Ecology

1.Castillo, L. E., de la Cruz, E. & Ruepert, C. Ecotoxicology and pesticides in tropical aquatic ecosystems of Central America. Environ. Toxicol. Chem. 16, 41–51. https://doi.org/10.1002/etc.5620160104 (1997).Article 
CAS 

Google Scholar 
2.Moreno-González, R. & León, V. Presence and distribution of current-use pesticides in surface marine sediments from a Mediterranean coastal lagoon (SE Spain). Environ. Sci. Pollut. Res. 24, 8033–8048. https://doi.org/10.1007/s11356-017-8456-0 (2017).Article 
CAS 

Google Scholar 
3.Hernández-Romero, A. H., Tovilla-Hernández, C., Malo, E. A. & Bello-Mendoza, R. Water quality and presence of pesticides in a tropical coastal wetland in southern Mexico. Mar. Pollut. Bull. 48, 1130–1141. https://doi.org/10.1016/j.marpolbul.2004.01.003 (2004).Article 
PubMed 
CAS 

Google Scholar 
4.Wurl, O. & Obbard, J. P. Organochlorine pesticides, polychlorinated biphenyls and polybrominated diphenyl ethers in Singapore’s coastal marine sediments. Chemosphere 58, 925–933. https://doi.org/10.1016/j.chemosphere.2004.09.054 (2005).ADS 
Article 
PubMed 
CAS 

Google Scholar 
5.Carvalho, F. P. et al. Organic contaminants in the marine environment of Manila Bay, Philippines. Arch. Environ. Contam. Toxicol. 57, 348–358. https://doi.org/10.1007/s00244-008-9271-x (2009).Article 
PubMed 
CAS 

Google Scholar 
6.Australian Government and Queensland Government. Reef 2050 Water Quality Improvement Plan, Monitoring Program. (Australian and Queensland Governments, 2018). https://www.reefplan.qld.gov.au/tracking-progress/paddock-to-reef/modelling-and-monitoring.7.O’Brien, D. et al. Spatial and temporal variability in pesticide exposure downstream of a heavily irrigated cropping area: Application of different monitoring techniques. J. Agric. Food Chem. 64, 3975–3989. https://doi.org/10.1021/acs.jafc.5b04710 (2016).Article 
PubMed 
CAS 

Google Scholar 
8.Warne, M. St. J., Smith, R. & Turner, R. Analysis of pesticide mixtures discharged to the lagoon of the Great Barrier Reef, Australia. Environ. Pollut. 265, 114088. https://doi.org/10.1016/j.envpol.2020.114088 (2020).Article 
PubMed 
CAS 

Google Scholar 
9.Shaw, M. et al. Monitoring pesticides in the Great Barrier Reef. Mar. Pollut. Bull. 60, 113–122. https://doi.org/10.1016/j.marpolbul.2009.08.026 (2010).Article 
PubMed 
CAS 

Google Scholar 
10.Kennedy, K. et al. The influence of a season of extreme wet weather events on exposure of the World Heritage Area Great Barrier Reef to pesticides. Mar. Pollut. Bull. 64, 1495–1507. https://doi.org/10.1016/j.marpolbul.2012.05.014 (2012).Article 
PubMed 
CAS 

Google Scholar 
11.Mercurio, P. et al. Degradation of herbicides in the tropical marine environment: Influence of light and sediment. PLoS ONE 11, e0165890. https://doi.org/10.1371/journal.pone.0165890 (2016).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
12.Gallen, C. et al. Marine Monitoring Program: Annual report for inshore pesticide monitoring 2017–18. Report for the Great Barrier Reef Marine Park Authority. http://elibrary.gbrmpa.gov.au/jspui/handle/11017/3489. (2019).13.Smith, R. et al. Large-scale pesticide monitoring across Great Barrier Reef catchments–paddock to reef integrated monitoring, modelling and reporting program. Mar. Pollut. Bull. 65, 117–127. https://doi.org/10.1016/j.marpolbul.2011.08.010 (2012).Article 
PubMed 
CAS 

Google Scholar 
14.Oettmeier, W. Herbicide resistance and supersensitivity in photosystem II. Cell. Mol. Life Sci. 55, 1255–1277. https://doi.org/10.1007/s000180050370 (1999).Article 
PubMed 
CAS 

Google Scholar 
15.Davis, A., Lewis, S., Brodie, J. & Benson, A. The potential benefits of herbicide regulation: A cautionary note for the Great Barrier Reef catchment area. Sci. Total Environ. 490, 81–92. https://doi.org/10.1016/j.scitotenv.2014.04.005 (2014).ADS 
Article 
PubMed 
CAS 

Google Scholar 
16.King, J., Alexander, F. & Brodie, J. Regulation of pesticides in Australia: The Great Barrier Reef as a case study for evaluating effectiveness. Agr. Ecosyst. Environ. 180, 54–67. https://doi.org/10.1016/j.agee.2012.07.001 (2013).Article 

Google Scholar 
17.Devlin, M. et al. Advancing our Understanding of the Source, Management, Transport and Impacts of Pesticides on the Great Barrier Reef 2011–2015. Report for the Queensland Department of Environment and Heritage Protection. (Tropical Water & Aquatic Ecosytem Research (TropWATER) Publication, James Cook University, 2015). https://www.qld.gov.au/environment/assets/documents/agriculture/sustainable-farming/reef/rp104c-pesticide-report.pdf/.18.Flores, F., Collier, C. J., Mercurio, P. & Negri, A. P. Phytotoxicity of four photosystem II herbicides to tropical seagrasses. PLoS ONE 8, e75798. https://doi.org/10.1371/journal.pone.0075798 (2013).ADS 
Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
19.Haynes, D. et al. The occurrence and impact of herbicides in the Great Barrier Reef, Australia. Reef Res. 10, 3–5 (2000).
Google Scholar 
20.Negri, A. P., Flores, F., Röthig, T. & Uthicke, S. Herbicides increase the vulnerability of corals to rising sea surface temperature. Limnol. Oceanogr. 56, 471–485. https://doi.org/10.4319/lo.2011.56.2.0471 (2011).ADS 
Article 
CAS 

Google Scholar 
21.Marques, J. A., Flores, F., Bianchini, A., Uthicke, S. & Negri, A. P. Acclimation history modulates effect size of calcareous algae (Halimeda opuntia) to herbicide exposure under future climate scenarios. Sci. Total Environ. 736, 140308. https://doi.org/10.1016/j.scitotenv.2020.140308 (2020).Article 
CAS 

Google Scholar 
22.van Dam, J. W., Negri, A. P., Mueller, J. F. & Uthicke, S. Symbiont-specific responses in foraminifera to the herbicide diuron. Mar. Pollut. Bull. 65, 373–383. https://doi.org/10.1016/j.marpolbul.2011.08.008 (2012).Article 
PubMed 
CAS 

Google Scholar 
23.Thomas, M. C., Flores, F., Kaserzon, S., Fisher, R. & Negri, A. P. Toxicity of ten herbicides to the tropical marine microalgae Rhodomonas salina. Sci. Rep. 10, 1–16. https://doi.org/10.1038/s41598-020-64116-y (2020).Article 
CAS 

Google Scholar 
24.Magnusson, M., Heimann, K. & Negri, A. P. Comparative effects of herbicides on photosynthesis and growth of tropical estuarine microalgae. Mar. Pollut. Bull. 56, 1545–1552. https://doi.org/10.1016/j.marpolbul.2008.05.023 (2008).Article 
PubMed 
CAS 

Google Scholar 
25.Muscatine, L. The role of symbiotic algae in carbon and energy flux in reef corals. Coral Reefs 25, 1–29 (1990).
Google Scholar 
26.Oettmeier, W. Herbicides of photosystems II. In Structure, Function and Molecular Biology (ed. Barber, J.) 349–408 (Elsevier, 1992).
Google Scholar 
27.Jones, R. J., Muller, J., Haynes, D. & Schreiber, U. Effects of herbicides diuron and atrazine on corals of the Great Barrier Reef, Australia. Mar. Ecol. Prog. Ser. 251, 153–167. https://doi.org/10.3354/meps251153 (2003).ADS 
Article 
CAS 

Google Scholar 
28.Jones, R. J. & Kerswell, A. P. Phytotoxicity of Photosystem II (PSII) herbicides to coral. Mar. Ecol. Prog. Ser. 261, 149–159. https://doi.org/10.3354/meps261149 (2003).ADS 
Article 
CAS 

Google Scholar 
29.Cantin, N. E., Negri, A. P. & Willis, B. L. Photoinhibition from chronic herbicide exposure reduces reproductive output of reef-building corals. Mar. Ecol. Prog. Ser. 344, 81–93. https://doi.org/10.3354/meps07059 (2007).ADS 
Article 
CAS 

Google Scholar 
30.Negri, A. et al. Effects of the herbicide diuron on the early life history stages of coral. Mar. Pollut. Bull. 51, 370–383. https://doi.org/10.1016/j.marpolbul.2004.10.053 (2005).Article 
PubMed 
CAS 

Google Scholar 
31.Decelle, J. et al. Worldwide occurrence and activity of the reef-building coral symbiont Symbiodinium in the open ocean. Curr. Biol. 28, 3625–3633. https://doi.org/10.1016/j.cub.2018.09.024 (2018).Article 
PubMed 
CAS 

Google Scholar 
32.Baker, A. C. Reef corals bleach to survive change. Nature 411, 765–766. https://doi.org/10.1038/35081151 (2001).ADS 
Article 
PubMed 
CAS 

Google Scholar 
33.Muller-Parker, G., D’elia, C. F. & Cook, C. B. Coral Reefs in the Anthropocene 99–116 (Springer, 2015). https://pdfs.semanticscholar.org/191e119/119ba111eab744a4054c4068f4057a4003bb4058bd4001b9628.pdf.34.Chakravarti, L. J., Negri, A. P. & Oppen, M. J. Thermal and herbicide tolerances of chromerid algae and their ability to form a symbiosis with corals. Front. Microbiol. 10, 173. https://doi.org/10.3389/fmicb.2019.00173 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
35.van Dam, J., Uthicke, S., Beltran, V., Mueller, J. & Negri, A. Combined thermal and herbicide stress in functionally diverse coral symbionts. Environ. Pollut. 204, 271–279. https://doi.org/10.1016/j.envpol.2015.05.013 (2015).Article 
PubMed 
CAS 

Google Scholar 
36.Mercurio, P. et al. Contribution of transformation products towards the total herbicide toxicity to tropical marine organisms. Sci. Rep. 8, 1–12. https://doi.org/10.1038/s41598-018-23153-4 (2018).Article 
CAS 

Google Scholar 
37.Magnusson, M., Heimann, K., Ridd, M. & Negri, A. P. Pesticide contamination and phytotoxicity of sediment interstitial water to tropical benthic microalgae. Water Res. 47, 5211–5221. https://doi.org/10.1016/j.watres.2013.06.003 (2013).Article 
PubMed 
CAS 

Google Scholar 
38.Thomas, M. C., Flores, F., Kaserzon, S., Reeks, T. & Negri, A. P. Toxicity of the herbicides diuron, propazine, tebuthiuron, and haloxyfop to the diatom Chaetoceros muelleri. Sci. Rep. 10, 19592. https://doi.org/10.1038/s41598-020-76363-0 (2020).ADS 
Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
39.Warne, M. St. J., King, O. & Smith, R. Ecotoxicity thresholds for ametryn, diuron, hexazinone and simazine in fresh and marine waters. Environ. Sci. Pollut. Res. 25, 3151–3169. https://doi.org/10.1007/s11356-017-1097-5 (2018).Article 
CAS 

Google Scholar 
40.Traas, T. P. et al. In Species Sensitivity Distributions in Ecotoxicology (eds Posthuma, L. et al.) 315–344 (CRC Press, 2002).
Google Scholar 
41.ANZG. Australian and New Zealand Guidelines for Fresh and Marine Water Quality. 1–103 (Australian and New Zealand Governments and Australian State and Territory Governments, 2018). http://waterquality.gov.au/anz-guidelines.42.King, O., Smith, R., Mann, R. & Warne, M. St. J. Proposed Aquatic Ecosystem Protection Guideline Values for Pesticides Commonly Used in the Great Barrier Reef catchment Area: Part 2— Bromacil, Chlorothalonil, Fipronil, Fluometuron, Fluroxypyr, Haloxyfop, MCPA, Pendimethalin, Prometryn, Propazine, Propiconazole, Terbutryn, Triclopyr and Terbuthylazine. (Department of Environment and Science, 2017). https://www.publications.qld.gov.au/dataset/proposed-guideline-values-27-pesticides-used-in-the-gbr-catchment.43.King, O., Smith, R., Mann, R. & Warne, M. St. J. Proposed Aquatic Ecosystem Protection Guideline Values for Pesticides Commonly Used in the Great Barrier Reef Catchment Area: Part 1–2, 4-D, Ametryn, Diuron, Glyphosate, Hexazinone, Imazapic, Imidacloprid, Isoxaflutole, Metolachlor, Metribuzin, Metsulfuron-methyl, Simazine and Tebuthiuron 296 (Department of Environment and Science, 2017). https://www.publications.qld.gov.au/dataset/proposed-guideline-values-27-pesticides-used-in-the-gbr-catchment.44.Marie, D., Rigaut-Jalabert, F. & Vaulot, D. An improved protocol for flow cytometry analysis of phytoplankton cultures and natural samples. Cytom. Part A 85, 962–968. https://doi.org/10.1002/cyto.a.22517 (2014).Article 
CAS 

Google Scholar 
45.Warne, M. St. J. et al. Revised Method for Deriving Australian and New Zealand Water Quality Guideline Values for Toxicants: Update of 2015 Version. Prepared for the Revision of the Australian and New Zealand Guidelines for Fresh and Marine Water Quality 48 (Australian and New Zealand Governments and Australian State and Territory Governments, 2018). https://www.waterquality.gov.au/sites/default/files/documents/warne-wqg-derivation2018.pdf.46.Vinyard, D. J., Ananyev, G. M. & Charles Dismukes, G. Photosystem II: The reaction center of oxygenic photosynthesis. Annu. Rev. Biochem. 82, 577–606. https://doi.org/10.1146/annurev-biochem-070511-100425 (2013).Article 
PubMed 
CAS 

Google Scholar 
47.Haworth, P. & Steinback, K. E. Interaction of herbicides and quinone with the qb-protein of the diuron-resistant Chlamydomonas reinhardtii mutant Dr2. Plant Physiol. 83, 1027–1031. https://doi.org/10.1104/pp.83.4.1027 (1987).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
48.USEPA. ECOTOX User Guide: ECOTOXicology Database System. Version 5.0. (United States Environmental Protection Agency, 2019) http://cfpub.epa.gov/ecotox/.49.Magnusson, M. Effects of Priority Herbicides and Their Breakdown Products on Tropical, ESTUARINE Microalgae of the Great Barrier Reef Lagoon. PhD thesis, James Cook University (2009).50.MacBean, C. The Pesticide Manual: A World Compendium (British Crop Protection Council, 2012).
Google Scholar 
51.Haq, S., Bachvaroff, T. R. & Place, A. R. Characterization of acetyl-CoA carboxylases in the basal dinoflagellate Amphidinium carterae. Mar. Drugs 15, 149. https://doi.org/10.3390/md15060149 (2017).Article 
PubMed Central 
CAS 

Google Scholar 
52.Tang, C. Y., Huang, Z. & Allen, H. C. Interfacial water structure and effects of Mg2+ and Ca2+ binding to the COOH headgroup of a palmitic acid monolayer studied by sum frequency spectroscopy. J. Phys. Chem. B 115, 34–40. https://doi.org/10.1021/jp1062447 (2011).Article 
PubMed 
CAS 

Google Scholar 
53.Brzozowska, A., Duits, M. H. & Mugele, F. Stability of stearic acid monolayers on artificial sea water. Colloid Surf. A 407, 38–48 (2012).Article 
CAS 

Google Scholar 
54.McCourt, J. & Duggleby, R. Acetohydroxyacid synthase and its role in the biosynthetic pathway for branched-chain amino acids. Amino Acids 31, 173–210. https://doi.org/10.1007/s00726-005-0297-3 (2006).Article 
PubMed 
CAS 

