Philippa Kaur

1.Hanson, J. M. Predator-prey interactions of American lobster (Homarus americanus) in the southern Gulf of St. Lawrence, Canada. New Zeal. J. Mar. Freshw. Res. 43, 69–88 (2009).
Google Scholar 
2.DFO. Canada’s Fisheries Fast Facts 2019. (2020).3.Fisheries and Oceans Canada. Integrated Fishery Management Plan (Summary). Lobster fishing area 27–38. Scotia-Fundy Sector Maritimes Region 2011. DFO Report (2009).4.Howell, W. H., Watson, W. H. & Jury, S. H. Skewed sex ratio in an estuarine lobster (Homarus americanus) population. J. Shellfish Res. 18, 193–201 (1999).
Google Scholar 
5.Jury, S. H., Pugh, T. L., Henninger, H., Carloni, J. T. & Watson, W. H. Patterns and possible causes of skewed sex ratios in American lobster (Homarus americanus) populations. Invertebr. Reprod. Dev. https://doi.org/10.1080/07924259.2019.1595184 (2019).Article 

Google Scholar 
6.Ogburn, B. M. The effects of sex-biased fisheries on crustacean sex ratios and reproductive output. Invertebr. Reprod. Dev. 63, 200–207 (2019).
Google Scholar 
7.Cooper, R., Clifford, R. & Newelll, C. Seasonal abundance of the American lobster, Homarus americanus, in the Boothbay region of Maine. Trans. Am. Fish. Soc. 104, 669–674 (1975).
Google Scholar 
8.Pitnick, S. Operational sex ratios and sperm limitation in populations of Drosophila pachea. Behav. Ecol. Sociobiol. 33, 383–391 (1993).
Google Scholar 
9.MacDiarmid, A. B. & Butler, M. J. IV. Sperm economy and limitation in spiny lobsters. Behav. Ecol. Sociobiol. 46, 14–24 (1999).
Google Scholar 
10.Sato, T. Plausible causes for sperm-store variations in the coconut crab Birgus latro under large male-selective harvesting. Aquat. Biol. 13, 11–19 (2011).
Google Scholar 
11.Ogburn, M., Roberts, P., Richie, K., Johnson, E. & Hines, A. Temporal and spatial variation in sperm stores in mature female blue crabs Callinectes sapidus and potential effects on brood production in Chesapeake Bay. Mar. Ecol. Prog. Ser. 507, 249–262 (2014).ADS 

Google Scholar 
12.Pardo, L. M., Rosas, Y., Fuentes, J. P., Riveros, M. P. & Chaparro, O. R. Fishery induces sperm depletion and reduction in male reproductive potential for crab species under male-biased harvest strategy. PLoS ONE 10, e0115525 (2015).PubMed 
PubMed Central 

Google Scholar 
13.Pardo, L. M. et al. High fishing intensity reduces females’ sperm reserve and brood fecundity in a eubrachyuran crab subject to sex-and size-biased harvest. ICES J. Mar. Sci. 74, 2459–2469 (2017).
Google Scholar 
14.Tremblay, J. M. & Smith, S. J. Lobster (Homarus americanus) catchability in different habitats in late spring and early fall. Mar. Freshw. Res. 52, 1321–1331 (2001).
Google Scholar 
15.Karnofsky, E., Atema, J. & RH, E. Field observations of social behavior, shelter use, and foraging in the lobster, Homarus americanus. Biol. Bull. 176, 239–246 (1989).PubMed 

Google Scholar 
16.Cowan, D. F., Watson, W., Solow, A. & Mountcastle, A. Thermal histories of brooding lobsters, Homarus americanus, in the Gulf of Maine. Springer 150, 463–470 (2007).
Google Scholar 
17.Chang, J., Chen, Y., Holland, D. & Grabowski, J. Estimating spatial distribution of American lobster Homarus americanus using habitat variables. Mar. Ecol. Prog. Ser. 420, 145–156 (2010).ADS 

Google Scholar 
18.Anderson, J., Olsen, Z., Wagner Glen Sutton, T., Gelpi, C. & Topping, D. Environmental drivers of the spatial and temporal distribution of spawning blue crabs Callinectes sapidus in the Western Gulf of Mexico. N. Am. J. Fish. Manag. 37, 920–934 (2017).
Google Scholar 
19.Crossin, G. T., Al-Ayoub, S. A., Jury, S. H., Howell, W. H. & Watson, W. H. Behavioral thermoregulation in the American lobster Homarus americanus. J. Exp. Biol. 201, 365–374 (1998).PubMed 
CAS 

Google Scholar 
20.Powers, J., Lopez, G., Cerrato, R. & Dove, A. Effects of thermal stress on Long Island Sound lobsters, H. americanus. in Long Island Sound Lobster Research Initiative Working Meeting. University of Connecticut at Avery Point, Groton. (2004).21.Comeau, M. & Savoie, F. Maturity and reproductive cycle of the female American lobster, Homarus americanus, in the southern Gulf of St. Lawrence, Canada. J. Crustac. Biol. https://doi.org/10.1163/20021975-99990290 (2002).Article 

