Ecology

1.
van Mantgem PJ, Stephenson NL, Byrne JC, Daniels LD, Franklin JF, Fule PZ, et al. Widespread increase of tree mortality rates in the western United States. Science. 2009;323:521–4.
PubMed  Article  CAS  PubMed Central  Google Scholar 
2.
Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag. 2010;259:660–84.
Article  Google Scholar 

3.
Carnicer J, Coll M, Ninyerola M, Pons X, Sanchez G, Penuelas J. Widespread crown condition decline, food web disruption, and amplified tree mortality with increased climate change-type drought. Proc Natl Acad Sci USA. 2011;108:1474–8.
CAS  PubMed  Article  PubMed Central  Google Scholar 

4.
Brown N, Vanguelova E, Parnell S, Broadmeadow S, Denman S. Predisposition of forests to biotic disturbance: predicting the distribution of Acute Oak Decline using environmental factors. For Ecol Manag. 2018;407:145–54.
Article  Google Scholar 

5.
Denman S, Doonan J, Ransom-Jones E, Broberg M, Plummer S, Kirk S, et al. Microbiome and infectivity studies reveal complex polyspecies tree disease in Acute Oak Decline. ISME J. 2017. https://doi.org/10.1038/ismej.2017.170.

6.
Denman S, Barrett G, Kirk SA, McDonald JE, Coetzee MPA. Identification of Armillaria species on oak in Britain: implications for Oak Health. Forestry. 2017;90:148–61.
Article  Google Scholar 

7.
Martınez-Vilalta J, Lloret F, Breshears DD. Drought-induced forest decline: causes, scope and implications. Biol Lett. 2012;8:689–91.
PubMed  Article  PubMed Central  Google Scholar 

8.
McDowell NG, Ryan MG, Zeppel MJB, Tissue DT. Improving our knowledge of drought-induced forest mortality through experiments, observations, and modeling. N. Phytologist. 2013;200:289–93.
Article  Google Scholar 

9.
Thomas FM, Blank R, Hartmann G. Abiotic and biotic factors and their interactions as causes of oak decline in central Europe. Pathol. 2002;32:277–307.
Article  Google Scholar 

10.
Niinemets Ü. Responses of forest trees to single and multiple environmental stresses from seedlings to mature plants: past stress history, stress interactions, tolerance and acclimation. Ecol Manag. 2010;260:1623–39.
Article  Google Scholar 

11.
Amoroso MM, Daniels LD, Larson BC. Temporal patterns of radial growth in declining Austrocedrus chilensis forests in Northern Patagonia: the use of treerings as an indicator of forest decline. Ecol Manag. 2012;265:62–70.
Article  Google Scholar 

12.
Bansal S, Hallsby G, Löfvenius MO, Nilsson MC. Synergistic, additive and antagonistic impacts of drought on herbivory on Pinus sylvestris: leaf, tissue and whole-plant responses and recovery. Tree Physiol. 2013;33:451–63.
CAS  PubMed  Article  Google Scholar 

13.
Whyte G, Howard K, Hardy GEStJ, Burgess T. The Tree Decline Recovery Seesaw; a conceptual model of the decline and recovery of drought stressed plantation trees. For Ecol Manag. 2016;370:102–13.
Article  Google Scholar 

14.
Calder JA, Kirkpatrick JB. Climate change and other factors influencing the decline of the Tasmanian cider gum (Eucalyptus gunnii). Australian J Botany. 2008;56. https://doi.org/10.1071/BT08105.

15.
Avila JM, Gallardo A, Ibáñez B, Gómez‐Aparicio L. Quercus suber dieback alters soil respiration and nutrient availability in Mediterranean forests. J Ecol. 2016;104:1441–52.
Article  Google Scholar 

16.
Crawford N. Nitrate: nutrient and signal for plant growth. Plant Cell. 1995;7:859–68.
CAS  PubMed  PubMed Central  Google Scholar 

17.
Lovett GM, Arthur MA, Weathers KC, Griffin JM. Long-term changes in forest carbon and nitrogen cycling caused by an introduced pest/pathogen complex. Ecosystems. 2010;13:1188–1200.
CAS  Article  Google Scholar 

18.
Throop H, Lerdau MT. Effects of nitrogen deposition on insect herbivory: Implications for community and ecosystem processes. Ecosystems. 2004;7:109–33.
CAS  Article  Google Scholar 

19.
Thomas FM, Ahlers U. Effects of excess nitrogen on frost hardiness and freezing injury of above-ground tissue in young oaks (Quercus petraea and Q. robur). N. Phytologist. 1999;144:73–83.
Article  Google Scholar 

20.
Hardham AR. The cell biology behind Phytophthora pathogenicity. Australas Plant Pathol. 2001;30:91–98.
Article  Google Scholar 

21.
Brown N, Jeger M, Kirk S, Xu X, Denman S. Spatial and temporal patterns in symptom expression within eight woodlands affected by acute Oak Decline. For Ecol Manag. 2016;360:97–109.
Article  Google Scholar 

22.
Scarlett K, Guest DI, Daniel R. Elevated soil nitrogen increases the severity of dieback due to Phytophthora cinnamomi. Australas Plant Pathol. 2013;42:155–62.
Article  Google Scholar 

23.
Yao H, Bowman D, Shi W. Seasonal variations in soil microbial biomass and activity in warm and cool season turfgrass systems. Soil Biol Biochem. 2011;43:1536–43.
CAS  Article  Google Scholar 

24.
Prosser JI, Nicol GW. Relative contributions of archaea and bacteria to aerobic ammonia oxidation in the environment. Environ Microbiol. 2008;10:2931–41.
CAS  PubMed  Article  Google Scholar 

25.
Prosser JI, Nicol GW. Archaeal and bacterial ammonia oxidisers in soil: the quest for niche specialisation and differentiation. Trends Microbiol. 2012;20:523–31.
CAS  PubMed  Article  Google Scholar 

26.
Erguder TH, Boon N, Wittebolle L, Marzorati M, Verstraete W. Environmental factors shaping the ecological niches of ammonia‐oxidizing archaea. FEMS Microbiol Rev. 2009;33:855–69.
CAS  PubMed  Article  Google Scholar 

27.
Hink L, Lycus P, Gubry-Rangin C, Frostgard A, Nicol GW, Prosser JI, et al. Kinetics of NH3‐oxidation, NO‐turnover, N2O‐production and electron flow during oxygen depletion in model bacterial and archaeal ammonia oxidisers. Environ Microbiol. 2017;19:4882–96.
CAS  PubMed  Article  Google Scholar 

28.
Gubry-Rangin C, Hai B, Quince C, Engel M, Thomson BC, James P, et al. Niche specialization of terrestrial archaeal ammonia oxidisers. Proc Natl Acad Sci. 2011;108:21206–11.
CAS  PubMed  Article  Google Scholar 

29.
Leininger S, Schloter UT, Schwark I, Qi J, Nicol GW, Prosser JI, et al. Archaea predominate among ammonia-oxidizing prokaryotes in soils. Nature. 2006;442:806–9.
CAS  PubMed  Article  Google Scholar 

30.
Gubry-Rangin C, Nicol GW, Prosser JI. Archaea rather than bacterial control nitrification in two agricultural acidic soils. FEMS Microbiol Ecol. 2010;74:566–74.
CAS  PubMed  Article  PubMed Central  Google Scholar 

31.
Verhamme DT, Prosser JI, Nicol GW. Ammonia concentration determines differential growth of ammonia oxidizing archaeal and bacteria in soil microcosms. ISME J. 2011;5:1067–71.
CAS  PubMed  PubMed Central  Article  Google Scholar 

32.
Di HJ, Cameron KC, Shen J-P, Winefield CS, O’Callaghan M, Bowatte S, et al. Ammonia-oxidizing bacteria and archaea grow under contrasting soil nitrogen conditions. FEMS Microbiol Ecol. 2010;72:386–94.
CAS  PubMed  Article  PubMed Central  Google Scholar 

33.
Hink L, Gubry-Rangin C, Nicol GW, Prosser J. The consequences of niche and physiological differentiation of archaeal and bacterial ammonia oxidisers for nitrous oxide emissions. ISME J. 2018;12:1084–93.
CAS  PubMed  PubMed Central  Article  Google Scholar 

34.
Clark D, McKew B, Dong L, Leung G, Dumbrell AJ, Stott A, et al. Mineralization and nitrification: archaea dominate ammonia-oxidising communities in grassland soils. Soil Biol Biochem. 2020;143:107725.
CAS  Article  Google Scholar 

35.
Delgado-Baquerizo M, Maestre FT, Eldridge DJ, Singh BK. Microsite differentiation drives the abundance of soil ammonia oxidizing bacteria along aridity gradients. Front Microbiol. 2016;7:505.
PubMed  PubMed Central  Article  Google Scholar 

36.
Martens-Habbena W, Berube PM, Urakawa H, de la Torre JR, Stahl DA. Ammonia oxidation kinetics determine niche separation of nitrifying Archaea and Bacteria. Nature. 2009;461:976–9.
CAS  PubMed  Article  PubMed Central  Google Scholar 

37.
Barta J, Tahovska K, Santruckova H, Oulehle F. Microbial communities with distinct denitrification potential in spruce and beech soils differing in nitrate leaching. Sci Rep Nat. 2017;7:9738.
Article  CAS  Google Scholar 

38.
Fierer N, Lauber CL, Ramirez KS, Zaneveld J, Bradford MA, Knight R. Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients. ISME J. 2012;6:1007–17. https://doi.org/10.1038/ismej.2011.159.
CAS  Article  PubMed  Google Scholar 

39.
Ramirez KS, Lauber CL, Knight R, Bradford MA, Fierer N. Consistent effects of nitrogen fertilization on soil bacterial communities in contrasting systems. Ecology. 2010;91:3463–70. https://doi.org/10.1890/10-0426.1.
Article  PubMed  PubMed Central  Google Scholar 

40.
Cranfield University 2020. The Soils Guide. www.landis.org.uk. UK; Cranfield University.

41.
G Kerr, J Haufe. Thinning practice. A Silvicultural Guide. Bristol: Forestry Commission; 2011;1:54.

42.
Cools N, De Vos B Sampling and Analysis of Soil. In: Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Hamburg: UNECE, ICP Forests; 2010, pp. 208.

43.
MAFF. Code of good agricultural practice for the protection of soil. London, UK: Ministry of Agriculture, Fisheries and Food; 1993.
Google Scholar 

44.
Li J, Nedwell DB, Beddow J, Dumbrell AJ, McKew BA, Thorpe EL, et al. amoA gene abundances and nitrification potential rates suggest that benthic ammonia-oxidizing bacteria (AOB) not archaea (AOA) dominate N cycling in the Colne estuary, UK. Appl Environ Microbiol. 2015;81:159–65.
PubMed  Article  CAS  Google Scholar 

45.
Beddow J, Stolpe B, Cole PA, Lead JR, Sapp M, Lyons BP, et al. Nanosilver inhibits nitrification and reduces ammonia-oxidizing bacterial but not archaeal amoA gene abundance in estuarine sediments. Environ Microbiol. 2017;19:500–10.
CAS  PubMed  Article  Google Scholar 

46.
Tourna M, Freitag TE, Nicol GW, Prosser JI. Growth, activity and temperature responses of ammonia-oxidizing archaea and bacteria in soil microcosms. Environ Microbiol. 2008;10:1357–64.
CAS  PubMed  Article  Google Scholar 

47.
Rotthauwe JH, Witzel KP, Liesack W. The ammonia monooxygenase structural gene amoA as a functional marker: molecular fine-scale analysis of natural ammonia-oxidizing populations. Appl Environ Microbiol. 1997;63:4704–12.
CAS  PubMed  PubMed Central  Article  Google Scholar 

48.
Throbäck IN, Enwall K, Jarvis A, Hallin S. Reassessing PCR primers targeting nirS, nirK and nosZ genes for community surveys of denitrifying bacteria with DGGE. FEMS Microbiol Ecol. 2004;49:401–17.
PubMed  Article  CAS  Google Scholar 

49.
Braker G, Fesefeldt A, Witzel KP. Development of PCR primer systems for amplification of nitrite reductase genes (nirK and nirS) to detect denitrifying bacteria in environmental samples. Appl Environ Microbiol. 1998;64:3769–75.
CAS  PubMed  PubMed Central  Article  Google Scholar 

50.
Henry S, Bru D, Stres B, Hallet S, Philippot L. Quantitative detection of the nosZ gene, encoding nitrous oxide reductase, and comparison of the abundances of 16S rRNA, narG, nirK, and nosZ Genes in Soils. Appl Environ Microbiol. 2006;72:5181–9.
CAS  PubMed  PubMed Central  Article  Google Scholar 

51.
Herlemann D, Labrenz M, Jürgens K, Bertilsson S, Waniek J, Andersson A. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 2011;5:1571–9.
CAS  PubMed  PubMed Central  Article  Google Scholar 

52.
Raskin L, Stromley JM, Rittmann BE, Stahl DA. Group-specific 16S rRNA hybridization probes to describe natural communities of methanogens. Appl Environ Microbiol. 1994;60:1232–40.
CAS  PubMed  PubMed Central  Article  Google Scholar 

53.
Stahl DA, Amann R Development and application of nucleic acid probes. In: Nucleic acid techniques in bacterial systematics. Stackebrandt, E, Goodfellow M, editors. Chichester, UK: John Wiley & Sons Ltd; 1991. pp. 205–48.

54.
Dumbrell AJ, Ferguson RMW, Clark DR. Microbial community analysis by single-amplicon high-throughput next generation sequencing: Data analysis—from raw output to ecology. In: McGenity T, Timmis K, Nogales B, editors. Hydrocarbon and Lipid Microbiology Protocols. Berlin, Heidelberg: Springer Protocols Handbooks. Springer; 2016. 155–206.

55.
Joshi NA, Fass JN Sickle: A Sliding-Window, Adaptive, Quality-Based Trimming Tool for FastQ Files 2011; (Version 1.33).

56.
Nurk S, Bankevich A, Antipov D, Gurevich AA, Korobeynikov A, Lapidus A, et al. Assembling single-cell genomes and mini-metagenomes from chimeric MDA products. J Comput Biol. 2013;20:714–37.
CAS  PubMed  PubMed Central  Article  Google Scholar 

57.
Nikolenko SI, Korobeynikov AI, Alekseyev MA. BayesHammer: Bayesian clustering for error correction in single-cell sequencing. BMC Genomics SP. 2013;14:S7.
Article  Google Scholar 

58.
Rognes T, Flouri T, Nichols B, Quince C, Mahé F VSEARCH: a versatile open source tool for metagenomics. PeerJ. 2016;4. https://doi.org/10.7717/peerj.2584.

59.
Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics. 2011;16:2194–200.
Article  CAS  Google Scholar 

60.
Wang Q, Quensen JF, Fish JA, Lee TK, Sun Y, Tiedje JM, et al. Ecological patterns of nifH genes in four terrestrial climatic zones explored with targeted metagenomics using FrameBot, a new informatics tool. MBio. 2013;4:e00592–13.
PubMed  PubMed Central  Google Scholar 

61.
Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007;16:5261–7.
Article  CAS  Google Scholar 

62.
Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;5:1792–7.
Article  CAS  Google Scholar 

63.
Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol. 2013;12:2725–9.
Article  CAS  Google Scholar 

64.
Fish J, Chai B, Wang Q, Sun Y, Brown CT, Tiedje JM, et al. FunGene: the functional gene pipeline and repository. Front Microbiol. 2013;4:291.
PubMed  PubMed Central  Article  Google Scholar 

65.
Altschul S, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25:3389–402.
CAS  PubMed  PubMed Central  Article  Google Scholar 

66.
Lefcheck J. PIECEWISESEM: Piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol Evol. 2016;7:573–9.
Article  Google Scholar 

67.
Shipley B. A new inferential test for path models based on directed acyclic graphs. Struct Equ Modeling. 2000;7:206–18.
Article  Google Scholar 

68.
Grace JB. Structural Equation Modelling and Natural Systems. New York, NY: Cambridge University Press; 2006.
Google Scholar 

69.
Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. Vegan: Community Ecology Package. R package Version. 2017;2:4–3.
Google Scholar 

70.
Leininger Wang Y, Naumann U, Wright S, Warton D. Mvabund—an R package for model‐based analysis of multivariate abundance data. Methods Ecol Evolution. 2012;3:471–4.
Article  Google Scholar 

71.
Lehtovirta-Morley LE, Stoecker K, Vilcinskas A, Prosser JI, Nicol GW. Cultivation of an obligate acidophilic ammonia oxidizer from a nitrifying acid soil. Proc Natl Acad Sci USA. 2011;108:15892–7.
CAS  PubMed  Article  PubMed Central  Google Scholar 

72.
Hu H, Zhang L, Dai Y, et al. pH-dependent distribution of soil ammonia oxidizers across a large geographical scale as revealed by high-throughput pyrosequencing. J Soils Sediment. 2013;13:1439–49.
Article  CAS  Google Scholar 

73.
Hu BL, Liu S, Wang W, Shen LD, Lou LP, Liu WP, et al. pH-dominated niche segregation of ammonia-oxidising microorganisms in Chinese agricultural soils. FEMS Microbiol Ecol. 2014;90:290–9. https://doi.org/10.1111/1574-6941.12391.
CAS  Article  Google Scholar 

74.
Hu H, Zhang L, Yuan C, Zheng Y, Wang J, Chen D, et al. The large-scale distribution of ammonia oxidizers in paddy soils is driven by soil pH, geographic distance, and climatic factors. Front Microbiol. 2015;6:938.
PubMed  PubMed Central  Google Scholar 

