More stories

  • in

    Detailed morphological structure and phylogenetic relationships of Degeeriella punctifer (Phthiraptera: Philopteridae), a parasite of the bearded vulture Gypaetus barbatus (Accipitriformes: Accipitridae)

    Durden, L. Lice (Phthiraptera). In Medical and Veterinary Entomology 3rd edn (eds Mullen, G. & Durden, L.) 79–106 (Academic Press, 2019).Chapter 

    Google Scholar 
    Stork, N. E. & Lyal, C. H. C. Extinction or ‘co-extinction’ rates?. Nature 366, 307. https://doi.org/10.1038/366307a0 (1993).Article 
    ADS 

    Google Scholar 
    Koh, L. P. et al. Species coextinctions and the biodiversity crisis. Science 305, 1632–1634. https://doi.org/10.1126/science.1101101 (2004).Article 
    ADS 
    CAS 

    Google Scholar 
    Gerlach J (2014) Haematopinus oliveri. The IUCN Red List of Threatened Species 2014: e.T9621A21423551. https://doi.org/10.2305/IUCN.UK.2014-1.RLTS.T9621A21423551.en.Mingozzi, T. & Stève, R. Analysis of a historical extirpation of the bearded vulture Gypaetus barbatus (L.) in the Western Alps (France-Italy): former distribution and causes of extirpation. Biol. Conserv. 79, 155–171. https://doi.org/10.1016/S0006-3207(96)00110-3 (1997).Article 

    Google Scholar 
    Schaub, M., Zink, R., Beissmann, H., Sarrazin, F. & Arlettaz, R. When to end releases in reintroduction programmes: demographic rates and population viability analysis of bearded vultures in the Alps. J. Appl. Ecol. 46, 92–100. https://doi.org/10.1111/j.1365-2664.2008.01585.x (2009).Article 

    Google Scholar 
    BirdLife International. Gypaetus barbatus (amended version of 2017 assessment). The IUCN Red List of Threatened Species 2017: e.T22695174A118590506. https://doi.org/10.2305/IUCN.UK.2017-3.RLTS.T22695174A118590506.en, accessed 07 Apr 2021 (2017).Price, R. D., Hellenthal, R. A., Palma, R. L., Johnson, K. P., & Clayton, D. H. The chewing lice: World checklist and biological overview. Illinois Natural History Survey Special Publication 24. Illinois (2003).Clay, T. Revisions of mallophaga genera. Degeeriella from the Falconiformes. Bull. Br. Mus. (Nat. Hist.) 7, 123–207 (1958).
    Google Scholar 
    Martín Mateo, M. P. Fauna Ibérica, Vol. 32. Phthiraptera, Ischnocera. Museo Nacional de Ciencias Naturales (CSIC), Madrid (2009).Hoberg, E. P., Brooks, D. R. & Siegel-Causey, D. Host-parasite co-speciation: history, principles, and prospects. In Host-Parasite Evolution: General Principles and Avian Models (eds Clayton, D. H. & Moore, J.) 212–235 (Oxford University Press, 1997).
    Google Scholar 
    Johnson, K. P., Weckstein, J. D., Witt, C. C., Faucett, R. C. & Moyle, R. G. The perils of using host relationships in parasite taxonomy: phylogeny of the Degeeriella complex. Mol. Phylogenet. Evol. 23, 150–157. https://doi.org/10.1016/S1055-7903(02)00014-3 (2002).Article 
    CAS 

    Google Scholar 
    Catanach, T. A. & Johnson, K. P. Independent origins of the feather lice (Insecta: Degeeriella) of raptors. Biol. J. Linn. Soc. 114, 837–847. https://doi.org/10.1111/bij.12453 (2015).Article 

    Google Scholar 
    Pérez, J. M., Ruiz-Martínez, I. & Cooper, J. E. Occurrence of chewing lice on Spanish raptors. Ardeola 43, 129–138 (1996).
    Google Scholar 
    Ash, J. S. A study of the mallophagan of birds with particular reference to their ecology. Ibis 102, 93–110. https://doi.org/10.1111/j.1474-919X.1960.tb05095.x (1960).Article 

    Google Scholar 
    Askew, R. R. Parasitic Insects (Heinemann Educational, 1971).
    Google Scholar 
    Marshall, A. G. The Ecology of Parasitic Insects (Academic Press, 1981).
    Google Scholar 
    Bartlow, A. W., Villa, S. M., Thompson, M. W. & Bush, S. E. Walk or ride? Phoretic behaviour of amblyceran and ischnoceran lice. Int. J. Parasitol. 46, 221–227. https://doi.org/10.1016/j.ijpara.2016.01.003 (2016).Article 

    Google Scholar 
    Leonardi, M. S., Crespo, E. A., Raga, J. A. & Fernández, M. Scanning electron microscopy of Antarctophthirus microchir (Phthiraptera: Anoplura: Echinophthiriidae): Studying morphological adaptations to aquatic life. Micron 43, 929–936. https://doi.org/10.1016/j.micron.2012.03.009 (2012).Article 

    Google Scholar 
    Ortega Insaurralde, I., Minoli, S., Toloza, A. C., Picollo, M. I. & Barrozo, R. B. The sensory machinery of the head louse Pediculus humanus capitis: from the antennae to the brain. Front. Physiol. 10, 434. https://doi.org/10.3389/fphys.2019.00434 (2019).Article 

    Google Scholar 
    Ortega Insaurralde, I., Picollo, M. I. & Barrozo, R. B. Sensory features of the human louse antenna: New contributions and comparisons between ecotypes. Med. Vet. Entomol. 35, 219–224. https://doi.org/10.1111/mve.12485 (2021).Article 
    CAS 

    Google Scholar 
    Page, R. D. M., Lee, P. L. M., Becher, S. A., Griffiths, R. & Clayton, D. H. A different tempo of mitochondrial DNA evolution in birds and their parasitic lice. Mol. Phylogenet. Evol. 9, 276–293. https://doi.org/10.1006/mpev.1997.0458 (1998).Article 
    CAS 

    Google Scholar 
    Cruickshank, R. H. et al. Phylogenetic analysis of partial sequences of elongation factor 1α identifies major groups of lice (Insecta: Phthiraptera). Mol. Phylogenet. Evol. 19, 202–215. https://doi.org/10.1006/mpev.2001.0928 (2001).Article 
    CAS 

    Google Scholar 
    Murrell, A. & Barker, S. C. Multiple origins of parasitism in lice: phylogenetic analysis of SSU rDNA indicates that the Phthiraptera and Psocoptera are not monophyletic. Parasitol. Res. 97, 274–280. https://doi.org/10.1007/s00436-005-1413-8 (2005).Article 

    Google Scholar 
    Whiteman, N. K., Kimball, R. T. & Parker, P. G. Co-phylogeography and comparative population genetics of the threatened Galápagos hawk and three ectoparasite species: ecology shapes population histories within parasite communities. Mol. Ecol. 16, 4759–4773. https://doi.org/10.1111/j.1365-294X.2007.03512.x (2007).Article 
    CAS 

    Google Scholar 
    Palma, R. L. Slide-mounting of Lice: a detailed description of the Canada Balsam technique. N. Z. Entomol. 6, 432–436. https://doi.org/10.1080/00779962.1978.9722313 (1978).Article 

    Google Scholar 
    Soler-Cruz, M. D. & Martín-Mateo, M. P. Scanning electron microscopy of legs of two species of sucking lice (Anoplura: Phthiraptera). Micron 40, 401–408. https://doi.org/10.1016/j.micron.2008.10.001 (2009).Article 
    CAS 

    Google Scholar 
    Hafner, M. S. et al. Disparate rates of molecular evolution in cospeciating hosts and parasites. Science 265, 1087–1090. https://doi.org/10.1126/science.8066445 (1994).Article 
    ADS 
    CAS 

    Google Scholar 
    Simon, C. et al. Evolution, weighting and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Ann. Entomol. Soc. Am. 87, 651–701. https://doi.org/10.1093/aesa/87.6.651 (1994).Article 
    CAS 

    Google Scholar 
    Danforth, B. N. & Ji, S. Elongation factor-1α occurs as two copies in bees: Implications for phylogenetic analysis of EF-1α sequences in insects. Mol. Biol. Evol. 15, 225–235. https://doi.org/10.1093/oxfordjournals.molbev.a025920 (1998).Article 
    CAS 

    Google Scholar 
    Smith, V. S., Page, R. D. M. & Johnson, K. P. Data incongruence and the problem of avian louse phylogeny. Zool. Scr. 33, 239–259. https://doi.org/10.1111/j.0300-3256.2004.00149.x (2004).Article 

    Google Scholar 
    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/10.1016/S0022-2836(05)80360-2 (1990).Article 
    CAS 

    Google Scholar 
    Darriba, D., Taboada, G. L., Doallo, R. & Posada, D. jModelTest 2: More models, new heuristics and parallel computing. Nat. Methods 9, 772. https://doi.org/10.1038/nmeth.2109 (2012).Article 
    CAS 

    Google Scholar 
    Huelsenbeck, J. P. & Ronquist, F. MRBAYES: Bayesian inference of phylogeny. Bioinformatics 17, 754–755. https://doi.org/10.1093/bioinformatics/17.8.754 (2001).Article 
    CAS 

    Google Scholar 
    Zwickl, D. J. Genetic algorithm approaches for the phylogenetic analysis of large biological sequence datasets under the maximum likelihood criterion. Ph.D. Thesis Dissertation, The University of Texas at Austin, Texas (2006).Rambaut, A. FigTree v1.4.2. Institute of Evolutionary Biology (University of Edinburgh, 2014).
    Google Scholar 
    Brown, C. J. Plumages and measurements of the Bearded Vulture in Southern Africa. Ostrich 60, 165–171 (1989).Article 

    Google Scholar 
    Chatterjee, P., Payra, A. & Sen, S. Insecta: Phthiraptera. In Faunal Diversity of Indian Himalaya (eds Chandra, K. et al.) 297–304 (Zoological Survey of India, 2018).
    Google Scholar 
    Liébanas, G. et al. The morphology of Colpocephalum pectinatum (Phthiraptera: Amblycera: Menoponidae) under scanning electron microscopy. Arthropod Struct. Dev. 64, 101085. https://doi.org/10.1016/j.asd.2021.101085 (2021).Article 

    Google Scholar 
    Pérez, J. M. Sobre algunos aspectos de la parasitación por malógafos en aves de presa. Ph.D. thesis Dissertation, Granada University (1990).Arya, G., Ahmad, A., Bansal, N., Saxena, R. & Saxena, A. K. Nature of placodean sensilla of four ischnoceran Phthiraptera. Entomon 35, 199–202 (2010).
    Google Scholar 
    Khan, V., Bansal, N., Arya, G., Ahmad, A. & Saxena, A. K. Contribution to the morphology of Degeeriella regalis (Insecta, Phthiraptera, Ischnocera). J. Entomol. Res. 35, 93–96 (2011).
    Google Scholar 
    Agarwal, G. P. et al. Bio-ecology of the louse, Upupicola upupae, infesting the Common Hoopoe, Upupa epops. J. Insect. Sci. 11, 46. https://doi.org/10.1673/031.011.4601 (2011).Article 
    CAS 

    Google Scholar 
    Singh, P., Gupta, N., Khan, G., Kumar, S. & Ahmad, A. Diagnostic characters of three nymphal instars and morphological features of adult Collard-dove louse Columbicola bacillus (Phthiraptera: Insecta). J. Appl. Nat. Sci. 11, 7–11. https://doi.org/10.31018/jans.v11i1.1855 (2019).Article 

    Google Scholar 
    Clayton, D. H. & Johnson, K. P. Linking coevolutionary history to ecological process: Doves and lice. Evolution 57, 2335–2341. https://doi.org/10.1111/j.0014-3820.2003.tb00245.x (2003).Article 

    Google Scholar 
    Barker, S. C. Lice, cospeciation and parasitism. Int J Parasitol 26, 219–222 (1996).Article 
    CAS 

    Google Scholar 
    Page, R. D. M., Clayton, D. H. & Paterson, A. A. Lice and cospeciation: A response to Barker. Int. J. Parasitol. 26, 213–218. https://doi.org/10.1016/0020-7519(95)00115-8 (1996).Article 
    CAS 

    Google Scholar 
    Paterson, A. M. & Gray, R. D. Host-parasite cospeciation, host-switching and missing the boat. In Host-Parasite Evolution: General Principles and Avian Models (eds Clayton, D. H. & Moore, J.) 236–250 (Oxford University Press, 1997).
    Google Scholar 
    Paterson, A. M., Palma, R. L. & Gray, R. D. How frequently do avian lice miss the boat? Implications for coevolutionary studies. Syst. Biol. 48, 214–223. https://doi.org/10.1080/106351599260544 (1999).Article 

