More stories

  • in

    Traits of a mussel transmissible cancer are reminiscent of a parasitic life style

    1.Aktipis, A. The Cheating Cell: How Evolution Helps Us Understand and Treat Cancer (Princeton University Press, 2020).Book 

    Google Scholar 
    2.Martinez-Outschoorn, U. E. et al. Stromal–epithelial metabolic coupling in cancer: integrating autophagy and metabolism in the tumor microenvironment. Int. J. Biochem. Cell. B. 43(7), 1045–1051. https://doi.org/10.1016/j.biocel.2011.01.023 (2011).CAS 
    Article 

    Google Scholar 
    3.Ujvari, B. et al. Cancer and life-history traits: lessons from host-parasite interactions. Parasitology 143, 533–541. https://doi.org/10.1017/S0031182016000147 (2016).Article 
    PubMed 

    Google Scholar 
    4.Overstreet, R. M. & Lotz, J. M. Host-symbiont relationships: understanding the change from guest to pest. In The Rasputin Effect: Why Commensals and Symbionts Become Parasitic. Advances in Environmental Microbiology (ed. Hurst, C.) (Springer, Cham, 2016). https://doi.org/10.1007/978-3-319-28170-4_2.Chapter 

    Google Scholar 
    5.Combes, C. Parasitism: The Ecology and Evolution of Intimate Inter-actions (University of Chicago Press, 2001).
    Google Scholar 
    6.Dujon, A. M. et al. Transmissible cancers in an evolutionary Perspective. iScience 23(7), 101269. https://doi.org/10.1016/j.isci.2020.101269 (2020).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    7.Murgia, C., Pritchard, J. K., Kim, S. Y., Fassati, A. & Weiss, R. A. Clonal origin and evolution of a transmissible cancer. Cell 126(3), 477–487. https://doi.org/10.1016/j.cell.2006.05.051 (2006).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    8.Rebbeck, C. A., Thomas, R., Breen, M., Leroi, A. M. & Burt, A. Origins and evolution of a transmissible cancer. Evolution 63(9), 2340–2349. https://doi.org/10.1111/j.1558-5646.2009.00724.x (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    9.Pearse, A. M. & Swift, K. Allograft theory: transmission of devil facial-tumor disease. Nature 439(7076), 549. https://doi.org/10.1038/439549a (2006).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    10.Pye, R. J. et al. A second transmissible cancer in Tasmanian devils. Proc. Natl. Acad. Sci. USA 113(2), 374–379. https://doi.org/10.1073/pnas.1519691113 (2016).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    11.Metzger, M. J., Reinisch, C., Sherry, J. & Goff, S. P. Horizontal transmission of clonal cancer cells causes leukemia in soft-shell clams. Cell 161(2), 255–263. https://doi.org/10.1016/j.cell.2015.02.042 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    12.Metzger, M. J. et al. Widespread transmission of independent cancer lineages within multiple bivalve species. Nature 534(7609), 705–709. https://doi.org/10.1038/nature18599 (2016).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    13.Yonemitsu, M. A. et al. A single clonal lineage of transmissible cancer identified in two marine mussel species in South America and Europe. ELife 8, 1029. https://doi.org/10.7554/eLife.47788 (2019).Article 

    Google Scholar 
    14.Garcia-Souto, D. et al. Mitochondrial genome sequencing of marine leukemias reveals cancer contagion between clam species in the Seas of Southern Europe. BioRxiv https://doi.org/10.1101/2021.03.10.434714 (2021).Article 

    Google Scholar 
    15.Hammel, M. et al. Prevalence and polymorphism of a mussel transmissible cancer in Europe. Mol. Ecol. 2, 1–16. https://doi.org/10.1111/mec.16052 (2021).CAS 
    Article 

    Google Scholar 
    16.Skazina, M. et al. First description of a widespread Mytilus trossulus-derived bivalve transmissible cancer lineage in M. trossulus itself. Sci. Rep. 11(5809), 56930 (2021).
    Google Scholar 
    17.Burioli, E. A. V. et al. Implementation of various approaches to study the prevalence, incidence and progression of disseminated neoplasia in mussel stocks. J. Invertebr. Patho. 168, 107271. https://doi.org/10.1016/j.jip.2019.107271 (2019).CAS 
    Article 

    Google Scholar 
    18.Murray, M., James, Z. H. & Martin, W. B. A study of the cytology and karyotype of the canine transmissible venereal tumour. Res. Vet. Sci. 10(6), 565–572. https://doi.org/10.1016/50034-5288(18)34394-7 (1969).CAS 
    Article 
    PubMed 

    Google Scholar 
    19.Hamede, R. K., McCallum, H. & Jones, M. Biting injuries and transmission of Tasmanian devil facial tumour disease. J. Anim. Ecol. 82(1), 182–190 (2013).Article 

    Google Scholar 
    20.Sunila, I. & Farley, C. Environmental limits for survival of sarcoma cells from the soft-shell clam Mya arenaria. Dis. Aquat. Organ. 7, 111–115. https://doi.org/10.3354/dao007111 (1989).Article 

    Google Scholar 
    21.Carballal, M. J., Barber, B. J., Iglesias, D. & Villalba, A. Neoplastic diseases of marine bivalves. J. Invertebr. Pathol. 131, 83–106. https://doi.org/10.1016/J.JIP.2015.06.004 (2015).Article 
    PubMed 

    Google Scholar 
    22.Carella, F., Figueras, A., Novoa, B. & De Vico, G. Cytomorphology and PCNA expression pattern in bivalves Mytilus galloprovincialis and Cerastoderma edule with haemic neoplasia. Dis. Aquat. Org. 105, 81–87. https://doi.org/10.3354/dao02612 (2013).Article 

    Google Scholar 
    23.Baudoin, M. Host castration as a parasitic strategy. Evolution 29, 335–352. https://doi.org/10.1111/j.1558-5646.1975.tb00213.x (1975).Article 
    PubMed 

    Google Scholar 
    24.Alderman, D. J., Van Banning, P. & Perez-Colomer, A. Two abnormal European oyster (Ostrea edulis) mortalities associated with an abnormal haemocytic condition. Aquaculture 10(4), 335–340. https://doi.org/10.1016/0044-8486(77)90124-7 (1977).Article 

    Google Scholar 
    25.Cosson-Mannevy, M. A., Wong, C. S. & Cretney, W. J. Putative neoplastic disorders in mussels (Mytilus edulis) from southern Vancouver Island waters, British Columbia. J. Invertebr. Pathol. 44(2), 151–160. https://doi.org/10.1016/0022-2011(84)90006-5 (1984).Article 

    Google Scholar 
    26.Brousseau, D. J. Seasonal aspects of sarcomatous neoplasia in Mya arenaria (soft-shell clam) from Long Island Sound. J. Invertebr. Pathol. 50(3), 269–276. https://doi.org/10.1016/0022-2011(87)90092-9 (1987).CAS 
    Article 
    PubMed 

    Google Scholar 
    27.Peters, E. C. Recent investigations on the disseminated sarcomas of marine bivalve molluscs. In: W. S. Fisher, editor. Diseases processes in marine bivalve mollusc. Washington, DC: special publication No. 18, American Fisheries Society. pp. 74–92 (1988).28.Ford, S. E., Barber, B. J. & Marks, E. Disseminated neoplasia in juvenile Eastern oyster Crassostrea virginica, and its relationship to the reproductive cycle. Dis. Aquat. Org. 28, 73–77. https://doi.org/10.3354/dao028073 (1997).Article 

    Google Scholar 
    29.Barber, B. J. Neoplastic diseases of commercially important marine bivalves. Aquat. Living Resour. 17, 449–466. https://doi.org/10.1051/alr:2004052 (2004).Article 

    Google Scholar 
    30.Randriananja, G. Evolution de la maturation de Mytilus edulis sur deux sites d’élevage du pertuis Breton : bouchots et filières. https://archimer.ifremer.fr/doc/00446/55762/57424.pdf (2006).31.Levitan, D. R. Sperm limitation, gamete competition and sexual selection in external fertilizers (eds. Birkhead, T. R., Moller, A. P.) 175–217. Sperm competition and sexual selection (Academic Press, 1998).32.Arzul, I. et al. Effects of temperature and salinity on the survival of Bonamia ostreae, a parasite infecting flat oysters Ostrea edulis. Dis. Aquat. Organ. 85, 67–75. https://doi.org/10.3354/dao02047 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    33.Greaves, M. & Maley, C. C. Clonal evolution in cancer. Nature 481(7381), 306–313. https://doi.org/10.1038/nature10762 (2012).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    34.Scott, J. & Marusyk, A. Somatic clonal evolution: a selection-centric perspective. Biochim. Biophys. Acta Rev. Cancer 1867(2), 139–150 (2017).CAS 
    Article 