Google Scholar 
55.Genty, B., Briantais, J.-M. & Baker, N. R. The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. BBA 990, 87–92. https://doi.org/10.1016/S0304-4165(89)80016-9 (1989).Article 
CAS 

Google Scholar 
56.Jeong, H. J. et al. Heterotrophic feeding as a newly identified survival strategy of the dinoflagellate Symbiodinium. Proc. Natl. Acad. Sci. U.S.A. 109, 12604–12609. https://doi.org/10.1073/pnas.1204302109 (2012).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
57.Ralph, P., Smith, R., Macinnis-Ng, C. & Seery, C. Use of fluorescence-based ecotoxicological bioassays in monitoring toxicants and pollution in aquatic systems. Toxicol. Environ. Chem. 89, 589–607. https://doi.org/10.1080/02772240701561593 (2007).Article 
CAS 

Google Scholar 
58.OECD. Test No. 201: Freshwater Alga and Cyanobacteria, Growth Inhibition Test, OECD Guidelines for the Testing of Chemicals, Section 2 (OECD Publishing, 2011).
Google Scholar 
59.Kamei, M., Takayama, K., Ishibashi, H. & Takeuchi, I. Effects of ecologically relevant concentrations of Irgarol 1051 in tropical to subtropical coastal seawater on hermatypic coral Acropora tenuis and its symbiotic dinoflagellates. Mar. Poll. Bull. 150, 110734. https://doi.org/10.1016/j.marpolbul.2019.110734 (2020).Article 
CAS 

Google Scholar 
60.McKenzie, M. R., Templeman, M. A. & Kingsford, M. J. Detecting effects of herbicide runoff: The use of Cassiopea maremetens as a biomonitor to hexazinone. Aquat. Toxicol. 221, 105442. https://doi.org/10.1016/j.aquatox.2020.105442 (2020).Article 
PubMed 
CAS 

Google Scholar 
61.Howe, P. L., Reichelt-Brushett, A. J., Clark, M. W. & Seery, C. R. Toxicity estimates for diuron and atrazine for the tropical marine cnidarian Exaiptasia pallida and in-hospite Symbiodinium spp. using PAM chlorophyll-a fluorometry. J. Photochem. Photobiol. B 171, 125–132. https://doi.org/10.1016/j.jphotobiol.2017.05.006 (2017).Article 
PubMed 
CAS 

Google Scholar 
62.Takahashi, S., Whitney, S. M. & Badger, M. R. Different thermal sensitivity of the repair of photodamaged photosynthetic machinery in cultured Symbiodinium species. Proc. Natl. Acad. Sci. U.S.A. 106, 3237–3242. https://doi.org/10.1073/pnas.0808363106 (2009).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
63.Jones, R. The ecotoxicological effects of Photosystem II herbicides on corals. Mar. Pollut. Bull. 51, 495–506. https://doi.org/10.1016/j.marpolbul.2005.06.027 (2005).Article 
PubMed 
CAS 

Google Scholar 
64.Rowen, D. J., Templeman, M. A. & Kingsford, M. J. Herbicide effects on the growth and photosynthetic efficiency of Cassiopea maremetens. Chemosphere 182, 143–148. https://doi.org/10.1016/j.chemosphere.2017.05.001 (2017).ADS 
Article 
PubMed 
CAS 

Google Scholar 
65.Cantin, N. E., van Oppen, M. J., Willis, B. L., Mieog, J. C. & Negri, A. P. Juvenile corals can acquire more carbon from high-performance algal symbionts. Coral Reefs 28, 405. https://doi.org/10.1007/s00338-009-0478-8 (2009).ADS 
Article 

Google Scholar 
66.Fitt, W. & Trench, R. The relation of diel patterns of cell division to diel patterns of motility in the symbiotic dinoflagellate Symbiodinium microadria ticum Freudenthal in culture. New Phytol. 94, 421–432 (1983).Article 

Google Scholar 
67.Randall, C. J. et al. Sexual production of corals for reef restoration in the Anthropocene. Mar. Ecol. Prog. Ser. 635, 203–232. https://doi.org/10.3354/meps13206 (2020).ADS 
Article 

Google Scholar 
68.Baird, A. H., Bhagooli, R., Ralph, P. J. & Takahashi, S. Coral bleaching: The role of the host. Trends Ecol. Evol. 24, 16–20. https://doi.org/10.1016/j.tree.2008.09.005 (2009).Article 
PubMed 

Google Scholar 
69.Flores, F., Kaserzon, S., Elisei, G., Ricardo, G. & Negri, A. P. Toxicity thresholds of three insecticides and two fungicides to larvae of the coral Acropora tenuis. PeerJ 8, e9615. https://doi.org/10.7717/peerj.9615 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
70.LaJeunesse, T. C. et al. Systematic revision of Symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570–2580. https://doi.org/10.1016/j.cub.2018.07.008 (2018).Article 
PubMed 
CAS 

Google Scholar 
71.Trenfield, M. A. et al. Aluminium, gallium, and molybdenum toxicity to the tropical marine microalga Isochrysis galbana. Environ. Toxicol. Chem. 34, 1833–1840. https://doi.org/10.1002/etc.2996 (2015).Article 
PubMed 
CAS 

Google Scholar 
72.Hennige, S., Suggett, D., Warner, M., McDougall, K. & Smith, D. Photobiology of Symbiodinium revisited: Bio-physical and bio-optical signatures. Coral Reefs 28, 179–195. https://doi.org/10.1007/s00338-008-0444-x (2009).ADS 
Article 

Google Scholar 
73.Klueter, A., Trapani, J., Archer, F. I., McIlroy, S. E. & Coffroth, M. A. Comparative growth rates of cultured marine dinoflagellates in the genus Symbiodinium and the effects of temperature and light. PLoS ONE 12, e0187707. https://doi.org/10.1371/journal.pone.0187707 (2017).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
74.Rogers, J. E. & Davis, R. H. Application of a new micro-culturing technique to assess the effects of temperature and salinity on specific growth rates of six Symbiodinium isolates. Bull. Mar. Sci. 79, 113–126 (2006).
Google Scholar 
75.Sakami, T. Effects of temperature, irradiance, salinity and inorganic nitrogen concentration on coral zooxanthellae in culture. Fish. Res. 66, 1006–1013. https://doi.org/10.1046/j.1444-2906.2000.00162.x (2000).Article 
CAS 

Google Scholar 
76.Schreiber, U., Müller, J. F., Haugg, A. & Gademann, R. New type of dual-channel PAM chlorophyll fluorometer for highly sensitive water toxicity biotests. Photosynth. Res. 74, 317–330. https://doi.org/10.1023/A:1021276003145 (2002).Article 
PubMed 
CAS 

Google Scholar 
77.Karim, W., Nakaema, S. & Hidaka, M. Temperature effects on the growth rates and photosynthetic activities of Symbiodinium cells. J. Mar. Sci. Eng. 3, 368–381. https://doi.org/10.3390/jmse3020368 (2015).Article 

Google Scholar 
78.Mercurio, P., Mueller, J. F., Eaglesham, G., Flores, F. & Negri, A. P. Herbicide persistence in seawater simulation experiments. PLoS ONE 10, e0136391. https://doi.org/10.1371/journal.pone.0136391 (2015).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
79.Mercurio, P. Herbicide Persistence and Toxicity in the Tropical Marine Environment. PhD thesis, The University of Queensland (2016).80.Fisher, R., Ricardo, G. & Fox, D. jags NEC: A Bayesian No Effect Concentration (NEC) Package. https://github.com/AIMS/NEC-estimation. (2019).81.Fox, D. R. A Bayesian approach for determining the no effect concentration and hazardous concentration in ecotoxicology. Ecotoxicol. Environ. Saf. 73, 123–131. https://doi.org/10.1016/j.ecoenv.2009.09.012 (2010).Article 
PubMed 
CAS 

Google Scholar  More

Design of species assemblages with contrasting species and functional diversitiesWe designed eight assemblages of native and perennial plants differing in terms of species richness (three levels), functional diversity of the traits involved in plant–arthropod interactions (two levels) and species identity (two sets of species). We combined these first two factors to define four categories of plant assemblages for further study:

Low functional diversity and medium species richness (14 species), LFMS;

High functional diversity and low species richness (9 species), HFLS;

High functional diversity and medium species richness (14 species), HFMS;

High functional diversity and high species richness (29 species), HFHS.

For each of these four categories, we designed two assemblages with different species identities, as described in the Supplementary information, resulting in eight plant assemblages in total. Functional characterization was based on a rough classification of plant species into functional groups (Supplementary Table S1), according to the mains traits involved in plant–species interactions easily accessible from databases: (1) flower resources, i.e. floral and extrafloral nectar or pollen, (2) accessibility of the resource, depending on flower shape, (3) availability of the resource, i.e. the flowering period and (4) flowering height.We generated the seed mixtures from commercial seeds, using ecotypes of local origin wherever possible (northern part of the Parisian basin, France). All applicable international, national, and institutional guidelines relevant for the use of plants were followed.Experimental designThe experiment was conducted between 2013 and 2017 in a 6.5-ha field at Grignon, France (N 48.837, E 1.956), on a deep loamy clay soil, in which soil depth decreased along a gradient from north to south. The field was divided in three blocks running from north to south to take this soil heterogeneity into account.Each assemblage was sown on a 6 × 44 m2 strip, with three replicates (Supplementary Fig. S2), with each assemblage represented once per block. A control treatment, sown with the same crop species as the rest of the field, was also included in the experimental design, resulting in nine experimental treatments in total. From the autumn of 2013 to the 2017 harvest, a winter barley–maize–faba bean–oilseed rape rotation was grown in the field. Crops were managed without insecticide treatment, but with a mean of 0.75 fungicide and 1.25 herbicide treatments per year. The observations were made in faba bean in 2016 and in oilseed rape in 2017.Botanical assessments and functional characterization of the plant communitiesBotanical assessments were conducted in April and June, in 2016 and 2017. In each treatment, the vegetation was assessed in 3 × 15 m2 plots at a position representative of the whole strip, generally in the center of the strip, to prevent edge effects. The percentage of the ground covered by each sown or spontaneously growing plant species was estimated by eye, by the same observer in each case. We noted the phenological development stage of each species in each treatment on an 11-point scale, to ensure an accurate assessment of flowering phenology. In the control plots (sown with the crop species only), we took into account the resources provided by weed species.The functional characterization of plant communities was based on the plant traits assumed to be involved in plant–parasitoid interactions6 (Supplementary Table S3). These traits were related to (1) the provision of trophic resources (presence of floral and extrafloral nectar, qualitative estimation of floral nectar), (2) the temporal availability of the resource (date of flowering onset and duration of flowering), (3) flower attractiveness (flower or inflorescence diameter, color, UV reflectance pattern), (4) nectar accessibility (flower opening diameter, corolla height, nectar depth and nectar tube diameter) and (5) the provision of physical habitats (leaf distribution, vegetative and flowering height). We measured most of these traits, particularly all those relating to flower morphology, phenology and nectar provision (see more detailed methods in the Supplementary information). Only a few were retrieved from previous publications and online databases: flower color and UV reflectance pattern, leaf distribution, vegetative and flower height.These traits were used (1) to determine the accessibility of nectar to each parasitoid (see below) and (2) to calculate the functional diversity of the plant assemblages. We calculated functional dispersion as the abundance-weighted mean distance of individual species from the centroid of all species in the trait space50 and Rao quadratic entropy51. Since these two parameters were highly correlated (Supplementary information), we considered only functional dispersion a measurement of functional diversity. The traits associated with the provision, availability and accessibility of nectar resources were measured for all the dicotyledonous species sown and for all spontaneous species occurring in the plant communities and flowering during parasitoid activity. Overall, considering the traits we measured and those retrieved from databases, the trait matrix was complete for more than 95% of the species, accounting for 99.6% of total plant cover.Assessment of the levels of parasitism on five herbivorous pests of faba bean and oilseed rapeIn the adjacent crop, 5 and 20 m from the wildflower strip, we measured the level of parasitism in one herbivorous pest of faba bean (2016) and four herbivorous pests of oilseed rape (2017). We chose a distance close to the strip (5 m) to prevent confounding effects with the other adjacent strips, knowing that their effect is the strongest in the first few meters from the strip52. A further distance was also chosen (20 m) to determine whether the strips promoted biological control at field level, while taking into account the spatial constraint of the distance between strips (50 m between opposing strips).All the protocols are detailed in the Supplementary information. Parasitism was assessed in Bruchus rufimanus larvae after the visual examination of faba bean seeds after harvest. For oilseed rape, we collected and reared Ceutorhynchus pallidactylus and Psylliodes chrysocephala larvae until the adult stage or parasitoid emergence. In Brassicogethes aeneus larvae, parasitism was assessed by observing the eggs of Tersilochus heterocerus in the host larvae in oilseed rape flowers. Finally, after oilseed rape harvest, we retrieved cocoons of Dasineura brassicae from the soil, which we dissected, recording the number of cocoons occupied by parasitoids.Measurement of parasitoid traitsWe carried out morphological measurements on parasitoids (Supplementary Table S4), to determine their degree of access to the nectar provided by plants, as a function of the size of their mouthparts and head, which limit corolla penetration, using an approach analogous to that of van Rijn and Wäckers16. Parasitoid individuals, preserved in 70% ethanol, were obtained (1) from our rearing experiments (for Bruchus rufimanus, Psylliodes chrysocephala and Ceutorhynchus pallidactylus), (2) from the dissection of cocoons for Dasineura brassicae or (3) by field sampling in the flower strips with a sweep net in April 2017 to collect Tersilochus heterocerus, parasitoids of Brassicogethes aeneus identified with53. For each parasitoid species or morphospecies, we measured, on at least 10 individuals, proboscis length, proboscis width (at mid-length)54 and the maximum dorsal head width, including the eyes. Observations were carried out under a binocular microscope (Leica M80, 60 ×) linked to a video camera (Moticam 10, Motic), and measurements were made with ImageJ v1.50i digital image analysis software (National Institute of Health, Bethesda, http://imagej.nih.gov/ij).Nectar resources for parasitoidsWe estimated the amount of nectar provided by the plants by summing, for each flower strip corresponding to a treatment, the percent cover of plants providing available and accessible nectar, as assessed in vegetation surveys. Separate estimates were obtained for each parasitoid species or morphospecies.Plant species producing floral or extrafloral nectar were first selected on the basis of the observations detailed in the botanical assessment section. Nectar was considered to be available when it was produced during the period of parasitoid activity (Supplementary Table S4), by selecting species at the flowering stage or producing extrafloral nectar based on the phenological observations carried out during the botanical assessments. Nectar accessibility depended on morphological matching between plants and insects. Extrafloral nectar, which is not enclosed in a perianth, but produced on bracts or stipules, was considered to be accessible. We determined the accessibility of floral nectar with a mechanistic trait-based approach (Supplementary Information), by adapting the geometric model proposed by van Rijn and Wäckers16. A decision tree was built (Fig. 2) to take into account the three constraints limiting nectar accessibility: (1) ability of the insect to penetrate the flower, which is dependent on head size and flower opening, (2) ability to reach the nectar, which depends on proboscis length, nectar depth and corolla height, and (3) proboscis width and nectar tube diameter in the presence of nectar.Statistical analysesWe investigated the effects of the different plant assemblages on the rates of parasitism for the five herbivorous species, at 5 and 20 m from the flower strip, considered separately as individual response variables. We first tested the effect of each assemblage (nine treatments as factors) on parasitism rates. We used generalized linear mixed models in the lme package55, with a binomial error distribution. The models included plot (n = 9 flower strips × 3 replicates = 27), strip (1–3) or block (1–3) as a random effect. All models were run three times with each random effect variable, and the model giving the lowest AIC was retained. Strips consistently yielded the lowest AIC. This factor was therefore introduced as a random effect variable for all statistical analyses. The significance of the fixed effects was evaluated by type II analyses of deviance with Wald chi-squared tests from the Anova function from the car package56. If a significant effect (p value  More

1.Sih, A., Crowley, P., McPeek, M., Petranka, J. & Strohmeier, K. Predation, competition, and prey communities: A review of field experiments. Annu. Rev. Ecol. Syst. 16, 269–311 (1985).Article 