    Google Scholar 
    Frey, H. & Walter, W. The reintroduction of the bearded vulture Gypaetus barbatus into the Alps. In Raptors in the Modern World (eds Meyburg, B. U. & Chancellor, R. D.) 341–344 (WWGBP, 1989).
    Google Scholar 
    Pérez, J. M., Sánchez, I. & Palma, R. L. The dilemma of conserving parasites: the case of Felicola (Lorisicola) isidoroi (Phthiraptera: Trichodectidae) and its host, the endangered Iberian lynx (Lynx pardinus). Insect. Conserv. Divers. 6, 680–686. https://doi.org/10.1111/icad.12021 (2013).Article 

    Google Scholar  More

  • in

    Author Correction: Predicting the potential for zoonotic transmission and host associations for novel viruses

    One Health Institute, School of Veterinary Medicine, University of California, Davis, Davis, CA, 95616, USAPranav S. Pandit, Tracey Goldstein, Megan M. Doyle, Nicole R. Gardner, Brian Bird, Woutrina Smith, David Wolking, Kirsten Gilardi, Corina Monagin, Terra Kelly, Marcela M. Uhart, Lucy Keatts, Jonna A. K. Mazet & Christine K. JohnsonCenter for Infection and Immunity, Columbia University, New York, NY, 10032, USASimon J. AnthonyEcoHealth Alliance, 520 Eighth Avenue, New York, NY, 10018, USAKevin J. Olival, Jonathan H. Epstein, Catherine Machalaba, Melinda K. Rostal, Patrick Dawson, Emily Hagan, Ava Sullivan, Hongying Li, Aleksei A. Chmura, Alice Latinne, Ariful Islam, James Desmond, Tom Hughes, William B. Karesh & Peter DaszakLabyrinth Global Health, Inc., 546 15th Ave NE, St Petersburg, FL, 33704, USAChristian Lange, Tammie O’Rourke & Karen SaylorsWildlife Conservation Society, Health Program, Bronx, NY, USASarah Olson, A. Patricia Mendoza, Cátia Dejuste de Paula, Amanda Fine & Cátia Dejuste de PaulaWildlife Conservation Society (WCS), Peru Program, Lima, PeruA. Patricia Mendoza & Alberto PerezGlobal Health Program, Smithsonian’s National Zoological Park and Conservation Biology Institute, Washington, DC, USADawn Zimmerman, Marc Valitutto & Ohnmar AungMosaic/Global Viral Cameroon, Yaoundé, CameroonMatthew LeBreton, Moctar Mouiche & Suzan MurrayMetabiota Inc, Nanaimo, VC, CanadaDavid McIver & Soubanh SilithammavongInstitut Pasteur du Cambodge, 5 Monivong Blvd, PO Box 983, Phnom Penh, 12201, CambodiaVeasna DuongWuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, ChinaZhengli ShiKinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the CongoPrime MulembakaniMetabiota Inc., Kinshasa, Democratic Republic of the CongoCharles KumakambaEgypt National Research Centre, 12311, Dokki, Giza, EgyptMohamed AliAklilu Lemma Institute of Pathobiology, Addis Ababa University, Addis Ababa, EthiopiaNigatu KebedeMetabiota Cameroon Ltd, Yaoundé, Centre Region Avenue Mvog-Fouda Ada, Av 1.085, Carrefour Intendance, Yaoundé, BP 15939, CameroonUbald TamoufeMilitary Veterinarian (Rtd.), P.O. Box CT2585, Accra, GhanaSamuel Bel-NonoCentre de Recherche en Virologie (VRV) Projet Fievres Hemoraquiques en Guinée, BP 5680, Nongo/Contéya-Commune de Ratoma, GuineaAlpha CamaraPrimate Research Center, Bogor Agricultural University, Bogor, 16151, IndonesiaJoko PamungkasFaculty of Veterinary Medicine, Bogor Agricultural University, Darmaga Campus, Bogor, 16680, IndonesiaJoko PamungkasDepartment Environment and Health, Institut Pasteur de Côte d’Ivoire, PO BOX 490, Abidjan 01, Ivory CoastKalpy J. CoulibalyDepartment of Basic Medical Veterinary Sciences, College of Veterinary Medicine, Jordan University of Science and Technology, Ar-Ramtha, JordanEhab Abu-BashaMolecular Biology Laboratory, Institute of Primate Research, Nairobi, KenyaJoseph KamauDepartment of Biochemistry, University of Nairobi, Nairobi, KenyaJoseph KamauConservation Medicine, Sungai Buloh, Selangor, MalaysiaTom HughesWildlife Conservation Society (WCS), Mongolia Program, Ulaanbaatar, MongoliaEnkhtuvshin ShiilegdambaCenter for Molecular Dynamics Nepal (CMDN), Thapathali -11, Kathmandu, NepalDibesh KarmacharyaRegional Headquarters, Mountain Gorilla Veterinary Project, Musanze, RwandaJulius Nziza & Benard SsebideUniversité Cheikh Anta Diop, BP 5005, Dakar, SénégalDaouda NdiayeMetabiota, Inc. Sierra Leone, Freetown, Sierra LeoneAiah GbakimaDepartment of Veterinary Medicine and Public Health, College of Veterinary Medicine and Biomedical Sciences, Sokoine University of Agriculture, Morogoro, TanzaniaZikankuba sajaliThai Red Cross Emerging Infectious Diseases Clinical Center, King Chulalongkorn Memorial Hospital, Bangkok, ThailandSupaporn WacharapluesadeeWildlife Conservation Society (WCS), Bolivia Program, La Paz, BoliviaErika Alandia RoblesFacultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México, México City, 04510, MexicoGerardo SuzánCentro de Biodiversidad y Genética, Universidad Mayor de San Simón, Cochabamba, BoliviaLuis F. AguirreLaboratório de Epidemiologia e Geoprocessamento (EpiGeo), Instituto de Medicina Veterinária (IMV) Universidade Federal do Pará (UFPA), BR-316 Km 31, Castanhal, Pará, 69746-360, BrazilMonica R. SolorioDepartment of Microbiology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, IndiaTapan N. DholeWildlife Conservation Society (WCS), Vietnam Program, Hanoi, VietnamNguyen T. T. NgaMelbourne Veterinary School, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Werribee, VIC, 3030, AustraliaPeta L. HitchensNyati Health Consulting, 2175 Dodds Road, Nanaimo, BC, V9X0A4, CanadaDamien O. Joly More

  • in

    Extreme local recycling of moisture via wetlands and forests in North-East Indian subcontinent: a Mini-Amazon

    van der Ent, R. J. & Tuinenburg, O. A. The residence time of water in the atmosphere revisited. Hydrol. Earth Syst. Sci. 21, 779–790 (2017).Article 
    ADS 

    Google Scholar 
    Risi, C., Noone, D., Frankenberg, C. & Worden, J. Role of continental recycling in intraseasonal variations of continental moisture as deduced from model simulations and water vapor isotopic measurements. Water Resour. Res. 49, 4136–4156 (2013).Article 
    ADS 
    CAS 

    Google Scholar 
    Gupta, S. K. & Deshpande, R. D. Water for India in 2050: First-order assessment of available options. Curr. Sci. 86, 9 (2004).
    Google Scholar 
    Kuttippurath, J. et al. Observed rainfall changes in the past century (1901–2019) over the wettest place on Earth. Environ. Res. Lett. 16, 024018 (2021).Article 
    ADS 

    Google Scholar 
    Rao, M. P. et al. Seven centuries of reconstructed Brahmaputra River discharge demonstrate underestimated high discharge and flood hazard frequency. Nat. Commun. 11, 6017 (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Bassi, N., Kumar, M. D., Sharma, A. & Pardha-Saradhi, P. Status of wetlands in India: A review of extent, ecosystem benefits, threats and management strategies. J. Hydrol. Regional Stud. 2, 1–19 (2014).Article 

    Google Scholar 
    Dikshit, K. R. & Dikshit, J. K. Natural vegetation: Forests and grasslands of North-East India. in North-East India: Land, People and Economy (eds. Dikshit, K. R. & Dikshit, J. K.) 213–255 (Springer, 2014). https://doi.org/10.1007/978-94-007-7055-3_9.Chakraborty, S. et al. Linkage between precipitation isotopes and biosphere-atmosphere interaction observed in northeast India. Npj Clim. Atmos. Sci. 5, 1–11 (2022).Article 

    Google Scholar 
    Pathak, A., Ghosh, S. & Kumar, P. Precipitation recycling in the Indian subcontinent during summer monsoon. J. Hydrometeorol. 15, 2050–2066 (2014).Article 
    ADS 

    Google Scholar 
    Mahanta, R., Sarma, D. & Choudhury, A. Heavy rainfall occurrences in northeast India. Int. J. Climatol. 33, 1456–1469 (2013).Article 

    Google Scholar 
    Murata, F. et al. dominant synoptic disturbance in the extreme rainfall at cherrapunji, northeast India, based on 104 years of rainfall data (1902–2005). J. Clim. 30, 8237–8251 (2017).Article 
    ADS 

    Google Scholar 
    Roy, S. C. & Chatterji, G. Origin of nor’westers. Nature 124, 481–481 (1929).Article 
    ADS 

    Google Scholar 
    Dhar, O. N. & Nandargi, S. A study of floods in the Brahmaputra basin in India. Int. J. Climatol. 20, 771–781 (2000).Article 

    Google Scholar 
    Reager, J. T., Thomas, B. F. & Famiglietti, J. S. River basin flood potential inferred using GRACE gravity observations at several months lead time. Nat. Geosci. 7, 588–592 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Gat, J. R. Isotope Hydrology: A Study of the Water Cycle (World Scientific, 2010).Book 

    Google Scholar 
    Salati, E., DallOlio, A., Matsui, E. & Gat, J. R. Recycling of water in the Amazon basin: An isotopic study. Water Resourc. Res. 15, 1250–1258 (1979).Article 
    ADS 
    CAS 

    Google Scholar 
    Victoria, R. L., Martinelli, L. A., Mortatti, J. & Richey, J. Mechanisms of water recycling in the Amazon basin: Isotopic insights. Ambio 20, 384–387 (1991).
    Google Scholar 
    Wright, J. S. et al. Rainforest-initiated wet season onset over the southern Amazon. PNAS 114, 8481–8486 (2017).Article 
    ADS 
    CAS 

    Google Scholar 
    Leite-Filho, A. T., Soares-Filho, B. S., Davis, J. L., Abrahão, G. M. & Börner, J. Deforestation reduces rainfall and agricultural revenues in the Brazilian Amazon. Nat. Commun. 12, 2591 (2021).Article 
    ADS 
    CAS 

    Google Scholar 
    Spracklen, D. V. & Garcia-Carreras, L. The impact of Amazonian deforestation on Amazon basin rainfall. Geophys. Res. Lett. 42, 9546–9552 (2015).Article 
    ADS 

    Google Scholar 
    Lele, N. & Joshi, P. K. Analyzing deforestation rates, spatial forest cover changes and identifying critical areas of forest cover changes in North-East India during 1972–1999. Environ. Monit. Assess. 156, 159 (2008).Article 

    Google Scholar 
    Sudhakar Reddy, C. et al. Quantification and monitoring of deforestation in India over eight decades (1930–2013). Biodivers. Conserv. 25, 93–116 (2016).Article 

    Google Scholar 
    Kathayat, G. et al. Interannual oxygen isotope variability in Indian summer monsoon precipitation reflects changes in moisture sources. Commun. Earth Environ. 2, 1–10 (2021).Article 

    Google Scholar 
    Kathayat, G. et al. Protracted Indian monsoon droughts of the past millennium and their societal impacts. Proc. Natl. Acad. Sci. 119, e2207487119 (2022).Article 
    CAS 

    Google Scholar 
    Breitenbach, S. F. M. et al. Strong influence of water vapor source dynamics on stable isotopes in precipitation observed in Southern Meghalaya, NE India. Earth Planet. Sci. Lett. 292, 212–220 (2010).Article 
    ADS 
    CAS 

    Google Scholar 
    Pradhan, R., Singh, N. & Singh, R. P. Onset of summer monsoon in Northeast India is preceded by enhanced transpiration. Sci. Rep. 9, 18646 (2019).Article 
    ADS 
    CAS 

    Google Scholar 
    Das, S., Sarkar, A., Das, M. K., Rahman, Md. M. & Islam, Md. N. Composite characteristics of Nor’westers based on observations and simulations. Atmos. Res. 158–159, 158–178 (2015).Article 

