Ecology

1.Almond, R. E. A., Grooten, M. & Petersen, T. (eds) Living Planet Report 2020 – Bending the Curve of Biodiversity Loss (WWF, 2020).2.Leung, B. et al. Clustered versus catastrophic global vertebrate declines. Nature 588, 267–271 (2020).ADS 
CAS 
Article 

Google Scholar 
3.Deinet, S. et al. Wildlife Comeback in Europe: The Recovery of Selected Mammal and Bird Species (final report to Rewilding Europe by ZSL, BirdLife International and the European Bird Census Council) (2013).4.Ceballos, G., Ehrlich, P. R. & Dirzo, R. Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proc. Natl Acad. Sci. USA 114, E6089–E6096 (2017).CAS 
Article 

Google Scholar 
5.Pauly, D. Anecdotes and the shifting baseline syndrome of fisheries. Trends Ecol. Evol. 10, 430 (1995).CAS 
Article 

Google Scholar 
6.Daskalova, G. N., Myers-Smith, I. H. & Godlee, J. L. Rare and common vertebrates span a wide spectrum of population trends. Nat. Commun. 11, 4394 (2020).ADS 
CAS 
Article 

Google Scholar 
7.Setiawan, R. et al. Preventing global extinction of the Javan rhino: tsunami risk and future conservation direction. Conserv. Lett. 11, e12366 (2018).Article 

Google Scholar 
8.Mondol, S., Bruford, M. W. & Ramakrishnan, U. Demographic loss, genetic structure and the conservation implications for Indian tigers. Proc. R. Soc. Lond. B 280, 20130496 (2013).
Google Scholar 
9.Milner-Gulland, E. J. & Beddington, J. R. The exploitation of elephants for the ivory trade: An historical perspective. Proc. R. Soc. Lond. B 252, 29–37 (1993).ADS 
Article 

Google Scholar 
10.Casas-Marce, M. et al. Spatiotemporal dynamics of genetic variation in the iberian lynx along its path to extinction reconstructed with ancient DNA. Mol. Biol. Evol. 34, 2893–2907 (2017).CAS 
Article 

Google Scholar 
11.Chase, M. J. et al. Continent-wide survey reveals massive decline in African savannah elephants. PeerJ 4, e2354 (2016).Article 

Google Scholar 
12.Jhala, Y. V, Qureshi, Q. & Nayak, A. K. (eds) Status of Tigers, Co-Predators and Prey in India 2018. Summary Report (National Tiger Conservation Authority, Government of India, New Delhi & Wildlife Institute of India, 2019).13.Sanderson, E. W. et al. The ecological future of the North American bison: conceiving long-term, large-scale conservation of wildlife. Conserv. Biol. 22, 252–266 (2008).Article 

Google Scholar  More

1.Laffoley, D. & Baxter, J.M. Ocean Deoxygenation: Everyone’s Problem-Causes, Impacts, Consequences and Solutions. (IUCN, 2019).2.Heinze, C. et al. The quiet crossing of ocean tipping points. Proc. Natl. Acad. Sci. 118(9), e2008478118 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
3.Ekau, W., Auel, H., Pörtner, H. O. & Gilbert, D. Impacts of hypoxia on the structure and processes in pelagic communities (zooplankton, macro-invertebrates and fish). Biogeosciences 7(5), 1669–1699 (2010).ADS 
CAS 

Google Scholar 
4.Gallo, N. D. & Levin, L. A. Fish ecology and evolution in the world’s oxygen minimum zones and implications of ocean deoxygenation. Adv. Mar. Biol. 74, 117–198 (2016).CAS 

Google Scholar 
5.Breitburg, D. et al. Declining oxygen in the global ocean and coastal waters. Science 359(6371), eaam7240 (2018).
Google Scholar 
6.Hoegh-Guldberg, O. et al. The human imperative of stabilizing global climate change at 1.5 C. Science 365(6459), eaaw6974 (2019).CAS 

Google Scholar 
7.Sampaio, E. et al. Impacts of hypoxic events surpass those of future ocean warming and acidification. Nat. Ecol. Evol. 5, 311–321 (2021).
Google Scholar 
8.Chan, F. et al. Emergence of anoxia in the California current large marine ecosystem. Science 319(5865), 920–920 (2008).ADS 
CAS 

Google Scholar 
9.Levin, L. A. et al. Effects of natural and human-induced hypoxia on coastal benthos. Biogeosciences 6, 2063–2098 (2009).ADS 
CAS 

Google Scholar 
10.Stramma, L., Schmidtko, S., Levin, L. A. & Johnson, G. C. Ocean oxygen minima expansions and their biological impacts. Deep Sea Res Part I Oceanogr. Res. Pap. 57(4), 587–595 (2010).ADS 
CAS 

Google Scholar 
11.Hoegh-Guldberg, O. et al. 2018: Impacts of 1.5 °C Global Warming on Natural and Human Systems. In: 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 175–311 (Intergovernmental Panel on Climate Change, 2019).12.Zhang, X. et al. In situ Raman-based measurements of high dissolved methane concentrations in hydrate-rich ocean sediments. Geophys. Res. Lett. 38, L08605 (2011).ADS 

Google Scholar 
13.Wright, J. J., Konwar, K. M. & Hallam, S. J. Microbial ecology of expanding oxygen minimum zones. Nat. Rev. Microbiol. 10, 381–394 (2012).CAS 

Google Scholar 
14.Kalvelage, T. et al. Nitrogen cycling driven by organic matter export in the South Pacific oxygen minimum zone. Nat. Geosci. 6, 228–234 (2013).ADS 
CAS 

Google Scholar 
15.Falkowski, P. G. Evolution of the nitrogen cycle and its influence on the biological sequestration of CO2 in the ocean. Nature 387(6630), 272–275 (1997).ADS 
CAS 

Google Scholar 
16.Zehr, J. P. & Kudela, R. M. Nitrogen cycle of the open ocean: From genes to ecosystems. Annu. Rev. Mar. Sci. 3, 197–225 (2011).ADS 

Google Scholar 
17.Pack, M. A. et al. Methane oxidation in the Eastern Tropical North Pacific Ocean water column. J. Geophys. Res. Biogeosci. 120, 1078–1092 (2015).CAS 

Google Scholar 
18.Lashof, D. A. & Ahuja, D. R. Relative contributions of greenhouse gas emissions to global warming. Nature 344, 529–531 (1990).ADS 
CAS 

Google Scholar 
19.Reeburgh, W. S. Oceanic methane biogeochemistry. Chem. Rev. 107, 486–513 (2007).CAS 

Google Scholar 
20.Stramma, L., Johnson, G. C., Sprintall, J. & Mohrholz, V. Expanding oxygen-minimum zones in the tropical oceans. Science 320, 655–658 (2008).ADS 
CAS 

Google Scholar 
21.Keeling, R. E., Körtzinger, A. & Gruber, N. Ocean deoxygenation in a warming world. Ann. Rev. Mar. Sci. 2, 199–229 (2010).
Google Scholar 
22.Helm, K. P., Bindoff, N. L. & Church, J. A. Observed decreases in oxygen content of the global ocean. Geophys. Res. Lett. 38, L23602 (2011).ADS 

Google Scholar 
23.Kirschke, S. et al. Three decades of global methane sources and sinks. Nat. Geosci. 6, 813–823 (2013).ADS 
CAS 

Google Scholar 
24.Savrda, C. E. & Bottjer, D. J. Trace·fossil model for reconstruction of paleo-oxgenation in bottom waters. Geology 14, 3–6 (1986).ADS 
CAS 

Google Scholar 
25.Savrda, C. E. & Bottjer, D. J. The exaerobic zone, a new oxygen-deficient marine biofacies. Nature 327, 54–56 (1987).ADS 

Google Scholar 
26.Savrda, C. E. & Bottjer, D. J. Trace·fossil model for reconstructing oxygenation histories of ancient marine bottom waters: Application to Upper Cretaceous Niobrara Formation, Colorado. Palaeogeogr. Palaeoclimatol. Palaeoecol. 74, 49–74 (1989).
Google Scholar 
27.Kaiho, K. Morphotype changes of deep-sea benthic foraminifera during the Cenozoic Era and their paleoenvironmental implications. Kaseki (Fossils) 47, 1–23 (1989).
Google Scholar 
28.Kaiho, K. Global changes of Paleogene aerobic/anaerobic Benthic foraminifera and deep-sea circulation. Palaeogeogr. Palaeoclimatol. Palaeoecol. 83, 65–85 (1991).
Google Scholar 
29.Kaiho, K. Benthic foraminiferal dissolved-oxygen index and dissolved-oxygen levels in the modern ocean. Geology 22, 719–722 (1994).ADS 
CAS 

Google Scholar 
30.Schumacher, S., Jorissen, F. J., Dissard, D., Larkin, K. E. & Gooday, A. J. Live (Rose Bengal stained) and dead benthic foraminifera from the oxygen minimum zone of the Pakistan continental margin (Arabian Sea). Mar. Micropaleontol. 62, 45–73 (2007).ADS 

Google Scholar 
31.Abu-Zied, R. H. et al. Benthic foraminiferal response to changes in bottom-water oxygenation and organic carbon flux in the eastern Mediterranean during LGM to Recent times. Mar. Micropaleontol. 67, 46–68 (2008).ADS 

Google Scholar 
32.Grunert, P. et al. Upwelling conditions in the Early Miocene Central Paratethys Sea. Geol. Carpath. 61(2), 129–145 (2010).ADS 
MathSciNet 
CAS 

Google Scholar 
33.Kaminski, M. A. Calibration of the benthic foraminiferal oxygen index in the Marmara Sea. Geol. Q. 56(4), 757–764 (2012).
Google Scholar 
34.Ilies, I. A. et al. Early middle Miocene paleoenvironmental evolution in southwest Transylvania (Romania): Interpretation based on foraminifera. Geol. Carpath. 71(5), 444–461 (2020).
Google Scholar 
35.Bernhard, J. M. & Bowser, S. S. Benthic foraminifera of dysoxic sediments: Chloroplast sequestration and functional morphology. Earth Sci. Rev. 46(1–4), 149–165 (1999).ADS 
CAS 

Google Scholar 
36.Ohkushi, K. et al. Quantified intermediate water oxygenation history of the NE Pacific: A new benthic foraminiferal record from Santa Barbara basin. Paleoceanography 28(3), 453–467 (2013).ADS 

Google Scholar 
37.Lu, W. et al. I/Ca in epifaunal benthic foraminifera: A semi-quantitative proxy for bottom water oxygen in a multi-proxy compilation for glacial ocean deoxygenation. EPSL 533, 116055 (2020).CAS 

Google Scholar 
38.Rathburn, A. E., Willingham, J., Ziebis, W., Burkett, A. M. & Corliss, B. H. A new biological proxy for deep-sea paleo-oxygen: Pores of epifaunal benthic foraminifera. Sci. Rep. 8, 1–8 (2018).CAS 

Google Scholar 
39.Singh, A. D., Rai, A. K., Verma, K., Das, S. & Bharti, S. K. Benthic foraminiferal diversity response to the climate induced changes in the eastern Arabian Sea oxygen minimum zone during the last 30 ka BP. Quat. Int. 374, 118–125 (2015).
Google Scholar 
40.Palmer, H. M. et al. Southern California margin benthic foraminiferal assemblages record recent centennial-scale changes in oxygen minimum zone. Biogeosciences 17(11), 2923–2937 (2020).ADS 

Google Scholar 
41.Tetard, M., Licari, L., Ovsepyan, E., Tachikawa, K. & Beaufort, L. Toward a global calibration for quantifying past oxygenation in oxygen minimum zones using benthic Foraminifera. Biogeosciences 18(9), 2827–2841 (2021).ADS 
CAS 

Google Scholar 
42.Moffitt, S. E., Hill, T. M., Ohkushi, K., Kennett, J. P. & Behl, R. J. Vertical oxygen minimum zone oscillations since 20 ka in Santa Barbara Basin: A benthic foraminiferal community perspective. Paleoceanography 29, 44–57 (2014).ADS 

Google Scholar 
43.Hoogakker, B. A., Elderfield, H., Schmiedl, G., McCave, I. N. & Rickaby, R. E. Glacial–interglacial changes in bottom-water oxygen content on the Portuguese margin. Nat. Geosci. 8, 40–43 (2015).ADS 
CAS 

Google Scholar 
44.Glock, N., Liebetrau, V. & Eisenhauer, A. I/Ca ratios in benthic foraminifera from the Peruvian oxygen minimum zone: analytical methodology and evaluation as a proxy for redox conditions. Biogeosciences 11(23), 7077–7095 (2014).ADS 

Google Scholar 
45.Jorissen, F.J., Fontanier, C., & Thomas, E. Paleoceanographical proxies based on deep-sea benthic foraminiferal assemblage characteristics. In: Hillaire-Marcel, C., & De Vernal, A. Proxies in late Cenozoic paleoceanography. Dev. Mar. Geol., 1, 263–325 (2007).46.Diaz, R. J. Overview of hypoxia around the world. J. Environ. Qual. 30(2), 275–281 (2001).CAS 

