaerobic digestion of various energy crops grown in sustainable crop rotations. Biosour Technol 98, 3204–3212 (2007).
CAS  Article  Google Scholar 

20.
Igliński, B., Buczkowski, R. & Cichosz, M. Biogas production in Poland—Current state, potential and perspectives. Renew. Sust. Energ. Rev. 50, 686–695 (2015).
Article  CAS  Google Scholar 

21.
Shete, M., Rutten, M., Schoneveld, G. C. & Zewude, E. Land-use changes by large-scale plantations and their effects on soil organic carbon, micronutrients and bulk density: empirical evidence from Ethiopia. Agr. Hum. Values 33, 689–704 (2015).
Article  Google Scholar 

22.
He, P. & Li, D. Develop bio-energy on marginal land from the perspective of food security. Rural Econ. 51–53 (2011).

23.
Blengini, G. A., Brizio, E., Cibrario, M. & Genon, G. LCA of bioenergy chains in Piedmont (Italy): A case study to support public decision makers towards sustainability. Resour. Conserv. Recycle 57, 36–47 (2011).
Article  Google Scholar 

24.
Zhao, C., Chen, B. & Yang, J. Embodied water consumption of biogas–digestate utilization. Energy Proc. 61, 615–618 (2014).
Article  Google Scholar 

25.
Pacetti, T., Lombardi, L. & Federici, G. Water–energy Nexus: a case of biogas production from energy crops evaluated by Water Footprint and Life Cycle Assessment (LCA) methods. J. Clean. Prod. 101, 278–291 (2015).
Article  Google Scholar 

26.
Chapagain, A. K. & Hoekstra, A. Y. The blue, green and grey water footprint of rice from production and consumption perspectives. Ecol. Econ. 70, 749–758 (2011).
Article  Google Scholar 

27.
Lovarelli, D., Bacenetti, J. & Fiala, M. Water Footprint of crop productions: A review. Sci. Total Environ. 548–549, 236–251 (2016).
ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

28.
Zhang, L., Dawes, W. R. & Walker, G. R. Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour. Res. 37, 701–708 (2001).
ADS  Article  Google Scholar 

29.
Yasar, A., Rasheed, R., Tabinda, A. B., Tahir, A. & Sarwar, F. Life cycle assessment of a medium commercial scale biogas plant and nutritional assessment of effluent slurry. Renew. Sust. Energ. Rev. 67, 364–371 (2017).
CAS  Article  Google Scholar 

30.
Xu, C., Shi, W., Hong, J., Zhang, F. & Chen, W. Life cycle assessment of food waste-based biogas generation. Renew. Sust. Energ. Rev. 49, 169–177 (2015).
CAS  Article  Google Scholar 

31.
Van Stappen, F. et al. Consequential environmental life cycle assessment of a farm-scale biogas plant. J. Environ. Manag. 175, 20–32 (2016).
Article  CAS  Google Scholar 

32.
Collet, P. et al. Techno-economic and life cycle assessment of methane production via biogas upgrading and power to gas technology. Appl. Energ. 192, 282–295 (2017).
CAS  Article  Google Scholar 

33.
Chen, B. & Chen, S. Life cycle assessment of coupling household biogas production to agricultural industry: A case study of biogas-linked persimmon cultivation and processing system. Energ Policy 62, 707–716 (2013).
CAS  Article  Google Scholar 

34.
Torquati, B., Venanzi, S., Ciani, A., Diotallevi, F. & Tamburi, V. Environmental sustainability and economic benefits of dairy farm biogas energy production: A case study in Umbria. Sustainability 6, 6696–6713 (2014).
Article  Google Scholar 

35.
Boulay, A.-M., Hoekstra, A. Y. & Vionnet, S. Complementarities of water-focused life cycle assessment and water footprint assessment. Environ. Sci. Technol. 47, 11926–11927 (2013).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

36.
Jefferies, D. et al. Water footprint and life cycle assessment as approaches to assess potential impacts of products on water consumption. Key learning points from pilot studies on tea and margarine. J. Clean. Prod. 33, 155–166 (2012).

37.
Mehmeti, A., Angelis-Dimakis, A., Arampatzis, G., McPhail, S. & Ulgiati, S. Life cycle assessment and water footprint of hydrogen production methods: from conventional to emerging technologies. Environments 5, 1–19 (2018).
Article  Google Scholar 

38.
Ridoutt, B. G., Page, G., Opie, K., Huang, J. & Bellotti, W. Carbon, water and land use footprints of beef cattle production systems in southern Australia. J. Clean. Prod. 73, 24–30 (2014).
Article  Google Scholar 

39.
Page, G., Ridoutt, B. & Bellotti, B. Carbon and water footprint tradeoffs in fresh tomato production. J. Clean. Prod. 32, 219–226 (2012).
Article  Google Scholar 

40.
Hijazi, O., Munro, S., Zerhusen, B. & Effenberger, M. Review of life cycle assessment for biogas production in Europe. Renew Sust Energ Rev 54, 1291–1300 (2016).
CAS  Article  Google Scholar 

41.
Rooney, W. L., Blumenthal, J., Bean, B. & Mullet, J. E. Designing sorghum as a dedicated bioenergy feedstock. Biofuels Biofuel Bioprod. Bior 1, 147–157 (2007).
CAS  Article  Google Scholar 

42.
Fracasso, A., Trindade, L. & Amaducci, S. Drought tolerance strategies highlighted by two Sorghum bicolor races in a dry-down experiment. J. Plant Physiol. 190, 1–14 (2016).
CAS  PubMed  Article  PubMed Central  Google Scholar 

43.
Duan, Q. Water footprint and Carbon balance in the cultivation, fermentation and energy utilization process of industrial biogas crops, Southwest University, (2017) (In Chinese).

44.
Fu, C., Dong, T. & Sun, Y. Selection of High Yield Energy Crops for marginal land and its biogas production potential. China Biogas 35, 72–76 (2017) ((In Chinese)).
Google Scholar 

45.
Ming, Z., Shaojie, O., Hui, S., Yujian, G. & Qiqi, Q. Overall review of distributed energy development in China: Status quo, barriers and solutions. Renew. Sust. Energ. Rev. 50, 1226–1238 (2015).
Article  Google Scholar 

46.
Lazarova, V., Choo, K.-H. & Cornel, P. Water-energy interactions in water reuse. (IWA, London, press, 2012).

47.
Holm-Nielsen, J. B., Al Seadi, T. & Oleskowicz-Popiel, P. The future of anaerobic digestion and biogas utilization. Biosour. Technol. 100, 5478–5484 (2009).