    Google Scholar 
    Vinay Kumar, P. & Venkateswara Naidu, C. Is pre-monsoon rainfall activity over India increasing in the recent era of global warming?. Pure Appl. Geophys. 177, 4423–4442 (2020).Article 
    ADS 

    Google Scholar 
    Narayanan, P., Sarkar, S., Basistha, A. & Sachdeva, K. Trend analysis and forecast of pre-monsoon rainfall over India. Weather 71, 94–99 (2016).Article 
    ADS 

    Google Scholar 
    Stevens, B. Atmospheric moist convection. Annu. Rev. Earth Planet. Sci. 33, 605–643 (2005).Article 
    ADS 
    MathSciNet 
    CAS 
    MATH 

    Google Scholar 
    Bershaw, J. Controls on deuterium excess across Asia. Geosciences 8, 257 (2018).Article 
    ADS 

    Google Scholar 
    Clark, I. D. & Fritz, P. Environmental Isotopes in Hydrogeology (CRC Press, 1997). https://doi.org/10.1201/9781482242911.Book 

    Google Scholar 
    Cui, J., Tian, L., Biggs, T. W. & Wen, R. Deuterium-excess determination of evaporation to inflow ratios of an alpine lake: Implications for water balance and modeling. Hydrol. Process. 31, 1034–1046 (2017).Article 
    ADS 

    Google Scholar 
    Laskar, A. H. et al. Stable isotopic characterization of Nor’westers of southern Assam, NE India. J. Clim. Chang. 1, 75–87 (2015).Article 

    Google Scholar 
    Tanoue, M. et al. Seasonal variation in isotopic composition and the origin of precipitation over Bangladesh. Prog. Earth Planet Sci. 5, 77 (2018).Article 
    ADS 

    Google Scholar 
    Oza, H., Ganguly, A., Padhya, V. & Deshpande, R. D. Hydrometeorological processes and evaporation from falling rain in Indian sub-continent: Insights from stable isotopes and meteorological parameters. J. Hydrol. 591, 125601 (2020).Article 
    CAS 

    Google Scholar 
    Chen, F. et al. Relationship between sub-cloud secondary evaporation and stable isotopes in precipitation of Lanzhou and surrounding area. Quatern. Int. 380–381, 68–74 (2015).Article 

    Google Scholar 
    Sinha, N. et al. Isotopic investigation of the moisture transport processes over the Bay of Bengal. J. Hydrol. X 2, 100021 (2019).Article 
    CAS 

    Google Scholar 
    Rawson, H. M., Begg, J. E. & Woodward, R. G. The effect of atmospheric humidity on photosynthesis, transpiration and water use efficiency of leaves of several plant species. Planta 134, 5–10 (1977).Article 
    CAS 

    Google Scholar 
    Chakraborty, S., Belekar, A. R., Datye, A. & Sinha, N. Isotopic study of intraseasonal variations of plant transpiration: An alternative means to characterise the dry phases of monsoon. Sci. Rep. 8, 8647 (2018).Article 
    ADS 
    CAS 

    Google Scholar 
    Sinha, N., Chakraborty, S. & Mohan, P. M. Modern rain-isotope data from Indian island and the mainland on the daily scale for the summer monsoon season. Data Brief 23, 103793 (2019).Article 

    Google Scholar 
    Grujic, D. et al. Formation of a Rain Shadow: O and H stable isotope records in authigenic clays from the Siwalik group in eastern Bhutan. Geochem. Geophys. Geosyst. 19, 3430–3447 (2018).Article 
    CAS 

    Google Scholar 
    Lambs, L., Balakrishna, K., Brunet, F. & Probst, J. L. Oxygen and hydrogen isotopic composition of major Indian rivers: A first global assessment. Hydrol. Process. 19, 3345–3355 (2005).Article 
    ADS 
    CAS 

    Google Scholar 
    Ek, M. B. & Holtslag, A. A. M. Influence of soil moisture on boundary layer cloud development. J. Hydrometeorol. 5, 86–99 (2004).Article 
    ADS 

    Google Scholar 
    Findell, K. L. & Eltahir, E. A. B. Atmospheric controls on soil moisture-boundary layer interactions. Part I: Framework development. J. Hydrometeorol. 4, 552–569 (2003).Article 
    ADS 

    Google Scholar 
    Syroka, J. & Toumi, R. On the withdrawal of the Indian summer monsoon. Q. J. R. Meteorol. Soc. 130, 989–1008 (2004).Article 
    ADS 

    Google Scholar 
    Bhatta, L. D. et al. Ecosystem service changes and livelihood impacts in the maguri-motapung wetlands of Assam. India. Land 5, 15 (2016).Article 

    Google Scholar 
    Choudhury, B. A., Saha, S. K., Konwar, M., Sujith, K. & Deshamukhya, A. Rapid drying of northeast India in the last three decades: Climate change or natural variability?. J. Geophys. Res. Atmos. 124, 227–237 (2019).Article 
    ADS 

    Google Scholar 
    Das, D. Changing climate and its impacts on Assam, Northeast India. Bandung J. Glob. South 2, 26 (2016).Article 

    Google Scholar 
    Deka, R. L., Mahanta, C., Pathak, H., Nath, K. K. & Das, S. Trends and fluctuations of rainfall regime in the Brahmaputra and Barak basins of Assam, India. Theor. Appl. Climatol. 114, 61–71 (2013).Article 
    ADS 

    Google Scholar 
    Maurya, A. S., Shah, M., Deshpande, R. D. & Gupta, S. K. Protocol for δ18O and δD analyses of water sample using Delta V plus IRMS in CF Mode with Gas Bench II for IWIN National Programme at PRL, Ahmedabad. in 11th ISMAS Triennial Conference of Indian Society for Mass Spectrometry vol. 314, 314–317 (Indian Society for Mass Spectrometry Hyderabad, 2009).Deshpande, R. D. & Gupta, S. K. Oxygen and hydrogen isotopes in hydrological cycle: new data from IWIN national programme. Proc. Indian Natl. Sci. Acad. 78, 321–331 (2012).CAS 

    Google Scholar 
    Deshpande, R. D. & Gupta, S. K. National programme on isotope fingerprinting of waters of India (IWIN). Glimpses of Geosciences Research in India, the Indian Report to IUGS, Indian National Science Academy (eds Singhvi, AK, Bhattacharya, A. & Guha, S.), 10–16 (2008).Oza, H., Padhya, V., Ganguly, A. & Deshpande, R. D. Investigating hydrometeorology of the Western Himalayas: Insights from stable isotopes of water and meteorological parameters. Atmos. Res. 268, 105997 (2022).Article 
    CAS 

    Google Scholar 
    Stein, A. F. et al. NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bull. Am. Meteor. Soc. 96, 2059–2077 (2015).Article 
    ADS 

    Google Scholar 
    Sodemann, H., Schwierz, C. & Wernli, H. Interannual variability of Greenland winter precipitation sources: Lagrangian moisture diagnostic and North Atlantic Oscillation influence. J. Geophys. Res. Atmos. 113, D3 (2008).
    Google Scholar 
    Oza, H. et al. Hydrometeorological processes in semi-arid western India: insights from long term isotope record of daily precipitation. Clim. Dyn. 54, 2745–2757 (2020).Article 

    Google Scholar 
    Su, L., Yuan, Z., Fung, J. C. H. & Lau, A. K. H. A comparison of HYSPLIT backward trajectories generated from two GDAS datasets. Sci. Total Environ. 506–507, 527–537 (2015).Article 
    ADS 

    Google Scholar 
    Ahmed, M., Seraj, R. & Islam, S. M. S. The k-means algorithm: A comprehensive survey and performance evaluation. Electronics 9, 1295 (2020).Article 

    Google Scholar  More

  • in

    Benthic composition changes on coral reefs at global scales

    Dudgeon, D. Multiple threats imperil freshwater biodiversity in the Anthropocene. Curr. Biol. 29, R942–R995 (2019).Article 

    Google Scholar 
    Betts, M. G. et al. Global forest loss disproportionately erodes biodiversity in intact landscapes. Nature 547, 441–444 (2017).Article 
    CAS 

    Google Scholar 
    Arrigo, K. R. et al. Synergistic interactions among growing stressors increase risk to an Arctic ecosystem. Nat. Commun. 11, 6255 (2020).Article 
    CAS 

    Google Scholar 
    Kopf, R. K., Finlayson, C. M., Humphries, P., Sims, N. C. & Hladyz, S. Anthropocene baselines: assessing change and managing biodiversity in human-dominated aquatic ecosystems. Bioscience 65, 798–811 (2015).Article 

    Google Scholar 
    Chapin, F. S. et al. Ecosystem stewardship: sustainability strategies for a rapidly changing planet. Trends Ecol. Evol. 25, 241–249 (2010).Article 

    Google Scholar 
    Seastedt, T. R., Hobbs, R. J. & Suding, K. N. Management of novel ecosystems: are novel approaches required? Front. Ecol. Environ. 6, 547–553 (2008).Article 

    Google Scholar 
    Hughes, T. P. et al. Coral reefs in the Anthropocene. Nature 546, 82–90 (2017).Article 
    CAS 

    Google Scholar 
    Bellwood, D. R. et al. Coral reef conservation in the Anthropocene: confronting spatial mismatches and prioritizing functions. Biol. Conserv. 236, 604–615 (2019).Article 

    Google Scholar 
    Graham, N. A. J., Cinner, J. E., Norström, A. V. & Nyström, M. Coral reefs as novel ecosystems: embracing new futures. Curr. Opin. Environ. Sustain. 7, 9–14 (2014).Article 

    Google Scholar 
    Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80–83 (2018).Article 
    CAS 

    Google Scholar 
    Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nat. Commun. 10, 1264 (2019).Article 
    CAS 

    Google Scholar 
    Fisher, R. et al. Species richness on coral reefs and the pursuit of convergent global estimates. Curr. Biol. 25, 500–505 (2015).Article 
    CAS 

    Google Scholar 
    Brandl, S. J. et al. Coral reef ecosystem functioning: eight core processes and the role of biodiversity. Front. Ecol. Environ. 17, 445–454 (2019).Article 

    Google Scholar 
    Teh, L. S. L., Teh, L. C. L. & Sumaila, U. R. A global estimate of the number of coral reef fishers. PLoS ONE 8, e65397 (2013).Article 
    CAS 

    Google Scholar 
    Ferrario, F. et al. The effectiveness of coral reefs for coastal hazard risk reduction and adaptation. Nat. Commun. 5, 3794 (2014).Article 
    CAS 

    Google Scholar 
    Skirving, W. J. et al. The relentless march of mass coral bleaching: a global perspective of changing heat stress. Coral Reefs 38, 547–557 (2019).Article 

    Google Scholar 
    Donovan, M. K. et al. Local conditions magnify coral loss after marine heatwaves. Science 372, 977–980 (2021).Article 
    CAS 

    Google Scholar 
    Gilmour, J. P., Smith, L. D., Heyward, A. J., Baird, A. H. & Pratchett, M. S. Recovery of an isolated coral reef system following severe disturbance. Science 340, 69–71 (2013).Article 

    Google Scholar 
    Diaz-Pulido, G. & McCook, L. J. The fate of bleached corals: patterns and dynamics of algal recruitment. Mar. Ecol. Prog. Ser. 232, 115–128 (2002).Article 

    Google Scholar 
    Bellwood, D. R., Hughes, T. P., Folke, C. & Nyström, M. Confronting the coral reef crisis. Nature 429, 827–833 (2004).Article 
    CAS 

    Google Scholar 
    Jouffray, J. B. et al. Parsing human and biophysical drivers of coral reef regimes. Proc. R. Soc. B Biol. Sci. 286, 20182544 (2019).Article 

    Google Scholar 
    Reverter, M., Helber, S. B., Rohde, S., Goeij, J. M. & Schupp, P. J. Coral reef benthic community changes in the Anthropocene: biogeographic heterogeneity, overlooked configurations, and methodology. Glob. Chang. Biol. 28, 1956–1971 (2022).Article 

    Google Scholar 
    Cheal, A. J., MacNeil, M. A., Emslie, M. J. & Sweatman, H. The threat to coral reefs from more intense cyclones under climate change. Glob. Chang. Biol. 23, 1511–1524 (2017).Article 

    Google Scholar 
    Done, T. in Perspectives on Coral Reefs (ed. Barnes, D. J.) 107–147 (Brian Clouston, 1983).Bruno, J. F., Côté, I. M. & Toth, L. T. Climate change, coral loss, and the curious case of the parrotfish paradigm: why don’t marine protected areas improve reef resilience? Ann. Rev. Mar. Sci. 11, 307–334 (2019).Article 

