Ecology

1.Namita, P., Mukesh, R. & Vijay, K. J. Camellia Sinensis (Green Tea): A review. Glob. J. Pharmacol. 6(2), 52–59 (2012).
Google Scholar 
2.Chang, K. World Tea Production and Trade. Current and Future Development (FAO, Rome, 2015).
Google Scholar 
3.Chang, K. & Brattlof, M. World Tea Production and Trade. Current and Future Development (FAO, 2015).
Google Scholar 
4.Kochlamazashvili, I. & Kakulia, N. The Georgian Tea Sector: A Value Chain Study. ISET Policy Institute. Study prepared in the framework of ENPARD project Cooperation for Rural Prosperity in Georgia (2015).5.Lesica, P., McCune, B., Cooper, S. V. & Hong, W. S. Differences in lichen and bryophyte communities between old-growth and managed second-growth forests in the Svan Valley Montana. Can. J. Bot. 69, 1745–1755 (1991).Article 

Google Scholar 
6.Nowak, A., Plášek, V., Nobis, M. & Nowak, S. Epiphytic communities of open habitats in the Western Tian-Shan Mts (Middle Asia: Kyrgyzstan). Cryptog. Bryol. 37(4), 415–433 (2016).Article 

Google Scholar 
7.Rhoades, F. M. Nonvascular epiphytes in forest canopies: Worldwide distribution, abundance and ecological roles. In Forest Canopies (eds. Lowman, M.D. & Nadkarni, N. M.) 353–408 (1995).8.Haines, W. P. & Renwick, J. A. A. Bryophytes as food: Comparative consumption and utilization of mosses by a generalist insect herbivore. Entomol Exp Appl. 133, 296–306. https://doi.org/10.1111/j.1570-7458.2009.00929.x (2009).Article 

Google Scholar 
9.Kuřavová, K. et al. Is feeding on mosses by groundhoppers in the genus Tetrix (Insecta: Orthoptera) opportunistic or selective?. Arthropod-Plant Int. 11, 35–43. https://doi.org/10.1007/s11829-016-9461-9 (2017).Article 

Google Scholar 
10.Matuszkiewicz, W. Przewodnik do Oznaczania Zbiorowisk Roślinnych Polski (Wyd Nauk, PWN, 2001).
Google Scholar 
11.Krestov, P. V. Forest vegetation of easternmost Russia (Russian Far East). In Forest Vegetation of Northeast Asia (eds Kolbek, J. et al.) 93–180 (Springer, 2003).Chapter 

Google Scholar 
12.Kuznetsov, O. Topology-ecological classification of mire vegetation in the Republic of Karelia (Russia). In Biodiversity and Conservation of Boreal Nature. Proceedings of the 10 years anniversary symposium of the Nature Reserve Friendship (eds Heikkilä, R. & Lindholm, T.) 117–123 (Elsevier, 2003).
Google Scholar 
13.Černý, T. Phytosociological Study of Selected Critical Thermophilous Vegetation Complexes in the Czech Republic. A thesis submitted for the degree of Doctor of Philosophy in the Department of Botany Faculty of Sciences, Charles University (2007).14.Chytrý, M. et al. A modern analogue of the Pleistocene steppe-tundra ecosystem in southern Siberia. Boreas 48, 36–56 (2019).Article 

Google Scholar 
15.Wolski, G. J. & Kruk, A. Determination of plant communities based on bryophytes: The combined use of Kohonen artificial neural network and indicator species analysis. Ecol. Indic 113, 106160. https://doi.org/10.1016/j.ecolind.2020.106160 (2020).Article 

Google Scholar 
16.Benzing, D. Vulnerabilities of tropical forests to climate change: The significance of resident epiphytes. Clim. Change 39, 519–540 (1998).Article 

Google Scholar 
17.Gustafsson, L., Fiskesjö, A., Ingelög, T., Petterson, B. & Thor, G. Factors of importance to some lichen species of deciduous broad-leaved woods in southern Sweden. Lichenologist 24, 255–266 (1992).Article 

Google Scholar 
18.Frahm, J. P. Ecology of bryophytes along altitudinal and latitudinal gradients in Chile. Trop. Bryol. 21, 67–79 (2002).
Google Scholar 
19.Číhal, L., Kaláb, O. & Plášek, V. Modeling the distribution of rare and interesting moss species of the family Orthotrichaceae (Bryophyta) in Tajikistan and Kyrgyzstan. Acta Soc. Bot. Pol. 86(2), 3543. https://doi.org/10.5586/asbp.3543 (2017).Article 

Google Scholar 
20.Łubek, A., Kukwa, M., Czortek, P. & Jaroszewicz, B. Impact of Fraxinus excelsior dieback on biota of ash-associated lichen epiphytes at the landscape and community level. Biodivers. Conserv. 29, 431–450. https://doi.org/10.1007/s10531-019-01890-w (2020).Article 

Google Scholar 
21.Łubek, A., Kukwa, M., Jaroszewicz, B. & Czortek, P. Identifying mechanisms shaping lichen functional diversity in a primeval forest. For. Ecol. Manag. 475, 118434. https://doi.org/10.1016/j.foreco.2020.118434 (2020).Article 

Google Scholar 
22.Barkman, J. J. Phytosociology and Ecology of Cryptogamic Epiphytes. Including a Taxonomic Survey and Description of Their Vegetation Units in Europe, Van Gorcum, Comp (N. V Assen, 1958).
Google Scholar 
23.Green, T. G. A. & Lange, O. L. Photosynthesis in poikilohydric plants: A comparison of lichens and bryophytes. In Ecophysiology of Photosynthesis (eds Schulze, E.-D. & Caldwell, M. M.) 319–341 (Springer-Verlag, 1995).Chapter 

Google Scholar 
24.Scheidegger, C., Wolseley, P. A. & Landolt, R. Towards conservation of lichens. Forest. Snow Landsc. Res. 75, 285–433 (2000).
Google Scholar 
25.Tønsberg, T. & Høiland, K. A study of the macrolichen flora on the sand-dune areas on Lista, SW Norway. Nor. J. Bot. 27, 131–134 (1980).
Google Scholar 
26.Thiet, R. K., Doshas, A. & Smith, S. M. Effects of biocrusts and lichen-moss mats on plant productivity in a US sand dune ecosystem. Plant Soil 377(1), 235–244 (2014).CAS 
Article 

Google Scholar 
27.Vaz, A. S., Marques, J. & Honrado, J. P. Patterns of lichen diversity in coastal sand-dunes of northern Portugal. Bot. Complut. 38, 89–96 (2014).Article 

Google Scholar 
28.Antoninka, A., Bowker, M. A., Reed, S. C. & Doherty, K. Production of greenhouse-grown biocrust mosses and associated cyanobacteria to rehabilitate dryland soil function. Restor. Ecol. 24(3), 324–335 (2016).Article 

Google Scholar 
29.Jüriado, I., Kämärä, M.-L. & Oja, E. Environmental factors and ground disturbance affecting the composition of species and functional traits of ground layer lichens on grey dunes and dune heaths of Estonia. Nord. J. Bot. 34(2), 244–255 (2016).Article 

Google Scholar 
30.Balogh, R. et al. Mosses and lichens in dynamics of acidic sandy grasslands: Specific response to grazing exclosure. Acta Biol. Plant. Agriensis 5(1), 30 (2017).
Google Scholar 
31.Concostrina-Zubiri, L., Arenas, J. M., Martínez, I. & Escudero, A. Unassisted establishment of biological soil crusts on dryland road slopes. Web Ecol. 19(1), 39–51 (2019).Article 

Google Scholar 
32.Kubiak, D. & Oszyczka, P. Non-forested vs forest environments: The effect of habitat conditionson host tree parameters and the occurrence of associated epiphytic lichens. Fungal Ecol. 47, 100957 (2020).Article 

Google Scholar 
33.Gradstein, S. R. & Sporn, S. G. Land-use change and epiphytic bryophyte diversity in the Tropics. Nova Hedwigia 138, 311–323 (2010).
Google Scholar 
34.Guevara, S., Purata, S. E. & Van der Maarel, E. The role of remnant forest trees in tropical secondary succession. Vegetatio 66, 77–84 (1986).
Google Scholar 
35.Sillett, S. C., Gradstein, S. R. & Griffin, D. Bryophyte diversity of Ficus tree crowns from cloud forest and pasture in Costa Rica. Bryologist 98(2), 251–260 (1995).Article 

Google Scholar 
36.Werner, F., Homeier, J. & Gradstein, S. R. Diversity of vascular epiphytes on isolated remnant trees in the montane forest belt of southern Ecuador. Ecotropica 11, 21–40 (2005).
Google Scholar 
37.Lara, F., Garilleti, R. & Mazimpaka, V. Orthotrichum karoo (Orthotrichaceae), a new species with hyaline-awned leaves from southwestern Africa. Bryologist 112(1), 194–201 (2009).Article 

Google Scholar 
38.Lara, F. & Mazimpaka, V. Ma´s sobre la presencia de Orthotrichum acuminatum en la Península Ibérica. Cryptog. Bryol. Lichenol. 13(4), 349–354 (1992).
Google Scholar 
39.Garilleti, R., Lara, F. & Mazimpaka, V. Orthotrichum anodon (Orthotrichaceae, Bryopsida), a new species from California, and its relationships with other Orthotricha sharing puckered capsule mouths. Bryologist 109(2), 188–196 (2006).Article 

Google Scholar 
40.Hallingbäck, T. & Hodgetts, N. Mosses Liverworts and Hornworts. Status survey and conservation action plan for bryophytes (Cambridge University Press, 2000).
Google Scholar 
41.Belinchón, R., Martínez, I., Escudero, A., Aragón, G. & Valladares, F. Edge effects on epiphytic communities in a Mediterranean Quercus pyrenaica forest. J. Veg. Sci. 18, 81–90. https://doi.org/10.1111/j.1654-1103.2007.tb02518.x (2007).Article 

Google Scholar 
42.Boudreault, C., Gauthier, S. & Bergeron, Y. Epiphytic lichens and bryophytes on Populus Tremuloides along a chronosequence in the Southwestern Boreal Forest of Quebec, Canada. Bryologist 103, 725–738. https://doi.org/10.1639/0007-2745(2000)103[0725:ELABOP]2.0.CO;2 (2009).Article 

Google Scholar 
43.Rambo, T. Structure and composition of corticolous epiphyte communities in a Sierra Nevada old-growth mixed-conifer forest. Bryologist 113, 55–71. https://doi.org/10.1639/0007-2745-113.1.55 (2010).Article 

Google Scholar 
44.Plášek, V., Nowak, A., Nobis, M., Kusza, G. & Kochanowska, K. Effect of 30 years of road traffic abandonment on epiphytic moss diversity. Environ. Monit. Assess. 186, 8943–8959. https://doi.org/10.1007/s10661-014-4056-3 (2014).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
45.Skoupá, Z., Ochyra, R., Guo, S. L., Sulayman, M. & Plášek, V. Distributional novelties for Lewinskya, Nyholmiella and Orthotrichum (Orthotrichaceae) in China. Herzogia 30, 58–73. https://doi.org/10.13158/heia.30.1.2017.58 (2017).Article 

Google Scholar 
46.Skoupá, Z., Ochyra, R., Guo, S.-L., Sulayman, M. & Plášek, V. Three remarkable additions of Orthotrichum species (Orthotrichaceae) to the moss flora of China. Herzogia 31, 88–100. https://doi.org/10.13158/099.031.0105 (2018).Article 

Google Scholar 
47.Gradstein, R. et al. Bryophytes of Mount Patuha, West Java, Indonesia. Reinwardtia 13(2), 107–123 (2010).
Google Scholar 
48.Saat, A., Talib, M. S., Harun, N., Hamzah, Z. & Wood, A. K. Spatial variability of arsenic and heavy metals in a highland tea plantation using lichens and mosses as bio-monitors. Asian J. Nat. Appl. Sci. 5(1), 10–21 (2016).
Google Scholar 
49.Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37(12), 4302–4315 (2017).Article 

Google Scholar 
50.Wirth, V. Ökologische Zeigerwerte von Flechten. Herzogia 23(2), 229–248 (2010).Article 

Google Scholar 
51.Ellenberger, H. et al. Zeigerwerte von Planzen in Mitteleuropa. Scr. Geobot. 18, 1–248 (1991).
Google Scholar 
52.Smith, C. W. et al. The Lichens of Great Britain and Ireland 1046 (British Lichen Society, 2009).
Google Scholar 
53.Hodgetts, N. et al. An annotated checklist of bryophytes of Europe, Macaronesia and Cyprus. J. Bryol. 42(1), 1–116. https://doi.org/10.1080/03736687.2019.1694329 (2020).Article 

Google Scholar 
54.Pancho, J. V. Some bryophytes in tea plantations, Pagilaran Central Java. Biotrop. Bull. 11, 279–282 (1979).
Google Scholar 
55.Tan, B. C. et al. Mosses of Gunung Halimun National Park, West Java, Indonesia. Reinwardtia 12, 205–214 (2006).
Google Scholar 
56.Ohsawa, M. Weeds of tea plantations. In Biology and Ecology of Weeds. Geobotany Vol. 2 (eds Holzner, W. & Numata, M.) (Springer, 1982).
Google Scholar 
57.Gradstein, R. et al. Bryophytes of Mount Patuha, West Java, Indonesia. Reinwardtia 13, 107–123 (2010).
Google Scholar 
58.Whitelaw, M. & Burton, M. A. S. Diversity and distribution of epiphytic bryophytes on Bramley’s Seedling trees in East of England apple orchards. Glob. Ecol. Conserv. 4, 380–387. https://doi.org/10.1016/j.gecco.2015.07.014 (2015).Article 

Google Scholar 
59.Söderström, L. Bryophytes and decaying wood – a comparison between manager and natural forest. Holarc. Ecol. 14, 121–130 (1991).
Google Scholar 
60.Cieśliński, S. et al. Relikty lasu puszczańskiego, In Białowieski Park Narodowy (1921–1996) w badaniach geobotanicznych. Phytocoenosis, 8 (N.S.), Seminarium Geobotanicum (ed. Faliński, J. B.) 4, 47–64 (1996).61.Vanderpoorten, A., Engels, P. & Sotiaux, A. Trends in diversity and abundance of obligate epiphytic bryophytes in a highly managed landscape. Ecography 27, 567–576 (2004).Article 

Google Scholar 
62.Ódor, P., van Dort, K., Aude, E., Heilmann-Clausen, J. & Christensen, M. Diversity and composition of dead wood inhabiting bryophyte communities in European beech forest. Biol. Soc. Esp. Briol. 26–27, 85–102 (2005).
Google Scholar 
63.Friedel, A., Oheimb, G. V., Dengler, J. & Härdtle, W. Species diversity and species composition of epiphytic bryophytes and lichens: A comparison of managed and unmanaged beech forests in NE Germany. Feddes Repert. 117(1–2), 172–185 (2006).Article 