    Google Scholar 
    35.Moore, M. N. & Lowe, D. M. The cytology and cytochemistry of the hemocytes of Mytilus edulis and their response to experimentally injected carbon particles. J. Invertebr. Pathol. 29, 18–30. https://doi.org/10.1016/0022-2011(77)90167-7 (1977).CAS 
    Article 
    PubMed 

    Google Scholar 
    36.Rasmussen, L. P. D., Hage, E. & Karlog, O. An electron microscope study of the circulating leucocytes of the marine mussel, Mytilus edulis. J. Invertebr. Pathol. 45, 158–167. https://doi.org/10.1016/0022-2011(85)90005-9 (1985).Article 

    Google Scholar 
    37.Carballal, M. J., López, M. C., Azevedo, C. & Villalba, A. Hemolymph cell types of the mussel Mytilus galloprovincialis. Dis. Aquat. Org. 29, 127–135. https://doi.org/10.3354/dao029127 (1997).Article 

    Google Scholar 
    38.Frei, E. 3rd. & Freireich, E. J. Progress and perspectives in the chemotherapy of acute leukemia. Adv. Chemother. 2, 269–298. https://doi.org/10.1016/b978-1-4831-9930-6.50011-3 (1965).CAS 
    Article 
    PubMed 

    Google Scholar 
    39.Ellison, R. R. & Murphy, M. L. “Apparent doubling time” of leukemic cells in marrow. Clin. Res. 12, 284 (1964).
    Google Scholar 
    40.Hirt, A., Schmid, A. M., Ammann, R. & Leibungut, K. In pediatric lymphoblastic leukemia of B-Cell origin, a small population of primitive blast cells is noncycling, suggesting them to be leukemia stem cell candidates. Pediatr. Res. 69, 194–199. https://doi.org/10.1203/PDR.0b013e3182092716 (2011).Article 
    PubMed 

    Google Scholar 
    41.Shimomatsuya, T., Tanigawa, N. & Muraoka, R. Proliferative activity of human tumors: assessment using bromodeoxyuridine and flow cytometry. Jpn. J. Cancer Res. 82(3), 357–362. https://doi.org/10.1111/j.1349-7006.1991.tb01854.x (1991).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    42.Ford, S., Schotthoefer, A. & Spruck, C. In vivo dynamics of the microparasite Perkinsus marinus during progression and regression of infections in Eastern oysters. J. Parasitol. 85(2), 273–282. https://doi.org/10.2307/3285632 (1999).CAS 
    Article 
    PubMed 

    Google Scholar 
    43.Caza, F., Bernet, E., Veyrier, F. J., Betoulle, S. & St-Pierre, Y. Hemocytes released in seawater act as Troyan horses for spreading of bacterial infections in mussels. Sci. Rep. 10, 19696 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    44.McCallum, H. I. et al. Does terrestrial epidemiology apply to marine systems?. Trends Ecol. Evol. 19(11), 585–591. https://doi.org/10.1016/j.tree.2004.08.009 (2004).Article 

    Google Scholar 
    45.Ewald, P. W. Evolutionary biology and the treatment of signs and symptoms of infectious disease. J. Theor. Biol. 86(1), 169–176. https://doi.org/10.1016/0022-5193(80)90073-9 (1980).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    46.Poulin, R. Chapter 5-Parasite Manipulation of Host Behavior: An Update and Frequently Asked Questions (eds: Brockmann, H. J., Roper, T. J., Naguib, M., Wynne-Edwards, K. E., Mitani, J. C., Simmons, L. W.). Advances in the Study of Behavior, Academic Press 41, 151–186. https://doi.org/10.1016/S0065-3454(10)41005-0 (2010).47.Cremonte, F., Vázquez, N. & Silva, M. R. Gonad atrophy caused by disseminated neoplasia in Mytilus chilensis cultured in the Beagle Channel, Tierra Del Fuego Province, Argentina. J. Shellfish Res. 30, 845–849. https://doi.org/10.2983/035.030.0325 (2011).Article 

    Google Scholar 
    48.Tissot, T. et al. Host manipulation by cancer cells: expectations, facts, and therapeutic implications. BioEssays 38(3), 276–285. https://doi.org/10.1002/bies/201500163 (2016).Article 
    PubMed 

    Google Scholar 
    49.Thomas, F., Guégan, J. F., Michalakis, Y. & Renaud, F. Parasites and host life-history traits: implications for community ecology and species co-existence. Int. J. Parasitol. 30(5), 669–674. https://doi.org/10.1016/s0020-7519(00)00040-0 (2000).CAS 
    Article 
    PubMed 

    Google Scholar 
    50.Charles, M. Etude des pathogènes, des conditions physiologiques et pathologiques impliqués dans les mortalités anormales de moules (Mytilus sp.). Biologie animale. Normandie Université. https://tel.archives-ouvertes.fr/tel-0.053331 (2019).51.Anderson, R. M. & May, R. M. Population biology of infectious diseases: part I. Nature 280, 361–367. https://doi.org/10.1038/280361a0 (1979).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    52.Kuris, A. M. Trophic interactions: similarity of parasitic castrators to parasitoids. Q. Rev. Biol. 49, 129–148 (1974).Article 

    Google Scholar 
    53.Faure, M. F., David, P., Bonhomme, F. & Bierne, N. Genetic hitchhiking in a subdivided population of Mytilus edulis. BMC Evol. Biol. 8, 164. https://doi.org/10.1186/1471-2148-8-164 (2008).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    54.Bierne, N. The distinctive footprints of local hitchhiking in a varied environment and global hitchhiking in a subdivided population. Evolution 64(11), 3254–3272. https://doi.org/10.1111/j.1558-5646.2010.01050.x (2010).CAS 
    Article 
    PubMed 

    Google Scholar 
    55.Suquet, M. et al. Anesthesia in Pacific oyster Crassostrea gigas. Aquat. Living Resour. 22, 29–34. https://doi.org/10.1051/alr/2009006 (2009).CAS 
    Article 

    Google Scholar 
    56.Lubet, P. Recherches sur le cycle sexuel et l’émission des gamètes chez les Mytilidés et les Pectinidés. Rev Trav Inst Pêches marit. 23(4), 390–548 (1959).
    Google Scholar 
    57.Bierne, N. et al. Introgression patterns in the mosaic hybrid zone between Mytilus edulis and M galloprovincialis. Mol. Ecol. 12(2), 447–61. https://doi.org/10.1046/j.1365-294x.2003.01730.x (2003).CAS 
    Article 
    PubMed 

    Google Scholar  More

  • in

    Global predictors of language endangerment and the future of linguistic diversity

    1.Rehg, K. L. & Campbell, L. The Oxford Handbook of Endangered Languages (Oxford Univ. Press, 2018).2.Romaine, S. in Language and Poverty (eds Harbert, W. et al.) Ch. 8 (Multilingual Matters, 2009).3.Sallabank, J. & Austin, P. The Cambridge Handbook of Endangered Languages (Cambridge Univ. Press, 2011).4.Sutherland, W. J. Parallel extinction risk and global distribution of languages and species. Nature 423, 276–279 (2003).CAS 
    Article 

    Google Scholar 
    5.Eberhard, D. M., Simons, G. F. & Fennig, C. D. Ethnologue: Languages of the World 22nd edn (SIL International, 2019); https://www.ethnologue.com/6.Moseley, C. Atlas of the World’s Languages in Danger (UNESCO Publishing, 2010); http://www.unesco.org/culture/en/endangeredlanguages/atlas7.Catalogue of Endangered Languages (University of Hawaii at Manoa, 2020); http://www.endangeredlanguages.com8.Campbell, L. & Okura, E. in Cataloguing the World’s Endangered Languages 1st edn (eds Campbell, L. & Belew, A.) 79–84 (Routledge, 2018).9.The IUCN Red List of Threatened Species Version 2019-2 (IUCN, 2019); http://www.iucnredlist.org10.Romaine, S. in The Routledge Handbook of Ecolinguistics (eds Fill, A. F. & Penz, H.) Ch. 3 (Routledge, 2017).11.Crystal, D. Language Death (Cambridge Univ. Press, 2000).12.Simons, G. F. Two centuries of spreading language loss. Proc. Linguist. Soc. Am. 4, 27–38 (2019).Article 

    Google Scholar 
    13.Krauss, M. The world’s languages in crisis. Language 68, 4–10 (1992).Article 