Google Scholar 
47.Tetard, M., Licari, L., Tachikawa, K., Ovsepyan, E. & Beaufort, L. Toward a global calibration for quantifying past oxygenation in oxygen minimum zones using benthic Foraminifera. Biogeosci. Discuss. 18(9), 2827–2841 (2021).48.Diaz, R. J. & Rosenberg, R. Marine benthic hypoxia: A review of its ecological effects and the behavioural responses of benthic macrofauna. Oceanogr. Mar. Biol. 33, 245–303 (1995).
Google Scholar 
49.Diaz, R. J. & Rosenberg, R. Spreading dead zones and consequences for marine ecosystems. Science 321, 926–929 (2008).ADS 
CAS 

Google Scholar 
50.Sen Gupta, B. K., Eugene Turner, R. & Rabalais, N. N. Seasonal oxygen depletion in continental-shelf waters of Louisiana: Historical record of benthic foraminifers. Geology 24(3), 227–230 (1996).ADS 

Google Scholar 
51.Schlanger, S. O. & Jenkyns, H. C. Cretaceous oceanic anoxic events: Causes and consequences. Geol. Mijnbouw 55, 179–184 (1976).
Google Scholar 
52.Jenkyns, H. C. Geochemistry of oceanic anoxic events. Geochem. Geophys. Geosyst. 11, Q03004 (2010).ADS 

Google Scholar 
53.Clark, P. U. et al. Consequences of twenty-first century policy for multi-millennial climate and sea-level change. Nat. Clim. Change 6, 360–369 (2016).ADS 

Google Scholar 
54.Clark, P. U. et al. Sea-level commitment as a gauge for climate policy. Nat. Clim. Change 8, 653–655 (2018).ADS 

Google Scholar 
55.Li, C., Held, H., Hokamp, S. & Marotzke, J. Optimal temperature overshoot profile found by limiting global sea level rise as a lower-cost climate target. Sci. Adv. 6(2), eaaw9490 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
56.Berner, R. A. & Raiswell, R. Burial of organic carbon and pyrite sulfur in sediments over Phanerozoic time: A new theory. Geochim. Cosmochim. Acta 47(5), 855–862 (1983).ADS 
CAS 

Google Scholar 
57.Gautier, D. L. Cretaceous shales from the western interior of North America: Sulfur/carbon ratios and sulfur-isotope composition. Geology 14(3), 225–228 (1986).ADS 
CAS 

Google Scholar 
58.Kajiwara, Y. & Kaiho, K. Oceanic anoxia at the Cretaceous/Tertiary boundary supported by the sulfur isotopic record. Palaeogeogr. Palaeoclimatol. Palaeoecol. 99, 151–162 (1992).
Google Scholar 
59.Anderson, R. F., LeHuray, A. P., Fleisher, M. Q. & Murray, J. W. Uranium deposition in ancouv inlet sediments, ancouver island. Geochim. Cosmochim. Acta 53(9), 2205–2213 (1989).ADS 
CAS 

Google Scholar 
60.Kaiho, K., Fujiwara, O. & Motoyama, I. Mid-Cretaceous faunal turnover of intermediate-water benthic foraminifera in the northwestern Pacific Ocean margin. Mar. Micropaleontol. 23, 13–49 (1993).ADS 

Google Scholar 
61.Kaiho, K., Morgans, H. E. & Okada, H. Faunal turnover of intermediate-water benthic foraminifera during the Paleogene in New Zealand. Mar. Micropaleontol. 23, 51–86 (1993).ADS 

Google Scholar 
62.Alegret, L., Molina, E. & Thomas, E. Benthic foraminiferal turnover across the Cretaceous/Paleogene boundary at Agost (southeastern Spain): Paleoenvironmental inferences. Mar. Micropaleontol. 48(3–4), 251–279 (2003).ADS 

Google Scholar 
63.Morigi, C. Benthic environmental changes in the Eastern Mediterranean Sea during sapropel S5 deposition. Palaeogeogr. Palaeoclimatol. Palaeoecol. 273(3–4), 258–271 (2009).
Google Scholar 
64.Cetean, C. G., Bălc, R., Kaminski, M. A. & Filipescu, S. Integrated biostratigraphy and palaeoenvironments of an upper Santonian—upper Campanian succession from the southern part of the Eastern Carpathians, Romania. Cretac. Res. 32(5), 575–590 (2011).
Google Scholar 
65.Drinia, H. & Anastasakis, G. Benthic foraminifer palaeoecology of the Late Quaternary continental outer shelf of a landlocked marine basin in central Aegean Sea, Greece. Quat. Int. 261, 43–52 (2012).
Google Scholar 
66.Baas, J. H., Schönfeld, J. & Zahn, R. Mid-depth oxygen drawdown during Heinrich events: Evidence from benthic foraminiferal community structure, trace-fossil tiering, and benthic δ13C at the Portuguese Margin. Mar. Geol. 152(1–3), 25–55 (1998).ADS 
CAS 

Google Scholar 
67.Kaiho, K. Global climatic forcing of deep-sea benthic foraminiferal test size during the past 120 my. Geology 26(6), 491–494 (1998).ADS 

Google Scholar 
68.Wang, N., Huang, B. & Dong, Y. The evolution of deepwater dissolved oxygen in the Northern South China Sea during the past 400 ka. In AGU Fall Meeting Abstracts 2016, PP43A-2297 (2016).69.Ukpong, A. J. & Macaulay, E. O. Evaluation of paleo-oxygen conditions of Priabonian-Rupelian sediments of the Agbada Formation, Niger delta based on Fisher’s Diversity Index and Benthic Foraminifera Oxygen Index. IJRD. 2(12), 65–80 (2017).
Google Scholar 
70.Harzhauser, M. et al. Miocene lithostratigraphy of the northern and central Vienna Basin (Austria). Aust. J. Earth Sci. 113, 169–199 (2020).ADS 

Google Scholar 
71.Kranner, M. et al. Miocene ecology of the central and northern Vienna Basin (Austria), based on foraminiferal ecology. Palaeogeogr. Palaeoclimatol. Palaeoecol. 581, 110640 (2021).
Google Scholar 
72.Loeblich, A. R. & Tappan, H. Foraminiferal Genera and Their Classification (Von Nostrand Reinhold Co., 1987).
Google Scholar 
73.Kaminski, M. A. The year 2010 classification of the agglutinated foraminifera. Micropaleontology 60, 89–108 (2014).
Google Scholar 
74.Pawlowski, J., Lejzerowicz, F. & Esling, P. Next-generation environmental diversity surveys of foraminifera: Preparing the future. Biol. Bull. 227(2), 93–106 (2014).CAS 

Google Scholar 
75.Boersma, A. Foraminifera. In Introduction to Marine Micropaleontology. 19–77 (Elsevier Science BV, 1998).76.Piller, W. E. & Haunold, T. G. The Northern Bay of Safaga (Red Sea, Egypt): An Actuopalaeontological Approach V. Foraminifera (Waldemar Kramer Verlag, 1998).
Google Scholar 
77.Amao, A. O. et al. Distribution of benthic foraminifera along the Iranian coast. Mar. Biodivers. 49, 399–945 (2019).
Google Scholar 
78.Charrieau, L. M. et al. The effects of multiple stressors on the distribution of coastal benthic foraminifera: A case study from the Skagerrak-Baltic Sea region. Mar. Micropaleontol. 139, 42–56 (2018).ADS 

Google Scholar 
79.Charrieau, L. M. et al. Rapid environmental responses to climate-induced hydrographic changes in the Baltic Sea entrance. Biogeosciences 16, 3835–3852 (2019).ADS 
CAS 

Google Scholar 
80.Groeneveld, J. et al. Assessing proxy signatures of temperature, salinity, and hypoxia in the Baltic Sea through foraminifera-based geochemistry and faunal assemblages. J. Micropalaeontol. 37, 403–429 (2018).ADS 

Google Scholar 
81.García-Gallardo, Á. et al. Benthic foraminifera-based reconstruction of the first Mediterranean-Atlantic exchange in the early Pliocene Gulf of Cadiz. Palaeogeogr. Palaeoclimatol. Palaeoecol. 472, 93–107 (2017).
Google Scholar 
82.Rupp, C. & Ćorić, S. Zur Eferding-Formation. Jahrb. Geol. Bundesanst. 155, 33–95 (2015).
Google Scholar 
83.Murray, J. W. Ecology and Applications of Benthic Foraminifera (Cambridge University Press, 2006).
Google Scholar 
84.Jorissen, F. J., de Stigter, H. C. & Widmark, J. G. A conceptual model explaining benthic foraminiferal microhabitats. Mar. Micropaleontol. 26, 3–15 (1995).ADS 

Google Scholar 
85.Garcia, H.E. et al. World Ocean Atlas 2013. Vol. 3: Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation. (NOAA Atlas NESDIS 75, 2013).86.Murray, J. W. Ecology and Palaeoecology of Benthic Foraminifera. (Longman Scientific and Technical, 1991).87.Reymond, C. E., Lloyd, A., Kline, D. I., Dove, S. G. & Pandolfi, J. M. Decline in growth of foraminifer Marginopora rossi under eutrophication and ocean acidification scenarios. Glob. Change Biol. 19, 291–302 (2013).ADS 

Google Scholar 
88.Titelboim, D. et al. Selective responses of benthic foraminifera to thermal pollution. Mar. Pollut. Bull. 105, 324–333 (2016).CAS 

Google Scholar 
89.Renema, W. Terrestrial influence as a key driver of spatial variability in large benthic foraminiferal assemblage composition in the Central Indo-Pacific. Earth-Sci. Rev. 177, 514–544 (2018).ADS 

Google Scholar 
90.Koho, K. A. et al. Sedimentary labile organic carbon and pore water redox control on species distribution of benthic foraminifera: A case study from Lisbon-Setúbal Canyon (southern Portugal). Prog. Oceanogr. 79, 55–82 (2008).ADS 

Google Scholar  More

1.Hoschitz, M. & Kaufmann, R. Nematode community composition in five alpine habitats. Nematology 6, 737–747 (2004).
Google Scholar 
2.Treonis, A. M. & Wall, D. H. Soil nematodes and desiccation survival in the extreme arid environment of the Antarctic dry valleys. Integr. Comp. Biol. 45, 741–750 (2005).PubMed 

Google Scholar 
3.Tong, F. C., Xiao, Y. & Wang, Q. L. Soil Nematode community structure on the northern slope of Changbai Mountain Northeast China. J. For. Res. 21, 93–98 (2010).
Google Scholar 
4.Yeates, G. W. Nematodes as soil indicators functional and biodiversity aspects. Biol. Fertil. Soils 37, 199–210 (2003).
Google Scholar 
5.Bakonyi, G. et al. Soil Nematode community structure as affected by temperature and moisture in a temperate semiarid shrubland. Appl. Soil. Ecol. 37(1–2), 31–40 (2007).
Google Scholar 
6.Van Eekeren, N. et al. Ecosystem services in grassland associated with biotic and abiotic soil parameters. Soil Biol. Biochem. 42(9), 1491–1504 (2010).
Google Scholar 
7.Kitagami, Y., Kanzaki, N. & Matsuda, Y. Distribution and community structure of soil nematodes in coastal Japanese pine forests were shaped by harsh environmental conditions. Appl. Soil. Ecol. 119, 91–98 (2017).
Google Scholar 
8.Salamun, P. et al. The effects of vegetation cover on soil Nematode communities in various biotopes disturbed by industrial emissions. Sci. Total Environ 592, 106–114 (2017).CAS 
PubMed 
ADS 

Google Scholar 
9.Kashyap, P., Bhardwaj, M. & Uniyal, V. P. Bibliography on the soil Nematodes of the Indian Himalayan Region. In Bibliography on the Fauna and Micro Flora of the Indian Himalayan Region. ENVIS Bulletin: Wildlife and Protected Areas Vol. 17 (ed. Sathyakumar, S.) 239–256 (Wildlife Institute of India, 2016).
Google Scholar 
10.Kumar, S. & Rawat, S. First report on the root-knot Nematode Meloidogyneenterolobii (Yang and Eisenback 1988) infecting guava (Psidiumguajava) in Udham Singh Nagar of Uttarakhand India. Int. J. Curr. Microbiol. Appl. Sci. 7(4), 1720–1724 (2018).CAS 

Google Scholar 
11.Kayani, M. Z., Mukhtar, T. & Hussain, M. A. Interaction between Nematode inoculum density and plant age on growth and yield of cucumber and reproduction of Meloidogyne incognita. Pak. J. Zool. 50(3), 897–902 (2018).
Google Scholar 
12.Rizvi, A. N., Sen, D., Maity, P. & Kumar, H. Nematoda (soil inhabiting Nematodes). In Faunal Diversity of Indian Himalaya (eds Chandra, K. et al.) 115–134 (Director Zool Surv India, 2018).
Google Scholar 
13.Devetter, M., Hanel, L., Rehakova, K. & Anddolezal, J. Diversity and feeding strategies of soil microfauna along elevation gradients in Himalayan cold deserts. PLoS ONE 12(11), e0187646 (2017).PubMed 
PubMed Central 