Google Scholar 
2.Werner, E. E. & Peacor, S. D. A review of trait-mediated indirect interactions in ecological communities. Ecology 84, 1083–1100 (2003).Article 

Google Scholar 
3.Abrams, P. A. The evolution of predator–prey interactions: theory and evidence. Annu. Rev. Ecol. Syst. 31, 79–105 (2000).Article 

Google Scholar 
4.Lima, S. L. & Bednekoff, P. A. Temporal variation in danger drives antipredator behavior: The predation risk allocation hypothesis. Am. Nat. 153, 649–659 (1999).PubMed 
Article 
PubMed Central 

Google Scholar 
5.Peacor, S. D. & Werner, E. E. Nonconsumptive effects of predators and trait-mediated indirect effects. Encycl. Life Sci. https://doi.org/10.1002/9780470015902.a0021216 (2008).Article 

Google Scholar 
6.Schmitz, O. J., Krivan, V. & Ovadia, O. Trophic cascades: The primacy of trait-mediated indirect interactions. Ecol. Lett. 7, 153–163 (2004).Article 

Google Scholar 
7.Mittelbach, G. G. Fish foraging and habitat choice: a theoretical perspective. In Handbook of Fish Biology and Fisheries, Volume 1 Fish Biology (eds Hart, P. J. B. & Reynolds, J. D.) 251–266 (Blackwell, 2002).Chapter 

Google Scholar 
8.Mittelbach, G. G. & McGill, B. J. Community Ecology (Oxford University Press, 2019) https://doi.org/10.1017/CBO9781107415324.004.Book 

Google Scholar 
9.Lima, S. L. Nonlethal effects in the ecology of predator-prey interactions. Bioscience 48, 25–34 (1998).Article 

Google Scholar 
10.Jeschke, J. M., Laforsch, C. & Tollrian, R. Animal prey defenses. In Encyclopedia of Ecology 189–194 (2008).11.Harvell, C. D. The ecology and evolution of inducible defenses. Q. Rev. Biol. 65, 323–340 (1990).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
12.Peckarsky, B. L. et al. Revisiting the classics: Considering nonconsumptive effects in textbook examples of predator prey interactions. Ecology 89, 2416–2425 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
13.Goricki, Š et al. Environmental DNA in subterranean biology: Range extension and taxonomic implications for Proteus. Sci. Rep. 7, 91–93 (2017).Article 
CAS 

Google Scholar 
14.Sket, B. Distribution of Proteus (Amphibia: Urodela: Proteidae) and its possible explanation. J. Biogeogr. 24, 263–280 (1997).Article 

Google Scholar 
15.Jugovic, J., Prevorčnik, S., Aljančič, G. & Sketa, B. The atyid shrimp (Crustacea: Decapoda: Atyidae) rostrum: Phylogeny versus adaptation, taxonomy versus trophic ecology. J. Nat. Hist. 44, 2509–2533 (2010).Article 

Google Scholar 
16.Aljančič, M. Prehrana močerila. Proteus 23, 224–225 (1961).
Google Scholar 
17.Parzefall, J., Durand, J. P. & Sket, B. Prouteus anguinus Laurenti, 1768—Grottenolm. In Handbuch der Reptilien und Amphibien Europas (ed. Böhme, W.) 59–76 (Aula-Verlag, 1999).
Google Scholar 
18.Trontelj, P., Blejec, A. & Fišer, C. Ecomorphological convergence of cave communities. Evolution 66, 3852–3865 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
19.Karaman, S. Podrod Orniphargus u Jugoslaviji I. & II. in O nekim amfipodima—izopodima Balkana i o njihovoj sistematici 119–159 (Srpska akademija nauka-Posebna izdanja CLXIII, 1950).20.Fišer, C., Trontelj, P. & Sket, B. Phylogenetic analysis of the Niphargus orcinus species-aggregate (Crustacea: Amphipoda: Niphargidae) with description of new taxa. J. Nat. Hist. 40, 2265–2315 (2006).Article 

Google Scholar 
21.Bollache, L. Ï., Kaldonski, N., Troussard, J. P., Lagrue, C. & Rigaud, T. Spines and behaviour as defences against fish predators in an invasive freshwater amphipod. Anim. Behav. 72, 627–633 (2006).Article 

Google Scholar 
22.Copilaş-Ciocianu, D., Borza, P. & Petrusek, A. Extensive variation in the morphological anti-predator defense mechanism of Gammarus roeselii Gervais, 1835 (Crustacea:Amphipoda). Freshw. Sci. 39, 47–55 (2020).Article 

Google Scholar 
23.Veech, J. A. A probabilistic model for analysing species co-occurrence. Glob. Ecol. Biogeogr. 22, 252–260 (2013).Article 

Google Scholar 
24.Borko, Š, Trontelj, P., Seehausen, O., Moškrič, A. & Fišer, C. A subterranean adaptive radiation of amphipods in Europe. Nat. Commun. 12, 1–12 (2021).Article 
CAS 

Google Scholar 
25.SubBioDB. Subterranean Fauna Database. Research group for speleobiology, Biotechnical faculty, University of Ljubljana. https://db.subbio.net/ (2021).26.Culver, D. C., Fong, D. W. & Jernigan, R. W. Species interactions in cave stream communities: Experimental results and microdistribution effects. Am. Midl. Nat. 126, 364 (1991).Article 

Google Scholar 
27.Lavoie, K. H., Helf, K. L. & Poulson, T. L. The biology and ecology of North American cave crickets. J. Cave Karst Stud. 69, 114–134 (2007).
Google Scholar 
28.Ercoli, F. et al. Differing trophic niches of three French stygobionts and their implications for conservation of endemic stygofauna. Aquat. Conserv. Mar. Freshw. Ecosyst. 29, 2193–2203 (2019).Article 

Google Scholar 
29.Pacioglu, O. et al. Ecophysiological and life-history adaptations of Gammarus balcanicus (Schäferna, 1922) in a sinking-cave stream from Western Carpathians (Romania). Zoology 139, 125754 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
30.Parimuchová, A., Dušátková, L. P., Kováč, Ľ & Macháčková, T. The food web in a subterranean ecosystem is driven by intraguild predation. Sci. Rep. https://doi.org/10.1038/s41598-021-84521-1 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
31.Premate, E. et al. Cave amphipods reveal co-variation between morphology and trophic niche in a low-productivity environment. Freshw. Biol. 66, 1876–1888 (2021).Article 

Google Scholar 
32.Sacco, M. et al. Elucidating stygofaunal trophic web interactions via isotopic ecology. PLoS ONE 14, 1–25 (2019).MathSciNet 
Article 
CAS 

Google Scholar 
33.Pohlman, J. W., Iliffe, T. M. & Cifuentes, L. A. A stable isotope study of organic cycling and the ecology of an anchialine cave ecosystem. Mar. Ecol. Prog. Ser. 155, 17–27 (1997).ADS 
CAS 
Article 

Google Scholar 
34.Graening, G. O. & Brown, A. V. Ecosystem dynamics and pollution effects in an Ozark cave stream. J. Am. Water Resour. Assoc. 39, 1497–1507 (2003).ADS 
CAS 
Article 

Google Scholar 
35.Manenti, R., Melotto, A., Guillaume, O., Ficetola, G. F. & Lunghi, E. Switching from mesopredator to apex predator: How do responses vary in amphibians adapted to cave living?. Behav. Ecol. Sociobiol. 74, 1–13 (2020).Article 

Google Scholar 
36.Uiblein, F. & Juberthie, C. Predation in caves: the effects of prey immobility and darkness on the foraging behaviour of two salamanders, Euproctus asper and Proteus anguinus. Behav. Process. 28, 33–40 (1992).CAS 
Article 

Google Scholar 
37.Prevorčnik, S., Verovnik, R., Zagmajster, M. & Sket, B. Biogeography and phylogenetic relations within the Dinaric subgenus Monolistra (Microlistra) (Crustacea: Isopoda: Sphaeromatidae), with a description of two new species. Zool. J. Linn. Soc. 159, 1–21 (2010).Article 

Google Scholar 
38.Mammola, S. Finding answers in the dark: Caves as models in ecology fifty years after Poulson and White. Ecography 42, 1331–1351 (2019).Article 

Google Scholar 
39.Culver, D. C. & Pipan, T. The Biology of Caves and Other Subterranean Habitats (Oxford University Press, 2009).
Google Scholar 
40.Kellner, K. F. & Swihart, R. K. Accounting for imperfect detection in ecology: A quantitative review. PLoS ONE 9, e111436 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
41.Mackenzie, D. I., Bailey, L. L. & Nichols, J. D. Investigating species co-occurrence patterns when species are detected imperfectly. J. Anim. Ecol. 73, 546–555 (2004).Article 

Google Scholar 
42.Vörös, J., Márton, O., Schmidt, B. R., Tünde Gál, J. & Jelić, D. Surveying Europe’s only cave-dwelling chordate species (Proteus anguinus) using environmental DNA. PLoS ONE 12, e0170945 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
43.Niemiller, M. L. et al. Evaluation of eDNA for groundwater invertebrate detection and monitoring: A case study with endangered Stygobromus (Amphipoda: Crangonyctidae). Conserv. Genet. Resour. 10, 247–257 (2018).Article 

Google Scholar 
44.Yonezawa, S., Nakano, T., Nakahama, N., Tomikawa, K. & Isagi, Y. Environmental DNA reveals cryptic diversity within the subterranean amphipod genus Pseudocrangonyx Akatsuka & Komai, 1922 (Amphipoda: Crangonyctoidea: Pseudocrangonyctidae) from Central Japan. J. Crustac. Biol. 40, 479–483 (2020).Article 

Google Scholar 
45.Arntzen, J. W. et al. Proteus anguinus. IUCN Red List Threat. Species (2009).46.Communities, T. C. of E. Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora. Official J. Eur. Communities 35, 8–51 (1992).
Google Scholar 
47.Vörös, J., Ursenbacher, S. & Jelić, D. Population genetic analyses using 10 new polymorphic microsatellite loci confirms genetic subdivision within the olm, Proteus anguinus. J. Hered. 110, 211–218 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
48.Gorički, Š & Trontelj, P. Structure and evolution of the mitochondrial control region and flanking sequences in the European cave salamander Proteus anguinus. Gene 378, 31–41 (2006).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
49.Gravel, D., Albouy, C. & Thuiller, W. The meaning of functional trait composition of food webs for ecosystem functioning. Philos. Trans. R. Soc. B Biol. Sci. 371, 20150268 (2016).Article 

Google Scholar 
50.Schmitz, O. Predator and prey functional traits: Understanding the adaptive machinery driving predator-prey interactions. F1000Research 6, 1767 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
51.R Development Core Team. A language and environment for statistical computing. (2020).52.R Studio Team. RStudio: Integrated Development for R. (2020).53.Wickham, H. & Bryan, J. readxl: Read Excel Files. R package version 1.3.1. (2019).54.Dragulescu, A. A. & Arendt, C. xlsx: Read, Write, Format Excel 2007 and Excel 97/2000/XP/2003 Files. R package version 0.6.1. (2018).55.Wickham, H., Francois, R., Henry, L. & Müller, K. dplyr: A Grammar of Data Manipulation. R package version 0.8.3. (2019).56.Wickham, H. ggplot2: Elegant Graphics for Data Analysis. (Springer-Verlag, 2016).57.Kong, D. Ipaper: Collection of personal practical R functions. (2021).58.Pebesma, E. Simple features for R: Standardized support for spatial vector data. R J. 10, 439–446 (2018).Article 

Google Scholar 
59.Hijmas, R. J. raster: Geographic Data Analysis and Modeling. (2020).60.Baddeley, A., Rubak, E. & Turner, R. Spatial Point Patterns: Methodology and Applications with R (Chapman and Hall/CRC Press, 2015).MATH 
Book 

Google Scholar 
61.Kassambara, A. rstatix: Pipe-Friendly Framework for Basic Statistical Tests. R package version 0.5.0. (2020).62.Griffith, D. M., Veech, J. A. & Marsh, C. J. Cooccur: Probabilistic species co-occurrence analysis in R. J. Stat. Softw. 69, 1–17 (2016).Article 

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

Google Scholar 
64.Meade, A. & Pagel, M. Bayes Traits V3. (2017).65.Griffin, R. H. btw: Run BayesTraitsV3 from R. (2018). More

1.McFall-Ngai, M. et al. Animals in a bacterial world, a new imperative for the life sciences. Proc. Natl Acad. Sci. USA 110, 3229–3236 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
2.Bang, C. et al. Metaorganisms in extreme environments: do microbes play a role in organismal adaptation? Zoology 127, 1–9 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
3.Mueller, U. G. & Sachs, J. L. Engineering microbiomes to improve plant and animal health. Trends Microbiol. 23, 606–617 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
4.Theis, K. R., Whittaker, D. J. & Rojas, C. A. A hologenomic approach to animal behavior. In Evolution in Action: Past, Present and Future 247–263 (Springer, 2020).5.Foster, K. R., Schluter, J., Coyte, K. Z. & Rakoff-Nahoum, S. The evolution of the host microbiome as an ecosystem on a leash. Nature 548, 43–51 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
6.Ziegler, M., Seneca, F. O., Yum, L. K., Palumbi, S. R. & Voolstra, C. R. Bacterial community dynamics are linked to patterns of coral heat tolerance. Nat. Commun. 8, 1–8 (2017).Article 
CAS 

Google Scholar 
7.Robbins, S. J. et al. A genomic view of the reef-building coral Porites lutea and its microbial symbionts. Nat. Microbiol. 4, 2090–2100 (2019).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
8.Berendsen, R. L., Pieterse, C. M. & Bakker, P. A. The rhizosphere microbiome and plant health. Trends Plant Sci. 17, 478–486 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Voolstra, C. R. & Ziegler, M. Adapting with microbial help: Microbiome flexibility facilitates rapid responses to environmental change. BioEssays 2, 2000004 (2020).Article 

Google Scholar 
10.Cárdenas, C. A., Bell, J. J., Davy, S. K., Hoggard, M. & Taylor, M. W. Influence of environmental variation on symbiotic bacterial communities of two temperate sponges. FEMS Microbiol. Ecol. 88, 516–527 (2014).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
11.Pantos, O., Bongaerts, P., Dennis, P. G., Tyson, G. W. & Hoegh-Guldberg, O. Habitat-specific environmental conditions primarily control the microbiomes of the coral Seriatopora hystrix. ISME J. 9, 1916–1927 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
12.Roder, C., Bayer, T., Aranda, M., Kruse, M. & Voolstra, C. R. Microbiome structure of the fungid coral Ctenactis echinata aligns with environmental differences. Mol. Ecol. 24, 3501–3511 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
13.Neave, M. J. et al. Differential specificity between closely related corals and abundant Endozoicomonas endosymbionts across global scales. ISME J. 11, 186–200 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
14.Carrier, T. J. & Reitzel, A. M. Convergent shifts in host-associated microbial communities across environmentally elicited phenotypes. Nat. Commun. 9, 1–9 (2018).CAS 
Article 

Google Scholar 
15.Pollock, F. J. et al. Coral-associated bacteria demonstrate phylosymbiosis and cophylogeny. Nat. Commun. 9, 1–13 (2018).CAS 
Article 

Google Scholar 
16.Glasl, B., Smith, C. E., Bourne, D. G. & Webster, N. S. Disentangling the effect of host-genotype and environment on the microbiome of the coral Acropora tenuis. PeerJ 7, e6377 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
17.Macke, E., Callens, M., De Meester, L. & Decaestecker, E. Host-genotype dependent gut microbiota drives zooplankton tolerance to toxic cyanobacteria. Nat. Commun. 8, 1–13 (2017).CAS 
Article 

Google Scholar 
18.Casey, J. M., Connolly, S. R. & Ainsworth, T. D. Coral transplantation triggers shift in microbiome and promotion of coral disease associated potential pathogens. Sci. Rep. 5, 11903 (2015).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Ziegler, M. et al. Coral bacterial community structure responds to environmental change in a host-specific manner. Nat. Commun. 10, 1–11 (2019).ADS 
CAS 
Article 

Google Scholar 
20.Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
21.Spor, A., Koren, O. & Ley, R. Unravelling the effects of the environment and host genotype on the gut microbiome. Nat. Rev. Microbiol. 9, 279–290 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
22.Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
23.Jaspers, C. et al. Resolving structure and function of metaorganisms through a holistic framework combining reductionist and integrative approaches. Zoology 113, 81–87 (2019).Article 