    Google Scholar 
    14.Brondizio, E. S., Settele, J., Díaz, S. & Ngo, H. T. (eds) Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES, 2019).15.Bowern, C. Language vitality: theorizing language loss, shift, and reclamation (Response to Mufwene). Language 93, e243–e253 (2017).Article 

    Google Scholar 
    16.Mufwene, S. S. Language vitality: The weak theoretical underpinnings of what can be an exciting research area. Language 93, e202–e223 (2017).Article 

    Google Scholar 
    17.Hua, X., Greenhill, S. J., Cardillo, M., Schneemann, H. & Bromham, L. The ecological drivers of variation in global language diversity. Nat. Commun. 10, 2047 (2019).Article 

    Google Scholar 
    18.Grenoble, L. A. & Whaley, L. J. in Endangered Languages (eds Grenoble, L. A. & Whaley, L. J.) 22–54 (Cambridge Univ. Press, 1998).19.Cardillo, M., Bromham, L. & Greenhill, S. J. Links between language diversity and species richness can be confounded by spatial autocorrelation. Proc. R. Soc. B 282, 20142986 (2015).Article 

    Google Scholar 
    20.Amano, T. et al. Global distribution and drivers of language extinction risk. Proc. R. Soc. B 281, 20141574 (2014).Article 

    Google Scholar 
    21.Loh, J. & Harmon, D. Biocultural Diversity: Threatened Species, Endangered Languages (WWF, 2014).22.Fishman, J. A. Reversing Language Shift: Theoretical and Empirical Foundations of Assistance to Threatened Languages Vol. 76 (Multilingual Matters, 1991).23.Lewis, M. P. & Simons, G. F. Assessing endangerment: expanding Fishman’s GIDS. Rev. Roum. Linguist. 55, 103–120 (2010).
    Google Scholar 
    24.Hinton, L. in The Green Book of Language Revitalization in Practice (eds Hinton, L. & Hale, K.) 413–417 (Brill, 2001).25.Hobson, J. R. Re-awakening Languages: Theory and Practice in the Revitalisation of Australia’s Indigenous Languages (Sydney Univ. Press, 2010).26.Di Marco, M. et al. A novel approach for global mammal extinction risk reduction. Conserv. Lett. 5, 134–141 (2012).Article 

    Google Scholar 
    27.Cardillo, M., Mace, G. M., Gittleman, J. L. & Purvis, A. Latent extinction risk and the future battlegrounds of mammal conservation. Proc. Natl Acad. Sci. USA 103, 4157–4161 (2006).CAS 
    Article 

    Google Scholar 
    28.Bolam, F. C. et al. How many bird and mammal extinctions has recent conservation action prevented? Conserv. Lett. 14, e12762 (2020).
    Google Scholar 
    29.Balmford, A. Extinction filters and current resilience: the significance of past selection pressures for conservation biology. Trends Ecol. Evol. 11, 193–196 (1996).CAS 
    Article 

    Google Scholar 
    30.Brenzinger, M. Language Death: Factual and Theoretical Explorations with Special Reference to East Africa (Mouton de Gruyter, 1992).31.Aikhenvald, A. Y. in Language Endangerment and Language Maintenance: An Active Approach (eds Bradley, D. & Bradley, M.) 24–33 (Taylor & Francis, 2002).32.Aikhenvald, A. Y. in Lectures on Endangered Languages: 5. Endangered Languages of the Pacific Rim (eds Sakiyama, O. & Endo, F.) 97–142 (ELPR, 2004).33.van Driem, G. in Language Diversity Endangered (ed. Brenzinger, M.) Ch. 14 (Mouton de Gruyter, 2007).34.Muysken, P. in Historicity and Variation in Creole Studies (eds Highfield, A. & Valdman, A.) 52–78 (Karoma, 1981).35.Gal, S. Language Shift: Social Determinants of Linguistic Change in Bilingual Austria (Academic Press, 1979).36.Holmquist, J. Social correlates of a linguistic variable: a study in a Spanish village. Lang. Soc. 14, 191–203 (1985).Article 

    Google Scholar 
    37.Dobrin, L. M. in Endangered Languages: Beliefs and Ideologies in Language Documentation and Revitalization (eds Austin, P. K. & Sallabank, J.) Ch. 7 (British Academy, 2014).38.Sasse, H.-J. in Language Death: Factual and Theoretical Explorations with Special Reference to East Africa (ed Brenzinger M.) 7–30 (Mouton de Gruyter, 1992).39.Wang, Y. & Phillion, J. Minority language policy and practice in China: the need for multicultural education. Int. J. Multicult. Educ. 11, 1–14 (2009).
    Google Scholar 
    40.McCarty, T. L. in Language Policies in Education: Critical Issues (ed. Tollefson, J. W.) 285–307 (2002).41.Wiese, A.-M. & Garcia, E. E. The Bilingual Education Act: language minority students and equal educational opportunity. Biling. Res. J. 22, 1–18 (1998).Article 

    Google Scholar 
    42.Bromham, L., Hua, X., Algy, C. & Meakins, F. Language endangerment: a multidimensional analysis of risk factors. J. Lang. Evol. 5, 75–91 (2020).Article 

    Google Scholar 
    43.Gao, X. & Ren, W. Controversies of bilingual education in China. Int. J. Biling. Educ. Biling. 22, 267–273 (2019).Article 

    Google Scholar 
    44.Dimmendaal, G. J. in Investigating Obsolescence: Studies in Language Contraction and Death (ed. Dorian N. C.) 13-32 (Cambridge Univ. Press, 1989).45.Brenzinger, M. in Language Diversity Endangered (ed. Brenzinger, M.) IX–XVII (Mouton de Gruyter, 2007).46.Kuussaari, M. et al. Extinction debt: a challenge for biodiversity conservation. Trends Ecol. Evol. 24, 564–571 (2009).Article 

    Google Scholar 
    47.Tilman, D., May, R. M., Lehman, C. L. & Nowak, M. A. Habitat destruction and the extinction debt. Nature 371, 65–66 (1994).Article 

    Google Scholar 
    48.Meijer, J. R., Huijbregts, M. A., Schotten, K. C. & Schipper, A. M. Global patterns of current and future road infrastructure. Environ. Res. Lett. 13, 064006 (2018).Article 

    Google Scholar 
    49.Laurance, W. F. & Balmford, A. A global map for road building. Nature 495, 308–309 (2013).CAS 
    Article 

    Google Scholar 
    50.Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).CAS 
    Article 

    Google Scholar 
    51.Crawford, J. Language politics in the U.S.A.: the paradox of bilingual education. Soc. Justice 25, 50–69 (1998).
    Google Scholar 
    52.Hallett, D., Chandler, M. J. & Lalonde, C. E. Aboriginal language knowledge and youth suicide. Cogn. Dev. 22, 392–399 (2007).Article 

    Google Scholar 
    53.Taff, A. et al. in The Oxford Handbook of Endangered Languages (eds Rehg, K. & Campbell, L.) 862–883 (Oxford Univ. Press, 2018).54.Dinku, Y. et al. Language Use is Connected to Indicators of Wellbeing: Evidence from the National Aboriginal and Torres Strait Islander Social Survey 2014/15. CAEPR Working Paper no. 132/2019 (CAEPR, 2020); https://doi.org/10.25911/5ddb9fd6394e855.Essegbey, J., Henderson, B. & McLaughlin, F. Language Documentation and Endangerment in Africa (John Benjamins, 2015).56.Davis, J. L. Language affiliation and ethnolinguistic identity in Chickasaw language revitalization. Lang. Commun. 47, 100–111 (2016).Article 

    Google Scholar 
    57.Clyne, M. in Maintenance and Loss of Minority Languages (eds Fase, W. et al.) 17–36 (John Benjamins, 1992).58.Cardillo, M. et al. The predictability of extinction: biological and external correlates of decline in mammals. Proc. R. Soc. B 275, 1441–1448 (2008).Article 

    Google Scholar 
    59.Evans, N. Dying Words: Endangered Languages and What They Have to Tell Us Vol. 22 (John Wiley & Sons, 2011).60.Ndhlovu, F. in Language Planning and Policy: Ideologies, Ethnicities, and Semiotic Spaces of Power (eds Abdelhay, A. et al.) 133–151 (Cambridge Scholars, 2020).61.Hammarström, H., Forkel, R. & Haspelmath, M. Glottolog 4.1. http://glottolog.org (Max Planck Institute for the Science of Human History, 2019).62.Lewis, M. P., Simons, G. F. & Fennig, C. D. Ethnologue: Languages of the World 17th edn http://www.ethnologue.com (SIL International, 2013).63.King, K. A., Schilling-Estes, N., Lou, J. J., Fogle, F. & Soukup, B. Sustaining Linguistic Diversity: Endangered and Minority Languages and Language Varieties (Georgetown Univ. Press, 2008).64.Lee, N. H. & van Way, J. Assessing levels of endangerment in the Catalogue of Endangered Languages (ELCat) using the Language Endangerment Index (LEI). Lang. Soc. 45, 271–292 (2016).Article 