48.
Kristensen, P. G., Jensen, J. K., Nielsen, M. & Illerup, J. B. Emission factors for gas fired CHP units< 25 MW. (IGRC, 2004). 49. Eggleston, S., Buendia, L., Miwa, K., Ngara, T. & Tanabe, K. 2006 IPCC guidelines for national greenhouse gas inventories (Institute for Global Environmental Strategies Hayama, Japan, 2006). Google Scholar  50. Mekonnen, M. & Hoekstra, A. Y. National water footprint accounts: the green, blue and grey water footprint of production and consumption. (UNESCO-IHE Institute for Water Education, Netherlands, 2017). 51. Gerbens-Leenes, W., Hoekstra, A. Y. & van der Meer, T. H. The water footprint of bioenergy. Proc. Natl. Acad. Sci. 106, 10219–10223 (2009). ADS  CAS  PubMed  Article  PubMed Central  Google Scholar  52. Gai, L., Xie, G., Li, S., Zhang, C. & Chen, D. A study on production water footprint of winter wheat and maize in the North China Plain. Resour. Sci. 32, 2066–2071 (2010) ([In Chinese]). Google Scholar  53. Chapagain, A. K., Hoekstra, A. Y., Savenije, H. H. G. & Gautam, R. The water footprint of cotton consumption: An assessment of the impact of worldwide consumption of cotton products on the water resources in the cotton producing countries. Ecol. Econ. 60, 186–203 (2006). Article  Google Scholar  54. Cao. et al. Water footprint assessment for crop production based on field measurements: A case study of irrigated paddy rice in East China. Sci. Total Environ. 610, 84–93 (2018). 55. Tian, J. 2013 Jinan effective utilization coefficient of irrigation water analysis and evaluation of estimates, Shandong University, (2014). 56. Hoekstra, A. Y., Chapagain, A. K., Mekonnen, M. M. & Aldaya, M. M. The water footprint assessment manual: Setting the global standard. (Routledge, 2011). 57. Wang, Z., Wu, Z. & Tang, S. Extracellular polymeric substances (EPS) properties and their effects on membrane fouling in a submerged membrane bioreactor. Water Res. 43, 2504–2512 (2009). CAS  PubMed  Article  PubMed Central  Google Scholar  58. Li, X., Yang, D. & Xia, F. Analysis of the water footprint of suburban planting in arid lands and determination of suitable farmland scale: a case study of Urumqi. Acta Ecol. Sin. 35, 2860–2869 (2015). Google Scholar  59. Su, M.-H., Huang, C.-H., Li, W.-Y., Tso, C.-T. & Lur, H.-S. Water footprint analysis of bioethanol energy crops in Taiwan. J Clean Prod 88, 132–138 (2015). Article  Google Scholar  60. 60Gu, J. Study of water footprint of coal-based fuels with life cycle assessment, Shanghai Jiao Tong University, (2015) [In Chinses]. 61. European, C. State of play on the sustainability of solid and gaseous biomass used for electricity, heating and cooling in the EU-Commission staff working document (2014). 62. Yu, C. Study on regional difference of profuction water footprint of main crop based on cropwat in Shandong Province Jinan: Shandong Normal University (2014) [In Chinese]. 63. Lijó, L., González-García, S., Bacenetti, J. & Moreira, M. T. The environmental effect of substituting energy crops for food waste as feedstock for biogas production. Energy 137, 1130–1143 (2017). Article  Google Scholar  64. Wang, Q. L., Li, W., Gao, X. & Li, S. J. Life cycle assessment on biogas production from straw and its sensitivity analysis. Biosour. Technol. 201, 208–214 (2016). CAS  Article  Google Scholar  65. Flesch, T. K., Desjardins, R. L. & Worth, D. Fugitive methane emissions from an agricultural biodigester. Biomass Bioenerg. 35, 3927–3935 (2011). CAS  Article  Google Scholar  66. Li, J. Scenario analysis of tourism’s water footprint for China’s Beijing–Tianjin–Hebei region in 2020: implications for water policy. J. Sustain. Tour 26(1), 127–145 (2017). Article  Google Scholar  More

1.
Cady, S. L., Farmer, J. D., Grotzinger, J. P., Schopf, J. W. & Steele, A. Morphological biosignatures and the search for life on mars. Astrobiology 3, 351–368 (2003).
ADS  CAS  PubMed  Article  Google Scholar 
2.
Squyres, S. W. et al. Detection of silica-rich deposits on Mars. Source Sci. New Ser. 320, 1063–1067 (2008).
CAS  Google Scholar 

3.
Rice, M. S. et al. Silica-rich deposits and hydrated minerals at Gusev Crater, Mars: Vis-NIR spectral characterization and regional mapping. Icarus 205, 375–395 (2010).
ADS  CAS  Article  Google Scholar 

4.
Ruff, S. W. et al. Characteristics, distribution, origin, and significance of opaline silica observed by the Spirit rover in Gusev crater, Mars. J. Geophys. Res. E Planets 116, E00F23 (2011).
Article  CAS  Google Scholar 

5.
Ruff, S. W. & Farmer, J. D. Silica deposits on Mars with features resembling hot spring biosignatures at El Tatio in Chile. Nat. Commun. 7, 13554 (2016).
ADS  PubMed  PubMed Central  Article  Google Scholar 

6.
Jones, B. & Renault, R. W. Hot spring and geyser sinters: the integrated product of precipitation, replacement, and deposition. Can. J. Earth Sci. 40, 1549–1569 (2003).
ADS  CAS  Article  Google Scholar 

7.
Konhauser, K. O., Jones, B., Phoenix, V. R., Ferris, G. & Renaut, R. W. The microbial role in Hhot spring silicification. Ambio 33, 552–558 (2004).
PubMed  Article  Google Scholar 

8.
Pepe-Ranney, C., Berelson, W. M., Corsetti, F. A., Treants, M. & Spear, J. R. Cyanobacterial construction of hot spring siliceous stromatolites in Yellowstone National Park. Environ. Microbiol. 14, 1182–1197 (2012).
CAS  PubMed  Article  Google Scholar 

9.
Barton, H. A. et al. Microbial diversity in a Venezuelan orthoquartzite cave is dominated by the Chloroflexi (Class Ktedonobacterales) and Thaumarchaeota Group I.1c. Front. Microbiol. 5, 615 (2014).
PubMed  PubMed Central  Article  Google Scholar 

10.
Sauro, F. et al. Microbial diversity and biosignatures of amorphous silica deposits in orthoquartzite caves. Sci. Rep. 8, 1–14 (2018).
ADS  CAS  Article  Google Scholar 

11.
Wong, F. K. Y. et al. Hypolithic microbial community of quartz pavement in the high-altitude tundra of Central Tibet. Microb. Ecol. 60, 730–790 (2010).
PubMed  PubMed Central  Article  Google Scholar 

12.
Lacap, D. C., Warren-Rhodes, K. A., McKay, C. P. & Pointing, S. B. Cyanobacteria and chloroflexi-dominated hypolithic colonization of quartz at the hyper-arid core of the Atacama Desert, Chile. Extremophiles 15, 31–38 (2011).
PubMed  Article  Google Scholar 

13.
Lynch, R. C. et al. The potential for microbial life in the highest-elevation ( >6000 m.a.s.l.) mineral soils of the Atacama region. J. Geophys. Res. 117, G02028 (2012).
Google Scholar 

14.
Tebo, B. M. et al. Microbial communities in dark oligotrophic volcanic ice cave ecosystems of Mt. Erebus, Antarctica. Front. Microbiol. 6, 179 (2015).
PubMed  PubMed Central  Article  Google Scholar 

15.
Sauro, F. et al. Source and genesis of sulphate and phosphate-sulphate minerals in a quartz-sandstone cave environment. Sedimentology 61, 1433–1451 (2014).
CAS  Article  Google Scholar 

16.
Mecchia, M., Sauro, F., Piccini, L., Columbu, A. & De Waele, J. A hybrid model to evaluate subsurface chemical weathering and fracture karstification in quartz sandstone. J. Hydrol. 572, 745–760 (2019).
ADS  CAS  Article  Google Scholar 

17.
Mecchia, M. et al. Geochemistry of surface and subsurface waters in quartz-sandstones: significance for the geomorphic evolution of tepui table mountains (Gran Sabana, Venezuela). J. Hydrol. 511, 117–138 (2014).
ADS  CAS  Article  Google Scholar 

18.
Ji, M. et al. Atmospheric trace gases support primary production in Antarctic desert surface soil. Nature 552, 400–403 (2017).
ADS  CAS  PubMed  Article  Google Scholar 

19.
King, G. M., Weber, C. F., Nanba, K., Sato, Y. & Ohta, H. Atmospheric CO and hydrogen uptake and CO oxidizer phylogeny for miyake-jima, Japan volcanic deposits. Microbes Environ. 23, 299–305 (2008).
PubMed  Article  Google Scholar 

20.
Cordero, P. R. F. et al. Atmospheric carbon monoxide oxidation is a widespread mechanism supporting microbial survival. ISME J. 13, 2868–2881 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

21.
Aubrecht, R., Brewer-Carías, C., Šmída, B., Audy, M. & Kováčik, Ľ. Anatomy of biologically mediated opal speleothems in the World’s largest sandstone cave: Cueva Charles Brewer, Chimantá Plateau, Venezuela. Sediment. Geol. 203, 181–195 (2008).
ADS  Article  Google Scholar 

22.
Vidal Romanì, J. R., Sànchez, J. S., Rodrìguez, M. V. & Mosquera, D. F. Speleothem development and biological activity in granite cavities. Géomorphol. Relief Process. Environ. 16, 337–346 (2010).
Article  Google Scholar 