Google Scholar 
24.Blackall, L. L., Wilson, B. & van Oppen, M. J. H. Coral—the world’s most diverse symbiotic ecosystem. Mol. Ecol. 24, 5330–5347 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
25.Hernandez-Agreda, A., Gates, R. D. & Ainsworth, T. D. Defining the core microbiome in corals’ microbial soup. Trends Microbiol. 25, 125–140 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
26.LaJeunesse, T. C. et al. Systematic revision of Symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570–2580 (2018).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
27.Rohwer, F., Seguritan, V., Azam, F. & Knowlton, N. Diversity and distribution of coral-associated bacteria. Mar. Ecol. Prog. Ser. 243, 1–10 (2002).ADS 
Article 

Google Scholar 
28.Rosenberg, E., Koren, O., Reshef, L., Efrony, R. & Zilber-Rosenberg, I. The role of microorganisms in coral health, disease and evolution. Nat. Rev. Microbiol. 5, 355–362 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
29.Bourne, D. G., Morrow, K. M. & Webster, N. S. Insights into the coral microbiome: underpinning the health and resilience of reef ecosystems. Annu. Rev. Microbiol. 70, 317–340 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
30.Muscatine, L., Porter, J. W. & Kaplan, I. R. Resource partitioning by reef corals as determined from stable isotope composition. Mar. Biol. 100, 185–193 (1989).Article 

Google Scholar 
31.Rädecker, N., Pogoreutz, C., Voolstra, C. R., Wiedenmann, J. & Wild, C. Nitrogen cycling in corals: the key to understanding holobiont functioning? Trends Microbiol. 23, 490–497 (2015).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
32.Wegley, L., Edwards, R., Rodriguez‐Brito, B., Liu, H. & Rohwer, F. Metagenomic analysis of the microbial community associated with the coral Porites astreoides. Environ. Microbiol. 9, 2707–2719 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
33.Raina, J. B., Tapiolas, D., Willis, B. L. & Bourne, D. G. Coral-associated bacteria and their role in the biogeochemical cycling of sulfur. Appl. Environ. Microbiol. 75, 3492–3501 (2009).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
34.Lema, K. A., Willis, B. L. & Bourne, D. G. Corals form characteristic associations with symbiotic nitrogen-fixing bacteria. Appl. Environ. Microbiol. 78, 3136–3144 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.Krediet, C. J., Ritchie, K. B., Paul, V. J. & Teplitski, M. Coral-associated micro-organisms and their roles in promoting coral health and thwarting diseases. Proc. R. Soc. B 280, 20122328 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
36.Glasl, B., Herndl, G. J. & Frade, P. R. The microbiome of coral surface mucus has a key role in mediating holobiont health and survival upon disturbance. ISME J. 10, 2280–2292 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
37.Boilard, A. et al. Defining coral bleaching as a microbial dysbiosis within the coral holobiont. Microorganisms 8, 1682 (2020).CAS 
PubMed Central 
Article 

Google Scholar 
38.Apprill, A., Weber, L. G. & Santoro, A. E. Distinguishing between microbial habitats unravels ecological complexity in coral microbiomes. mSystems 1, e00143–16 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
39.Glasl, E.B., B. et al. Microbial indicators of environmental perturbations in coral reef ecosystems. Microbiome 7, 1–13 (2019).Article 

Google Scholar 
40.Damjanovic, K., Blackall, L. L., Peplow, L. M. & van Oppen, M. J. H. Assessment of bacterial community composition within and among Acropora loripes colonies in the wild and in captivity. Coral Reefs 39, 1245–1255 (2020).Article 

Google Scholar 
41.Dubé, E. B. et al. Ecology, biology and genetics of Millepora hydrocorals on coral reefs. In Invertebrates – Ecophysiology and Management (eds. Ray, S., Diarte-Plata, G. &  Escamilla-Montes, R.), (IntechOpen, 2019).42.Rodríguez, L. et al. Genetic relationships of the hydrocoral Millepora alcicornis and its symbionts within and between locations across the Atlantic. Coral Reefs 38, 255–268 (2019).ADS 
Article 

Google Scholar 
43.Lewis, J. B. Biology and ecology of the hydrocoral Millepora on coral reefs. Adv. Mar. Biol. 50, 1–55 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
44.Arrigoni, R. et al. An integrated morpho-molecular approach to delineate species boundaries of Millepora from the Red Sea. Coral Reefs 37, 967–984 (2018).ADS 
Article 

Google Scholar 
45.Boissin, E., Leung, J. K., Denis, V., Bourmaud, C. A. & Gravier-Bonnet, N. Morpho-molecular delineation of structurally important reef species, the fire corals, Millepora spp., at Réunion Island, Southwestern Indian Ocean. Hydrobiologia 847, 1237–1255 (2020).Article 

Google Scholar 
46.Dubé, C. E., Boissin, E., Maynard, J. A. & Planes, S. Fire coral clones demonstrate phenotypic plasticity among reef habitats. Mol. Ecol. 26, 3860–3869 (2017).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
47.Schwartzman, J. A. & Ruby, E. G. Stress as a normal cue in the symbiotic environment. Trends Microbiol. 24, 414–424 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
48.van Oppen, M. J. H. et al. Adaptation to reef habitats through selection on the coral animal and its associated microbiome. Mol. Ecol. 27, 2956–2971 (2018).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
49.Sunagawa, S. et al. Structure and function of the global ocean microbiome. Science 348, 6237 (2015).Article 
CAS 

Google Scholar 
50.Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
51.Hernandez-Agreda, A., Leggat, W., Bongaerts, P., Herrera, C. & Ainsworth, T. D. Rethinking the coral microbiome: simplicity exists within a diverse microbial biosphere. MBio 9, e00812–18 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
52.Bongaerts, P. et al. Adaptive divergence in a scleractinian coral: physiological adaptation of Seriatopora hystrix to shallow and deep reef habitats. BMC Evol. Biol. 11, 303 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
53.Albright, R., Benthuysen, J., Cantin, N., Caldeira, K. & Anthony, K. Coral reef metabolism and carbon chemistry dynamics of a coral reef flat. Geophys. Res. Lett. 42, 3980–3988 (2015).ADS 
CAS 
Article 

Google Scholar 
54.Pootakham, W. et al. Dynamics of coral‐associated microbiomes during a thermal bleaching event. MicrobiologyOpen 7, e00604 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
55.Neave, M. J., Apprill, A., Ferrier-Pagès, C. & Voolstra, C. R. Diversity and function of prevalent symbiotic marine bacteria in the genus Endozoicomonas. Appl. Microbiol. Biotechnol. 100, 8315–8324 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
56.Meyer, J. L., Paul, V. J. & Teplitski, M. Community shifts in the surface microbiomes of the coral Porites astreoides with unusual lesions. PLoS ONE 9, e100316 (2014).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
57.Bayer, T. et al. The microbiome of the Red Sea coral Stylophora pistillata is dominated by tissue-associated Endozoicomonas bacteria. Appl. Environ. Microbiol. 79, 4759–4762 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
58.Jessen, C. et al. In-situ effects of eutrophication and overfishing on physiology and bacterial diversity of the Red Sea coral Acropora hemprichii. PLoS ONE 8, e62091 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
59.Morrow, K. M. et al. Natural volcanic CO2 seeps reveal future trajectories for host–microbial associations in corals and sponges. ISME J. 9, 894–908 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
60.Dubé, C. E., Ky, C. L. & Planes, S. Microbiome of the black-lipped pearl oyster Pinctada margaritifera, a multi-tissue description with functional profiling. Front. Microbiol. 10, 1548 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
61.Neave, M. J., Michell, C. T., Apprill, A. & Voolstra, C. R. Endozoicomonas genomes reveal functional adaptation and plasticity in bacterial strains symbiotically associated with diverse marine hosts. Sci. Rep. 7, 40579 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
62.Tandon, K. et al. Comparative genomics: dominant coral-bacterium Endozoicomonas acroporae metabolizes dimethylsulfoniopropionate (DMSP). ISME J. 14, 1290–1303 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
63.Ngugi, D. K., Ziegler, M., Duarte, C. M. & Voolstra, C. R. Genomic blueprint of glycine betaine metabolism in coral metaorganisms and their contribution to reef nitrogen budgets. iScience 23, 101120 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
64.González, J. M., Kiene, R. P. & Moran, M. A. Transformation of sulfur compounds by an abundant lineage of marine bacteria in the α-subclass of the class Proteobacteria. Appl. Environ. Microbiol. 65, 3810–3819 (1999).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
65.Curson, A. R. J., Rogers, R., Todd, J. D., Brearley, C. A. & Johnston, A. W. B. Molecular genetic analysis of a dimethylsulfoniopropionate lyase that liberates the climate-changing gas dimethylsulfide in several marine α-proteobacteria and Rhodobacter spharoides. Environ. Microbiol. 10, 757–767 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
66.Reisch, C. R., Moran, M. A. & Whitman, W. B. Bacterial catabolism of dimethylsulfoniopropionate (DMSP). Front. Microbiol. 2, 172 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
67.Thompson, J. R., Rivera, H. E., Closek, C. J. & Medina, M. Microbes in the coral holobiont: partners through evolution, development, and ecological interactions. Front. Cell. Infect. Microbiol. 4, 176 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
68.Durante, M. K., Baums, I. B., Williams, D. E., Vohsen, S. & Kemp, D. W. What drives phenotypic divergence among coral clonemates of Acropora palmata? Mol. Ecol. 28, 3208–3224 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
69.Wagner, M. R. et al. Host genotype and age shape the leaf and root microbiomes of a wild perennial plant. Nat. Commun. 7, 1–5 (2016).ADS 
CAS 
Article 

Google Scholar 
70.Fuerst, J. & Sagulenko, E. Beyond the bacterium: planctomycetes challenge our concepts of microbial structure and function. Nat. Rev. Microbiol. 9, 403–413 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
71.Forquin-Gomez, M. P. et al. The family Brevibacteriaceae. In Prokaryotes Actinobacteria. 4th edn., (eds. Rosenberg E. et al.), 141–153 (Springer, 2014).72.Baker, B. J., Lazar, C. S., Teske, A. P. & Dick, G. J. Genomic resolution of linkages in carbon, nitrogen, and sulfur cycling among widespread estuary sediment bacteria. Microbiome 3, 14 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
73.Tian, R. M. et al. Genomic analysis reveals versatile heterotrophic capacity of a potentially symbiotic sulfur‐oxidizing bacterium in sponge. Environ. Microbiol. 16, 3548–3561 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
74.Gauthier, M. E., Watson, J. R. & Degnan, S. M. Draft genomes shed light on the dual bacterial symbiosis that dominates the microbiome of the coral reef sponge Amphimedon queenslandica. Front. Mar. Sci. 3, 196 (2016).Article 

Google Scholar 
75.Dyksma, S. et al. Ubiquitous Gammaproteo-bacteria dominate dark carbon fixation in coastal sediments. ISME J. 8, 1939–1953 (2016).Article 
CAS 

Google Scholar 
76.Raina, J. B., Dinsdale, E. A., Willis, B. L. & Bourne, D. G. Do the organic sulfur compounds DMSP and DMS drive coral microbial associations? Trends Microbiol. 18, 101–108 (2010).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
77.Morrow, K. M., Moss, A. G., Chadwick, N. E. & Liles, M. R. Bacterial associates of two Caribbean coral species reveal species-specific distribution and geographic variability. Appl. Environ. Microbiol. 78, 6438–6449 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
78.Sabdono, A. & Radjasa, O. K. Phylogenetic diversity of organophosphorous pesticide-degrading coral bacteria from mid-west coast of Indonesia. Biotechnology 7, 694–701 (2008).CAS 
Article 

Google Scholar 
79.Kannapiran, E. & Ravindran, J. Dynamics and diversity of phosphate mineralizing bacteria in the coral reefs of Gulf of Mannar. J. Basic Microbiol. 52, 91–98 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
80.Mahmoud, H. M. & Kalendar, A. A. Coral-associated actinobacteria: diversity, abundance, and biotechnological potentials. Front. Microbiol. 7, 204 (2016).PubMed 
PubMed Central 

Google Scholar 
81.Probandt, D. et al. Permeability shapes bacterial communities in sublittoral surface sediments. Environ. Microbiol. 19, 1584–1599 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
82.Doolittle, W. F. & Booth, A. It’s the song, not the singer: an exploration of holobiosis and evolutionary theory. Biol. Philos. 32, 5–24 (2017).Article 

Google Scholar 
83.Louca, S. et al. Function and functional redundancy in microbial systems. Nat. Ecol. Evol. 2, 936–943 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
84.Kelly, L. W. et al. Local genomic adaptation of coral reef-associated microbiomes to gradients of natural variability and anthropogenic stressors. Proc. Natl Acad. Sci. USA 111, 10227–10232 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
85.Peixoto, R. S., Rosado, P. M., Leite, D. C. D. A., Rosado, A. S. & Bourne, D. G. Beneficial microorganisms for corals (BMC): proposed mechanisms for coral health and resilience. Front. Microbiol. 8, 341 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
86.Peixoto, R. S. et al. Coral probiotics: premise, promise, prospects. Annu. Rev. Anim. Biosci. 9, 265–288 (2021).PubMed 
Article 
PubMed Central 

Google Scholar 
87.Voolstra, C. R. et al. Extending the natural adaptive capacity of coral holobionts. Nat Rev Earth Environ. 1–16 (2021). https://doi.org/10.1038/s43017-021-00214-3.88.Santoro, E. P. et al. Coral microbiome manipulation elicits metabolic and genetic restructuring to mitigate heat stress and evade mortality. Sci Adv. 7 (2021). https://doi.org/10.1126/sciadv.abg3088.89.Adam, T. C. et al. Landscape‐scale patterns of nutrient enrichment in a coral reef ecosystem: implications for coral to algae phase shifts. Ecol. Appl. 31, e2227 (2021).PubMed 
Article 
PubMed Central 

Google Scholar 
90.Buckling, A., Kassen, R., Bell, G. & Rainey, P. B. Disturbance and diversity in experimental microcosms. Nature 408, 961–964 (2000).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
91.Berga, M., Szekely, A. J. & Langenheder, S. Effects of disturbance intensity and frequency on bacterial community composition and function. PLoS ONE 7, e36959 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
92.Neulinger, S. C., Järnegren, J., Ludvigsen, M., Lochte, K. & Dullo, W. C. Phenotype-specific bacterial communities in the cold-water coral Lophelia pertusa (Scleractinia) and their implications for the coral’s nutrition, health, and distribution. Appl. Environ. Microbiol. 74, 7272–7285 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
93.Kanukollu, S. et al. Distinct compositions of free-living, particle-associated and benthic communities of the Roseobacter group in the North Sea. FEMS Microbiol. Ecol. 92, 1 (2016).Article 
CAS 

Google Scholar 
94.Santos, H. F. et al. Climate change affects key nitrogen-fixing bacterial populations on coral reefs. ISME J. 8, 2272–2279 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
95.Sorokin, D. Y., Tourova, T. P. & Muyzer, G. Citreicella thiooxidans gen. nov., sp. nov., a novel lithoheterotrophic sulfur-oxidizing bacterium from the Black Sea. Syst. Appl. Microbiol. 28, 679–687 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
96.Chen, Y. J. et al. Metabolic flexibility allows generalist bacteria to become dominant in a frequently disturbed ecosystem. bioRxiv (2020). Preprint at https://doi.org/10.1101/2020.02.12.94522097.Spring, S., Scheuner, C., Göker, M. & Klenk, H. P. A taxonomic framework for emerging groups of ecologically important marine gammaproteobacteria based on the reconstruction of evolutionary relationships using genome-scale data. Front. Microbiol. 9, 281 (2015).
Google Scholar 
98.Preston, G. M. Metropolitan microbes: type III secretion in multi-host symbionts. Cell Host Microbe 2, 291–294 (2007).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
99.Lutz, A., Raina, J.-B., Motti, C. A., Miller, D. J. & van Oppen, M. J. H. Host coenzyme Q redox state is an early biomarker of thermal stress in the coral Acropora millepora. PLoS ONE 10, e0139290 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
100.Smith, D. J., Suggett, D. J. & Baker, N. R. Is photoinhibition of zooxanthellae photosynthesis the primary cause of thermal bleaching in corals? Glob. Chang. Biol. 11, 1–11 (2005).ADS 
Article 