75.
Delgado-Baquerizo M, Gallardo A, Wallenstein MD, Maestre FT. Vascular plants mediate the effects of aridity and soil properties on ammonia-oxidizing bacteria and archaea. FEMS Microbiol Ecol. 2013;13:273–82.
Article  CAS  Google Scholar 

76.
Eldridge DJ, Beecham G, Grace J. Do shrubs reduce the adverse effects of grazing on soil properties? Ecohydrology. 2015;8:1503–13.
Article  Google Scholar 

77.
Berdugo M, Soliveres S, Maestre FT. Vascular plants and biocrusts modulate how abiotic factors affect wetting and drying events in drylands. Ecosystems. 2014;17:1242–56.
CAS  Article  Google Scholar 

78.
Köhler S, Levia DF, Jungkunst HF, Gerold G. An In Situ Method to Measure and Map Bark pH. J Wood Chem Technol. 2015;35:438–49.
Article  CAS  Google Scholar 

79.
Matschonat G, Falkengren-Grerup U. Recovery of soil pH, Cation-exchange Capacity and the Saturation of Exchange Sites from Stemflow-induced Soil Acidification in Three Swedish Beech (Fagus sylvatica L.) Forests. Scand J For Res. 2000;15:39–48.
Article  Google Scholar 

80.
Wang Y, Uchida Y, Shimomura U, Akiyama H, Hayatsu M. Responses of denitrifying bacterial communities to short-term waterlogging of soils. Sci Rep. 2017;7:803.
PubMed  PubMed Central  Article  CAS  Google Scholar 

81.
Liu J, Yu Z, Yao Q, Sui Y, Shi Y, Chu H, et al. Ammonia-oxidizing Archaea show more distinct biogeographic distribution patterns than ammonia-oxidizing bacteria across the black soil zone of Northeast China. Front Microbiol. 2018;9:171.
PubMed  PubMed Central  Article  Google Scholar 

82.
Shen C, Xiong J, Zhang H, Feng Y, Lin X, Li X, et al. Soil pH drives the spatial distribution of bacterial communities along elevation on Changbai Mountain. Soil Biol Biochem. 2013;57:204–11.
CAS  Article  Google Scholar 

83.
Nicol GW, Leininger S, Schleper C, Prosser JI. The influence of soil pH on the diversity, abundance and transcriptional activity of ammonia oxidizing archaea and bacteria. Environ Microbiol. 2008;10:2966–78.
CAS  PubMed  Article  Google Scholar 

84.
Rousk J, Baath E, Brookes PC, Lauber CL, Lozupone C, Caporaso JG, et al. Soil bacterial and fungal communities across a pH gradient in an arable soil. ISME J. 2010;4:1340–51.
PubMed  Article  Google Scholar 

85.
Yuan YL, Si GC, Wang J, Luo TX, Zhang GX. Bacterial community in alpine grasslands along an altitudinal gradient on the Tibetan Plateau. FEMS Microbiol Ecol. 2014;87:121–32.
CAS  PubMed  Article  Google Scholar 

86.
Kaiser k, Wemheuer B, Korolkow V, Wemheuer F, Nacke H, Schöning I, et al. Driving forces of soil bacterial community structure, diversity, and function in temperate grasslands and forests. Sci Rep. 2017;7:9738.
Article  CAS  Google Scholar 

87.
Meaden S, Metcalf CJE, Koskella B. The effects of host age and spatial location on bacterial community composition in the English Oak tree (Quercus robur). Environ Microbiol Rep. 2016;8:649–58.
CAS  PubMed  Article  Google Scholar 

88.
Patra AK, Abbadie L, Clays-Josserand A, Degrange V, Grayston SJ, Guillaumaud N, et al. Effects of management regime and plant species on the enzyme activity and genetic structure of N-fixing, denitrifying and nitrifying bacterial communities in grassland soils. Environ Microbiol. 2006;8:1005–16.
CAS  PubMed  Article  Google Scholar 

89.
Bremer C, Braker G, Matthies D, Beierkuhnlein C, Conrad R. Plant presence and species combination, but not diversity, influence denitrifier activity and the composition of nirK-type denitrifier communities in grassland soil. FEMS Microbiol Ecol. 2009;70:377–87.
CAS  PubMed  Article  Google Scholar  More

1.
Hamilton, W. D. The genetic theory of social behaviour I and II. J. Theor. Biol. 7, 1–52 (1964).
CAS  PubMed  Article  Google Scholar 
2.
Ward, A., & Webster, M. Sociality: the behaviour of group-living animals (Springer,2016).

3.
Lehmann, L., & Keller, L. The evolution of cooperation and altruism. A general framework and classification of models. J. Evol. Biol.19, 1365–1378 (2006).

4.
Sueur, C. et al. Collective decision-making and fission–fusion dynamics: a conceptual framework. Oikos 120, 1608–1617 (2011).
Article  Google Scholar 

5.
Jones, T. B. et al. Consistent sociality but flexible social associations across temporal and spatial foraging contexts in a colonial breeder. Ecol. Lett. https://doi.org/10.1111/ele.13507 (2020).
Article  PubMed  Google Scholar 

6.
Carter, G. G. & Wilkinson, G. S. Food sharing in vampire bats: reciprocal help predicts donations more than relatedness or harassment. Proc. R. Soc. B. 280, 20122573. https://doi.org/10.1098/rspb.2012.2573 (2013).
Article  PubMed  Google Scholar 

7.
Baglione, V., Canestrari, D., Marcos, J. M. & Ekman, J. Kin selection in cooperative alliances of carrion crows. Science 300, 1947–1949 (2003).
ADS  CAS  PubMed  Article  Google Scholar 

8.
Wahaj, S. A. et al. Kin discrimination in the spotted hyena (Crocuta crocuta): nepotism among siblings. Behav. Ecol. Sociobiol. 56, 237–247 (2004).
Article  Google Scholar 

9.
East, M. L. et al. Maternal effects on offspring social status in spotted hyenas. Behav. Ecol. 20, 478–483 (2009).
Article  Google Scholar 

10.
Komdeur, J., Burke, T., Dugdale, H.L., & Richardson, D.S. Seychelles warblers: Complexities of the helping paradox in Cooperative breeding in vertebrates: studies of ecology, evolution and behavior (ed. Koenig, W. D. & Dickinson, J. L.) 197–216 (Cambridge University Press, 2016).

11.
Krakauer, A. H. Kin selection and cooperative courtship in wild turkeys. Nature 434, 69–72 (2005).
ADS  CAS  PubMed  Article  Google Scholar 

12.
De Moor, D., Roos, C., Ostner, J. & Schülke, O. Bonds of bros and brothers: kinship and social bonding in post-dispersal male macaques. Mol. Ecol. https://doi.org/10.1111/mec.15560 (2020).
Article  PubMed  Google Scholar 

13.
Koykka, C. & Wild, W. Concessions, lifetime fitness consequences, and the evolution of coalitionary behaviour. Behav. Ecol. 28, 20–30 (2016).
Article  Google Scholar 

14.
Clutton-Brock, T. Cooperation between non-kin in animal societies. Nature 46, 51–57 (2009).
ADS  Article  CAS  Google Scholar 

15.
Schaller, G.B. The Serengeti Lion: a study of predator-prey relations. (University of Chicago Press, 1972).

16.
Bertram, B. C. Social factors influencing reproduction in wild lions. J. Zool. 177, 463–482 (1975).
Article  Google Scholar 

17.
Bygott, J. D., Bertram, B. C. & Hanby, J. P. Male lions in large coalitions gain reproductive advantages. Nature 282, 839 (1979).
ADS  Article  Google Scholar 

18.
Packer, C. & Pusey, A. E. Cooperation and competition within coalitions of male lions: Kin selection or game theory?. Nature 296, 740 (1982).
ADS  Article  Google Scholar 

19.
Grinnell, J., Packer, C. & Pusey, A. E. Cooperation in male lions: kinship, reciprocity or mutualism?. Anim. Behav. 49, 95–105 (1995).
Article  Google Scholar 

20.
Chakrabarti, S. & Jhala, Y. V. Selfish partners: resource partitioning in male coalitions of Asiatic lions. Behav. Ecol. 28, 1532–1539 (2017).
PubMed  PubMed Central  Article  Google Scholar 

21.
Packer, C. et al. Reproductive success of lions in Reproductive success (ed. Clutton-Brock, T.H.) 363–383 (University of Chicago Press, 1988).

22.
Packer, C., Gilbert, D. A., Pusey, A. E. & O’Brien, S. J. A molecular genetic analysis of kinship and cooperation in African lions. Nature 351, 562–565 (1991).
ADS  CAS  Article  Google Scholar 

23.
Connor, R. C., Smolker, R. A., & Richards, A. F. Two levels of alliance formation among male bottlenose dolphins (Tursiops sp.). PNAS. 89, 987–990 (1992).

24.
Parsons, K. M. et al. Kinship as a basis for alliance formation between male bottlenose dolphins, Tursiops truncatus, in the Bahamas. Anim. Behav. 66, 185–194 (2003).
Article  Google Scholar 

25.
Widdig, A., Streich, W. J. & Tembrock, G. Coalition formation among male Barbary macaques (Macaca sylvanus). Am. J. Primatol. 50, 37–51 (2000).
CAS  PubMed  Article  Google Scholar 

26.
Gottelli, D., Wang, J., Bashir, S. & Durant, S. M. Genetic analysis reveals promiscuity among female cheetahs. Proc. R. Soc. B. 274, 1993–2001 (2007).
PubMed  Article  Google Scholar 

27.
Bertram, B.C. Pride of lions. (JM Dent and Sons Ltd, 1978).

28.
O’Brien, S.J. Prides and Prejudice in Tears of the cheetah and other tales from the genetic frontier: the genetic secrets of our animal ancestors (ed. O’Brien, S.J.) 35–55 (Thomas Dunne Books, 2003).

29.
de Manuel, M. et al. The evolutionary history of extinct and living lions. PNAS 117, 10927–10934 (2020).
PubMed  Article  CAS  Google Scholar 

30.
Clutton-Brock, T. H. Reproductive skew, concessions and limited control. Trends Ecol. Evol. 13, 288–292 (1998).
CAS  PubMed  Article  Google Scholar 

31.
Queller, D. C. & Keith, F. G. Estimating relatedness using genetic markers. Evolution 43, 258–275 (1989).
PubMed  Article  Google Scholar 

32.
Wang, J. Estimating pairwise relatedness in a small sample of individuals. Heredity 119, 302–313 (2017).
CAS  PubMed  PubMed Central  Article  Google Scholar 

33.
Sandel, A. A., Langergraber, K. E. & Mitani, J. C. Adolescent male chimpanzees (Pan troglodytes) form social bonds with their brothers and others during the transition to adulthood. Am. J. Primatol. 82, 23091. https://doi.org/10.1002/ajp.23091 (2020).
Article  Google Scholar 

34.
Dal Pesco, F. Dynamics and fitness benefits of male-male sociality in wild Guinea baboons (Papio papio). (PhD thesis), Georg-August University, Göttingen, Germany.

35.
Christakis, N. A. & Fowler, J. H. Friendship and natural selection. PNAS 111, 10796–10801 (2014).
ADS  CAS  PubMed  Article  Google Scholar 

36.
Engh, A. L. et al. Behavioural and hormonal responses to predation in female chacma baboons (Papio hamadryas ursinus). Proc. R. Soc. B. 273, 707–712 (2006).
CAS  PubMed  Article  Google Scholar 

37.
Hill, K. R. et al. Co-residence patterns in hunter-gatherer societies show unique human social structure. Science 331, 1286–1289 (2011).
ADS  CAS  PubMed  Article  Google Scholar 

38.
Silk, J.B. Practicing Hamilton’s Rule: kin selection in primate groups in Cooperation in primates and humans (ed. Kappeler, P.M., & van Schaik, C.P.) 25–46 (Springer, 2006).

39.
Chakrabarti, S. et al. Adding constraints to predation through allometric relation of scats to consumption. J. Anim. Ecol. 85, 660–670 (2016).
PubMed  Article  Google Scholar 

40.
Møller, A. P. & Birkhead, T. R. Copulation behaviour in mammals: evidence that sperm competition is widespread. Biol. J. Linn. Soc. 38, 119–131 (1989).
Article  Google Scholar 

41.
Chakrabarti, S. & Jhala, Y. V. Battle of the sexes: a multi-male mating strategy helps lionesses win the gender war of fitness. Behav. Ecol. 30, 1050–1061 (2019).
Article  Google Scholar 

42.
Jhala, Y. V. et al. Asiatic lion: ecology, economics and politics of conservation. Front. Ecol. Evol. 7, 312 (2019).
ADS  Article  Google Scholar 

43.
Boom, R. C. J. A. et al. Rapid and simple method for purification of nucleic acids. J. Clin. Microbiol. 28, 495–503 (1990).
CAS  PubMed  PubMed Central  Article  Google Scholar 

44.
Antunes, A. et al. The evolutionary dynamics of the lion Panthera leo revealed by host and viral population genomics. PLoS Genet. 4, 1000251. https://doi.org/10.1371/journal.pgen.1000251 (2008).
CAS  Article  Google Scholar 

45.
Singh, A., Shailaja, K., Gaur, A., & Singh., L. Development and characterization of novel microsatellite markers in the Asiatic lion (Panthera leo persica). Mol. Ecol. Notes. 2, 542–543 (2002).

46.
Gaur, A. et al. Twenty polymorphic microsatellite markers in the Asiatic lion (Panthera leo persica). Conserv. Genet. 7, 1005–1008 (2006).
CAS  Article  Google Scholar 

47.
Menotti-Raymond, M. et al. A genetic linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57, 9–23 (1999).
CAS  PubMed  Article  Google Scholar 

48.
Menotti-Raymond, M. et al. An STR forensic typing system for genetic individualization of domestic cat (Felis catus) samples. J. Forensic Sci. 50, 1061–1070 (2005).
CAS  PubMed  Article  Google Scholar 

49.
Williamson, J. E., Huebinger, R. M., Sommer, J. A., Louis, E. E. Jr. & Barber, R. C. Development and cross-species amplification of 18 microsatellite markers in the Sumatran tiger (Panthera tigris sumatrae). Mol. Ecol. Notes. 2, 110–112 (2002).
CAS  Article  Google Scholar 

50.
Drummond, A.J.A.B. et. al. v5. 4. Auckland (2011).

51.
Matschiner, M. & Salzburger, W. TANDEM: integrating automated allele binning into genetics and genomics workflows. Bioinformatics 25, 1982–1983 (2009).
CAS  PubMed  Article  Google Scholar 

52.
Taberlet, P. et al. Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Res. 24, 3189–3194 (1996).
CAS  PubMed  PubMed Central  Article  Google Scholar 

53.
Peakall, R.O.D., & Smouse, P.E. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes. 6, 288–295 (2006).

54.
Bergner, L. M., Jamieson, I. G. & Robertson, B. C. Combining genetic data to identify relatedness among founders in a genetically depauperate parrot, the Kakapo (Strigops habroptilus). Conserv. Genet. 15, 1013–1020 (2014).
Article  Google Scholar 

55.
Gilbert, D. A., Packer, C., Pusey, A. E., Stephens, J. C. & O’Brien, S. J. Analytical DNA fingerprinting in lions: parentage, genetic diversity, and kinship. J. Hered. 82, 378–386 (1991).
CAS  PubMed  Article  Google Scholar 

56.
Pemberton, J. M., Albon, S. D., Guinness, F. E., Clutton-Brock, T. H. & Dover, G. A. Behavioral estimates of male mating success tested by DNA fingerprinting in a polygynous mammal. Behav. Ecol. 3, 66–75 (1992).
Article  Google Scholar 

57.
Dixson, A. F., Bossi, T. & Wickings, E. J. Male dominance and genetically determined reproductive success in the mandrill (Mandrillus sphinx). Primates 34, 525–532 (1993).
Article  Google Scholar 

58.
Krebs, J.R., & Davies, N.B. An introduction to behavioural ecology. (Blackwell Scientific Publications, 1987).

59.
Smith, J. M. Group selection and kin selection. Nature 201, 1145–1147 (1964).
ADS  Article  Google Scholar 

60.
Banerjee, K. & Jhala, Y. V. Demographic parameters of endangered Asiatic lions (Panthera leo persica) in Gir forests India. J. Mammal. 93, 1420–1430 (2012).
Article  Google Scholar 

61.
Meena, V. Reproductive strategy and behaviour of male Asiatic lions. [Dissertation/Ph.D. thesis]. (Forest Research Institute University, 2008).

62.
Banerjee, K. Ranging patterns, habitat use and food habits of the satellite lion populations (Panthera leo persica) in Gujarat, India. [Dissertation/Ph.D. thesis]. (Forest Research Institute Deemed University, 2012).