    Google Scholar 
    65.Language Vitality and Endangerment: International Expert Meeting on UNESCO Programme Safeguarding of Endangered Languages (UNESCO, 2003).66.Tershy, B. R., Shen, K.-W., Newton, K. M., Holmes, N. D. & Croll, D. A. The importance of islands for the protection of biological and linguistic diversity. BioScience 65, 592–597 (2015).Article 

    Google Scholar 
    67.Igboanusi, H. Is Igbo an endangered language? Multilingua 25, 443–452 (2006).Article 

    Google Scholar 
    68.Ravindranath, M. & Cohn, A. C. Can a language with millions of speakers be endangered? J. Southeast Asian Linguist. Soc. 7, 64–75 (2014).
    Google Scholar 
    69.Venter, O. et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat. Commun. 7, 12558 (2016).CAS 
    Article 

    Google Scholar 
    70.Bromham, L., Hua, X., Cardillo, M., Schneemann, H. & Greenhill, S. J. Parasites and politics: why cross-cultural studies must control for relatedness, proximity and covariation. R. Soc. Open Sci. 5, 181100 (2018).Article 

    Google Scholar 
    71.Bromham, L., Skeels, A., Schneemann, H., Dinnage, R. & Hua, X. There is little evidence that spicy food in hot countries is an adaptation to reducing infection risk. Nat. Hum. Behav. https://doi.org/10.1038/s41562-020-01039-8 (2021).72.Purvis, A., Cardillo, M., Grenyer, R. & Collen, B. in Phylogeny and Conservation (eds Purvis, A. et al.) 295–316 (Cambridge Univ. Press, 2005).73.Hurlbert, S. H. Pseudoreplication and the design of ecological field experiments. Ecol. Monogr. 54, 187–211 (1984).Article 

    Google Scholar 
    74.Dow, M. M. Network autocorrelation regression with binary and ordinal dependent variables: Galton’s problem. Cross Cult. Res. 42, 394–419 (2008).Article 

    Google Scholar 
    75.Wurm, M. J., Rathouz, P. J. & Hanlon, B. M. Regularized ordinal regression and the ordinalNet R package. Preprint at https://arxiv.org/abs/1706.05003 (2017).76.Byrd, R. H., Lu, P., Nocedal, J. & Zhu, C. A limited memory algorithm for bound constrained optimization. SIAM J. Sci. Comput. 16, 1190–1208 (1995).Article 

    Google Scholar 
    77.Barro, R. L. & Lee, J.-W. A new data set of educational attainment in the world, 1950–2010. J. Dev. Econ. 104, 184–198 (2013).Article 

    Google Scholar 
    78.Leclerc, J. L’aménagement linguistique dans le monde http://www.axl.cefan.ulaval.ca/monde/index_alphabetique.htm (2019).79.Solt, F. The Standardized World Income Inequality Database, Version 8 https://doi.org/10.7910/DVN/LM4OWF (2019).80.Global Agro-ecological Zones (GAEZ v3.0) (FAO, IIASA, 2010). More

  • in

    Simulating grazing beef and sheep systems

    Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
    the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
    Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
    and JavaScript. More

  • in

    Distance sampling surveys reveal 17 million vertebrates directly killed by the 2020’s wildfires in the Pantanal, Brazil

    1.Chiang, F., Mazdiyasni, O. & AghaKouchak, A. Evidence of anthropogenic impacts on global drought frequency, duration, and intensity. Nat. Commun. 12, 2754 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    2.Spinoni, J., Naumann, G., Carrao, H., Barbosa, P. & Vogt, J. World drought frequency, duration, and severity for 1951–2010. Int. J. Climatol. 34, 2792–2804 (2014).
    Google Scholar 
    3.Duane, A., Castellnou, M. & Brotons, L. Towards a comprehensive look at global drivers of novel extreme wildfire events. Clim. Change 165(3), 1–21 (2021).
    Google Scholar 
    4.Krawchuk, M. A., Moritz, M. A., Parisien, M. A., Van Dorn, J. & Hayhoe, K. Global Pyrogeography: The current and future distribution of wildfire. PLoS ONE 4(4), e5102 (2009).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    5.Williams, A. P. et al. Observed impacts of anthropogenic climate change on wildfire in California. Earth’s Fut. 7, 892–910 (2019).ADS 

    Google Scholar 
    6.Garcia, L. C. et al. Record-breaking wildfires in the world’s largest continuous tropical wetland: Integrative Fire Management is urgently needed for both biodiversity and humans. J. Environ. Manag. 293, 112870 (2021).CAS 

    Google Scholar 
    7.Bowman, D. M. J. S. et al. Vegetation fires in the Anthropocene. Nat. Rev. Earth Environ. 1, 500–515 (2020).ADS 

    Google Scholar 
    8.Criado, M. G., Myers-Smith, I. H., Bjorkman, A. D., Lehmann, C. E. R. & Stevens, N. Woody plant encroachment intensifies under climate change across tundra and savanna biomes. Glob. Ecol. Biogeogr. 29(5), 925–943 (2020).
    Google Scholar 
    9.Mancini, L. D., Corona, P. & Salvati, L. Ranking the importance of Wildfires’ human drivers through a multi-model regression approach. Environ. Impact Assess. Rev. 72, 177–186 (2018).
    Google Scholar 
    10.Moreira, F. et al. Landscape – wildfire interactions in southern Europe: Implications for landscape management. J. Environ. Manag. 92(10), 2389–2402 (2011).
    Google Scholar 
    11.Clarke, H. et al. The proximal drivers of large fires: A pyrogeographic study. Front. Earth Sci. 8, 90 (2020).ADS 

    Google Scholar 
    12.Abram, N. J. et al. Connections of climate change and variability to large and extreme forest fires in southeast Australia. Commun. Earth Environ. 2, 1 (2021).ADS 

    Google Scholar 
    13.Daskin, J. H., Aires, F. & Staver, A. C. Determinants of tree cover in tropical floodplains. Proc. R. Soc. B. 286, 20191755 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    14.Kotze, D. C. The effects of fire on wetland structure and functioning. Afr. J. Aquat. Sci. 38(3), 237–247 (2013).
    Google Scholar 
    15.Tedim, F. et al. Defining Extreme Wildfire Events: difficulties, challenges, and impacts. Fire 1, 9 (2018).
    Google Scholar 
    16.Libonati, R. et al. Sistema ALARMES – Alerta de área queimada Pantanal, situação final de 2020 https://www.researchgate.net/publication/350103205_Nota_Tecnica_012021_LASA-UFRJ_Queimadas_Pantanal_2020?channel=doi&linkId=6051109d92851cd8ce483fb1&showFulltext=true (2021).17.Libonati, R., DaCamara, C. C., Peres, F. L., de Carvalho, L. A. S. & Garcia, L. C. Rescue Brazil’s burning Pantanal wetlands. Nature 588, 217–219 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    18.Marengo, J. A. et al. Extreme drought in the Brazilian Pantanal in 2019–2020: Characterization, causes and impacts. Front. Water 3, 639204 (2021).
    Google Scholar 
    19.Marengo, J. A., Alves, L. M. & Torres, R. R. Regional climate change scenarios in the Brazilian Pantanal watershed. Clim. Res. 68(2–3), 201–213 (2016).
    Google Scholar 
    20.Hardesty, J., Myers, R. & Fulks, W. Fire, ecosystems, and people: A preliminary assessment of fire as a global conservation issue. George Wright Forum 22, 78–87 (2005).
    Google Scholar 
    21.Bliege Bird, R., Bird, D. W., Codding, B. F., Parker, C. H. & Jones, J. H. The “fire stick farming” hypothesis: Australian Aboriginal foraging strategies, biodiversity, and anthropogenic fire mosaics. Proc. Natl. Acad. Sci. USA 105(39), 14796–14801 (2008).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    22.Beerling, D. J. & Osborne, C. P. The origin of the savanna biome. Glob. Chang. Biol. 12, 2023–2031 (2006).ADS 