Google Scholar 
14.Afzal, S., Nesar, H., Imran, Z. & Ahmad, W. Altitudinal gradient affect abundance, diversity and metabolicfootprint of soil nematodesin Banihal-Pass of Pir-Panjalmountain range. Sci. Rep. 11, 16214 (2021).CAS 
PubMed 
PubMed Central 
ADS 

Google Scholar 
15.Dong, K. et al. Soil nematodes show a mid-elevation diversity maximum and elevational zonation on Mt. Norikura, Japan. Sci. Rep. 7, 3028 (2017).PubMed 
PubMed Central 
ADS 

Google Scholar 
16.Powers, L. E., Ho, M. C., Freckman, D. W. & Virginia, R. A. Distribution, community structure and microhabitats of soil invertebrates along an elevational gradient in Taylor Valley Antarctica. Arct. Alp. Res. 30, 133–141 (1998).
Google Scholar 
17.Kergunteuil, A., Campos-Herrera, R., Sánchez-Moreno, S., Vittoz, P. & Rasmann, S. T. Abundance, diversity, and metabolic footprint of soil nematodes is highest in high elevation alpine grasslands. Front. Ecol. Evol. 4, 84 (2016).
Google Scholar 
18.Veen, G. F. et al. Coordinated responses of soil communities to elevation in three subarctic vegetation types. Oikos 126, 1586–1599 (2017).
Google Scholar 
19.Burrows, C. J. Processes of Vegetation Change 1 (Unwin Hyman, 1990).
Google Scholar 
20.De Kort, H. et al. Life history, climate and biogeography interactively affect worldwide genetic diversity of plant and animal populations. Nat. Commun. 12, 516 (2021).PubMed 
PubMed Central 
ADS 

Google Scholar 
21.Liu, J., Yang, Q., Siemann, E., Huang, W. & Ding, J. Latitudinal and altitudinal patterns of soil nematode communities under tallow tree (Triadicasebifera) in China. Plant Ecol. 220, 965–976 (2019).
Google Scholar 
22.Qing, X., Bert, W., Steel, H., Quisado, J. & de Ley, I. T. Soil and litter nematode diversity of Mount Hamiguitan, the Philippines, with description of Bicirronemahamiguitanense n. sp (Rhabditida: Bicirronematidae). Nematology 17, 325–344 (2015).
Google Scholar 
23.Wasilewska, L. Soil invertebrates as bioindicators with special reference to soil inhabiting nematodes. Russ. J. Nematol. 5, 113–126 (1997).
Google Scholar 
24.Mladenov, A., Lazarova, S. & Peneva, V. Distribution patterns of Nematode communities in an urban forest in Sofia Bulgaria. In Ecology of the City of Sofia. Species and Communities in an Urban Environment (eds Peneva, L. et al.) 281–297 (Sofia Bulgaria Pen-soft Publishers, 2004).
Google Scholar 
25.Hánel, L. Comparison of soil Nematode communities in three spruce forests at the Bobín Mount Czech Republic. Biológia 51, 485–493 (1996).
Google Scholar 
26.Hanel, L. Soil Nematodes in five spruce forests of the Beskydymountains Czech Republic. Fundam. Appl. Nematol. 19(1), 15–24 (1996).
Google Scholar 
27.Zhang, S. et al. Impacts of altitude and position on the rates of soil nitrogen mineralization and nitrification in alpine meadows on the eastern Qinghai-Tibetan Plateau China. Biol. Fertil. Soils 48(4), 393–400 (2012).CAS 

Google Scholar 
28.Yeates, G. W. Abundance diversityand resilience of Nematode assemblage in forest soils. Can. J. For. Res. 37, 216–225 (2007).
Google Scholar 
29.Mulder, C., Zwart, D. D., Van Wijnen, H. J., Schouten, A. J. & Andbreure, A. M. Observational and simulated evidence of ecological shifts within the soil Nematode community of agroecosystems under conventional and organic farming. Funct. Ecol. 17(4), 516–525 (2003).
Google Scholar 
30.Butenko, K. O., Gongalsky, K. B., Korobushkin, D. I., Ekschmitt, K. & Zaitsev, A. S. Forest fires alter the trophic structure of soil nematode communities. Soil Biol. Biochem. 109, 107–117 (2017).CAS 

Google Scholar 
31.Tibbett, M. et al. Long-term acidification of pH neutral grasslands affects soil biodiversity fertility and function in a heathland restoration. CATENA 180, 401–415 (2019).CAS 

Google Scholar 
32.Zhang, S. et al. Tillage effects outweigh seasonal effects on soil Nematode community structure. Soil Tillage Res. 192, 233–239 (2019).
Google Scholar 
33.Liang, S. et al. Soil Nematode community composition and stability under different nitrogen additions in a semiarid grassland. Glob. Ecol. Conserv. 22, e00965n (2020).
Google Scholar 
34.Olatunji, O. A. et al. The effect of phosphorus addition, soil moisture, and plant type on soil nematode abundance and community composition. J. Soil. Sediment 19, 1139–1150 (2019).CAS 

Google Scholar 
35.Wang, J. et al. Changes in soil nematode abundance and composition under elevated [CO2] and canopy warming in a rice paddy field. Plant Soil 445(1), 425–437 (2019).CAS 

Google Scholar 
36.Zhang, Z. W. et al. The impacts of nutrient addition and livestock exclosure on the soil Nematode community in degraded grassland. Land Degrad. Dev. 30(13), 1574–1583 (2019).
Google Scholar 
37.Bastow, J. The impacts of a wildfire in a semiarid grassland on soil Nematode abundances over 4 years. Biol. Fertil. Soils 56, 675–685 (2020).
Google Scholar 
38.Renčo, M., Gomoryova, E. & Cerevková, A. The effect of soil type and ecosystems on the soil nematode and microbial communities. Helminthologia 57(2), 129 (2020).PubMed 
PubMed Central 

Google Scholar 
39.Saeed, S., Barozai, M. Y. K., Ahmad, A. & Shah, S. H. Impact of altitude on soil physical and chemical properties in SraGhurgai (Takatu mountain range) Quetta Balochistan. Int. J. Sci. Eng. Res. 5(3), 730–735 (2014).
Google Scholar 
40.Zhang, X. Y. et al. Effects of rainfall amount and frequency on soil nitrogen mineralization in Zoigê alpine wetland. Eur. J. Soil Biol. 97, 103170 (2020).CAS 

Google Scholar 
41.Juan, Y. et al. Simulation of soil freezing-thawing cycles under typical winter conditions: Implications for nitrogen mineralization. J. Soils Sediments 20(1), 143–152 (2020).CAS 

Google Scholar 
42.Cutz-Pool, L. Q., Palacios-Vargas, J. G., Cano-Santana, Z. & Castaño-Meneses, G. Diversity patterns of Collembola in an elevational gradient in the NW slope of Iztaccíhuatl volcano state of Mexico, Mexico. Entomol. News 121, 249–261 (2010).
Google Scholar 
43.Baniyamuddin, M., Tomar, V. V. S. & Ahmad, W. Functional diversity of soil inhabiting nematodes in natural forests of Arunachal Pradesh India. Nematol. Mediterr. 35, 109–121 (2007).
Google Scholar 
44.Hanel, L. Nematode assemblages indicate soil restoration on colliery spoils afforested by planting different tree species and by natural succession. Appl. Soil. Ecol. 40, 86–99 (2008).
Google Scholar 
45.Rizvi, A. N. Community analysis of soil inhabiting nematodes in natural Sal forests of Dehradun India. Int. J. Nematol. 18, 181–190 (2008).
Google Scholar 
46.Keith, A. M. et al. Strong impacts of below-ground tree inputs on soil nematode trophic composition. Soil Biol. Biochem. 41, 1060–1065 (2009).CAS 

Google Scholar 
47.Keith, A. M. et al. Birch invasion of heather moorland increases nematode diversity and trophic complexity. Soil Biol. Biochem. 38, 3421–3430 (2006).CAS 

Google Scholar 
48.Forge, T. & Simard, S. Structure of nematode communities in forest soils of southern British Columbia relationships to nitrogen mineralization and effects of clearcut harvesting and fertilization. Biol. Fertil. Soils 34, 170–178 (2001).CAS 

Google Scholar 
49.Savin, M. C., Gorres, J. H., Neher, D. A. & Amador, J. A. Biogeophysical factors influencing soil respiration and mineral nitrogen content in an old field soil. Soil Biol. Biochem. 33, 429–438 (2001).CAS 

Google Scholar 
50.Postma-Blaauw, M. B. et al. Within trophic group interactions of bacterivorous nematode species and their effects on the bacterial community and nitrogen mineralization. Oecologia 142, 428–439 (2005).CAS 
PubMed 
ADS 

Google Scholar 
51.Bongers, T. & Ferris, H. Nematode community structure as a bioindicator in environmental monitoring. Trends Ecol. Evol. 14, 224–228 (1999).CAS 
PubMed 

Google Scholar 
52.Ferris, H., Bongers, T. & De Goede, R. G. M. A framework for soil food web diagnostics extension of the nematode faunal analysis concept. Appl. Soil. Ecol. 18, 13–29 (2001).
Google Scholar 
53.Ferris, H., Bongers, A.M.T. & De Goede, R. Nematode faunal analyses to assess food web enrichment and connectance. Nematology monographs and perspectives. In Proceedings of the Fourth International Congress of Nematology, Brill 503–510 (2004).54.Ferris, H., Zheng, L. & Walker, M. A. Resistance of grape rootstocks to plant-parasitic nematodes. J. Nematol. 44, 377–386 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
55.Quist, C. W., Van Der Putten, W. H. & Thakur, M. P. Soil predator loss alters aboveground stoichiometry in a native but not in a related range-expanding plant when exposed to periodic heat waves. Soil Biol. Biochem. 150, 107999 (2020).CAS 

Google Scholar 
56.Ferris, H. & Matute, M. M. Structural and functional succession in the nematode fauna of a soil food web. Appl. Soil. Ecol. 23, 93–110 (2003).
Google Scholar 
57.Tomar, W. W. S. & Ahmad, W. Food web diagnostics and functional diversity of soil inhabiting nematodes in a natural woodland. Helminthologia 46, 183–189 (2009).
Google Scholar 
58.Hanel, N. Soil Nematodes in alpine meadows of the Tatra National Park (Slovak Republic). Helminthologia 54(1), 48–67 (2017).
Google Scholar 
59.Hanel, L. & Cerevkova, A. Diversity of soil Nematodes in meadows of the White Carpathians. Helminthologia 43, 109–116 (2006).
Google Scholar 
60.Neely, C. L., Beare, M. H., Hargrove, W. L. & Coleman, D. C. Relationships between fungal and bacterial substrate-induced respiration biomass and plant residue decomposition. Soil Biol. Biochem. 23(10), 947–954 (1991).CAS 

Google Scholar 
61.Moller, J., Miller, M. & Kjoller, A. Fungal–bacterial interaction on beech leaves: Influence on decomposition and dissolved organic carbon quality. Soil Biol. Biochem. 31(3), 367–374 (1999).CAS 

Google Scholar 
62.Banerjee, S. et al. Network analysis reveals functional redundancy and keystone taxa amongst bacterial and fungal communities during organic matter decomposition in an arable soil. Soil Biol. Biochem. 97, 188–198 (2016).CAS 

Google Scholar 
63.Nottingham, A. T. et al. Nutrient limitations to bacterial and fungal growth during cellulose decomposition in tropical forest soils. Biol. Fertil. Soils 54(2), 219–228 (2018).CAS 

Google Scholar 
64.Albright, M. B. et al. Soil bacterial and fungal richness forecast patterns of early pine litter decomposition. Front. Microbiol. 11, 542220 (2020).PubMed 
PubMed Central 

Google Scholar 
65.Champion, H. G. & Seth, S. K. Revised Forest Types of India (Manager of Publications Government of India Delhi, 1968).
Google Scholar 
66.Singh, D., Chhonkar, P. K. & Pandey, R. N. Manual on Soil, Plant and Water Analysis (Westville Publishing House, 2005).
Google Scholar 
67.Jackson, M. L. Soil Chemical Analysis 498 (Prentice-Hall of India Pvt. Ltd, 1973).
Google Scholar 
68.Walkley, A. & Black, I. A. An examination of Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Sci. 37, 29–37 (1934).CAS 
ADS 

Google Scholar 
69.Kjeldahl, J. New method for the determination of nitrogen. Chem. News 48(1240), 101–102 (1883).
Google Scholar 
70.Olsen, S. R., Cole, W., Watanable, F. S. & Dean, L. A. Estimation of available phosphorus in soils by extraction with sodium bicarbonate. Methods Soil Anal. Circ. 939(1883), 1–56 (1954).
Google Scholar 
71.Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1km spatial resolution climate surfaces for globalland areas. Int. J. Climatol. 37(12), 4302–4315 (2017).
Google Scholar 
72.Cobb, N.A. Estimating the Nematode population of the soil. In Agricultural Technical Circular No. 1 48 (United States Department of Agriculture Bureau of Plant Industry, 1918).73.Yeates, G. W., Bongers, T., De Goede, R. G. M., Freckman, D. W. & Georgieva, S. S. Feeding habits in soil Nematode families and genera—An outline for soil ecologists. J. Nematol. 25, 315–331 (1993).CAS 
PubMed 
PubMed Central 