    Google Scholar 
    Gardner, T. A., Cote, I. M., Gill, J. A., Grant, A. & Watkinson, A. R. Long-term region-wide declines in Caribbean corals. Science 301, 958–960 (2003).Article 
    CAS 

    Google Scholar 
    Schutte, V. G. W., Selig, E. R. & Bruno, J. F. Regional spatio-temporal trends in Caribbean coral reef benthic communities. Mar. Ecol. Prog. Ser. 402, 115–122 (2010).Article 

    Google Scholar 
    Hughes, T. P. Catastrophes, phase shifts and large-scale degradation of a Caribbean coral reef. Science 265, 1547–1551 (1994).Article 
    CAS 

    Google Scholar 
    Souter, D. et al. Status of Coral Reefs of the World: 2020 (Global Coral Reef Monitoring Network, 2021).Bruno, J. F. & Selig, E. R. Regional decline of coral cover in the Indo-Pacific: timing, extent, and subregional comparisons. PLoS One 2, e711 (2007).Article 

    Google Scholar 
    Ateweberhan, M., McClanahan, T. R., Graham, N. A. J. & Sheppard, C. R. C. Episodic heterogeneous decline and recovery of coral cover in the Indian Ocean. Coral Reefs 30, 739–752 (2011).Article 

    Google Scholar 
    Bellwood, D. R., Hemingson, C. R. & Tebbett, S. B. Subconscious biases in coral reef fish studies. Bioscience 70, 621–627 (2020).Article 

    Google Scholar 
    Kench, P. S. et al. Sustained coral reef growth in the critical wave dissipation zone of a Maldivian atoll. Commun. Earth Environ. 3, 9 (2022).Article 

    Google Scholar 
    Eddy, T. D. et al. Global decline in capacity of coral reefs to provide ecosystem services. One Earth 4, 1278–1285 (2021).Article 

    Google Scholar 
    Mumby, P. J., Hastings, A. & Edwards, H. J. Thresholds and the resilience of Caribbean coral reefs. Nature 450, 98–101 (2007).Article 
    CAS 

    Google Scholar 
    Roff, G. & Mumby, P. J. Global disparity in the resilience of coral reefs. Trends Ecol. Evol. 27, 404–413 (2012).Article 

    Google Scholar 
    Bruno, J. F., Sweatman, H., Precht, W. F., Selig, E. R. & Schutte, V. G. W. Assessing evidence of phase shifts from coral to macroalgal dominance on coral reefs. Ecology 90, 1478–1484 (2009).Article 

    Google Scholar 
    Renema, W. et al. Hopping hotspots: global shifts in marine biodiversity. Science 321, 654–657 (2008).Article 
    CAS 

    Google Scholar 
    Bellwood, D. R., Goatley, C. H. R. & Bellwood, O. The evolution of fishes and corals on reefs: form, function and interdependence. Biol. Rev. 92, 878–901 (2017).Article 

    Google Scholar 
    Roff, G. Evolutionary history drives biogeographic patterns of coral reef resilience. Bioscience 71, 26–39 (2021).
    Google Scholar 
    Siqueira, A. C., Bellwood, D. R. & Cowman, P. F. The evolution of traits and functions in herbivorous coral reef fishes through space and time. Proc. R. Soc. B Biol. Sci. 286, 20182672 (2019).Article 

    Google Scholar 
    Birrell, C. L., McCook, L. J., Willis, B. L. & Diaz-Pulido, G. A. Effects of benthic algae on the replenishment of corals and the implications for the resilience of coral reefs. Oceanogr. Mar. Biol. Annu. Rev. 46, 25–63 (2008).
    Google Scholar 
    Speare, K. E., Duran, A., Miller, M. W. & Burkepile, D. E. Sediment associated with algal turfs inhibits the settlement of two endangered coral species. Mar. Pollut. Bull. 144, 189–195 (2019).Article 
    CAS 

    Google Scholar 
    Diaz-Pulido, G., Harii, S., McCook, L. J. & Hoegh-Guldberg, O. The impact of benthic algae on the settlement of a reef-building coral. Coral Reefs 29, 203–208 (2010).Article 

    Google Scholar 
    Johns, K. A. et al. Macroalgal feedbacks and substrate properties maintain a coral reef regime shift. Ecosphere 9, e02349 (2018).Article 

    Google Scholar 
    Houk, P. et al. Commercial coral-reef fisheries across Micronesia: a need for improving management. Coral Reefs 31, 13–26 (2012).Article 

    Google Scholar 
    Edwards, C. B. et al. Global assessment of the status of coral reef herbivorous fishes: evidence for fishing effects. Proc. R. Soc. B Biol. Sci. 281, 20131835 (2014).Article 
    CAS 

    Google Scholar 
    Choat, J. H. & Clements, K. D. Vertebrate herbivores in marine and terrestrial environments: a nutritional ecology perspective. Annu. Rev. Ecol. Syst. 29, 375–403 (1998).Article 

    Google Scholar 
    Tebbett, S. B., Morais, R. A., Goatley, C. H. R. & Bellwood, D. R. Collapsing ecosystem functions on an inshore coral reef. J. Environ. Manag. 289, 112471 (2021).Article 

    Google Scholar 
    Cornwall, C. E. et al. Global declines in coral reef calcium carbonate production under ocean acidification and warming. Proc. Natl Acad. Sci. USA. 118, e2015265118 (2021).Article 
    CAS 

    Google Scholar 
    Diaz-Pulido, G. et al. Greenhouse conditions induce mineralogical changes and dolomite accumulation in coralline algae on tropical reefs. Nat. Commun. 5, 3310 (2014).Article 

    Google Scholar 
    Nash, M. C. et al. Dolomite-rich coralline algae in reefs resist dissolution in acidified conditions. Nat. Clim. Chang. 3, 268–272 (2013).Article 
    CAS 

    Google Scholar 
    Lyons, M., Larsen K. & Skone, M. Allen Coral Atlas. Imagery, maps and monitoring of the world’s tropical coral reefs. Zenodo https://doi.org/10.5281/zenodo.3833242 (2020).Tebbett, S. B. & Bellwood, D. R. Algal turf sediments on coral reefs: what’s known and what’s next. Mar. Pollut. Bull. 149, 110542 (2019).Article 
    CAS 

    Google Scholar 
    Nugues, M. M. & Bak, R. P. M. Long-term dynamics of the brown macroalga Lobophora variegata on deep reefs in Curaçao. Coral Reefs 27, 389–393 (2008).Article 

    Google Scholar 
    Tsounis, G. & Edmunds, P. J. Three decades of coral reef community dynamics in St. John, USVI: a contrast of scleractinians and octocorals. Ecosphere 8, e01646 (2017).Article 

    Google Scholar 
    Toth, L. T. et al. Do no-take reserves benefit Florida’s corals? 14 years of change and stasis in the Florida Keys National Marine Sanctuary. Coral Reefs 33, 565–577 (2014).Article 

    Google Scholar 
    Smith, J. E. et al. Re-evaluating the health of coral reef communities: baselines and evidence for human impacts across the central Pacific. Proc. R. Soc. B Biol. Sci. 283, 20151985 (2016).Article 

    Google Scholar 
    Wolfe, K., Kenyon, T. M. & Mumby, P. J. The biology and ecology of coral rubble and implications for the future of coral reefs. Coral Reefs 40, 1769–1806 (2021).Article 

    Google Scholar 
    Harris, J. L., Lewis, L. S. & Smith, J. E. Quantifying scales of spatial variability in algal turf assemblages on coral reefs. Mar. Ecol. Prog. Ser. 532, 41–57 (2015).Article 

    Google Scholar 
    Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G. & Group, T. P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6, e1000097 (2009).Article 

    Google Scholar 
    Crisp, S. K., Tebbett, S. B. & Bellwood, D. R. A critical evaluation of benthic phase shift studies on coral reefs. Mar. Environ. Res. 178, 105667 (2022).Article 
    CAS 

    Google Scholar 
    WebPlotDigitizer v. 4.3 (A. Rohatgi, 2020); https://automeris.io/WebPlotDigitizerKulbicki, M. et al. Global biogeography of reef fishes: a hierarchical quantitative delineation of regions. PLoS ONE 8, e81847 (2013).Article 

    Google Scholar 
    Spalding, M. D. et al. Marine ecoregions of the world: a bioregionalization of coastal and shelf areas. Bioscience 57, 573–583 (2007).Article 

    Google Scholar 
    R Core Team: R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020).Zychaluk, K., Bruno, J. F., Clancy, D., McClanahan, T. R. & Spencer, M. Data-driven models for regional coral-reef dynamics. Ecol. Lett. 15, 151–158 (2012).Article 

    Google Scholar 
    Dudgeon, S. R., Aronson, R. B., Bruno, J. F. & Precht, W. F. Phase shifts and stable states on coral reefs. Mar. Ecol. Prog. Ser. 413, 201–216 (2010).Article 

    Google Scholar 
    Jost, L., Chao, A. & Chazdon, R. L. in Biological Diversity: Frontiers in Measurement and Assessment (eds Magurran, A. E. & McGill, B. J.) 66–84 (Oxford Univ. Press, 2011).Oksanen, J. F. et al. Vegan: Community ecology package. R package version 2.5-6 (2019).Calenge, C. The package “adehabitat” for the R software: a tool for the analysis of space and habitat use by animals. Ecol. Modell. 197, 516–519 (2006).Article 

    Google Scholar 
    Worton, B. J. Kernel methods for estimating the utilization distribution in home‐range studies. Ecology 70, 164–168 (1989).Article 

    Google Scholar 
    Blonder, B. Hypervolume concepts in niche- and trait-based ecology. Ecography 41, 1441–1455 (2018).Article 

    Google Scholar 
    Wood, S. N. Generalized Additive Models: an Introduction with R 2nd edn (Chapman & Hall/CRC, 2017).Gräler, B., Pebesma, E. & Heuvelink, G. Spatio-temporal interpolation using gstat. R. J. 8, 204–218 (2016).Article 

    Google Scholar 
    Hartig, F. DHARMa: Residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.3.3.0 (2020).Lenth, R. emmeans: Estimated marginal means, aka least-squares means. R package version 1.5.1 (2020).Wickham, H. et al. tidyverse: easily install and load the ‘tidyverse’. J. Open Source Softw. 4, 1686 (2019).Article 

    Google Scholar 
    Pebesma, E. Simple features for R: standardized support for spatial vector data. R. J. 10, 439–446 (2018).Article 

    Google Scholar 
    South, A. rnaturalearth: World map data from natural earth. R package version 0.1.0 (2017).Hamilton, N. E. & Ferry, M. ggtern: ternary diagrams using ggplot2. J. Stat. Softw., Code Snippets 87, 1–17 (2018).
    Google Scholar 
    Pedersen, T. L. patchwork: The composer of plots. R package version 1.1.1 (2020). More

  • in

    Resolving the intricate role of climate in litter decomposition

    Swift, M. J., Heal, O. W. & Anderson, J. M. Decomposition in Terrestrial Ecosystems. Vol. 5.5 (Blackwell, 1979).Aerts, R. Climate, leaf litter chemistry and leaf litter decomposition in terrestrial ecosystems: a triangular relationship. Oikos 79, 439 (1997).Article 

    Google Scholar 
    Makkonen, M. et al. Highly consistent effects of plant litter identity and functional traits on decomposition across a latitudinal gradient. Ecol. Lett. 15, 1033–1041 (2012).Article 

    Google Scholar 
    Coûteaux, M. M., Bottner, P. & Berg, B. Litter decomposition, climate and liter quality. Trends Ecol. Evol. 10, 63–66 (1995).Article 

    Google Scholar 
    Cornwell, W. K. et al. Plant species traits are the predominant control on litter decomposition rates within biomes worldwide. Ecol. Lett. 11, 1065–1071 (2008).Article 

    Google Scholar 
    Bradford, M. A. et al. Climate fails to predict wood decomposition at regional scales. Nat. Clim. Change 4, 625–630 (2014).Article 
    CAS 

    Google Scholar 
    Bradford, M. A., Berg, B., Maynard, D. S., Wieder, W. R. & Wood, S. A. Understanding the dominant controls on litter decomposition. J. Ecol. 104, 229–238 (2016).Article 
    CAS 

    Google Scholar 
    Joly, F.-X. et al. Tree species diversity affects decomposition through modified micro-environmental conditions across European forests. New Phytol. 214, 1281–1293 (2017).Article 
    CAS 

    Google Scholar 
    Bradford, M. A. et al. A test of the hierarchical model of litter decomposition. Nat. Ecol. Evol. 1, 1836–1845 (2017).Article 