23.
Miller, A. Z. et al. Siliceous speleothems and associated microbe-mineral interactions from Ana Heva lava tube in Easter Island (Chile). Geomicrobiol. J. 31, 236–245 (2014).
CAS  Article  Google Scholar 

24.
Hill, C. A. & Forti, P. Cave Minerals of the World 1–463 (National Speleological Society, Alabama, 1997).
Google Scholar 

25.
Willis, C., Desai, D. & LaRoche, J. Influence of 16S rRNA variable region on perceived diversity of marine microbial communities of the Northern North Atlantic. FEMS Microbiol. Lett. 366, fnz152 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

26.
Peiffer, J. A. et al. Diversity and heritability of the maize rhizosphere microbiome under field conditions. Proc. Natl. Acad. Sci. U.S.A. 110, 6548–6553 (2013).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

27.
Wang, F. et al. Assessment of 16S rRNA gene primers for studying bacterial community structure and function of aging flue-cured tobaccos. AMB Express 8, 182 (2018).
PubMed  PubMed Central  Article  CAS  Google Scholar 

28.
Wu, X. et al. Impact of mitigation strategies on acid sulfate soil chemistry and microbial community. Sci. Total Environ. 526, 215–221 (2015).
ADS  CAS  PubMed  Article  Google Scholar 

29.
Min, X., Wang, Y., Chai, L., Yang, Z. & Liao, Q. High-resolution analyses reveal structural diversity patterns of microbial communities in chromite ore processing residue (COPR) contaminated soils. Chemosphere 183, 266–276 (2017).
ADS  CAS  PubMed  Article  Google Scholar 

30.
Weber, C. F. & King, G. M. Distribution and diversity of carbon monoxide-oxidizing bacteria and bulk bacterial communities across a succession gradient on a Hawaiian volcanic deposit. Environ. Microbiol. 12, 1855–1867 (2010).
CAS  PubMed  Article  Google Scholar 

31.
Saitta, E. T. et al. Cretaceous dinosaur bone contains recent organic material and provides an environment conducive to microbial communities. Elife 8, e46205 (2019).
PubMed  PubMed Central  Article  Google Scholar 

32.
Aubrecht, R. Speleothems. In Encyclopedia of Earth Sciences Series, 836–840 (Springer Netherlands, 2011)

33.
Reitner, J. & Volker, T. Encyclopedia of Geobiology (Springer, Cham, 2011).
Google Scholar 

34.
Miller, C. S. et al. Short-read assembly of full-length 16S amplicons reveals bacterial diversity in subsurface sediments. PLoS ONE 8, e56018 (2013).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

35.
Miller, C. S., Baker, B. J., Thomas, B. C., Singer, S. W. & Banfield, J. F. EMIRGE: Reconstruction of full-length ribosomal genes from microbial community short read sequencing data. Genome Biol. 12, R44 (2011).
CAS  PubMed  PubMed Central  Article  Google Scholar 

36.
Aubrecht, R. Venezuelan Tepuis: Their Caves and Biota (Acta Geologica Slovaca, Comenius University, Bratislava, 2012).
Google Scholar 

37.
Piccini, L. & Mecchia, M. Solution weathering rate and origin of karst landforms and caves in the quartzite of Auyan-tepui (Gran Sabana, Venezuela). Geomorphology 106, 15–25 (2009).
ADS  Article  Google Scholar 

38.
Sauro, F. et al. Genesis of giant sinkholes and caves in the quartz sandstone of Sarisariñama tepui, Venezuela. Geomorphology 342, 223–238 (2019).
ADS  Article  Google Scholar 

39.
Wray, R. A. & Sauro, F. An updated global review of solutional weathering processes and forms in quartz sandstones and quartzites. Earth-Sci. Rev. 171, 520–557 (2017).
ADS  CAS  Article  Google Scholar 

40.
Hug, L. et al. Community genomic analyses constrain the distribution of metabolic traits across the Chloroflexi phylum and indicate roles in sediment carbon cycling. Microbiome 1, 22 (2013).
PubMed  PubMed Central  Article  Google Scholar 

41.
Islam, Z. F. et al. Two Chloroflexi classes independently evolved the ability to persist on atmospheric hydrogen and carbon monoxide. ISME J. 13, 1801–1813 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

42.
Oliveira, C. et al. 16S rRNA gene-based metagenomic analysis of Ozark cave bacteria. Diversity 9, 31 (2017).
PubMed  PubMed Central  Article  CAS  Google Scholar 

43.
Yabe, S., Aiba, Y., Sakai, Y., Hazaka, M. & Yokota, A. A life cycle of branched aerial mycelium- and multiple budding spore-forming bacterium Thermosporothrix hazakensis belonging to the phylum Chloroflexi. J. Gen. Appl. Microbiol. 56, 137–141 (2010).
CAS  PubMed  Article  PubMed Central  Google Scholar 

44.
Yabe, S., Sakai, Y., Abe, K. & Yokota, A. Diversity of Ktedonobacteria with Actinomycetes-like morphology in terrestrial environments. Microbes Environ. 32, 61–70 (2017).
PubMed  PubMed Central  Article  Google Scholar 

45.
Yabe, S. et al. Formation of Sporangiospores in Dictyobacter aurantiacus (Class Ktedonobacteria in Phylum Chloroflexi). J. Gen. Appl. Microbiol. 65, 316–319 (2019).
CAS  PubMed  Article  PubMed Central  Google Scholar 

46.
Zheng, Y. et al. Genome features and secondary metabolites biosynthetic potential of the class Ktedonobacteria. Front. Microbiol. 10, 1–21 (2019).
PubMed  PubMed Central  Article  Google Scholar 

47.
Handley, K. M. et al. Disturbed subsurface microbial communities follow equivalent trajectories despite different structural starting points. Environ. Microbiol. 17, 622–636 (2015).
CAS  PubMed  Article  PubMed Central  Google Scholar 

48.
Sáenz de Miera, L. E., Arroyo, P., de Luis Calabuig, E., Falagán, J. & Ansola, G. High-throughput sequencing of 16S RNA genes of soil bacterial communities from a naturally occurring CO2 gas vent. Int. J. Greenh. Gas Control 29, 176–184 (2014).
Article  CAS  Google Scholar 

49.
Yarza, P. et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat. Rev. Microbiol. 12, 635–645 (2014).
CAS  PubMed  Article  Google Scholar 

50.
Cavaletti, L. et al. New lineage of filamentous, spore-forming, gram-positive bacteria from soil. Appl. Environ. Microbiol. 72, 4360–4369 (2006).
CAS  PubMed  PubMed Central  Article  Google Scholar 

51.
Yan, B., Guo, X., Liu, M. & Huang, Y. Ktedonosporobacter rubrisoli gen. nov., sp. Nov., a novel representative of the class Ktedonobacteria, isolated from red soil, and proposal of Ktedonosporobacteraceae fam. nov. Int. J. Syst. Evol. Microbiol. 70, 1015–1025 (2019).
Article  CAS  Google Scholar 

52.
Yabe, S., Aiba, Y., Sakai, Y., Hazaka, M. & Yokota, A. Thermosporothrix hazakensis gen. nov., sp. Nov., isolated from compost, description of Thermosporotrichaceae fam. Nov. within the class Ktedonobacteria Cavaletti et al. 2007 and emended description of the class Ktedonobacteria. Int. J. Syst. Evol. Microbiol. 60, 1794–1801 (2010).
CAS  PubMed  Article  Google Scholar 

53.
Yabe, S., Aiba, Y., Sakai, Y., Hazaka, M. & Yokota, A. Thermogemmatispora onikobensis gen. nov., sp. Nov. and Thermogemmatispora foliorum sp. nov., isolated from fallen leaves on geothermal soils, and description of Thermogemmatisporaceae fam. nov. and Thermogemmatisporales ord. nov. within the class Ktedonobacteria. Int. J. Syst. Evol. Microbiol. 61, 903–910 (2011).
CAS  PubMed  Article  Google Scholar 

54.
Jones, A. A. & Bennett, P. C. Mineral microniches control the diversity of subsurface microbial populations. Geomicrobiol. J. 31, 246–261 (2014).
CAS  Article  Google Scholar 