63.
Gogoi, K., Kumar, U., Banerjee, K. & Jhala, Y. V. Spatially explicit density and its determinants for Asiatic lions in the Gir forests. PLoS ONE 15, 0228374. https://doi.org/10.1371/journal.pone.0228374 (2020).
CAS  Article  Google Scholar 

64.
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. (2019). More

Effects of FeS on nitrogen removal
The start-up period could be divided into two phases based on the operating strategy of the reactor, as illustrated in Table 1. The first phase was characterized by high HRT and low substrate concentration (days 0–18), in which the HRT was 48 h and the concentrations of influent NH4+-N and NO2−-N were 50 and 60 mg L−1, respectively. The second phase was characterized by low HRT and high substrate concentration (days 24–68), in which the HRT was 36 h and the theoretical concentrations of influent NH4+-N and NO2−-N were 100 and 120 mg L−1, respectively.
Table 1 Operational conditions of R1 and R2 under different phases.
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The effluent ammonium concentration was significantly higher than that of influent at the beginning of the reactor operation shown in Fig. 1a. On the first day, the effluent NH4+-N concentration of R1 and R2 reached 106.0 and 80.6 mg L−1, respectively, nearly twice as high as the influent NH4+-N concentration. This is mainly due to the fact that some microorganisms were unable to adapt to the new environmental conditions, inducing cellular lysis21. At the same time, effluent NO2−-N concentration of R1 and R2 on the fourth day were 18.4 and 17.3 mg L−1, respectively, with the removal efficiency of more than 70% (Fig. 1b); and NO3−-N accumulated in the effluent. The high-throughput results showed that Nitrospirae, which contained massive nitrite-oxidizing bacteria (NOB), accounted for a higher proportion in the inoculation sludge (Supplementary Fig. 1)22. qPCR results also indicated that NOB abundance was higher in the inoculation sludge as shown in the section “Effect of FeS on functional bacteria abundance”. Therefore, the removal of NO2−-N in the beginning might be attributed to the role of nitrification. Denitrification also might promote the decrease of NO2−-N through using the organic matter which was released by decay of biomass23. From day 7 to day 10, effluent NH4+-N of R1 and R2 decreased rapidly from 38.1 and 49.4 mg L−1 to 6.8 and 6.8 mg L−1, respectively, however the removal rate of NO2−-N did not change much. From day 1 to day 18, the accumulation of NO3−-N in R1 and R2 gradually decreased from 10 mg L−1 to 0 mg L−1. These phenomena indicated that NOB was gradually eliminated in the low-oxygen environment and the activity of anammox bacteria was increasing. In addition, microbial metabolism and decay of biomass will release organic carbon, which can be used as carbon sources by denitrifying bacteria23. From day 4 to day 18, the total nitrogen removal efficiency (TNRE) of R1 and R2 increased from 30.4% and 22.2% to 96.0% and 98.3%, respectively. On day 18, the values of removed NO2−-N/NH4+-N and produced NO3−-N/removed NH4+-N were 1.14 and 0 in R1 while these were 1.17 and 0 in R2, which was the result of the combined action of nitrifying bacteria, denitrifying bacteria and anammox bacteria.
Fig. 1: Nitrogen removal performances of R1 and R2.

a Influent and effluent NH4+-N concentration; b Influent and effluent NO2−-N concentration; c Nitrogen loading rate (NLR), nitrogen removal rate (NRR), and total nitrogen removal efficiency (TNRE).

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On the 21st day, when influent NH4+-N and NO2−-N concentrations increased to 100.3 and 138.1 mg L−1, effluent NH4+-N and NO2−-N concentrations of R1 increased to 6.5 and 24.2 mg L−1, respectively; while those of R2 increased to 2.6 and 19.9 mg L−1. On the 24th day, when HRT decreased from 48 h to 36 h, effluent NH4+-N and NO2−-N continued to increase. At this time, the abundance of anammox bacteria in the reactors was relatively low and had not played a dominant role. Meanwhile, the cell lysis phase was over and denitrifying bacteria activity began to decrease with the continuous consumption of organic substance23. Therefore, the NH4+-N and NO2−-N removal efficiencies fluctuated widely when the nitrogen loading rate (NLR) increased. Moreover, the higher removal rate of NH4+-N and NO2−-N in R2 can be attributed to the promotion effect of FeS on anammox growth. On the 27th day, effluent NO2−-N concentration of R1 and R2 reached the highest values (81.8 mg L−1, 71.1 mg L−1); the TNRE was the lowest, which were 52.8% and 61.0%, respectively. After this point, the NH4+-N and NO2−-N removal efficiencies of both R1 and R2 gradually increased and there were significant differences in total nitrogen removal capability between the two reactors. As shown in Fig. 1c, the TNRE of R2 on the 30th day increased to 73.3%; R1 achieved a TNRE of over 70% 12 days later, while the TNRE of R2 reached over 80% at this time. On the 45th day, the accumulation of nitrate appeared again in the effluent of the two reactors, meaning anammox was predominant. On the 51st day, the NH4+-N and NO2−-N removal in R2 reached more than 85% simultaneously, and the values of removed NO2−-N/NH4+-N and produced NO3−-N/removed NH4+-N were 1.12 and 0.17, respectively, closing to the theoretical stoichiometric ratio of anammox reaction, which marks that anammox reactor was started up successfully21. Based on Eq. (1) and the experimental data on day 51, an assumed transformation model was constructed to reflect the pathways of the nitrogen conversions in the system as shown in Supplementary Fig. 2. Due to the lack of oxygen and organic matter and the inhibition of denitrification by FeS, anammox played a dominant role. The same phenomenon occurred in R1 on day 56. Bi et al. studied the effect of Fe(II) concentration on the start-up of anammox process with a HRT of 12 h and found that the start-up time of anammox process could be shortened from 70 to 58 days when the concentration of Fe(II) ranged from 1.68 to 3.36 mg L−121. Because the concentration of Fe(II) was relatively lower than previous study, the influence was relatively less but this method is more convenient. The heme c content at day 50 in R2 was higher than that in R1 as shown in the section “Fe2+ release and Heme c content”, demonstrating that the activity of anammox bacteria in R2 was higher than that in R1. In summary, FeS effectively shortened the start-up time and improved the nitrogen removal performance.
On the 71st day, when influent NH4+-N and NO2−-N concentrations increased to 150 mg L−1 and 180 mg L−1, respectively, the NH4+-N and NO2−-N removal rates in the two reactors decreased. On the 75th day, effluent NH4+-N concentrations of R1 and R2 increased to 37.1 and 35.3 mg L−1, meantime effluent NO2−-N concentration increased to 93.3 and 84.8 mg L−1. Although the nitrogen removal rate of the two reactors decreased obviously after the NLR was increased, it quickly recovered to the original level. As shown in Fig. 1a, b, on day 81, effluent NH4+-N in R1 and R2 decreased to 11.1 and 7.1 mg L−1 and effluent NO2−-N concentrations decreased to 16.5 and 6.2 mg L−1. The TNRE increased to about 90%. This indicated that the reactors have a certain capacity in resistance to weak shock loading due to the enrichment of anammox bacteria. And, when influent NH4+-N and NO2−-N were further increased, effluent NH4+-N and NO2−-N concentrations of R2 were significantly lower than these of R1. Meantime, the responses caused by the unit intensity of shock (R) of R2 was substantially lower than these of R1 as shown in Supplementary Table 1, indicating that R2 had more resistance to shock loading rate. The same trend was observed when HRT were further shortened to 36 h and 12 h, suggested that the stability of anammox reactors can be improved with the addition of FeS.
During the start-up period, the NO3−-N concentration in R2 was substantially higher than that in R1 as shown in Supplementary Fig. 3, which might be attributed to the inhibition of denitrification process in R2 by FeS24,25. However, in the stabilization period, the NO3−-N concentration in R2 was substantially lower than that in R1. This was due to the lack of organic matter in R1 which inactivated denitrifying bacteria. Meantime, the presence of FeS in R2 might promote sulfur autotrophic denitrification and DNRA to reduce nitrate. The KEGG function prediction result as shown in the section “Effect of FeS on microbial community” verified this inference.
FeS structure change
The appearance of FeS with dark brown color, particle size between 1 and 5 mm and compact texture before being added to the reactor was observed (Supplementary Fig. 4). After 180 days of reactor operation, the FeS materials remaining in R2 were found to be covered with a layer of sludge. And the appearance displayed clear differences: most of the color changed from dark brown to khaki and the texture was sparse, which may be caused by the oxidation of FeS. Moreover, the red anammox granule sludge as shown in Supplementary Fig. 4 was observed in R2. Touching these red anammox granule sludge felt that the interior was relatively hard, which was made of FeS particles. FeS may promote the formation of anammox granular sludge.
To further understand the structure change, the morphology of FeS before and after reaction were observed by SEM at different magnifications. As shown in Fig. 2c, d, there were many honeycomb style holes on the surface and inside of the FeS particles after the reaction. The voids formed on the surface may facilitate the attachment of microorganisms, which acted like microbial carriers. Therefore, anammox granular sludge containing FeS as inert cores formed in R2. In addition, Fe2+/Fe3+ produced by oxidation and ionization of FeS could weaken the electrostatic repulsion among negatively charged anammox cells and promote the aggregation of anammox bacteria into zoogloea by the effect of salt bridge26. Thus, the addition of FeS could promote the formation of anammox granular sludge, then improve the stability of the reactor. Figure 2e, f showed that many plate-shaped secondary minerals were produced after the reaction of FeS. In the presence of dissolved oxygen (DO), O2 can diffuse into the FeS surface and oxidize Fe2+ to Fe3+ (Eq. (5))6. The formation of these secondary minerals may hinder the release of iron ions from FeS27.

$${mathrm{FeS}} + {mathrm{2}}{mathrm{.25}}{mathrm{O}}_2 + {mathrm{2}}{mathrm{.5}},{mathrm{H}}_2{mathrm{O}} to {mathrm{Fe}}({mathrm{OH}})_3 + {mathrm{S}}{mathrm{O}}_4^{{mathrm{2}} – } + {mathrm{2}}{mathrm{H}}^ +$$
(5)

Fig. 2: SEM of FeS.

Before (a, b) and after (c–f) reaction.

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Effect of FeS on functional bacteria abundance
The abundance of anammox bacteria in the two reactors were monitored during the period of their operation. As shown in Fig. 3a, the copy numbers of anammox 16S rRNA gene in the inoculation sludge was 3.31 × 106 copies per ng DNA. After 150 days of cultivation, the copy numbers of anammox 16S rRNA gene in R1 and R2 (1.21 × 107, 1.42 × 107copies per ng DNA) were significantly higher than that in the inoculation sludge. The data demonstrate that although the content of anammox in the inoculation sludge was low, anammox bacteria can be rapidly enriched and the reactor could be properly started-up as long as the cultural conditions for anammox bacteria growth were suitable. The anammox 16S rRNA gene copy numbers of R1 and R2 were 5.68 × 106 and 7.04 × 106 copies per ng DNA on day 70, respectively. Compared with R1, the abundance of anammox bacteria in R2 was increased by 29%. The contrast in cell quantities between R1 and R2 indicated that the addition of FeS with this concentration promoted the growth of anammox bacteria. Combined with the water quality results, the faster growth rate of anammox bacteria in R2 was responsible for the higher removal efficiencies of NH4+-N and NO2−-N and shorter start-up time of reactor.
Fig. 3: The qPCR results of sludge samples.

a Anammox 16S rRNA gene copy number in different period; b other functional genes copy number on day 70. Data indicate average, and error bars represent standard deviation of the results from three independent sampling, each tested in triplicate.

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In addition to anammox, the contents of ammonia-oxidizing bacteria (AOB), NOB and denitrifying bacteria also affect the start-up time and nitrogen removal capacity of anammox reactor. Compared with the inoculation sludge, the expression levels of amoA (NH4+ → NO2−) and nirS (NO3− → NO2−) genes in both R1 and R2 were increased, while the expression levels of Nitrospira spp. 16S rRNA genes (NO2− → NO3−) and nirK (NO3− → NO2−) genes were decreased (Fig. 3b). The expression levels of Nitrospira spp. 16S rRNA genes could reflect the content of NOB in anammox reactor28. As anammox was cultured in an anaerobic environment, which was not conducive to the growth of NOB, the content of NOB was gradually decreased with the increase of culture time. And the expression level of Nitrospira spp. 16S rRNA genes in the inoculated sludge was 2.14 × 106 copies per ng DNA, which was consistent with the higher nitrite removal efficiency initially. On day 70, the expression levels of amoA gene in R1 and R2 were 1.34 × 104 and 2.07 × 103 copies per ng DNA, while anammox 16S rRNA gene expression level was 5.68 × 106 and 7.04 × 106 copies per ng DNA. It was clear that the content of anammox was two or three orders of magnitude higher than AOB. The qPCR results also demonstrated that the anammox bacteria were dominant after 70 days of operation, at which time the removal of ammonium nitrogen was mainly from anammox. In addition, the expression level of amoA gene in R2 was much lower than that of R1, and the NOB content of both reactors was higher than AOB content on day 70 (Fig. 3b). FeS could react with dissolved oxygen (DO) in the reactor, leading to an inhibitory effect on the growth of AOB6. But Nitrospira-like NOB has higher hypoxia tolerance ability than AOB. Liu et al. reported that when the reactor was operated under low oxygen conditions (0.16 mg DO L−1) for a long time, some of Nitrospira-like NOB can adapt to anaerobic environment and maintain activity29. Both nirS and nirK are functional genes of denitrifying bacteria. The expression level of nirS gene in R2 (2.05 × 106 copies per ng DNA) was higher than that of R1 (1.11 × 106 copies per ng DNA), while the expression of nirK gene in R2 (3.27 × 106 copies per ng DNA) was slightly lower than that of R1 (3.65 × 106 copies per ng DNA). According to previous reports, the nirK gene encodes copper-containing nitrite reductase and the nirS gene encodes heme-containing cd1 nitrite reductase which contains heme d as its catalytic center30. And iron ions are involved in the synthesis of various types of heme. It is reasonable to speculate that the synthesis of cd1 nitrite reductase in microorganisms was promoted after adding FeS into the reactor.
Fe2+ release and Heme c content
The effluent Fe2+ and intracellular heme c concentrations were determined and illustrated in Fig. 4. Initially, the Fe2+ content in the effluent of R1 and R2 was similar because FeS particles with compact texture had a smaller specific surface area (Fig. 2a, b) and released less iron ions (Fig. 4a). After the reactor was operated for a period, the effluent Fe2+ concentration of R2 was significantly higher than that of R1. On the 30th day, the effluent Fe2+ concentration of R1 and R2 were 0.132 and 1.762 mg L−1, respectively. The results on days 45 and 60 also showed that there was a significant difference in effluent Fe2+ concentration between R1 and R2. During this period, massive holes were corroded on the surface and inside of FeS particles as shown in Fig. 2, the specific surface area of FeS increased and the activity of FeS was higher, contributing to more release of iron ions. On day 70, the content of heme c in R1 and R2 was 7.2 and 11.8 μmol per g-protein, respectively (Fig. 4b). It has been reported that Fe2+ was involved in the formation of heme c, which was the active center of many enzyme proteins31. In many biochemical reactions, the transformation of substrate and intermediate is accomplished by the catalysis and electron transfer of c-type heme protein32,33. Anammox cells contain a large amount of multi-heme cytochromes, for example one subunit of hydroxylamine oxidoreductase enzyme (HAO) binds 8 heme c34. In this experiment, the positive correlation between Fe2+ and heme c confirmed that the concentration of Fe2+ in the reactor could be increased with the addition of FeS, then promoting the synthesis of heme c. On the 75th and 90th days, the Fe2+ content in the effluent of both reactors became lower, probably because the abundance of anammox bacteria increased gradually, corresponding to an increased consumption of iron ions. At the same time, the results showed that the content of Fe2+ in R2 effluent did not differ much from that in R1 effluent. On one hand, as the reaction progress, secondary minerals and biofilm were formed on the surface of FeS (Fig. 2), which led to a decrease in FeS activity. On the other hand, the abundance of anammox bacteria in R2 was higher than that in R1 (Fig. 3), thus more iron ions would be consumed.
Fig. 4: Effluent Fe2+ concentration and the content of Heme c.

a effluent Fe2+ concentration; b the content of Heme c. Data indicate average, and error bars represent standard deviation of the results from three independent sampling, each tested in triplicate.

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Effect of FeS on microbial community
Through clustering analysis of OTU, the number of OTUs shared among samples and the number of OTUs unique to each sample can be intuitively observed. The number of OTUs shared by the R1 and R2 samples was 816, which accounted for 71.8% and 69.9% of the total OTUs, respectively; the number of OUT unique to R1 was 321 and that for R2 was 352 (Supplementary Fig. 5). The addition of FeS led to different species composition of the two communities. The shared OTUs number of R1 and R2 samples with inoculated sludge was 168, accounting for 14.8% and 14.4% of the total OTUs of R1 and R2 samples, respectively. Obviously, after domestication, the R1 and R2 samples were less similar to the inoculated sludge.
The ACE, Chao1, Simpson and Shannon listed in Table 2 are the alpha diversity indexes that reflect the richness and diversity of the community. The ACE and Chao 1 indexes are mainly used to indicate the richness of the community. In general, the larger the two index values are, the higher the richness of the community is. Comparing the ACE and Chao1 index values of R1 and R2 samples, the richness of R2 community was higher than that of R1. The Simpson and Shannon indexes account for the richness and evenness of the community. The larger the two index values are, the higher the diversity of the community is. As shown in Table 2, the two index values of R2 samples were higher than these of R1, so the diversity of R2 community was higher. In summary, the community of R2 sample had higher richness and diversity. During the cultivation and acclimation process, some species in the seed sludge couldn’t adapt to the new environmental conditions and were gradually washed out from the system. The addition of FeS reduced the tendency of some species to disappear under its role in facilitating the formation of granular sludge.
Table 2 The OTU numbers and bacterial diversity indices of sludge samples.
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It can be seen from the results of microbial diversity analysis that the addition of FeS had a certain influence on the number of species of R1 and R2. The differences in microbial community composition at different classification levels with or without the presence of FeS were shown in Fig. 5.
Fig. 5: The microbial community of sludge samples at different levels on day 180.

a Phylum level; b top 9 abundant genera at genus level; c the microbial community of Brocadiaceae.