Google Scholar 
74.Forge, T. & Simard, S. Structure of nematode communities in forest soils of southern British Columbia: Relationships to nitrogen mineralization and effects of clearcut harvesting and fertilization. Biol. Fertil. Soils 34, 170–178. https://doi.org/10.1007/s003740100390 (2001).CAS 
Article 

Google Scholar 
75.Bongers, T. The maturity index an ecological measure of environmental disturbance based on nematode species composition. Oecologia 83, 14–19 (1990).PubMed 
ADS 

Google Scholar 
76.Bongers, T. & Bongers, M. Functional diversity of nematodes. Appl. Soil. Ecol. 10, 239–251 (1998).
Google Scholar 
77.Bongers, T., De Goede, R. G. M., Korthals, G. W. & Yeates, G. W. Proposed changes of c–p classification for nematodes. Russ. J. Nematol. 3, 61–62 (1995).
Google Scholar 
78.Neher, D. A. & Campbell, C. L. Nematode communities and microbial biomass in soils with annual and perennial crops. Appl. Soil. Ecol. 1(1), 17–28 (1994).
Google Scholar 
79.Sieriebriennikov, B., Ferris, H. & de Goede, R. G. NINJA: An automated calculation system for nematode-based biological monitoring. Eur. J. Soil Biol. 61, 90–93 (2014).
Google Scholar 
80.Andrassy, I. T. Determination of volume and weight of nematodes. Acta Zool. Acad. Sci. Hung. 2, 1–15 (1956).
Google Scholar 
81.Ferris, H. Form and function: Metabolic footprints of nematodes in the soil food web. Eur. J. Soil Biol. 46, 97–104 (2010).
Google Scholar 
82.Oksanen, J.B. et al. vegan: Community ecology package. R package version 5–6 (2020).83.R Core Team. R: A Language and Environment for Statistical Computing (2019). Retrieved from https://www.R-project.org.84.Figures 1, 3 and 4 was prepared using GraphPad Prism version 8.0.2 for Windows, GraphPadSofware, La Jolla California USA. www.graphpad.com. More

1.IPCC. Shukla, P. et al. Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. (2019).2.Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Courchamp, F. Impacts of climate change on the future of biodiversity. Ecol. Lett. 15, 365–377 (2012).PubMed 
PubMed Central 

Google Scholar 
3.Moritz, C. & Agudo, R. The future of species under climate change: resilience or decline?. Science (80-) 80(341), 504–508 (2013).ADS 

Google Scholar 
4.Gobiet, A. et al. 21st century climate change in the European Alps—A review. Sci. Total Environ. 493, 1138–1151 (2014).ADS 
CAS 

Google Scholar 
5.Damschen, E. I., Harrison, S., Ackerly, D. D., Fernandez-Going, B. M. & Anacker, B. L. Endemic plant communities on special soils: early victims or hardy survivors of climate change?. J. Ecol. 100(5), 1122–1130 (2012).
Google Scholar 
6.Essl, F. et al. Distribution patterns, range size and niche breadth of Austrian endemic plants. Biol. Conserv. 142, 2547–2558 (2009).
Google Scholar 
7.Hülber, K. et al. Uncertainty in predicting range dynamics of endemic alpine plants under climate warming. Glob. Change Biol. 22, 2608–2619 (2016).ADS 

Google Scholar 
8.Wershow, S. T. & DeChaine, E. G. Retreat to refugia: Severe habitat contraction projected for endemic alpine plants of the Olympic Peninsula. Am. J. Bot. 105, 760–778 (2018).
Google Scholar 
9.Dagnino, D. et al. Climate change and the future of endemic flora in the South Western Alps: relationships between niche properties and extinction risk. Reg. Environ. Change 20, 1–12 (2020).
Google Scholar 
10.Dirnböck, T., Essl, F. & Rabitsch, W. Disproportional risk for habitat loss of high-altitude endemic species under climate change. Glob. Chang. Biol. 17, 990–996 (2011).ADS 

Google Scholar 
11.Parmesan, C. & Hanley, M. E. Plants and climate change: complexities and surprises. Ann. Bot. 116, 849–864 (2015).PubMed 
PubMed Central 

Google Scholar 
12.Pauli, H., Gottfried, M., Dirnböck, T., Dullinger, S. & Grabherr, G. Assessing the long-term dynamics of endemic plants at summit habitats. in Alpine biodiversity in Europe 195–207 (Springer, 2003).13.Parolo, G. & Rossi, G. Upward migration of vascular plants following a climate warming trend in the Alps. Basic Appl. Ecol. 9, 100–107 (2008).
Google Scholar 
14.Dullinger, S. et al. Extinction debt of high-mountain plants under twenty-first-century climate change. Nat. Clim. Change 2, 619–622 (2012).ADS 

Google Scholar 
15.Scherrer, D. & Körner, C. Topographically controlled thermal-habitat differentiation buffers alpine plant diversity against climate warming. J. Biogeogr. 38, 406–416 (2011).
Google Scholar 
16.Randin, C. F. et al. Climate change and plant distribution: local models predict high-elevation persistence. Glob. Change Biol. 15, 1557–1569 (2009).ADS 

Google Scholar 
17.Patsiou, T. S., Conti, E., Zimmermann, N. E., Theodoridis, S. & Randin, C. F. Topo-climatic microrefugia explain the persistence of a rare endemic plant in the Alps during the last 21 millennia. Glob. Change Biol. 20, 2286–2300 (2014).ADS 

Google Scholar 
18.Suggitt, A. J. et al. Extinction risk from climate change is reduced by microclimatic buffering. Nat. Clim. Change 8, 713–717 (2018).ADS 

Google Scholar 
19.Körner, C. The alpine life zone. in Alpine Plant Life 9–20 (Springer, 2003).20.Badgley, C. et al. Biodiversity and topographic complexity: modern and geohistorical perspectives. Trends Ecol. Evol. 32, 211–226 (2017).PubMed 
PubMed Central 

Google Scholar 
21.Graae, B. J. et al. Stay or go–how topographic complexity influences alpine plant population and community responses to climate change. Perspect. Plant Ecol. Evol. Syst. 30, 41–50 (2018).
Google Scholar 
22.Dobrowski, S. Z. A climatic basis for microrefugia: the influence of terrain on climate. Glob. Change Biol. 17, 1022–1035 (2011).ADS 

Google Scholar 
23.Keppel, G. et al. Refugia: identifying and understanding safe havens for biodiversity under climate change. Glob. Ecol. Biogeogr. 21, 393–404 (2012).
Google Scholar 
24.Hülber, K. et al. Habitat availability disproportionally amplifies climate change risks for lowland compared to alpine species. Glob. Ecol. Conserv. 23, e01113 (2020).
Google Scholar 
25.Loarie, S. R. et al. The velocity of climate change. Nature 462, 1052–1055 (2009).ADS 
CAS 

Google Scholar 
26.Vittoz, P. & Engler, R. Seed dispersal distances: a typology based on dispersal modes and plant traits. Bot. Helv. 117, 109–124 (2007).
Google Scholar 
27.Sandel, B. et al. The influence of Late Quaternary climate-change velocity on species endemism. Science (80-) 80(334), 660–664 (2011).ADS 

Google Scholar 
28.Harrison, S. & Noss, R. Endemism hotspots are linked to stable climatic refugia. Ann. Bot. 119, 207–214 (2017).PubMed 
PubMed Central 

Google Scholar 
29.Pignatti, E. & Pignatti, S. Plant life of the Dolomites. (Springer, 2016).30.Pawlowski, B. Remarks on endemism in the flora of the Alps and the Carpathians. Vegetatio 21, 181–243 (1970).
Google Scholar 
31.Schönswetter, P., Stehlik, I., Holderegger, R. & Tribsch, A. Molecular evidence for glacial refugia of mountain plants in the European Alps. Mol. Ecol. 14, 3547–3555 (2005).PubMed 
PubMed Central 

Google Scholar 
32.Carton, A. & Soldati, M. Geomorphological features of the Dolomites (Italy). (1993).33.Bosellini, A., Gianolla, P. & Stefani, M. Geology of the Dolomites. Episodes 26(3), 181–185 (2003).
Google Scholar 
34.Gianolla, P., Panizza, M., Micheletti, C. & Viola, F. Nomination of the Dolomites for inscription on the World Natural Heritage list UNESCO, nomination document. Prov. di Belluno, Prov. Auton. di Bolzano—Bozen, Prov. di Pordenone, Prov. Auton. di Trento, Prov. di Udine (2008).35.Erschbamer, B. et al. Changes in plant species diversity revealed by long-term monitoring on mountain summits in the Dolomites (northern Italy). Preslia 83, 387–401 (2011).
Google Scholar 
36.Unterluggauer, P., Mallaun, M. & Erschbamer, B. The higher the summit, the higher the diversity changes–results of a long-term monitoring project in the Dolomites. Gredleriana 16, 5–34 (2016).
Google Scholar 
37.Guisan, A. & Zimmermann, N. E. Predictive habitat distribution models in ecology. Ecol. Modell. 135, 147–186 (2000).
Google Scholar 
38.Pearson, R. G. Species’ distribution modeling for conservation educators and practitioners. Synth. Am. Museum Nat. Hist. 50, 54–89 (2007).
Google Scholar 
39.Trivedi, M. R., Berry, P. M., Morecroft, M. D. & Dawson, T. P. Spatial scale affects bioclimate model projections of climate change impacts on mountain plants. Glob. Change Biol. 14, 1089–1103 (2008).ADS 

Google Scholar 
40.Lembrechts, J. J., Nijs, I. & Lenoir, J. Incorporating microclimate into species distribution models. Ecography (Cop.) 42, 1267–1279 (2019).
Google Scholar 
41.Perazza, G. & Lorenz, R. Le orchidee dell’Italia nordorientale. Atlante corologico e Guid. al riconoscimento. Ed. Osiride, Rovereto (2013).42.Prosser, F., Bertolli, A., Festi, F. & Perazza, G. Flora del Trentino. Fondazione Museo civico di Rovereto (2019)43.Bertolli A., Prosser F., Tomasi G., Argenti C., – Flora Dolomitica. 50 fiori da conoscere nel patrimonio Unesco. Edizioni Osiride, Rovereto, 68 pp. (2019)44.Guisan, A., Thuiller, W. & Zimmermann, N. E. Habitat suitability and distribution models: with applications in R (Cambridge University Press, Cambridge, 2017).
Google Scholar 
45.Rossi G., Orsenigo S., Gargano D., Montagnani C., Peruzzi L., Fenu G., Abeli T., Alessandrini A., Astuti G., Bacchetta G., Bartolucci F., Bernardo L., Bovio M., Brullo S., Carta A., Castello M., Cogoni D., Conti F., Domina G., Foggi B., Gennai M., Gigante D., Iberite M., Lasen C., Magrini S., Nicolella G., Pinna M.S., Poggio L., Prosser F., Santangelo A., Selvaggi A., Stinca A., Tartaglini N., Troia A., Villani M.C., Wagensommer R.P., Wilhalm T., Blasi C.,. Lista Rossa della Flora Italiana. 2 Endemiti e altre specie minacciate. Ministero dell’Ambiente e della Tutela del Territorio e del Mare (2020)46.Rossi G., Montagnani C., Gargano D., Peruzzi L., Abeli T., Ravera S., Cogoni A., Fenu G., Magrini S., Gennai M., Foggi B., Wagensommer R.P., Venturella G., Blasi C., Raimondo F.M., Orsenigo S. (Eds.), Lista Rossa della Flora Italiana. 1. Policy Species e altre specie minacciate. Comitato Italiano IUCN e Ministero dell’Ambiente e della Tutela del Territorio e del Mare (2013)47.Buffa G., Carpenè B., Casarotto N., Da Pozzo M., Filesi L., Lasen C., Marcucci R., Masin R., Prosser F., Tasinazzo S., Villani M., Zanatta K. Lista rossa regionale piante vascolari del Veneto. Regione Veneto (2016)48.Wilhalm, T. & Hilpold, A. Rote Liste der gefährdeten Gefäßpflanzen Südtirols (Naturmuseum Südtirols, Bozen, 2006).
Google Scholar 
49.Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. data 4, 1–20 (2017).
Google Scholar 
50.Schwalm, C. R., Glendon, S. & Duffy, P. B. RCP8 5 tracks cumulative CO2 emissions. Proc. Natl. Acad. Sci. 117(33), 19656–19657 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
51.Sanderson, B. M., Knutti, R. & Caldwell, P. A representative democracy to reduce interdependency in a multimodel ensemble. J. Clim. 28, 5171–5194 (2015).ADS 