    Google Scholar 
    Berg, B. et al. Litter mass loss rates in pine forests of Europe and Eastern United States: some relationships with climate and litter quality. Biogeochemistry 20, 127–159 (1993).Article 

    Google Scholar 
    Powers, J. S. et al. Decomposition in tropical forests: a pan-tropical study of the effects of litter type, litter placement and mesofaunal exclusion across a precipitation gradient. J. Ecol. 97, 801–811 (2009).Article 
    CAS 

    Google Scholar 
    Djukic, I. et al. Early stage litter decomposition across biomes. Sci. Total Environ. 628–629, 1369–1394 (2018).Article 

    Google Scholar 
    Cornelissen, J. H. C. & Thompson, K. Functional leaf attributes predict litter decomposition rate in herbaceous plants. New Phytol. 135, 109–114 (1997).Article 
    CAS 

    Google Scholar 
    Coq, S., Souquet, J.-M., Meudec, E., Cheynier, V. & Hättenschwiler, S. Interspecific variation in leaf litter tannins drives decomposition in a tropical rain forest of French Guiana. Ecology 91, 2080–2091 (2010).Article 

    Google Scholar 
    Sun, T. et al. Contrasting dynamics and trait controls in first-order root compared with leaf litter decomposition. Proc. Natl Acad. Sci. USA 115, 10392–10397 (2018).Article 
    CAS 

    Google Scholar 
    Baeten, L. et al. A novel comparative research platform designed to determine the functional significance of tree species diversity in European forests. Perspect. Plant Ecol. Evol. Syst. 15, 281–291 (2013).Article 

    Google Scholar 
    Hobbie, S. E. et al. Tree species effects on decomposition and forest floor dynamics in a common garden. Ecology 87, 2288–2297 (2006).Article 

    Google Scholar 
    von Arx, G., Graf Pannatier, E., Thimonier, A. & Rebetez, M. Microclimate in forests with varying leaf area index and soil moisture: potential implications for seedling establishment in a changing climate. J. Ecol. 101, 1201–1213 (2013).Article 

    Google Scholar 
    Ayres, E. et al. Home-field advantage accelerates leaf litter decomposition in forests. Soil Biol. Biochem. 41, 606–610 (2009).Article 
    CAS 

    Google Scholar 
    Freschet, G. T., Aerts, R. & Cornelissen, J. H. C. Multiple mechanisms for trait effects on litter decomposition: moving beyond home-field advantage with a new hypothesis. J. Ecol. 100, 619–630 (2012).Article 

    Google Scholar 
    Meentemeyer, V. Macroclimate and lignin control of litter decomposition rates. Ecology 59, 465–472 (1978).Article 
    CAS 

    Google Scholar 
    Currie, W. S. et al. Cross-biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale. Glob. Change Biol. 16, 1744–1761 (2010).Article 

    Google Scholar 
    Canessa, R. et al. Relative effects of climate and litter traits on decomposition change with time, climate and trait variability. J. Ecol. 109, 447–458 (2021).Article 

    Google Scholar 
    García-Palacios, P., Shaw, E. A., Wall, D. H. & Hättenschwiler, S. Temporal dynamics of biotic and abiotic drivers of litter decomposition. Ecol. Lett. 19, 554–563 (2016).Article 

    Google Scholar 
    Prescott, C. E. Litter decomposition: what controls it and how can we alter it to sequester more carbon in forest soils? Biogeochemistry 101, 133–149 (2010).Article 
    CAS 

    Google Scholar 
    Prescott, C. E. & Vesterdal, L. Decomposition and transformations along the continuum from litter to soil organic matter in forest soils. For. Ecol. Manage. 498, 119522 (2021).Article 

    Google Scholar 
    Stadler, S. J. in Encyclopedia of World Climatology 89–94 (Springer, 2005).Moore, T. R., Bubier, J. L. & Bledzki, L. Litter decomposition in temperate peatland ecosystems: the effect of substrate and site. Ecosystems 10, 949–963 (2007).Article 

    Google Scholar 
    Austin, A. T. Has water limited our imagination for aridland biogeochemistry. Trends Ecol. Evol. 26, 229–235 (2011).Article 

    Google Scholar 
    Joly, F.-X., Kurupas, K. & Throop, H. Pulse frequency and soil-litter mixing alter the control of cumulative precipitation over litter decomposition. Ecology 98, 2255–2260 (2017).Article 

    Google Scholar 
    Scherer-Lorenzen, M., Bonilla, J. L. & Potvin, C. Tree species richness affects litter production and decomposition rates in a tropical biodiversity experiment. Oikos 116, 2108–2124 (2007).Article 

    Google Scholar 
    Vivanco, L. & Austin, A. T. Tree species identity alters forest litter decomposition through long-term plant and soil interactions in Patagonia, Argentina. J. Ecol. 96, 727–736 (2008).Article 
    CAS 

    Google Scholar 
    Fanin, N. et al. Home‐field advantage of litter decomposition: from the phyllosphere to the soil. New Phytol. 231, 1353–1358 (2021).Article 

    Google Scholar 
    Hättenschwiler, S., Tiunov, A. V. & Scheu, S. Biodiversity and litter decomposition in terrestrial ecosystems. Annu. Rev. Ecol. Evol. Syst. 36, 191–218 (2005).Article 

    Google Scholar 
    Keuskamp, J. A., Dingemans, B. J. J., Lehtinen, T., Sarneel, J. M. & Hefting, M. M. Tea Bag Index: a novel approach to collect uniform decomposition data across ecosystems. Methods Ecol. Evol. 4, 1070–1075 (2013).Article 

    Google Scholar 
    Thakur, M. P. et al. Reduced feeding activity of soil detritivores under warmer and drier conditions. Nat. Clim. Change 8, 75–78 (2018).Article 

    Google Scholar 
    Harrison, A. F., Latter, P. M. & Walton, D. W. H. (eds) Cotton Strip Assay: An Index of Decomposition in Soils (Institute of Terrestrial Ecology, 1988).García-Palacios, P., Maestre, F. T., Kattge, J. & Wall, D. H. Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes. Ecol. Lett. 16, 1045–1053 (2013).Article 

    Google Scholar 
    Garnier, E. et al. Plant functional markers capture ecosystem properties during secondary succession. Ecology 85, 2630–2637 (2004).Article 

    Google Scholar 
    Dawud, S. M. et al. Tree species functional group is a more important driver of soil properties than tree species diversity across major European forest types. Funct. Ecol. 31, 1153–1162 (2017).Article 

    Google Scholar 
    Pollastrini, M. et al. Taxonomic and ecological relevance of the chlorophyll a fluorescence signature of tree species in mixed European forests. New Phytol. 212, 51–65 (2016).Article 
    CAS 

    Google Scholar 
    R Development Core Team. R: A Language and Environment for Statistical Computing (R Core Team, 2013).Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

    Google Scholar 
    Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

    Google Scholar  More

  • in

    Changing plant functional diversity over the last 12,000 years provides perspectives for tracking future changes in vegetation communities

    Wingard, G. L., Bernhardt, C. E. & Wachnicka, A. H. The role of paleoecology in restoration and resource management—the past as a guide to future decision-making: review and example from the Greater Everglades ecosystem, U.S.A. Front. Ecol. Evol 5, 11 (2017).Article 

    Google Scholar 
    Gillson, L., Dirk, C. & Gell, P. Using long-term data to inform a decision pathway for restoration of ecosystem resilience. Anthropocene 36, 100315 (2021).Article 

    Google Scholar 
    Nieto-Lugilde, D. et al. Time to better integrate paleoecological research infrastructures with neoecology to improve understanding of biodiversity long-term dynamics and to inform future conservation. Environ. Res. Lett. 16, 095005 (2021).Article 

    Google Scholar 
    Leo, G. A. D. & Levin, S. A. The multifaceted aspects of ecosystem integrity. Conserv. Ecol. 1, 3 (1997).
    Google Scholar 
    Mason, N. & Mouillot, D. in Encyclopedia of Biodiversity (ed. Levin, S. A.) 597–608 (Elsevier, 2013).Carvalho, F. et al. A method for reconstructing temporal changes in vegetation functional trait composition using Holocene pollen assemblages. PLoS ONE 14, e0216698 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Brussel, T. & Brewer, S. C. Functional paleoecology and the pollen-plant functional trait linkage. Front. Ecol. Evol 8, 564609 (2021).Article 

    Google Scholar 
    Brussel, T., Minckley, T. A., Brewer, S. C. & Long, C. J. Community-level functional interactions with fire track long-term structural development and fire adaptation. J. Veg. Sci. 29, 450–458 (2018).Article 

    Google Scholar 
    Barboni, D. et al. Relationships between plant traits and climate in the Mediterranean region: a pollen data analysis. J. Veg. Sci. 15, 635–646 (2004).Article 

    Google Scholar 
    Reitalu, T. et al. Novel insights into post-glacial vegetation change: functional and phylogenetic diversity in pollen records. J. Veg. Sci. 26, 911–922 (2015).Article 

    Google Scholar 
    Blaus, A. et al. Modern pollen-plant diversity relationships inform palaeoecological reconstructions of functional and phylogenetic diversity in calcareous fens. Front. Ecol. Evol 8, 207 (2020).Article 

    Google Scholar 
    Morris, J. L. et al. Stable or seral? Fire-driven alternative states in aspen forests of western North America. Biol. Lett. 15, 20190011 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ordonez, A. & Svenning, J.-C. Greater tree species richness in eastern North America compared to Europe is coupled to denser, more clustered functional trait space filling, not to trait space expansion. Glob. Ecol. Biogeogr. 27, 1288–1299 (2018).Article 

    Google Scholar 
    van der Sande, M. T. et al. A 7000-year history of changing plant trait composition in an Amazonian landscape; the role of humans and climate. Ecol. Lett. 22, 925–935 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lacourse, T. & Adeleye, M. A. Climate and species traits drive changes in Holocene forest composition along an elevation gradient in Pacific Canada. Front. Ecol. Evol 10, 838545 (2022).Article 

    Google Scholar 
    Lacourse, T. Environmental change controls postglacial forest dynamics through interspecific differences in life-history traits. Ecology 90, 2149–2160 (2009).Article 
    PubMed 

    Google Scholar 
    Veeken, A., Santos, M. J., McGowan, S., Davies, A. L. & Schrodt, F. Pollen-based reconstruction reveals the impact of the onset of agriculture on plant functional trait composition. Ecol. Lett. 25, 1937–1951 (2022).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ellis, E. C., Antill, E. C. & Kreft, H. All is not loss: plant biodiversity in the anthropocene. PLoS ONE 7, e30535 (2012).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    GILL, A. M. Fire and the Australian flora: a review. Aust. For. 38, 4–25 (1975).Article 

    Google Scholar 
    Crisp, M. D., Burrows, G. E., Cook, L. G., Thornhill, A. H. & Bowman, D. M. J. S. Flammable biomes dominated by eucalypts originated at the Cretaceous–Palaeogene boundary. Nat. Commun. 2, 193 (2011).Article 
    PubMed 

    Google Scholar 
    Keith, D. A. Australian Vegetation (Cambridge Univ. Press, 2017).Woinarski, J. C. Z., Burbidge, A. A. & Harrison, P. L. Ongoing unraveling of a continental fauna: decline and extinction of Australian mammals since European settlement. Proc. Natl Acad. Sci. USA 112, 4531–4540 (2015).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Broadhurst, L. & Coates, D. Plant conservation in Australia: current directions and future challenges. Plant Divers. 39, 348–356 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Adeleye, M. A., Connor, S. E., Haberle, S. G., Herbert, A. & Brown, J. European colonization and the emergence of novel fire regimes in southeast Australia. Anthr. Rev. https://doi.org/10.1177/205301962110446 (2021).Gallagher, R. V. et al. High fire frequency and the impact of the 2019–2020 megafires on Australian plant diversity. Divers. Distrib. 27, 1166–1179 (2021).Article 

    Google Scholar 
    Gallagher, R. V. et al. An integrated approach to assessing abiotic and biotic threats to post-fire plant species recovery: lessons from the 2019–2020 Australian fire season. Glob. Ecol. Biogeogr. 31, 2056–2069.Mariani, M. et al. Disruption of cultural burning promotes shrub encroachment and unprecedented wildfires. Front. Ecol. Environ. 20, 292–300 (2022).Article 

    Google Scholar 
    Williams, A. N., Mooney, S. D., Sisson, S. A. & Marlon, J. Exploring the relationship between Aboriginal population indices and fire in Australia over the last 20,000 years. Palaeogeogr. Palaeoclimatol. Palaeoecol. 432, 49–57 (2015).Article 