Google Scholar 
101.Gardner, S. G. et al. A multi-trait systems approach reveals a response cascade to bleaching in corals. BMC Biol. 15, 1–14 (2017).Article 
CAS 

Google Scholar 
102.Lema, K. A., Bourne, D. G. & Willis, B. L. Onset and establishment of diazotrophs and other bacterial associates in the early life history stages of the coral Acropora millepora. Mol. Ecol. 23, 4682–4695 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
103.Pogoreutz, C. et al. Nitrogen fixation aligns with nifH abundance and expression in two coral trophic functional groups. Front. Microbiol. 8, 1187 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
104.Marangoni, L. F. et al. Peroxynitrite generation and increased heterotrophic capacity are linked to the disruption of the coral–dinoflagellate symbiosis in a scleractinian and hydrocoral species. Microorganisms 7, 426 (2019).PubMed Central 
Article 
CAS 

Google Scholar 
105.Quigley, K. M., Alvarez Roa, C., Torda, G., Bourne, D. G. & Willis, B. L. Co‐dynamics of Symbiodiniaceae and bacterial populations during the first year of symbiosis with Acropora tenuis juveniles. MicrobiologyOpen 9, e959 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
106.Dubé, C. E., Mercière, A., Vermeij, M. J. A. & Planes, S. Population structure of the hydrocoral Millepora platyphylla in habitats experiencing different flow regimes in Moorea, French Polynesia. PLoS ONE 12, e0173513 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
107.Agostini, S. et al. Biological and chemical characteristics of the coral gastric cavity. Coral Reefs 31, 147–156 (2012).ADS 
Article 

Google Scholar 
108.Williams, A. D., Brown, B. E., Putchim, L. & Sweet, M. J. Age-related shifts in bacterial diversity in a reef coral. PLoS ONE 10, e0144902 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
109.Sweet, M. J., Brown, B. E., Dunne, R. P., Singleton, I. & Bulling, M. Evidence for rapid, tide-related shifts in the microbiome of the coral Coelastrea aspera. Coral Reefs 36, 815–828 (2017).ADS 
Article 

Google Scholar 
110.Dubé, C. E., Boissin, E., Mercière, A. & Planes, S. Parentage analyses identify local dispersal events and sibling aggregations in a natural population of Millepora hydrocorals, a free‐spawning marine invertebrate. Mol. Ecol. 29, 1508–1522 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
111.Abràmoff, M. D., Magalhães, P. J. & Ram, S. J. Image processing with ImageJ. Biophotonics Int. 11, 36–42 (2004).
Google Scholar 
112.Dubé, C. E., Planes, S., Zhou, Y., Berteaux-Lecellier, V. & Boissin, E. Genetic diversity and differentiation in reef-building Millepora species, as revealed by cross-species amplification of fifteen novel microsatellite loci. PeerJ 5, e2936 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
113.Arnaud-Haond, S. & Belkhir, K. GENCLONE: A computer pro- gram to analyze genotypic data, test for clonality and describe spatial clonal organization. Mol. Ecol. Notes 7, 15–17 (2007).CAS 
Article 

Google Scholar 
114.Peakall, R. & Smouse, P. E. GENALEX 6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295 (2006).Article 

Google Scholar 
115.Wickham, H. ggplot2: Elegant Graphics for Data Analysis. (Springer, 2016).116.R Development Core Team. R: A language and environment for statistical computing (ISBN 3-900051-07-0, http://www.R-project.org/ (R Foundation for Statistical Computing, 2020).117.Andersson, A. F. et al. Comparative analysis of human gut microbiota by barcoded pyrosequencing. PloS ONE 3, e2836 (2008).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
118.Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
119.Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
120.Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79, 5112–5120 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
121.Pedregosa, F. et al. Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).MathSciNet 
MATH 

Google Scholar 
122.Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 1–17 (2018).Article 

Google Scholar 
123.Yilmaz, P. et al. The SILVA and “All-species Living Tree Project (LTP)” taxonomic frameworks. Nucl. Acids Res. 42, D643–D648 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
124.Oksanen, J. et al. vegan: Community Ecology Package (2018).125.Weerdt, W. H. Transplantation experiments with Caribbean Millepora species (Hydrozoa, Coelenterata), including some ecological observations on growth forms. Bijdr. Dierkd. 51, 1–19 (1981).Article 

Google Scholar 
126.Cáceres, M. D. & Legendre, P. Associations between species and groups of sites: indices and statistical inference. Ecology 90, 3566–3574 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
127.Langille, M. G. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821 (2013).CAS 
PubMed 
PubMed Central 
Article 

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

Google Scholar  More

1.Schäferna, K. Amphipoda balcanica, spolu s poznámkami o jiných sladkovodních Amphipodech. Mem. Soc. R. Sci. Boheme Prague 12, 1–111 (1922).
Google Scholar 
2.Martynov, A. B. Zur Kenntnis der Amphipoden der Krim. Zool. Jahrb. 60, 573–606 (1931).
Google Scholar 
3.Karaman, S. L. Beitrag zur Kenntni s der Susswasseramphiopden. Bull. Soc. Scien Skoplje IX, 93–107 (1931).
Google Scholar 
4.Schellenberg, A. Schlussel und Diagnosen der dem Susswasser-Gammarus nahestehenden Einheiten ausschlisslich der Arten des Baikalsees und Australiens. Zool. Anz. 117, 267–280 (1937).
Google Scholar 
5.Barnard, J. L. & Karaman, S. G. Classificatory revisions in gammaridean amphipoda (Crustacea), Part 2. Proc. Biol. Soc. Wash. 95, 167–187 (1982).
Google Scholar 
6.Karaman, G. & Pinkster, S. Freshwater Gammarus species from Europe, North Africa and adjacent regions of Asia (CrustaceaAmphipoda): Part I: Gammarus pulex-group and related species. Bijdr Dierkd 47, 1–97 (1977).Article 

Google Scholar 
7.Karaman, G. & Pinkster, S. Freshwater Gammarus species from Europe, North Africa and adjacent regions of Asia (Crustacea Amphipoda): Part II: Gammarus roeseli-group and related species. Bijdr Dierkd 47, 165–196 (1977).Article 

Google Scholar 
8.Karaman, G. & Pinkster, S. Freshwater Gammarus species from Europe, North Africa and adjacent regions of Asia (Crustacea-Amphipoda): Part III: Gammarus balcanicus-group and related species. Bijdr Dierkd 57, 207–260 (1987).Article 

Google Scholar 
9.Jażdżewski, K. Remarks on Gammarus lacustris G.O. Sars, 1863, with description of Gammarus varsoviensis n. sp. Bijdr Dierkd 45, 71–86 (1975).Article 

Google Scholar 
10.Jażdżewski, K. & Konopacka, A. Gammarus leopoliensis nov. sp. (Crustacea, Amphipoda) from Eastern Carpathians. Bull. Zoölogisch Museum 11, 185–196 (1989).
Google Scholar 
11.Karaman, G. S. New species of the family Gammaridae from Ohrid Lake basin, Gammarus sketi, n. sp., with emphasis on the subterranean members of genus Gammarus Fabr. (Contribution to the knowledge of the Amphipoda 191). Glasnik Odjeljenja prirodnih nauka, Crnogorska akademija nauka i umjetnosti 7, 53–71 (1989).
Google Scholar 
12.Iannilli, V. & Ruffo, S. Apennine and Sardinian species of Gammarus, with the description of Gammarus elvirae n. sp. (Crustacea Amphipoda, Gammaridae). Boll. Acc. Gioenia Sci. Nat 35, 519–532 (2002).
Google Scholar 
13.Alther, R., Fišer, C. & Altermatt, F. Description of a widely distributed but overlooked amphipod species in the European Alps. Zool. J. Linn Soc.-Lond. https://doi.org/10.1111/zoj.12477 (2016).Article 

Google Scholar 
14.Grabowski, M., Wysocka, A. & Mamos, T. Molecular species delimitation methods provide new insight into taxonomy of the endemic gammarid species flock from the ancient Lake Ohrid. Zool. J. Linn. Soc.-Lond. 20, 1–14. https://doi.org/10.1093/zoolinnean/zlw025 (2017).Article 

Google Scholar 
15.Hupalo, K., Mamos, T., Wrzesinska, W. & Grabowski, M. First endemic freshwater Gammarus from Crete and its evolutionary history-an integrative taxonomy approach. PeerJ 6, e4457. https://doi.org/10.7717/peerj.4457 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
16.Rudolph, K., Coleman, C. O., Mamos, T. & Grabowski, M. Description and post-glacial demography of Gammarus jazdzewskii sp. Nov. (Crustacea: Amphipoda) from Central Europe. Syst. Biodivers. 16, 587–603. https://doi.org/10.1080/14772000.2018.1470118 (2018).Article 

Google Scholar 
17.Hou, Z., Sket, B. & Li, S. Phylogenetic analyses of Gammaridae crustacean reveal different diversification patterns among sister lineages in the Tethyan region. Cladistics https://doi.org/10.1111/cla.12055 (2014).Article 

Google Scholar 
18.Hou, Z. & Sket, B. A review of Gammaridae (Crustacea: Amphipoda): The family extent, its evolutionary history, and taxonomic redefinition of genera. Zool. J. Linn. Soc.-Lond. 176, 323–348. https://doi.org/10.1111/zoj.12318 (2016).Article 

Google Scholar 
19.Sket, B. & Hou, Z. Family Gammaridae (Crustacea: Amphipoda), mainly its Echinogammarus clade in SW Europe. Further elucidation of its phylogeny and taxonomy. ABS 61 (2018).20.Mamos, T., Wattier, R., Burzyński, A. & Grabowski, M. The legacy of a vanished sea: A high level of diversification within a European freshwater amphipod species complex driven by 15 My of Paratethys regression. Mol. Ecol. 25, 795–810. https://doi.org/10.1111/mec.13499 (2016).Article 
PubMed 

Google Scholar 
21.Mamos, T., Wattier, R., Majda, A., Sket, B. & Grabowski, M. Morphological vs. molecular delineation of taxa across montane regions in Europe: The case study of Gammarus balcanicus Schäferna, 1922 (Crustacea: Amphipoda). J. Zoolog. Syst. Evol. Res. 52, 237–248. https://doi.org/10.1111/jzs.12062 (2014).Article 

Google Scholar 
22.Grabowski, M., Mamos, T., Bącela-Spychalska, K., Rewicz, T. & Wattier, R. A. Neogene paleogeography provides context for understanding the origin and spatial distribution of cryptic diversity in a widespread Balkan freshwater amphipod. PeerJ 5, e3016. https://doi.org/10.7717/peerj.3016 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
23.Copilaş-Ciocianu, D., Zimţa, A.-A., Grabowski, M. & Petrusek, A. Survival in northern microrefugia in an endemic Carpathian gammarid (Crustacea: Amphipoda). Zool. Scr. 47, 357–372. https://doi.org/10.1111/zsc.12285 (2018).Article 

Google Scholar 
24.Copilaş-Ciocianu, D. & Petrusek, A. Phylogeography of a freshwater crustacean species complex reflects a long-gone archipelago. J. Biogeogr. 44, 421–432. https://doi.org/10.1111/jbi.12853 (2017).Article 

Google Scholar 
25.Wattier, R. et al. Continental-scale patterns of hyper-cryptic diversity within the freshwater model taxon Gammarus fossarum (Crustacea, Amphipoda). Sci. Rep. 10, 16536. https://doi.org/10.1038/s41598-020-73739-0 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
26.Meier, R. & Wheeler, Q. D. in The New Taxonomy (ed Q. D. Wheeler) 256 (CRC Press, 2008).27.Coleman, C. O. Taxonomy in times of the taxonomic impediment: Examples from the community of experts on amphipod crustaceans. J. Crustacean Biol. 35, 729–740. https://doi.org/10.1163/1937240x-00002381 (2015).Article 

Google Scholar 
28.Puillandre, N., Brouillet, S. & Achaz, G. ASAP: Assemble species by automatic partitioning. Mol. Ecol. Resour. 21, 609–620. https://doi.org/10.1111/1755-0998.13281 (2021).Article 
PubMed 

Google Scholar 
29.Kondracki, J. Karpaty. (WSiP, 1989).30.Mráz, P. & Ronikier, M. Biogeography of the Carpathians: Evolutionary and spatial facets of biodiversity. Biol. J. Linn. Soc. 119, 528–559. https://doi.org/10.1111/bij.12918 (2016).Article 

Google Scholar 
31.Balint, M. et al. Biodiversity Hotspots: Distribution and Protection of Conservation Priority Areas 189–205 (Springer, 2011).Book 

Google Scholar 
32.Schmitt, T. & Varga, Z. Extra-Mediterranean refugia: The rule and not the exception?. Front Zool. https://doi.org/10.1186/1742-9994-9-22 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
33.Ronikier, M. Biogeography of high-mountain plants in the Carpathians: An emerging phylogeographical perspective. Taxon 60, 373–389. https://doi.org/10.1002/tax.602008 (2011).Article 

Google Scholar 
34.Hájková, P. et al. Using multi-proxy palaeoecology to test a relict status of refugial populations of calcareous-fen species in the Western Carpathians. The Holocene 25, 702–715. https://doi.org/10.1177/0959683614566251 (2015).ADS 
Article 

Google Scholar 
35.Malicky, H. Chorological patterns and biome types of European Trichoptera and other freshwater insects. Arch. Hydrobiol. 96, 223–244 (1983).
Google Scholar 
36.Malicky, H. Arealdynamik und Biomgrundtypen am Beispiel der Köcherfliegen (Trichoptera). Entom Basi 22, 235–259 (2000).
Google Scholar 
37.Keresztes, L., Kolcsár, L.-P., Török, E. & Dénes, A.-L. in The Carpathians as speciation centres and barriers: From case studies to general patterns (eds L Keresztes & B. Markó) 168 (Cluj University Press, 2011).38.Bozáová, J., Čiamporová Zat’ovičová, Z., Čiampor, F., Mamos, T. & Grabowski, M. The tale of springs and streams: How different aquatic ecosystems impacted the mtDNA population structure of two riffle beetles in the Western Carpathians. PeerJ 8, e10039. https://doi.org/10.7717/peerj.10039 (2020).Article 

Google Scholar 
39.Copilas-Ciocianu, D., Rutová, T., Pařil, P. & Petrusek, A. Epigean gammarids survived millions of years of severe climatic fluctuations in high latitude refugia throughout the Western Carpathians. Mol. Phylogenet. Evol. 112, 218–229. https://doi.org/10.1016/j.ympev.2017.04.027 (2017).Article 
PubMed 

Google Scholar 
40.Grabowski, M. & Mamos, T. Contact Zones, Range Boundaries, and Vertical Distribution of Three Epigean Gammarids (Amphipoda) in the Sudeten and Carpathian Mountains (Poland). Crustaceana 84, 153–168. https://doi.org/10.1163/001121611×554328 (2011).Article 

Google Scholar 
41.Jażdżewski, K. Morfologia, taksonomia i występowanie w Polsce kiełży z rodzajów Gammarus Fabr. i Chaetogammarus Mart. (Crustacea, Amphipoda). 185 (Acta Universitatis Lodziensis, 1975).42.Jażdżewski, K. & Konopacka, A. Notes on the Gammaridean Amphipoda of the Dniester River Basin and Eastern Carpathians. Crustaceana. Supplement, 72–89 (1988).43.Zieliński, D. Life History of Gammarus balcanicus Schäferna, 1922 from the Bieszczady Mountains (Eastern Carpathians, Poland). Crustaceana 68(1), 61–72 (1995).Article 