Google Scholar 
52.Kassambara A., & Mundt F. factoextra: Extract
and Visualize the Results of Multivariate Data Analyses. R package
version 1.0.7. https://CRAN.R-project.org/package=factoextra (2020).53.Lenoir, J., Hattab, T. & Pierre, G. Climatic microrefugia under anthropogenic climate change: implications for species redistribution. Ecography (Cop.) 40, 253–266 (2017).
Google Scholar 
54.Araújo, M. B. & New, M. Ensemble forecasting of species distributions. Trends Ecol. Evol. 22, 42–47 (2007).
Google Scholar 
55.Thuiller, W. et al. Package ‘biomod2’. Species Distrib. Model. within an ensemble Forecast. Framew. (2016).56.Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many?. Methods Ecol. Evol. 3, 327–338 (2012).
Google Scholar 
57.Elith, J. et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography (Cop.) 29, 129–151 (2006).
Google Scholar 
58.Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).
Google Scholar 
59.Liu, C., Berry, P. M., Dawson, T. P. & Pearson, R. G. Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28, 385–393 (2005).
Google Scholar 
60.Cao, Y. et al. Using Maxent to model the historic distributions of stonefly species in Illinois streams: the effects of regularization and threshold selections. Ecol. Modell. 259, 30–39 (2013).
Google Scholar 
61.R Core Team. R: A Language and Environment for Statistical Computing. (2020).62.Riley, S. J., DeGloria, S. D. & Elliot, R. Index that quantifies topographic heterogeneity. Intermt. J. Sci. 5, 23–27 (1999).
Google Scholar 
63.Irl, S. D. H. et al. Climate vs topography–spatial patterns of plant species diversity and endemism on a high-elevation island. J. Ecol. 103, 1621–1633 (2015).
Google Scholar 
64.Tarquini, S. & Nannipieri, L. The 10 m-resolution TINITALY DEM as a trans-disciplinary basis for the analysis of the Italian territory: Current trends and new perspectives. Geomorphology 281, 108–115 (2017).ADS 

Google Scholar 
65.Hamann, A., Roberts, D. R., Barber, Q. E., Carroll, C. & Nielsen, S. E. Velocity of climate change algorithms for guiding conservation and management. Glob. Chang. Biol. 21, 997–1004 (2015).ADS 

Google Scholar 
66.Dexter, F. Wilcoxon-Mann-Whitney test used for data that are not normally distributed. Anesth. Anal. 117, 537–538 (2013)67.Geppert, C. et al. Consistent population declines but idiosyncratic range shifts in Alpine orchids under global change. Nat. Commun. 11, 1–11 (2020).
Google Scholar 
68.Erfanian, M. B., Sagharyan, M., Memariani, F. & Ejtehadi, H. Predicting range shifts of three endangered endemic plants of the Khorassan-Kopet Dagh floristic province under global change. Sci. Rep. 11, 1–13 (2021).
Google Scholar 
69.Muñoz-Sáez, A., Choe, H., Boynton, R. M., Elsen, P. R. & Thorne, J. H. Climate exposure shows high risk and few climate refugia for Chilean native vegetation. Sci. Total Environ. 785, 147399 (2021).ADS 

Google Scholar 
70.Dullinger, S. et al. Post-glacial migration lag restricts range filling of plants in the European Alps. Glob. Ecol. Biogeogr. 21, 829–840 (2012).
Google Scholar 
71.Sedlacek, J. F., Bossdorf, O., Cortés, A. J., Wheeler, J. A. & van Kleunen, M. What role do plant–soil interactions play in the habitat suitability and potential range expansion of the alpine dwarf shrub Salix herbacea?. Basic Appl. Ecol. 15(4), 305–315 (2014).
Google Scholar 
72.Di Nuzzo, L. et al. Contrasting multitaxon responses to climate change in Mediterranean mountains. Sci. Rep. 11, 1–12 (2021).
Google Scholar 
73.Zecca, G., Casazza, G., Piscopo, S., Minuto, L. & Grassi, F. Are the responses of plant species to Quaternary climatic changes idiosyncratic? A demographic perspective from the Western Alps. Plant Ecol. Divers. 10, 273–281 (2017).
Google Scholar 
74.Dainese, M. et al. Human disturbance and upward expansion of plants in a warming climate. Nat. Clim. Chang. 7, 577–580 (2017).ADS 

Google Scholar 
75.Boisvert-Marsh, L., Périé, C. & de Blois, S. Divergent responses to climate change and disturbance drive recruitment patterns underlying latitudinal shifts of tree species. J. Ecol. 107, 1956–1969 (2019).
Google Scholar 
76.Malcolm, J. R., Liu, C., Neilson, R. P., Hansen, L. & Hannah, L. E. E. Global warming and extinctions of endemic species from biodiversity hotspots. Conserv. Biol. 20, 538–548 (2006).PubMed 
PubMed Central 

Google Scholar 
77.Casazza, G. et al. Climate change hastens the urgency of conservation for range-restricted plant species in the central-northern Mediterranean region. Biol. Conserv. 179, 129–138 (2014).
Google Scholar 
78.Körner, C. The use of ‘altitude’in ecological research. Trends Ecol. Evol. 22, 569–574 (2007).PubMed 
PubMed Central 

Google Scholar 
79.Engler, R. et al. Predicting future distributions of mountain plants under climate change: does dispersal capacity matter?. Ecography (Cop.) 32, 34–45 (2009).
Google Scholar 
80.Ozinga, W. A. et al. Dispersal failure contributes to plant losses in NW Europe. Ecol. Lett. 12, 66–74 (2009).
Google Scholar 
81.Morueta-Holme, N. et al. Strong upslope shifts in Chimborazo’s vegetation over two centuries since Humboldt. Proc. Natl. Acad. Sci. 112, 12741–12745 (2015).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
82.Niskanen, A. K. J., Niittynen, P., Aalto, J., Väre, H. & Luoto, M. Lost at high latitudes: Arctic and endemic plants under threat as climate warms. Divers. Distrib. 25, 809–821 (2019).
Google Scholar 
83.Trew, B. T. & Maclean, I. M. D. Vulnerability of global biodiversity hotspots to climate change. Glob. Ecol. Biogeogr. 30, 768–783 (2021).
Google Scholar 
84.Garcia, M. B. et al. Rocky habitats as microclimatic refuges for biodiversity. A close-up thermal approach. Environ. Exp. Bot. 170, 103886 (2020).
Google Scholar 
85.Tribsch, A. Areas of endemism of vascular plants in the Eastern Alps in relation to Pleistocene glaciation. J. Biogeogr. 31, 747–760 (2004).
Google Scholar 
86.Keppel, G. et al. The capacity of refugia for conservation planning under climate change. Front. Ecol. Environ. 13, 106–112 (2015).
Google Scholar 
87.Panizza, M. The geomorphodiversity of the Dolomites (Italy): a key of geoheritage assessment. Geoheritage 1, 33–42 (2009).
Google Scholar 
88.Santini, L., Benitez-López, A., Maiorano, L., Čengić, M. & Huijbregts, M. A. J. Assessing the reliability of species distribution projections in climate change research. Divers. Distrib. 27, 1035–1050 (2021).
Google Scholar 
89.Blois, J. L., Zarnetske, P. L., Fitzpatrick, M. C. & Finnegan, S. Climate change and the past, present, and future of biotic interactions. Science (80-) 341, 499–504 (2013).ADS 
CAS 

Google Scholar 
90.Meineri, E. & Hylander, K. Fine-grain, large-domain climate models based on climate station and comprehensive topographic information improve microrefugia detection. Ecography (Cop.) 40, 1003–1013 (2017).
Google Scholar 
91.Ferrarini, A. et al. Planning for assisted colonization of plants in a warming world. Sci. Rep. 6, 1–6 (2016).
Google Scholar 
92.Casazza, G. et al. Combining conservation status and species distribution models for planning assisted colonisation under climate change. J. Ecol. 109, 2284–2295 (2021) More

1.Gartman A, Findlay AJ. Impacts of hydrothermal plume processes on oceanic metal cycles and transport. Nat Geosci. 2020;13:396–402.CAS 

Google Scholar 
2.Sander SG, Koschinsky A. Metal flux from hydrothermal vents increased by organic complexation. Nat Geosci. 2011;4:145–50.CAS 

Google Scholar 
3.German CR, Casciotti KA, Dutay JC, Heimbürger LE, Jenkins WJ, Measures CI, et al. Hydrothermal impacts on trace element and isotope ocean biogeochemistry. Philos Trans R Soc A Math Phys Eng Sci. 2016;374:20160035.
Google Scholar 
4.Ardyna M, Lacour L, Sergi S, d’Ovidio F, Sallée JB, Rembauville M, et al. Hydrothermal vents trigger massive phytoplankton blooms in the Southern Ocean. Nat Commun. 2019;10:1–8.CAS 

Google Scholar 
5.McCollom TM. Geochemical constraints on primary productivity in submarine hydrothermal vent plumes. Deep Res Part I Oceanogr Res Pap. 2000;47:85–101.CAS 

Google Scholar 
6.Dick GJ, Tebo BM. Microbial diversity and biogeochemistry of the Guaymas Basin deep-sea hydrothermal plume. Environ Microbiol. 2010;12:1334–47.CAS 
PubMed 

Google Scholar 
7.Nakamura K, Takai K. Theoretical constraints of physical and chemical properties of hydrothermal fluids on variations in chemolithotrophic microbial communities in seafloor hydrothermal systems. Prog Earth Planet Sci. 2014;1:1–24.
Google Scholar 
8.Dick GJ. The microbiomes of deep-sea hydrothermal vents: distributed globally, shaped locally. Nat Rev Microbiol. 2019;17:271–83.CAS 
PubMed 

Google Scholar 
9.Sunamura M, Higashi Y, Miyako C, Ishibashi JI, Maruyama A. Two bacteria phylotypes are predominant in the Suiyo Seamount hydrothermal plume. Appl Environ Microbiol. 2004;70:1190–8.CAS 
PubMed 
PubMed Central 

Google Scholar 
10.Lavik G, Stührmann T, Brüchert V, Van Der Plas A, Mohrholz V, Lam P, et al. Detoxification of sulphidic African shelf waters by blooming chemolithotrophs. Nature. 2009;457:581–4.CAS 
PubMed 

Google Scholar 
11.Canfield DE, Stewart FJ, Thamdrup B, De Brabandere L, Dalsgaard T, Delong EF, et al. A cryptic sulfur cycle in oxygen-minimum-zone waters off the Chilean coast. Science. 2010;330:1375–8.CAS 
PubMed 

Google Scholar 
12.Callbeck CM, Lavik G, Ferdelman TG, Fuchs B, Gruber-Vodicka HR, Hach PF, et al. Oxygen minimum zone cryptic sulfur cycling sustained by offshore transport of key sulfur oxidizing bacteria. Nat Commun. 2018;9:1.CAS 

Google Scholar 
13.Glaubitz S, Kießlich K, Meeske C, Labrenz M, Jürgens K. SUP05 Dominates the gammaproteobacterial sulfur oxidizer assemblages in pelagic redoxclines of the central baltic and black seas. Appl Environ Microbiol. 2013;79:2767–76.CAS 
PubMed 
PubMed Central 

Google Scholar 
14.Pjevac P, Korlević M, Berg JS, Bura-Nakić E, Ciglenečki I, Amann R, et al. Community shift from phototrophic to chemotrophic sulfide oxidation following anoxic holomixis in a stratified seawater lake. Appl Environ Microbiol. 2015;81:298–308.PubMed 

Google Scholar 
15.Zhou K, Zhang R, Sun J, Zhang W, Tian RM, Chen C, et al. Potential interactions between clade SUP05 sulfur-oxidizing bacteria and phages in hydrothermal vent sponges. Appl Environ Microbiol. 2019;85:1–20.
Google Scholar 
16.Duperron S, Nadalig T, Caprais JC, Sibuet M, Fiala-Médioni A, Amann R, et al. Dual symbiosis in a Bathymodiolus sp. mussel from a methane seep on the Gabon Continental Margin (Southeast Atlantic): 16S rRNA phylogeny and distribution of the symbionts in gills. Appl Environ Microbiol. 2005;71:1694–700.CAS 
PubMed 
PubMed Central 

Google Scholar 
17.Ansorge R, Romano S, Sayavedra L, Porras MÁG, Kupczok A, Tegetmeyer HE, et al. Functional diversity enables multiple symbiont strains to coexist in deep-sea mussels. Nat Microbiol. 2019;4:2487–97.PubMed 

Google Scholar 
18.Anantharaman K, Breier JA, Sheik CS, Dick GJ. Evidence for hydrogen oxidation and metabolic plasticity in widespread deep-sea sulfur-oxidizing bacteria. Proc Natl Acad Sci USA. 2013;110:330–5.CAS 
PubMed 

Google Scholar 
19.Wang W, Li Z, Zeng L, Dong C, Shao Z. The oxidation of hydrocarbons by diverse heterotrophic and mixotrophic bacteria that inhabit deep-sea hydrothermal ecosystems. ISME J. 2020;14:1994–2006.CAS 
PubMed 
PubMed Central 

Google Scholar 
20.Spietz RL, Lundeen RA, Zhao X, Nicastro D, Ingalls AE, Morris RM. Heterotrophic carbon metabolism and energy acquisition in Candidatus Thioglobus singularis strain PS1, a member of the SUP05 clade of marine Gammaproteobacteria. Environ Microbiol. 2019;21:2391–401.CAS 
PubMed 