Google Scholar 
64.Wolski, G. J. Siedliskowe Uwarunkowania Występowania Mszaków w Rezerwatach Przyrody Chroniących Jodłę Pospolitą w Polsce Środkowej (Praca doktorska wykonana w Katedrze Geobotaniki i Ekologii Roślin UŁ, 2013).
Google Scholar 
65.Fudali, E. & Wolski, G. J. Ecological diversity of bryophytes on tree trunks in protected forests (a case study from Central Poland). Herzogia 28(1), 91–107 (2015).Article 

Google Scholar 
66.Shi, X.-M. et al. Epiphytic bryophytes as bio-indicators of atmospheric nitrogen deposition in a subtropical montane cloud forest: Response patterns, mechanism, and critical load. Environ. Pollut. 229, 932–941. https://doi.org/10.1016/j.envpol.2017.07.077 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
67.Cornelissen, J. H. C. & Gradstein, S. R. On the occurrence of bryophytes and macrolichens in different lowland rain forest types of Mabura Hill, Guyana. Trop. Bryol. 3, 29–35. https://doi.org/10.11646/bde.3.1.4 (1990).Article 

Google Scholar 
68.Lyons, B., Nadkarni, N. M. & North, M. P. Spatial distribution and succession of epiphytes on Tsuga heterophylla (western hemlock) in an old-growth Douglas-fir forest. Can. J. Bot. 78(7), 957–968. https://doi.org/10.1139/cjb-78-7-957 (2000).Article 

Google Scholar 
69.Cornelissen, J. H. C. & Steege, H. T. Distribution and ecology of epiphytic bryophytes and lichens in dry evergreen forest of Guyana. J. Trop. Ecol. 5, 131–150. https://doi.org/10.1017/S0266467400003400 (1989).Article 

Google Scholar 
70.Woods, C. L., Cardelús, C. L., Dewalt, S. J. & Piper, F. Microhabitat associations of vascular epiphytes in a wet tropical forest canopy. J. Ecol. 103(2), 421–430. https://doi.org/10.1111/1365-2745.12357 (2015).Article 

Google Scholar 
71.Sporn, S. G., Bos, M. M., Kessler, M. & Gradstein, S. R. Vertical distribution of epiphytic bryophytes in an Indonesian rainforest. Biodivers. Conserv. 19(3), 745–760. https://doi.org/10.1007/s10531-009-9731-2 (2010).Article 

Google Scholar 
72.Czerepko, J. et al. How sensitive are epiphytic and epixylic cryptogams as indicators of forest naturalness? Testing bryophyte and lichen predictive power in stands under different management regimes in the Białowieża forest. Ecol. Indic. 125, 107532. https://doi.org/10.1016/j.ecolind.2021.107532 (2021).Article 

Google Scholar 
73.Putna, S. & Mězaka, A. Preferences of epiphytic bryophytes for forest stand and substrate in North-East Latvia. Folia Cryptog. Estonica 51, 75–83 (2014).Article 

Google Scholar 
74.Manakyan, V. A. Results of bryological studies in Armenia. Arctoa 5, 15–33 (1995).Article 

Google Scholar 
75.Redfearn, P. L., Tan, B. C. & He, S. A newly updated and annotated checklist of Chines mosses. J. Hattori Bot. Lab. 79, 163–357 (1996).
Google Scholar 
76.Kürschner, H. Bryophyte Flora of the Arabian Peninsula and Socotra. Bryophytorum Bibliotheca (JCramer in der Gebrüder Borntraeger Verlagsbuchhandlung, 2000).
Google Scholar 
77.Higuchi, M. & Nishimura, N. Mosses of Pakistan. J. Hattori Bot. Lab. 93, 273–291 (2003).
Google Scholar 
78.Ignatov, M. S., Afonina, O. M. & Ignatova, E. A. Check-list of mosses of East Europe and North Asia. Arctoa 15, 1–130. https://doi.org/10.15298/arctoa.15.01 (2006).Article 

Google Scholar 
79.Sabovljević, M. et al. Check-list of the mosses of SE Europe. Phytol. Balcan. 14(2), 207–244 (2008).
Google Scholar 
80.Dandotiya, D., Govindapyari, H., Suman, S. & Uniyal, P. L. Checklist of the bryophytes of India. Arch. Bryol. 88, 71–72 (2011).
Google Scholar 
81.Hodgetts, N. G. Checklist and Country Status of European bryophytes—Towards a New Red List for Europe. Irish Wildlife Manuals, No. 84. (National Parks and Wildlife Service, Department of Arts, Heritage and the Gaeltacht, 2011). https://www.hdl.handle.net/2262/73373.82.Kürschner, H. & Frey, W. Liverworts, Mosses and Hornworts of Southwest Asia (Marchantiophyta, Bryophyta, Anthoceroptophyta). Nova Hedwigia 139, 179–180 (2011).
Google Scholar 
83.Suzuki, T. A revised new catalog of the mosses of Japan. Hattoria 7, 9–223. https://doi.org/10.18968/hattoria.7.0_9 (2016).Article 

Google Scholar 
84.Kürschner, H. & Frey, W. Liverworts, mosses and hornworts of Afghanistan—our present knowledge. Acta Mus. Siles. Sci. Natur. 68, 11–24 (2019).
Google Scholar 
85.Brotherus, V. F. Enumeratio muscorum Caucasi. Acta Soc. Sci. Fenn. 19, 1–170 (1892).
Google Scholar 
86.Chikovani, N. & Svanidze, T. Checklist of bryophyte species of Georgia. Braun-Blanquetia 34, 97–116. https://doi.org/10.13158/heia.26.1.2013.213 (2004).Article 

Google Scholar 
87.Doroshina, G. Y. New moss records from Georgia. 1. Arctoa 19, 281 (2010).
Google Scholar 
88.Sohrabi, M., Ahti, T. & Urbanavichus, G. Parmelioid lichens of Iran and the caucasus Region. Mycol. Balc. 4, 21–30 (2007).
Google Scholar 
89.Hawksworth, D. L., Blanco, O., Divakar, P. K., Ahti, T. & Crespo, A. A first checklist of parmelioid and similar lichens in Europe and some adjacent territories, adopting revised generic circumscriptions and with indications of species distributions. Lichenologist 40(1), 1–21. https://doi.org/10.1017/S0024282908007329 (2008).Article 

Google Scholar 
90.Syrek, M. & Kukwa, M. Taxonomy of the lichen Cladonia rei and its status in Poland. Biologia 63(4), 493–497. https://doi.org/10.2478/s11756-008-0092-1 (2008).Article 

Google Scholar 
91.Burgaz, A. R., Ahti, T., Inashvili, T., Batsatsashvili, K. & Kupradze, I. Study of georgian Cladoniaceae. Bot. Complut. 42, 19–55. https://doi.org/10.5209/BOCM.61367 (2018).Article 

Google Scholar 
92.Fałtynowicz, W. The lichens, lichenicolous and allied fungi of Poland. An annotated checklist. In Biodiversity of Poland (ed. Mirek, A.) 1–435 (W. Szafer Institute of Botany, Polish Academy of Sciences, 2003).
Google Scholar 
93.Plášek, V., Sawicki, J., Ochyra, R., Szczecińska, M. & Kulik, T. New taxonomical arrangement of the traditionally conceived genera Orthotrichum and Ulota (Orthotrichaceae, Bryophyta). Acta Mus. Sil. 64, 169–174. https://doi.org/10.1515/cszma-2015-0024 (2015).Article 

Google Scholar 
94.Lara, F. et al. Lewinskya, a new genus to accommodate the phaneroporous and monoicous taxa of Orthotrichum (Bryophyta, Orthotrichaceae). Cryptog. Bryol. 37, 361–382. https://doi.org/10.7872/cryb/v37.iss4.2016.361 (2016).Article 

Google Scholar 
95.Sawicki, J. et al. Mitogenomic analyses support the recent division of the genus Orthotrichum (Orthotrichaceae, Bryophyta). Sci. Rep. 7, 4408. https://doi.org/10.1038/s41598-017-04833-z (2017).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
96.Kürschner, H., Batsatsashvili, K. & Parolly, G. Noteworthy additions to the bryophyte flora of Georgia. Herzogia 26, 213–216. https://doi.org/10.13158/heia.26.1.2013.213 (2013).Article 

Google Scholar 
97.Ellis, L. T. et al. New national and regional bryophyte records, 49. J. Bryol. 38(4), 327–347 (2016).Article 

Google Scholar 
98.Ellis, L. T. et al. New national and regional bryophyte records, 51. J. Bryol. 39(2), 177–190 (2017).Article 

Google Scholar 
99.Eckstein, J., Garilleti, R. & Lara, F. Lewinskya transcaucasica (Orthotrichaceae, Bryopsida) sp. nov. A contribution to the bryophyte flora of Georgia. J. Bryol. 40(1), 31–38. https://doi.org/10.1080/03736687.2017.1365218 (2018).Article 

Google Scholar 
100.Eckstein, J. & Zündorf, H.-J. Orthotrichaceous mosses (Orthotricheae, Orthotrichaceae) of the Genera Lewinskya, Nyholmiella, Orthotrichum, Pulvigera and Ulota Contributions to the bryophyte flora of Georgia 1. Cryptog. Bryol. 38(4), 365–382. https://doi.org/10.7872/cryb/v38.iss4.2017.365 (2017).Article 

Google Scholar 
101.Schäfer-Verwimp, A. Orthotrichum Hedw. In Die Moose Baden-Württembergs. Band 2: Spezieller Teil (Bryophytina II, Schistostegales bis Hypnobryales) (eds Nebel, M. & Philippi, G.) 170–197 (Eugen Ulmer, 2001).
Google Scholar 
102.Lara, F. & Garilleti, R. Orthotrichum Hedw. In Flora briofítica Ibérica (eds Guerra, J. & Brugués, C. M.) 50–135 (Universidad de Murcia Sociedad Española de Briología, 2014).
Google Scholar 
103.Lewinsky, J. The genus Orthotrichum Hedw. (Orthotrichaceae, Musci) in Southeast Asia. A taxonomic revision. J. Hattori Bot. Lab. 72, 1–88 (1992).
Google Scholar 
104.Schäfer-Verwimp, A. & Gruber, J. P. Orthotrichum (Orthotrichaceae, Bryopsida) in Pakistan. Trop. Bryol. 21, 1–9. https://doi.org/10.11646/bde.21.1.2 (2002).Article 

Google Scholar 
105.Draper, I., Mazimpaka, V., Albertos, B., Garilleti, R. & Lara, F. A survey of the epiphytic bryophyte flora of the Rif and Tazzeka Mountains (northern Morocco). J. Bryol. 27, 23–34. https://doi.org/10.1179/174328205X40554 (2005).Article 

Google Scholar 
106.Brassard, G. R. Orthotrichum stramineum new to North America. Bryologist 87, 168 (1984).Article 

Google Scholar 
107.Lewinsky-Haapasaari, J. & Long, D. G. Orthotrichum stramineum Hornsch. new to China. J. Bryol. 19, 350–352. https://doi.org/10.1179/jbr.1996.19.2.350 (1996).Article 

Google Scholar 
108.Plášek, V. et al. A synopsis of Orthotrichum s. lato (Bryophyta, Orthotrichaceae) in China, with distribution maps and a key to determination. Plants 10, 499. https://doi.org/10.3390/plants10030499 (2021).Article 
PubMed 
PubMed Central 

Google Scholar  More

1.Stein, A., Gerstner, K. & Kreft, H. Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales. Ecol. Lett. 17, 866–880 (2014).PubMed 
Article 

Google Scholar 
2.Tews, J. et al. Animal species diversity driven by habitat heterogeneity/diversity: The importance of keystone structures—Animal species diversity driven by habitat heterogeneity. J. Biogeogr. 31, 79–92 (2004).Article 

Google Scholar 
3.Graham, N. A. J. & Nash, K. L. The importance of structural complexity in coral reef ecosystems. Coral Reefs 32, 315–326 (2013).ADS 
Article 

Google Scholar 
4.Reimchen, T. E. Substratum heterogeneity, crypsis, and colour polymorphism in an intertidal snail (Littorina mariae). Can. J. Zool. 57, 1070–1085 (1979).Article 

Google Scholar 
5.Petren, K. & Case, T. J. Habitat structure determines competition intensity and invasion success in gecko lizards. Proc. Natl. Acad. Sci. 95, 11739–11744 (1998).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
6.Gratwicke, B. & Speight, M. R. The relationship between fish species richness, abundance and habitat complexity in a range of shallow tropical marine habitats. J. Fish Biol. 66, 650–667 (2005).Article 

Google Scholar 
7.Williams, S. E., Marsh, H. & Winter, J. Spatial scale, species diversity, and habitat structure: Small mammals in Australian tropical rain forest. Ecology 83, 1317–1329 (2002).Article 

Google Scholar 
8.Renoult, J. P., Kelber, A. & Schaefer, H. M. Colour spaces in ecology and evolutionary biology. Biol. Rev. 92, 292–315 (2017).PubMed 
Article 

Google Scholar 
9.Cuthill, I. C. et al. The biology of color. Science 357, eaan0221 (2017).PubMed 
Article 
CAS 

Google Scholar 
10.Guilford, T. & Dawkins, M. S. Receiver psychology and the evolution of animal signals. Anim. Behav. 42, 1–14 (1991).Article 

Google Scholar 
11.Crook, A. C. Colour patterns in a coral reef fish is background complexity important?. J. Exp. Mar. Biol. Ecol. 217, 237–252 (1997).Article 

Google Scholar 
12.Marshall, J. Communication and camouflage with the same ‘bright’ colours in reef fishes. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 355, 1243–1248 (2000).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
13.Seehausen, O. et al. Speciation through sensory drive in cichlid fish. Nature 455, 620–626 (2008).ADS 
CAS 
PubMed 
Article 

Google Scholar 
14.Wilkins, L., Marshall, N. J., Johnsen, S. & Osorio, D. Modelling colour constancy in fish: Implications for vision and signalling in water. J. Exp. Biol. 219, 1884–1892 (2016).PubMed 

Google Scholar 
15.Osorio, D. & Vorobyev, M. A review of the evolution of animal colour vision and visual communication signals. Vis. Res. 48, 2042–2051 (2008).CAS 
PubMed 
Article 

Google Scholar 
16.Caley, J. & St John, J. Refuge availability structures assemblages of tropical reef fishes. J. Anim. Ecol. 45, 414–428 (1996).Article 