    Google Scholar 
    23.Simon, M. F. et al. Recent assembly of the Cerrado, a neotropical plant diversity hotspot, by in situ evolution of adaptations to fire. Proc. Natl. Acad. Sci. USA 106, 20359–20364 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    24.Pott, A. & Pott, V. J. Features and conservation of the Brazilian Pantanal wetland. Wetl. Ecol. Manag. 12, 547–552 (2004).
    Google Scholar 
    25.Ferraz-Vicentini, K. R. & Salgado-Laboriau, M. L. Palynological analysis of a palm swamp in Central Brasil. J. South Am. Earth Sci. 9(3–4), 207–219 (1996).ADS 

    Google Scholar 
    26.Engstrom, R. T. First-order fire effects on animals: review and recommendations. Fire Ecol. 6(1), 115–130 (2010).
    Google Scholar 
    27.Whelan, R. J., Rodgerson, L., Dickman, C. R. & Sutherland, E. F. Critical life processes of plants and animals: Developing a process-based understanding of population changes in fireprone landscapes (Cambridge University Press, 2002).
    Google Scholar 
    28.van Eeden, L. M. et al. Impacts of the unprecedented 2019–2020 bushfires on Australian animals. https://www.wwf.org.au/ArticleDocuments/353/WWF_Impacts-of-the-unprecedented-2019-2020-bushfires-on-Australian-animals.pdf.aspx (2020).29.Pacheco, L. F., Quispe-Calle, L. C., Suárez-Guzmán, F. A., Ocampo, M. & Claure-Herrera, A. J. Muerte de mamíferos por los incendios de 2019 en la Chiquitania. Ecol. Boliv. 56(1), 4–16 (2021).
    Google Scholar 
    30.Berlinck, C. B. et al. The Pantanal is on fire and only a sustainable agenda can save the largest wetland in the world. Braz. J. Biol. 82, e244200 (2021).CAS 
    PubMed 

    Google Scholar 
    31.Andersen, A. N., Woinarski, J. C. Z. & Parr, C. L. Savanna burning for biodiversity: Fire management for faunal conservation in Australian tropical savannas. Austral Ecol. 37, 658–667 (2012).
    Google Scholar 
    32.Komarek, R. Fire and the changing wildlife habitat. Proc. Tall Timbers Fire Ecol. Conf. 2, 35–43 (1963).
    Google Scholar 
    33.Layme, V. M. G., Lima, A. P. & Magnusson, W. E. Effects of fire, food availability and vegetation on the distribution of the rodent Bolomys lasiurus in an Amazonian savanna. J. Trop. Ecol. 20, 183–187 (2004).
    Google Scholar 
    34.Roberts, S. L., van Wagtendonk, J. W., Miles, A. K., Kelt, D. A. & Lutz, J. A. Modeling the effects of fire severity and spatial complexity on small mammals in Yosemite National Park, California. Fire Ecol. 4(2), 83–104 (2008).
    Google Scholar 
    35.Smith, J. K. Wildland Fire in Ecosystems: Effects of Fire on Fauna (Rocky Mountain Research Station, Colorado, 2000).36.Woinarski, J. C. Z. & Legge, S. The impacts of fire on birds in Australia’s tropical savannas. Emu 113(4), 319–352 (2013).
    Google Scholar 
    37.Pires, A. S., Fernandez, F. A., de Freitas, D. & Feliciano, B. R. Influence of edge and fire-induced changes on spatial distribution of small mammals in Brazilian Atlantic Forest fragments. Stud. Neotrop. Fauna Environ. 40(1), 7–14 (2005).
    Google Scholar 
    38.Silveira, L. F., Rodrigues, H. G., Jácomo, A. T. A. & Diniz Filho, J. A. F. Impact of wildfires on the megafauna of Emas National Park, Central Brazil. Oryx 33, 108–114 (1999).39.Tomas, W. M. et al. Checklist of mammals from Mato Grosso do Sul, Brazil. Iheringia, Sér. zool. 107(Suppl), e2017155 (2017).40.Tomas, W. M. et al. Mammals in the Pantanal wetland, Brazil (Pensoft Publishers, 2010).
    Google Scholar 
    41.Burnham, K. P., Anderson, D. R. & Laake, J. L. Estimation of density from line transect sampling of biological populations. Ecol. Monogr. 72, 1–202 (1980).
    Google Scholar 
    42.Jolly, W. M. et al. Climate-induced variations in global wildfire danger from 1979 to 2013. Nat. Commun. 6, 7537 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    43.Thielen, D. Quo vadis Pantanal? Expected precipitation extremes and drought dynamics from changing sea surface temperature. PLoS ONE 15(1), e0227437 (2020).44.Ciemer, C. et al. An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic Sea surface temperatures. Environ. Res. Lett. 15, 094087 (2020).45.Boers, N., Marwan, N., Barbosa, H. M. J. & Kurths, J. A deforestation-induced tipping point for the South American monsoon system. Sci. Rep. 7, 41489 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    46.Bergier, I. et al. Amazon rainforest modulation of water security in the Pantanal wetland. Sci. Total Environ. 619–620, 1116–1125 (2018).ADS 
    PubMed 

    Google Scholar 
    47.Hofmann, G. et al. The Brazilian Cerrado is becoming hotter and drier. Glob. Chang. Biol. 00, 1–14 (2021).
    Google Scholar 
    48.Tomas, W. M. et al. Sustainability Agenda for the Pantanal Wetland: perspectives on a collaborative interface for science, policy, and decision-making. Trop. Conserv. Sci. 12, 1–30 (2019).ADS 

    Google Scholar 
    49.Schulz, C. Physical, ecological and human dimensions of environmental change in Brazil’s Pantanal wetland: Synthesis and research agenda. Sci. Total Environ. 687, 1011–1027 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    50.Harris, M. B. et al. Safeguarding the Pantanal wetlands: Threats and conservation initiatives. Conserv. Biol. 19(3), 714–720 (2005).
    Google Scholar 
    51.Ely, P., Fantin-Cruz, I., Tritico, H. M., Girard, P. & Kaplan, D. Dam-induced hydrologic alterations in the rivers feeding the Pantanal. Front. Environ. Sci. 8, 256 (2020).
    Google Scholar 
    52.Roque, F. O. et al. Simulating land use changes, sediment yields, and pesticide use in the Upper Paraguay River Basin: Implications for conservation of the Pantanal wetland. Agric. Ecosyst. Environ. 314, 107405 (2021).53.Guerra, A. et al. Drivers and projections of vegetation loss in the Pantanal and surrounding ecosystems. Land Use Policy 91, 104388 (2020).54.Berlinck, C. N., Lima, L. H. A. & Carvalho Junior, E. A. R. Historical survey of research related to fire management and fauna conservation in the world and in Brazil. Biota Neotropica 21(3), e20201144 (2021).55.Estado de Mato Grosso do Sul. DECRETO Nº 15.654, de 15 de abril de 2021. Institui o Plano Estadual de Manejo Integrado do Fogo, e Dá Outras Providências. (Diário Oficial do Estado, Mato Grosso do Sul nº 10.477, 2021).56.Marino, E. et al. Forest fuel management for wildfire prevention in Spain: A quantitative SWOT analysis. Int. J. Wildland Fire 23, 373–384 (2014).
    Google Scholar 
    57.Finney, M. A. & Cohen, J. D. Expectation and Evaluation of Fuel Management Objectives (Rocky Mountain Research Station, Colorado, 2003).58.Amiro, B. D., Stocks, B. J., Alexander, M. E., Flannigan, M. D. & Wotton, B. M. Fire, climate change, carbon and fuel management in the Canadian boreal forest. Int. J. Wildland Fire 10(4), 405–413 (2001).
    Google Scholar 
    59.Rocca, M. E., Brown, P. M., MacDonald, L. H. & Carrico, C. M. Climate change impacts on fire regimes and key ecosystem services in Rocky Mountain forests. Forest Ecol. Manag. 327, 290–305 (2014).
    Google Scholar 
    60.Pott, V. J., Pott, A., Lima, L. C. P., Moreira, S. N. & Oliveira, A. K. M. Aquatic macrophyte diversity of the Pantanal wetland and upper basin. Braz. J. Biol. 71(1), 255–563 (2011).CAS 
    PubMed 

    Google Scholar 
    61.Britski, H. A., Silimon, K. Z. S. & Lopes, B. S. Peixes do Pantanal: Manual de Identificação (EMPRAPA, Brasília, 2007).62.Sousa, T. P. et al. Cytogenetic and molecular data Support the occurrence of three Gymnotus species (Gymnotiformes: Gymnotidae) used as live bait in Corumbá, Brazil: Implications for conservation and management of professional fishing. Zebrafish 14(2), 177–186 (2017).PubMed 