55.
Urzì, C. & Realini, M. Colour changes of Noto’s calcareous sandstone as related to its colonisation by microorganisms. Int. Biodeter. Biodegr. 42, 45–54 (1998).
Article  Google Scholar 

56.
Riquelme, C. et al. Actinobacterial diversity in volcanic caves and associated geomicrobiological interactions. Front. Microbiol. 6, 1342 (2015).
PubMed  PubMed Central  Article  Google Scholar 

57.
Cañaveras, J. C. et al. On the origin of fiber calcite crystals in moonmilk deposits. Naturwissenschaften 93, 27–32 (2006).
ADS  PubMed  Article  CAS  Google Scholar 

58.
Cockell, C. S., Kelly, L. C. & Marteinsson, V. Actinobacteria–An ancient phylum active in volcanic rock weathering. Geomicrobiol. J. 30, 706–720 (2013).
CAS  Article  Google Scholar 

59.
Lynch, R. C., Darcy, J. L., Kane, N. C., Nemergut, D. R. & Schmidt, S. K. Metagenomic evidence for metabolism of trace atmospheric gases by high-elevation desert Actinobacteria. Front. Microbiol. 5, 698 (2014).
PubMed  PubMed Central  Article  Google Scholar 

60.
Sellstedt, A. & Richau, K. H. Aspects of nitrogen-fixing Actinobacteria, in particular free-living and symbiotic Frankia. FEMS Microbiol. Lett. 342, 179–186 (2013).
CAS  PubMed  Article  PubMed Central  Google Scholar 

61.
Gonzalez-Pimentel, J. L. et al. Yellow coloured mats from lava tubes of La Palma (Canary Islands, Spain) are dominated by metabolically active Actinobacteria. Sci. Rep. 8, 1944 (2018).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

62.
Wu, Y. et al. Profiling bacterial diversity in a limestone cave of the western Loess Plateau of China. Front. Microbiol. 6, 244 (2015).
PubMed  PubMed Central  Google Scholar 

63.
Lavoie, K. H. et al. Comparison of bacterial communities from lava cave microbial mats to overlying surface soils from Lava Beds National Monument, USA. PLoS ONE 12, e0169339 (2017).
PubMed  PubMed Central  Article  CAS  Google Scholar 

64.
Barton, H. A. et al. The impact of host rock geochemistry on bacterial community structure in oligotrophic cave environments. Int. J. Speleol. 36, 93–104 (2007).
Article  Google Scholar 

65.
Li, Q., Zhang, B., Yang, X. & Ge, Q. Deterioration-associated microbiome of stone monuments: structure, variation, and assembly. Appl. Environ. Microbiol. 84, e02680 (2018).
PubMed  PubMed Central  Google Scholar 

66.
Mohagheghi, A., Grohmann, K. & Himmel, M. Isolation and characterization of Acidothermus cellulolyticus gen. nov., sp. nov., a new genus of thermophilic, acidophilic, cellulolytic bacteria. Int. J. Syst. Bacteriol. 36, 435–443 (1986).
CAS  Article  Google Scholar 

67.
Borsodi, A. K. et al. Biofilm bacterial communities inhabiting the cave walls of the Buda thermal karst system, Hungary. Geomicrobiol. J. 29, 611–627 (2012).
Article  Google Scholar 

68.
Huang, T.-Y. et al. Role of microbial communities in the weathering and stalactite formation in karst topography. Biogeosci. Discuss. https://doi.org/10.5194/bg-2019-12 (2019).
Article  Google Scholar 

69.
Mohanty, A. et al. Iron mineralizing bacterioferritin A from Mycobacterium tuberculosis exhibits unique catalase-Dps-like dual activities. Inorg. Chem. 58, 4741–4752 (2019).
CAS  PubMed  Article  Google Scholar 

70.
Kennedy, K., Hall, M. W., Lynch, M. D. J., Moreno-Hagelsieb, G. & Neufeld, J. D. Evaluating bias of Illumina-based bacterial 16S rRNA gene profiles. Appl. Environ. Microbiol. 80, 5717–5722 (2014).
PubMed  PubMed Central  Article  CAS  Google Scholar 

71.
Oppenheimer-Shaanan, Y. et al. Spatio-temporal assembly of functional mineral scaffolds within microbial biofilms. NPJ Biofilms Microbiomes 2, 1–10 (2016).
Article  Google Scholar 

72.
Nishiyama, M., Sugita, R., Otsuka, S. & Senoo, K. Community structure of bacteria on different types of mineral particles in a sandy soil. Soil Sci. Plant Nutr. 58, 562–567 (2012).
CAS  Article  Google Scholar 

73.
Vasanthi, N., Saleena, L. M. & Anthoni Raj, S. Silica solubilization potential of certain bacterial species in the presence of different Ssilicate minerals. Silicon 10, 267–275 (2018).
CAS  Article  Google Scholar 

74.
Mohammadi, S. S. et al. The acidophilic methanotroph Methylacidimicrobium tartarophylax 4AC grows as autotroph on H2 under microoxic conditions. Front. Microbiol. 10, 2352 (2019).
PubMed  PubMed Central  Article  Google Scholar 

75.
Lorite, M. J., Tachil, J., Sanjuán, J., Meyer, O. & Bedmar, E. J. Carbon monoxide dehydrogenase activity in Bradyrhizobium japonicum. Appl. Environ. Microbiol. 66, 1871–1876 (2000).
CAS  PubMed  PubMed Central  Article  Google Scholar 

76.
Tran, P. et al. Microbial life under ice: metagenome diversity and in situ activity of Verrucomicrobia in seasonally ice-covered lakes. Environ. Microbiol. 20, 2568–2584 (2018).
CAS  PubMed  Article  Google Scholar 

77.
Funari, V., Braga, R., Bokhari, S. N. H., Dinelli, E. & Meisel, T. Solid residues from Italian municipal solid waste incinerators: a source for ‘“critical”’ raw materials. Waste Manag. 45, 206–216 (2015).
CAS  PubMed  Article  Google Scholar 

78.
Cappelletti, M., Ghezzi, D., Zannoni, D., Capaccioni, B. & Fedi, S. Diversity of methane-oxidizing bacteria in soils from “Hot Lands of Medolla” (Italy) featured by anomalous high-temperatures and biogenic CO2 emission. Microbes Environ. 31, 369–377 (2016).
PubMed  PubMed Central  Article  Google Scholar 

79.
D’Angeli, I. M. et al. Geomicrobiology of a seawater-influenced active sulfuric acid cave. PLoS ONE 14, e0220706 (2019).
PubMed  PubMed Central  Article  CAS  Google Scholar 

80.
Koskinen, K. et al. First insights into the diverse human archaeome: specific detection of Archaea in the gastrointestinal tract, lung, and nose and on skin. mBio 8, e00824-e917 (2017).
CAS  PubMed  PubMed Central  Article  Google Scholar 

81.
Klymiuk, I., Bambach, I., Patra, V., Trajanoski, S. & Wolf, P. 16S based microbiome analysis from healthy subjects’ skin swabs stored for different storage periods reveal phylum to genus level changes. Front. Microbiol. 7, 2012 (2016).
PubMed  PubMed Central  Article  Google Scholar 

82.
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41(Database issue), D590–D596 (2013).
CAS  Google Scholar 

83.
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).
CAS  PubMed  PubMed Central  Article  Google Scholar 

84.
Pausan, M. R. et al. Exploring the archaeome: detection of archaeal signatures in the human body. Front. Microbiol. 10, 2796 (2019).
PubMed  PubMed Central  Article  Google Scholar 

85.
King, G. M. Molecular and culture-based analyses of aerobic carbon monoxide oxidizer diversity. Appl. Environ. Microbiol. 69, 7257–7265 (2003).
CAS  PubMed  PubMed Central  Article  Google Scholar 

86.
Beimgraben, C., Gutekunst, K., Opitz, F. & Appel, J. HypD as a marker for [NiFe]-hydrogenases in microbial communities of surface waters. Appl. Environ. Microbiol. 80, 3776–3782 (2014).
PubMed  PubMed Central  Article  CAS  Google Scholar 