Google Scholar 
17.Connolly, S. R., Hughes, T. P., Bellwood, D. R. & Karlson, R. H. Community structure of corals and reef fishes at multiple scales. Science 309, 1363–1365 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
18.Allen, G. R. & Steene, R. Indo-Pacific Coral Reef Field Guide (Tropical Reef Research, 1994).
Google Scholar 
19.Bellwood, D. R. Regional-scale assembly rules and biodiversity of coral reefs. Science 292, 1532–1535 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
20.Humann, P., DeLoach, N., Allen, G. & Steene, G. Reef Fish Identification: Tropical Pacific (New World Publications, 2015).
Google Scholar 
21.Barneche, D. R. et al. Body size, reef area and temperature predict global reef-fish species richness across spatial scales. Glob. Ecol. Biogeogr. 28, 315–327 (2019).Article 

Google Scholar 
22.Brandl, S. J., Goatley, C. H. R., Bellwood, D. R. & Tornabene, L. The hidden half: ecology and evolution of cryptobenthic fishes on coral reefs: Cryptobenthic reef fishes. Biol. Rev. 93, 1846–1873 (2018).PubMed 
Article 

Google Scholar 
23.Carr, M. H., Anderson, T. W. & Hixon, M. A. Biodiversity, population regulation, and the stability of coral-reef fish communities. Proc. Natl. Acad. Sci. 99, 11241–11245 (2002).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
24.Hixon, M. A. 60 years of coral reef fish ecology: Past, present, future. Bull. Mar. Sci. 87, 727–765 (2011).Article 

Google Scholar 
25.Stuart-Smith, R. D. et al. Integrating abundance and functional traits reveals new global hotspots of fish diversity. Nature 501, 539–542 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
26.Froese, R. & Pauly, D. FishBase. World Wide Web electronic publication. http://www.fishbase.org (2019).27.Marshall, N. J., Jennings, K., McFarland, W. N., Loew, E. R. & Losey, G. S. Visual biology of Hawaiian coral reef fishes. II. Colors of Hawaiian coral reef fish. Copeia 2003, 455–466 (2003).Article 

Google Scholar 
28.Merilaita, S. Visual background complexity facilitates the evolution of camouflage. Evolution 57, 1248–1254 (2003).PubMed 
Article 

Google Scholar 
29.Matz, M. V., Lukyanov, K. A. & Lukyanov, S. A. Family of the green fluorescent protein: Journey to the end of the rainbow. BioEssays 24, 953–959 (2002).CAS 
PubMed 
Article 

Google Scholar 
30.Alieva, N. O. et al. Diversity and evolution of coral fluorescent proteins. PLoS ONE 3, e2680 (2008).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
31.Salih, A., Larkum, A., Cox, G., Kühl, M. & Hoegh-Guldberg, O. Fluorescent pigments in corals are photoprotective. Nature 408, 850–853 (2000).ADS 
CAS 
PubMed 
Article 

Google Scholar 
32.Veron, J., Stafford-Smith, M., DeVantier, L. & Turak, E. Overview of distribution patterns of zooxanthellate Scleractinia. Front. Mar. Sci. 1, 81 (2015).Article 

Google Scholar 
33.Matz, M. V., Marshall, N. J. & Vorobyev, M. Are corals colorful?. Photochem. Photobiol. 82, 345 (2006).CAS 
PubMed 
Article 

Google Scholar 
34.Marshall, N. J., Jennings, K., McFarland, W. N., Loew, E. R. & Losey, G. S. Visual biology of Hawaiian coral reef fishes. III. Environmental light and an integrated approach to the ecology of reef fish vision. Copeia 2003, 467–480 (2003).Article 

Google Scholar 
35.Neumeyer, C. Color vision in fishes and its neural basis. In Sensory Processing in Aquatic Environments (eds Collin, S. P. & Marshall, N. J.) 223–235 (Springer, 2003). https://doi.org/10.1007/978-0-387-22628-6_11.Chapter 

Google Scholar 
36.Oswald, F. et al. Contributions of host and symbiont pigments to the coloration of reef corals. FEBS J. 274, 1102–1122 (2007).CAS 
PubMed 
Article 

Google Scholar 
37.Schweikert, L. E., Fitak, R. R., Caves, E. M., Sutton, T. T. & Johnsen, S. Spectral sensitivity in ray-finned fishes: Diversity, ecology, and shared descent. J. Exp. Biol. https://doi.org/10.1242/jeb.189761 (2018).Article 
PubMed 

Google Scholar 
38.Veron, J. E. N., Stafford-Smith., M. G., Turak, E. & DeVantier, L. M. Corals of the World. www.coralsoftheworld.org (2020). Accessed April 2019.39.Weller, H. I. & Westneat, M. W. Quantitative color profiling of digital images with earth mover’s distance using the R package colordistance. PeerJ 7, e6398 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
40.Cox, K., Woods, M. & Reimchen, T. E. Coral species richness, coral hue, and reef fish richness across 74 ecoregions within four oceanic basins. Figshare https://doi.org/10.6084/m9.figshare.12317591 (2020).41.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).
Google Scholar 
42.The Ocean Agency & XL Catlin Seaview Survey. Coral Reef Image Bank. www.coralreefimagebank.org (2019). Accessed April 2019.43.Choat, J. H. & Bellwood, D. R. Reef fishes: Their history and evolution. In The Ecology of Fishes on Coral Reefs (ed. Sale, P. F.) 39–66 (Academic Press, 1991).Chapter 

Google Scholar 
44.Jones, G. P., Barone, G., Sambrook, K. & Bonin, M. C. Isolation promotes abundance and species richness of fishes recruiting to coral reef patches. Mar. Biol. 167, 1–13 (2020).Article 
CAS 

Google Scholar 
45.Lirman, D. et al. Severe 2010 cold-water event caused unprecedented mortality to corals of the florida reef tract and reversed previous survivorship patterns. PLoS ONE 6, e23047 (2011).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
46.Habary, A., Johansen, J. L., Nay, T. J., Steffensen, J. F. & Rummer, J. L. Adapt, move or die: How will tropical coral reef fishes cope with ocean warming?. Glob. Change Biol. 23, 566–577 (2017).ADS 
Article 

Google Scholar 
47.Almany, G. R. & Webster, M. S. The predation gauntlet: Early post-settlement mortality in reef fishes. Coral Reefs 25, 19–22 (2006).ADS 
Article 

Google Scholar 
48.Brandl, S. J. et al. Demographic dynamics of the smallest marine vertebrates fuel coral reef ecosystem functioning. Science 364, 1189–1192 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
49.Coker, D. J., Wilson, S. K. & Pratchett, M. S. Importance of live coral habitat for reef fishes. Rev. Fish Biol. Fish. 24, 89–126 (2014).Article 

Google Scholar 
50.Coker, D. J., Pratchett, M. S. & Munday, P. L. Coral bleaching and habitat degradation increase susceptibility to predation for coral-dwelling fishes. Behav. Ecol. 20, 1204–1210 (2009).Article 

Google Scholar 
51.Sale, P. F. Maintenance of high diversity in coral reef fish communities. Am. Nat. 111, 337–359 (1977).Article 

Google Scholar 
52.Munday, P. L. Competitive coexistence of coral-dwelling fishes: The lottery hypothesis revisited. Ecology 85, 623–628 (2004).Article 

Google Scholar 
53.Hixon, M. A. Synergistic predation, density dependence, and population regulation in marine fish. Science 277, 946–949 (1997).CAS 
Article 

Google Scholar 
54.Endler, J. A. & Thery, M. Interacting effects of Lek placement, display behavior, ambient light, and color patterns in three neotropical forest-dwelling birds. Am. Nat. 148, 421–452 (1996).Article 

Google Scholar 
55.Reimchen, T. E. Shell colour ontogeny and tubeworm mimicry in a marine gastropod Littorina mariae. Biol. J. Linn. Soc. 36, 97–109 (1989).Article 

Google Scholar 
56.Sparks, J. S. et al. The covert world of fish biofluorescence: A phylogenetically widespread and phenotypically variable phenomenon. PLoS ONE 9, e83259 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
57.Allen, J. J., Akkaynak, D., Sugden, A. U. & Hanlon, R. T. Adaptive body patterning, three-dimensional skin morphology and camouflage measures of the slender filefish Monacanthus tuckeri on a Caribbean coral reef. Biol. J. Linn. Soc. 116, 377–396 (2015).Article 

Google Scholar 
58.Cheney, K. L., Skogh, C., Hart, N. S. & Marshall, N. J. Mimicry, colour forms and spectral sensitivity of the bluestriped fangblenny, Plagiotremus rhinorhynchos. Proc. R. Soc. B Biol. Sci. 276, 1565–1573 (2009).Article 

Google Scholar 
59.Stevens, M., Lown, A. E. & Denton, A. M. Rockpool gobies change colour for camouflage. PLoS ONE 9, e110325 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
60.Gilby, B. L. et al. Colour change in a filefish (Monacanthus chinensis) faced with the challenge of changing backgrounds. Environ. Biol. Fishes 98, 2021–2029 (2015).Article 

Google Scholar 
61.Barnett, J. B. & Cuthill, I. C. Distance-dependent defensive coloration. Curr. Biol. 24, R1157–R1158 (2014).CAS 
PubMed 
Article 

Google Scholar 
62.Vega Thurber, R. L. et al. Chronic nutrient enrichment increases prevalence and severity of coral disease and bleaching. Glob. Change Biol. 20, 544–554 (2014).ADS 
Article 

Google Scholar 
63.Hughes, T. P. et al. Global warming and recurrent mass bleaching of corals. Nature 543, 373–377 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
64.Ortiz, J.-C. et al. Impaired recovery of the great barrier reef under cumulative stress. Sci. Adv. 4, eaar6127 (2018).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
65.Grottoli, A. G., Rodrigues, L. J. & Palardy, J. E. Heterotrophic plasticity and resilience in bleached corals. Nature 440, 1186–1189 (2006).ADS 
CAS 
PubMed 
Article 

Google Scholar 
66.Roff, G. et al. Porites and the Phoenix effect: Unprecedented recovery after a mass coral bleaching event at Rangiroa Atoll, French Polynesia. Mar. Biol. 161, 1385–1393 (2014).Article 

Google Scholar 
67.Adjeroud, M. et al. Recovery of coral assemblages despite acute and recurrent disturbances on a South Central Pacific reef. Sci. Rep. 8, 1–8 (2018).ADS 
CAS 
Article 

Google Scholar 
68.Tittensor, D. P. et al. Global patterns and predictors of marine biodiversity across taxa. Nature 466, 1098–1101 (2010).ADS 
CAS 
PubMed 
Article 

Google Scholar 
69.Soetaert, K. plot3D: Plotting Multi-Dimensional Data R package version 1.4. https://CRAN.R-project.org/package=plot3D (2021).70.Sarkar, D. Lattice: Multivariate Data Visualization with R (Springer, 2008).MATH 
Book 

Google Scholar 
71.Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).MATH 
Book 

Google Scholar 
72.Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
73.Centore, P. sRGB centroids for the ISCC-NBS colour system. Munsell Colour Sci. Paint. 21, 1–21 (2016).
Google Scholar 
74.Kelly, K. L. Central notations for the revised ISCC-NBS color-name blocks. J. Res. Natl. Bur. Stand. 61, 427 (1958).Article 

Google Scholar 
75.Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Softw. 36, 1–48 (2010).Article 

Google Scholar  More

1.McNaughton, S. J., Ruess, R. W. & Seagle, S. W. Large mammals and process dynamics in Aftican ecosystems. Bioscience 38, 794–800 (1988).Article 

Google Scholar 
2.Vanni, M. J. Nutrient cycling by animals in freshwater ecosystems. Annu. Rev. Ecol. Syst. 33, 341–370 (2002).Article 

Google Scholar 
3.Schmitz, O. J. et al. Animating the carbon cycle. Ecosystems 17, 344–359 (2014).CAS 
Article 

Google Scholar 
4.Doughty, C. E. et al. Global nutrient transport in a world of giants. Proc. Natl Acad. Sci. USA 113, 868–873 (2016).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
5.Allgeier, J. E., Burkepile, D. E. & Layman, C. A. Animal pee in the sea: consumer-mediated nutrient dynamics in the world’s changing oceans. Glob. Change Biol. 23, 2166–2178 (2017).ADS 
Article 

Google Scholar 
6.Duffy, J. E. Biodiversity and ecosystem function: the consumer connection. Oikos 99, 201–219 (2002).Article 

Google Scholar 
7.Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).ADS 
CAS 
Article 

Google Scholar 
8.Loreau, M. et al. Biodiversity and ecosystem functioning: current knowledge and future challenges. Science 294, 804–808 (2001).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005).Article 

Google Scholar 
10.McIntyre, P. B., Jones, L. E., Flecker, A. S. & Vanni, M. J. Fish extinctions alter nutrient recycling in tropical freshwaters. Proc. Natl Acad. Sci. USA 104, 4461–4466 (2007).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
11.Pigot, A. L. et al. Macroevolutionary convergence connects morphological form to ecological function in birds. Nat. Ecol. Evolution 4, 230–239 (2020).Article 

Google Scholar 
12.Harvey, P. H. & Pagel, M. D. The Comparative Method in Evolutionary Biology. (Oxford University Press, 1991).13.Wiens, J. J. et al. Niche conservatism as an emerging principle in ecology and conservation biology. Ecol. Lett. 13, 1310–1324 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Weeks, B., Claramunt, S. & Cracraft, J. Integrating systematics and biogeography to disentangle the roles of history and ecology in biotic assembly. J. Biogeogr. 43 (2016).15.Reiners, W. A. Complementary models for ecosystems. Am. Nat. 127, 59–73 (1986).Article 

Google Scholar 
16.Schreck, C. B. & Moyle, P. B. Methods for Fish Biology. (American Fisheries Society, 1990).17.Sterner, R. W. & Elser, J. J. Ecological Stoichiometry: The Biology of Elements from Molecules to the Biosphere. 429 (2002).18.Vaitla, B. et al. Predicting nutrient content of ray-finned fishes using phylogenetic information. Nat. Commun. 9, 3742 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
19.Gonzalez, A. L. et al. Ecological mechanisms and phylogeny shape invertebrate stoichiometry: a test using detritus-based communities across Central and South America. Funct. Ecol. 32, 2448–2463 (2018).Article 