    Google Scholar 
    Bird, M. I., O’Grady, D. & Ulm, S. Humans, water, and the colonization of Australia. Proc. Natl Acad. Sci. USA 113, 11477–11482 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Adeleye, M. A., Haberle, S. G., Connor, S. E., Stevenson, J. & Bowman, D. M. J. S. Indigenous fire-managed landscapes in Southeast Australia during the Holocene—new insights from the Furneaux Group Islands, Bass Strait. Fire 4, 17 (2021).Article 

    Google Scholar 
    Fletcher, M.-S., Romano, A., Connor, S., Mariani, M. & Maezumi, S. Y. Catastrophic bushfires, Indigenous fire knowledge and reframing science in Southeast Australia. Fire 4, 61 (2021).Article 

    Google Scholar 
    Fletcher, M.-S., Hall, T. & Alexandra, A. N. The loss of an indigenous constructed landscape following British invasion of Australia: an insight into the deep human imprint on the Australian landscape. Ambio 50, 138–149 (2021).Article 
    CAS 
    PubMed 

    Google Scholar 
    Adeleye, M. A. et al. Long-term drivers of vegetation turnover in Southern Hemisphere temperate ecosystems. Glob. Ecol. Biogeogr. 30, 557–571 (2021).Article 

    Google Scholar 
    Kershaw, A. P., D’Costa, D. M., McEwen Mason, J. R. C. & Wagstaff, B. E. Palynological evidence for Quaternary vegetation and environments of mainland southeastern Australia. Quat. Sci. Rev. 10, 391–404 (1991).Article 

    Google Scholar 
    Colhoun, E. A. & Shimeld, P. W. in Peopled Landscapes: Archaeological and Biogeographic Approaches to Landscapes (eds. Haberle, S. G. & David, B.) 297–328 (ANU Press, 2012).Madani, N. et al. Future global productivity will be affected by plant trait response to climate. Sci. Rep. 8, 2870 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Squire, D. T. et al. Likelihood of unprecedented drought and fire weather during Australia’s 2019 megafires. npj Clim. Atmos. Sci. 4, 64 (2021).Article 

    Google Scholar 
    Ukkola, A. M., De Kauwe, M. G., Roderick, M. L., Abramowitz, G. & Pitman, A. J. Robust future changes in meteorological drought in CMIP6 projections despite uncertainty in precipitation. Geophys. Res. Lett. 47, e2020GL087820 (2020).Article 

    Google Scholar 
    Mori, A. S., Furukawa, T. & Sasaki, T. Response diversity determines the resilience of ecosystems to environmental change. Biol. Rev. 88, 349–364 (2013).Article 
    PubMed 

    Google Scholar 
    Arias, P. A. et al. In Climate Change 2021: The Physical Science Basis (eds. Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).Laliberté, E., Legendre, P. & Shipley, B. FD: measuring (FD) from multiple traits, and other tools for functional ecology. R package version 1.0-12 (2014).Laliberté, E. & Legendre, P. A distance-based framework for measuring from multiple traits. Ecology 91, 299–305 (2010).Article 
    PubMed 

    Google Scholar 
    Tilman, D. in Encyclopedia of Biodiversity (ed. Levin, S. A.) 109–120 (Elsevier, 2001).Fletcher, M.-S. & Moreno, P. I. Have the Southern Westerlies changed in a zonally symmetric manner over the last 14,000 years? A hemisphere-wide take on a controversial problem. Quat. Int. 253, 32–46 (2012).Article 

    Google Scholar 
    Markgraf, V., Bradbury, J. P. & Busby, J. R. Paleoclimates in Southwestern Tasmania during the last 13,000 years. PALAIOS 1, 368 (1986).Article 

    Google Scholar 
    Moros, M. et al. Hydrographic shifts south of Australia over the last deglaciation and possible interhemispheric linkages. Quat. Res. 102, 130–141 (2021).Article 

    Google Scholar 
    Perner, K. et al. Heat export from the tropics drives mid to late Holocene palaeoceanographic changes offshore southern Australia. Quat. Sci. Rev. 180, 96–110 (2018).Article 

    Google Scholar 
    Mariani, M. & Fletcher, M.-S. Long-term climate dynamics in the extra-tropics of the South Pacific revealed from sedimentary charcoal analysis. Quat. Sci. Rev. 173, 181–192 (2017).Article 

    Google Scholar 
    McWethy, D. B. et al. A conceptual framework for predicting temperate ecosystem sensitivity to human impacts on fire regimes. Glob. Ecol. Biogeogr. 22, 900–912 (2013).Article 

    Google Scholar 
    Baker, A. G., Catterall, C. & Benkendorff, K. Invading rain forest pioneers initiate positive fire suppression feedbacks that reinforce shifts from open to closed forest in eastern Australia. J. Veg. Sci. 32, e13102 (2021).Article 

    Google Scholar 
    Lambeck, K. & Chappell, J. Sea level change through the last glacial cycle. Science 292, 679–686 (2001).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sloss, C. R., Murray-Wallace, C. V. & Jones, B. G. Holocene sea-level change on the southeast coast of Australia: a review. Holocene 17, 999–1014 (2007).Article 

    Google Scholar 
    Adeleye, M. A. et al. Holocene heathland development in temperate oceanic Southern Hemisphere: key drivers in a global context. J. Biogeogr. 48, 1048–1062 (2021).Article 

    Google Scholar 
    McWethy, D. B., Haberle, S. G., Hopf, F. & Bowman, D. M. J. S. Aboriginal impacts on fire and vegetation on a Tasmanian island. J. Biogeogr. 44, 1319–1330 (2017).Article 

    Google Scholar 
    Hope, G. Vegetation and fire response to late Holocene human occupation in island and mainland north west Tasmania. Quat. Int. 59, 47–60 (1999).Article 

    Google Scholar 
    Sim, R. The Archaeology of Isolation? Prehistoric Occupation in the Furneaux Group of Islands, Bass Strait, Tasmania. PhD thesis, Australian National Univ. (1998).Lourandos, H. Intensification: a late Pleistocene-Holocene archaeological sequence from Southwestern Victoria. Archaeol. Ocean. 18, 81–94 (1983).Article 

    Google Scholar 
    Bowman, D. M. J. S. The impact of Aboriginal landscape burning on the Australian biota. New Phytol. 140, 385–410 (1998).Article 
    CAS 
    PubMed 

    Google Scholar 
    Iversen, J. in Systematics of Today (ed. Hedberg, O.) 210–215 (Acta Universitatis Upsaliensis/Uppsala Universitets Årsskrift, 1958).Colhoun, E. A. Application of Iversen’s glacial–interglacial cycle to interpretation of the late last glacial and Holocene vegetation history of western Tasmania. Quat. Sci. Rev. 15, 557–580 (1996).Article 

    Google Scholar 
    Adeleye, M. A., Haberle, S. G., Ondei, S. & Bowman, D. M. J. S. Ecosystem transformation following the mid-nineteenth century cessation of Aboriginal fire management in Cape Pillar, Tasmania. Reg. Environ. Change 22, 99 (2022).Article 

    Google Scholar 
    Mccann, K. The diversity–stability debate. Nature 405, 228–233 (2000).Article 
    CAS 
    PubMed 

    Google Scholar 
    Hallett, L. M., Stein, C. & Suding, K. N. Functional diversity increases ecological stability in a grazed grassland. Oecologia 183, 831–840 (2017).Article 
    PubMed 

    Google Scholar 
    Bello, Fde et al. Functional trait effects on ecosystem stability: assembling the jigsaw puzzle. Trends Ecol. Evol. 36, 822–836 (2021).Article 
    PubMed 

    Google Scholar 
    Lucini, F. A., Morone, F., Tomassone, M. S. & Makse, H. A. Diversity increases the stability of ecosystems. PLoS ONE 15, e0228692 (2020).Article 

    Google Scholar 
    Tilman, D., Reich, P. B. & Knops, J. M. H. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature 441, 629–632 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Gallagher, R. V., Hughes, L. & Leishman, M. R. Species loss and gain in communities under future climate change: consequences for functional diversity. Ecography 36, 531–540 (2013).Article 

    Google Scholar 
    Song, Y., Wang, P., Li, G. & Zhou, D. Relationships between and ecosystem functioning: a review. Acta Ecol. Sin. 34, 85–91 (2014).Article 
    CAS 

    Google Scholar 
    Li, W. et al. Plant can be independent of species diversity: observations based on the impact of 4-yrs of nitrogen and phosphorus additions in an alpine meadow. PLoS ONE 10, e0136040 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lewis, C. J., Huang, Y., Siems, S. T. & Manton, M. J. Wintertime orographic precipitation over western Tasmania. J. South. Hemisphere Earth Syst. Sci. 68, 22–40 (2018).Article 

    Google Scholar 
    Andrew, S. C. et al. Functional diversity of the Australian flora: strong links to species richness and climate. J. Veg. Sci. 32, e13018 (2021).Article 

    Google Scholar 
    Biswas, S. R. & Mallik, A. U. Species diversity and relationship varies with disturbance intensity. Ecosphere 2, art52 (2011).Article 

    Google Scholar 
    Gallagher, R. V. et al. A guide to using species trait data in conservation. One Earth 4, 927–936 (2021).Article 

    Google Scholar 
    Siefert, A. et al. A global meta-analysis of the relative extent of intraspecific trait variation in plant communities. Ecol. Lett. 18, 1406–1419 (2015).Article 
    PubMed 

    Google Scholar 
    Harris, S. & Kitchener, A. From Forest to Fjaeldmark. Descriptions of Tasmania’s Vegetation (Department of Primary Industries, Water and Environment, Tasmania, 2005).Adeleye, M. A., Haberle, S. G., McWethy, D., Connor, S. E. & Stevenson, J. Environmental change during the last glacial on an ancient land bridge of southeast Australia. J. Biogeogr. 48, 2946–2960 (2021).Article 

    Google Scholar 
    Hopf, F. V. L., Colhoun, E. A. & Barton, C. E. Late-glacial and Holocene record of vegetation and climate from Cynthia Bay, Lake St Clair, Tasmania. J. Quat. Sci. 15, 725–732 (2000).Article 

    Google Scholar 
    Stahle, L. N., Whitlock, C. & Haberle, S. G. A 17,000-year-long record of vegetation and fire from Cradle Mountain National Park, Tasmania. Front. Ecol. Evol 4, 82 (2016).Article 

    Google Scholar 
    Michael-Shawn, F. et al. The influence of climatic change, fire and species invasion on a Tasmanian temperate rainforest system over the past 18,000 years. Quat. Sci. Rev. 260, 106824 (2021).Article 

    Google Scholar 
    Climate and Water Availability in South-Eastern Australia: A Synthesis of Findings From Phase 2 of the South-Eastern Australian Climate initiative (SEACI) (CSIRO, 2012); https://doi.org/10.4225/08/584af3986fe96Australian Climate Influences (Commonwealth of Australia, Bureau of Meteorology, 2010); http://www.bom.gov.au/watl/about-weather-and-climate/australian-climate-influences.shtmlRisbey, J. S., Pook, M. J., McIntosh, P. C., Wheeler, M. C. & Hendon, H. H. On the remote drivers of rainfall variability in Australia. Mon. Weather Rev. 137, 3233–3253 (2009).Article 

    Google Scholar 
    Mariani, M., Fletcher, M.-S., Holz, A. & Nyman, P. ENSO controls interannual fire activity in southeast Australia. Geophys. Res. Lett. 43, 10891–10900 (2016).Article 

    Google Scholar 
    Mariani, M. & Fletcher, M.-S. The Southern Annular Mode determines interannual and centennial-scale fire activity in temperate southwest Tasmania, Australia. Geophys. Res. Lett. 43, 1702–1709 (2016).Article 

    Google Scholar 
    Herbert, A. V. & Harrison, S. P. Evaluation of a modern-analogue methodology for reconstructing Australian palaeoclimate from pollen. Rev. Palaeobot. Palynol. 226, 65–77 (2016).Article 

    Google Scholar 
    Blaauw, M. et al. rbacon: Age-depth modelling using Bayesian statistics. R package version 4.2.0 (2022).Hogg, A. G. et al. SHCal20 Southern Hemisphere calibration, 0–55,000 years cal BP. Radiocarbon 62, 759–778 (2020).Article 
    CAS 

    Google Scholar 
    Falster, D. et al. AusTraits, a curated plant trait database for the Australian flora. Sci. Data 8, 254 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pérez-Harguindeguy, N. et al. Corrigendum to: New handbook for standardised measurement of plant functional traits worldwide. Aust. J. Bot. 64, 715–716 (2016).Article 

    Google Scholar 
    Wright, I. J. et al. Global climatic drivers of leaf size. Science 357, 917–921 (2017).Article 
    CAS 
    PubMed 