87.
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 

88.
Prodan, A. et al. Comparing bioinformatic pipelines for microbial 16S rRNA amplicon sequencing. PLoS ONE 15, e0227434 (2020).
CAS  PubMed  PubMed Central  Article  Google Scholar  More

1.
FAO. The state of world fisheries and aquaculture 2016: Contributing to food security and nutrition for all (FAO, 2016).
2.
De Groot, S. J. The impact of bottom trawling on benthic fauna of the North Sea. Ocean Manag. 9, 177–190 (1984).
Article  Google Scholar 

3.
Dayton, P. K., Thrush, S. F., Agardy, M. T. & Hofman, R. J. Environmental effects of marine fishing. Aquat. Conserv. 5, 205–232 (1995).
Article  Google Scholar 

4.
Kumar, A. B. & Deepthi, G. R. Trawling and by-catch: implications on marine ecosystem. Curr. Sci. 90, 922–931 (2006).
Google Scholar 

5.
Foden, J., Rogers, S. I. & Jones, A. P. Human pressures on UK seabed habitats: a cumulative impact assessment. Mar. Ecol. Prog. Ser. 428, 33–47 (2011).
Article  Google Scholar 

6.
Jones, J. B. Environmental impact of trawling on the seabed: a review. N. Z. J. Mar. Freshwat. Res. 26, 59–67 (1992).
Article  Google Scholar 

7.
Thrush, S. F. & Dayton, P. K. Disturbance to marine benthic habitats by trawling and dredging: implications for marine biodiversity. Annu. Rev. Ecol. Evol. Syst. 33, 449–473 (2002).
Article  Google Scholar 

8.
Hiddink, J. G. et al. Global analysis of depletion and recovery of seabed biota after bottom trawling disturbance. Proc. Natl. Acad. Sci. USA 114, 8301–8306 (2017).
CAS  Article  Google Scholar 

9.
Churchill, J. H. In Effects of Fishing Gear on the Sea Floor of New England (ed. Dorsey, E. M.) (Conservation Law Foundation, 1998).

10.
Pusceddu, A. et al. Impact of natural (storm) and anthropogenic (trawling) sediment resuspension on particulate organic matter in coastal environments. Cont. Shelf Res. 25, 2506–2520 (2005).
Article  Google Scholar 

11.
Palanques, A., Guillén, J. & Puig, P. Impact of bottom trawling on water turbidity and muddy sediment of an unfished continental shelf. Limnol. Oceanogr. 46, 1100–1110 (2001).
Article  Google Scholar 

12.
Riemann, B. & Hoffmann, E. Ecological consequences of dredging and bottom trawling in the Limfjord, Denmark. Mar. Ecol. Prog. Ser. Oldendorf 69, 171–178 (1991).
CAS  Article  Google Scholar 

13.
Kaiser, M. J., Ramsay, K., Richardson, C. A., Spence, F. E. & Brand, A. R. Chronic fishing disturbance has changed shelf sea benthic community structure. J. Anim. Ecol. 69, 494–503 (2000).
Article  Google Scholar 

14.
Jennings, S., Dinmore, T. A., Duplisea, D. E., Warr, K. J. & Lancaster, J. E. Trawling disturbance can modify benthic production processes. J. Anim. Ecol. 70, 459–475 (2001).
Article  Google Scholar 

15.
Pipitone, C., Badalamenti, F., D’Anna, G. & Patti, B. Fish biomass increase after a four-year trawl ban in the Gulf of Castellammare (NW Sicily, Mediterranean Sea). Fish. Res. 48, 23–30 (2000).
Article  Google Scholar 

16.
Pranovi, F., Monti, M. A., Caccin, A., Brigolin, D. & Zucchetta, M. Permanent trawl fishery closures in the Mediterranean Sea: an effective management strategy. Mar. Policy 60, 272–279 (2015).
Article  Google Scholar 

17.
Ardron, J., Gjerde, K., Pullen, S. & Tilot, V. Marine spatial planning in the high seas. Mar. Policy 32, 832–839 (2008).
Article  Google Scholar 

18.
Burridge, C. Y., Pitcher, C. R., Hill, B. J., Wassenberg, T. J. & Poiner, I. R. A comparison of demersal communities in an area closed to trawling with those in adjacent areas open to trawling: a study in the Great Barrier Reef Marine Park, Australia. Fish. Res. 79, 64–74 (2006).
Article  Google Scholar 

19.
Buchary, E. A., Cheung, W. L., Sumaila, U. R. & Pitcher, T. J. Back to the future: a paradigm shift for restoring Hong Kong’s marine ecosystem. Am. Fish. Soc. Symp. 38, 727–746 (2003).
Google Scholar 

20.
Cheung, W. W. L. Reconstructed catches in waters administrated by the Hong Kong Special Administrative Region (Fisheries Centre Working Paper #2015-93, University of British Columbia, 2015).

21.
ERM. Fisheries Resource and Fishing Operation in Hong Kong Waters, Final Report. (Agriculture, Fisheries and Conservation Department, 1998).

22.
Morton, B. Protecting Hong Kong’s marine biodiversity: present proposals, future challenges. Environ. Conserv. 23, 55–65 (1996).
Article  Google Scholar 

23.
Leung, K. F. & Morton, B. In Perspectives on Marine Environment Change in Hong Kong and Southern China, 1977–2001 (ed. Morton, B.) (Hong Kong University Press, 2003).

24.
Leung, A. W. Y. In Perspectives on Marine Environment Change in Hong Kong and Southern China, 1977–2001 (ed. Morton, B.) (Hong Kong University Press, 2003).

25.
Agriculture, Fisheries and Conservation Department. Agriculture, Fisheries and Conservation Department Port Survey. https://www.afcd.gov.hk/english/fisheries/fish_cap/fish_cap_latest/fish_cap_latest.html (2006).

26.
Wilson, K. D., Leung, A. W. & Kennish, R. Restoration of Hong Kong fisheries through deployment of artificial reefs in marine protected areas. ICES J. Mar. Sci. 59, 157–163 (2002).
Article  Google Scholar 

27.
Legislative Council of Hong Kong. Legislation Council Brief: A ban on trawling activities in Hong Kong waters (File Ref.: FH CR 1/2576/07). http://www.fhb.gov.hk/download/press_and_publications/otherinfo/101013_f_hkwaters/e_hk_waters.pdf (Food and Health Bureau, 2010).

28.
Wang, Z., Leung, K. M. Y., Li, X., Zhang, T. & Qiu, J. W. Macrobenthic communities in Hong Kong waters: comparison between 2001 and 2012 and potential link to pollution control. Mar. Pollut. Bull. 124, 694–700 (2017).
CAS  Article  Google Scholar 

29.
Shin, P. K. S., Huang, Z. G. & Wu, R. S. S. An updated baseline of subtropical macrobenthic communities in Hong Kong. Mar. Pollut. Bull. 49, 119–141 (2004). [Data source: City U Professional Services Ltd. 2002. Consultancy Study on Marine Benthic Communities in Hong Kong: Final Report, prepared for Agriculture, Fisheries and Conservation Department, the Hong Kong Special Administrative Region Government.].
Article  Google Scholar 

30.
Pitcher, T. J. et al. Marine reserves and the restoration of fisheries and marine ecosystems in the South China Sea. Bull. Mar. Sci. 66, 543–566 (2000).
Google Scholar 

31.
Pitcher, T. J. A cover story: fisheries may drive stocks to extinction. Rev. Fish. Biol. Fish. 8, 367–370 (1998).
Article  Google Scholar 

32.
Pearson, T. H. & Rosenberg, R. Macrobenthic succession in relation to organic enrichment and pollution of the marine environment. Oceanogr. Mar. Biol. Annu. Rev. 16, 229–311 (1978).
Google Scholar 

33.
Kaiser, M. J. et al. Global analysis and prediction of the response of benthic biota and habitats to fishing. Mar. Ecol. Prog. Ser. 311, 1–14 (2006).
Article  Google Scholar 

34.
Jennings, S. & Kaiser, M. J. The effects of fishing on marine ecosystems. Adv. Mar. Biol. 34, 201–352 (1998).
Article  Google Scholar 

35.
Morton, B. The subsidiary impacts of dredging (and trawling) on a subtidal benthic molluscan community in the southern waters of Hong Kong. Mar. Pollut. Bull. 32, 701–710 (1996).
CAS  Article  Google Scholar 

36.
Lindeboom, H. J. & de Groot, S. J. Impact-II: The effects of different types of fisheries on the North Sea and Irish Sea benthic ecosystems. (Netherlands Institute of Sea Research, 1998).