Google Scholar 
22.Quinn, B. K. Threshold temperatures for performance and survival of American lobster larvae: A review of current knowledge and implications to modeling impacts of climate change. Fish. Res. 186, 383–396 (2017).
Google Scholar 
23.Campbell, A. & Stasko, A. Movement of lobsters (Homarus americanus) tagged in the Bay of Fundy, Canada. Mar. Biol. 92, 393–404 (1986).
Google Scholar 
24.Campbell, A. Aggregations of berried lobsters (Homarus americanus) in shallow waters off Grand Manan, eastern Canada. Can. J. Fish. Aquat. Sci. 47, 520–523 (1990).
Google Scholar 
25.Watson, W. & Jury, S. H. The relationship between American lobster catch, entry rate into traps and density. Taylor Fr. 9, 59–68 (2013).
Google Scholar 
26.Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the world’s marine ecosystems. Science 328, 1523–1528 (2010).ADS 
PubMed 
CAS 

Google Scholar 
27.Cheng, L. et al. Improved estimates of ocean heat content from 1960 to 2015. Sci. Adv. 3, 10 (2017).
Google Scholar 
28.Aiken, D. E. & Waddy, S. L. Environmental influence on recruitment of the American lobster, Homarus americanus: A perspective. Can. J. Fish. Aquat. Sci. 43, 2258–2270 (1986).
Google Scholar 
29.Greenan, B. J. W. et al. Climate change vulnerability of American lobster fishing communities in Atlantic Canada. Front. Mar. Sci. 6, 579 (2019).
Google Scholar 
30.QGIS Geographic Information System. QGIS Association. http://www.qgis.org/ (2021).31.Tveite, H. NNJoin. http://arken.nmbu.no/~havatv/gis/qgisplugins/NNJoin (2014).32.Hosmer, D. J., Lemeshow, S. & Sturdivant, R. Applied Logistic Regression (John Wiley & Sons, 2013).MATH 

Google Scholar 
33.Thakur, K. K. et al. Risk factors associated with soft-shelled lobsters (Homarus americanus) in southwestern Nova Scotia, Canada. FACETS 2, 15–33 (2017).
Google Scholar 
34.Dohoo, I., Martin, W. & Stryhn, H. Veterinary Epidemiologic Research (VER Inc., 2009).
Google Scholar 
35.Pezzack, D. S. et al. The American lobster Homarus americanus fishery off of south-western Nova Scotia (Lobster Fishing Area 34). Canadian Stock Assessment Secretariat Research Document 99/32 (1999).36.Watson, W. H. & Little, S. A. Differences in the size at maturity of female American lobsters, Homarus americanus, captured throughout the range of the offshore fishery. J. Crustac. Biol. 25, 585–592 (2005).
Google Scholar 
37.Pezzack, D., Tremblay, J., Claytor, R., Frail, C. & Smith, S. Stock status and indicators for the lobster fishery in Lobster Fishing Area 34. Canadian Stock Assessment Secretariat Research Document 2006/101 (2006).38.Wu, Y. & Tang, C. Atlas of ocean currents in eastern Canadian waters. Canadian Technical Report of Hydrography and Ocean Sciences. 271 (2011).39.Brickman, D. Could ocean currents be responsible for the west to east spread of aquatic invasive species in Maritime Canadian waters?. Mar. Pollut. Bull. 85, 235–243 (2014).PubMed 
CAS 

Google Scholar 
40.Cowan, D. F., Solow, A. & Beet, A. R. Patterns in abundance and growth of juvenile lobster Homarus americanus. CSIRO https://doi.org/10.1071/MF01191 (2001).Article 

Google Scholar 
41.Morse, B. L., Quinn, B. K., Comeau, M. & Rochette, R. Stock structure and connectivity of the American lobster (Homarus americanus) in the southern Gulf of St. Lawrence: Do benthic movements matter?. Can. J. Fish. Aquat. Sci. 75, 2096–2108 (2018).
Google Scholar 
42.Staples, K. W., Chen, Y., Townsend, D. W. & Brady, D. C. Spatiotemporal variability in the phenology of the initial intra-annual molt of American lobster (Homarus americanus Milne Edwards, 1837) and its relationship with bottom temperatures in a changing Gulf of Maine. Fish. Oceanogr. 28, 468–485 (2019).
Google Scholar 
43.Goñi, R., Quetglas, A. & Reñones, O. Differential catchability of male and female European spiny lobster Palinurus elephas (Fabricius, 1787) in traps and trammelnets. Fish. Res. 65, 295–307 (2003).
Google Scholar 
44.Audet, D., Miron, G. & Moriyasu, M. Biological characteristics of a newly established green crab (Carcinus maenas) population in the southern gulf of St. Lawrence, Canada. J. Shellfish Res. 27, 427–441 (2008).
Google Scholar 
45.Laurans, M., Fifas, S., Demaneche, S., Brérette, S. & Debec, O. Modelling seasonal and annual variation in size at functional maturity in the European lobster (Homarus gammarus) from self-sampling data. ICES J. Mar. Sci. 66, 1892–1898 (2009).
Google Scholar 
46.Cooper, R. & Uzmann, J. Migrations and growth of deep-sea lobsters, Homarus americanus. Science 171, 288–290 (1971).ADS 
PubMed 
CAS 