    Google Scholar 
    Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).Article 
    CAS 
    PubMed 

    Google Scholar 
    Westoby, M., Falster, D. S., Moles, A. T., Vesk, P. A. & Wright, I. J. Plant ecological strategies: some leading dimensions of variation between species. Annu. Rev. Ecol. Syst. 33, 125–159 (2002).Article 

    Google Scholar 
    Moles, A. T. & Westoby, M. Seed size and plant strategy across the whole life cycle. Oikos 113, 91–105 (2006).Article 

    Google Scholar 
    Leishman, M. R. & Westoby, M. The role of seed size in seedling establishment in dry soil conditions—experimental evidence from semi-arid species. J. Ecol. 82, 249–258 (1994).Article 

    Google Scholar 
    Falster, D. S. & Westoby, M. Plant height and evolutionary games. Trends Ecol. Evol. 18, 337–343 (2003).Article 

    Google Scholar 
    Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).Article 
    PubMed 

    Google Scholar 
    Mason, N. W. H., Mouillot, D., Lee, W. G. & Wilson, J. B. Functional richness, functional evenness and functional divergence: the primary components of functional diversity. Oikos 111, 112–118 (2005).Article 

    Google Scholar 
    Pakeman, R. J. Functional trait metrics are sensitive to the completeness of the species’ trait data? Methods Ecol. Evol. 5, 9–15 (2014).Article 

    Google Scholar 
    Scheiner, S. M., Kosman, E., Presley, S. J. & Willig, M. R. Decomposing. Methods Ecol. Evol. 8, 809–820 (2017).Article 

    Google Scholar 
    Ripley, B. et al. MASS: Support functions and datasets for venables and Ripley’s MASS. R package version ??? (2022).Moy, C. M., Seltzer, G. O., Rodbell, D. T. & Anderson, D. M. Variability of El Niño/Southern Oscillation activity at millennial timescales during the Holocene epoch. Nature 420, 162–165 (2002).Article 
    CAS 
    PubMed 

    Google Scholar  More

  • in

    Ecological insights into soil health according to the genomic traits and environment-wide associations of bacteria in agricultural soils

    Doran JW. Soil health and global sustainability: translating science into practice. Agric Ecosyst Environ. 2002;88:119–27.Article 

    Google Scholar 
    Wander MM, Cihacek LJ, Coyne M, Drijber RA, Grossman JM, Gutknecht JLM, et al. Developments in Agricultural Soil Quality and Health: Reflections by the Research Committee on Soil Organic Matter Management. Front Environ Sci. 2019;7:1–9.Article 

    Google Scholar 
    Stewart RD, Jian J, Gyawali AJ, Thomason WE, Badgley BD, Reiter MS, et al. What we talk about when we talk about soil health. Agric Environ Lett. 2018;3:5–9.Article 

    Google Scholar 
    Rinot O, Levy GJ, Steinberger Y, Svoray T, Eshel G. Soil health assessment: A critical review of current methodologies and a proposed new approach. Sci Total Environ. 2019;648:1484–91.Article 
    CAS 

    Google Scholar 
    Hurisso TT, Culman SW, Zhao K. Repeatability and spatiotemporal variability of emerging soil health indicators relative to routine soil nutrient tests. Soil Sci Soc Am J. 2018;82:939–48.Article 
    CAS 

    Google Scholar 
    Lilburne L, Sparling G, Schipper L. Soil quality monitoring in New Zealand: Development of an interpretative framework. Agric Ecosyst Environ. 2004;104:535–44.Article 

    Google Scholar 
    Moebius-Clune BN, Moebius-Clune DJ, Gugino BK, Idowu OJ, Schindelbeck RR, Ristow AJ, et al. Comprehensive assessment of soil health – the Cornell framework manual, 3rd ed. Ithaca, NY:Cornell University; 2017.Fierer N, Wood SA, Bueno de Mesquita CP. How microbes can, and cannot, be used to assess soil health. Soil Biol Biochem. 2021;153:108111.Article 
    CAS 

    Google Scholar 
    Amsili JP, van Es HM, Schindelbeck RR. Cropping system and soil texture shape soil health outcomes and scoring functions. Soil Secur. 2021;4:100012.Article 

    Google Scholar 
    Wade J, Culman SW, Gasch CK, Lazcano C, Maltais-Landry G, Margenot AJ, et al. Rigorous, empirical, and quantitative: a proposed pipeline for soil health assessments. Soil Biol Biochem. 2022;170:108710.Article 
    CAS 

    Google Scholar 
    Simonin M, Voss KA, Hassett BA, Rocca JD, Wang SY, Bier RL, et al. In search of microbial indicator taxa: shifts in stream bacterial communities along an urbanization gradient. Environ Microbiol. 2019;21:3653–68.Article 

    Google Scholar 
    Bissett A, Brown MV, Siciliano SD, Thrall PH. Microbial community responses to anthropogenically induced environmental change: Towards a systems approach. Ecol Lett. 2013;16:128–39.Article 

    Google Scholar 
    Wilhelm RC, Cardenas E, Maas KR, Leung H, McNeil L, Berch S, et al. Biogeography and organic matter removal shape long-term effects of timber harvesting on forest soil microbial communities. ISME J. 2017;11:2552–68.Article 

    Google Scholar 
    Gibbons SM, Scholz M, Hutchison AL, Dinner AR, Gilbert JA, Colemana ML, et al. Disturbance regimes predictably alter diversity in an ecologically complex bacterial system. MBio. 2016;7:1–10.Article 

    Google Scholar 
    Trivedi P, Delgado-Baquerizo M, Anderson IC, Singh BK. Response of soil properties and microbial communities to agriculture: Implications for primary productivity and soil health indicators. Front Plant Sci. 2016;7:1–13.Article 

    Google Scholar 
    Jiao S, Xu Y, Zhang J, Hao X. Core microbiota in agricultural soils and their potential associations with nutrient cycling. mSystems. 2019;4:1–16.Article 

    Google Scholar 
    Chang HX, Haudenshield JS, Bowen CR, Allen R, Iii W, Parnell JJ, et al. Metagenome-wide association study and machine learning prediction of bulk soil microbiome and crop productivity. Front Microbiol. 2017;8:519.Article 

    Google Scholar 
    Trivedi P, Delgado-Baquerizo M, Jeffries TC, Trivedi C, Anderson IC, Lai K, et al. Soil aggregation and associated microbial communities modify the impact of agricultural management on carbon content. Environ Microbiol. 2017;19:3070–86.Article 
    CAS 

    Google Scholar 
    Armbruster M, Goodall T, Hirsch PR, Ostle N, Puissant J, Fagan KC, et al. Bacterial and archaeal taxa are reliable indicators of soil restoration across distributed calcareous grasslands. Eur J Soil Sci. 2021;72:2430–44.Rieke EL, Cappellazzi SB, Cope M, Liptzin D, Mac Bean G, Greub KLH, et al. Linking soil microbial community structure to potential carbon mineralization: A continental scale assessment of reduced tillage. Soil Biol Biochem. 2022;168:108618.Article 
    CAS 

    Google Scholar 
    Wilhelm RC, Van Es HM, Buckley DH. Predicting measures of soil health using the microbiome and supervised machine learning. Soil Biol Biochem. 2022;164:108472.Article 
    CAS 

    Google Scholar 
    Douglas GM, Maffei VJ, Zaneveld J, Yurgel SN, Brown JR, Taylor CM, et al. PICRUSt2: An improved and customizable approach for metagenome inference 2. bioRxiv. 2020. https://doi.org/10.1101/672295.Gravuer K, Eskelinen A. Nutrient and rainfall additions shift phylogenetically estimated traits of soil microbial communities. Front Microbiol. 2017;8:1–16.Article 

    Google Scholar 
    Chen Y, Maier RM, Barberán A, Neilson JW, Kushwaha P, Maier RM, et al. Life-history strategies of soil microbial communities in an arid ecosystem. ISME J. 2021;15:649–57.Article 
    CAS 

    Google Scholar 
    Fierer N. Embracing the unknown: Disentangling the complexities of the soil microbiome. Nat Rev Microbiol. 2017;15:579–90.Article 
    CAS 

    Google Scholar 
    Malik AA, Martiny JBHH, Brodie EL, Martiny AC, Treseder KK, Allison SD, et al. Defining trait-based microbial strategies with consequences for soil carbon cycling under climate change. ISME J. 2020;14:1–9.Article 
    CAS 

    Google Scholar 
    Roller BRK, Stoddard SF, Schmidt TM. Exploiting rRNA operon copy number to investigate bacterial reproductive strategies. Nat Microbiol. 2016;1:1–7.Nunan N, Schmidt H, Raynaud X, Schmidt H. The ecology of heterogeneity: Soil bacterial communities and C dynamics. Philos Trans R Soc B Biol Sci. 2020;375:20190249.Article 
    CAS 

    Google Scholar 
    Grime JP. Evidence for the existence of three primary strategies in plants and its relevance for ecological and evolutionary theory. Am Nat. 1977;111:1169–94.Article 

    Google Scholar 
    Barnett S, Youngblut ND, Koechli CN, Buckley DH. Multisubstrate DNA stable isotope probing reveals guild structure of bacteria that mediate soil carbon cycling. PNAS. 2021;118:e2115292118.Wilhelm RC, Pepe-Ranney C, Weisenhorn P, Lipton M, Buckley DH. Competitive exclusion and metabolic dependency among microorganisms structure the cellulose economy of an agricultural soil. MBio. 2021;12:1–19.Article 

    Google Scholar 
    Schmidt R, Gravuer K, Bossange AV, Mitchell J, Scow K. Long-term use of cover crops and no-till shift soil microbial community life strategies in agricultural soil. PLoS ONE. 2018;13:1–19.Article 

    Google Scholar 
    Neal AL, Hughes D, Clark IM, Jansson JK, Hirsch PR. Microbiome Aggregated Traits and Assembly Are More Sensitive to Soil Management than Diversity. mSystems 2021;6:e0105620.Lupatini M, Korthals GW, de Hollander M, Janssens TKS, Kuramae EE. Soil microbiome is more heterogeneous in organic than in conventional farming system. Front Microbiol. 2017;7:1–13.Article 

    Google Scholar 
    Koechli C, Campbell AN, Pepe-ranney C, Buckley DH. Assessing fungal contributions to cellulose degradation in soil by using high- throughput stable isotope probing. Soil Biol Biochem. 2019;130:150–8.Article 
    CAS 

    Google Scholar 
    Furtak K, Grządziel J, Gałązka A, Niedźwiecki J. Prevalence of unclassified bacteria in the soil bacterial community from floodplain meadows (fluvisols) under simulated flood conditions revealed by a metataxonomic approachss. Catena. 2020;188:104448.Article 
    CAS 

    Google Scholar 
    Schmidt R, Mitchell J, Scow K. Cover cropping and no-till increase diversity and symbiotroph: saprotroph ratios of soil fungal communities. Soil Biol Biochem. 2019;129:99–109.Article 
    CAS 

    Google Scholar 
    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.Article 
    CAS 

    Google Scholar 
    Callahan BJ, McMurdie PJ, Holmes SP. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 2017;11:2639–43.Article 

    Google Scholar 
    Levy R, Borenstein E. Reverse Ecology: From systems to environments and back. Adv Exp Med Biol. 2012;751:329–45.Article 
    CAS 

    Google Scholar 
    Nguyen NH, Song Z, Bates ST, Branco S, Tedersoo L, Menke J, et al. FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 2016;20:241–8.Article 

    Google Scholar 
    Hamilton JP, Neeno-Eckwall EC, Adhikari BN, Perna NT, Tisserat N, Leach JE, et al. The Comprehensive Phytopathogen Genomics Resource: a web-based resource for data-mining plant pathogen genomes. Database. 2011;2011:bar053.Detheridge AP, Brand G, Fychan R, Crotty FV, Sanderson R, Griffith GW, et al. The legacy effect of cover crops on soil fungal populations in a cereal rotation. Agric Ecosyst Environ. 2016;228:49–61.Article 

    Google Scholar 
    McKenna TP, Crews TE, Kemp L, Sikes BA. Community structure of soil fungi in a novel perennial crop monoculture, annual agriculture, and native prairie reconstruction. PLoS ONE. 2020;15:1–15.Article 

    Google Scholar 
    Rocca JD, Simonin M, Blaszczak JR, Ernakovich JG, Gibbons SM, Midani FS, et al. The Microbiome Stress Project: Toward a global meta-analysis of environmental stressors and their effects on microbial communities. Front Microbiol. 2019;9:3272.Article 