Google Scholar 
44.Zieliński, D. Life Cycle and Altitude Range of Gammarus leopoliensis Jażdżewski & Konopacka, 1989 (Amphipoda) in South-Eastern Poland. Crustaceana 71 (1998).45.Konopacka A., Jażdżewski K., Jędryczkowski W. In Monografie Bieszczadzkie, vol. VII (ed. Pawłowski, J.) (2000).46.Straškraba, M. Předběžná zpráva o rozšíření rodu Gammarus v ČSR. Věstník Československé Společnosti Zoologické 17, 212–227 (1953).
Google Scholar 
47.Straškraba, M. Beitrag zur Kenntnis der Amphipodenfauna Karpatenrusslands (USSR). Věstník Československé Společnosti Zoologické 21, 256–272 (1957).
Google Scholar 
48.Micherdziński, W. Kiełże rodzaju Gammarus Fabricius (Amphipoda) w wodach Polski. Acta Zoologica Cracoviensia 4, 527–637 (1959).
Google Scholar 
49.Straškraba, M. Amphipoden der Tschechoslovakei nach den Sammlungen von. Prof. Hrabě. I. Věstník Československé Společnosti Zoologické 26, 117–145 (1962).50.Provan, J. & Bennett, K. D. Phylogeographic insights into cryptic glacial refugia. Trends Ecol. Evol. 23, 564–571. https://doi.org/10.1016/j.tree.2008.06.010 (2008).Article 
PubMed 

Google Scholar 
51.Tzedakis, P. C., Emerson, B. C. & Hewitt, G. M. Cryptic or mystic? Glacial tree refugia in northern Europe. Trends Ecol. Evol. 28, 696–704. https://doi.org/10.1016/j.tree.2013.09.001 (2013).CAS 
Article 
PubMed 

Google Scholar 
52.Harl, J., Duda, M., Kruckenhauser, L., Sattmann, H. & Haring, E. In Search of Glacial Refuges of the Land Snail Orcula dolium (Pulmonata, Orculidae): An Integrative Approach Using DNA Sequence and Fossil Data. PLoS ONE 9, e96012. https://doi.org/10.1371/journal.pone.0096012 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
53.Juřičková, L., Horáčková, J. & Ložek, V. Direct evidence of central European forest refugia during the last glacial period based on mollusc fossils. Quaternary Res. 82, 222–228. https://doi.org/10.1016/j.yqres.2014.01.015 (2014).ADS 
Article 

Google Scholar 
54.Väinölä, R. et al. Global diversity of amphipods (Amphipoda; Crustacea) in freshwater. Hydrobiologia 595, 241–255. https://doi.org/10.1007/s10750-007-9020-6 (2008).Article 

Google Scholar 
55.Zasadni, J. & Kłapyta, P. The tatra mountains during the last glacial maximum. J. Maps 10, 440–456. https://doi.org/10.1080/17445647.2014.885854 (2014).Article 

Google Scholar 
56.Sworobowicz, L., Mamos, T., Grabowski, M. & Wysocka, A. Lasting through the ice age: The role of the proglacial refugia in the maintenance of genetic diversity, population growth, and high dispersal rate in a widespread freshwater crustacean. Freshwater Biol. 65, 1028–1046. https://doi.org/10.1111/fwb.13487 (2020).CAS 
Article 

Google Scholar 
57.Ratnasingham, S. & Hebert, P. Bold: The barcode of life data system. Mol. Ecol. Not. 7, 355–364. https://doi.org/10.1111/j.1471-8286.2007.01678.x (2007).CAS 
Article 

Google Scholar 
58.Weigand, H. et al. DNA barcode reference libraries for the monitoring of aquatic biota in Europe: Gap-analysis and recommendations for future work. STOTEN 678, 499–524. https://doi.org/10.1016/j.scitotenv.2019.04.247 (2019).ADS 
CAS 
Article 

Google Scholar 
59.Katouzian, A.-R. et al. Drastic underestimation of amphipod biodiversity in the endangered Irano-Anatolian and Caucasus biodiversity hotspots. Sci. Rep. 6, 22507. https://doi.org/10.1038/srep22507 (2016).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
60.Bickford, D. et al. Cryptic species as a window on diversity and conservation. Trends Ecol. Evol. 22, 148–155. https://doi.org/10.1016/j.tree.2006.11.004 (2007).Article 
PubMed 

Google Scholar 
61.Delić, T., Trontelj, P., Rendoš, M. & Fišer, C. The importance of naming cryptic species and the conservation of endemic subterranean amphipods. Sci. Rep. 7, 3391. https://doi.org/10.1038/s41598-017-02938-z (2017).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
62.Maddison, W. P. Gene trees in species trees. Syst. Biol. 46, 523–536. https://doi.org/10.2307/2413694 (1997).Article 

Google Scholar 
63.Nosil, P. Speciation with gene flow could be common. Mol. Ecol. 17, 2103–2106. https://doi.org/10.1111/j.1365-294X.2008.03715.x (2008).Article 
PubMed 

Google Scholar 
64.Berner, D. & Salzburger, W. The genomics of organismal diversification illuminated by adaptive radiations. Trends Genet. 31, 491–499. https://doi.org/10.1016/j.tig.2015.07.002 (2015).CAS 
Article 
PubMed 

Google Scholar 
65.Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. .Biol 215, 403–410. https://doi.org/10.1006/jmbi.1990.9999 (1990).CAS 
Article 
PubMed 

Google Scholar 
66.Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. https://doi.org/10.1093/molbev/mst010 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
67.Xia, X. DAMBE5: A comprehensive software package for data analysis. Mol. Biol. Evol. 30, 1720–1728. https://doi.org/10.1093/molbev/mst064 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
68.Xia, X., Xie, Z., Salemi, M., Chen, L. & Wang, Y. An index of substitution saturation and its application. Mol. Phylogenet. Evol. 26, 1–7. https://doi.org/10.1016/S1055-7903(02)00326-3 (2003).CAS 
Article 
PubMed 

Google Scholar 
69.Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549. https://doi.org/10.1093/molbev/msy096 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
70.Saitou, N. & Nei, M. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425. https://doi.org/10.1093/oxfordjournals.molbev.a040454 (1987).CAS 
Article 
PubMed 

Google Scholar 
71.Kimura, M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. https://doi.org/10.1007/bf01731581 (1980).Article 
PubMed 

Google Scholar 
72.Felsenstein, J. Confidence limits on phylogenies: An approach using the bootstrap. Evol. Int. J. Org. Evol. 39, 783–791 (1985).Article 

Google Scholar 
73.Ratnasingham, S. & Hebert, P. D. A DNA-based registry for all animal species: The barcode index number (BIN) system. PLoS ONE 8, e66213. https://doi.org/10.1371/journal.pone.0066213 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
74.Puillandre, N., Lambert, A., Brouillet, S. & Achaz, G. ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol. Ecol. 21, 1864–1877. https://doi.org/10.1111/j.1365-294X.2011.05239.x (2012).CAS 
Article 
PubMed 

Google Scholar 
75.Bouckaert, R. et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. Plos Comput. Biol. 15, e1006650. https://doi.org/10.1371/journal.pcbi.1006650 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
76.Bouckaert, R. R. & Drummond, A. J. bModelTest: Bayesian phylogenetic site model averaging and model comparison. BMC Evol. Biol. 17, 42. https://doi.org/10.1186/s12862-017-0890-6 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
77.Rambaut, A., Drummond, A. J., Xie, D., Baele, G. & Suchard, M. A. Posterior summarization in bayesian phylogenetics using tracer 1.7. Syst. Biol. 67, 901–904. https://doi.org/10.1093/sysbio/syy032 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
78.Pons, J. et al. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. Syst. Biol. 55, 595–609. https://doi.org/10.1080/10635150600852011 (2006).Article 
PubMed 

Google Scholar 
79.Ezard, T., Fujisawa, T. & Barraclough, T. G. SPLITS: SPecies’ LImits by Threshold Statistics. R package version 1.0–18/r45 Available from: http://R-Forge.R-project.org/projects/splits/ (2009).80.Team, R. C. R: A language and environment for statistical computing, https://www.R-project.org/ (2020).81.Zhang, J., Kapli, P., Pavlidis, P. & Stamatakis, A. A general species delimitation method with applications to phylogenetic placements. Bioinformatics 29, 2869–2876. https://doi.org/10.1093/bioinformatics/btt499 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
82.Kapli, P. et al. Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo. Bioinformatics 33, 1630–1638. https://doi.org/10.1093/bioinformatics/btx025 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
83.Jones, G. Algorithmic improvements to species delimitation and phylogeny estimation under the multispecies coalescent. J. Math. Biol. 74, 447–467. https://doi.org/10.1007/s00285-016-1034-0 (2017).MathSciNet 
Article 
PubMed 
MATH 

Google Scholar 
84.Jones, G., Aydin, Z. & Oxelman, B. DISSECT: An assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent. Bioinformatics 31, 991–998. https://doi.org/10.1093/bioinformatics/btu770 (2015).CAS 
Article 
PubMed 

Google Scholar 
85.Rabosky, D. L. Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees. PLoS ONE 9, e89543. https://doi.org/10.1371/journal.pone.0089543 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
86.Rabosky, D. L. et al. BAMMtools: An R package for the analysis of evolutionary dynamics on phylogenetic trees. Methods Ecol. Evol. 5, 701–707. https://doi.org/10.1111/2041-210X.12199 (2014).Article 

Google Scholar 
87.Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 34, 3299–3302. https://doi.org/10.1093/molbev/msx248 (2017).CAS 
Article 
PubMed 

Google Scholar 
88.Heled, J. & Drummond, A. Bayesian inference of population size history from multiple loci. BMC Evol. Biol. 8, 289 (2008).Article 

Google Scholar 
89.Leigh, J. W. & Bryant, D. POPART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116. https://doi.org/10.1111/2041-210X.12410 (2015).Article 

Google Scholar 
90.Flot, J. F., Couloux, A. & Tillier, S. Haplowebs as a graphical tool for delimiting species: A revival of Doyle’s “field for recombination” approach and its application to the coral genus Pocillopora in Clipperton. BMC Evol. Biol. 10, 1. https://doi.org/10.1186/1471-2148-10-372 (2010).Article 

Google Scholar 
91.Stephens, M., Smith, N. J. & Donnelly, P. A new statistical method for haplotype reconstruction from population data. Am. J. Hum. Genet. 68, 978–989. https://doi.org/10.1086/319501 (2001).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
92.Spöri, Y. & Flot, J.-F. HaplowebMaker and CoMa: Two web tools to delimit species using haplowebs and conspecificity matrices. Methods Ecol. Evol. 11, 1434–1438. https://doi.org/10.1111/2041-210X.13454 (2020).Article 

Google Scholar  More

1.Lal, R. Soil carbon sequestration impacts on global climate change and food security. Science (80-). 304, 1623–1627 (2004).ADS 
CAS 
Article 

Google Scholar 
2.Janzen, H. H. Carbon cycling in earth systems—A soil science perspective. Agric. Ecosyst. Environ. 104, 399–417 (2004).CAS 
Article 

Google Scholar 
3.Leinweber, P., Jandl, G., Baum, C., Eckhardt, K. U. & Kandeler, E. Stability and composition of soil organic matter control respiration and soil enzyme activities. Soil Biol. Biochem. 40, 1496–1505 (2008).CAS 
Article 

Google Scholar 
4.Kosugi, Y. et al. Spatial and temporal variation in soil respiration in a Southeast Asian tropical rainforest. Agric. For. Meteorol. 147, 35–47 (2007).ADS 
Article 

Google Scholar 
5.Epron, D. Separating autotrophic and heterotrophic components of soil respiration: Lessons learned from trenching and related root-exclusion experiments. Soil Carbon Dyn. Integr. Methodol. https://doi.org/10.1017/CBO9780511711794.009 (2010).Article 

Google Scholar 
6.Musselman, R. C. & Fox, D. G. A review of the role of temperate forests in the global CO2 balance. J. Air Waste Manag. Assoc. 41, 798–807 (1991).CAS 
Article 

Google Scholar 
7.Lal, R. Carbon sequestration. Philos. Trans. R. Soc. B Biol. Sci. 363, 815–830 (2008).CAS 
Article 

Google Scholar 
8.Lal, R. Forest soils and carbon sequestration. For. Ecol. Manag. 220, 242–258 (2005).Article 

Google Scholar 
9.Kaiser, K., Guggenberger, G. & Zech, W. Sorption of DOM and DOM fractions to forest soils. Geoderma 74, 281–303 (1996).ADS 
Article 

Google Scholar 
10.Hassink, J. A model of the physical protection of organic matter in soils the capacity of soils to preserve organic C and N by their association with clay and silt particles. Plant Soil 191, 77–87 (1997).CAS 
Article 

Google Scholar 
11.Saidy, A. R. et al. Effects of clay mineralogy and hydrous iron oxides on labile organic carbon stabilisation. Geoderma 173–174, 104–110 (2012).ADS 
Article 
CAS 

Google Scholar 
12.Mueller, K. E. et al. Tree species effects on coupled cycles of carbon, nitrogen, and acidity in mineral soils at a common garden experiment. Biogeochemistry 111, 601–614 (2012).CAS 
Article 

Google Scholar 
13.Mulder, J., De Wit, H. A., Boonen, H. W. J. & Bakken, L. R. Increased levels of aluminium in forest soils: Effects on the stores of soil organic carbon. Water Air. Soil Pollut. 130, 989–994 (2001).ADS 
Article 

Google Scholar 
14.Gruba, P. & Socha, J. Exploring the effects of dominant forest tree species, soil texture, altitude, and pHH2O on soil carbon stocks using generalized additive models. For. Ecol. Manag. 447, 105–114 (2019).Article 

Google Scholar 
15.Chrzan, A. Zawartość wybranych metali ciężkich w glebie i faunie glebowej. Proc. ECOpole. 7, 23–26 (2013).
Google Scholar 
16.Ampoorter, E., Van Nevel, L., De Vos, B., Hermy, M. & Verheyen, K. Assessing the effects of initial soil characteristics, machine mass and traffic intensity on forest soil compaction. For. Ecol. Manag. 260, 1664–1676 (2010).Article 

Google Scholar 
17.Meriano, M., Eyles, N. & Howard, K. W. F. Hydrogeological impacts of road salt from Canada’s busiest highway on a Lake Ontario watershed (Frenchman’s Bay) and lagoon, City of Pickering. J. Contam. Hydrol. 107, 66–81 (2009).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
18.Barbier, L., Suaire, R., Durickovic, I., Laurent, J. & Simonnot, M. O. Is a road stormwater retention pond able to intercept deicing salt?. Water Air. Soil Pollut. 229, 1–12 (2018).CAS 
Article 

Google Scholar 
19.Willmert, H. M., Osso, J. D., Twiss, M. R. & Langen, T. A. Winter road management effects on roadside soil and vegetation along a mountain pass in the Adirondack Park, New York, USA. J. Environ. Manag. 225, 215–223 (2018).CAS 
Article 

Google Scholar 
20.General Directorate for National Roads and Motorways. Detailed technical specifications. Winter maintenance of the road network administered by the General Directorate for National Roads and Motorways, Lublin Branch in the years: 2012÷2016 (in Polish). (2012).21.Durickovic, I. NaCl material for winter maintenance and its environmental effect. Salt Earth https://doi.org/10.5772/intechopen.86907 (2020).Article 

Google Scholar 
22.General Directorate for National Roads and Motorways. We’ll recap the winter of 2019/2020 and explain what road maintenance is all about (in Polish). (2020). https://www.archiwum.gddkia.gov.pl/pl/a/37500/Podsumujemy-zime-20192020-i-wyjasnimy-o-co-chodzi-w-utrzymaniu-drog. Accessed on October 20, 2021.23.General Directorate for National Roads and Motorways. Ready for all weather. The 2020/2021 winter season has begun (in Polish). (2020). https://www.archiwum.gddkia.gov.pl/pl/a/40259/Gotowi-na-kazda-pogode-Zaczal-sie-sezon-zimowy-20202021. Accessed on October 20, 2021.24.General Directorate for National Roads and Motorways. Average annual daily traffic (AADT) at measuring points in 2015 on state roads (in Polish). (2015). https://www.archiwum.gddkia.gov.pl/pl/2551/GPR-2015. Accessed on October 20, 2021.25.QGIS Association. QGIS Geographic Information System. (2021). http://www.qgis.org Accessed on October 20, 2021.26.Woś, A. The Climate of Poland (in Polish) (Polish Scientific Publishers PWN, 1999).
Google Scholar 
27.Polish State Forests. Nature and forest conditions of Suchedniów Forest Inspectorate (in Polish). A report. (2011). https://suchedniow.radom.lasy.gov.pl/documents/11058/18775352/warunki+przyrodniczo-lesne.pdf Accessed on October 20, 2021.28.Hopkins, D. W. Carbon mineralization. In Soil Sampling and Methods of Analysis (eds. Carter, M. R. & Gregorich, E. G.) (CRC Press, 2008).29.Buurman, P., van Lagen, B. & Velthorst, E. J. Manual for Soil and Water Analysis (Backhuys Publishers, 1996).
Google Scholar 
30.R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ Accessed on October 20, 2021..31.Navrátil, T. et al. Soil mercury distribution in adjacent coniferous and deciduous stands highly impacted by acid rain in the Ore Mountains, Czech Republic. Appl. Geochem. 75, 63–75 (2016).Article 
CAS 