Google Scholar 
21.Marshall KT, Morris RM. Isolation of an aerobic sulfur oxidizer from the SUP05/Arctic96BD-19 clade. ISME J. 2013;7:452–5.CAS 
PubMed 

Google Scholar 
22.Shah V, Morris RM. Genome sequence of “Candidatus Thioglobus autotrophica” strain EF1, a chemoautotroph from the SUP05 clade of marine Gammaproteobacteria. Genome Announc. 2015;3:e01156–15.PubMed 
PubMed Central 

Google Scholar 
23.van Vliet DM, von Meijenfeldt FAB, Dutilh BE, Villanueva L, Sinninghe Damsté JS, Stams AJM, et al. The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters. Environ Microbiol. 2021;23:2834–57.PubMed 

Google Scholar 
24.De Ronde CEJ, Baker ET, Massoth GJ, Lupton JE, Wright IC, Feely RA, et al. Intra-oceanic subduction-related hydrothermal venting, Kermadec volcanic arc, New Zealand. Earth Planet Sci Lett. 2001;193:359–69.
Google Scholar 
25.De Ronde CEJ, Baker ET, Massoth GJ, Lupton JE, Wright IC, Sparks RJ, et al. Submarine hydrothermal activity along the mid-Kermadec Arc, New Zealand: large-scale effects on venting. Geochem Geophys Geosyst. 2007;8:Q07007.
Google Scholar 
26.Kleint C, Bach W, Diehl A, Fröhberg N, Garbe-Schönberg D, Hartmann JF, et al. Geochemical characterization of highly diverse hydrothermal fluids from volcanic vent systems of the Kermadec intraoceanic arc. Chem Geol. 2019;528:119289.CAS 

Google Scholar 
27.Baker ET, Resing JA, Haymon RM, Tunnicliffe V, Martinez F, Ferrini V, et al. How many vent fields? New estimates of vent field populations on ocean ridges from precise mapping of hydrothermal discharge locations. Prog Earth Planet Sci. 2016;449:186–96.CAS 

Google Scholar 
28.Walker SL, Baker ET, Resing JA, Nakamura K, McLain PD. A new tool for detecting hydrothermal plumes: an ORP sensor for the PMEL MAPR. AGU Fall Meet Abstr. 2007;2007:V21D–0753.
Google Scholar 
29.Herlemann DPR, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 2011;5:1571–9.CAS 
PubMed 
PubMed Central 

Google Scholar 
30.Reintjes G, Tegetmeyer HE, Bürgisser M, Orlić S, Tews I, Zubkov M, et al. On-site analysis of bacterial communities of the ultraoligotrophic South Pacific Gyre. Appl Environ Microbiol. 2019;85:e00184–19.CAS 
PubMed 
PubMed Central 

Google Scholar 
31.Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10–2.
Google Scholar 
32.Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75:7537–41.CAS 
PubMed 
PubMed Central 

Google Scholar 
33.Bushnell B. BBMap (version 35.14) [Software]. 2015. https://sourceforge.net/projects/bbmap/.34.Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–6.CAS 
PubMed 
PubMed Central 

Google Scholar 
35.Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yadhukumar A, et al. ARB: a software environment for sequence data. Nucleic Acids Res. 2004;32:1363–71.CAS 
PubMed 
PubMed Central 

Google Scholar 
36.Pernthaler A, Pernthaler J, Amann R.  Fluorescence in situ hybridization and catalyzed reporter deposition for the identification of marine bacteria. Appl Environ Microbiol. 2002;68:3094–101.CAS 
PubMed 
PubMed Central 

Google Scholar 
37.Andrews S. FastQC: a quality control tool for high throughput sequence data. Babraham Bioinformatics; 2010.38.Rodriguez-R LM, Gunturu S, Tiedje JM, Cole JR, Konstantinidis KT. Nonpareil 3: fast estimation of metagenomic coverage and sequence diversity. mSystems. 2018;3:e00039–18.PubMed 
PubMed Central 

Google Scholar 
39.Li D, Luo R, Liu CM, Leung CM, Ting HF, Sadakane K, et al. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods. 2016;102:3–11.CAS 
PubMed 

Google Scholar 
40.Strous M, Kraft B, Bisdorf R, Tegetmeyer HE. The binning of metagenomic contigs for microbial physiology of mixed cultures. Front Microbiol. 2012;3:410.PubMed 
PubMed Central 

Google Scholar 
41.Alneberg J, Bjarnason BS, De Bruijn I, Schirmer M, Quick J, Ijaz UZ, et al. Binning metagenomic contigs by coverage and composition. Nat Methods. 2014;11:1144–6.CAS 
PubMed 

Google Scholar 
42.Eren AM, Kiefl E, Shaiber A, Veseli I, Miller SE, Schechter MS, et al. Community-led, integrated, reproducible multi-omics with anvi’o. Nat Microbiol. 2021;6:3–6.CAS 
PubMed 
PubMed Central 

Google Scholar 
43.Meier DV, Bach W, Girguis PR, Gruber-Vodicka HR, Reeves EP, Richter M, et al. Heterotrophic proteobacteria in the vicinity of diffuse hydrothermal venting. Environ Microbiol. 2016;18:4348–68.PubMed 

Google Scholar 
44.Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77.CAS 
PubMed 
PubMed Central 

Google Scholar 
45.Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.CAS 
PubMed 
PubMed Central 

Google Scholar 
46.Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
PubMed 
PubMed Central 

Google Scholar 
47.Kopylova E, Noé L, Touzet H. SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics. 2012;28:3211–7.CAS 
PubMed 

Google Scholar 
48.Gomes AÉ, Stuchi LP, Siqueira NM, Henrique JB, Vicentini R, Ribeiro ML, et al. Selection and validation of reference genes for gene expression studies in Klebsiella pneumoniae using Reverse Transcription Quantitative real-time PCR. Sci Rep. 2018;8:1–4.
Google Scholar 
49.Kolde R. pheatmap: Pretty heatmaps. 2015. https://CRAN.R-project.org/package=pheatmap.50.Garnier S. viridis: Default Color Maps from’matplotlib’. 2017. https://CRAN.R-project.org/.51.R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2013.52.Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. Vegan: Community ecology package. 2020.53.Pena EA, Slate EH. gvlma: Global validation of linear models assumptions. R package version 1.0.0.3. 2019. https://CRAN.R-project.org/package=gvlma.54.Anderson MJ. A new method for non parametric multivariate analysis of variance. Austral Ecol. 2001;26:32–46.
Google Scholar 
55.Waite DW, Chuvochina M, Pelikan C, Parks DH, Yilmaz P, Wagner M, et al. Proposal to reclassify the proteobacterial classes Deltaproteobacteria and Oligoflexia, and the phylum Thermodesulfobacteria into four phyla reflecting major functional capabilities. Int J Syst Evol Microbiol. 2020;70:5972–6016.CAS 
PubMed 

Google Scholar 
56.Anantharaman K, Breier JA, Dick GJ. Metagenomic resolution of microbial functions in deep-sea hydrothermal plumes across the Eastern Lau Spreading Center. ISME J. 2016;10:225–39.CAS 
PubMed 

Google Scholar 
57.Biller SJ, Berube PM, Dooley K, Williams M, Satinsky BM, Hackl T, et al. Data descriptor: marine microbial metagenomes sampled across space and time. Sci Data. 2018;5:1–7.
Google Scholar 
58.Meier DV, Pjevac P, Bach W, Hourdez S, Girguis PR, Vidoudez C, et al. Niche partitioning of diverse sulfur-oxidizing bacteria at hydrothermal vents. ISME J. 2017;11:1545–58.CAS 
PubMed 
PubMed Central 

Google Scholar 
59.Chaumeil P-A, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2019;36:1925–7.PubMed Central 

Google Scholar 
60.Zhou Z, Tran PQ, Kieft K, Anantharaman K. Genome diversification in globally distributed novel marine Proteobacteria is linked to environmental adaptation. ISME J. 2020;14:2060–77.CAS 
PubMed 
PubMed Central 

Google Scholar 
61.Parks DH, Rinke C, Chuvochina M, Chaumeil PA, Woodcroft BJ, Evans PN, et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat Microbiol. 2017;2:1533–42.CAS 
PubMed 

Google Scholar 
62.Blackburn NT, Clarke AJ. Identification of four families of peptidoglycan lytic transglycosylases. J Mol Evol. 2001;52:78–84.CAS 
PubMed 

Google Scholar 
63.Hashimoto W, Ochiai A, Momma K, Itoh T, Mikami B, Maruyama Y, et al. Crystal structure of the glycosidase family 73 peptidoglycan hydrolase FlgJ. Biochem Biophys Res Commun. 2009;381:16–21.CAS 
PubMed 

Google Scholar 
64.Ilbert M, Bonnefoy V. Insight into the evolution of the iron oxidation pathways. Biochim Biophys Acta Bioenerg. 2013;1827:161–75.CAS 

Google Scholar 
65.Barco RA, Emerson D, Sylvan JB, Orcutt BN, Jacobson Meyers ME, Ramírez GA, et al. New insight into microbial iron oxidation as revealed by the proteomic profile of an obligate iron-oxidizing chemolithoautotroph. Appl Environ Microbiol. 2015;81:5927–37.CAS 
PubMed 
PubMed Central 

Google Scholar 
66.Guo J, Bolduc B, Zayed AA, Varsani A, Dominguez-Huerta G, Delmont TO, et al. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome. 2021;9:1–13.67.Duarte CM. Seafaring in the 21st century: the Malaspina 2010 circumnavigation expedition. Limnol Oceanogr Bull. 2015;24:11–14.
Google Scholar 
68.Sheik CS, Anantharaman K, Breier JA, Sylvan JB, Edwards KJ, Dick GJ. Spatially resolved sampling reveals dynamic microbial communities in rising hydrothermal plumes across a back-arc basin. ISME J. 2015;9:1434–45.PubMed 

Google Scholar 
69.Konstantinidis KT, Rosselló-Móra R, Amann R. Uncultivated microbes in need of their own taxonomy. ISME J. 2017;11:2399–406.PubMed 
PubMed Central 

Google Scholar 
70.Murray AE, Freudenstein J, Gribaldo S, Hatzenpichler R, Hugenholtz P, Kämpfer P, et al. Roadmap for naming uncultivated Archaea and Bacteria. Nat Microbiol. 2020;5:987–94.CAS 
PubMed 
PubMed Central 

Google Scholar 
71.Shah V, Zhao X, Lundeen RA, Ingalls AE, Nicastro D, Morris RM. Morphological plasticity in a sulfur-oxidizing marine bacterium from the SUP05 clade enhances dark carbon fixation. MBio. 2019;10:e00216–19.CAS 
PubMed 
PubMed Central 

Google Scholar 
72.Yamamoto M, Takai K. Sulfur metabolisms in Epsilon- and Gammaproteobacteria in deep-sea hydrothermal fields. Front Microbiol. 2011;2:192.CAS 
PubMed 
PubMed Central 

Google Scholar 
73.White GF, Edwards MJ, Gomez-Perez L, Richardson DJ, Butt JN, Clarke TA. Mechanisms of bacterial extracellular electron exchange. Adv Micro Physiol. 2016;68:87–138.CAS 

Google Scholar 
74.Findlay AJ, Estes ER, Gartman A, Yücel M, Kamyshny A, Luther GW. Iron and sulfide nanoparticle formation and transport in nascent hydrothermal vent plumes. Nat Commun. 2019;10:1–7.CAS 

Google Scholar 
75.Gartman A, Luther GW. Oxidation of synthesized sub-micron pyrite (FeS2) in seawater. Geochim Cosmochim Acta. 2014;144:96–108.CAS 

Google Scholar 
76.Bonnefoy V, Holmes DS. Genomic insights into microbial iron oxidation and iron uptake strategies in extremely acidic environments. Environ Microbiol. 2012;14:1597–611.CAS 
PubMed 

Google Scholar 
77.Singh VK, Singh AL, Singh R, Kumar A. Iron oxidizing bacteria: insights on diversity, mechanism of iron oxidation and role in management of metal pollution. Environ Sustain. 2018;1:221–31.
Google Scholar 
78.He S, Barco RA, Emerson D, Roden EE. Comparative genomic analysis of neutrophilic iron(II) oxidizer genomes for candidate genes in extracellular electron transfer. Front Microbiol. 2017;8:1584.PubMed 
PubMed Central 

Google Scholar 
79.McAllister SM, Polson SW, Butterfield DA, Glazer BT, Sylvan JB, Chan CS. Validating the Cyc2 neutrophilic iron oxidation pathway using meta-omics of Zetaproteobacteria iron mats at marine hydrothermal vents. mSystems. 2020;5:e00553–19.PubMed 
PubMed Central 

Google Scholar 
80.Barco RA, Hoffman CL, Ramírez GA, Toner BM, Edwards KJ, Sylvan JB. In-situ incubation of iron-sulfur mineral reveals a diverse chemolithoautotrophic community and a new biogeochemical role for Thiomicrospira. Environ Microbiol. 2017;19:1322–37.CAS 
PubMed 

Google Scholar 
81.Lesniewski RA, Jain S, Anantharaman K, Schloss PD, Dick GJ. The metatranscriptome of a deep-sea hydrothermal plume is dominated by water column methanotrophs and lithotrophs. ISME J. 2012;6:2257–68.CAS 
PubMed 
PubMed Central 