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The microbial community composition of R1 and R2 was similar at phylum classification level (Fig. 5a). The dominant phylum in two reactors was Protobacteria, accounting for 40.1% and 29.6%, respectively, followed by Chloroflexi (12.5% and 14.1%). Other reports also showed there were higher contents of Protobacteria and Chloroflexi in anammox reactor35,36. The relative abundance of Planctomycetes which anammox belonged to in R1 and R2 was 9.1% and 9.9%, respectively. The values were not very high, mainly due to the small proportion of Planctomycetes in the inoculated sludge (Supplementary Fig. 1) and the slower growth rate of the anammox bacteria. The proportion of Acidobacteria in R1 and R2 showed obvious difference, with relative abundances of 7.0% and 11.9%, respectively. Several publications demonstrated that some microorganisms belonged to Acidobacteria have the ability to dissimilate iron reduction with various simple organic acids such as acetate as alternative electron donors under anaerobic conditions37,38,39. In addition, the relative abundance of Nitrospirae which Nitrospira belonged to in R1 and R2 was extremely low compared with the inoculated sludge, which was reduced from 16.58% to 0.45% and 0.15%, respectively (Supplementary Fig. 1). This result was consistent with the water quality.
Figure 5b showed the genus of the top 9 abundance in the microbial community of R1 and R2. The most abundant genus in R1 was Halomonas, accounting for 9.7%. Most parts of the microbes belonged to Halomonas were denitrifying bacteria, which could reduce NO3−-N to NO2−-N40. Denitratisoma with a high relative abundance (7.3%) in R1 is also one type of denitrifying bacteria41. The proportions of Halomonas and Denitratisoma in R2 was 6.5% and 4.3%, respectively, significantly lower than these in R1. The relative abundance of Thiobacillus, which was the major autotrophic denitrifier detected in most sulfur-based autotrophic denitrification reactors, increased from 0.012% in R1 to 0.041% in R2 with the addition of FeS42,43. The most abundant genus in R2 was Clone_Anammox_20, accounting for 9.0%. Clone_Anammox_20 and Clone_Anammox_2 are a class of microorganisms with anammox function. The most abundant anammox genus obtained in both reactors was “Ca. Kuenenia” and the proportion was relatively close. In order to further explore the effect of FeS on the distribution of anammox bacteria, the composition of R1 and R2 samples on Brocadiaceae classification level was analyzed. The Brocadiaceae family in R1 consisted of three anammox genus, “Ca. Kuenenia”, “Ca. Brocadia” and “Ca. Jettenia”, accounting for 99%, 0.9%, and 0.1%, while the Brocadiaceae family in R2 consisted of two anammox genus, “Ca. Kuenenia” and “Ca. Brocadia”, accounting for 98% and 2%, respectively (Fig. 5c). The dominant anammox bacteria in R1 and R2 was “Ca. Kuenenia”, and the proportion of “Ca. Brocadia” in R2 was higher than in R1. Other works have found that some of the anammox bacteria under the genus “Ca. Kuenenia” and “Ca. Brocadia” could oxidize Fe2+ with NO3−-N while anammox process occurred44. Thus, FeS might affect the distribution of species and relative abundance of anammox genus but did not change the dominant status of the anammox bacteria in the community.
To further explore the influence mechanism of FeS on nitrogen transportation, PICRUSTs was used in this experiment to predict the contents of enzymes related to NO2−-N conversion based on KEGG database. As shown in Fig. 6a, nitrite can be reduced to nitrogen (NO2−-N→N2) through denitrification and ammonia nitrogen (NO2−-N→NH4+-N) through dissimilatory nitrate reduction to ammonium (DNRA), in addition to being removed by anammox. The nitrite reductase (ammonia-forming) content of R2 was significantly higher than that of R1, while nitrite reductase (NO-forming) and nitric oxide reductase content of R2 was lower than that of R1. It had been reported that some DNRA bacteria can conduct DNRA process with sulfide (S2−) or elemental sulfur (S0) as electron donors45. And sulfide had an inhibitory effect on nitrous oxide reductase and nitric oxide reductase, which can inhibit the denitrification reaction, have an inhibitory effect on nitrite reductase (NO-forming) due to the accumulation of NO and promote the nitrite reduction reaction by the DNRA process24,25,46. In addition, heme was involved in the formation of nitrite reductase (ammonia-forming)47. Robertson et al. found that the addition of Fe2+ improved DNRA and inhibited denitrification48,49. It is postulated that the iron ions and sulfur ions released by FeS encouraged the occurrence of DNRA process and somehow decreased the denitrification reaction. Therefore, the removal rates of NO2−-N in the two reactors were significantly different, and the removal rates of NH4+-N were similar. This may also account for the relatively low abundance of denitrifying bacteria in R2. Moreover, Fig. 6b showed the predicted metabolism function of the two reactors’ communities, and the results indicated that the metabolic function of R2 was slightly higher than that of R1. It can be seen that the addition of FeS to the anammox reactor can increase microbial metabolism.
Fig. 6: Prediction of community functions based on KEGG.

a Nitrogen invertase content; b metabolism functions.

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Engineering significance
As a new type of environmentally-friendly biological nitrogen removal process, the anammox process has been a research hotspot, but it still encounters some issues to limit its wider application. Anammox bacteria are slow-growing microorganisms, and are sensitive to environmental conditions, such as salinity and organic carbon50. Another challenge of the anammox process system is the maintenance of effluent quality since about 10% nitrate would be produced in the anammox reaction, failing to meet discharge standards51.
In this study, the start-up time of the anammox reactor was shortened and the nitrogen removal rate was significantly increased with the addition of FeS. There were mainly two reasons: On one hand, FeS promoted the formation of anammox granular sludge and increased the abundance of anammox bacteria; on the other hand, FeS stimulated the synthesis of the heme c, which participated in the synthesis of a variety of enzymes. In addition, FeS can promote the DNRA process by inhibiting denitrification. Microbial oxidation of FeS, which links to the efficiency of denitrification, DNRA and anammox, plays an important role in the N cycle and S cycle15. According to previous report, FeS could function as an alternative electron donor for sulfur-dependent autotrophic denitrification52. Nitrate reduction was achieved by using pyrrhotite as the biofilter medium and autotrophic denitrifiers as seed in lab17. And DNRA process could occur due to HS− release18. This study found that FeS could promote the start-up of anammox process and promote the nitrite reduction reaction by the DNRA process through inhibiting denitrification. Therefore, it is possible to couple anammox with sulfur-autotrophic DNRA or sulfur-autotrophic denitrification in full-scale application by adding FeS to improve the total nitrogen removal efficiency. More

1.
Walther, G. R. Community and ecosystem responses to recent climate change. Philos Trans R Soc B Biol Sci 365, 2019–2024 (2010).
Article  Google Scholar 
2.
Poloczanska, E. S. et al. Global imprint of climate change on marine life. Nat. Clim. Change. 3, 919–925 (2013).
ADS  Article  Google Scholar 

3.
Hoegh-Guldberg, O. & Poloczanska, E. S. The effect of climate change across ocean regions. Front. Mar. Sci. 4, 361 (2017).
Article  Google Scholar 

4.
Bruno, J. F. et al. Climate change threatens the world’s marine protected areas. Nat. Clim. Change. 8, 499–503 (2018).
ADS  Article  Google Scholar 

5.
Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the world’s marine ecosystems. Science 328, 1523–1528 (2010).
ADS  CAS  Article  Google Scholar 

6.
Smale, D. A., Taylor, J. D., Coombs, S. H., Moore, G. & Cunliffe, M. Community responses to seawater warming are conserved across diverse biological groupings and taxonomic resolutions. Proc. R. Soc. B Biol. Sci. 284, 20170534 (2017).
Article  Google Scholar 

7.
Gauzens, B., Rall, B. C., Mendonça, V., Vinagre, C. & Brose, U. Biodiversity of intertidal food webs in response to warming across latitudes. Nat. Clim. Change. 10, 264–269 (2020).
ADS  Article  Google Scholar 

8.
Sahney, S. & Benton, M. J. Recovery from the most profound mass extinction of all time. Proc. R. Soc. B Biol. Sci. 275, 759–765 (2008).
Article  Google Scholar 

9.
Urban, M. C. Accelereting extinction risk from climate change. Science 348, 571–573 (2012).
ADS  Article  CAS  Google Scholar 

10.
Wiens, J. J. Climate-related local extinctions are already widespread among plant and animal species. PLoS Biol. 14, e2001104 (2016).
Article  CAS  PubMed  PubMed Central  Google Scholar 

11.
Pinsky, M. L., Eikeset, A. M., McCauley, D. J., Payne, J. L. & Sunday, J. M. Greater vulnerability to warming of marine versus terrestrial ectotherms. Nature 569, 108–111 (2019).
ADS  CAS  Article  PubMed  Google Scholar 

12.
Smale, D. A. & Wernberg, T. Extreme climatic event drives range contraction of a habitat-forming species. Proc. R. Soc. B Biol. Sci. 280, 20122829 (2013).
Article  Google Scholar 

13.
Wernberg, T. et al. An extreme climatic event alters marine ecosystem structure in a global biodiversity hotspot. Nat. Clim. Change. 3, 78–82 (2013).
ADS  Article  Google Scholar 

14.
Wernberg, T. et al. Climate-driven regime shift of a temperate marine ecosystem. Science 353, 169–172 (2016).
ADS  CAS  Article  PubMed  Google Scholar 

15.
Hobday, A. J. et al. A hierarchical approach to defining marine heatwaves. Prog. Oceanogr. 141, 227–238 (2016).
ADS  Article  Google Scholar 

16.
Oliver, E. C. J. et al. Longer and more frequent marine heatwaves over the past century. Nat. Commun. 9, 1–12 (2018).
CAS  Article  Google Scholar 

17.
Oliver, E. C. J. et al. Projected marine heatwaves in the 21st century and the potential for ecological impact. Front. Mar. Sci. 6, 1–12 (2019).
Article  Google Scholar 

18.
Smale, D. A. et al. Marine heatwaves threaten global biodiversity and the provision of ecosystem services. Nat. Clim. Change. 9, 306–312 (2019).
ADS  Article  Google Scholar 

19.
Eakin, C. M. et al. Caribbean corals in crisis: record thermal stress, bleaching, and mortality in 2005. PLoS ONE 5, e13969 (2010).
ADS  Article  CAS  PubMed  PubMed Central  Google Scholar 

20.
Bruno, J. F. & Valdivia, A. Coral reef degradation is not correlated with local human population density. Sci. Rep. 6, 29778 (2016).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

21.
Marbà, N. & Duarte, C. M. Mediterranean warming triggers seagrass (Posidonia oceanica) shoot mortality. Glob. Chang. Biol. 16, 2366–2375 (2010).
ADS  Article  Google Scholar 

22.
Thomson, J. A. et al. Extreme temperatures, foundation species, and abrupt ecosystem change: An example from an iconic seagrass ecosystem. Glob. Chang. Biol. 21, 1463–1474 (2015).
ADS  Article  PubMed  Google Scholar 

23.
Hyndes, G. A. et al. Accelerating tropicalization and the transformation of temperate seagrass meadows. Bioscience 66, 938–945 (2016).
Article  PubMed  PubMed Central  Google Scholar 

24.
Babcock, R. C. et al. Severe continental-scale impacts of climate change are happening now: Extreme climate events impact marine habitat forming communities along 45% of Australia’s coast. Front. Mar. Sci. 6, 411 (2019).
Article  Google Scholar 

25.
Rogers-Bennett, L. & Catton, C. A. Marine heat wave and multiple stressors tip bull kelp forest to sea urchin barrens. Sci. Rep. 9, 15050 (2019).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

26.
E.C., MSFD 2008/56/EC of the European Parliament and of the Council, 17 June 2008, establishing a framework for Community action in the field of marine environmental policy (Marine Strategy Framework Directive). Off. J. Eur. Comm. 25/6/2008, L164/19, 22 (2008).

27.
Martin, C. S. et al. Coralligenous and maërl habitats: Predictive modelling to identify their spatial distributions across the Mediterranean sea. Sci. Rep. 4, 5073 (2015).
Article  CAS  Google Scholar 

28.
Ballesteros, E., Avançats, E. & Csic, D. B. Mediterranean coralligenous assemblages: A synthesis of present knowledge. Oceanogr. Mar. Biol. 44, 123–195 (2006).
Article  Google Scholar 

29.
Kružić, P. Bioconstructions in the Mediterranean: present and futture in The Mediterranean sea: its history and present challenges (ed. Goffredo, S. & Dubinsky, Z) 435–447 (2014).

30.
E.C., Council Directive 92/43/EEC (Habitat Directive) of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora. Off. J. Eur. Comm. 22/7/1992, L206, 7 (1992).

31.
Martin, S. & Gattuso, J. P. Response of Mediterranean coralline algae to ocean acidification and elevated temperature. Glob. Chang. Biol. 15, 2089–2100 (2009).
ADS  Article  Google Scholar 

32.
Boudouresque, C. F. et al.Where seaweed forests meet animal forests: The examples of macroalgae in coral reefs and the Mediterranean coralligenous ecosystem marine animal forests in Marine Animal Forests. Springer, Berlin, pp 1–28 (2016).

33.
Coma, R., Pola, E., Ribes, M. & Zabala, M. Long-term assessment of temperate octocoral mortality patterns, protected vs. unprotected areas. Ecol. Appl. 14, 1466–1478 (2004).
Article  Google Scholar 

34.
Salomidi, M. et al. Assessment of goods and services, vulnerability, and conservation status of European seabed biotopes: a stepping stone towards ecosystem-based marine spatial management. Mediterr. Mar. Sci. 13, 49–88 (2012).
Article  Google Scholar 

35.
Piazzi, L., La Manna, G., Cecchi, E., Serena, F. & Ceccherelli, G. Protection changes the relevancy of scales of variability in coralligenous assemblages. Estuar. Coast. Shelf Sci. 175, 62–69 (2016).
ADS  Article  Google Scholar 

36.
Cerrano, C. et al. A catastrophic mass-mortality episode of gorgonians and other organisms in the Ligurian Sea (North-western Mediterranean), summer 1999. Ecol. Lett. 3, 284–293 (2000).
Article  Google Scholar 

37.
Garrabou, J. et al. Mass mortality in Northwestern Mediterranean rocky benthic communities: Effects of the 2003 heat wave. Glob. Chang. Biol. 15, 1090–1103 (2009).
ADS  Article  Google Scholar 

38.
Gatti, G. et al. Ecological change, sliding baselines and the importance of historical data: Lessons from combing observational and quantitative data on a temperate reef over 70 years. PLoS ONE 10, e0118581 (2015).
Article  CAS  PubMed  PubMed Central  Google Scholar 

39.
Coma, R. et al. Consequences of a mass mortality in populations of Eunicella singularis (Cnidaria: Octocorallia) in Menorca (NW Mediterranean). Mar. Ecol. Prog. Ser. 327, 51–60 (2006).
ADS  Article  Google Scholar 

40.
Huete-Stauffer, C. et al. Paramuricea clavata (Anthozoa, Octocorallia) loss in the Marine Protected Area of Tavolara (Sardinia, Italy) due to a mass mortality event. Mar. Ecol. 32, 107–116 (2011).
ADS  Article  Google Scholar 

41.
Martin, Y., Bonnefont, J. L. & Chancerelle, L. Gorgonians mass mortality during the 1999 late summer in French Mediterranean coastal waters: the bacterial hypothesis. Water Res. 36, 779–782 (2001).
Article  Google Scholar 

42.
Crisci, C., Bensoussan, N., Romano, J. C. & Garrabou, J. Temperature anomalies and mortality events in marine communities: Insights on factors behind differential mortality impacts in the NW Mediterranean. PLoS ONE 6, e23814 (2011).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

43.
Torrents, O., Tambutté, E., Caminiti, N. & Garrabou, J. Upper thermal thresholds of shallow vs deep populations of the precious Mediterranean red coral Corallium rubrum (L.): Assessing the potential effects of warming in the NW Mediterranean. J. Exp. Mar. Biol. Ecol. 357, 7–19 (2008).
Article  Google Scholar 

44.
Pagès-Escolà, M. et al. Divergent responses to warming of two common co-occurring Mediterranean bryozoans. Sci. Rep. 8, 17455 (2018).
ADS  Article  CAS  PubMed  PubMed Central  Google Scholar 

45.
Gómez-Gras, D. et al. Response diversity in Mediterranean coralligenous assemblages facing climate change: Insights from a multispecific thermotolerance experiment. Ecol. Evol. 9, 4168–4180 (2019).
Article  PubMed  PubMed Central  Google Scholar 

46.
Galli, G., Solidoro, C. & Lovato, T. Marine heat waves hazard 3D maps and the risk for low motility organisms in a warming Mediterranean Sea. Front. Mar. Sci. 4, 136 (2017).
Article  Google Scholar 

47.
Pansch, C. et al. Heat waves and their significance for a temperate benthic community: A near-natural experimental approach. Glob. Chang. Biol. 24, 4357–4367 (2018).
ADS  Article  PubMed  Google Scholar 

48.
Hobday, A. J. et al. Categorizing and naming Marine Heatwaves. Oceanography 31, 162–173 (2018).
Article  Google Scholar 

49.
Roberts, S. D., Van Ruth, P. D., Wilkinson, C., Bastianello, S. S. & Bansemer, M. S. Marine heatwave, harmful algae blooms and an extensive fish kill event during 2013 in South Australia. Front. Mar. Sci. 6, 610 (2019).
Article  Google Scholar 

50.
Smale, D. A. & Wernberg, T. Satellite-derived SST data as a proxy for water temperature in nearshore benthic ecology. Mar. Ecol. Prog. Ser. 387, 27–37 (2009).
ADS  Article  Google Scholar 

51.
Bensoussan, N., Romano, J. C., Harmelin, J. G. & Garrabou, J. High resolution characterization of northwest Mediterranean coastal waters thermal regimes: To better understand responses of benthic communities to climate change. Estuar. Coast. Shelf Sci. 87, 431–441 (2010).
ADS  Article  Google Scholar 

52.
Bruno, J. F., Carr, L. A. & O’Connor, M. I. Exploring the role of temperature in the ocean through metabolic scaling. Ecology 96, 3126–3140 (2015).
Article  PubMed  Google Scholar 

53.
Silbiger, N. J., Goodbody-Gringley, G., Bruno, J. F. & Putnam, H. M. Comparative thermal performance of the reef-building coral Orbicella franksi at its latitudinal range limits. Mar. Biol. 166, 126 (2019).
Article  Google Scholar 

54.
Linares, C., Cebrian, E., Kipson, S. & Garrabou, J. Does thermal history influence the tolerance of temperate gorgonians to future warming?. Mar. Environ. Res. 89, 45–52 (2013).
CAS  Article  PubMed  Google Scholar 

55.
Piazzi, L. et al. What’s in an index? Comparing the ecological information provided by two indices to assess the status of coralligenous reefs in the NW Mediterranean Sea. Aquat. Conserv. Mar. Freshw. Ecosyst. 27, 1091–1100 (2017).
Article  Google Scholar 

56.
Ceccherelli G., et al. Vertical gradient and spatial variability of Coralligenous reefs in Sardinia: the interactive effect of depth and location. S.It.E. (Italian Society of Ecology) conference (Ferrara, Italy 10–12 September 2019) https://www.ecologia.it/wp-content/uploads/2019/09/AbstractBook-SItE-Ferrara-2019.pdf, 124 (2019).