Google Scholar 
20.Atkinson, C. L., van Ee, B. C. & Pfeiffer, J. M. Evolutionary history drives aspects of stoichiometric niche variation and functional effects within a guild. Ecology 101, e03100 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
21.Schluter, D. The Ecology of Adaptive Radiation. (OUP Oxford, 2000).22.Allgeier, J. E., Wenger, S. & Layman, C. A. Taxonomic identity best explains variation in body nutrient stoichiometry in a diverse marine animal community. Sci. Rep. 10, 13718 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
23.Allgeier, J. E., Wenger, S. J., Schindler, D. E., Rosemond, A. D. & Layman, C. A. Metabolic theory and taxonomic identity predict nutrient cycling in a diverse food web. Proc. Natl Acad. Sci. USA 112, 2640–2647 (2015).Article 
CAS 

Google Scholar 
24.Odum, H. T. & Odum, E. P. Trohic structure and productivity of a windward coral reef community on Eniwetok Atoll. Ecol. Monogr. 25, 291–320 (1955).Article 

Google Scholar 
25.Hatcher, B. G. Coral reef primary productivity—a beggars banquet. Trends Ecol. Evolut. 3, 106–111 (1988).CAS 
Article 

Google Scholar 
26.Deangelis, D. L. Energy-flow, nutrient cycling, and ecosystem resilience. Ecology 61, 764–771 (1980).Article 

Google Scholar 
27.Allgeier, J. E., Valdivia, A., Cox, C. & Layman, C. A. Fishing down nutrients on coral reefs. Nat. Commun. 7, 1–5 (2016).Article 
CAS 

Google Scholar 
28.Allgeier, J. E., Layman, C. A., Mumby, P. J. & Rosemond, A. D. Consistent nutrient storage and supply mediated by diverse fish communities in coral reef ecosystems. Glob. Change Biol. 20, 2459–2472 (2014).ADS 
Article 

Google Scholar 
29.Allgeier, J. E., Layman, C. A., Mumby, P. J. & Rosemond, A. D. Biogeochemical implications of biodiversity loss across regional gradients of coastal marine ecosystems. Ecol. Monogr. 85, 132 (2015).Article 

Google Scholar 
30.Bellwood, D. R. & Wainwright, P. C. CHAPTER 1—The History and Biogeography of Fishes on Coral Reefs. in Coral Reef Fishes (ed Sale, P. F.) 5–32 (Academic Press, 2002). https://doi.org/10.1016/B978-012615185-5/50003-7.31.Littler, M. M., Littler, D. S. & Titlyanov, E. A. Comparisons of N- and P-limited productivity between high granitic islands versus low carbonate atolls in the Seychelles Archipelago: a test of the relative-dominance paradigm. Coral Reefs 10, 199–209 (1991).ADS 
Article 

Google Scholar 
32.Haßler, K. et al. Provenance of nutrients in submarine fresh groundwater discharge on Tahiti and Moorea, French Polynesia. Appl. Geochem. 100, 181–189 (2019).Article 
CAS 

Google Scholar 
33.Carew, J. L. & Mylroie, J. E. Geology of the Bahamas. Geol. Hydrogeol. Carbonate Isl. 54, 91–139 (1997).CAS 
Article 

Google Scholar 
34.Allgeier, J. E., Rosemond, A. D., Mehring, A. S. & Layman, C. A. Synergistic nutrient co-limitation across a gradient of ecosystem fragmentation in subtropical mangrove-dominated wetlands. Limnol. Oceanogr. 55, 2660–2668 (2010).ADS 
CAS 
Article 

Google Scholar 
35.Koch, M. S. & Madden, C. J. Patterns of primary production and nutrient availability in a Bahamas lagoon with fringing mangroves. Mar. Ecol. Prog. Ser. 219, 109–119 (2001).ADS 
CAS 
Article 

Google Scholar 
36.Hendrixson, H. A., Sterner, R. W. & Kay, A. D. Elemental stoichiometry of freshwater fishes in relation to phylogeny, allometry and ecology. J. Fish. Biol. 70, 121–140 (2007).Article 

Google Scholar 
37.Vanni, M. J., Flecker, A. S., Hood, J. M. & Headworth, J. L. Stoichiometry of nutrient recycling by vertebrates in a tropical stream: linking species identity and ecosystem processes. Ecol. Lett. 5, 285–293 (2002).Article 

Google Scholar 
38.Vanni, M. J. & McIntyre, P. B. Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis. Ecology 97, 3460–3471 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
39.Sokal, R. R. The comparative method in evolutionary biology. (eds Paul H. Harvey, Mark D. Pagel) (Oxford University Press, New York, 1991). viii + 239 pp. ISBN 0-19-854640-8. $24.95 (paper). Am. J. Phys. Anthropol. 88, 405–406 (1992).40.Downs, K. N., Hayes, N. M., Rock, A. M., Vanni, M. J. & González, M. J. Light and nutrient supply mediate intraspecific variation in the nutrient stoichiometry of juvenile fish. Ecosphere 7, e01452 (2016).Article 

Google Scholar 
41.Sterner, R. W. & George, N. B. Carbon, nitrogen, and phosphorus stoichiometry of cyprinid fishes. Ecology 81, 127–140 (2000).Article 

Google Scholar 
42.Brown, W. L. Jr & Wilson, E. O. Character displacement. Syst. Biol. 5, 49–64 (1956).
Google Scholar 
43.Losos, J. B. Ecological character displacement and the study of adaptation. Proc. Natl Acad. Sci. USA 97, 5693–5695 (2000).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
44.Dayan, T. & Simberloff, D. Ecological and community-wide character displacement: the next generation. Ecol. Lett. 8, 875–894 (2005).Article 

Google Scholar 
45.Abrams, P. A. Evolution and the consequences of species introductions and deletions. Ecology 77, 1321–1328 (1996).Article 

Google Scholar 
46.Buchan, K. C. The Bahamas. Mar. Pollut. Bull. 41, 94–111 (2000).CAS 
Article 

Google Scholar 
47.Siu, G. et al. Shore fishes of french polynesia. Cybium 41 (2017).48.Miloslavich, P. et al. Marine biodiversity in the Caribbean: regional estimates and distribution patterns. PloS ONE 5, 119–126 (2010).Article 
CAS 

Google Scholar 
49.Schaus, M. H. & Vanni, M. J. Effects of gizzard shad on phytoplankton and nutrient dynamics: role of sediment feeding and fish size. Ecology 81, 1701–1719 (2000).Article 

Google Scholar 
50.Whiles, M. R., Huryn, A. D., Taylor, B. W. & Reeve, J. D. Influence of handling stress and fasting on estimates of ammonium excretion by tadpoles and fish: recommendations for designing excretion experiments. Limnol. Oceanogr. 7, 1–7 (2009).CAS 
Article 

Google Scholar 
51.Taylor, B. W. et al. Improving the fluorometric ammonium method: matrix effects, background fluorescence, and standard additions. J. North Am. Benthol. Soc. 26, 167–177 (2007).Article 

Google Scholar 
52.APHA. Standard Methods for the Examination of Water and Wastewater. American Public Health Association, American Water Works Association, and Water Pollution Control Federation. (1995).53.Mouillot, D. et al. Functional over-redundancy and high functional vulnerability in global fish faunas on tropical reefs. Proc. Natl Acad. Sci. USA 111, 13757–13762 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
54.Rabosky, D. L. et al. An inverse latitudinal gradient in speciation rate for marine fishes. Nature 559, 392–395 (2018).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
55.Chang, J., Rabosky, D. L., Smith, S. A. & Alfaro, M. E. An r package and online resource for macroevolutionary studies using the ray-finned fish tree of life. Methods Ecol. Evolut. 10, 1118–1124 (2019).Article 

Google Scholar 
56.Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evolut. 3, 217–223 (2012).Article 

Google Scholar 
57.Hadfield, J. D. & Nakagawa, S. General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters. J. Evolut. Biol. 23, 494–508 (2010).CAS 
Article 

Google Scholar 
58.Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R Package. J. Stat. Softw. 33, 1–22 (2010).Article 

Google Scholar 
59.Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R 2 from generalized linear mixed-effects models. Methods Ecol. Evolut. 4, 133–142 (2013).Article 

Google Scholar 
60.Gelman, A. & Hill, J. Data Analysis Using Regression. (Cambridge University Press, 2007).61.Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
62.Jackson, A. L., Inger, R., Parnell, A. C. & Bearhop, S. Comparing isotopic niche widths among and within communities: SIBER—Stable Isotope Bayesian Ellipses in R. J. Anim. Ecol. 80, 595–602 (2011).PubMed 
Article 
PubMed Central 

Google Scholar  More

The research was carried out on the basis of direct measurements in the surroundings of four selected working coal-fired power plants and four working coking plants. The samples of suspended dust PM10, respirable fraction PM2.5 and submicron particulate matter PM1 were collected in the surroundings of power generation facilities and in the surroundings of coking plants.Location of measurement pointsThe location of the measurement points was selected in southern Poland, around the selected four working coal-fired power plants and four working coking plants. The sampling points in the surroundings of the power plant (P1, P2, P3 and P4) and the coking plant (K1, K2, K3 and K4) were located at the distance of approximately 2 km to the north-east from the respective object (Fig. 1).Figure 1Location of the sampling sites (the map was generated based on data from the BDL18 website).Full size imageThe location of the measurement points was a compromise, taking into account the representativeness of the receptor, the possibility to connect the testing equipment and the consent of the property owners. To eliminate the impact of a heating season, and especially that of low emissions, presented in the studies by19, the measurement sessions were carried out only in the summer season. The samples of particulate matter were collected on a weekly basis, with 4 sessions at one site. The methodology applied in this work is presented in20,21. The location of measurement sites:

point P1: 50° 08′ 37.87″ N; 18° 32′ 15.76″ (Golejów—a suburban district of Rybnik in the Śląskie Voivodeship, in the vicinity of a working power plant with a capacity of 1775 MW; population:

2 300);

point P2: 50° 45′ 35.41″ N; 17° 56′ 20.43″ E (Świerkle—a rural area in the Opolskie Voivodeship (Dobrzeń Wielki commune) near a working power plant with a capacity of 1,492 MW; population: 520);

point P3: 50° 12′ 33.46″ N; 19° 28′ 28.77″ E (Czyżówka—rural area in the Małopolskie Voivodeship (commune of Trzebinia) near a working power plant with a capacity of 786 MW; population: 700);

point P4: 50° 13′ 48.90″ N; 19° 13′ 24.45″ E (suburbs of Jaworzno (Śląskie Voivodeship) in the vicinity of a 1,345 MW power plant; number of inhabitants: 95 500);

K1 point: 50° 10′ 11.36″ N; 18° 40′ 34.35″ E (Czerwionka—Leszczyny in the Śląskie Voivodeship, in the vicinity of a small coking plant; number of inhabitants: 27 300);

K2 point: 50° 3′ 19.76″ N; 18° 30′ 21.69″ E (Popielów—a suburban district of Rybnik in the Śląskie Voivodeship, surrounded by a small working coking plant; population:3 300);

K3 point: 50° 21′ 24.08″ N; 19° 21′ 37.46″ E (Łęka—Dąbrowa Górnicza district, in the Śląskie Voivodeship, surrounded by a large coking plant; number of inhabitants: 700);

K4 point: 50° 21′ 0.47″ N; 18° 53′ 15.44″ E (Bytom—a city in the Śląskie Voivodeship, a small coking plant located on the outskirts of the city; population: 174 700).

The state of air pollution with particulate matter in the area investigated in the study is affected by various local sources of pollution emissions. At the measurement sites P1, P2, P3 and P4, the emissions are mainly from power plant chimneys, but also from auxiliary processes, i.e. coal storage and its transport. In addition, the recorded emissions are also influenced by other industrial plants operating in the vicinity of the measurement sites, domestic and municipal sector and the impact of automotive industry. The measurement sites K1, K2, K3 and K4 involve primarily the emissions accompanying the processes of coal coking as well as auxiliary processes, i.e. coal deposition, its transmission, management of products and post-production wastes. Additionally, they are affected by the emissions from industrial plants and low emission sources operating in this area, as well as the emission from the combustion of solid fuels for domestic or municipal purposes, as well as by the automotive industry.Sampling processThe samples of suspended dust (PM10), respirable fraction (PM2.5) and submicron particulate matter (PM1) were collected using the Dekati PM10 cascade impactor serial No. 6648 by Dekati (Finland) with the air flow rate of (1.8 {mathrm{m}}^{3}/mathrm{h}). The impactor Dekati PM10 guarantees the collection of dust samples for three cutpoint diameters: 10 μm, 2.5 μm and 1 μm. For the sampling at the first, second and third stages of the impactor, polycarbonate filters were used (Nuclepore 800 203, with the diameter of 25 mm, by Whatman International Ltd., Maidstone, UK). At the fourth stage, the dust was collected on a Teflon filter for particles ≤ 1 μm in diameter (Pall Teflo R2PJ047, 47 mm in diameter, by Pall International Ltd., New York, NY, USA). The average volume of air passing through the filters was approximately 300 m3. The impactor’s capture efficiency was characterized by the uncertainty below 2.8%. The mass of dust collected at the individual stages of the impactor was determined by the gravimetric method, and it was referenced to the volume of passed air (left(mathrm{mu g}/{mathrm{m}}^{3}right)) according to the PN-EN1234122. All impactor samples were analysed by inductively coupled plasma mass spectrometry (ICP-MS).The samples were collected at a height of 1.5 m from the ground, i.e. in the breathing zone for people. The respective dust fractions were collected in 7-day cycles from 28 May to 24 September 2014 (16 weeks) in the surroundings of four working coal-fired power plants and from 4 May to 28 August 2015 (16 weeks) in the surroundings of four working coking plants. The measurement campaign comprised four measurement sessions separately for each sampling site. One session comprised dust sampling at each stage of the Dekati PM10 cascade impactor and filters used for reference. The filters were taken back after study period and labeled during the collection process in the field and stored in the plastic containers for safe transportation and storage in laboratory for further analysis.In each measurement session, blind filters were stored at the sampling site, but they were not subjected to exposure. The sample data were corrected from these blanks. The length of the measurement cycles was conditioned by the need to collect an appropriate amount of research material (with the aerodynamic diameter of the dust grains  10 μm). Analogous (7-day) periods of dust sampling were used in the studies by4,23.Polycarbonate and Teflon filters were conditioned before and after dust collection at a temperature of 20 ± 1 °C (relative humidity 50%(pm ) 5%) for 48 h, and then weighed on a microbalance with an accuracy of 1 (mathrm{mu g}) (MXA5/1, by RADWAG, Poland).Taking into account the measurement sessions at four sites in the surroundings of the power plant (P1 (div) P4) and at four sites in the surroundings of the coking plant (K1 (div) K4), the aggregate number of samples exceeded 450.Chemical analysisThe qualitative and quantitative analysis of the obtained solutions was performed by inductively coupled plasma mass spectrometry using an ICP-MS instrument (NexION 300D, PerkinElmer, Inc., Waltham, MA, USA). For all elements determined simultaneously, the same parameters of the instrument were used, which are presented in the publications20,21,24.As standards for the determination of 75As, 111Cd, 59Co, 53Cr, 200Hg, 55Mn, 60Ni, 206Pb, 121Sb and 82Se, we applied the 1000 (mathrm{mu g}/{mathrm{cm}}^{3}) CertPUR ICP multi-element standard solution VI for ICP-MS by Merck, Germany. Ten repetitions were performed for all samples. The determined limits of detection (LOD) were based on 10 independent measurements for blank test. For the results obtained in that way, the mean value and the value of the standard deviation SD were calculated. The values of LOD for individual elements were determined on the basis of the dependence (1):$$mathrm{LOD}= {mathrm{x}}_{mathrm{sr}}+ 3mathrm{SD}$$
(1)

where: xśr—mean concentration value of the element, (mathrm{g}/{mathrm{dm}}^{3}), SD—standard deviation.The determination correctness of the content of the elements was verified with the use of certified reference materials: European Reference Material ERM-CZ120 and Standard Reference Material SRM 1648a (National Institute of Standards and Technology, USA). The recovery with the use of the said certified reference materials was respectively as follows: As (111% for ERM-CZ120 and 96% for SRM 1648a), Cd (97% and 105%), Co (108% and 97%), Cr (103% and 94%), Mn (106% and 100%), Ni (107% and 102%), Pb (107% and 105%) and Sb (99% and 91%). The certified reference materials did not contain Hg or Se. More