    Google Scholar 
    Ramirez KS, Knight CG, De Hollander M, Brearley FQ, Constantinides B, Cotton A, et al. Detecting macroecological patterns in bacterial communities across independent studies of global soils. Nat Microbiol. 2018;3:189–96.Article 
    CAS 

    Google Scholar 
    Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551:457–63.Article 
    CAS 

    Google Scholar 
    Lagkouvardos I, Joseph D, Kapfhammer M, Giritli S, Horn M, Haller D, et al. IMNGS: A comprehensive open resource of processed 16S rRNA microbial profiles for ecology and diversity studies. Sci Rep. 2016;6:1–9.Article 

    Google Scholar 
    Jurburg SD, Konzack M, Eisenhauer N, Heintz-Buschart A. The archives are half-empty: a field-wide assessment of the availability of microbial community sequencing data. Commun Biol. 2020;3:474.Emerson JB, Everhart SE, Eversole K, Frost KE, Herr JR, Huerta AI, et al. Community-driven metadata standards for agricultural microbiome research. Phytobiomes J. 2020; 4:115-121.Anderson TH, Martens R. DNA determinations during growth of soil microbial biomasses. Soil Biol Biochem. 2013;57:487–95.Article 
    CAS 

    Google Scholar 
    Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the Miseq Illumina sequencing platform. Appl Environ Microbiol. 2013;79:5112–20.Article 
    CAS 

    Google Scholar 
    Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7.Article 
    CAS 

    Google Scholar 
    Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41:590–6.Article 

    Google Scholar 
    Harrell F, Dupont C. Hmisc: Harrell miscellaneous. R Package 2015.Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc. 1995;57:289–300.
    Google Scholar 
    Weiss S, Van Treuren W, Lozupone C, Faust K, Friedman J, Deng Y, et al. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. ISME J. 2016;10:1669–81.Article 
    CAS 

    Google Scholar 
    Mills RH, Dulai PS, Vázquez-Baeza Y, Sauceda C, Daniel N, Gerner RR, et al. Multi-omics analyses of the ulcerative colitis gut microbiome link Bacteroides vulgatus proteases with disease severity. Nat Microbiol. 2022;7:262–76.Article 
    CAS 

    Google Scholar 
    De Cáceres M, Legendre P, De Caceres M, Legendre P. Associations between species and groups of sites: indices and statistical inference. Ecology. 2009;90:3566–74.Article 

    Google Scholar 
    Markowitz VM, Ivanova NN, Szeto E, Palaniappan K, Chu K, Dalevi D, et al. IMG/M: A data management and analysis system for metagenomes. Nucleic Acids Res. 2008;36:534–8.Article 

    Google Scholar 
    Stoddard SF, Smith BJ, Hein R, Roller BRK, Schmidt M. rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Res. 2015;43:593–8.R Core Team. R: a language and environment for statistical computing. R Foundation. 2020.Wickham H. Reshaping data with the reshape package. J Stat Soft. 2007;21:1–20.Article 

    Google Scholar 
    Wickham H. The split-apply-combine strategy for data analysis. J Stat Soft. 2009;40:1–29.
    Google Scholar 
    Wickham H. Elegant graphics for data analysis. Media. 2009;35:211.
    Google Scholar 
    McMurdie PJ, Holmes S. Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 2013;8:e61217.Grömping U. Relative importance for linear regression in R: the package relaimpo. J Stat Softw. 2006;17:1–27.Article 

    Google Scholar 
    Bastian M, Heymann S. Gephi: an open source software for exploring and manipulating networks. Proc Int AAAI Conf Web Soc Media. 2009:361–2.Hu Y. Efficient, high-quality force-directed graph drawing. Math J. 2006;10:37–71.
    Google Scholar 
    Ranea JAG, Grant A, Thornton JM, Orengo CA. Microeconomic principles explain an optimal genome size in bacteria. Trends Genet. 2005;21:21–5.Article 
    CAS 

    Google Scholar 
    Nielsen DA, Fierer N, Geoghegan JL, Gillings MR, Gumerov V, Madin JS, et al. Aerobic bacteria and archaea tend to have larger and more versatile genomes. Oikos. 2021;130:501–11.Article 
    CAS 

    Google Scholar 
    Chen Y, Leung PM, Wood JL, Bay SK, Kessler AJ, Shelley G, et al. Metabolic flexibility allows bacterial habitat generalists to become dominant in a frequently disturbed ecosystem. ISME J. 2021;15:2986–3004.Article 
    CAS 

    Google Scholar 
    Brewer TE, Handley KM, Carini P, Gilbert JA, Fierer N. Genome reduction in an abundant and ubiquitous soil bacterium ‘Candidatus Udaeobacter copiosus’. Nat Microbiol. 2016;2:16198.Willms IM, Rudolph AY, Göschel I, Bolz SH, Schneider D, Penone C, et al. Globally Abundant “Candidatus Udaeobacter” Benefits from Release of Antibiotics in Soil and Potentially Performs Trace Gas Scavenging. mSphere. 2020;5:1–17.Article 

    Google Scholar 
    Kaboré OD, Godreuil S, Drancourt M. Planctomycetes as host-associated bacteria: a perspective that holds promise for their future isolations, by mimicking their native environmental niches in clinical microbiology laboratories. Front Cell Infect Microbiol. 2020;10:1–19.Article 

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

    Google Scholar 
    Zhalnina K, De Quadros PD, Gano KA, Davis-Richardson A, Fagen JR, Brown CT, et al. Ca. Nitrososphaera and Bradyrhizobium are inversely correlated and related to agricultural practices in long-term field experiments. Front Microbiol. 2013;4:1–13.Article 

    Google Scholar 
    Land M, Hauser L, Jun S, Nookaew I, Leuze MR, Ahn T, et al. Insights from 20 years of bacterial genome sequencing. Funct Integr Genom. 2015;15:141–61.Article 
    CAS 

    Google Scholar 
    Gil R, Latorre A, Postal A. Factors behind junk DNA in bacteria. Genes (Basel). 2012;3:634–50.Article 

    Google Scholar 
    Williamson KE, Radosevich M, Wommack KE. Abundance and diversity of viruses in six Delaware soils. Appl Environ Microbiol. 2005;71:3119–25.Article 
    CAS 

    Google Scholar 
    Williamson KE, Corzo KA, Drissi CL, Buckingham JM, Thompson CP, Helton RR. Estimates of viral abundance in soils are strongly influenced by extraction and enumeration methods. Biol Fertil Soils. 2013;49:857–69.Article 

    Google Scholar 
    Van Goethem MW, Swenson TL, Trubl G, Roux S, Northen TR. Characteristics of wetting-induced bacteriophage blooms in biological soil crust. MBio. 2019;10:e02287-19.Westra ER, Van Houte S, Gandon S, Whitaker R, Van Houte S, Gandon S, et al. The ecology and evolution of microbial CRISPR-Cas adaptive immune systems. Philos Trans R Soc B Biol Sci. 2019;374:20190101.Martinez-Gutierrez CA, Aylward FO. Genome size distributions in bacteria and archaea are strongly linked to evolutionary history at broad phylogenetic scales. PLoS Genet. 2022;18:1–17.Article 

    Google Scholar 
    Saifuddin M, Bhatnagar JM, Finzi AC, Segrè D, Finzi AC. Microbial carbon use efficiency predicted from genome-scale metabolic models. Nat Commun. 2019;10:1–10.Article 
    CAS 

    Google Scholar  More

  • in

    Exposure of aquatic organisms to natural radionuclides in irrigation drains, Qena, Egypt

    Samples collection and preparationFreshwater and sediment samples were collected from 5 irrigation drains (EL-Shikah, EL- Tramsa, EL-Mahrosa, EL-Aslia, and EL-Rawy) located in the geographical area of Qena city, the capital of Qena Governorate, 600 km south of Cairo, (Figs. 1 and 2). 3 sites inside each drain were randomly selected as sampling site; one of these sites represents the outlet of the drain into the Nile River. In addition, one site facing each drain in the main stream of the Nile River was selected to collect freshwater only, thus the total number of samples are 20 freshwater and 15 sediment samples.Figure 1Location map of the area under study (ArcGIS software 10.8.1; ArcGIS Online).Full size imageFigure 2Irrigation drain under study.Full size imagePolyethylene Marinelli beakers with a capacity of 1.4 L are used as collection and measuring containers. The beakers were washed with dilute hydrochloric acid and distilled water before use, filled to brim, and then pressed the tight lid to eliminate the internal air. Drops of HNO3 were added to the samples to prevent the adhesive of radionuclides with bottle walls8.Sediment samples were collected by Ekman grab sediment sampler. The collected samples were dried using electrical oven at a temperature of 105℃ for 24 h, then sieved through 200 mesh size. The dried samples were filled in hermetical sealed 500 ml polyethylene beakers. The prepared water and sediment samples were stored for 4 weeks to reach a secular equilibrium of radium and thorium with their progenies9.Measuring systemsGamma-ray spectrometer consisting of ″3 × 3″ NaI (Tl) detector enclosed in 5 cm thick cylindrical lead shield to reduce the background radiation and connected with 1024 multichannel analyzer was used. The spectrometer was calibrated for energy using 60Co and 137Cs standard point sources, and calibrated for efficiency using a multi-nuclides standard solution which covers a wide range of energy10. The spectrum was accumulated from each sample over 24 h and analyzed by Maestro software. The background was measured under the same condition of sample measurement.226Ra was determined using 214Bi and 214Pb gamma-lines at 609 keV and 352 keV, respectively, while 232Th from gamma-lines of 228Ac (911 keV) and 212Pb (238 keV). 40K was determined from its single gamma-line at 1460 keV. The activity concentration was calculated using the following formula (Eq. 1)11.$$A = frac{{C_{n} }}{{T times varepsilon { } times {text{P}} times {text{V }}left( {{text{or}}} right){text{M}}}}$$
    (1)

    where A is the activity concentration (Bq kg−1) or (Bq l−1), Cn is the net counts under a given peak area, T the sample counting time, (varepsilon) is the detection efficiency at measured energy, P is the emission probability and V is the sample volume in liter, M is the sample mass in kilogram. Minimum detectable activity (MDA) was estimated according to Currie definition using Eq. 212 and the MDA values were 0.031, 0.035 and 1.94 Bq L−1 for 226Ra, 232Th, and 40K, respectively.$${text{MDA}} = frac{2.71 + 465sqrt B }{{T times varepsilon times P times V}}$$
    (2)

    where B is the background counts under a given peak area,T,ɛ, P, and V are defined above.Doses for aquatic organismsThe external and internal absorbed dose rate for aquatic organisms (Phytoplankton, Mollusca, and Crustacean) in the studied irrigation drains was calculated based on the measured activity concentrations of 226Ra, 232Th, and 40K in environmental media (water and sediment) and using dose conversion coefficients of a given radionuclide for the reference organisms according to the method outlined by Brown et al. described below13,14.$$begin{aligned}& left( {Sediment,, conc. ,,wet} right)_{radionuclide} = (Sediment ,,conc. ,,dry)_{radionuclide} times left( {solids ,,fraction} right) \& qquad qquad + (water ,,conc.)_{radionuclide} times (1 – left( {solids ,,fraction} right). \ end{aligned}$$
    (3)
    $$begin{aligned}& left( {user2{External ,,dose ,,rate}} right)_{radionuclide,, organism} = DPUC_{radionuclide, ,organism}^{external} times left[ {Sediment ,conc. ,wet_{radionuclide} times left( {fsed_{organism} + fsedsur_{organism} /2} right)} right. \& quad quad left. { + left( {fwater_{organism} + fsedsur_{organism} /2} right) times water ,conc._{radionuclide } /1000} right] \ end{aligned}$$
    (4)
    $$left( {user2{Internal,dose,rate}} right)_{{radionuclide,,organism}} = ~left( {water,conc.} right)_{{radionuclide}} times CF_{{radionuclide}}^{{organism}} times DPUC_{{radionuclide,,organism}}^{{internal}}$$
    (5)

    where sediment conc. is the sediment activity concentration of a given radionuclide in Bq kg−1,water conc. is the water activity concentration of a given radionuclide in Bq m−3, CF is distribution coefficient factors for given radionuclide in freshwater sediment in m3 kg−1, DPUC is the dose rate per unit concentration coefficients (fresh weight) in μGy h−1 per Bq kg−1 weighted for radiation type (alpha = 10, low energy beta = 3, and high energy beta and gamma = 1), solids fraction of wet sediment (0.4), fsed organism is the time fraction spends by organism in sediment, fsedsur organism is the time fraction spends by organism at the sediment/water interface, fwater organism is the time fraction spends by organism in the water column. All parameters used in calculation are taken from Pröhl (2003)15 and Vives i Battle et al. (2004)16. The total dose is then calculated by summating the external and internal doses. More