57.
Holbrook, N. J. et al. A global assessment of marine heatwaves and their drivers. Nat. Commun. 10, 2624 (2019).
ADS  Article  CAS  PubMed  PubMed Central  Google Scholar 

58.
Smit, A. J. et al. A coastal seawater temperature dataset for biogeographical studies: Large biases between in situ and remotely-sensed data sets around the coast of South Africa. PLoS ONE 8, e81944 (2013).
ADS  Article  CAS  PubMed  PubMed Central  Google Scholar 

59.
Brewin, R. J. W. et al. Evaluating operational AVHRR sea surface temperature data at the coastline using benthic temperature loggers. Remote Sens. 10, 925 (2018).
ADS  Article  Google Scholar 

60.
Coma, R. et al. Global warming-enhanced stratification and mass mortality events in the Mediterranean. Proc. Natl. Acad. Sci. 106, 6176–6181 (2009).
ADS  CAS  Article  PubMed  Google Scholar 

61.
Verdura, J. et al. Biodiversity loss in a Mediterranean ecosystem due to an extreme warming event unveils the role of an engineering gorgonian species. Sci. Rep. 9, 5911 (2019).
ADS  Article  CAS  PubMed  PubMed Central  Google Scholar 

62.
Kendrick, G. A. et al. A systematic review of how multiple stressors from an extreme event drove ecosystem-wide loss of resilience in an iconic seagrass community. Front. Mar. Sci. 6, 455 (2019).
Article  Google Scholar 

63.
Kim, J. B., Park, J. I., Jung, C. S., Lee, P. Y. & Lee, K. S. Distributional range extension of the seagrass Halophila nipponica into coastal waters off the Korean peninsula. Aquat. Bot. 90, 269–272 (2009).
Article  Google Scholar 

64.
Johnson, C. R. et al. Climate change cascades: shifts in oceanography, species’ ranges and subtidal marine community dynamics in eastern Tasmania. J. Exp. Mar. Bio. Ecol. 400, 17–32 (2011).
Article  Google Scholar 

65.
Saha, M. et al. Response of foundation macrophytes to near-natural simulated marine heatwaves. Glob. Chang. Biol. 26, 417–430 (2020).
ADS  Article  PubMed  Google Scholar 

66.
Garrabou, J. et al. Collaborative database to track mass mortality events in the Mediterranean Sea. Front. Mar. Sci. 6, 707 (2019).
Article  Google Scholar 

67.
Hartley, S. & Kunin, W. E. Scale Dependency of rarity, extinction risk, and conservation priority. Conserv. Biol. 17, 1559–1570 (2003).
Article  Google Scholar 

68.
Bavestrello, G. et al. Mass mortality of Paramuricea clavata (Anthozoa, Cnidaria) on Portofino Promontory cliffs, Ligurian Sea. Mediterranean Sea. Mar. Life 4, 15–19 (1994).
Google Scholar 

69.
Ponti, M. et al. Ecological shifts in mediterranean coralligenous assemblages related to gorgonian forest loss. PLoS ONE 9, e102782 (2014).
ADS  Article  CAS  PubMed  PubMed Central  Google Scholar 

70.
Lombardi, C., Cocito, S., Occhipinti-Ambrogi, A. & Hiscock, K. The influence of seawater temperature on zooid size and growth rate in Pentapora fascialis (Bryozoa: Cheilostomata). Mar. Biol. 149, 1103–1109 (2006).
Article  Google Scholar 

71.
Novosel, M., Požar-Domac, A. & Pasarić, M. Diversity and distribution of the bryozoa along underwater cliffs in the Adriatic sea with special reference to thermal regime. Mar. Ecol. 25, 155–170 (2004).
ADS  Article  Google Scholar 

72.
Rindi, F. et al. Coralline algae in a changing Mediterranean Sea: how can we predict their future, if we do not know their present?. Front. Mar. Sci. 6, 2 (2019).
Article  Google Scholar 

73.
Crisci, C. et al. Regional and local environmental conditions do not shape the response to warming of a marine habitat-forming species. Sci. Rep. 7, 5069 (2017).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

74.
Piazzi, L. et al. STAR: An integrated and standardized procedure to evaluate the ecological status of coralligenous reefs. Aquat. Conserv. Mar. Freshw. Ecosyst. 29, 189–201 (2019).
Article  Google Scholar 

75.
Piazzi, L. et al. Integration of ESCA index through the use of sessile invertebrates. Sci. Mar. 81, 283–290 (2017).
Article  Google Scholar 

76.
Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed effects models and extensions in ecology with R (Springer, Berlin, 2009).
Google Scholar 

77.
Hastie, T. & Tibshirani, R. Generalized additive models (Taylor and Francis Ltd, New York, 1990).
Google Scholar  More

1.
Lochmiller, R. L. & Deerenberg, C. Trade-offs in evolutionary immunology: Just what is the cost of immunity?. Oikos 88(1), 87–98 (2000).
Article  Google Scholar 
2.
Martin, L. B., Scheuerlein, A. & Wikelski, M. Immune activity elevates energy expenditure of house sparrows: A link between direct and indirect costs?. Proc. R. Soc. Lond. B 270(1511), 153–158 (2003).
Article  Google Scholar 

3.
Klasing, J.C. The costs of immunity. Acta Zool. Sin. 50, 961–969 (2004).

4.
Hasselquist, D. & Nilsson, J. Å. Physiological mechanisms mediating costs of immune responses: What can we learn from studies of birds?. Anim. Behav. 83(6), 1303–1312 (2012).
Article  Google Scholar 

5.
Demas, G. E., Chefer, V., Talan, M. I. & Nelson, R. J. Metabolic costs of mounting an antigen-stimulated immune response in adult and aged C57BL/6J mice. Am. J. Physiol 273, R1631–R1637 (1997).
CAS  PubMed  PubMed Central  Google Scholar 

6.
Otálora-Ardila, A., Herrera, M. L. G., Flores-Martinez, J. J. & Welch, K. C. Jr. Metabolic cost of the activation of immune response in the fish-eating myotis (Myotis vivesi): The effects of inflammation and the acute phase response. PLoS ONE 11, e0164938 (2016).
PubMed  PubMed Central  Article  CAS  Google Scholar 

7.
Costantini, D. & Møller, A. P. Does immune response cause oxidative stress in birds? A meta-analysis. Comp. Biochem. Physiol. A 153, 339–344 (2009).
Article  CAS  Google Scholar 

8.
Canale, C. I. & Henry, P. Y. Energetic costs of the immune response and torpor use in a primate. Funct. Ecol. 25, 557–565 (2011).
Article  Google Scholar 

9.
Wikelski, M. et al. Costs of migration in free-flying songbirds. Nature 423(6941), 704–704 (2003).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

10.
Jenni-Eiermann, S., Jenni, L., Smith, S. & Costantini, D. Oxidative stress in endurance flight: An unconsidered factor in bird migration. PLoS ONE 9, e97650 (2014).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

11.
Costantini, D., Lindecke, O., Petersons, G. & Voigt, C. C. Migratory flight imposes oxidative stress in bats. Curr. Zool. 65, 147–153 (2019).
PubMed  Article  Google Scholar 

12.
Troxell, S. A., Holderied, M. W., Pētersons, G. & Voigt, C. C. Nathusius’ bats optimize long-distance migration by flying at maximum range speed. J. Exp. Biol. 222, jeb176396 (2019).

13.
Dierschke, V., Mendel, B. & Schmaljohann, H. Differential timing of spring migration in northern wheatears Oenanthe oenanthe: Hurried males or weak females?. Behav. Ecol. Sociobiol. 57, 470–480 (2005).
Article  Google Scholar 

14.
Hasselquist, D. Comparative immunoecology in birds: Hypotheses and tests. J. Ornith. 148(2), 571–582 (2007).
Article  Google Scholar 

15.
Buehler, D. M. & Piersma, T. Travelling on a budget: predictions and ecological evidence for bottlenecks in the annual cycle of long-distance migrants. Philos. Trans. R. Soc. B 363(1490), 247–266 (2007).
Article  Google Scholar 

16.
Svensson, E., Råberg, L., Koch, C. & Hasselquist, D. Energetic stress, immunosuppression and the costs of an antibody response. Funct. Ecol. 12(6), 912–919 (1998).
Article  Google Scholar 

17.
Owen, J. C. & Moore, F. R. Seasonal differences in immunological condition of three species of thrushes. Condor 108(2), 389–398 (2006).
Article  Google Scholar 

18.
Altizer, S. et al. Animal migration and infectious disease risk. Science 331(6015), 296–302 (2011).
ADS  CAS  PubMed  Article  Google Scholar 

19.
Eikenaar, C., Isaksson, C. & Hegemann, A. A hidden cost of migration? Innate immune function versus antioxidant defense. Ecol. Evol. 8(5), 2721–2728 (2018).
PubMed  PubMed Central  Article  Google Scholar 

20.
Weber, T. P. & Stilianakis, N. I. Ecologic immunology of avian influenza (H5N1) in migratory birds. Emerg. Infect. Dis. 13(8), 1139 (2007).
PubMed  PubMed Central  Article  Google Scholar 

21.
Owen, J. C. & Moore, F. R. Relationship between energetic condition and indicators of immune function in thrushes during spring migration. Can. J. Zool. 7, 638–647 (2008).
Article  CAS  Google Scholar 

22.
Tobler, M., Ballen, C., Healey, M., Wilson, M. & Olsson, M. Oxidant trade-offs in immunity: An experimental test in a lizard. PLoS ONE 10(5), e0126155 (2015).
PubMed  PubMed Central  Article  CAS  Google Scholar 

23.
Wang, D., Malo, D. & Hekimi, S. Elevated mitochondrial reactive oxygen species generation affects the immune response via hypoxia-inducible factor-1 in long-lived Mclk1+/− mouse mutants. J. Immunol. 184, 582–590 (2009).
PubMed  Article  CAS  Google Scholar 

24.
Case, A. J. et al. Elevated mitochondrial superoxide disrupts normal T cell development, impairing adaptive immune responses to an influenza challenge. Free Radic. Biol. Med. 50, 448–458 (2011).
CAS  PubMed  Article  Google Scholar 

25.
Møller, A. P. & Erritzøe, J. Host immune defence and migration in birds. Evol. Ecol. 12(8), 945–953 (1998).
Article  Google Scholar 

26.
Popa-Lisseanu, A. G. & Voigt, C. C. Bats on the move. J. Mammal. 90(6), 1283–1289 (2009).
Article  Google Scholar 

27.
Krauel, J.J., & McCracken, G. F. Recent advances in bat migration research. in Bat Evolution, Ecology, and Conservation 293–313. (Springer, New York, 2013).

28.
Steffens, R., Zöphel, U. & Brockmann, D. 40th Anniversary Bat Marking Centre Dresden—Evaluation of Methods and Overview of Results. (Sächsisches Landesamt für Umwelt und Geologie, Dresden, 2004).

29.
Roberts, B. J., Catterall, C. P., Eby, P. & Kanowski, J. Long-distance and frequent movements of the flying-fox Pteropus poliocephalus: Implications for management. PLoS ONE 7(8), e42532 (2012).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

30.
Speakman, J. R., Thomas, D. W., Kunz, T. H., & Fenton, M. B. Physiological ecology and energetics of bats. in Bat Ecology (eds. Kunz, T.H. & Fenton M.B.), 430–490 (Chicago University Press, Chicago, 2003).

31.
Voigt, C. C., Borrisov, I. M. & Voigt-Heucke, S. L. Terrestrial locomotion imposes high metabolic requirements on bats. J. Exp. Biol. 215(24), 4340–4344 (2012).
CAS  PubMed  Article  PubMed Central  Google Scholar 

32.
McGuire, L. P., Jonasson, K. A., & Guglielmo, C.G. Bats on a budget: torpor-assisted migration saves time and energy. PLoS ONE9(12) (2014).

33.
Brunet-Rossinni, A. K. Reduced free-radical production and extreme longevity in the little brown bat (Myotis lucifugus) versus two non-flying mammals. Mech. Ageing Dev. 125, 11–20 (2004).
CAS  PubMed  Article  PubMed Central  Google Scholar 

34.
Filho, D. W., Althoff, S. L., Dafré, A. L. & Boveris, A. Antioxidant defenses, longevity and ecophysiology of South American bats. Comp. Biochem. Physiol. Part C 146, 214–220 (2007).
Google Scholar 

35.
Salmon, A. B. et al. The long lifespan of two bat species is correlated with resistance to protein oxidation and enhanced protein homeostasis. FASEB J 23, 2317–2326 (2009).
CAS  PubMed  PubMed Central  Article  Google Scholar 

36.
Zhang, G. et al. Comparative analysis of bat genomes provides insight into the evolution of flight and immunity. Science 339, 456–460 (2013).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

37.
Schneeberger, K., Czirják, G. Á. & Voigt, C. C. Frugivory is associated with low measures of plasma oxidative stress and high antioxidant concentration in free-ranging bats. Naturwissenschaften 101(4), 285–290 (2014).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

38.
Schneeberger, K., Czirják, G. Á. & Voigt, C. C. Inflammatory challenge increases measures of oxidative stress in a free-ranging, long-lived mammal. J. Exp. Biol. 216, 4514–4519 (2013).
CAS  PubMed  Article  PubMed Central  Google Scholar 

39.
Costantini D, Czirják, G. Á., Bustamante, P., Bumrungsri, S., & Voigt, C.C. Impact of land use on an insectivorous tropical bat: the importance of mercury, physio-immunology and trophic position. Sci. Total Environ.671, 1077–1085 (2019).

40.
Wibbelt, G., Moore, M. S., Schountz, T. & Voigt, C. C. Emerging diseases in Chiroptera: Why bats?. Biol. Lett. 6, 438–440 (2010).
PubMed  PubMed Central  Article  Google Scholar 

41.
Luis, A. D. et al. A comparison of bats and rodents as reservoirs of zoonotic viruses: Are bats special?. Proc. R. Soc. B 280(1756), 20122753 (2013).
PubMed  Article  PubMed Central  Google Scholar 

42.
Olival, K. J. et al. Host and viral traits predict zoonotic spillover from mammals. Nature 546(7660), 646–650 (2017).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

43.
Drexler, J. F. et al. Bats host major mammalian paramyxoviruses. Nat. Commun. 3, 796 (2012).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

44.
Hayman, D. T. S. et al. Ecology of zoonotic infectious diseases in bats: Current knowledge and future directions. Zoonoses Public Health 60(1), 2–21 (2013).
CAS  PubMed  Article  PubMed Central  Google Scholar 

45.
Pētersons, G. Seasonal migrations of northeastern populations of Pipistrellus nathusii. Myotis 41–42, 29–56 (2004).
Google Scholar 

46.
Lee, K. A. Linking immune defenses and life history at the levels of the individual and the species. Integr. Comp. Biol. 46(6), 1000–1015 (2006).
CAS  PubMed  Article  PubMed Central  Google Scholar 

47.
Fritze, M., et al. Immune response of hibernating European bats to a fungal challenge. Biol. Open8, bio046078 (2019).