37.
Tao, L. S. R. et al. Trawl ban in a heavily exploited marine environment: responses in population dynamics of four stomatopod species. Sci. Rep. 8, 17876 (2018).
CAS  Article  Google Scholar 

38.
Rijnsdorp, A. D. et al. Towards a framework for the quantitative assessment of trawling impact on the seabed and benthic ecosystem. ICES J. Mar. Sci. 73(suppl_1), i127–i138 (2015).
Article  Google Scholar 

39.
Watling, L., Findlay, R. H., Mayer, L. M. & Schick, D. F. Impact of a scallop drag on the sediment chemistry, microbiota, and faunal assemblages of a shallow subtidal marine benthic community. J. Sea Res. 46, 309–324 (2001).
CAS  Article  Google Scholar 

40.
Wu, R. S. S. Periodic defaunation and recovery in subtropical epibenthic community, in relation to organic pollution. J. Exp. Mar. Biol. Ecol. 64, 253–269 (1982).
Article  Google Scholar 

41.
Dauer, D. M., Ranasinghe, J. A. & Weisberg, S. B. Relationships between benthic community condition, water quality, sediment quality, nutrient loads, and land use patterns in Chesapeake Bay. Estuaries 23, 80–96 (2000).
Article  Google Scholar 

42.
Environmental Protection Department. Marine Water Quality Data. (EPD, 2018).

43.
Cheung, S. G., Lam, N. W. Y., Wu, R. S. S. & Shin, P. K. S. Spatio-temporal changes of marine macrobenthic community in sub-tropical waters upon recovery from eutrophication. II. Life-history traits and feeding guilds of polychaete community. Mar. Pollut. Bull. 56, 297–307 (2008).
CAS  Article  Google Scholar 

44.
Fauchald, K. & Jumars, P. A. The diet of worms: a study of polychaete feeding guilds. Oceanogr. Mar. Biol. Ann. Rev. 17, 193–284 (1979).
Google Scholar 

45.
Macdonald, T. A., Burd, B. J., Macdonald, V. I. & Van Roodselaar, A. Taxonomic and feeding guild classification for the marine benthic macroinvertebrates of the Strait of Georgia, British Columbia. Can. Tech. Rep. Fish. Aquat. Sci. 2874, 1–63 (2010).
Google Scholar 

46.
Jumars, P. A., Dorgan, K. M. & Lindsay, S. M. Diet of worms emended: an update of polychaete feeding guilds. Annu. Rev. Mar. Sci. 7, 497–520 (2015). (2015).
Article  Google Scholar 

47.
WoRMS Editorial Board. World Register of Marine Species. http://www.marinespecies.org (2019).

48.
Pagliosa, P. R. Another diet of worms: the applicability of polychaete feeding guilds as a useful conceptual framework and biological variable. Mar. Ecol. 26, 246–254 (2005).
Article  Google Scholar 

49.
Clarke, K. R. & Warwick, R. M. Change in Marine Communities: An Approach to Statistical Analysis and Interpretation. (Primer-E Ltd, 2001).

50.
Grall, J. & Glémarec, M. Using biotic indices to estimate macrobenthic community perturbations in the Bay of Brest. Estuar. Coast. Shelf Sci. 44, 43–53 (1997).
Article  Google Scholar 

51.
Borja, A., Franco, J. & Pérez, V. A marine biotic index to establish the ecological quality of soft-bottom benthos within European estuarine and coastal environments. Mar. Pollut. Bull. 40, 1100–1114 (2000).
CAS  Article  Google Scholar 

52.
AZTI-Tecnalia. AMBI software. http://ambi.azti.es/descarga-de-ambi/ (2017).

53.
Lê, S., Josse, J. & Husson, F. FactoMineR: an R package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).
Article  Google Scholar 

54.
RStudio Team. RStudio: Integrated Development for R. http://www.rstudio.com/ (2015).

55.
Fox, J. & Weisberg, S. An R Companion to Applied Regression. (Sage, 2011).

56.
Neter, J., Wasserman, W. & Hutner M. H. Applied linear statistical models: Regression, analysis of variance, and experimental design (Irwin, 1990).

57.
Chatterjee, S. & Price, B. Regression Analysis by Example. (John Wiley & Sons, 1991). More

1.
Haynes, G. in Encyclopedia of the Anthropocene (eds. DellaSala, D. & Goldstein, M.) 219–226 (Amsterdam: Elsevier, 2018).
2.
Meltzer, D. J. Pleistocene overkill and North American mammalian extinctions. Annu. Rev. Anthropol. 44, 33–53 (2015).
Article  Google Scholar 

3.
Grayson, D. K. in Quaternary Extinctions: A Prehistoric Revolution (eds. Martin, P. S. & Klein, R. G.) 5–39 (The University of Arizona Press, Tucson, Arizona, 1984).

4.
Turner, G. Memoir on the extraneous fossils, denominated mammoth bones; principally designed to shew that they are the remains of more than one species of non-descript animal. Trans. Am. Philos. Soc. 4, 510–518 (1799).
Article  Google Scholar 

5.
Martin, P. S. in Pleistocene Extinctions: The Search for a Cause (eds. Martin, P. S. & Wright, H. E.) 75–120 (Yale University Press, New Haven, CT, 1967).

6.
Martin, P. S. The discovery of America: the first Americans may have swept the Western Hemisphere and decimated its fauna within 1000 years. Science 179, 969–974 (1973).
ADS  CAS  PubMed  Article  Google Scholar 

7.
Martin, P. S. in Quaternary Extinctions: A Prehistoric Revolution (eds. Martin, P. S. & Klein, R. G.) 354–403 (The University of Arizona Press, Tucson, Arizona, 1984).

8.
Long, A. & Martin, P. S. Death of american ground sloths. Science 186, 638–640 (1974).
ADS  CAS  PubMed  Article  Google Scholar 

9.
Mosimann, J. E. & Martin, P. S. Simulating Overkill by Paleoindians: Did man hunt the giant mammals of the New World to extinction? Mathematical models show that the hypothesis is feasible. Am. Sci. 63, 304–313 (1975).
ADS  Google Scholar 

10.
Diamond, J. M. Quaternary megafaunal extinctions: variations on a theme by paganini. J. Archaeol. Sci. 16, 167–175 (1989).
Article  Google Scholar 

11.
Grayson, D. K. An analysis of the chronology of late Pleistocene mammalian extinctions in North America. Quat. Res. 28, 281–289 (1987).
Article  Google Scholar 

12.
Shapiro, B. et al. Rise and fall of the Beringian steppe bison. Science 306, 1561–1565 (2004).
ADS  CAS  PubMed  Article  Google Scholar 

13.
Hofreiter, M. & Barnes, I. Diversity lost: are all Holarctic large mammal species just relict populations? BMC Biol. 8, 46 (2010).
PubMed  PubMed Central  Article  Google Scholar 

14.
Orlando, L. & Cooper, A. Using ancient DNA to understand evolutionary and ecological processes. Annu. Rev. Ecol. Evol. Syst. 45, 573–598 (2014).
Article  Google Scholar 

15.
Faith, J. T. in Encyclopedia of Global Archaeology (ed. Smith, C.) 5426–5435 (Springer, 2014).

16.
Jackson, S. T. & Weng, C. Late Quaternary extinction of a tree species in eastern North America. Proc. Natl Acad. Sci. USA 96, 13847–13852 (1999).
ADS  CAS  PubMed  Article  Google Scholar 

17.
Guthrie, R. D. Rapid body size decline in Alaskan Pleistocene horses before extinction. Nature 426, 169–171 (2003).
ADS  PubMed  Article  CAS  Google Scholar 

18.
Hill, M. E., Hill, M. G. & Widga, C. C. Late Quaternary Bison diminution on the Great Plains of North America: evaluating the role of human hunting versus climate change. Quat. Sci. Rev. 27, 1752–1771 (2008).
ADS  Article  Google Scholar 

19.
Lyman, R. L. Taphonomy, pathology, and paleoecology of the terminal Pleistocene Marmes Rockshelter (45FR50) “big elk” (Cervus elaphus), southeastern Washington State, USA. Can. J. Earth Sci. 47, 1367–1382 (2010).
Article  Google Scholar 

20.
Lyman, R. L. The Holocene history of bighorn sheep (Ovis canadensis) in eastern Washington state, northwestern USA. Holocene 19, 143–150 (2009).
ADS  Article  Google Scholar 

21.
Grayson, D. K. Deciphering North American pleistocene extinctions. J. Anthropol. Res. 63, 185–213 (2007).
Article  Google Scholar 

22.
Signor, P. W. & Lipps, J. H. in Geological Implications of Impacts of Large Asteroids and Comets on the Earth (eds. Silver, L. T. & Schultz, P. H.) Vol. 190, p. 291–296 (Geological Society of America Boulder, CO, 1982).