1.Suttle, C. A. Marine viruses — major players in the global ecosystem. Nat. Rev. Microbiol. 5, 801–812 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
2.Rohwer, F. & Thurber, R. V. Viruses manipulate the marine environment. Nature 459, 207–212 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
3.Simmonds, P. et al. Virus taxonomy in the age of metagenomics. Nat. Rev. Microbiol. 15, 161–168 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
4.Fuhrman, J. A. Marine viruses and their biogeochemical and ecological effects. Nature 399, 541–548 (1999).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
5.Suttle, C. A. Viruses in the sea. Nature 437, 356–361 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
6.Jiang, S., Steward, G., Jellison, R., Chu, W. & Choi, S. Abundance, distribution, and diversity of viruses in alkaline, hypersaline Mono Lake, California. Microb. Ecol. 47, 9–17 (2004).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
7.Williamson, K. E., Fuhrmann, J. J., Wommack, K. E. & Radosevich, M. Viruses in soil ecosystems: an unknown quantity within an unexplored territory. Annu. Rev. Virol. 4, 201–219 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
8.Cai, L. et al. Active and diverse viruses persist in the deep sub-seafloor sediments over thousands of years. ISME J. 13, 1857–1864 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
9.Wei, M. & Xu, K. New insights into the virus-to-prokaryote ratio (VPR) in marine sediments. Front. Microbiol. 11, 1102 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
10.Wilhelm, S. W. & Suttle, C. A. Viruses and nutrient cycles in the sea. BioScience 49, 781–788 (1999).Article 

Google Scholar 
11.Brussaard, C. P. D. et al. Global-scale processes with a nanoscale drive: the role of marine viruses. ISME J. 2, 575–578 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
12.Howard-Varona, C. et al. Phage-specific metabolic reprogramming of virocells. ISME J. 14, 881–895 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
13.Nee, S. & Maynard Smith, J. The evolutionary biology of molecular parasites. Parasitology 100, S5–S18 (1990).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Hambly, E. & Suttle, C. A. The viriosphere, diversity, and genetic exchange within phage communities. Curr. Opin. Microbiol. 8, 444–450 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
15.Sullivan, M. B. et al. Prevalence and evolution of core photosystem II genes in marine cyanobacterial viruses and their hosts. PLoS Biol. 4, e234 (2006).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
16.Holmes, E. C. What does virus evolution tell us about virus origins? J. Virol. 85, 5247–5251 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
17.Wolf, Y. I. et al. Origins and evolution of the global RNA virome. mBio 9, e02329-18 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
18.Kuhn, J. H. et al. Classify viruses-the gain is worth the pain. Nature 566, 318–320 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
19.Record, N. R., Talmy, D. & Våge, S. Quantifying tradeoffs for marine viruses. Front. Mar. Sci. https://doi.org/10.3389/fmars.2016.00251 (2016). Investigates trade-offs in phenotypes of marine viruses that may influence virus population dynamics and biogeography.Article 

Google Scholar 
20.Domingo, E. et al. Basic concepts in RNA virus evolution. FASEB J. 10, 859–864 (1996).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
21.Solé, R. V., Ferrer, R., González-García, I., Quer, J. & Domingo, E. Red queen dynamics, competition and critical points in a model of RNA virus quasispecies. J. Theor. Biol. 198, 47–59 (1999).PubMed 
Article 
PubMed Central 

Google Scholar 
22.Stern, A. & Sorek, R. The phage-host arms race: shaping the evolution of microbes. Bioessays 33, 43–51 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
23.Daugherty, M. D. & Malik, H. S. Rules of engagement: molecular insights from host-virus arms races. Annu. Rev. Genet. 46, 677–700 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
24.Tegally, H. et al. Sixteen novel lineages of SARS-CoV-2 in South Africa. Nat. Med. 27, 440–446 (2021).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
25.Lederberg, J. in Emerging Viruses (ed. Morse, S. S.) 3–9 (Oxford University Press, 1993).26.Baltimore, D. Expression of animal virus genomes. Microbiol. Mol. Biol. Rev. 35, 235–241 (1971).CAS 

Google Scholar 
27.Coutinho, F. H., Edwards, R. A. & Rodríguez-Valera, F. Charting the diversity of uncultured viruses of archaea and bacteria. BMC Biol. 17, 109 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
28.King, A. M. Q., Adams, M. J., Carstens, E. B. & Lefkowitz, E. J. (eds) Virus Taxonomy. 163–173 (Elsevier, 2012).29.Forterre, P. The virocell concept and environmental microbiology. ISME J. 7, 233–236 (2013). Among the first reports articulating the viewpoint that infected cells undergoing active virus replication should be recognized as the ‘living form’ of a virus known as a virocell.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
30.Lowen, A. C. Constraints, drivers, and implications of influenza A virus reassortment. Annu. Rev. Virol. 4, 105–121 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
31.Mahner, M. & Kary, M. What exactly are genomes, genotypes and phenotypes? And what about phenomes? J. Theor. Biol. 186, 55–63 (1997).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
32.Edwards, K. F. & Steward, G. F. Host traits drive viral life histories across phytoplankton viruses. Am. Nat. 191, 566–581 (2018). Examines the inter-relationships between virus traits and their consequences for population dynamics and the evolution of burst size.PubMed 
Article 
PubMed Central 

Google Scholar 
33.Flint, S. J., Racaniello, V. R., Rall, G. F., Skalka, A. M. & Enquist, L. W. Principles of Virology 4th Edn (Wiley, 2015).34.Ghabrial, S. A., Castón, J. R., Jiang, D., Nibert, M. L. & Suzuki, N. 50-plus years of fungal viruses. Virology 479–480, 356–368 (2015).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
35.Dunigan, D. D. et al. Chloroviruses lure hosts through long-distance chemical signaling. J. Virol. 93, e01688-18 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
36.Anantharaman, K. et al. Sulfur oxidation genes in diverse deep-sea viruses. Science 344, 757–760 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
37.Mann, N. H., Cook, A., Millard, A., Bailey, S. & Clokie, M. Bacterial photosynthesis genes in a virus. Nature 424, 741 (2003). Shows how the virus genome interacts with the host to facilitate virus reproduction.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
38.Mavrich, T. N. & Hatfull, G. F. Evolution of superinfection immunity in cluster A mycobacteriophages. mBio 10, e00971-19 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
39.Marine, R. L., Nasko, D. J., Wray, J., Polson, S. W. & Wommack, K. E. Novel chaperonins are prevalent in the virioplankton and demonstrate links to viral biology and ecology. ISME J. 11, 2479–2491 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
40.ICTV. Virus Taxonomy: The ICTV Report on Virus Classification and Taxon Nomenclature. https://talk.ictvonline.org/ictv-reports/ictv_9th_report/ (2019).41.Ojosnegros, S. et al. Viral genome segmentation can result from a trade-off between genetic content and particle stability. PLoS Genet 7, e1001344 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
42.Belshaw, R., Pybus, O. G. & Rambaut, A. The evolution of genome compression and genomic novelty in RNA viruses. Genome Res. 17, 1496–1504 (2007).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
43.Van Etten, J. L., Agarkova, I. V. & Dunigan, D. D. Chloroviruses. Viruses 12, 20 (2020).Article 
CAS 

Google Scholar 
44.Iranzo, J. & Manrubia, S. C. Evolutionary dynamics of genome segmentation in multipartite viruses. Proc. Biol. Sci. 279, 3812–3819 (2012).PubMed 
PubMed Central 

Google Scholar 
45.Kellogg, C. A. & Paul, J. H. Degree of ultraviolet radiation damage and repair capabilities are related to G+C content in marine vibriophages. Aquat. Microb. Ecol. 27, 13–20 (2002).Article 

Google Scholar 
46.Violle, C. et al. Let the concept of trait be functional! Oikos 116, 882–892 (2007).Article 

Google Scholar 
47.Edwards, K. F., Steward, G. F. & Schvarcz, C. R. Making sense of virus size and the tradeoffs shaping viral fitness. Ecol. Lett. 24, 363–373 (2021).PubMed 
Article 
PubMed Central 

Google Scholar 
48.Bonachela, J. A. & Levin, S. A. Evolutionary comparison between viral lysis rate and latent period. J. Theor. Biol. 345, 32–42 (2014).PubMed 
Article 
PubMed Central 

Google Scholar 
49.Yashchenko, V. V., Gavrilova, O. V., Rautian, M. S. & Jakobsen, K. S. Association of Paramecium bursaria Chlorella viruses with Paramecium bursaria cells: ultrastructural studies. Eur. J. Protistol. 48, 149–159 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
50.DeLong, J. P., Al-Ameeli, Z., Duncan, G., Van Etten, J. L. & Dunigan, D. D. Predators catalyze an increase in chloroviruses by foraging on the symbiotic hosts of zoochlorellae. Proc. Natl Acad. Sci. USA 113, 13780–13784 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
51.Wang, I.-N. Lysis timing and bacteriophage fitness. Genetics 172, 17–26 (2006).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
52.Smith, C. & Fretwell, S. The optimal balance between size and number of offspring. Am. Nat. 108, 499–506 (1974).Article 

Google Scholar 
53.You, L., Suthers, P. F. & Yin, J. Effects of Escherichia coli physiology on growth of phage T7 In vivo and in silico. J. Bacteriol. 184, 1888–1894 (2002).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
54.Swan, B. K. et al. Prevalent genome streamlining and latitudinal divergence of planktonic bacteria in the surface ocean. Proc. Natl Acad. Sci. USA 110, 11463–11468 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
55.Hellweger, F. L. Carrying photosynthesis genes increases ecological fitness of cyanophage in silico. Environ. Microbiol. 11, 1386–1394 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
56.Schenk, H. & Sieber, M. Bacteriophage can promote the emergence of physiologically sub-optimal host phenotypes. bioRxiv https://doi.org/10.1101/621524 (2019).Article 

Google Scholar 
57.Howard-Varona, C. et al. Multiple mechanisms drive phage infection efficiency in nearly identical hosts. ISME J. 12, 1605–1618 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
58.Zimmerman, A. E. et al. Metabolic and biogeochemical consequences of viral infection in aquatic ecosystems. Nat. Rev. Microbiol. 18, 21–34 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
59.Grove, J. & Marsh, M. The cell biology of receptor-mediated virus entry. J. Cell Biol. 195, 1071–1082 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
60.McFadden, G., Mohamed, M. R., Rahman, M. M. & Bartee, E. Cytokine determinants of viral tropism. Nat. Rev. Immunol. 9, 645–655 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
61.Bernheim, A. & Sorek, R. The pan-immune system of bacteria: antiviral defence as a community resource. Nat. Rev. Microbiol. 18, 113–119 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
62.Nussenzweig, P. M. & Marraffini, L. A. Molecular mechanisms of CRISPR-Cas immunity in bacteria. Annu. Rev. Genet. 54, 93–120 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
63.Hampton, H. G., Watson, B. N. J. & Fineran, P. C. The arms race between bacteria and their phage foes. Nature 577, 327–336 (2020). An overview of the mechanisms and phenotypes related to phage infection and host defence mechanisms.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
64.Samson, J. E., Magadán, A. H., Sabri, M. & Moineau, S. Revenge of the phages: defeating bacterial defences. Nat. Rev. Microbiol. 11, 675–687 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
65.Flores, C. O., Meyer, J. R., Valverde, S., Farr, L. & Weitz, J. S. Statistical structure of host–phage interactions. Proc. Natl Acad. Sci. USA 108, E288–E297 (2011). Demonstrates the role of virus host range in generating community-wide patterns of host–phage interactions.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
66.Regoes, R. R. & Bonhoeffer, S. The HIV coreceptor switch: a population dynamical perspective. Trends Microbiol. 13, 269–277 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
67.Atkinson, D., Ciotti, B. J. & Montagnes, D. J. Protists decrease in size linearly with temperature: ca. 2.5% C-1. Proc. R. Soc. Lond. B 270, 2605–2611 (2003).Article 

Google Scholar 
68.Falkowski, P. G. in Primary Productivity in the Sea (ed. Falkowski, P. G.) 99–119 (Springer, 1980).69.Salsbery, M. E. & DeLong, J. P. The benefit of algae endosymbionts in Paramecium bursariais temperature dependent. Evol. Ecol. Res. 19, 669–678 (2018).
Google Scholar 
70.Kimmance, S. A., Atkinson, D. & Montagnes, D. J. S. Do temperature–food interactions matter? Responses of production and its components in the model heterotrophic flagellate Oxyrrhis marina. Aquat. Microb. Ecol. 42, 63–73 (2006).Article 

Google Scholar 
71.Maat, D. S., van Bleijswijk, J. D. L., Witte, H. J. & Brussaard, C. P. D. Virus production in phosphorus-limited Micromonas pusilla stimulated by a supply of naturally low concentrations of different phosphorus sources, far into the lytic cycle. FEMS Microbiol. Ecol. 92, fiw136 (2016).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
72.Amla, D. V., Rowell, P. & Stewart, W. D. P. Metabolic changes associated with cyanophage N-1 infection of the cyanobacterium Nostoc muscorum. Arch. Microbiol. 148, 321–327 (1987).CAS 
Article 