48.
Stockmaier, S., Dechmann, D. K., Page, R. A. & O’Mara, M. T. No fever and leukocytosis in response to a lipopolysaccharide challenge in an insectivorous bat. Biol. Lett. 11, 4–7 (2015).
Article  CAS  Google Scholar 

49.
Weise, P., Czirják, G. Á., Lindecke, O., Bumrungsri, S. & Voigt, C. C. Simulated bacterial infection disrupts the circadian fluctuation of immune cells in wrinkle-lipped bats (Chaereophon plicatus). PeerJ 5, e3570 (2017).
PubMed  PubMed Central  Article  CAS  Google Scholar 

50.
Hegemann, A. et al. Immune function and blood parasite infections impact stopover ecology in passerine birds. Oecologia 188(4), 1011–1024 (2018).
ADS  PubMed  PubMed Central  Article  Google Scholar 

51.
Eikenaar, C. & Hegemann, A. Migratory common blackbirds have lower innate immune function during autumn migration than resident conspecifics. Biol. Lett. 12, 20160078 (2016).
PubMed  PubMed Central  Article  CAS  Google Scholar 

52.
Owen, J. C. & Moore, F. R. Swainson’s thrushes in migratory disposition exhibit reduced immune function. J. Ethol. 26(3), 383–388 (2008).
Article  Google Scholar 

53.
Sikes, R. S. & Gannon, W. L. Guidelines of the American Society of Mammalogists for the use of wild mammals in research. J. Mammal. 92, 235–253 (2011).
Article  Google Scholar 

54.
Kozak, W.I.E.S., Conn, C.A. & Kluger, M. J.Lipopolysaccharide induces fever and depresses locomotor activity in unrestrained mice. Am. J. Physiol. Reg. Integr. Comp. Physiol.266(1), R125–R135 (1994).

55.
Schneeberger, K., Czirják, G. Á. & Voigt, C. C. Measures of the constitutive immune system are linked to diet and roosting habits of neotropical bats. PLoS ONE 8(1), e54023 (2013).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

56.
Cray, C., Zaias, J. & Altman, N. H. Acute phase response in animals: A review. Comp. Med. 59, 517–526 (2009).
CAS  PubMed  PubMed Central  Google Scholar 

57.
Field, K. A. et al. The white-nose syndrome transcriptome: Activation of anti-fungal host responses in wing tissue of hibernating little brown myotis. PLoS Pathog. 11(10), e1005168 (2015).
PubMed  PubMed Central  Article  CAS  Google Scholar 

58.
Costantini, D., Dell’Ariccia, G. & Lipp, H.-P. Long flights and age affect oxidative status of homing pigeons (Columba livia). J. Exp. Biol. 211, 377–381 (2008).
CAS  PubMed  Article  Google Scholar 

59.
Kuznetsova, A., Brockhoff, P. B. & Bojesen Christensen, R. H. Package ‘lmerTest’. CRAN. https://cran.r-project.org/web/packages/lmerTest/lmerTest.pdf (2019).

60.
Zeileis, A., Cribari-Neto, F., Gruen, B., Kosmidis, I., Simas, A. B., & Rocha, A. V. Package ‘betareg’. CRAN, https://cran.r-project.org/web/packages/betareg/betareg.pdf (2020). More

1.
Walther, G. et al. Ecological responses to recent climate change. Nature 416, 389–395. https://doi.org/10.1038/416389a (2002).
ADS  CAS  Article  PubMed  Google Scholar 
2.
Pereira, H. M. et al. Scenarios for global biodiversity in the 21st century. Science 330, 1496–1501. https://doi.org/10.1126/science.1196624 (2010).
ADS  CAS  Article  PubMed  Google Scholar 

3.
Carter, S. K., Saenz, D. & Rudolf, V. H. W. Shifts in phenological distributions reshape interaction potential in natural communities. Ecol. Lett. 21, 1143–1151. https://doi.org/10.1111/ele.13081 (2018).
Article  PubMed  Google Scholar 

4.
Kahl, S. M., Lenhard, M. & Joshi, J. Compensatory mechanisms to climate change in the widely distributed species Silene vulgaris. J. Ecol. 107, 1918–1930. https://doi.org/10.1111/1365-2745.13133 (2019).
Article  Google Scholar 

5.
Easterling, D. R. et al. Climate extremes: observations, modeling, and impacts. Science 289, 2068–2074. https://doi.org/10.1126/science.289.5487.2068 (2000).
ADS  CAS  Article  PubMed  Google Scholar 

6.
IPCC. Global Warming of 1.5°C: An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty https://www.ipcc.ch/sr15/ (2018).

7.
Wolkovich, et al. Warming experiments underpredict plant phenological responses to climate change. Nature 485, 494–497. https://doi.org/10.1038/nature11014 (2012).
ADS  CAS  Article  PubMed  Google Scholar 

8.
Ahammed, G. J., Li, X., Wan, H., Zhou, G. & Cheng, Y. SlWRKY81 reduces drought tolerance by attenuating proline biosynthesis in tomato. Sci. Hortic. 270, 109444. https://doi.org/10.1016/j.scienta.2020.109444 (2020).
CAS  Article  Google Scholar 

9.
Dorji, T. et al. Impacts of climate change on flowering phenology and production in alpine plants: the importance of end of flowering. Agric. Ecosyst. Environ. 291, 106795. https://doi.org/10.1016/j.agee.2019.106795 (2020).
Article  Google Scholar 

10.
Bertin, R. I. Plant phenology and distribution in relation to recent climate change. J. Torrey Bot. Soc. 135, 126–146. https://doi.org/10.3159/07-RP-035R.1 (2008).
Article  Google Scholar 

11.
Lawson, C. R., Vindenes, Y., Bailey, L. & van de Poll, M. Environmental variation and population responses to global change. Ecol. Lett. 18, 724–736. https://doi.org/10.1111/ele.12437 (2015).
Article  PubMed  Google Scholar 

12.
Sherry, R. A. et al. Divergence of reproductive phenology under climate warming. Proc. Nat. Acad. Sci. USA 104, 198–202. https://doi.org/10.1073/pnas.0605642104 (2007).
ADS  CAS  Article  PubMed  Google Scholar 

13.
Nicotra, A. B. et al. Plant phenotypic plasticity in a changing climate. Trends Plant Sci. 15, 684–692. https://doi.org/10.1016/j.tplants.2010.09.008 (2010).
CAS  Article  PubMed  Google Scholar 

14.
Prevéy, J. S. et al. Warming shortens flowering seasons of tundra plant communities. Nat. Ecol. Evol. 3, 45–52. https://doi.org/10.1038/s41559-018-0745-6 (2019).
Article  PubMed  Google Scholar 

15.
Ahammed, G. J., Li, X., Liu, A. & Chen, S. Physiological and defense responses of tea plants to elevated CO2: a review. Front. Plant Sci. 11, 305. https://doi.org/10.3389/fpls.2020.00305 (2020).
Article  PubMed  PubMed Central  Google Scholar 

16.
Fogelström, E. & Ehrlén, J. Phenotypic but not genotypic selection for earlier flowering in a perennial herb. J. Ecol. 107, 2650–2659. https://doi.org/10.1111/1365-2745.13240 (2019).
Article  Google Scholar 

17.
Badeck, F. et al. Responses of spring phenology to climate change. New Phytol. 162, 295–309. https://doi.org/10.1111/j.1469-8137.2004.01059.x (2004).
Article  Google Scholar 

18.
Ehrlén, J., Raabova, J. & Dahlgren, J. P. Flowering schedule in a perennial plant: life-history trade-offs, seed predation, and total offspring fitness. Ecology 96, 2280–2288. https://doi.org/10.1890/14-1860.1 (2015).
Article  PubMed  Google Scholar 

19.
Körner, C. & Basler, D. Phenology under global warming. Science 327, 1461–1462. https://doi.org/10.1126/science.1186473 (2010).
ADS  Article  PubMed  Google Scholar 

20.
Gerst, K. L., Rossington, N. L. & Mazer, S. J. Phenological responsiveness to climate differs among four species of Quercus in North America. J. Ecol. 105, 1610–1622. https://doi.org/10.1111/1365-2745.12774 (2017).
Article  Google Scholar 

21.
Grossiord, C. et al. Precipitation, not air temperature, drives functional responses of trees in semi-arid ecosystems. J. Ecol. 105, 163–175. https://doi.org/10.1111/1365-2745.12662 (2017).
Article  Google Scholar 

22.
Crimmins, T. M., Crimmins, M. A. & Bertelsen, C. D. Onset of summer flowering in a ‘Sky Island’ is driven by monsoon moisture. New Phytol. 191, 468–479. https://doi.org/10.1111/j.1469-8137.2011.03705.x (2011).
Article  PubMed  Google Scholar 

23.
Meng, F. D. et al. Changes in flowering functional group affect responses of community phenological sequences to temperature change. Ecology 98, 734–740. https://doi.org/10.1002/ecy.1685 (2017).
CAS  Article  PubMed  Google Scholar 

24.
Dunne, J. A., Harte, J. & Taylor, K. J. Subalpine meadow flowering phenology responses to climate change: integrating experimental and gradient methods. Ecol. Monogr. 73, 69–86. https://doi.org/10.1890/0012-9615(2003)073[0069:SMFPRT]2.0.CO;2 (2003).
Article  Google Scholar 

25.
Gugger, S., Kesselring, H., Stöcklin, J. & Hamann, E. Lower plasticity exhibited by high- versus mid- elevation species in their phenological responses to manipulated temperature and drought. Annu. Bot. 116, 953–962. https://doi.org/10.1093/aob/mcv155 (2015).
Article  Google Scholar 

26.
Richardson, A. D. et al. Ecosystem warming extends vegetation activity but heightens vulnerability to cold temperatures. Nature 560, 368–371. https://doi.org/10.1038/s41586-018-0399-1 (2018).
ADS  CAS  Article  PubMed  Google Scholar 

27.
Fenner, M. The phenology of growth and reproduction in plants. Perspect. Plant Ecol. 1, 78–91. https://doi.org/10.1078/1433-8319-00053 (1998).
Article  Google Scholar 

28
Lee, H. & Kang, H. Temperature-driven changes of pollinator assemblage and activity of Megaleranthis saniculifolia (Ranunculaceae) at high altitudes on Mt. Sobaeksan, South Korea. J. Ecol. Environ. 42, 31. https://doi.org/10.1186/s41610-018-0092-1 (2018).
Article  Google Scholar 

29.
Yu, H., Luedeling, E. & Xu, J. Winter and spring warming result in delayed spring phenology on the Tibetan Plateau. Proc. Nat. Acad. Sci. USA 107, 22151–22156. https://doi.org/10.1073/pnas.1012490107 (2010).
ADS  Article  PubMed  Google Scholar 

30.
Cook, B. I., Wolkovich, E. M. & Parmesan, C. Divergent responses to spring and winter warming drive community level flowering trends. Proc. Nat. Acad. Sci. USA 109, 9000–9005. https://doi.org/10.1073/pnas.1118364109 (2012).
ADS  Article  PubMed  Google Scholar 

31.
Meier, A. J., Bratton, S. P. & Duffy, D. C. Possible ecological mechanisms for loss of vernal-herb diversity in logged eastern deciduous forests. Ecol. Appl. 5, 935–946. https://doi.org/10.2307/2269344 (1995).
Article  Google Scholar 

32.
Sung, J. et al. Growth environment and vegetation structure of native habitat of Corydalis cornupetala. Korean J. Environ. Ecol. 27, 271–279 (2013).
Google Scholar 

33.
Augspurger, C. K. & Salk, C. F. Constraints of cold and shade on the phenology of spring ephemeral herb species. J. Ecol. 105, 246–254. https://doi.org/10.1111/1365-2745.12651 (2017).
CAS  Article  Google Scholar 

34.
Rizhsky, L. et al. When defense pathways collide: the response of Arabidopsis to a combination of drought and heat stress. Plant Physiol. 134, 1683–1696. https://doi.org/10.1104/pp.103.033431 (2004).
CAS  Article  PubMed  PubMed Central  Google Scholar 

35.
Su, Z. et al. Flower development under drought stress: morphological and transcriptomic analyses reveal acute response of long-term acclimation in Arabidopsis. Plant Cell 25, 3785–3807. https://doi.org/10.1105/tpc.113.115428 (2013).
CAS  Article  PubMed  PubMed Central  Google Scholar 

36.
Vallales, F., Wright, S. J., Lasso, E., Kitajima, K. & Pearcy, R. W. Plastic phenotypic response to light of 16 congeneric shrubs from a Panamanian rainforest. Ecology 81, 1925–1936. https://doi.org/10.1890/0012-9658(2000)081[1925:PPRTLO]2.0.CO;2 (2000).
Article  Google Scholar 

37.
Valladares, F., Sanchez-Gomez, D. & Zavala, M. A. Quantitative estimation of phenotypic plasticity: bridging the gap between the evolutionary concept and its ecological applications. J. Ecol. 94, 1103–1116. https://doi.org/10.1111/j.1365-2745.2006.01176.x (2006).
Article  Google Scholar 

38.
CaraDonna, P. J., Iler, A. M. & Inouye, D. W. Shifts in flowering phenology reshape a subalpine plant community. Proc. Nat. Acad. Sci. USA 111, 13. https://doi.org/10.1073/pnas.1323073111 (2014).
CAS  Article  Google Scholar 

39.
Forrest, J. & Miller-Rushing, A. J. Toward a synthetic understanding of the role of phenology in ecology and evolution. Philos. Trans. Biol. Sci. 365, 3101–3112. https://doi.org/10.1098/rstb.2010.0145 (2010).
Article  Google Scholar 

40.
Richardson, A. D. et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agric. For. Meteorol. 169, 156–173. https://doi.org/10.1016/j.agrformet.2012.09.012 (2013).
ADS  Article  Google Scholar 

41.
Richards, F. J. A flexible growth function for empirical use. J. Exp. Bot. 29, 290–300. https://doi.org/10.1093/jxb/10.2.290 (1959).
Article  Google Scholar 

42.
Barnabás, B., Jäger, K. & Fehér, A. The effect of drought and heat stress on reproductive processes in cereals. Plant Cell Environ. 31, 11–38. https://doi.org/10.1111/j.1365-3040.2007.01727.x (2008).
CAS  Article  PubMed  Google Scholar 

43.
Limousin, J.-M. et al. Morphological and phenological shoot plasticity in a Mediterranean evergreen oak facing long-term increased drought. Oecologia 169, 565–577. https://doi.org/10.1007/s00442-011-2221-8 (2012).
ADS  Article  PubMed  Google Scholar 

44.
Li, X. et al. Exogeneous melatonin improves tea quality under moderate high temperatures by increasing epigallacatechin-3-gallate and theanine biosynthesis in Camellia sinensis L. J. Plant Physiol. 253, 153273. https://doi.org/10.1016/j.jplph.2020.153273 (2020).
CAS  Article  PubMed  Google Scholar 

45.
Wheeler, J. A. et al. The snow and the willows: earlier spring snowmelt reduces performance in the low-lying alpine shrub Salix herbacea. J. Ecol. 104, 1041–1050. https://doi.org/10.1111/1365-2745.12579 (2016).
CAS  Article  Google Scholar 

46.
Llorens, L. & Peñuelas, J. Experimental evidence of future drier and warmer conditions affecting flowering of two co-occurring Mediterranean shrubs. Int. J. Plant Sci. 166, 235–245. https://doi.org/10.1086/427480 (2005).
Article  Google Scholar 

47.
Bernal, M., Estiarte, M. & Penuelas, J. Drought advances spring growth phenology of the Mediterranean shrub Erica multiflora. Plant Biol. 13, 252–257. https://doi.org/10.1111/j.1438-8677.2010.00358.x (2011).
CAS  Article  PubMed  Google Scholar 

48.
Shavrukov, Y. et al. Early flowering as a drought escape mechanism in plants: how can it aid wheat production?. Front. Plant Sci. 8, 1950. https://doi.org/10.3389/fpls.2017.01950 (2017).
Article  PubMed  PubMed Central  Google Scholar 

49.
Sherry, R. A. et al. Changes in duration of reproductive phases and lagged phenological response to experimental climate warming. Plant Ecol. Divers. 4, 23–35. https://doi.org/10.1080/17550874.2011.557669 (2011).
Article  Google Scholar 

50.
Prasad, P. V. V., Pisipati, S. R., Momčilović, I. & Ristic, Z. Independent and combined effects of high temperature and drought stress during grain filling on plant yield and chloroplast EF-Tu expression in spring wheat. J. Agric. Crop Sci. 197(430–441), 2011. https://doi.org/10.1111/j.1439-037X.2011.00477.x (2011).
CAS  Article  Google Scholar 

51.
Zong, J.-M. et al. The AaDREB1 transcription factor from the cold-tolerant plant Adonis amurensis enhances abiotic stress tolerance in transgenic plant. Int. J. Mol. Sci. 17, 611. https://doi.org/10.3390/ijms17040611 (2016).
ADS  CAS  Article  PubMed Central  Google Scholar 

52.
Żuraw, B., Rysiak, K. & Szymczak, G. Ecology and morphology of the flowers of Hepatica nobilisSchreb. (Ranunculaceae). Mod. Phytomorphol. 4, 39–43. https://doi.org/10.5281/zenodo.161177 (2013).
Article  Google Scholar 

53.
Kalliovirta, M., Ryttäri, T. & Heikkinen, R. K. Population structure of a threatened plant, Pulsatilla patens, in boreal forests: modeling relationships to overgrowth and site closure. Biodivers. Conserv. 15, 3095–3108. https://doi.org/10.1007/s10531-005-5403-z (2006).
Article  Google Scholar 