    Google Scholar 
    63.Piva, A., Caramaschi, U. & Albuquerque, N. R. A new species of Elachistocleis (Anura: Microhylidae) from the Brazilian Pantanal. Phyllomedusa 16(2), 143–154 (2017).
    Google Scholar 
    64.Strüssmann, C., Ribeiro, R. A. K., Ferreira, V. L., & Beda, A. D. F. Herpetofauna do Pantanal Brasileiro [Herpetofauna of the Brazilian Pantanal]. (Sociedade Brasileira de Herpetologia, Belo Horizonte, 2007).65.Ferreira, V. L. et al. Répteis do Mato Grosso do Sul [Reptiles from Mato Grosso do Sul]. Brazil. Iheringia Sér. Zool. 107(Suppl), e2017153 (2017).66.Nunes, A. P. Quantas espécies de aves ocorrem no Pantanal? [How many bird species do occur in the Pantanal?]. Atualidades Ornitológicas 160, 45–54 (2011).
    Google Scholar 
    67.Tubelis, D. P. & Tomas, W. M. Bird species of the Pantanal wetland, Brazil.. Ararajuba 11(1), 5–37 (2003).
    Google Scholar 
    68.Thomas, L. et al. Distance software: design and analysis of distance sampling surveys for estimating population size. J. Appl. Ecol. 47, 5–14 (2010).PubMed 

    Google Scholar  More

  • in

    Statistical inference, scale and noise in comparative anthropology

    To the Editor — In an insightful Comment Bliege Bird and Codding1 highlight a number of important issues to consider in the analysis of cross-cultural anthropological data. However, a casual reader of the Comment could be forgiven for taking away the message that cross-cultural data in anthropology is inherently flawed, and so is of limited use. We want to emphasize that comparative analysis plays an essential role in all non-experimental sciences, including anthropology and archaeology. This is because when systems cannot be manipulated due to scales of time and space, or issues of logistics or ethics, the only way to evaluate alternative outcomes is by analysing the results of natural experiments. More

  • in

    Drivers of language loss

    1.Nettle, D. Linguistic Diversity (Oxford Univ. Press, USA, 1999).2.Campbell, L. & Belew, A. Cataloguing the World’s Endangered Languages (Routledge, 2018).3.Bromham, L. et al. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-021-01604-y (2021).4.Amano, T. et al. Proc. R. Soc. B 281, 20141574 (2014).Article 

    Google Scholar 
    5.Austin, P. K. & Sallabank, J. The Cambridge Handbook of Endangered Languages (Cambridge Univ. Press, 2011).6.Kandler, A., Unger, R. & Steele, J. Phil. Trans. R. Soc. B 365, 3855–3864 (2010).Article 

    Google Scholar 
    7.Kik, A. et al. Proc. Natl Acad. Sci. USA 118, e2100096118 (2021).CAS 
    Article 

    Google Scholar 
    8.Lewis, M. P., Simons, G. F. & Fennig, C. D. Ethnologue: Languages of the World 17th edn (SIL International, 2013).9.Fischer, S. D. in The Routledge Handbook of Historical Linguistics (ed. Bowern, C. & Evans, B.) Ch. 20, 443–465 (CRC Press, Routledge, 2015).10.Hou, L. & Kusters, A. in The Routledge Handbook of Linguistic Ethnography (ed. Tusting, K.) Ch. 25 (CRC Press, Routledge, 2019).11.Turner, M. K. & McDonald, B. M. J. Iwenhe Tyerrtye: What it Means to be an Aboriginal Person (IAD Press, 2010).12.Hercus, L. A. & Sutton, P. This is What Happened: Historical Narratives by Aborigines (Australian Institute of Aboriginal Studies, 1986).13.Meek, B. A. Annu. Rev. Anthropol. 48, 95–115 (2019).Article 

    Google Scholar  More

  • in

    The global loss of floristic uniqueness

    Quantification of changes in floristic similarityTo quantify changes in floristic similarity by naturalized flowering plant species, we extracted regional lists of alien species from the Global Naturalized Alien Flora (GloNAF) database45 and regional lists of native species from the Global Inventory of Floras and Traits (GIFT) database46. The GloNAF database contains lists of naturalized vascular plant taxa for 861 regions (countries or subnational administrative units), ranging in size from 0.03 to 6,864,961 km2 (median size is 15,152 km2) and covering >80% of the terrestrial ice-free surface globally47. GloNAF includes 13,803 plant taxa that, according to the original data sources, are alien plants and have established self-sustaining wild populations in the respective regions (i.e., are naturalized5). The GIFT database is a compilation of floras and checklists of predominantly native vascular plant species with an indication of their floristic status for more than 300,000 species across nearly 3000 regions with near global coverage46. We first selected regions that matched perfectly between GloNAF and GIFT. Additionally, we merged some GloNAF regions to match a larger GIFT region, and vice versa, by comparing the overlapping area of nested regions using the R package ‘sf’ (version 0.8-0)48.To ensure the highest data quality, and to be on the conservative side, we restricted our analysis to regions with complete or nearly complete checklists of both native and naturalized alien species. For GloNAF, we only included regions for which there was at least one species list judged to include more than 50% of the naturalized taxa for that region45. Although the judgment of species-list completeness is coarse and for most lists made by the GloNAF curators, it allows the exclusion of regions for which the data are obviously poor. For GIFT, we included a region only if at least one species list aimed to represent its entire native angiosperm flora. Our strict selection criteria resulted in a dataset including native and naturalized species for 658 non-overlapping regions, including 154 island regions, 503 mainland regions and one region including both islands and mainland areas (Chile). These regions covered all continents, except Antarctica, but there was low coverage for parts of Africa and Asia (Fig. 4).We restricted our analyses to flowering plants (angiosperms), which had the most complete species lists, and to species with accepted names in The Plant List24 (http://www.theplantlist.org/). We excluded species with an uncertain native/alien status or with a conflicting status, i.e., being native to a region according to GIFT but being alien to the same region according to GloNAF. Furthermore, since the native/alien status of many infraspecific taxa and hybrid taxa are less clear, we restricted our analyses to the species level (i.e., infraspecific taxa were assigned to the binomial species name), and we excluded hybrids. Our final dataset included 1,139,254 native species-by-region records for 189,110 species and 141,762 naturalized species-by-region records for 10,130 species.For all 216,153 possible pairwise combinations of the 658 regions, we quantified the taxonomic and phylogenetic similarities between their native floras (SimTaxnative, SimPhylnative), and between their floras including both native and naturalized alien species (SimTaxnative+naturalized, SimPhylnative+naturalized). As the regions vary largely in species richness (ranging from 11 to 13,720 species with a median of 1704), we used the Simpson similarity index for taxonomic similarity (Eq. 1)49, which is largely insensitive to species richness:50$${SimTax}=1-frac{{{min }}left(b,cright)}{a+{{min }}left(b,cright)}$$
    (1)
    Here a is the number of species common to both regions, b is the number of species that occur in the first region but not in the second and c is the number of species that occur in the second region but not in the first51. Likewise, we calculated the Simpson phylogenetic similarity index as phylogenetic similarity (Eq. 2) as implemented in the R package ‘betapart’ (version 1.5.1)52:$${SimPhyl}=1-frac{{{min }}left(B,Cright)}{A+{{min }}left(B,Cright)}$$
    (2)
    Here A is the total length of the phylogenetic branches in the phylogenetic tree that are shared by the species of both regions, B is the total length of the phylogenetic branches that are shared only by the first region and C is the total length of the phylogenetic branches that are shared only by the second region51. To quantify changes in similarity due to naturalization of alien species, we calculated the degree of homogenization H (or differentiation, see below) for each pair of regions as$$H={ln}frac{{{Sim}}_{{native}+{naturalized}}+0.001}{{{Sim}}_{{native}}+0.001}$$
    (3)
    A small value of 0.001 was added to both similarities to avoid infinite values. A positive log-response ratio indicates homogenization (i.e., increased floristic similarity between two regions), and a negative one indicates differentiation (i.e., decreased floristic similarity). As an alternative to the Simpson similarity index, we also calculate the Sørensen similarity index, which additionally takes into consideration the nestedness of the floras in the paired regions51. As the results were not sensitive to the choice of similarity indices (Supplementary Fig. 14), we focused our analyses on the Simpson similarity index.To quantify phylogenetic similarity, we used a phylogenetic tree including all angiosperms with accepted names in The Plant List (Supplementary Fig. 2). The tree was developed based on the mega phylogeny of Smith and Brown53. We added missing species (n = 71,124, of which 733 are naturalized in other regions) with their accepted names in The Plant List to the root of their genus or families. For details on the development of the phylogenetic tree, see ref. 47.Quantification of geographic distances and climatic distancesWe calculated the pairwise geographic distance between regions as the distance between their geographic centroids using the R package ‘geosphere’ (version 1.5-10)54. We also calculated the nearest distance between the geographic borders of regions. However, since the distances between geographic centroids are highly correlated with distances between region borders (n = 216,153, r = 0.996, P  More