Google Scholar 
73.Hadas, H., Einav, M., Fishov, I. & Zaritsky, A. Bacteriophage T4 development depends on the physiology of its host Escherichia coli. Microbiology 143, 179–185 (1997).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
74.Demory, D. et al. Temperature is a key factor in Micromonas–virus interactions. ISME J. 11, 601–612 (2017). Shows the effect of temperature on the kinetics, phenotypes and life history strategies of prasinoviruses.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
75.Schachtele, C. F., Oman, R. W. & Anderson, D. L. Effect of elevated temperature on deoxyribonucleic acid synthesis in bacteriophage φ29-infected Bacillus amyloliquefaciens. J. Virol. 6, 430–437 (1970).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
76.Choua, M., Heath, M. R., Speirs, D. C. & Bonachela, J. A. The effect of viral plasticity on the persistence of host-virus systems. J. Theor. Biol. 498, 110263 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
77.Ni, T. & Zeng, Q. Diel infection of cyanobacteria by cyanophages. Front. Mar. Sci. https://doi.org/10.3389/fmars.2015.00123 (2016).Article 

Google Scholar 
78.Sakowski, E. G. et al. Ribonucleotide reductases reveal novel viral diversity and predict biological and ecological features of unknown marine viruses. Proc. Natl Acad. Sci. USA 111, 15786–15791 (2014). Demonstrates that genomic features in the viral replicon (that is, module of genes responsible for viral genome replication) may predict the biogeographical distribution of viruses.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
79.Reeson, A. F. et al. Effects of phenotypic plasticity on pathogen transmission in the field in a Lepidoptera-NPV system. Oecologia 124, 373–380 (2000).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
80.Stearns, S. C. The evolutionary significance of phenotypic plasticity. BioScience 39, 436–445 (1989).Article 

Google Scholar 
81.Leggett, H. C., Benmayor, R., Hodgson, D. J. & Buckling, A. Experimental evolution of adaptive phenotypic plasticity in a parasite. Curr. Biol. 23, 139–142 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
82.Oppenheim, A. B., Kobiler, O., Stavans, J., Court, D. L. & Adhya, S. Switches in bacteriophage lambda development. Annu. Rev. Genet. 39, 409–429 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
83.Erez, Z. et al. Communication between viruses guides lysis–lysogeny decisions. Nature 541, 488–493 (2017). Demonstrates the use of communication peptides that determine lysogeny in temperate phages.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
84.Weitz, J. S., Li, G., Gulbudak, H., Cortez, M. H. & Whitaker, R. J. Viral invasion fitness across a continuum from lysis to latency. Virus Evol. 5, vez006 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
85.Labonté, J. M. et al. Single cell genomics indicates horizontal gene transfer and viral infections in a deep subsurface Firmicutes population. Front. Microbiol. 6, 349 (2015).PubMed 
PubMed Central 

Google Scholar 
86.Koskella, B. & Brockhurst, M. A. Bacteria–phage coevolution as a driver of ecological and evolutionary processes in microbial communities. FEMS Microbiol. Rev. 38, 916–931 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
87.Meyer, J. R. et al. Repeatability and contingency in the evolution of a key innovation in phage lambda. Science 335, 428–432 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
88.Marston, M. F. et al. Rapid diversification of coevolving marine Synechococcus and a virus. Proc. Natl Acad. Sci. USA 109, 4544–4549 (2012). Demonstrates the rapid co-evolution of virus and host but highlights the challenge of identifying the critical phenotypes mediating the interaction.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
89.Frickel, J., Feulner, P. G. D., Karakoc, E. & Becks, L. Population size changes and selection drive patterns of parallel evolution in a host–virus system. Nat. Commun. 9, 1706 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
90.Knowles, B. et al. Temperate infection in a virus–host system previously known for virulent dynamics. Nat. Commun. 11, 4626 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
91.Wang, I.-N., Dykhuizen, D. E. & Slobodkin, L. B. The evolution of phage lysis timing. Evol. Ecol. 10, 545–558 (1996).Article 

Google Scholar 
92.Abedon, S. T., Hyman, P. & Thomas, C. Experimental examination of bacteriophage latent-period evolution as a response to bacterial availability. Appl. Environ. Microbiol. 69, 7499–7506 (2003).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
93.Palkovacs, E. P. & Hendry, A. P. Eco-evolutionary dynamics: intertwining ecological and evolutionary processes in contemporary time. F1000 Biol. Rep. 2, 1 (2010).PubMed 
PubMed Central 
Article 

Google Scholar 
94.Brown, C. M., Lawrence, J. E. & Campbell, D. A. Are phytoplankton population density maxima predictable through analysis of host and viral genomic DNA content? J. Mar. Biol. Assoc. UK 86, 491–498 (2006).CAS 
Article 

Google Scholar 
95.Wommack, K. E. & Colwell, R. R. Virioplankton: viruses in aquatic ecosystems. Microbiol. Mol. Biol. Rev. 64, 69–114 (2000).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
96.Weitz, J. S. et al. A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes. ISME J. 9, 1352–1364 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
97.Poorvin, L., Rinta-Kanto, J. M., Hutchins, D. A. & Wilhelm, S. W. Viral release of iron and its bioavailability to marine plankton. Limnol. Oceanogr. 49, 1734–1741 (2004).CAS 
Article 

Google Scholar 
98.Shelford, E. J., Middelboe, M., Møller, E. F. & Suttle, C. A. Virus-driven nitrogen cycling enhances phytoplankton growth. Aquat. Microb. Ecol. 66, 41–46 (2012).Article 

Google Scholar 
99.Ankrah, N. Y. D. et al. Phage infection of an environmentally relevant marine bacterium alters host metabolism and lysate composition. ISME J. 8, 1089–1100 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
100.Jover, L. F., Effler, T. C., Buchan, A., Wilhelm, S. W. & Weitz, J. S. The elemental composition of virus particles: implications for marine biogeochemical cycles. Nat. Rev. Microbiol. 12, 519–528 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
101.Dawkins, R. The Extended Phenotype: The Long Reach of the Gene (Oxford University Press, 1999).102.Dawkins, R. Extended phenotype–but not too extended. A reply to Laland, Turner and Jablonka. Biol. Philosophy 19, 377–396 (2004).Article 

Google Scholar 
103.Ogata, H. Habitat alterations by viruses: strategies by Tupanviruses and others. Microbes Environ. 33, 117–119 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
104.Abrahão, J. et al. Tailed giant Tupanvirus possesses the most complete translational apparatus of the known virosphere. Nat. Commun. 9, 749 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
105.Clark, H. F. & Wiktor, T. J. Plasticity of phenotypic characters of rabies-related viroses: spontaneous variation in the plaque morphology, virulence, and temperature-sensitivity characters of serially propagated Lagos bat and Mokola viruses. J. Infect. Dis. 130, 608–618 (1974).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
106.Abedon, S. T. & Culler, R. R. Optimizing bacteriophage plaque fecundity. J. Theor. Biol. 249, 582–592 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
107.Luo, E., Eppley, J. M., Romano, A. E., Mende, D. R. & DeLong, E. F. Double-stranded DNA virioplankton dynamics and reproductive strategies in the oligotrophic open ocean water column. ISME J. 14, 1304–1315 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
108.Bidle, K. D. Elucidating marine virus ecology through a unified heartbeat. Proc. Natl Acad. Sci. USA 111, 15606–15607 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
109.Schmidt, H. F., Sakowski, E. G., Williamson, S. J., Polson, S. W. & Wommack, K. E. Shotgun metagenomics indicates novel family A DNA polymerases predominate within marine virioplankton. ISME J. 8, 103–114 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
110.Nasko, D. J. et al. Family A DNA polymerase phylogeny uncovers diversity and replication gene organization in the virioplankton. Front. Microbiol. 9, 3053 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
111.Harrison, A. O., Moore, R. M., Polson, S. W. & Wommack, K. E. Reannotation of the ribonucleotide reductase in a cyanophage reveals life history strategies within the virioplankton. Front. Microbiol. 10, 134 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
112.Breitbart, M. Marine viruses: truth or dare. Annu. Rev. Mar. Sci. 4, 425–448 (2012).Article 

Google Scholar 
113.Hurwitz, B. L. & U’Ren, J. M. Viral metabolic reprogramming in marine ecosystems. Curr. Opin. Microbiol. 31, 161–168 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
114.Lindell, D., Jaffe, J. D., Johnson, Z. I., Church, G. M. & Chisholm, S. W. Photosynthesis genes in marine viruses yield proteins during host infection. Nature 438, 86–89 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
115.Rusconi, R., Garren, M. & Stocker, R. Microfluidics expanding the frontiers of microbial ecology. Annu. Rev. Biophys. 43, 65–91 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
116.Walker, G. M., Ozers, M. S. & Beebe, D. J. Cell infection within a microfluidic device using virus gradients. Sens. Actuators B Chem. 98, 347–355 (2004).CAS 
Article 

Google Scholar 
117.Cimetta, E. et al. Microfluidic-driven viral infection on cell cultures: theoretical and experimental study. Biomicrofluidics 6, 024127 (2012).PubMed Central 
Article 
CAS 

Google Scholar 
118.Xu, N. et al. A microfluidic platform for real-time and in situ monitoring of virus infection process. Biomicrofluidics 6, 034122 (2012).PubMed Central 
Article 
CAS 

Google Scholar 
119.Akin, D., Li, H. & Bashir, R. Real-time virus trapping and fluorescent imaging in microfluidic devices. Nano Lett. 4, 257–259 (2004).CAS 
Article 

Google Scholar 
120.Yu, J. Q. et al. Droplet optofluidic imaging for λ-bacteriophage detection via co-culture with host cell Escherichia coli. Lab. Chip 14, 3519–3524 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
121.Mashaghi, S. & van Oijen, A. M. Droplet microfluidics for kinetic studies of viral fusion. Biomicrofluidics 10, 024102 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
122.Fischer, A. E. et al. A high-throughput drop microfluidic system for virus culture and analysis. J. Virol. Methods 213, 111–117 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar  More

AnimalsThe experimental yaks were divided into four groups: 1-day old, 30-days-old, 180-days-old and adult. Three yaks were selected for each group, regardless of sex, and purchased from a local herdsmen in Haiyan County of Qinghai Province. All of the yaks showed a good nutritional status, and appeared healthy with no apparent diseases or conditions. The yaks were sacrificed by exsanguination in a slaughterhouse. The lungs were obtained immediately after the yak had died, and tissue samples were immediately collected from the diaphragmatic lobe of right lungs (to ensure that obvious blood vessels and the trachea were not gathered). The tissue samples were divided into three parts. One part was cut into 1 cm3 sections and fixed with 4% paraformaldehyde (PFA). The other two parts were cut into 1 mm3 pieces; one part was fixed with 2.5% glutaraldehyde, and the other was put into a freezing tube and placed into liquid nitrogen.Ethics statementThis study was approved by the Institutional Animal Care and Use Committee of Qinghai University (Xining, China). All methods were carried out in accordance with the ARRIVE guidelines and the Animal Ethics Procedures and Guidelines of the People’s Republic of China. No local regulations or laws were overlooked. All yaks used in this study were purchased from local farmers.Haematoxylin and eosin stainingLung tissue samples (1 cm3) were fixed in 4% PFA, dehydrated in 30%, 50%, 75%, 95% and 100% ethanol and then treated with xylene before embedding in paraffin. Paraffin-embedded lung tissues were cut into 4 µm sections. The sections were deparaffinized in xylene, and sections were stained either with haematoxylin and eosin (HE) (Y&K Bio, Xi’an, China) or Masson’s trichrome stain, to examine general morphology.ImmunohistochemistryThe unstained, deparaffinized sections were rinsed with Phosphate Buffered Saline with Twen-20 (PBST) 3 times for 5 min each time. Then, endogenous peroxidase was quenched using 3% peroxide-methanol at room temperature in the dark for 25 min, and then the samples were placed on a decolorizing shaking table 3 times, for 5 min each. The slides were then incubated with 3% foetal bovine serum (Sangon Biotech, Shanghai, China) at room temperature for 25 min. The serum was discarded, and rabbit anti-cattle CD34 and rabbit anti-CD34 polyclonal antibodies (Proteintech group, Wuhan, China) diluted in phosphate buffer saline (PBS) were added. CD34 is a transmembrane glycoprotein known as an angiogenesis marker. The sections were incubated in the primary antibodies overnight at 4 °C. Then, the sections were rinsed in Phosphate Buffered Saline with Twen-20 (PBST) (3 × 5 min), goat anti-rabbit IgG was added, and the sections were incubated for 30 min at 37 °C. 3,3-Diaminobenzidin (DAB) was added to the sections to visualise antibody binding, and the sections were washed 3 times in PBST. Haematoxylin was used to counterstain the nucleus prior to the samples being dehydrated and mounted.An Olympus BX51 microscope was used to take photomicrographs of the microstructures, images depict 1000× magnification. Transmission electron microscopy.The TEM lung tissue samples were processed using previously published methods16. Fresh lung samples (1 mm3) were fixed with glutaraldehyde (2.5%, 24 h) and postfixed with osmium tetroxide (1%, 2 h). The samples were dehydrated in a series of increasing concentrations of ethanol and embedded in Epon812. After preparing semithin sections, ultrathin sections were double stained with uranyl acetate and lead citrate. A 10,000× magnification was used to observe and photograph the sections with a JEM 1230 electron microscope (JEOL, Tokyo, Japan) set at 120 kV.Quantitative real-time PCR (qPCR)The gene expression levels in lung tissues from the yaks in the four age groups were analysed using qPCR. Total RNA was isolated with TRIzol® reagent (Invitrogen, CA, USA). cDNA was obtained by reverse transcription of total RNA using the SYBR PrimeScript RT reagent Kit with gDNA Eraser (Perfect Real Time; Takara, Dalian, China). The forward and reverse primers sequences for the qPCR are shown in Table 1. The genes expression levels were detected using TB Green™ Premix Ex Taq™ II (TIi RNaseH Plus; Takara, Dalian, China) according to the manufacturer’s instructions. The 2−ΔΔCT method was used to analyse the relative expression of target genes, and the housekeeping gene β-actin was used for normalization.Table 1 Primer sequences.Full size tableWestern blot analysisEqual amounts of proteins of yak lung tissue in different development stages were harvested. These proteins were separated on 10% polyacrylamide gels and transferred onto polyvinylidene difluoride (PVDF) membranes (Sangon Biotech, Shanghai, China). PVDF membranes were blocked in 10% non-fat (skimmed) milk for 3 h and then incubated in rabbit anti-VEGFA polyclonal antibody (OriGene, Maryland, USA) at 4 °C overnight. The membranes were then incubated with a goat anti-rabbit IgG antibody (Abcam, Cambridge, UK) for 2 h being washed 3 times (10 min / time) with Tris-buffered saline with Twen-20 (TBST; containing 0.1% Twen-20). All antibodies were diluted according to the manufacturer’s instructions. Immunoblots were analysed by autograph using a Gel Doc™ XR + Gel documentation system (BIO-RAD, California, USA).Statistical analysisThe experimental data are showed as the mean ± standard deviation (SD). The differences between the four groups were compared using one-way ANOVA. P values at less than 0.05 were considered significantly different. More