54
Inghe, O. & Tamm, C. O. Survival and flowering of perennial herbs. IV. The behavior of Hepatica nobilis and Sanicula europaea on permanent plots during 1943–1981. Oikos 45, 400–420. https://doi.org/10.2307/3565576 (1985).
Article  Google Scholar 

55.
Lee, T. B. Colored Flora of Korea (Hyangmunsa, Seoul, 2003).
Google Scholar 

56.
Kang, H. & Jang, S. Flowering patterns among angiosperm species in Korea: diversity and constraints. J. Plant Biol. 47, 348–355. https://doi.org/10.1007/BF03030550 (2004).
Article  Google Scholar 

57.
Culley, T. M. Reproductive biology and delayed selfing in Viola pubscens (Violaceae), an understory herb with chasmogamous and cleistogamous flowers. Int. J. Plant Sci. 163, 113–122. https://doi.org/10.1086/324180 (2002).
Article  Google Scholar 

58.
R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, https://www.R-project.org (2017). More

1.
Falkowski, P. G., Dubinsky, Z., Muscatine, L. & Porter, J. W. Light and the bioenergetics of a symbiotic coral. Bioscience 34, 705–709 (1984).
CAS  Article  Google Scholar 
2.
Morris, L. A., Voolstra, C. R., Quigley, K. M., Bourne, D. G. & Bay, L. K. Nutrient availability and metabolism affect the stability of coral–symbiodiniaceae symbioses. Trends Microbiol. 27, 678–689 (2019).
CAS  PubMed  Article  Google Scholar 

3.
LaJeunesse, T. C. et al. Systematic revision of symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570-2580.e6 (2018).
CAS  PubMed  Article  Google Scholar 

4.
Cunning, R., Silverstein, R. N. & Baker, A. C. Symbiont shuffling linked to differential photochemical dynamics of Symbiodinium in three Caribbean reef corals. Coral Reefs 37, 145–152 (2018).
ADS  Article  Google Scholar 

5.
Muscatine, L., Falkowski, P. G., Porter, J. W. & Dubinsky, Z. Fate of photosynthetic fixed carbon in light- and shade-adapted colonies of the symbiotic coral Stylophora pistillata. Proc. R. Soc. B Biol. Sci. 222, 181–202 (1984).
ADS  CAS  Google Scholar 

6.
Porter, J. W. Primary productivity in the sea: Reef corals in situ. In Primary Productivity in the Sea. Environmental Science Research (ed. Falkowski, P. G.) 403–410 (Springer, Boston, 1980).
Google Scholar 

7.
Patterson, M. R., Sebens, K. P. & Olson, R. O. In situ measurements of flow effects on primary production and dark respiration in reef corals. Limnol. Oceanogr. 36, 936–948 (1991).
ADS  CAS  Article  Google Scholar 

8.
Wangpraseurt, D. et al. Spectral effects on Symbiodinium photobiology studied with a programmable light engine. PLoS ONE 9, e112809 (2014).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

9.
Kühl, M. et al. Microenvironment and photosynthesis of zooxanthellae in scleractinian corals studied with microsensors for O2, pH and light. Mar. Ecol. Prog. Ser. 117, 159–172 (1995).
ADS  Article  Google Scholar 

10.
Burriesci, M. S., Raab, T. K. & Pringle, J. R. Evidence that glucose is the major transferred metabolite in dinoflagellate-cnidarian symbiosis. J. Exp. Biol. 215, 3467–3477 (2012).
CAS  PubMed  PubMed Central  Article  Google Scholar 

11.
Houlbrèque, F. & Ferrier-Pagès, C. Heterotrophy in tropical scleractinian corals. Biol. Rev. 84, 1–17 (2009).
PubMed  Article  Google Scholar 

12.
Holcomb, M., Tambutté, E., Allemand, D. & Tambutté, S. Light enhanced calcification in Stylophora pistillata: effects of glucose, glycerol and oxygen. PeerJ 2, e375 (2014).
PubMed  PubMed Central  Article  CAS  Google Scholar 

13.
Agostini, S., Fujimura, H., Hayashi, H. & Fujita, K. Mitochondrial electron transport activity and metabolism of experimentally bleached hermatypic corals. J. Exp. Mar. Biol. Ecol. 475, 100–107 (2016).
CAS  Article  Google Scholar 

14.
Imbs, A. B. & Yakovleva, I. M. Dynamics of lipid and fatty acid composition of shallow-water corals under thermal stress: and experimental approach. Coral Reefs 31, 31–41 (2012).
ADS  Article  Google Scholar 

15.
Dunn, S. R., Pernice, M., Green, K., Hoegh-Guldberg, O. & Dove, S. G. Thermal stress promotes host mitochondrial degradation in symbiotic cnidarians: are the batteries of the reef going to run out?. PLoS ONE 7, e39024 (2012).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

16.
Blackstone, N. Mitochondria and the redox control of development in cnidarians. Semin. Cell Dev. Biol. 20, 330–336 (2009).
CAS  PubMed  Article  Google Scholar 

17.
McDonald, A. E., Vanlerberghe, G. C. & Staples, J. F. Alternative oxidase in animals: unique characteristics and taxonomic distribution. J. Exp. Biol. 212, 2627–2634 (2009).
CAS  PubMed  Article  Google Scholar 

18.
McDonald, A. E. & Gospodaryov, D. V. Alternative NAD(P)H dehydrogenase and alternative oxidase: proposed physiological roles in animals. Mitochondrion 45, 7–17 (2019).
CAS  PubMed  Article  Google Scholar 

19.
Raven, J. A. & Beardall, J. Consequences of the genotypic loss of mitochondrial Complex I in dinoflagellates and of phenotypic regulation of Complex I content in other photosynthetic organisms. J. Exp. Bot. 68, 2683–2692 (2017).
CAS  Article  Google Scholar 

20.
Oakley, C. A., Hopkinson, B. M. & Schmidt, G. W. Mitochondrial terminal alternative oxidase and its enhancement by thermal stress in the coral symbiont Symbiodinium. Coral Reefs 33, 543–552 (2014).
ADS  Article  Google Scholar 

21.
Nelson, H. R. & Altieri, A. H. Oxygen: The universal currency on coral reefs. Coral Reefs 38, 177–189 (2019).
ADS  Article  Google Scholar 

22.
Iglesias-prieto, A. R., Govind, N. S. & Trench, R. K. Isolation and characterization of three membrane bound chlorophyll-protein complexes from four dinoflagellate species. Philos. Trans. R. Soc. Lond. B 340, 381–392 (1993).
CAS  Article  Google Scholar 

23.
Aihara, Y., Takahashi, S. & Minagawa, J. Heat induction of cyclic electron flow around photosystem I in the symbiotic dinoflagellate Symbiodinium. Plant Physiol. 171, 522–529 (2016).
CAS  PubMed  PubMed Central  Article  Google Scholar 

24.
Leggat, W., Badger, M. & Yellowlees, D. Evidence for an inorganic carbon-concentrating mechanism in the symbiotic dinoflagellate Symbiodinium sp. Plant Physiol. 121, 1247–1255 (1999).
CAS  PubMed  PubMed Central  Article  Google Scholar 

25.
Raven, J. A., Suggett, D. J. & Giordano, M. Inorganic carbon concentrating mechanisms in free-living and symbiotic dinoflagellates and chromerids. J. Phycol. https://doi.org/10.1111/jpy.13050 (2020).
Article  PubMed  PubMed Central  Google Scholar 

26.
Barott, K. L. et al. Coral host cells acidify symbiotic algal microenvironment to promote photosynthesis. Proc. Natl. Acad. Sci. USA 112, 607–612 (2015).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

27.
Mayfield, A. B., Hsiao, Y. Y., Chen, H. K. & Chen, C. S. Rubisco expression in the dinoflagellate Symbiodinium sp. is influenced by both photoperiod and endosymbiotic lifestyle. Mar. Biotechnol. 16, 371–384 (2014).
CAS  PubMed  Article  PubMed Central  Google Scholar 

28.
Tremblay, P., Grover, R., Maguer, J. F., Legendre, L. & Ferrier-Pagès, C. Autotrophic carbon budget in coral tissue: A new 13C-based model of photosynthate translocation. J. Exp. Biol. 215, 1384–1393 (2012).
CAS  PubMed  Article  PubMed Central  Google Scholar 

29.
Maor-Landaw, K., van Oppen, M. J. H. & McFadden, G. I. Symbiotic lifestyle triggers drastic changes in the gene expression of the algal endosymbiont Breviolum minutum (Symbiodiniaceae). Ecol. Evol. 10, 451–466 (2020).
PubMed  Article  PubMed Central  Google Scholar 

30.
Roth, M. S. The engine of the reef: photobiology of the coral-algal symbiosis. Front. Microbiol. 5, 1–22 (2014).
ADS  Article  Google Scholar 

31.
Roberty, S., Béraud, E., Grover, R. & Ferrier-Pagès, C. Coral productivity is co-limited by bicarbonate and ammonium availability. Microorganisms 8, 640 (2020).
PubMed Central  Article  PubMed  Google Scholar 

32.
Tchernov, D. et al. Membrane lipids of symbiotic algae are diagnostic of sensitivity to thermal bleaching in corals. Proc. Natl. Acad. Sci. USA 101, 13531–13535 (2004).
ADS  CAS  PubMed  Article  Google Scholar 

33.
Cardol, P., Forti, G. & Finazzi, G. Regulation of electron transport in microalgae. Biochim. Biophys. Acta 1807, 912–918 (2011).
CAS  PubMed  Article  Google Scholar 

34.
Papageorgiou, G. C. Chlorophyll a Fluorescence. A Signature of Photosynthesis (Springer, Dordrecht, 2004).
Google Scholar 

35.
Hennige, S. J., Suggett, D. J., Warner, M. E., McDougall, K. E. & Smith, D. J. Photobiology of Symbiodinium revisited: Bio-physical and bio-optical signatures. Coral Reefs 28, 179–195 (2009).
ADS  Article  Google Scholar 

36.
Reynolds, J. M. C., Bruns, B. U., Fitt, W. K. & Schmidt, G. W. Enhanced photoprotection pathways in symbiotic dinoflagellates of shallow-water corals and other cnidarians. Proc. Natl. Acad. Sci. USA 105, 17206 (2008).
CAS  Article  Google Scholar 

37.
Roberty, S., Bailleul, B., Berne, N., Franck, F. & Cardol, P. PSI Mehler reaction is the main alternative photosynthetic electron pathway in Symbiodinium sp., symbiotic dinoflagellates of cnidarians. New Phytol. 204, 81–91 (2014).
CAS  PubMed  Article  Google Scholar 

38.
Dang, K. V., Pierangelini, M., Roberty, S. & Cardol, P. Alternative photosynthetic electron transfers and bleaching phenotypes upon acute heat stress in Symbiodinium and Breviolum spp. (Symbiodiniaceae) in culture. Front. Mar. Sci. 6, 1–10 (2019).
Article  Google Scholar 

39.
Hoogenboom, M. O., Campbell, D. A., Beraud, E., DeZeeuw, K. & Ferrier-Pagès, C. Effects of light, food availability and temperature stress on the function of photosystem II and photosystem I of coral symbionts. PLoS ONE 7, e30167 (2012).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

40.
Szabó, M. et al. Non-intrusive assessment of photosystem II and photosystem I in whole coral tissues. Front. Mar. Sci. 4, 269 (2017).
Article  Google Scholar 

41.
Enríquez, S., Méndez, E. R. & Iglesias-Prieto, R. Multiple scattering on coral skeletons enhances light absorption by symbiotic algae. Limnol. Oceanogr. 50, 1025–1032 (2005).
ADS  Article  Google Scholar 

42.
Gilmore, A. M. et al. Simultaneous time resolution of the emission spectra of fluorescent proteins and zooxanthellar chlorophyll in reef-building corals. Photochem. Photobiol. 77, 515 (2003).
CAS  PubMed  Article  Google Scholar 

43.
Maxwell, K. & Johnson, G. N. Chlorophyll fluorescence-a practical guide. J. Exp. Bot. 51, 659–668 (2000).
CAS  PubMed  Article  Google Scholar 

44.
Sandmann, G., Reck, H., Kessler, E. & Böger, P. Distribution of plastocyanin and soluble plastidic cytochrome c in various classes of algae. Arch. Microbiol. 134, 23–27 (1983).
CAS  Article  Google Scholar 

45.
Schreiber, U. Redox changes of ferredoxin, P700, and plastocyanin measured simultaneously in intact leaves. Photosynth. Res. 134, 343–360 (2017).
CAS  PubMed  PubMed Central  Article  Google Scholar 

46.
Joliot, P. & Joliot, A. Quantification of cyclic and linear flows in plants. Proc. Natl. Acad. Sci. USA 102, 4913–4918 (2005).
ADS  CAS  PubMed  Article  Google Scholar 

47.
Witt, H. et al. Species-specific differences of the spectroscopic properties of P700: Analysis of the influence of non-conserved amino acid residues by site-directed mutagenesis of photosystem I from Chlamydomonas reinhardtii. J. Biol. Chem. 278, 46760–46771 (2003).
CAS  PubMed  Article  Google Scholar 

48.
Klughammer, C. & Schreiber, U. An improved method, using saturating light pulses, for the determination of photosystem I quantum yield via P700+-absorbance changes at 830 nm. Planta 192, 261–268 (1994).
CAS  Article  Google Scholar 

49.
Bailleul, B., Cardol, P., Breyton, C. & Finazzi, G. Electrochromism: A useful probe to study algal photosynthesis. Photosynth. Res. 106, 179–189 (2010).
CAS  PubMed  Article  Google Scholar 

50.
Vega De Luna, F., Dang, K. V., Cardol, M., Roberty, S. & Cardol, P. Photosynthetic capacity of the endosymbiotic dinoflagellate Cladocopium sp. is preserved during digestion of its jellyfish host Mastigias papua by the anemone Entacmaea medusivora. FEMS Microbiol. Ecol. 95, 1–7 (2019).
Google Scholar 

51.
Ritchie, R. J. Consistent sets of spectrophotometric chlorophyll equations for acetone, methanol and ethanol solvents. Photosynth. Res. 89, 27–41 (2006).
CAS  PubMed  Article  PubMed Central  Google Scholar 

52.
Hume, B. C. C. et al. An improved primer set and amplification protocol with increased specificity and sensitivity targeting the Symbiodinium ITS2 region. PeerJ 6, e4816 (2018).
PubMed  PubMed Central  Article  CAS  Google Scholar 

53.
Hume, B. C. C. et al. SymPortal: A novel analytical framework and platform for coral algal symbiont next-generation sequencing ITS2 profiling. Mol. Ecol. Resour. 19, 1063–1080 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

54.
Shafir, S., Van Rijn, J. & Rinkevich, B. Nubbing of coral colonies: a novel approach for the development of inland broodstocks. Aquar. Sci. Conserv. 3, 183–190 (2001).
Article  Google Scholar 

55.
Hoadley, K. D. et al. Host–symbiont combinations dictate the photo-physiological response of reef-building corals to thermal stress. Sci. Rep. 9, 1–15 (2019).
CAS  Article  Google Scholar 

56.
Heyward, A. J. & Collins, J. D. Fragmentation in Montipora ramosa: the genet and ramet concept applied to a reef coral. Coral Reefs 4, 35–40 (1985).
ADS  Article  Google Scholar 

57.
Raz-Bahat, M., Erez, J. & Rinkevich, B. In vivo light-microscopic documentation for primary calcification processes in the hermatypic coral Stylophora pistillata. Cell Tissue Res. 325, 361–368 (2006).
PubMed  Article  Google Scholar 

58.
Warner, M. E., Fitt, W. K. & Schmidt, G. W. Damage to photosystem II in symbiotic dinoflagellates: a determinant of coral bleaching. Proc. Natl. Acad. Sci. USA 96, 8007–8012 (1999).
ADS  CAS  PubMed  Article  Google Scholar 

59.
Rehman, A. U. et al. Symbiodinium sp. cells produce light-induced intra- and extracellular singlet oxygen, which mediates photodamage of the photosynthetic apparatus and has the potential to interact with the animal host in coral symbiosis. New Phytol. 212, 472–484 (2016).
CAS  PubMed  Article  Google Scholar 

60.
Hill, R. & Ralph, P. J. Dark-induced reduction of the plastoquinone pool in zooxanthellae of scleractinian corals and implications for measurements of chlorophyll a fluorescence. Symbiosis 46, 45–56 (2008).
CAS  Google Scholar 

61.
Einbinder, S. et al. Novel adaptive photosynthetic characteristics of mesophotic symbiotic microalgae within the reef-building coral, Stylophora pistillata. Front. Mar. Sci. 3, 1–9 (2016).
Article  Google Scholar 

62.
Mass, T. et al. Photoacclimation of Stylophora pistillata to light extremes: metabolism and calcification. Mar. Ecol. Prog. Ser. 334, 93–102 (2007).
ADS  CAS  Article  Google Scholar 

63.
Ferrier-Pagès, C., Gattuso, J. P., Dallot, S. & Jaubert, J. Effect of nutrient enrichment on growth and photosynthesis of the zooxanthellae coral Stylophora pistillata. Coral Reefs 19, 103–113 (2000).
Article  Google Scholar 

64.
Peltier, G., Tolleter, D., Billon, E. & Cournac, L. Auxiliary electron transport pathways in chloroplasts of microalgae. Photosynth. Res. 106, 19–31 (2010).
CAS  PubMed  Article  PubMed Central  Google Scholar 