  • in

    Phytoplankton settling quality has a subtle but significant effect on sediment microeukaryotic and bacterial communities

    1.Griffiths, J. R. et al. The importance of benthic-pelagic coupling for marine ecosystem functioning in a changing world. Glob. Chang. Biol. 23, 2179–2196 (2017).ADS 
    PubMed 

    Google Scholar 
    2.Graf, G., Bengtsson, W., Diesner, U., Schulz, R. & Theede, H. Benthic response to sedimentation of a spring phytoplankton bloom: Process and budget. Mar. Biol. 67, 201–208 (1982).
    Google Scholar 
    3.Campanyà-llovet, N., Snelgrove, P. V. R. & Parrish, C. C. Rethinking the importance of food quality in marine benthic food webs. Prog. Oceanogr. 156, 240–251 (2017).
    Google Scholar 
    4.Blomqvist, S. & Heiskanen, A.-S. The challenge of sedimentation in the Baltic Sea. In A Systems Analysis of the Baltic Sea. Ecological Studies (Analysis and Synthesis) Vol. 148 (eds Wulff, F. V. et al.) 211–227 (Springer, Berlin, 2001).
    Google Scholar 
    5.Elmgren, R. Trophic dynamics in the enclosed, brackish Baltic Sea. Rapp. P.-V. Réun. Cons. int. Explor. Mer. 183, 152–169 (1984).
    Google Scholar 
    6.Kahru, M., Elmgren, R., Di Lorenzo, E. & Savchuk, O. Unexplained interannual oscillations of cyanobacterial blooms in the Baltic Sea. Sci. Rep. 8, 6–10 (2018).ADS 

    Google Scholar 
    7.BACC II Author Team. Second Assessment of Climate Change for the Baltic Sea Basin. (SpringerOpen, 2015) https://doi.org/10.1007/978-3-319-16006-1.8.Spilling, K. & Lindström, M. Phytoplankton life cycle transformations lead to species-specific effects on sediment processes in the Baltic Sea. Cont. Shelf Res. 28, 2488–2495 (2008).ADS 

    Google Scholar 
    9.Suikkanen, S. et al. Climate change and eutrophication induced shifts in northern summer plankton communities. PLoS ONE 8, e66475 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    10.Tamelander, T., Spilling, K. & Winder, M. Organic matter export to the seafloor in the Baltic Sea: Drivers of change and future projections. Ambio 46, 842–851 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    11.Giere, O. Meiobenthology: The Microscopic Motile Fauna of Aquatic Sediments (Springer, 2009).
    Google Scholar 
    12.Schratzberger, M. & Ingels, J. Meiofauna matters: The roles of meiofauna in benthic ecosystems. J. Exp. Mar. Biol. Ecol. 502, 12–25 (2018).
    Google Scholar 
    13.Bonaglia, S., Nascimento, F. J. A., Bartoli, M., Klawonn, I. & Brüchert, V. Meiofauna increases bacterial denitrification in marine sediments. Nat. Commun. 5, 5133 (2014).ADS 
    CAS 
    PubMed 

    Google Scholar 
    14.Nascimento, F. J. A., Näslund, J. & Elmgren, R. Meiofauna enhances organic matter mineralization in soft sediment ecosystems. Limnol. Oceanogr. 57, 338–346 (2012).ADS 
    CAS 

    Google Scholar 
    15.Nealson, K. H. Sediment bacteria: Who’s there, what are they doing, and what’s new?. Annu. Rev. Earth Planet Sci. 25, 403–434 (1997).ADS 
    CAS 
    PubMed 

    Google Scholar 
    16.Meyer-Reil, L.-A. Seasonal and spatial distribution of extracellular enzymatic activities and microbial incorporation of dissolved organic substrates in marine sediments. Appl. Environ. Microbiol. 53, 1748–1755 (1987).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    17.Ólafsson, E. & Elmgren, R. Seasonal dynamics of sublittoral meiobenthos in relation to phytoplankton sedimentation in the Baltic Sea. Estuar. Coast. Shelf Sci. 45, 149–164 (1997).ADS 

    Google Scholar 
    18.Pfannkuche, O. Benthic response to the sedimentation of particulate organic matter at the BIOTRANS station, 47°N, 20°W. Deep. Res. Part II 40, 135–149 (1993).
    Google Scholar 
    19.Hoffmann, K., Hassenrück, C., Salman-Carvalho, V., Holtappels, M. & Bienhold, C. Response of bacterial communities to different detritus compositions in Arctic deep-sea sediments. Front. Microbiol. 8, 266 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    20.Stoeck, T., Kochems, R., Forster, D., Lejzerowicz, F. & Pawlowski, J. Metabarcoding of benthic ciliate communities shows high potential for environmental monitoring in salmon aquaculture. Ecol. Indic. 85, 153–164 (2018).
    Google Scholar 
    21.Rudnick, D. T. Time lags between the deposition and meiobenthic assimilation of phytodetritus. Mar. Ecol. Prog. Ser. 50, 231–240 (1989).ADS 

    Google Scholar 
    22.van der Heijden, L. H. et al. How do food sources drive meiofauna community structure in soft-bottom coastal food webs?. Mar. Biol. 165, 166 (2018).
    Google Scholar 
    23.Schratzberger, M., Forster, R. M., Goodsir, F. & Jennings, S. Nematode community dynamics over an annual production cycle in the central North Sea. Mar. Environ. Res. 66, 508–519 (2008).CAS 
    PubMed 

    Google Scholar 
    24.Wieser, W. Die beziehung zwischen mundhöhlengestalt, ernährungsweise und vorkommen bei freilebenden marinen nematoden. Ark Zool 2, 439–484 (1953).
    Google Scholar 
    25.Moens, T., Van Gansbeke, D. & Vincx, M. Linking estuarine nematodes to their suspected food. A case study from the Westerschelde Estuary (south-west Netherlands). J. Mar. Biol. Assoc. UK 79, 1017–1027 (1999).
    Google Scholar 
    26.Nascimento, F. J. A., Karlson, A. M. L. & Elmgren, R. Settling blooms of filamentous cyanobacteria as food for meiofauna assemblages. Limnol. Oceanogr. 53, 2636–2643 (2008).ADS 

    Google Scholar 
    27.Nascimento, F. J. A., Karlson, A. M. L., Näslund, J. & Gorokhova, E. Settling cyanobacterial blooms do not improve growth conditions for soft bottom meiofauna. J. Exp. Mar. Biol. Ecol. 368, 138–146 (2009).
    Google Scholar 
    28.Groendahl, S. & Fink, P. High dietary quality of non-toxic cyanobacteria for a benthic grazer and its implications for the control of cyanobacterial biofilms. BMC Ecol. 17, 20 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    29.Broman, E. et al. Spring and late summer phytoplankton biomass impact on the coastal sediment microbial community structure. Microb. Ecol. 77, 288–303 (2019).CAS 
    PubMed 

    Google Scholar 
    30.Fagervold, S. K. et al. River organic matter shapes microbial communities in the sediment of the Rhône prodelta. ISME J. 8, 2327–2338 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    31.Reed, H. E. & Martiny, J. B. H. Microbial composition affects the functioning of estuarine sediments. ISME J. 7, 868–879 (2013).CAS 
    PubMed 

    Google Scholar 
    32.Tuominen, L. et al. Nutrient fluxes, porewater profiles and denitrification in sediment influenced by algal sedimentation and bioturbation by Monoporeia affinis. Estuar. Coast. Shelf Sci. 49, 83–97 (1999).ADS 
    CAS 

    Google Scholar 
    33.Zilius, M., De Wit, R. & Bartoli, M. Response of sedimentary processes to cyanobacteria loading. J. Limnol. 75, 236–247 (2016).
    Google Scholar 
    34.Blazewicz, S. J., Barnard, R. L., Daly, R. A. & Firestone, M. K. Evaluating rRNA as an indicator of microbial activity in environmental communities: Limitations and uses. ISME J. 7, 2061–2068 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    35.Guardiola, M. et al. Spatio-temporal monitoring of deep-sea communities using metabarcoding of sediment DNA and RNA. PeerJ 4, e2807 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    36.Soto, E., Quiroga, E., Ganga, B. & Alarcón, G. Influence of organic matter inputs and grain size on soft-bottom macrobenthic biodiversity in the upwelling ecosystem of central Chile. Mar. Biodivers. 47, 433–450 (2017).
    Google Scholar 
    37.Broman, E., Bonaglia, S., Norkko, A., Creer, S. & Nascimento, F. J. A. High throughput shotgun sequencing of eRNA reveals taxonomic and derived functional shifts across a benthic productivity gradient. Mol. Ecol. 00, 1–17 (2020).CAS 