1.Kalnay E, Cai M. Impact of urbanization and land-use change on climate. Nature. 2003;423:528–31.CAS 
PubMed 
Article 

Google Scholar 
2.Archer SDJ, Pointing SB. Anthropogenic impact on the atmospheric microbiome. Nat Microbiol. 2020;5:229–31.CAS 
PubMed 
Article 

Google Scholar 
3.Powers RP, Jetz W. Global habitat loss and extinction risk of terrestrial vertebrates under future land-use-change scenarios. Nat Clim Change. 2019;9:323–9.Article 

Google Scholar 
4.Sandifer PA, Sutton-Grier AE, Ward BP. Exploring connections among nature, biodiversity, ecosystem services, and human health and well-being: Opportunities to enhance health and biodiversity conservation. Ecosyst Serv. 2015;12:1–15.Article 

Google Scholar 
5.Jansson JK, Hofmockel KS. Soil microbiomes and climate change. Nat Rev Microbiol. 2020;18:35–46.CAS 
PubMed 
Article 

Google Scholar 
6.Huttenhower C, Gevers D, Knight R, Abubucker S, Badger JH, Chinwalla AT, et al. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486:207–14.CAS 
Article 

Google Scholar 
7.Banerjee S, Schlaeppi K, van der Heijden MGA. Keystone taxa as drivers of microbiome structure and functioning. Nat Rev Microbiol. 2018;16:567–76.CAS 
PubMed 
Article 

Google Scholar 
8.Sapp M, Ploch S, Fiore-Donno AM, Bonkowski M, Rose LE. Protists are an integral part of the Arabidopsis thaliana microbiome. Environ Microbiol. 2018;20:30–43.CAS 
PubMed 
Article 

Google Scholar 
9.Vorholt JA. Microbial life in the phyllosphere. Nat Rev Microbiol. 2012;10:828–40.CAS 
PubMed 
Article 

Google Scholar 
10.Laforest-Lapointe I, Messier C, Kembel SW. Host species identity, site and time drive temperate tree phyllosphere bacterial community structure. Microbiome. 2016;4:27.PubMed 
PubMed Central 
Article 

Google Scholar 
11.Andrews JH, Harris RF. The ecology and biogeography of microorganisms on plant surfaces. Annu Rev Phytopathol. 2000;38:145–80.Article 

Google Scholar 
12.Lugtenberg B, Kamilova F. Plant-growth-promoting Rhizobacteria. Annu Rev Microbiol. 2009;63:541–56.CAS 
PubMed 
Article 

Google Scholar 
13.Philippot L, Raaijmakers JM, Lemanceau P, van der Putten WH. Going back to the roots: the microbial ecology of the rhizosphere. Nat Rev Microbiol. 2013;11:789–99.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
14.Davison J. Plant beneficial bacteria. Bio/Technol. 1988;6:282–6.CAS 

Google Scholar 
15.Schauer S, Kutschera U. A novel growth-promoting microbe, Methylobacterium funariae sp. nov., isolated from the leaf surface of a common moss. Plant Signal Behav. 2011;6:510–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
16.Innerebner G, Knief C, Vorholt JA. Protection of arabidopsis thaliana against leaf-pathogenic pseudomonas syringae by sphingomonas strains in a controlled model system. Appl Environ Microbiol. 2011;77:3202–10.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
17.Laforest-Lapointe I, Paquette A, Messier C, Kembel SW. Leaf bacterial diversity mediates plant diversity and ecosystem function relationships. Nature. 2017;546:145–7.CAS 
PubMed 
Article 

Google Scholar 
18.Koskella B, Meaden S, Crowther WJ, Leimu R, Metcalf CJE. A signature of tree health? Shifts in the microbiome and the ecological drivers of horse chestnut bleeding canker disease. N Phytol. 2017;215:737–46.CAS 
Article 

Google Scholar 
19.Isbell F, Tilman D, Polasky S, Loreau M. The biodiversity-dependent ecosystem service debt. Ecol Lett. 2015;18:119–34.PubMed 
Article 

Google Scholar 
20.Barnosky A, Matzke N, Tomiya S, Wogan G, Swartz B, Quental T, et al. Has the earth’s sixth mass extinction already arrived? Nat Nat. 2011;471:51–7.CAS 
Article 

Google Scholar 
21.Pascual U, Balvanera P, Díaz S, Pataki G, Roth E, Stenseke M, et al. Valuing nature’s contributions to people: the IPBES approach. Curr Opin Environ Sustain. 2017;26–27:7–16.Article 

Google Scholar 
22.Cavicchioli R, Ripple WJ, Timmis KN, Azam F, Bakken LR, Baylis M, et al. Scientists’ warning to humanity: microorganisms and climate change. Nat Rev Microbiol. 2019;17:569–86.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
23.Annamalai J, Namasivayam V. Endocrine disrupting chemicals in the atmosphere: Their effects on humans and wildlife. Environ Int. 2015;76:78–97.CAS 
PubMed 
Article 

Google Scholar 
24.Jumpponen A, Jones KL. Seasonally dynamic fungal communities in the Quercus macrocarpa phyllosphere differ between urban and nonurban environments. N Phytol. 2010;186:496–513.CAS 
Article 

Google Scholar 
25.Imperato V, Kowalkowski L, Portillo-Estrada M, Gawronski SW, Vangronsveld J, Thijs S. Characterisation of the Carpinus betulus L. Phyllomicrobiome in urban and forest areas. Front Microbiol. 2019;10:1110.PubMed 
PubMed Central 
Article 

Google Scholar 
26.Bowers RM, McLetchie S, Knight R, Fierer N. Spatial variability in airborne bacterial communities across land-use types and their relationship to the bacterial communities of potential source environments. ISME J. 2011;5:601–12.CAS 
PubMed 
Article 

Google Scholar 
27.Lymperopoulou DS, Adams RI, Lindow SE. Contribution of vegetation to the microbial composition of nearby outdoor air. Appl Environ Microbiol. 2016;82:3822–33.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
28.De Kempeneer L, Sercu B, Vanbrabant W, Van Langenhove H, Verstraete W. Bioaugmentation of the phyllosphere for the removal of toluene from indoor air. Appl Microbiol Biotechnol. 2004;64:284–8.PubMed 
Article 
CAS 

Google Scholar 
29.Hanski I, Hertzen Lvon, Fyhrquist N, Koskinen K, Torppa K, Laatikainen T, et al. Environmental biodiversity, human microbiota, and allergy are interrelated. Proc Natl Acad Sci. 2012;109:8334–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
30.Smets W, Wuyts K, Oerlemans E, Wuyts S, Denys S, Samson R, et al. Impact of urban land use on the bacterial phyllosphere of ivy (Hedera sp.). Atmos Environ. 2016;147:376–83.CAS 
Article 

Google Scholar 
31.Laforest-Lapointe I, Messier C, Kembel SW. Tree Leaf Bacterial Community Structure and Diversity Differ along a Gradient of Urban Intensity. mSystems. 2017;2:e00087–17.PubMed 
PubMed Central 
Article 

Google Scholar 
32.Espenshade J, Thijs S, Gawronski S, Bové H, Weyens N, Vangronsveld J. Influence of urbanization on epiphytic bacterial communities of the platanus × hispanica tree leaves in a Biennial Study. Front Microbiol. 2019;10:675.PubMed 
PubMed Central 
Article 

Google Scholar 
33.Wuyts K, Smets W, Lebeer S, Samson R. Green infrastructure and atmospheric pollution shape diversity and composition of phyllosphere bacterial communities in an urban landscape. FEMS Microbiol Ecol 2020;96:fiz173.CAS 
PubMed 
Article 

Google Scholar 
34.Zhao D, Liu G, Wang X, Daraz U, Sun Q. Abundance of human pathogen genes in the phyllosphere of four landscape plants. J Environ Manag. 2020;255:109933.CAS 
Article 

Google Scholar 
35.Gandolfi I, Canedoli C, Imperato V, Tagliaferri I, Gkorezis P, Vangronsveld J, et al. Diversity and hydrocarbon-degrading potential of epiphytic microbial communities on Platanus x acerifolia leaves in an urban area. Environ Pollut. 2017;220:650–8.CAS 
PubMed 
Article 

Google Scholar 
36.Weyens N, van der Lelie D, Taghavi S, Vangronsveld J. Phytoremediation: plant–endophyte partnerships take the challenge. Curr Opin Biotechnol. 2009;20:248–54.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
37.Afzal M, Khan QM, Sessitsch A. Endophytic bacteria: prospects and applications for the phytoremediation of organic pollutants. Chemosphere. 2014;117:232–42.CAS 
PubMed 
Article 

Google Scholar 
38.Siciliano SD, Fortin N, Mihoc A, Wisse G, Labelle S, Beaumier D, et al. Selection of specific endophytic bacterial genotypes by plants in response to soil contamination. Appl Environ Microbiol. 2001;67:2469–75.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
39.Barac T, Taghavi S, Borremans B, Provoost A, Oeyen L, Colpaert JV, et al. Engineered endophytic bacteria improve phytoremediation of water-soluble, volatile, organic pollutants. Nat Biotechnol. 2004;22:583–8.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
40.Sandhu A, Halverson LJ, Beattie GA. Bacterial degradation of airborne phenol in the phyllosphere. Environ Microbiol. 2007;9:383–92.CAS 
PubMed 
Article 

Google Scholar 
41.Weyens N, Thijs S, Popek R, Witters N, Przybysz A, Espenshade J, et al. The role of plant–microbe interactions and their exploitation for phytoremediation of air pollutants. Int J Mol Sci. 2015;16:25576–604.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
42.Essl F, Dullinger S, Rabitsch W, Hulme PE, Hülber K, Jarošík V, et al. Socioeconomic legacy yields an invasion debt. Proc Natl Acad Sci. 2011;108:203–7.CAS 
PubMed 
Article 

Google Scholar 
43.Walther G-R, Roques A, Hulme PE, Sykes MT, Pyšek P, Kühn I, et al. Alien species in a warmer world: risks and opportunities. Trends Ecol Evol. 2009;24:686–93.PubMed 
Article 

Google Scholar 
44.Blüthgen N, Menzel F, Blüthgen N. Measuring specialization in species interaction networks. BMC Ecol. 2006;6:9.PubMed 
PubMed Central 
Article 

Google Scholar 
45.Cobian GM, Egan CP, Amend AS. Plant–microbe specificity varies as a function of elevation. ISME J. 2019;13:2778–88.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
46.Bálint M, Bartha L, O’Hara RB, Olson MS, Otte J, Pfenninger M, et al. Relocation, high-latitude warming and host genetic identity shape the foliar fungal microbiome of poplars. Mol Ecol. 2015;24:235–48.PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
47.Vacher C, Cordier T, Vallance J. Phyllosphere fungal communities differentiate more thoroughly than bacterial communities along an elevation gradient. Micro Ecol. 2016;72:1–3.Article 

Google Scholar 
48.Callaway RM, Brooker RW, Choler P, Kikvidze Z, Lortie CJ, Michalet R, et al. Positive interactions among alpine plants increase with stress. Nature. 2002;417:844–8.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
49.Bever JD. Feeback between plants and their soil communities in an old field. Community Ecol. 1994;75:1965–77.Article 

Google Scholar 
50.Bever JD. Soil community feedback and the coexistence of competitors: conceptual frameworks and empirical tests. N Phytol. 2003;157:465–73.Article 

Google Scholar 
51.Klironomos JN. Feedback with soil biota contributes to plant rarity and invasiveness in communities. Nature. 2002;417:67–70.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
52.Reinhart KO, Callaway RM. Soil biota and invasive plants. N Phytol. 2006;170:445–57.Article 

Google Scholar 
53.Callaway RM, Thelen GC, Rodriguez A, Holben WE. Soil biota and exotic plant invasion. Nature. 2004;427:731–3.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
54.Brown CD, Vellend M. Non-climatic constraints on upper elevational plant range expansion under climate change. Proc R Soc B Biol Sci. 2014;281:20141779.Article 

Google Scholar 
55.Carteron A, Parasquive V, Blanchard F, Guilbeault‐Mayers X, Turner BL, Vellend M, et al. Soil abiotic and biotic properties constrain the establishment of a dominant temperate tree into boreal forests. J Ecol. 2020;108:931–44.Article 

Google Scholar 
56.Williamson M. Biological invasions. 1996. Springer Netherlands.57.Mitchell CE, Power AG. Release of invasive plants from fungal and viral pathogens. Nature. 2003;421:625–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
58.Ramirez KS, Snoek LB, Koorem K, Geisen S, Bloem LJ, ten Hooven F, et al. Range-expansion effects on the belowground plant microbiome. Nat Ecol Evol. 2019;3:604–11.PubMed 
PubMed Central 
Article 

Google Scholar 
59.Diez JM, Dickie I, Edwards G, Hulme PE, Sullivan JJ, Duncan RP. Negative soil feedbacks accumulate over time for non-native plant species. Ecol Lett. 2010;13:803–9.PubMed 
Article 

Google Scholar 
60.Lenssen NJL, Schmidt GA, Hansen JE, Menne MJ, Persin A, Ruedy R, et al. Improvements in the GISTEMP uncertainty model. J Geophys Res Atmos. 2019;124:6307–26.Article 

Google Scholar 
61.O’brien RD, Lindow SE. Effect of plant species and environmental conditions on ice nucleation activity of pseudomonas syringae on leaves. Appl Environ Microbiol. 1988;54:2281–6.PubMed 
PubMed Central 
Article 

Google Scholar 
62.Klinkert B, Narberhaus F. Microbial thermosensors. Cell Mol Life Sci. 2009;66:2661–76.CAS 
PubMed 
Article 

Google Scholar 
63.Velásquez AC, Castroverde CDM, He SY. Plant-pathogen warfare under changing climate conditions. Curr Biol CB. 2018;28:R619–R634.PubMed 
Article 
CAS 

Google Scholar 
64.Compant S, van der Heijden MGA, Sessitsch A. Climate change effects on beneficial plant-microorganism interactions. FEMS Microbiol Ecol. 2010;73:197–214.CAS 
PubMed 