23.
Haile, J. et al. Ancient DNA reveals late survival of mammoth and horse in interior Alaska. Proc. Natl Acad. Sci. USA 106, 22352–22357 (2009).
ADS  CAS  PubMed  Article  Google Scholar 

24.
Broughton, J. M. & Weitzel, E. M. Population reconstructions for humans and megafauna suggest mixed causes for North American Pleistocene extinctions. Nat. Commun. 9, 5441 (2018).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

25.
Boulanger, M. T. & Lyman, R. L. Northeastern North American Pleistocene megafauna chronologically overlapped minimally with Paleoindians. Quat. Sci. Rev. 85, 35–46 (2014).
ADS  Article  Google Scholar 

26.
Rick, J. W. Dates as data: an examination of the peruvian preceramic radiocarbon record. Am. Antiq. 52, 55–73 (1987).
Article  Google Scholar 

27.
Mann, D. H. et al. Life and extinction of megafauna in the ice-age Arctic. Proc. Natl Acad. Sci. USA 112, 14301–14306 (2015).
ADS  CAS  PubMed  Article  Google Scholar 

28.
MacDonald, G. M. et al. Pattern of extinction of the woolly mammoth in Beringia. Nat. Commun. 3, 839 (2012).
Article  CAS  Google Scholar 

29.
Pino, M. et al. Sedimentary record from Patagonia, southern Chile supports cosmic-impact triggering of biomass burning, climate change, and megafaunal extinctions at 12.8 ka. Sci. Rep. 9, 4413 (2019).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

30.
Williams, A. N. The use of summed radiocarbon probability distributions in archaeology: a review of methods. J. Archaeol. Sci. 39, 578–589 (2012).
Article  Google Scholar 

31.
Contreras, D. A. & Meadows, J. Summed radiocarbon calibrations as a population proxy: a critical evaluation using a realistic simulation approach. J. Archaeol. Sci. 52, 591–608 (2014).
Article  Google Scholar 

32.
Carleton, W. C. & Groucutt, H. S. Sum things are not what they seem: Problems with point-wise interpretations and quantitative analyses of proxies based on aggregated radiocarbon dates. Holocene 1–14 https://doi.org/10.1177/0959683620981700 (2020).

33.
Ramsey, C. B. Methods for summarizing radiocarbon datasets. Radiocarbon 59, 1809–1833 (2017).
CAS  Article  Google Scholar 

34.
Carleton, W. C. Evaluating Bayesian radiocarbon-dated event-count modelling for the study of long-term human and environmental processes. J. Quat. Sci. 36, 110–123 (2020).

35.
Brown, W. A. The past and future of growth rate estimation in demographic temporal frequency analysis: biodemographic interpretability and the ascendance of dynamic growth models. J. Archaeol. Sci. 80, 96–108 (2017).
Article  Google Scholar 

36.
Wicks, K. & Mithen, S. The impact of the abrupt 8.2 ka cold event on the Mesolithic population of western Scotland: a Bayesian chronological analysis using ‘activity events’ as a population proxy. J. Archaeol. Sci. 45, 240–269 (2014).
Article  Google Scholar 

37.
Lorenzen, E. D. et al. Species-specific responses of Late Quaternary megafauna to climate and humans. Nature 479, 359–364 (2011).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

38.
Price, G. J., Louys, J., Faith, J. T., Lorenzen, E. & Westaway, M. C. Big data little help in megafauna mysteries. Nature 558, 23–25 (2018).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

39.
Surovell, T. A., Finley, J. B., Smith, G. M., Jeffrey Brantingham, P. & Kelly, R. Correcting temporal frequency distributions for taphonomic bias. J. Archaeol. Sci. 36, 1715–1724 (2009).
Article  Google Scholar 

40.
Cooper, A. et al. Abrupt warming events drove Late Pleistocene Holarctic megafaunal turnover. Science 349, 602–606 (2015).
ADS  CAS  PubMed  Article  Google Scholar 

41.
Metcalf, J. L. et al. Synergistic roles of climate warming and human occupation in Patagonian megafaunal extinctions during the Last Deglaciation. Sci. Adv. 2, e1501682 (2016).
ADS  PubMed  PubMed Central  Article  Google Scholar 

42.
Boers, N., Goswami, B. & Ghil, M. A complete representation of uncertainties in layer-counted paleoclimatic archives. Climate 13, 1169–1180 (2017).
Google Scholar 

43.
Andersen, K. K. et al. High-resolution record of Northern Hemisphere climate extending into the last interglacial period. Nature 431, 147–151 (2004).
ADS  CAS  PubMed  Article  Google Scholar 

44.
Clark, P. U. et al. The last glacial maximum. Science 325, 710–714 (2009).
ADS  CAS  PubMed  Article  Google Scholar 

45.
Meltzer, D. J. & Mead, J. I. The timing of late pleistocene mammalian extinctions in North America. Quat. Res. 19, 130–135 (1983).
Article  Google Scholar 

46.
Owen-Smith, N. Pleistocene extinctions: the pivotal role of megaherbivores. Paleobiology 13, 351–362 (1987).
Article  Google Scholar 

47.
Zimov, S. A. et al. Steppe-tundra transition: a herbivore-driven biome shift at the end of the Pleistocene. Am. Nat. 146, 765–794 (1995).
Article  Google Scholar 

48.
Bakker, E. S. et al. Combining paleo-data and modern exclosure experiments to assess the impact of megafauna extinctions on woody vegetation. Proc. Natl Acad. Sci. USA 113, 847–855 (2016).
ADS  CAS  PubMed  Article  Google Scholar 

49.
Forbes, E. S. et al. Synthesizing the effects of large, wild herbivore exclusion on ecosystem function. Funct. Ecol. 33, 1597–1610 (2019).
Article  Google Scholar 

50.
Ripple, W. J. & Van Valkenburgh, B. Linking top-down forces to the pleistocene megafaunal extinctions. BioScience 60, 516–526 (2010).
Article  Google Scholar 

51.
VanValkenburgh, B. & Hertel, F. Tough times at la brea: tooth breakage in large carnivores of the late pleistocene. Science 261, 456–459 (1993).
ADS  CAS  PubMed  Article  Google Scholar 

52.
Koch, P. L. & Barnosky, A. D. Late quaternary extinctions: state of the debate. Annu. Rev. Ecol. Evol. Syst. 37, 215–250 (2006).
Article  Google Scholar 

53.
Haynes, G. Extinctions in North America’s Late Glacial landscapes. Quat. Int. 285, 89–98 (2013).
Article  Google Scholar 

54.
Berti, E. & Svenning, J. Megafauna extinctions have reduced biotic connectivity worldwide. Glob. Ecol. Biogeogr. 373, 20170008 (2020).
Google Scholar 

55.
Faith, J. T. & Surovell, T. A. Synchronous extinction of North America’s Pleistocene mammals. Proc. Natl Acad. Sci. USA 106, 20641–20645 (2009).
ADS  CAS  PubMed  Article  Google Scholar 