Google Scholar 
82.Reed DC, Breier JA, Jiang H, Anantharaman K, Klausmeier CA, Toner BM, et al. Predicting the response of the deep-ocean microbiome to geochemical perturbations by hydrothermal vents. ISME J. 2015;9:1857–69.PubMed 
PubMed Central 

Google Scholar 
83.Maki JS. Bacterial intracellular sulfur globules: structure and function. J Mol Microbiol Biotechnol. 2013;23:270–80.CAS 
PubMed 

Google Scholar 
84.Neuholz R, Kleint C, Schnetger B, Koschinsky A, Laan P, Middag R, et al. Submarine hydrothermal discharge and fluxes of dissolved Fe and Mn, and He isotopes at Brothers Volcano based on radium isotopes. Minerals. 2020;10:969.CAS 

Google Scholar 
85.Waite DW, Vanwonterghem I, Rinke C, Parks DH, Zhang Y, Takai K, et al. Comparative genomic analysis of the class Epsilonproteobacteria and proposed reclassification to Epsilonbacteraeota (phyl. nov.). Front Microbiol. 2017;8:682.PubMed 
PubMed Central 

Google Scholar 
86.Waite DW, Vanwonterghem I, Rinke C, Parks DH, Zhang Y, Takai K, et al. Addendum: comparative genomic analysis of the class Epsilonproteobacteria and proposed reclassification to Epsilonbacteraeota (phyl. nov.). Front Microbiol. 2018;9:772.PubMed 
PubMed Central 

Google Scholar  More

1.Kiessling, W., Simpson, C. & Foote, M. Reefs as cradles of evolution and sources of biodiversity in the Phanerozoic. Science 327, 196–198. https://doi.org/10.1126/science.1182241 (2016).ADS 
CAS 
Article 

Google Scholar 
2.Kiessling, W. Geological and biologic controls on the evolution of reefs. Annu. Rev. Ecol. Evol. Syst. 40, 173–192. https://doi.org/10.1146/annurev.ecolsys.110308.120251(2009) (2009).Article 

Google Scholar 
3.Talent, J. A. Organic reef-building: Episodes of extinction and symbiosis?. Senckenb. Lethaea 69, 315–368 (1988).
Google Scholar 
4.Flügel, E. & Kiessling, W. Patterns of Phanerozoic reef crises. SEPM Spec. Public. 72, 691–733 (2002).
Google Scholar 
5.Pandolfi, J. M. & Kiessling, W. Gaining insights from past reefs to inform understanding of coral reef response to global climate change. Curr. Opin. Environ. Sustain. 7, 52–58. https://doi.org/10.1016/j.cosust.2013.11.020 (2014).Article 

Google Scholar 
6.Copper, P. Ancient reef ecosystem expansion and collapse. Coral Reefs 13, 3–11 (1994).ADS 
Article 

Google Scholar 
7.Copper, P. Silurian and Devonian reefs: 80 million years of global greenhouse between two ice ages. SEPM Spec. Public. 72, 181–238 (2002).
Google Scholar 
8.Copper, P. & Scotese, C. R. Megareefs in Middle Devonain supergreenhouse climates. Spec. Public. Geol. Soc. Am. 370, 209–230. https://doi.org/10.1130/0-8137-2370-1.209 (2003).Article 

Google Scholar 
9.Ries, J. B. Geological and experimental evidence for secular variation in seawater Mg/Ca (calcite-aragonite seas) and its effects on marine biological calcification. Biogeosciences 7(9), 2795–2849 (2010).ADS 
CAS 
Article 

Google Scholar 
10.Scotese, C. R., Song, H., Mills, B. J. & van der Meer, D. G. Phanerozoic paleotemperatures: The earth’s changing climate during the last 540 million years. Earth Sci. Rev. https://doi.org/10.1016/j.earscirev.2021.103503 (2021).Article 

Google Scholar 
11.Zapalski, M. K., Nowicki, J., Jakubowicz, M. & Berkowski, B. Tabulate corals across the Frasnian/Famennian boundary: architectural turnover and its possible relation to ancient photosymbiosis. Palaeogeogr. Palaeoclimatol. Palaeoecol. 487, 416–429. https://doi.org/10.1016/j.palaeo.2017.09.028 (2017).Article 

Google Scholar 
12.Mora, C. I., Driese, S. G. & Seager, P. G. Carbon dioxide in the Paleozoic atmosphere: Evidence from carbon-isotope compositions of pedogenic carbonate. Geology 19(10), 1017–1020 (1991).ADS 
CAS 
Article 

Google Scholar 
13.Foster, G. L., Royer, D. L. & Lunt, D. J. Future climate forcing potentially without precedent in the last 420 million years. Nat. Commun. 8(1), 1–8. https://doi.org/10.1038/ncomms14845 (2017).ADS 
CAS 
Article 

Google Scholar 
14.Kiessling, W., Flügel, E. & Golonka, J. Paleoreef maps: evaluation of a comprehensive database on Phanerozoic reefs. AAPG Bull. 83(10), 1552–1587 (1999).
Google Scholar 
15.Burchette, T. P. European Devonian reefs: a review of current concepts and models. SEPM Spec. Public. 30, 85–142 (1981).
Google Scholar 
16.Ziegler, A. M., Scotese, C. R., McKerrow, W. S., Johnson, M. E. & Bambach, R. K. Paleozoic paleogeography. Annu. Rev. Earth Planet. Sci. 7(1), 473–502 (1979).ADS 
Article 

Google Scholar 
17.Belka, Z. & Narkiewicz, M. Devonian. In: McCann, T. The Geology of Central Europe, 1: Precambrian and Palaeozoic. 383–410. The Geological Society of London (2008).18.Golonka, J. Plate-tectonic maps of the Phanerozoic. SEPM Spec. Public. 72, 21–75 (2002).
Google Scholar 
19.Oczlon, M. S. Ocean currents and unconformities: the north Gondwana Middle Devonian. Geology 18(6), 509–512 (1990).ADS 
Article 

Google Scholar 
20.Dopieralska, J. Reconstructing seawater circulation on the Moroccan shelf of Gondwana during the Late Devonian: Evidence from Nd isotope composition of conodonts. Geochem. Geophys. Geosyst. 10(3), Q03015. https://doi.org/10.1029/2008GC002247 (2009).ADS 
CAS 
Article 

Google Scholar 
21.Jakubowicz, M. et al. At the southern limits of the Devonian reef zone: Palaeoecology of the Aferdou el Mrakib reef (Givetian, eastern Anti-Atlas, Morocco). Geol. J. 54(1), 10–38. https://doi.org/10.1002/gj.3152 (2019).Article 

Google Scholar 
22.Wood, R. Reef evolution (Oxford University Press, 1999).
Google Scholar 
23.Raup, D. M. & Sepkoski, J. J. Mass extinctions in the marine fossil record. Science 215(4539), 1501–1503 (1982).ADS 
CAS 
Article 

Google Scholar 
24.McGhee, G. R. Jr., Sheehan, P. M., Bottjer, D. J. & Droser, M. L. Ecological ranking of Phanerozoic biodiversity crises: the Serpukhovian (early Carboniferous) crisis had a greater ecological impact than the end-Ordovician. Geology 40(2), 147–150. https://doi.org/10.1016/j.palaeo.2004.05.010 (2012).ADS 
Article 

Google Scholar 
25.Stanley, S. M. Estimates of the magnitudes of major marine mass extinctions in earth history. Proc. Natl. Acad. Sci. 113(42), E6325–E6334. https://doi.org/10.1073/pnas.1613094113 (2016).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
26.Zapalski, M. K., Wrzołek, T., Skompski, S. & Berkowski, B. Deep in shadows, deep in time: the oldest mesophotic coral ecosystems from the Devonian of the Holy Cross Mountains (Poland). Coral Reefs 36(3), 847–860. https://doi.org/10.1007/s00338-017-1575-8 (2017).ADS 
Article 

Google Scholar 
27.Zapalski, M. K., Baird, A. H., Bridge, T., Jakubowicz, M. & Daniell, J. Unusual shallow water Devonian coral community from Queensland and its recent analogues from the inshore Great Barrier Reef. Coral Reefs 40(2), 417–431. https://doi.org/10.1007/s00338-020-02048-9 (2021).Article 

Google Scholar 
28.Zapalski, M. K., Hubert, B. L., Nicollin, J. P., Mistiaen, B. & Brice, D. The palaeobiodiversity of stromatoporoids, tabulates and brachiopods in the Devonian of the Ardennes–changes through time. Bulletin de la Société Géologique de France 178(5), 383–390. https://doi.org/10.2113/gssgfbull.178.5.383 (2007).Article 

Google Scholar 
29.Zapalski, M., Pinte, E. & Mistiaen, B. Late Famennian? Chaetosalpinx in Yavorskia (Tabulata): the youngest record of tabulate endobionts. Acta Geol. Pol. 58(3), 321–324 (2008).
Google Scholar 
30.Zapalski, M. K. & Berkowski, B. The oldest species of? Yavorskia (Tabulata) from the upper Famennian of the Holy Cross Mountains (Poland). Acta Geol. Pol. 62(2), 197–204 (2012).
Google Scholar 
31.Zapalski, M. K., Berkowski, B. & Wrzołek, T. Tabulate corals after the Frasnian/Famennian crisis: a unique fauna from the Holy Cross Mountains, Poland. PLoS ONE 11(3), e0149767. https://doi.org/10.1371/journal.pone.0149767 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
32.Stanley, G. D. Jr. & Lipps, J. H. Photosymbiosis: the driving force for reef success and failure. Paleontol. Soc. Paper 17, 33–60 (2011).Article 

Google Scholar 
33.Coates, A. G. & Jackson, J. B. C. Clonal growth, algal symbiosis, and reef formation by corals. Paleobiology 13, 363–378 (1987).Article 

Google Scholar 
34.Zapalski, M. K. Evidence of photosymbiosis in Palaeozoic tabulate corals. Proc. R. Soc B Biol. Sci. 281(1775), 20132663. https://doi.org/10.1098/rspb.2013.2663 (2014).CAS 
Article 

Google Scholar 
35.Zapalski, M. K. & Berkowski, B. The Silurian mesophotic coral ecosystems: 430 million years of photosymbiosis. Coral Reefs 38(1), 137–147. https://doi.org/10.1007/s00338-018-01761-w (2019).ADS 
Article 

Google Scholar 
36.Coates, A. G., & Oliver Jr, W. A. Coloniality of Coral Zoantharia: Animal Colonies.–3–29 (1973).37.Lipps, J. H., & Stanley, G. D. Photosymbiosis in past and present reefs. In Coral Reefs at the Crossroads (pp. 47–68). Springer (2016).38.Blieck, A., Brice, D., Fesir, R., Guillot, F., Majesté-Mejoulas, C., and Meillez, F., The Devonian of France and Belgium, in McMillan, A.F., Embry, A.F., and Glass, D.J., eds., Devonian of the world, Canadian Society of Petroleum Geologists, Calgary, 1, p. 359–400 (1988)39.Porter, J. W. Autotrophy, heterotrophy, and resource partitioning in Caribbean reef-building corals. Am. Nat. 110, 731–742 (1976).ADS 
Article 

Google Scholar 
40.McGhee, G. R. Jr., Clapham, M. E., Sheehan, P. M., Bottjer, D. J. & Droser, M. L. A new ecological-severity ranking of major Phanerozoic biodiversity crises. Palaeogeogr. Palaeoclimatol. Palaeoecol. 370, 260–270 (2013).Article 

Google Scholar 
41.Aboussalam, Z. S. & Becker, R. T. The global Taghanic Biocrisis (Givetian) in the eastern Anti-Atlas, Morocco. Palaeogeogr. Palaeoclimatol. Palaeoecol. 304(1–2), 136–164 (2011).Article 

Google Scholar 
42.Zambito, J. J., Brett, C. E., & Baird, G. C. The Late Middle Devonian (Givetian) Global Taghanic Biocrisis in its type area (northern Appalachian Basin): geologically rapid faunal transitions driven by global and local environmental changes. In Earth and Life (pp. 677–703). Springer (2012).43.Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359(6371), 80–83. https://doi.org/10.1126/science.aan8048 (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
44.Racki, G. A volcanic scenario for the Frasnian-Fammenian major biotic crisis and other Late Devonian global changes: More answers than questions?. Global Planet. Change 189, 103174 (2020).Article 

Google Scholar 
45.Kiessling, W. & Simpson, C. On the potential for ocean acidification to be a general cause of ancient reef crises. Glob. Change Biol. 17(1), 56–67 (2011).ADS 
Article 

Google Scholar 
46.Kowalewski, M. Time-averaging, overcompleteness, and the geological record. J. Geol. 104(3), 317–326 (1996).ADS 
Article 