Google Scholar 
32.Gruba, P., Pietrzykowski, M. & Pasichnyk, D. Tree species affects the concentration of total mercury (Hg) in forest soils: Evidence from a forest soil inventory in Poland. Sci. Total Environ. 647, 141–148 (2019).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
33.Obrist, D. et al. Mercury distribution across 14 U.S. Forests. Part I: Spatial patterns of concentrations in biomass, litter, and soils. Environ. Sci. Technol. 45, 3974–3981 (2011).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
34.Kupka, D., Kania, M., Pietrzykowski, M., Łukasik, A. & Gruba, P. Multiple factors influence the accumulation of heavy metals (Cu, Pb, Ni, Zn) in forest soils in the vicinity of roadways. Water Air Soil Pollut. 232, 1–13 (2021).Article 
CAS 

Google Scholar 
35.Borchers, J. G. & Perry, A. D. The influence of soil texture and aggregation on carbon and nitrogen dynamics in southwest Oregon forests and clearcuts. Can. J. For. Res. 22, 298–305 (1992).CAS 
Article 

Google Scholar 
36.Chantigny, M. H., Angers, D. A., Kaiser, K. & Kalbitz, K. Extraction and characterization of dissolved organic matter. In Soil Sampling and Methods of Analysis (eds. Carter, M. & Gregorich, E. G.) (CRC Press, 2008).37.Zehetner, F., Rosenfellner, U., Mentler, A. & Gerzabek, M. H. Distribution of road salt residues, heavy metals and polycyclic aromatic hydrocarbons across a highway-forest interface. Water Air Soil Pollut. 198, 125–132 (2009).ADS 
CAS 
Article 

Google Scholar 
38.Grigalaviciene, I., Rutkoviene, V. & Marozas, V. The accumulation of heavy metals Pb, Cu and Cd at roadside forest soil. Polish J. Environ. Stud. 14, 109–115 (2005).CAS 

Google Scholar 
39.Bäckström, M., Bäckman, L., Folkeson, L., Karlsson, S. & Lind, B. Mobilisation of heavy metals by deicing salts in a roadside environment. Water Res. 38, 720–732 (2004).PubMed 
Article 
CAS 

Google Scholar 
40.Singh, D. V., Bhat, J. I. A., Bhat, R. A., Dervash, M. A. & Ganei, S. A. Vehicular stress a cause for heavy metal accumulation and change in physico-chemical characteristics of road side soils in Pahalgam. Environ. Monit. Assess. 190, 1–10 (2018).Article 
CAS 

Google Scholar 
41.Doelman, P. & Haanstra, L. Short-term and long-term effects of cadmium, chromium, copper, nickel, lead and zinc on soil microbial respiration in relation to abiotic soil factors. Plant Soil 79, 317–327 (1984).CAS 
Article 

Google Scholar 
42.Hattori, H. Influence of heavy metals on soil mcrobial activities. Soil Sci. Plant Nutr. 38, 93–100 (1992).CAS 
Article 

Google Scholar 
43.Gülser, F. & Erdoǧan, E. The effects of heavy metal pollution on enzyme activities and basal soil respiration of roadside soils. Environ. Monit. Assess. 145, 127–133 (2008).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
44.Lofgren, S. The chemical effects of deicing salt on soil and stream water of five catchments in southeast Sweden. Water Air Soil Pollut. 130, 863–868 (2001).ADS 
Article 

Google Scholar 
45.Mason, C. F., Norton, S. A., Fernandez, I. J. & Katz, L. E. Deconstruction of the chemical effects of road salt on stream water chemistry. J. Environ. Qual. 28, 82–91 (1999).CAS 
Article 

Google Scholar 
46.Robinson, H. K., Hasenmueller, E. A. & Chambers, L. G. Soil as a reservoir for road salt retention leading to its gradual release to groundwater. Appl. Geochem. 83, 72–85 (2017).CAS 
Article 

Google Scholar 
47.Rhodes, A. L. & Guswa, A. J. Storage and release of road-salt contamination from a calcareous lake-basin fen, western Massachusetts, USA. Sci. Total Environ. 545–546, 525–545 (2016).ADS 
PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
48.Cunningham, M. A., Snyder, E., Yonkin, D., Ross, M. & Elsen, T. Accumulation of deicing salts in soils in an urban environment. Urban Ecosyst. 11, 17–31 (2008).Article 

Google Scholar 
49.Berggren, D., Mulder, J. & Westerhof, R. Prolonged leaching of mineral forest soils with dilute HCl solutions: The solubility of Al and soil organic matter. Eur. J. Soil Sci. 49, 305–316 (1998).CAS 
Article 

Google Scholar 
50.Prenzel, J. & Schulte-Bisping, H. Some chemical parameter relations in a population of German forest soils. Geoderma 64, 309–326 (1995).ADS 
CAS 
Article 

Google Scholar 
51.Reuss, J. O., Walthall, P. M., Roswall, E. C. & Hopper, R. W. E. Aluminum solubility, calcium-aluminum exchange, and pH in acid forest soils. Soil Sci. Soc. Am. J. 54, 374–380 (1990).ADS 
CAS 
Article 

Google Scholar 
52.Hobbie, S. E. et al. Tree species effects on soil organic matter dynamics: The role of soil cation composition. Ecosystems 10, 999–1018 (2007).CAS 
Article 

Google Scholar 
53.Scheel, T., Jansen, B., Van Wijk, A. J., Verstraten, J. M. & Kalbitz, K. Stabilization of dissolved organic matter by aluminium: A toxic effect or stabilization through precipitation?. Eur. J. Soil Sci. 59, 1122–1132 (2008).CAS 
Article 

Google Scholar 
54.Lützow, M. V. et al. Stabilization of organic matter in temperate soils: Mechanisms and their relevance under different soil conditions—A review. Eur. J. Soil Sci. 57, 426–445 (2006).Article 
CAS 

Google Scholar 
55.Gruba, P. & Socha, J. Effect of parent material on soil acidity and carbon content in soils under silver fir (Abies alba Mill.) stands in Poland. CATENA 140, 90–95 (2016).CAS 
Article 

Google Scholar 
56.Gruba, P. & Mulder, J. Tree species affect cation exchange capacity (CEC) and cation binding properties of organic matter in acid forest soils. Sci. Total Environ. 511, 655–662 (2015).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
57.Reich, P. B. et al. Linking litter calcium, earthworms and soil properties: A common garden test with 14 tree species. Ecol. Lett. 8, 811–818 (2005).Article 

Google Scholar  More

1.Jarvis, E. D. et al. Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346, 1320–1331 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
2.Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
3.Claramunt, S. & Cracraft, J. A new time tree reveals Earth history’s imprint on the evolution of modern birds. Sci. Adv. 1, e1501005 (2015).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
4.Jenni, L. & Winkler, R. Moult and Ageing of European Passerines. (Bloomsbury Publishing, 2020).5.Ginn, H. B. & Melville, D. S. Moult in Birds (BTO guide). (British Trust for Ornithology, 1983).6.Stresemann, E. & Stresemann, V. Die Mauser der Vögel. (Friedländer, 1966).7.Jenni, L. & Winkler, R. The Biology of Moult in Birds. (Bloomsbury Publishing, 2020).8.Kiat, Y., Izhaki, I. & Sapir, N. The effects of long-distance migration on the evolution of moult strategies in Western-Palearctic passerines. Biol. Rev. 94, 700–720 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
9.Kiat, Y. et al. Sequential molt in a feathered dinosaur and implications for early paravian ecology and locomotion. Curr. Biol. 30, 3633–3638 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
10.Pyle, P. Identification guide to North American birds: A Compendium of Information on Identifying, Ageing, and Sexing ‘Near-Passerines’ and Passerines in the Hand. (Slate Creek Press, 1997).11.Berlow, E. L., Brose, U. & Martinez, N. D. The, “Goldilocks factor” in food webs. Proc. Natl. Acad. Sci. 105, 4079–4080 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
12.Dale, J., Dey, C. J., Delhey, K., Kempenaers, B. & Valcu, M. The effects of life history and sexual selection on male and female plumage colouration. Nature 529, 367–370 (2015).ADS 
Article 
CAS 

Google Scholar 
13.Kleiber, M. Body size and metabolism. Hilgardia 6, 315–353 (1932).CAS 
Article 

Google Scholar 
14.McKinnon, L. et al. Lower predation risk for migratory birds at high latitudes. Science 327, 326–327 (2010).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
15.Meiri, S., Dayan, T. & Simberloff, D. Biogeographical patterns in the Western Palearctic: the fasting-endurance hypothesis and the status of Murphy’s rule. J. Biogeogr. 32, 369–375 (2005).Article 

Google Scholar 
16.Millar, J. S. & Hickling, G. J. Fasting endurance and the evolution of mammalian body size. Funct. Ecol. 4, 5–12 (1990).Article 

Google Scholar 
17.Peters, R. H. & Peters, R. H. The Ecological Implications of Body Size. vol. 2 (Cambridge University Press, 1986).18.Pérez-Granados, C. et al. Time available for moulting shapes inter- and intra-specific variability in post-juvenile moult extent in wheatears (genus Oenanthe). J. Ornithol. 162, 255–264 (2020).Article 

Google Scholar 
19.Hemborg, C., Sanz, J. & Lundberg, A. Effects of latitude on the trade-off between reproduction and moult: a long-term study with Pied Flycatcher. Oecologia 129, 206–212 (2001).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
20.de la Hera, I., Díaz, J. a., Pérez-Tris, J. & Tellería, J. L. A comparative study of migratory behaviour and body mass as determinants of moult duration in passerines. J. Avian Biol. 40, 461–465 (2009).21.Kiat, Y. & Sapir, N. Age-dependent modulation of songbird summer feather moult by temporal and functional constraints. Am. Nat. 189, 184–195 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
22.Møller, A. P. The allometry of number of feathers in birds changes seasonally. Avian Res. 6, 1–5 (2015).Article 

Google Scholar 
23.Rohwer, S., Ricklefs, R. E., Rohwer, V. G. & Copple, M. M. Allometry of the duration of flight feather molt in birds. PLoS Biol. 7, 1246 (2009).Article 
CAS 

Google Scholar 
24.Rohwer, V. G. & Rohwer, S. How do birds adjust the time required to replace their flight feathers?. Auk 130, 699–707 (2013).Article 

Google Scholar 
25.Barta, Z. et al. Annual routines of non-migratory birds: optimal moult strategies. Oikos 112, 580–593 (2006).Article 

Google Scholar 
26.Barta, Z. et al. Optimal moult strategies in migratory birds. Philos. Trans. R. Soc. London B Biol. Sci. 363, 211–229 (2008).27.Wunderle, J. M. Age-specific foraging proficiency in birds. Curr. Ornithol. 8, 273–324 (1991).
Google Scholar 
28.Marchetti, K. & Price, T. Differences in the foraging of juvenile and adult birds: the importance of developmental constraints. Biol. Rev. 64, 51–70 (1989).Article 

Google Scholar 
29.Delhey, K. et al. Partial or complete? The evolution of post-juvenile moult strategies in passerine birds. J. Anim. Ecol. 89, 2896–2908 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
30.Kiat, Y. & Izhaki, I. Why renew fresh feathers? Advantages and conditions for the evolution of complete post-juvenile moult. J. Avian Biol. 47, 47–56 (2016).Article 

Google Scholar 
31.Kiat, Y. & Sapir, N. Life-history trade-offs result in evolutionary optimization of feather quality. Biol. J. Linn. Soc. 125, 613–624 (2018).
Google Scholar 
32.Callan, L. M., La Sorte, F. A., Martin, T. E. & Rohwer, V. G. Higher nest predation favors rapid fledging at the cost of plumage quality in nestling birds. Am. Nat. 193, 717–724 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
33.Del Hoyo, J., Elliott, A., Sargatal, J., Christie, D. A. & de Juana, E. Handbook of the Birds of the World Alive (Lynx Edicions, 2019).
Google Scholar 
34.Dunning Jr, J. B. CRC Handbook of Avian Body Masses. (CRC Press, 2007).35.Billerman, S. M., Keeney, B. K., Rodewald, P. G. & Schulenberg, T. S. Birds of the World. (Cornell Laboratory of Ornithology, 2020).36.Bird species distribution maps of the world. BirdLife International (2019).37.Jetz, W. et al. Global distribution and conservation of evolutionary distinctness in birds. Curr. Biol. 24, 919–930 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
38.Rubolini, D., Liker, A., Garamszegi, L. Z., Møller, A. P. & Saino, N. Using the BirdTree.org website to obtain robust phylogenies for avian comparative studies: a primer. Curr. Zool. 61, 959–965 (2015).39.Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).Article 

Google Scholar 
40.Akaike, H. Factor analysis and AIC. Psychometrika 52, 317–332 (1987).MathSciNet 
MATH 
Article 

Google Scholar 
41.Rabosky, D. L. No substitute for real data: a cautionary note on the use of phylogenies from birth–death polytomy resolvers for downstream comparative analyses. Evolution 69, 3207–3216 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
42.Thomas, G. H. An avian explosion. Nature 526, 516–517 (2015).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
43.Prum, R. O. et al. A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA sequencing. Nature 526, 569–573 (2015).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
44.Ives, A. R. & Garland, T. Jr. Phylogenetic logistic regression for binary dependent variables. Syst. Biol. 59, 9–26 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
45.Tung Ho, L. si & Ané, C. A linear-time algorithm for Gaussian and non-Gaussian trait evolution models. Syst. Biol. 63, 397–408 (2014).46.Felsenstein, J. A comparative method for both discrete and continuous characters using the threshold model. Am. Nat. 179, 145–156 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
47.Cody, M. L. A general theory of clutch size. Evolution 174–184 (1966).48.Newton, I. The Migration Ecology of Birds. (Academic Press, 2010).49.Newton, I. Speciation and Biogeography of Birds. (Academic Press, 2003).50.Terrill, R. S., Seeholzer, G. F. & Wolfe, J. D. Evolution of breeding plumages in birds: a multiple-step pathway to seasonal dichromatism in New World warblers (Aves: Parulidae). Ecol. Evol. 10, 9223–9239 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
51.Fogden, M. P. L. The seasonality and population dynamics of equatorial forest birds in Sarawak. Ibis 114, 307–343 (1972).Article 

Google Scholar 
52.Kiat, Y., Davaasuren, B., Erdenechimeg, T., Troupin, D. & Sapir, N. Large-scale longitudinal climate gradient across the Palearctic region affects passerine feather moult extent. Ecography 44, 124–133 (2020).Article 

Google Scholar 
53.Kiat, Y., Vortman, Y. & Sapir, N. Feather moult and bird appearance are correlated with global warming over the last 200 years. Nat. Commun. 10, 1–7 (2019).ADS 
CAS 
Article 

Google Scholar 
54.Bojarinova, J. G., Lehikoinen, E. & Eeva, T. Dependence of postjuvenile moult on hatching date, condition and sex in the Great Tit. J. Avian Biol. 30, 437–446 (1999).Article 

Google Scholar 
55.Ryzhanovsky, V. N. Subspecies-specific features of molt in the Common Chiffchaff (Phylloscopus collybita) from Europe and Western Siberia. Russ. J. Ecol. 48, 268–274 (2017).Article 

Google Scholar 
56.Slavenko, A. et al. Global patterns of body size evolution in squamate reptiles are not driven by climate. Glob. Ecol. Biogeogr. 28, 471–483 (2019).Article 