56.
Robinson, G. S., Burney, L. P. & Burney, D. A. Landscape paleoecology and megafaunal extinction in southeastern New York State. Ecol. Monogr. 75, 295–315 (2005).
Article  Google Scholar 

57.
Gill, J. L., Williams, J. W., Jackson, S. T., Lininger, K. B. & Robinson, G. S. Pleistocene megafaunal collapse, novel plant communities, and enhanced fire regimes in North America. Science 326, 1100–1103 (2009).
ADS  CAS  PubMed  Article  Google Scholar 

58.
Meltzer, D. J. & Holliday, V. T. Would North American paleoindians have noticed younger dryas age climate changes? J. World Prehistory 23, 1–41 (2010).
Article  Google Scholar 

59.
Shuman, B., Webb, T., Bartlein, P. & Williams, J. W. The anatomy of a climatic oscillation: vegetation change in eastern North America during the Younger Dryas chronozone. Quat. Sci. Rev. 21, 1777–1791 (2002).
ADS  Article  Google Scholar 

60.
Monnin, E. et al. Atmospheric CO2 concentrations over the last glacial termination. Science 291, 112–114 (2001).
ADS  CAS  PubMed  Article  Google Scholar 

61.
Williams, J. W., Shuman, B. N. & Webb, T. III Dissimilarity analyses of Late-Quaternary vegetation and climate in eastern North America. Ecology 82, 3346–3362 (2001).
Google Scholar 

62.
Yu, Z. Rapid response of forested vegetation to multiple climatic oscillations during the last deglaciation in the northeastern United States. Quat. Res. 67, 297–303 (2007).
Article  Google Scholar 

63.
Wolverton, S., Lee Lyman, R., Kennedy, J. H. & La Point, T. W. The terminal pleistocene extinctions in North America, hypermorphic evolution, and the dynamic equilibrium model. J. Ethnobiol. 29, 28–63 (2009).
Article  Google Scholar 

64.
Guthrie, R. D. in Quaternary Extinctions: A Prehistoric Revolution (eds. Martin, P. S. & Klein, R. G.) 259–298 (The University of Arizona Press, Tucson, Arizona, 1984).

65.
Faith, J. T. Late Pleistocene climate change, nutrient cycling, and the megafaunal extinctions in North America. Quat. Sci. Rev. 30, 1675–1680 (2011).
ADS  Article  Google Scholar 

66.
Haynes, C. V. Younger Dryas “black mats” and the Rancholabrean termination in North America. Proc. Natl Acad. Sci. USA 105, 6520–6525 (2008).
ADS  CAS  PubMed  Article  Google Scholar 

67.
Seersholm, F. V. et al. Rapid range shifts and megafaunal extinctions associated with late Pleistocene climate change. Nat. Commun. 11, 2770 (2020).

68.
Firestone, R. B. et al. Evidence for an extraterrestrial impact 12,900 years ago that contributed to the megafaunal extinctions and the Younger Dryas cooling. Proc. Natl Acad. Sci. USA 104, 16016–16021 (2007).
ADS  CAS  PubMed  Article  Google Scholar 

69.
Holliday, V. T. & Meltzer, D. J. The 12.9-ka ET impact hypothesis and North American Paleoindians. Curr. Anthropol. 51, 575–607 (2010).
Article  Google Scholar 

70.
Graham, R. W. & Lundelius, E. L. in Quaternary Extinctions: A Prehistoric Revolution (eds. Martin, P. S. & Klein, R. G.) 223–249 (The University of Arizona Press, Tucson, Arizona, 1984).

71.
Yu, Z. & Wright, H. E. Response of interior North America to abrupt climate oscillations in the North Atlantic region during the last deglaciation. Earth Sci. Rev. 52, 333–369 (2001).
ADS  CAS  Article  Google Scholar 

72.
Gill, J. L., Williams, J. W., Jackson, S. T., Donnelly, J. P. & Schellinger, G. C. Climatic and megaherbivory controls on late-glacial vegetation dynamics: a new, high-resolution, multi-proxy record from Silver Lake, Ohio. Quat. Sci. Rev. 34, 66–80 (2012).
ADS  Article  Google Scholar 

73.
Yansa, C. H. & Adams, K. M. Mastodons and mammoths in the great lakes region, USA and Canada: new insights into their diets as they neared extinction. Geogr. Compass 6, 175–188 (2012).
Article  Google Scholar 

74.
Asmerom, Y., Polyak, V. J. & Burns, S. J. Variable winter moisture in the southwestern United States linked to rapid glacial climate shifts. Nat. Geosci. 3, 114–117 (2010).
ADS  CAS  Article  Google Scholar 

75.
Wagner, J. D. M. et al. Moisture variability in the southwestern United States linked to abrupt glacial climate change. Nat. Geosci. 3, 110–113 (2010).
ADS  CAS  Article  Google Scholar 

76.
Kirby, M. E., Feakins, S. J., Bonuso, N., Fantozzi, J. M. & Hiner, C. A. Latest pleistocene to holocene hydroclimates from Lake Elsinore, California. Quat. Sci. Rev. 76, 1–15 (2013).
ADS  Article  Google Scholar 

77.
Polyak, V. J., Asmerom, Y., Burns, S. J. & Lachniet, M. S. Climatic backdrop to the terminal Pleistocene extinction of North American mammals. Geology 40, 1023–1026 (2012).
ADS  Article  Google Scholar 

78.
MacDonald, G. M. et al. Evidence of temperature depression and hydrological variations in the eastern Sierra Nevada during the Younger Dryas Stade. Quat. Res. 70, 131–140 (2008).
Article  Google Scholar 

79.
Polyak, V. J., Rasmussen, J. B. T. & Asmerom, Y. Prolonged wet period in the southwestern United States through the Younger Dryas. Geology 32, 5 (2004).
ADS  CAS  Article  Google Scholar 

80.
Holliday, V. T. Folsom Drought and episodic drying on the southern high plains from 10,900–10,200 14C yr B.P. Quat. Res. 53, 1–12 (2000).
Article  Google Scholar 

81.
Ballenger, J. A. M. et al. Evidence for Younger Dryas global climate oscillation and human response in the American Southwest. Quat. Int. 242, 502–519 (2011).
Article  Google Scholar 

82.
Heusser, L. E., Kirby, M. E. & Nichols, J. E. Pollen-based evidence of extreme drought during the last Glacial (32.6–9.0 ka) in coastal southern California. Quat. Sci. Rev. 126, 242–253 (2015).
ADS  Article  Google Scholar 

83.
Holmgren, C. A., Betancourt, J. L. & Rylander, K. A. A 36,000-yr vegetation history from the Peloncillo Mountains, southeastern Arizona, USA. Palaeogeogr. Palaeoclimatol. Palaeoecol. 240, 405–422 (2006).
Article  Google Scholar 

84.
Van Devender, T. R. & Spaulding, W. G. Development of vegetation and climate in the Southwestern United States. Science 204, 701–710 (1979).
ADS  PubMed  Article  Google Scholar 

85.
Marcus, L. F. & Berger, R. in Quaternary Extinctions: A Prehistoric Revolution (eds. Martin, P. S. & Klein, R. G.) 159–183 (The University of Arizona Press, Tucson, Arizona, 1984).

86.
Friscia, A. R., Van Valkenburgh, B., Spencer, L. & Harris, J. Chronology and spatial distribution of large mammal bones in Pit 91, Rancho La Brea. Palaios 23, 25–42 (2008).
ADS  Article  Google Scholar 

87.
Shackleton, N. J., Hall, M. A. & Vincent, E. Phase relationships between millennial-scale events 64,000–24,000 years ago. Paleoceanography 15, 565–569 (2000).
ADS  Article  Google Scholar 

88.
Affolter, S. et al. Central Europe temperature constrained by speleothem fluid inclusion water isotopes over the past 14,000 years. Sci. Adv. 5, eaav3809 (2019).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

89.
RStudio Team. RStudio: Integrated Development for R. (RStudio, PBC, Boston, MA, 2020).

90.
NIMBLE Development Team. NIMBLE: MCMC, Particle Filtering, and Programmable Hierarchical Modeling (2020).

91.
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (2016).

92.
Kassambara, A. ggpubr: “ggplot2” Based Publication Ready Plots (2020). More