65.
Pierangelini, M., Thiry, M. & Cardol, P. Different levels of energetic coupling between photosynthesis and respiration do not determine the occurrence of adaptive responses of Symbiodiniaceae to global warming. New Phytol. https://doi.org/10.1111/nph.16738 (2020).
Article  PubMed  PubMed Central  Google Scholar 

66.
Bailleul, B. et al. Energetic coupling between plastids and mitochondria drives CO2 assimilation in diatoms. Nature 524, 366–369 (2015).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

67.
Badger, M. R. et al. Electron flow to oxygen in higher plants and algae: Rates and control of direct photoreduction (Mehler reaction) and rubisco oxygenase. Philos. Trans. R. Soc. B 355, 1433–1446 (2000).
CAS  Article  Google Scholar 

68.
Fan, D. Y. et al. Obstacles in the quantification of the cyclic electron flux around photosystem I in leaves of C3 plants. Photosynth. Res. 129, 239–251 (2016).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

69.
Szabó, M. et al. Effective light absorption and absolute electron transport rates in the coral Pocillopora damicornis. Plant Physiol. Biochem. 83, 159–167 (2014).
ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

70.
Kato, H. et al. Characterization of a giant photosystem I supercomplex in the symbiotic dinoflagellate Symbiodiniaceae. Plant Physiol. https://doi.org/10.1104/pp.20.00726 (2020).
Article  PubMed  PubMed Central  Google Scholar 

71.
Alric, J. Cyclic electron flow around photosystem I in unicellular green algae. Photosynth. Res. 106, 47–56 (2010).
CAS  PubMed  Article  Google Scholar 

72.
Melis, A. & Jeanette, J. S. Stoichiometry of system I and system II reaction centers and of plastoquinone in different photosynthetic membranes. Proc. Natl. Acad. Sci. USA. 77, 4712–4716 (1980).
ADS  CAS  PubMed  Article  Google Scholar  More

1.
Bé, A. W. An ecological, zoogeographic and taxonomic review of Recent planktonic foraminifera. In Oceanic micropaleontology (ed. Ramsay, A. T. S.) 1–100 (Academic Press, New York, 1977).
Google Scholar 
2.
Schiebel, R. & Hemleben, C. Planktic Foraminifera in the Modern Ocean (Springer, Berlin, 2017).
Google Scholar 

3.
Taylor, B. J. et al. Distribution and ecology of planktic foraminifera in the North Pacific: implications for paleo-reconstructions. Quat. Sci. Rev. 191, 256–274 (2018).
ADS  Article  Google Scholar 

4.
Schiebel, R. Planktic foraminiferal sedimentation and the marine calcite budget. Global Biogeochem. Cycles 16, 3-1-3–21 (2002).
Article  CAS  Google Scholar 

5.
Kucera, M. Chapter six planktonic foraminifera as tracers of past oceanic environments. Dev. Mar. Geol. 1, 213–262 (2007).
Google Scholar 

6.
Fox, L., Stukins, S., Hill, T. & Miller, C. G. Quantifying the Effect of Anthropogenic Climate Change on Calcifying Plankton. Sci. Rep. 10, 1620 (2020).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

7.
De Moel, H. et al. Planktic foraminiferal shell thinning in the Arabian Sea due to anthropogenic ocean acidification?. Biogeosci. Discuss. 6, 1811–1835 (2009).
ADS  Article  Google Scholar 

8.
Moy, A. D., Howard, W. R., Bray, S. G. & Trull, T. W. Reduced calcification in modern Southern Ocean planktonic foraminifera. Nat. Geosci. 2, 276–280 (2009).
ADS  Article  CAS  Google Scholar 

9.
Jonkers, L., Hillebrand, H. & Kucera, M. Global change drives modern plankton communities away from the pre-industrial state. Nature 570, 372–375 (2019).
ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

10.
Wefer, G., Berger, W. H., Bijma, J. & Fischer, G. Clues to ocean history: a brief overview of proxies. In Use of Proxies in Paleoceanography 1–68 (Springer, Berlin, 1999). http://doi.org/10.1007/978-3-642-58646-0_1

11
Bé, A. W. H., Bishop, J. K. B., Sverdlove, M. S. & Gardner, W. D. Standing stock, vertical distribution and flux of planktonic foraminifera in the Panama Basin. Mar. Micropaleontol. 9, 307–333 (1985).
ADS  Article  Google Scholar 

12.
Pados, T. & Spielhagen, R. F. Species distribution and depth habitat of recent planktic foraminifera in Fram Strait, Arctic Ocean. Polar Res. 33, 22483 (2014).
Article  Google Scholar 

13.
Salmon, K. H., Anand, P., Sexton, P. F. & Conte, M. Upper ocean mixing controls the seasonality of planktonic foraminifer fluxes and associated strength of the carbonate pump in the oligotrophic North Atlantic. Biogeosciences 12, 223–235 (2015).
ADS  Article  Google Scholar 

14.
Žarić, S., Donner, B., Fischer, G., Mulitza, S. & Wefer, G. Sensitivity of planktic foraminifera to sea surface temperature and export production as derived from sediment trap data. Mar. Micropaleontol. 55, 75–105 (2005).
ADS  Article  Google Scholar 

15.
Schiebel, R., Waniek, J., Bork, M. & Hemleben, C. Planktic foraminiferal production stimulated by chlorophyll redistribution and entrainment of nutrients. Deep Sea Res. Part I 48, 721–740 (2001).
Article  CAS  Google Scholar 

16.
Venancio, I. M. et al. Planktonic foraminifera shell fluxes from a weekly resolved sediment trap record in the southwestern Atlantic: evidence for synchronized reproduction. Mar. Micropaleontol. 125, 25–35 (2016).
ADS  Article  Google Scholar 

17.
Erez, J. & Honjo, S. Comparison of isotopic composition of planktonic foraminifera in plankton tows, sediment traps and sediments. Palaeogeogr. Palaeoclimatol. Palaeoecol. 33, 129–156 (1981).
Article  Google Scholar 

18.
Deuser, W. G., Ross, E. H., Hemleben, C. & Spindler, M. Seasonal changes in species composition, numbers, mass, size, and isotopic composition of planktonic foraminifera settling into the deep Sargasso Sea. Palaeogeogr. Palaeoclimatol. Palaeoecol. 33, 103–127 (1981).
Article  Google Scholar 

19.
Deuser, W. G. & Ross, E. H. Seasonally abundant planktonic foraminifera of the Sargasso Sea: succession, deep-water fluxes, isotopic compositions, and paleoceanographic implications. J. Foraminifer. Res. 19, 268–293 (1989).
Article  Google Scholar 

20.
Sautter, L. R. & Thunell, R. C. Seasonal succession of planktonic Foraminifera: results from a four-year time-series sediment trap experiment in the Northeast Pacific. J. Foraminifer. Res. 19, 253–267 (1989).
Article  Google Scholar 

21.
Curry, W. B., Thunell, R. C. & Honjo, S. Seasonal changes in the isotopic composition of planktonic foraminifera collected in Panama Basin sediment traps. Earth Planet. Sci. Lett. 64, 33–43 (1983).
ADS  Article  CAS  Google Scholar 

22.
Thunell, R. C. & Honjo, S. Seasonal and interannual changes in planktonic foraminiferal production in the North Pacific. Nature 328, 335–337 (1988).
ADS  Article  Google Scholar 

23.
Smart, S. M. et al. Ground-truthing the planktic foraminifer-bound nitrogen isotope paleo-proxy in the Sargasso Sea. Geochim. Cosmochim. Acta 235, 463–482 (2018).
ADS  Article  CAS  Google Scholar 

24.
King, A. L. & Howard, W. R. Seasonality of foraminiferal flux in sediment traps at Chatham rise, SW Pacific: implications for paleotemperature estimates. Deep Res. Part I Oceanogr. Res. Pap. 48, 1687–1708 (2001).
ADS  Article  Google Scholar 

25.
Levanon-Spanier, I., Padan, E. & Reiss, Z. Primary production in a desert-enclosed sea—the Gulf of Elat (Aqaba), Red Sea. Deep Sea Res Part A. Oceanogr. Res. Pap. 26, 673–685 (1979).
ADS  Article  CAS  Google Scholar 

26.
Reiss, Z. & Hottinger, L. The Gulf of Aqaba: ecological micropaleontology (Springer, Berlin, 1984).
Google Scholar 

27.
Lazar, B. et al. Recent environmental changes in the chemical–biological oceanography of the Gulf of Aqaba (Eilat). In Aqaba-Eilat, the Improbable Gulf. Environment, Biodiversity and Preservation 49–61 (2008).

28.
Erez, J., Almogi-Labin, A. & Avraham, S. On the life history of planktonic Foraminifera: lunar reproduction cycle in Globigerinoides sacculifer (Brady). Paleoceanography 6, 295–306 (1991).
ADS  Article  Google Scholar 

29.
Zarubin, M., Lindemann, Y. & Genin, A. The Dispersion-Confinement mechanism: phytoplankton dynamics and the spring bloom in a deeply-mixing subtropical sea. Prog. Oceanogr. 155, 13–27 (2017).
ADS  Article  Google Scholar 

30.
Kimor, B. & Golandsky, B. Microplankton of the Gulf of Elat: Aspects of seasonal and bathymetric distribution. Mar. Biol. 42, 55–67 (1977).
Article  Google Scholar 

31.
Winter, A., Reiss, Z. & Luz, B. Distribution of living coccolithophore assemblages in the Gulf of Elat (Aqaba). Mar. Micropaleontol. 4, 197–223 (1979).
ADS  Article  Google Scholar 

32.
Lindell, D. & Post, A. Ultraphytoplankton succession is triggered by deep winter mixing in the Gulf of Aqaba (Eilat), Red Sea. Limnol. Oceanogr. 40, 1130–1141 (1995).
ADS  Article  Google Scholar 

33.
Labiosa, R. G., Arrigo, K. R., Genin, A., Monismith, S. G. & Van Dijken, G. The interplay between upwelling and deep convective mixing in determining the seasonal phytoplankton dynamics in the Gulf of Aqaba: evidence from SeaWiFS and MODIS. Limnol. Oceanogr. 48, 2355–2368 (2003).
ADS  Article  Google Scholar 

34.
Meeder, E. et al. Nitrite dynamics in the open ocean – clues from seasonal and diurnal variations. Mar. Ecol. Prog. Ser. 453, 11–26 (2012).
ADS  Article  CAS  Google Scholar 

35.
Carlson, D. F., Fredj, E. & Gildor, H. The annual cycle of vertical mixing and restratification in the Northern Gulf of Eilat/Aqaba (Red Sea) based on high temporal and vertical resolution observations. Deep. Res. Part I(84), 1–17 (2014).
Google Scholar 

36.
Shaked, Y. Iron redox dynamics in the surface waters of the Gulf of Aqaba, Red Sea. Geochim. Cosmochim. Acta 72, 1540–1554 (2008).
ADS  Article  CAS  Google Scholar 

37.
Almogi-Labin, A. Population dynamics of planktic Foraminifera and Pteropoda—Gulf of Aqaba, Red Sea. Proc. R. Netherl. Acad. Sci. B 87, 481–511 (1984).
Google Scholar 

38.
Chernihovsky, N., Torfstein, A. & Almogi-Labin, A. Seasonal flux patterns of planktonic foraminifera in a deep, oligotrophic, marginal sea: Sediment trap time series from the Gulf of Aqaba, northern Red Sea. Deep Sea Res Part I Oceanogr. Res. Pap. 140, 78–94 (2018).
ADS  Article  CAS  Google Scholar 

39.
Torfstein, A., Kienast, S. S., Yarden, B., Rivlin, A., Isaacs, S. & Shaked, Y. Bulk and export production fluxes in the Gulf of Aqaba, Northern Red Sea. ACS Earth Space Chem. 4(8), 1461–1479 (2020).
Article  CAS  Google Scholar 

40.
Shaked, Y. & Genin, A. Israel National Monitroing Program at the Gulf of Eilat Annual Report. (2018).

41.
Genin, A., Lazar, B. & Brenner, S. Vertical mixing and coral death in the Red Sea following the eruption of Mount Pinatubo. Nature 377, 507–510 (1995).
ADS  Article  CAS  Google Scholar 

42.
Torfstein, A. & Kienast, S. S. No Correlation between atmospheric dust and surface ocean chlorophyll-a in the oligotrophic Gulf of Aqaba, Northern Red Sea. J. Geophys. Res. Biogeosciences 123, 391–405 (2018).
ADS  Article  Google Scholar 

43.
Meilland, J. et al. Highly replicated sampling reveals no diurnal vertical migration but stable species-specific vertical habitats in planktonic foraminifera. J. Plankton Res. https://doi.org/10.1093/plankt/fbz002 (2019).
Article  Google Scholar 

44.
Iluz, D. et al. Short-term variability in primary productivity during a wind-driven diatom bloom in the Gulf of Eilat (Aqaba). Aquat. Microb. Ecol. 56, 205–215 (2009).
Article  Google Scholar 

45.
Jonkers, L., Brummer, G.-J.A., Peeters, F. J. C., van Aken, H. M. & De Jong, M. F. Seasonal stratification, shell flux, and oxygen isotope dynamics of left-coiling N. pachyderma and T. quinqueloba in the western subpolar North Atlantic. Paleoceanography 25, 1–13 (2010).
Google Scholar 

46.
Jonkers, L. & Kučera, M. Global analysis of seasonality in the shell flux of extant planktonic Foraminifera. Biogeosciences 12, 2207–2226 (2015).
ADS  Article  Google Scholar 

47.
Hemleben, C., Spindler, M. & Anderson, O. R. Modern Planktonic Foraminifera (Springer, Berlin, 2012).
Google Scholar 

48.
Brummer, G.-J.A., Hemleben, C. & Spindler, M. Planktonic foraminiferal ontogeny and new perspectives for micropalaeontology. Nature 319, 50–52 (1986).
ADS  Article  Google Scholar 

49.
Boltovsky, E. Globigerinita clarkei (Rögl & Bolli) – an unfairly ignored small planktic foraminifer. Boreas 20, 151–154 (2008).
Article  Google Scholar 

50.
Takagi, H. et al. Characterizing photosymbiosis in modern planktonic foraminifera. Biogeosciences 16, 3377–3396 (2019).
ADS  Article  CAS  Google Scholar 

51.
Grigoratou, M. et al. A trait-based modelling approach to planktonic foraminifera ecology. Biogeosciences 16, 1469–1492 (2019).
ADS  Article  Google Scholar 

52.
Spindler, M., Hemleben, C., Salomons, J. B. & Smit, L. P. Feeding behavior of some planktonic foraminifers in laboratory cultures. J. Foraminifer. Res. 14, 237–249 (1984).
Article  Google Scholar 

53.
Spindler, M., Hemleben, C., Bayer, U., Bé, A. & Anderson, O. Lunar periodicity of reproduction in the planktonic foraminifer Hastigerina pelagica. Mar. Ecol. Prog. Ser. 1, 61–64 (1979).
ADS  Article  Google Scholar 

54.
Jonkers, L., Reynolds, C. E., Richey, J. & Hall, I. R. Lunar periodicity in the shell flux of planktonic foraminifera in the Gulf of Mexico. Biogeosciences 12, 3061–3070 (2015).
ADS  Article  Google Scholar 

55.
Bijma, J., Erez, J. & Hemleben, C. Lunar and semi-lunar reproduction cycles in some spinose planktonic foraminifers. J. Foraminifer. Res. 20, 117–127 (1990).
Article  Google Scholar 

56.
Lin, H.-L. The seasonal succession of modern planktonic foraminifera: sediment traps observations from southwest Taiwan waters. Cont. Shelf Res. 84, 13–22 (2014).
ADS  Article  Google Scholar 

57.
Lončarić, N., Brummer, G. J. A. & Kroon, D. Lunar cycles and seasonal variations in deposition fluxes of planktic foraminiferal shell carbonate to the deep South Atlantic (central Walvis Ridge). Deep Res. Part I Oceanogr. Res. Pap. 52, 1178–1188 (2005).
ADS  Article  Google Scholar 

58.
Davis, C. V. et al. Extensive morphological variability in asexually produced planktic foraminifera. Sci. Adv. https://doi.org/10.1126/sciadv.abb8930 (2020).
Article  PubMed  PubMed Central  Google Scholar 

59.
Takagi, H., Kurasawa, A. & Kimoto, K. Observation of asexual reproduction with symbiont transmission in planktonic foraminifera. J. Plankton Res. https://doi.org/10.1093/plankt/fbaa033 (2020).
Article  Google Scholar 

60.
Hottinger, L., Halicz, E. & Reiss, Z. Recent Foraminiferida from the Gulf of Aqaba, Red Sea. Opera Sazu, Ljubljana, Slovania (1993).

61.
Brummer, G. J. A. & Kroon, D. Planktonic foraminifers as tracers of ocean-climate history: Ontogeny, relationships and preservation of modern species and stable isotopes, phenotypes and assemblage distribution in different water masses (Free University Press, 1988).

62.
Sprintall, J. & Tomczak, M. Evidence of the barrier layer in the surface layer of the tropics. J. Geophys. Res. 97, 7305 (1992).
ADS  Article  Google Scholar 

63.
Trauth, M. H. MATLAB Recipes for Earth Sciences MATLAB Recipes for Earth Sciences 2nd edn. (Springer, Berlin, 2007). https://doi.org/10.1007/978-3-540-72749-1.
Google Scholar  More