Google Scholar 
65.Cheng YT, Zhang L, He SY. Plant-microbe interactions facing environmental challenge. Cell Host Microbe. 2019;26:183–92.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
66.Guerra CA, Delgado‐Baquerizo M, Duarte E, Marigliano O, Görgen C, Maestre FT, et al. Global projections of the soil microbiome in the Anthropocene. Glob Ecol Biogeogr. 2021;30:987–99.PubMed 
Article 

Google Scholar 
67.Frindte K, Pape R, Werner K, Löffler J, Knief C. Temperature and soil moisture control microbial community composition in an arctic–alpine ecosystem along elevational and micro-topographic gradients. ISME J. 2019;13:2031–43.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
68.Cordier T, Robin C, Capdevielle X, Fabreguettes O, Desprez-Loustau M-L, Vacher C. The composition of phyllosphere fungal assemblages of European beech (Fagus sylvatica) varies significantly along an elevation gradient. N Phytol. 2012;196:510–9.Article 

Google Scholar 
69.Tedersoo L, Bahram M, Toots M, Diédhiou AG, Henkel TW, Kjøller R, et al. Towards global patterns in the diversity and community structure of ectomycorrhizal fungi. Mol Ecol. 2012;21:4160–70.PubMed 
Article 

Google Scholar 
70.Gomes T, Pereira JA, Benhadi J, Lino-Neto T, Baptista P. Endophytic and epiphytic phyllosphere fungal communities are shaped by different environmental factors in a Mediterranean ecosystem. Micro Ecol. 2018;76:668–79.Article 

Google Scholar 
71.Peñuelas J, Rico L, Ogaya R, Jump AS, Terradas J. Summer season and long-term drought increase the richness of bacteria and fungi in the foliar phyllosphere of Quercus ilex in a mixed Mediterranean forest. Plant Biol Stuttg Ger. 2012;14:565–75.Article 

Google Scholar 
72.Rico L, Ogaya R, Terradas J, Peñuelas J. Community structures of N2 -fixing bacteria associated with the phyllosphere of a Holm oak forest and their response to drought. Plant Biol Stuttg Ger. 2014;16:586–93.CAS 
Article 

Google Scholar 
73.Grady KL, Sorensen JW, Stopnisek N, Guittar J, Shade A. Assembly and seasonality of core phyllosphere microbiota on perennial biofuel crops. Nat Commun. 2019;10:1–10.Article 
CAS 

Google Scholar 
74.Redford AJ, Fierer N. Bacterial Succession on the Leaf Surface: A Novel System for Studying Successional Dynamics. Micro Ecol. 2009;58:189–98.Article 

Google Scholar 
75.Edwards JA, Santos-Medellín CM, Liechty ZS, Nguyen B, Lurie E, Eason S, et al. Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice. PLOS Biol. 2018;16:e2003862.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
76.Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems. Nature. 2003;421:37–42.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
77.Zhao C, Liu B, Piao S, Wang X, Lobell DB, Huang Y, et al. Temperature increase reduces global yields of major crops in four independent estimates. Proc Natl Acad Sci. 2017;114:9326–31.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
78.Ray DK, Mueller ND, West PC, Foley JA. Yield trends are insufficient to double global crop production by 2050. PLOS ONE. 2013;8:e66428.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
79.Angel R, Soares MIM, Ungar ED, Gillor O. Biogeography of soil archaea and bacteria along a steep precipitation gradient. ISME J. 2010;4:553–63.PubMed 
Article 

Google Scholar 
80.Kaisermann A, Vries FTde, Griffiths RI, Bardgett RD. Legacy effects of drought on plant–soil feedbacks and plant–plant interactions. N Phytol. 2017;215:1413–24.CAS 
Article 

Google Scholar 
81.Hawkes CV, Kivlin SN, Rocca JD, Huguet V, Thomsen MA, Suttle KB. Fungal community responses to precipitation. Glob Change Biol. 2011;17:1637–45.Article 

Google Scholar 
82.Lau JA, Lennon JT. Rapid responses of soil microorganisms improve plant fitness in novel environments. Proc Natl Acad Sci. 2012;109:14058–62.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
83.Sheik CS, Beasley WH, Elshahed MS, Zhou X, Luo Y, Krumholz LR. Effect of warming and drought on grassland microbial communities. ISME J. 2011;5:1692–700.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
84.Bradford MA. Thermal adaptation of decomposer communities in warming soils. Front Microbiol. 2013;4:333.PubMed 
PubMed Central 
Article 

Google Scholar 
85.Li F, Deng J, Nzabanita C, Li Y, Duan T. Growth and physiological responses of perennial ryegrass to an AMF and an Epichloë endophyte under different soil water contents. Symbiosis. 2019;79:151–61.CAS 
Article 

Google Scholar 
86.Ibekwe AM, Ors S, Ferreira JFS, Liu X, Suarez DL, Ma J, et al. Functional relationships between aboveground and belowground spinach (Spinacia oleracea L., cv. Racoon) microbiomes impacted by salinity and drought. Sci Total Environ. 2020;717:137207.CAS 
PubMed 
Article 

Google Scholar 
87.Prosser JI, Bohannan BJM, Curtis TP, Ellis RJ, Firestone MK, Freckleton RP, et al. The role of ecological theory in microbial ecology. Nat Rev Microbiol. 2007;5:384–92.CAS 
PubMed 
Article 

Google Scholar 
88.Shoemaker WR, Locey KJ, Lennon JT. A macroecological theory of microbial biodiversity. Nat Ecol Evol. 2017;1:0107.Article 

Google Scholar 
89.Ratzke C, Denk J, Gore J. Ecological suicide in microbes. Nat Ecol Evol. 2018;2:867–72.PubMed 
PubMed Central 
Article 

Google Scholar 
90.Shade A, Dunn RR, Blowes SA, Keil P, Bohannan BJM, Herrmann M, et al. Macroecology to unite all life, large and small. Trends Ecol Evol. 2018;33:731–44.PubMed 
Article 

Google Scholar 
91.Grilli J. Macroecological laws describe variation and diversity in microbial communities. Nat Commun. 2020;11:4743.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
92.Knief C, Ramette A, Frances L, Alonso-Blanco C, Vorholt JA. Site and plant species are important determinants of the Methylobacterium community composition in the plant phyllosphere. ISME J. 2010;4:719–28.CAS 
PubMed 
Article 

Google Scholar 
93.Redford AJ, Bowers RM, Knight R, Linhart Y, Fierer N. The ecology of the phyllosphere: geographic and phylogenetic variability in the distribution of bacteria on tree leaves: Biogeography of phyllosphere bacterial communities. Environ Microbiol. 2010;12:2885–93.PubMed 
PubMed Central 
Article 

Google Scholar 
94.Remus-Emsermann MNP, Tecon R, Kowalchuk GA, Leveau JHJ. Variation in local carrying capacity and the individual fate of bacterial colonizers in the phyllosphere. ISME J. 2012;6:756–65.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
95.Kembel SW, O’Connor TK, Arnold HK, Hubbell SP, Wright SJ, Green JL. Relationships between phyllosphere bacterial communities and plant functional traits in a neotropical forest. Proc Natl Acad Sci. 2014;111:13715–20.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
96.Maignien L, DeForce EA, Chafee ME, Eren AM, Simmons SL. Ecological succession and stochastic variation in the assembly of Arabidopsis thaliana phyllosphere communities. mBio. 2014;5:e00682–13.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
97.Wagner MR, Lundberg DS, del Rio TG, Tringe SG, Dangl JL, Mitchell-Olds T. Host genotype and age shape the leaf and root microbiomes of a wild perennial plant. Nat Commun. 2016;7:12151.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
98.Carlström CI, Field CM, Bortfeld-Miller M, Müller B, Sunagawa S, Vorholt JA. Synthetic microbiota reveal priority effects and keystone strains in the Arabidopsis phyllosphere. Nat. Ecol Evol. 2019;3:1445–54.
Google Scholar 
99.Lajoie G, Maglione R, Kembel SW. Adaptive matching between phyllosphere bacteria and their tree hosts in a neotropical forest. Microbiome. 2020;8:70.PubMed 
PubMed Central 
Article 

Google Scholar 
100.Massoni J, Bortfeld-Miller M, Jardillier L, Salazar G, Sunagawa S, Vorholt JA. Consistent host and organ occupancy of phyllosphere bacteria in a community of wild herbaceous plant species. ISME J. 2020;14:245–58.CAS 
PubMed 
Article 

Google Scholar 
101.Lajoie G, Kembel SW. Host neighborhood shapes bacterial community assembly and specialization on tree species across a latitudinal gradient. Ecol Monogr. 2021;91:e01443.Article 

Google Scholar 
102.Vellend M. Conceptual synthesis in community ecology. Q Rev Biol. 2010;85:183–206.Article 
PubMed 

Google Scholar 
103.Bernhardt ES, Rosi EJ, Gessner MO. Synthetic chemicals as agents of global change. Front Ecol Environ. 2017;15:84–90.Article 

Google Scholar  More

Despite only focusing on one female Chinese pangolin, LF28, our study, to our knowledge, is the first to provide highly detailed records on the nursing behavior of this poorly studied but critically endangered species. During the entire tracking period, the body weight of LF28 increased from 2 kg at the age of 1 year to 3 kg at the age of 2 years, and LF28 reached her maximum body weight of 4 kg at the age of 3 years. Based on the uninterrupted monitoring between Dec 2014 and June 2016, LF28 gave birth to her first offspring when she was 3 years old and another one at the age of 4 years (Fig. 1). Both infants were born in early December, which were in accordance with the peak birth season of the species10. Our observations confirmed that the Chinese pangolin is a seasonal breeder in the wild, and they give birth once a year10,11. Also, they can give birth in consecutive years with a litter size of one17.Other studies (n = 4) have found that the lightest weight, or youngest age, a female Chinese pangolin can give birth at the age of 2 years or weight of 3 kg11,17,18, which indicated that they can conceive at an age of 1–2 years. Therefore, the first birth of LF28, which took place when she was 3 years old, might suggest a delay in pregnancy or sex maturation. However, information concerning the average primipara age for this species is not available to date, more research, especially in the wild, is necessary.Our results indicate that female Chinese pangolins will carry their offspring frequently from one nursing burrow to another during the entire nursing period. In the case of LF28, nursing burrows were only some of the resting burrows utilized and were predominantly located within the core area (MCP75) of her home range (Fig. 4), despite the close proximity to human settlements. This suggests that familiarity of the environment or food resource availability should be important considerations in nursing burrow selection.Nursing burrows were normally used only once during the same nursing period, with durations varying from 1 day to more than 1 month (Fig. 5). This frequent relocation behavior should be important to avoid predation of the newborn. Our monitoring showed that small carnivores, such as ferret-badgers or crab-eating mongoose, will enter the nursing burrow, which may suggest they are searching for prey. Therefore, this could reflect a potential threat to the infant pangolin, especially when the mother is absent for foraging8.Burrows where LF28 gave birth were not only used for the longest duration after birth, they were also used before parturition. Similar to our findings, a previous study reported that both males and females will collect and pull hay into the resting burrow in the wintertime3. Therefore, in addition to providing insulation, the hay could also serve as necessary bedding for the delivery and nursing of offspring. Other functions of hay that have been proposed include false barriers that can act as predator deterrent structures19.Our records revealed at least two different adult male pangolins approaching and entering the nursing burrows multiple times throughout the nursing period. Most of these visits lasted only minutes, whereas a few lasted longer. During one long visit, in March, mating behavior was observed, therefore the occurrence of post-partum estrus, or even ovulation, may be likely for this species. In captivity, mating behavior was also observed between February and July10,20. Although there is no direct evidence yet, these adult male visits suggest that at least some of them were for mate-searching. It has been proposed that while mammalian females spend more energy on parental care, males often invest more energy towards seeking mates21. For solitary and fossorial species such as the pangolin, a male’s mate-finding tactics can be critical for mating success, especially due to the low population density22,23. Male pangolins most likely depend on olfactory cues to locate females in heat. In mammals, female chemical signals have important roles in sexual attraction and facilitating sexual receptivity24,25,26,27. Female Chinese pangolins tend to defecate close to the burrow during the nursing period (N.C.M. Sun unpubl. data), therefore, despite the frequent relocation behavior expressed by the mother, it was likely to generate sufficient olfactory information for male pangolins.It is also possible that female pangolins will mate more than once, even with different males, during the same nursing period. Sun et al.17 have reported that certain female Chinese pangolins exhibited a lack of mate fidelity based on microsatellite marker assessments. Our observation provides additional support for this phenomenon. Multiple mating with the same or different males has been observed in several solitary carnivores28,29,30,31. For males, frequent pre-copulatory encounters with females may offer advantages that increase opportunities for mating compared to males that are less familiar with females32,33. Hypotheses concerning the advantages of females exhibiting promiscuity have also been widely proposed, including direct benefits (e.g., stimulation of reproduction, fertilization assurance, mate retention etc.) and genetic benefits (e.g., choice of paternity, sperm competition, inbreeding avoidance etc.)34,35.Interestingly, during two separate visitations adult males exhibited excavation behavior, and both events took place shortly after parturition. This excavation behavior at a parturition burrow has never been reported before for male pangolins, therefore, further research is needed to better understand the role male pangolins play in parental care.The fetus of LF28’s second offspring detected in the ultrasonographic image in Aug. 15 provided additional information on the gestation length of the species. Following the fetal and extra-fetal structure development of small-sized (3–8 kg) dogs described in Luvoni and Grioni36 and Kim and Son37, we estimated the gestation period of this fetus may have lasted 30–40 days or less. The implantation of the blastocyst, therefore, most likely occurred in early July. This infant pangolin was born on Dec. 8 later that year, and the gestation length was estimated to be around 150 days, which was shorter than previous reports4,9,10. This was the first estimation of gestation length of the Chinese pangolin based on physiological evidence under natural conditions.Our findings of the gestation period, which took place later in the year (July–December), coupled together with the occurrence of post-partum estrus and mating earlier in the year (December–May), suggests that delayed implantation likely takes place in this species, as proposed by Chin et al.11. This also explains why there was such an extensive variation in the gestation length, from 180 to more than 372 days, determined based on the observation of mating behavior and parturition in captivity10,11,18. More studies on the reproductive physiology for this species are necessary.Lastly, the present study also demonstrated that the difficulties associated with researching the life history and behaviors of the elusive pangolin could be alleviated with the use of technologies (e.g., camera trapping, radio tracking, etc.). This is especially true for non-migratory fossorial species if one has an appropriate knowledge of their home range or residential environment. There are more and more new technologies and devices that have been developed and applied to wildlife research in the field, which should greatly improve our understanding and promote conservation efforts of endangered species such as the pangolin. More