Google Scholar 
57.Graham, C. H., Storch, D. & Machac, A. Phylogenetic scale in ecology and evolution. Glob. Ecol. Biogeogr. 27, 175–187 (2018).Article 

Google Scholar 
58.Hone, D. W. E., Dyke, G. J., Haden, M. & Benton, M. J. Body size evolution in Mesozoic birds. J. Evol. Biol. 21, 618–624 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
59.Xu, X. et al. An integrative approach to understanding bird origins. Science 346, 1253293 (2014).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
60.Berv, J. S. & Field, D. J. Genomic signature of an avian Lilliput effect across the K-Pg extinction. Syst. Biol. 67, 1–13 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
61.Dececchi, T. A. & Larsson, H. C. E. Body and limb size dissociation at the origin of birds: uncoupling allometric constraints across a macroevolutionary transition. Evolution 67, 2741–2752 (2013).PubMed 
Article 
PubMed Central 

Google Scholar 
62.Puttick, M. N., Thomas, G. H. & Benton, M. J. High rates of evolution preceded the origin of birds. Evolution 68, 1497–1510 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
63.Vizcaíno, S. F. & Fariña, R. A. On the flight capabilities and distribution of the giant Miocene bird Argentavis magnificens (Teratornithidae). Lethaia 32, 271–278 (1999).Article 

Google Scholar 
64.McNeill Alexander, R. All-time giants: the largest animals and their problems. Palaeontology 41, 1231–1246 (1998).
Google Scholar  More

1.Zaiss, M. M. & Harris, N. L. Interactions between the intestinal microbiome and helminth parasites. Parasite Immunol. 38, 5–11 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
2.Cortés, A., Peachey, L. E., Jenkins, T. P., Scotti, R. & Cantacessi, C. Helminths and microbes within the vertebrate gut—not all studies are created equal. Parasitology 146, 1371–1378 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
3.Sender, R., Fuchs, S. & Milo, R. Revised estimates for the number of human and bacteria cells in the body. PLoS Biol. 14, e1002533 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
4.Claesson, M. J. et al. Gut microbiota composition correlates with diet and health in the elderly. Nature 488, 178–184 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
5.Clemente, J. C., Ursell, L. K., Parfrey, L. W. & Knight, R. The impact of the gut microbiota on human health: An integrative view. Cell 148, 1258–1270 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
6.McFall-Ngai, M. et al. Animals in a bacterial world, a new imperative for the life sciences. Proc. Nat. Acad. Sci. 110, 3229–3236 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
7.Hooper, L. V., Littman, D. R. & Macpherson, A. J. Interactions between the microbiota and the immune system. Science 336, 1268–1273 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
8.Tremaroli, V. & Bäckhed, F. Functional interactions between the gut microbiota and host metabolism. Nature 489, 242–249 (2012).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Brown, E. M., Sadarangani, M. & Finlay, B. B. The role of the immune system in governing host-microbe interactions in the intestine. Nat. Immunol. 14, 660–667 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
10.Kim, S., Covington, A. & Pamer, E. G. The intestinal microbiota: Antibiotics, colonization resistance, and enteric pathogens. Immunol. Rev. 279, 90–105 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
11.Ducarmon, Q. R. et al. Gut microbiota and colonization resistance against bacterial enteric infection. Microbiol. Mol. Biol. Rev. 83, e00007-19 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
12.Sorbara, M. T. & Pamer, E. G. Interbacterial mechanisms of colonization resistance and the strategies pathogens use to overcome them. Mucosal Immunol. 12, 1–9 (2019).CAS 
PubMed 
Article 

Google Scholar 
13.Jourdan, P. M., Lamberton, P. H. L., Fenwick, A. & Addiss, D. G. Soil-transmitted helminth infections. Lancet 391, 252–265 (2018).PubMed 
Article 

Google Scholar 
14.Wammes, L. J., Mpairwe, H., Elliott, A. M. & Yazdanbakhsh, M. Helminth therapy or elimination: Epidemiological, immunological, and clinical considerations. Lancet Infect. Dis. 14, 1150–1162 (2014).CAS 
PubMed 
Article 

Google Scholar 
15.Jenkins, T. P. et al. Experimental infection with the hookworm, Necator americanus, is associated with stable gut microbial diversity in human volunteers with relapsing multiple sclerosis. BMC Biol. 19, 1–17 (2021).Article 
CAS 

Google Scholar 
16.Holm, J. B. et al. Chronic Trichuris muris infection decreases diversity of the intestinal microbiota and concomitantly increases the abundance of Lactobacilli. PLoS ONE 10, e0125495 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
17.Ducarmon, Q. R. et al. Dynamics of the bacterial gut microbiota during controlled human infection with Necator americanus larvae. Gut Microbes 12, 1840764 (2020).PubMed Central 
Article 
CAS 
PubMed 

Google Scholar 
18.Broadhurst, M. J. et al. Therapeutic helminth infection of macaques with idiopathic chronic diarrhea alters the inflammatory signature and mucosal microbiota of the colon. PLoS Pathog. 8, e1003000 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Kreisinger, J., Bastien, G., Hauffe, H. C., Marchesi, J. & Perkins, S. E. Interactions between multiple helminths and the gut microbiota in wild rodents. Philos. Trans. R. Soc. Lond. B Biol. Sci. 370, 20140295 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
20.Filyk, H. A. & Osborne, L. C. The multibiome: The intestinal ecosystem’s influence on immune homeostasis, health, and disease. EBioMedicine 13, 46–54 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
21.Cantacessi, C. et al. Impact of experimental hookworm infection on the human gut microbiota. J. Infect. Dis. 210, 1431–1434 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
22.Li, R. W. et al. Alterations in the porcine colon microbiota induced by the gastrointestinal nematode Trichuris suis. Infect. Immun. 80, 2150–2157 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
23.Reynolds, L. A., Brett Finlay, B. & Maizels, R. M. Cohabitation in the intestine: Interactions among helminth parasites, bacterial microbiota, and host immunity. J. Immunol. 195, 4059–4066 (2015).CAS 
PubMed 
Article 

Google Scholar 
24.Lee, S. C. et al. Helminth colonization is associated with increased diversity of the gut microbiota. PLoS Negl. Trop. Dis. 8, e2880 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
25.Rosa, B. A. et al. Differential human gut microbiome assemblages during soil-transmitted helminth infections in Indonesia and Liberia. Microbiome 6, 33 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
26.Newbold, L. K. et al. Helminth burden and ecological factors associated with alterations in wild host gastrointestinal microbiota. ISME J. 11, 663–675 (2017).PubMed 
Article 

Google Scholar 
27.Baxter, N. T. et al. Intra- and interindividual variations mask interspecies variation in the microbiota of sympatric Peromyscus populations. Appl. Environ. Microbiol. 81, 396–404 (2015).ADS 
PubMed 
Article 
CAS 

Google Scholar 
28.Cooper, P. et al. Patent human infections with the whipworm, Trichuris trichiura, are not associated with alterations in the faecal microbiota. PLoS ONE 8, e76573 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
29.Rapin, A. & Harris, N. L. Helminth-bacterial interactions: Cause and consequence. Trends Immunol. 39, 724–733 (2018).CAS 
PubMed 
Article 

Google Scholar 
30.Cowlishaw, G. & Dunbar, R. I. Primate Conservation Biology (University of Chicago Press, 2000).Book 

Google Scholar 
31.Estrada, A. et al. Impending extinction crisis of the world’s primates: Why primates matter. Sci. Adv. 3, e1600946 (2017).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
32.Barelli, C. et al. The gut microbiota communities of wild arboreal and ground-feeding tropical primates are affected differently by habitat disturbance. mSystems 5, 3 (2020).Article 

Google Scholar 
33.Barelli, C. et al. Habitat fragmentation is associated to gut microbiota diversity of an endangered primate: Implications for conservation. Sci. Rep. 5, 14862 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
34.Barelli, C. et al. Altitude and human disturbance are associated with helminth diversity in an endangered primate, Procolobus gordonorum. PLoS ONE 14, e0225142 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.Barelli, C. et al. Loss of protozoan and metazoan intestinal symbiont biodiversity in wild primates living in unprotected forests. Sci. Rep. 10, 1–12 (2020).Article 
CAS 

Google Scholar 
36.Aivelo, T. & Norberg, A. Parasite-microbiota interactions potentially affect intestinal communities in wild mammals. J. Anim. Ecol. 87, 438–447 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
37.Vlčková, K. et al. Relationships between gastrointestinal parasite infections and the fecal microbiome in free-ranging western lowland gorillas. Front. Microbiol. 9, 1202 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
38.Mann, A. E. et al. Biodiversity of protists and nematodes in the wild nonhuman primate gut. ISME J. 14, 609–622 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
39.de Winter, I. I. et al. Effects of seasonality and previous logging on faecal helminth-microbiota associations in wild lemurs. Sci. Rep. 10, 16818 (2020).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
40.Ghai, R. R. et al. Hidden population structure and cross-species transmission of whipworms (Trichuris sp.) in humans and non-human primates in Uganda. PLoS Negl. Trop. Dis. 8, e3256 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
41.Nutman, T. B. Human infection with Strongyloides stercoralis and other related Strongyloides species. Parasitology 144, 263–273 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
42.Stephenson, L. S., Holland, C. V. & Cooper, E. S. The public health significance of Trichuris trichiura. Parasitology 121, S73–S95 (2000).PubMed 
Article 
PubMed Central 

Google Scholar 
43.Viney, M. E. The biology of Strongyloides spp. WormBook https://doi.org/10.1895/wormbook.1.141.2 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
44.Renelies-Hamilton, J. et al. Exploring interactions between Blastocystis sp., Strongyloides spp. and the gut microbiomes of wild chimpanzees in Senegal. Infect. Genet. Evol. 74, 104010 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
45.Afrin, T. et al. Sequential changes in the host gut microbiota during infection with the intestinal parasitic nematode. Front. Cell Infect. Microbiol. 9, 217 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
46.Rubel, M. A. et al. Lifestyle and the presence of helminths is associated with gut microbiome composition in Cameroonians. Genome Biol. 21, 122 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
47.Jenkins, T. P. et al. Author Correction: A comprehensive analysis of the faecal microbiome and metabolome of Strongyloides stercoralis infected volunteers from a non-endemic area. Sci. Rep. 9, 8571 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
48.Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
49.van der Zande, H. J. P., Zawistowska-Deniziak, A. & Guigas, B. Immune regulation of metabolic homeostasis by helminths and their molecules. Trends Parasitol. 35, 795–808 (2019).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
50.Maeda, Y. & Takeda, K. Host–microbiota interactions in rheumatoid arthritis. Exp. Mol. Med. 51, 1–6 (2019).CAS 
PubMed 
Article 

Google Scholar 
51.Biddle, A., Stewart, L., Blanchard, J. & Leschine, S. Untangling the genetic basis of fibrolytic specialization by Lachnospiraceae and Ruminococcaceae in diverse gut communities. Diversity 5, 627–640 (2013).Article 

Google Scholar 
52.Brulc, J. M. et al. Gene-centric metagenomics of the fiber-adherent bovine rumen microbiome reveals forage specific glycoside hydrolases. Proc. Natl. Acad. Sci. USA 106, 1948–1953 (2009).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
53.Hale, V. L. et al. Diet versus phylogeny: A comparison of gut microbiota in captive Colobine monkey species. Microb. Ecol. 75, 515–527 (2018).PubMed 
Article 

Google Scholar 
54.Trosvik, P. et al. Multilevel social structure and diet shape the gut microbiota of the gelada monkey, the only grazing primate. Microbiome 6, 84 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
55.Liu, B. et al. Western diet feeding influences gut microbiota profiles in apoE knockout mice. Lipids Health Dis. 17, 159 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
56.Bhute, S. S. et al. Gut microbial diversity assessment of Indian Type-2-diabetics reveals alterations in Eubacteria, Archaea, and Eukaryotes. Front. Microbiol. 8, 214 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
57.Wang, Y. et al. Phocea, Pseudoflavonifractor and Lactobacillus intestinalis: Three potential biomarkers of gut microbiota that affect progression and complications of obesity-induced Type 2 diabetes Mellitus. Diabetes Metab. Syndr. Obes. 13, 835–850 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
58.Yarahmadi, M. et al. The anti-giardial effectiveness of fungal and commercial chitosan against Giardia intestinalis cysts in vitro. J. Parasit. Dis. 40, 75–80 (2016).PubMed 
Article 

Google Scholar 
59.Dinleyici, E. C. et al. Clinical efficacy of Saccharomyces boulardii or metronidazole in symptomatic children with Blastocystis hominis infection. Parasitol. Res. 108, 541–545 (2011).PubMed 
Article 

Google Scholar 
60.Lepczyńska, M. & Dzika, E. The influence of probiotic bacteria and human gut microorganisms causing opportunistic infections on ST3. Gut Pathog. 11, 6 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
61.Huseyin, C. E., O’Toole, P. W., Cotter, P. D. & Scanlan, P. D. Forgotten fungi—the gut mycobiome in human health and disease. FEMS Microbiol. Rev. 41, 479–511 (2017).CAS 
PubMed 
Article 

Google Scholar 
62.Mittermeier, R. A., Myers, N., Gill, P. C. & Mittermeier, C. G. Hotspots: Earth’s Richest and Most Endangered Terrestrial Ecoregions (CEMEX, 2000).
Google Scholar 
63.Platts, P. J. et al. Delimiting tropical mountain ecoregions for conservation. Environ. Conserv. 38, 312–324 (2011).Article 

Google Scholar 
64.Ruiz-Lopez, M. J. et al. A novel landscape genetic approach demonstrates the effects of human disturbance on the Udzungwa red colobus monkey (Procolobus gordonorum). Heredity 116, 167–176 (2016).CAS 
PubMed 
Article 

Google Scholar 
65.Cavada, N., Tenan, S., Barelli, C. & Rovero, F. Effects of anthropogenic disturbance on primate density at the landscape scale. Conserv. Biol. 33, 873–882 (2019).PubMed 
Article 

Google Scholar 
66.Laurance, W. F. et al. Averting biodiversity collapse in tropical forest protected areas. Nature 489, 290–294 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
67.Rovero, F. et al. Primates decline rapidly in unprotected forests: Evidence from a monitoring program with data constraints. PLoS ONE 10, e0118330 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
68.International Union for the Conservation of Nature and Natural Resources (IUCN). 2021. IUCN red list of threatened species version 2020-2. International Union for the Conservation of Nature and Natural Resources http://www.iucnredlist.org. (Accessed 21 Apr 2021).69.Modrý, D., Pafčo, B., Petrželková, K. J. & Hasegawa, H. Parasites of Apes: An Atlas of Coproscopic Diagnostics (2018).70.Gillespie, T. R. Noninvasive assessment of gastrointestinal parasite infections in free-ranging primates. Int. J. Primatol. 27, 1129–1143 (2006).Article 

Google Scholar 
71.Hasegawa, H. Methods of collection and identification of minute nematodes from the feces of primates, with special application to coevolutionary study of pinworms. In Primate Parasite Ecology: The Dynamics of Host-parasite Relationships (eds Huffman, M. A. & Chapman, C. A.) 29–46 (Cambridge University Press, 2009).
Google Scholar 
72.Mallott, E. K., Malhi, R. S. & Garber, P. A. High-throughput sequencing of fecal DNA to identify insects consumed by wild Weddell’s saddleback tamarins (Saguinus weddelli, Cebidae, Primates) in Bolivia. Am. J. Phys. Anthropol. 156, 474–481 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
73.Mallott, E. K., Garber, P. A. & Malhi, R. S. Integrating feeding behavior, ecological data, and DNA barcoding to identify developmental differences in invertebrate foraging strategies in wild white-faced capuchins (Cebus capucinus). Am. J. Phys. Anthropol. 162, 241–254 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
74.Albanese, D., Fontana, P., De Filippo, C., Cavalieri, D. & Donati, C. MICCA: A complete and accurate software for taxonomic profiling of metagenomic data. Sci. Rep. 5, 9743 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
75.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021) https://www.R-project.org.76.Lenth, R., Singmann, H., Love, J., Buerkner, P. & Herve, M. Emmeans: Estimated marginal means, aka least-squares means. R package version, Vol. 1, 3 (2018) https://CRAN.R-project.org/package=emmeans. More