    Google Scholar 
    38.Ingels, J., Tchesunov, A. V. & Vanreusel, A. Meiofauna in the Gollum Channels and the Whittard Canyon, Celtic Margin—How local environmental conditions shape nematode structure and function. PLoS ONE 6, e20094 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    39.Albert, S. et al. Influence of settling organic matter quantity and quality on benthic nitrogen cycling. Limnol. Oceanogr. 66, 1882–1895 (2021).ADS 
    CAS 

    Google Scholar 
    40.Modig, H. & Ólafsson, E. Responses of Baltic benthic invertebrates to hypoxic events. J. Exp. Mar. Biol. Ecol. 229, 133–148 (1998).
    Google Scholar 
    41.Ankar, S. Annual dynamics of a Northern Baltic Soft Bottom. In Cyclic Phenomena in Marine Plants and Animals (eds Naylor, E. & Hartnoll, R. G.) 29–36 (Pergamon Press, 1979). https://doi.org/10.1016/b978-0-08-023217-1.50011-4.Chapter 

    Google Scholar 
    42.Karlson, A. M. L., Nascimento, F. J. A. & Elmgren, R. Incorporation and burial of carbon from settling cyanobacterial blooms by deposit-feeding macrofauna. Limnol. Oceanogr. 53, 2754–2758 (2008).ADS 

    Google Scholar 
    43.Hedberg, P., Albert, S., Nascimento, F. J. A. & Winder, M. Effects of changing phytoplankton species composition on carbon and nitrogen uptake in benthic invertebrates. Limnol. Oceanogr. 66, 469–480 (2021).ADS 
    CAS 

    Google Scholar 
    44.Ólafsson, E., Modig, H. & van de Bund, W. J. Species specific uptake of radio-labelled phytodetritus by benthic meiofauna from the Baltic Sea. Mar. Ecol. Prog. Ser. 177, 63–72 (1999).ADS 

    Google Scholar 
    45.Guden, R. M., Vafeiadou, A., De Meester, N., Derycke, S. & Moens, T. Living apart-together: Microhabitat differentiation of cryptic nematode species in a saltmarsh habitat. PLoS ONE 13, e0204750 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    46.Rudnick, D. T. & Oviatt, C. A. Seasonal lags between organic carbon deposition and mineralization in marine sediments. J. Mar. Res. 44, 815–837 (1986).CAS 

    Google Scholar 
    47.Moens, T. et al. Diatom feeding across trophic guilds in tidal flat nematodes, and the importance of diatom cell size. J. Sea Res. 92, 125–133 (2014).ADS 

    Google Scholar 
    48.Schuelke, T., Pereira, T. J., Hardy, S. M. & Bik, H. M. Nematode-associated microbial taxa do not correlate with host phylogeny, geographic region or feeding morphology in marine sediment habitats. Mol. Ecol. 27, 1930–1951 (2018).PubMed 

    Google Scholar 
    49.Fenchel, T. & Jansson, B.-O. On the vertical distribution of the microfauna in the sediments of a brackish-water beach. Ophelia 3, 161–177 (1966).
    Google Scholar 
    50.Fenchel, T. The ecology of marine microbenthos II. The food of marine benthic ciliates. Ophelia 5, 73–121 (1968).
    Google Scholar 
    51.Shimeta, J., Starczak, V. R., Ashiru, O. M. & Zimmer, C. A. Influences of benthic boundary-layer flow on feeding rates of ciliates and flagellates at the sediment-water interface. Limnol. Oceanogr. 46, 1709–1719 (2001).ADS 

    Google Scholar 
    52.Nagata, T. Organic matter–bacteria interactions in seawater. In Microbial Ecology of the Oceans 2nd edn (ed. Kirchman, D. L.) 207–241 (Wiley, 2008).
    Google Scholar 
    53.De Mesel, I. et al. Top-down impact of bacterivorous nematodes on the bacterial community structure: A microcosm study. Environ. Microbiol. 6, 733–744 (2004).PubMed 

    Google Scholar 
    54.Landa, M. et al. Phylogenetic and structural response of heterotrophic bacteria to dissolved organic matter of different chemical composition in a continuous culture study. Environ. Microbiol. 16, 1668–1681 (2014).CAS 
    PubMed 

    Google Scholar 
    55.Izabel-Shen, D., Albert, S., Winder, M., Farnelid, H. & Nascimento, F. J. A. Quality of phytoplankton deposition structures bacterial communities at the water-sediment interface. Mol. Ecol. 30, 3515–3529 (2021).CAS 
    PubMed 

    Google Scholar 
    56.Bowen, J. L., Babbin, A. R., Kearns, P. J. & Ward, B. B. Connecting the dots: Linking nitrogen cycle gene expression to nitrogen fluxes in marine sediment mesocosms. Front. Microbiol. 5, 429 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    57.Broman, E. et al. Denitrification responses to increasing cadmium exposure in Baltic Sea sediments. Aquat. Toxicol. 217, 105328 (2019).CAS 
    PubMed 

    Google Scholar 
    58.van der Loos, L. M. & Nijland, R. Biases in bulk: DNA metabarcoding of marine communities and the methodology involved. Mol. Ecol. 30, 3270–3288 (2021).PubMed 

    Google Scholar 
    59.Zinger, L. et al. DNA metabarcoding—Need for robust experimental designs to draw sound ecological conclusions. Mol. Ecol. 28, 1857–1862 (2019).PubMed 

    Google Scholar 
    60.Prokopowich, C. D., Gregory, T. R. & Crease, T. J. The correlation between rDNA copy number and genome size in eukaryotes. Genome 46, 48–50 (2003).CAS 

    Google Scholar 
    61.Nascimento, F. J. A., Lallias, D., Bik, H. M. & Creer, S. Sample size effects on the assessment of eukaryotic diversity and community structure in aquatic sediments using high-throughput sequencing. Sci. Rep. 8, 11737 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    62.Brannock, P. M. & Halanych, K. M. Meiofaunal community analysis by high-throughput sequencing: Comparison of extraction, quality filtering, and clustering methods. Mar. Genomics 23, 67–75 (2015).PubMed 

    Google Scholar 
    63.Wallenstein, M. D., Myrold, D. D., Firestone, M. & Voytek, M. Environmental controls on denitrifying communities and denitrification rates: Insights from molecular methods. Ecol. Appl. 16, 2143–2152 (2006).PubMed 

    Google Scholar 
    64.Höglander, H., Larsson, U. & Hajdu, S. Vertical distribution and settling of spring phytoplankton in the offshore NW Baltic Sea proper. Mar. Ecol. Prog. Ser. 283, 15–27 (2004).ADS 

    Google Scholar 
    65.Walsby, A. E. Gas vesicles. Annu. Rev. Plant Physiol. 26, 427–439 (1975).CAS 

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

    Google Scholar 
    67.Benson, D. A. et al. GenBank. Nucleic Acids Res. 41, 36–42 (2013).
    Google Scholar 
    68.Huson, D. H. et al. MEGAN community edition—Interactive exploration and analysis of large-scale microbiome sequencing data. PLoS Comput. Biol. 12, e1004957 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    69.Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, 590–596 (2013).
    Google Scholar 
    70.Murali, A., Bhargava, A. & Wright, E. S. IDTAXA: A novel approach for accurate taxonomic classification of microbiome sequences. Microbiome 6, 1–14 (2018).
    Google Scholar 
    71.Urban-Malinga, B., Warzocha, J. & Zalewski, M. Effects of the invasive polychaete Marenzelleria spp. on benthic processes and meiobenthos of a species-poor brackish system. J. Sea Res. 80, 25–34 (2013).ADS 

    Google Scholar 
    72.McMurdie, P. J. & Holmes, S. Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    73.Oksanen, J. et al. Vegan: Community ecology package. version 2.5-7, 1–298 (2020).74.Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).MATH 

    Google Scholar 
    75.Alberdi, A., Aizpurua, O., Gilbert, M. T. P. & Bohmann, K. Scrutinizing key steps for reliable metabarcoding of environmental samples. Methods Ecol. Evol. 9, 134–147 (2017).
    Google Scholar 
    76.Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 1–21 (2014).
    Google Scholar  More