Google Scholar 
47.Hubert, B. L., Zapalski, M., Nicollin, J. P., Mistiaen, B. & Brice, D. Selected benthic faunas from the Devonian of the Ardennes: an estimation of palaeobiodiversity. Acta Geol. Pol. 57(2), 223–262 (2007).
Google Scholar 
48.Zapalski, M. K. Tabulata (anthozoa) from the givetian and frasnian of the southern region of the holy cross Mts. (Poland). Spec. Pap. Palaeontol. 87, 1–100 (2012).
Google Scholar 
49.Nowiński, A. Tabulata and chaetetida from the devonian and carboniferous of southern Poland. Palaeontol. Pol. 35, 1–125 (1976).
Google Scholar 
50.McWilliam, M. et al. Biogeographical disparity in the functional diversity and redundancy of corals. Proc. Natl. Acad. Sci. 115(12), 3084–3089. https://doi.org/10.1073/pnas.1716643115 (2018).CAS 
Article 
PubMed 
PubMed Central 

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

Google Scholar 
52.Laliberté, E., Legendre, P., & Shipley, B. (2014). FD: measuring functional diversity from multiple traits, and other tools for functional ecology. R package version 1.0–12.53.Mouillot, D., Graham, N. A. J., Villeger, S., Mason, N. W. H. & Bellwood, D. R. A functional approach reveals community responses to disturbance. Trends Ecol. Evol. 28, 167–177. https://doi.org/10.1016/j.tree.2012.10.004 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
54.Oksanen, Jari, F. Guillaume Blanchet, Michael Friendly, Roeland Kindt, Pierre Legendre, Dan McGlinn, Peter R. Minchin et al. “Package ‘vegan’.” (2020). More

Pollen collection and RNA extractionPollen is a microscopic and notoriously resistant plant product. Thus, methods to collect a sufficient and roughly equivalent volume of pollen per species, and to ensure RNA was collected from viruses both internal and external to pollen grains, were developed specifically for this work. At each of the four regions, we identified visually asymptomatic plants species that were in full flower and in high enough abundance to achieve our pollen sample minimum. Many of the pollen samples were collected from public roadsides. However, some from the California Grasslands were collected from the University of California’s McLaughlin Natural Reserve, and some from the Eastern Deciduous Agro-forest Interface were collected from the University of Pittsburgh’s Pymatuning Laboratory of Ecology. We had permission to sample in both places. In addition, we obtained permission from the USDA Forest Service to sample in the Till Ridge Cove area of the Chattahoochee-Oconee National Forest for sampling in Central Appalachia. None of the sampled plants displayed classic viral symptoms (e.g., leaf yellowing, vein clearing, leaf distortions, growth abnormalities). To achieve the broadest representation of plant species, we selected species in different families, where feasible. Also when possible, we focused primarily on perennial species to avoid any effects of life history variation. From these, we collected 30 to 50 mg of pollen from newly dehiscing anthers (3–967 fresh hermaphroditic flowers from 1–27 plants per species; Supplementary Table 3) in situ using a sterile sonic dismembrator (Fisherbrand Model 50, Fisher Scientific, Waltham, MA, USA) with a frequency of 20 Hz. We removed non-pollen tissues (e.g., anther debris) with sterile forceps. In addition to removing non-pollen debris that was visible to the naked eye in the field at the time of pollen sample collection, we conducted microscopic and gene expression analyses to confirm the purity of the pollen samples in the lab (Supplementary Methods). Visibly pure pollen from a single species was transferred to a 2-mL collection tube with Lysing Matrix D (MP Biomedicals, Irvine, CA, USA) and kept on dry ice until transported to and stored at −80°C at the University of Pittsburgh (Pittsburgh, PA, USA).Before extracting the total RNA, we freeze-dried the pollen samples (FreeZone 4.5 Liter Benchtop Freeze Dry System, Labconco Corporation, Kansas City, MO, USA) and lysed with a TissueLyser II (Qiagen, Inc., Germantown, MD, USA) at 30 Hz with varying times for different plant species (Supplementary Table 3). We confirmed via microscopy that this protocol resulted in the breakage of ≥50% of the pollen grains in a sample. The total RNA, including dsRNA, was extracted using the Quick-RNA Plant Miniprep Extraction Kit (Zymo Research Corporation, Irvine, CA, USA), following the full manufacturer’s protocol, including the optional steps of in-column DNA digestion and inhibitor removal.RNA sequencingWe assessed the quantity and quality of the total RNA extracted from each pollen sample with a Qubit 2.0 fluorometer (Invitrogen, ThermoFisher Scientific, Waltham, MA, USA) and with TapeStation analyses performed by the Genomics Research Core (GRC) at the University of Pittsburgh. Only samples with an RNA integrity value of ≥1.9 were used (Supplementary Table 3). Stranded RNA libraries were prepared by the GRC using the TruSeq Total RNA Library Kit (Illumina, Inc., San Diego, CA, USA), and ribosomal depletion was performed using a RiboZero Plant Leaf Kit (Illumina, Inc., San Diego, CA, USA). At the GRC, we pooled depleted RNA libraries from six species on a single lane of an Illumina NextSeq500 platform.Pre-virus detection stepsA sequencing depth of 117–260 million 75 bp paired-end reads was achieved per sample (Supplementary Table 3). Sequences were demultiplexed and trimmed of adapter sequences. We used the Pickaxe pipeline42,60,61 to detect known and novel pollen-associated viruses. First, Pickaxe removes poor-quality raw reads42,60,61 and aligns the quality-filtered reads using the Bowtie2 aligner with default parameters62 to a subtraction library. Each customized subtraction library contained the host plant species genome or the most closely related plant genomes in the National Center for Biotechnology Information (NCBI) database, if the host plant genome was not available (Supplementary Table 7), as well as other possible contaminant genomes (e.g., the human genome)42,60,61. The subtraction libraries with 1–8 closely related plant genomes, a bioinformatically tractable amount, were used to remove plant sequences, which allows for a conservative estimate of the viruses associated with pollen to be made. The size of the subtraction libraries did not influence the number of identified viruses, as there was no correlation between library size and either estimate of virus richness (conservative: r = 0.08, P = 0.75; relaxed: r = 0.06, P = 0.77). After subtraction, only non-plant reads remained and were used for viral detection.Known RNA virus detection, identity confirmationWith Pickaxe, we used the Bowtie2 aligner with default parameters62 (v2.3.4.2-3) to align viral non-plant reads to Viral RefSeq42,60,61 (hereafter, VRS; Index of /refseq/release/viral (nih.gov)). Each known virus reflects the top hit of an alignment to VRS42,60,61. Following Cantalupo et al.42, we considered a known virus to be present if the viral reads covered at least 20% of the top hit and aligned to it at least ten times. For viruses with segmented genomes, at least one segment was required to meet these criteria.Contig annotation and extension; novel RNA viral genome detection, identity confirmationViral reads were assembled into contigs using the CLC Assembly Cell (Qiagen Digital Insights, Redwood City, CA, USA), and Pickaxe was used to remove repetitive, short ( More

Female plants must not only allocate resources to flowering but also to producing seeds as well as fruits and/or cones. This suggests that the costs of reproduction are higher for female than male plants, or for female function of hermaphrodite plants. Some dioecious plants (i.e. separate male and female plants) are vegetatively very different (i.e. dimorphic) between the sexes, such as females having larger branch and leaf sizes. Differences between male and female resource allocation to reproduction and the possible consequences of this for vegetative dimorphism in dioecious plants, is a central issue in plant evolution but it is a controversial and difficult topic1,2. In the most highly cited paper on this topic, Obeso1 notes it is practically impossible to measure the direct costs of male and female allocation to sexual reproduction. For example, most vascular plant species (about 95%) are hermaphrodites which makes measuring direct allocation by the two sexes, difficult. Thus Paterno et al.3 used an indirect allometric method to measure sexual allocation in hermaphroditic inflorescences and concluded that larger flowers represent greater relative allocation to male function.The problem of shared sexual allocation to inflorescences is avoided in dioecious plants making them important tests for ideas of sexual allocation in plants. However, they are both rare as species and as individuals and are typically large, forest trees. For example, there are relatively few dioecious individual trees in the very large Barro Colorado forest tree data set4. Again, this large size makes direct measurement, such as of allocation to reproductive structures, difficult. The Cape Floral Region is a useful place to investigate sexual allocation in plants and its consequences, because dioecy is relatively common and vegetative dimorphism between the sexes can be extreme. Also, Cape plants are amenable to research being short (about 2–5 m), rapidly mature and short-lived (about 5–20 years). Thus, the large (about 85 spp.) Cape genus Leucadendron (Proteaceae) is probably the most researched genus globally for male and female differences5,6,7,8,9,10,11,12,13,14.Even in these dioecious plants it is difficult to directly measure allocation to male and female function because of the difficulty of finding a common currency to compare allocation. For example, comparing allocation differences in attractiveness, nectar, seeds, pollen, cones and fruits and differences in the timing of producing these structures1. In Leucadendron males are generally more visually attractive than females. This is achieved by the loss of photosynthetic capacity in floral leaves and bracts12,15. It would be difficult to directly compare this photosynthetic loss in males, with for instance, female allocation to cones and seeds. Despite the difficulties in directly measuring and comparing allocation to reproduction, the consensus is that female allocation to sexual reproduction typically exceeds male allocation1, including in Leucadendron2,9.Greater female allocation to reproduction is one of the suggested reasons for vegetative dimorphism between the sexes2. The three main hypotheses for sexual vegetative dimorphism are (i) greater female sexual resource allocation requires this to be balanced by having a more efficient physiology (resource use efficiency hypothesis), or (ii) greater female allocation requires females to be in the more optimum habitats (the sexual site dimorphism hypothesis) and this facilitates vegetative differences, such as larger female leaves in the more mesic habitats. Finally, (iii) vegetative dimorphism may be a consequence of selection on reproductive traits (reproductive traits hypothesis). In support of the resource use efficiency hypothesis in Leucadendron, Harris and Pannell9 argue that supplying water to live, closed cones in the canopy of serotinous Leucadendron females is a form of maternal care that non-serotinous species and males do not incur. To keep these cones from opening they need always to be hydrated and therefore serotinous females need to be more efficient in their water use than their males. They argued that fewer and thicker branches in females provides a hydraulic advantage. However, the data in Midgley8 and Roddy et al.14 showed no support for sexual differences in water use efficiency. Clearly, there are opposing views as to whether females allocate more to reproduction than males and whether females are eco-physiologically more efficient than males.The sexual site dimorphism hypothesis has not been tested for Leucadendron presumably because males and females co-occur on a small spatial scale16 but is tested in the present analysis of Aulax umbellata and A. cancellata. In support of the reproductive trait’s hypothesis, it was argued5 that in Leucadendron, vegetative dimorphism is an allometric consequence of selection for smaller male inflorescences. Smaller inflorescences are then associated with more, but narrower, stems and thus smaller leaves via Corners Rules5. Besides the evolutionary relevance for understanding sexual differences in allocation, it may also have conservation implications. For example, Hultine et al.17 argued that dioecious plants are under more threat than hermaphrodites because dioecious females are presumed to allocate more resources to reproduction than males. As global change progresses, females may suffer greater mortality and thus dioecious populations may have lower reproductive potential if they become more male biased.One way around the measurement problem of determining direct allocation to sexual reproduction is to use indirect methods based on trade-offs1 such as the influence of allocation to sexual reproduction, on sex ratios and sizes of co-occurring male and female plants. If for example, males allocated less to reproduction than co-occurring females, they should be relatively larger or live longer and this would impact size and sex ratios, especially as plants age and competition intensifies.
The Cape is uniquely suitable to consider allocation differences between the sexes because populations of dioecious Cape species are often large ( > 1000’s of plants ha−1) and with males and females co-existing at a fine spatial scale. The Cape Proteaceae grow in a stressful summer dry Mediterranean climate with nutrient-poor soils18. This provides strong selection on reproductive allocation to seeds (such as large size and high nutrient concentrations) to produce seedlings large enough to survive their first summer. The Cape Proteaceae are strongly fire-adapted. For example, many species are serotinous (canopy storage of seeds in live, closed cones which mainly open after fire)19. This too requires high female sex allocation to maintaining cones in the canopy. Most Cape Proteaceae species are post-fire re-seeders19 in that all plants die in fire. This results in single-aged populations of single-stemmed non-clonal individuals; adults die in fires and dense patches of seedlings establish in the first winter after the fire and die in the next fire. Co-occurring males and females have the same age and thus differences in size or sex ratios will mostly reflect allocation differences and competition rather than age or habitat. Also, because seedlings in the Cape grow up in an open post-fire environment, woody plants do not need to allocate specifically to height growth, to achieve full light. They are in full light their whole lives and therefore any sexual architectural differences do not reflect differences in habitat shadiness. Here we focused on Aulax umbellata, but also present sex ratios and size metrics for the congeneric A. cancellata. These are two common, single-stemmed strongly serotinous Cape species in the Proteaceae which are highly vegetatively dimorphic. Although both Leucadendron and Aulax are dioecious, a rare trait in the family, this represents independent evolution as the two genera are not close phylogenetically20. We test the hypothesis that vegetative sexual dimorphism in Aulax umbellata and Aulax cancellata can be explained by differences in allocation to growth. We predicted that co-occurring males and females would occur in equal sex ratios and be equal in size due to equal growth, despite vegetative dimorphism. More