Google Scholar 
47.Robichaud, D. A. & Campbell, A. Annual and seasonal size-frequency changes of trap-caught lobsters (Homarus americanus) in the Bay of Fundy. J. Northw. Atl. Fish. Sci 11, 2 (1991).
Google Scholar 
48.Waddy, S. L. & Aiken, D. E. Seasonal variation in spawning by preovigerous American lobster (Homarus americanus) in response to temperature and photoperiod manipulation. Can. J. Fish. Aquat. Sci. 49, 1114–1117 (1992).
Google Scholar 
49.Campbell, A. & Stasko, A. B. Movements of lobsters (Homarus americanus) tagged in the Bay of Fundy, Canada. Mar. Biol. Int. J. Life Ocean. Coast. Waters 92, 393–404 (1986).
Google Scholar 
50.Haakonsen, H. & Anoruo, A. Tagging and migration of the American lobster Homarus americanus. Rev. Fish. Sci. 2, 79–93 (1994).
Google Scholar 
51.Lawton, P. & Lavalli, K. Postlarval, juvenile, adolescent and adult ecology. In Biology of the lobster Homarus americanus (ed. Jd, F.) 47–81 (Academic, 1995).
Google Scholar 
52.Attard, J. & Hudon, C. Embryonic development and energetic investment in egg production in relation to size of female lobster (Homarus americanus). Can. J. Fish. Aquat. Sci. 44, 1157–1164 (1987).
Google Scholar 
53.Krouse, J. Maturity, sex ratio, and size composition of the natural population of American lobster, Homarus americanus, along the Maine coast. Fish. Bull. 71, 165–173 (1973).
Google Scholar 
54.Sato, T. Impacts of large male-selective harvesting on reproduction: Illustration with large decapod crustacean resources. Aqua-BioSci. Monogr. 5, 67–102 (2012).CAS 

Google Scholar 
55.Raymond, S. M. C. & Todd, C. R. Assessing risks to threatened crayfish populations from sex-based harvesting and differential encounter rates: A new indicator for reproductive state. Ecol. Indic. 118, 106661 (2020).
Google Scholar 
56.Estrella, B. & McKiernan, D. Catch-Per-Unit-Effort and Biological Parameters from the Massachusetts Coastal Lobster (Homarus americanus) Resource: Description and Trends (NOAA Technical Report, 1989).
Google Scholar 
57.Smolowitz, R., Chistoserdov, A. Y. & Hsu, A. A description of the pathology epizootic shell disease in the American lobster (Homarus americanus) H. Milne Edwards 1837. J. Shellfish Res. 24, 749–756 (2005).
Google Scholar 
58.Glenn, R. & Pugh, T. Epizootic shell disease in American lobster (Homarus americanus) in Massachusetts coastal waters: Interactions of temperature, maturity, and intermolt duration. J. Crustac. Biol. 26, 639–645 (2006).
Google Scholar 
59.Chistoserdov, A., Quinn, R., Gubbala, S. & Smolowitz, R. Bacterial communities associated with lesions of shell disease in the American lobster Homarus americanus. J. Shellfish Res. 31, 449–462 (2012).
Google Scholar 
60.Meres, N. et al. Dysbiosis in epizootic shell disease of the American lobster (Homarus americanus). J. Shellfish Res. 31, 463–472 (2012).
Google Scholar 
61.Shields, J. D., Wheeler, K. N. & Moss, J. A. Histological assessment of the lobster (Homarus americanus) in the ‘100 Lobsters’ project. J. Shellfish Res. 31, 439–447 (2012).
Google Scholar 
62.Hoenig, J. M. et al. Impact of disease on the survival of three commercially fished species. Ecol. Appl. 27, 2116–2127 (2017).PubMed 

Google Scholar 
63.Stevens, B. Effects of epizootic shell disease in American lobster Homarus americanus determined using a quantitative disease index. Dis. Aquat. Organ. 88, 25–34 (2009).PubMed 

Google Scholar 
64.Clark, A. S., Jury, S. H., Goldstein, J. S., Langley, T. G. & Watson, W. H. A comparison of American lobster size structure and abundance using standard and ventless traps. Fish. Res. 167, 243–251 (2015).
Google Scholar 
65.Jury, S., Kinnison, M., Howell, W., Winsor, H. & Watson, I. The behavior of lobsters in response to reduced salinity. J. Exp. Mar. Biol. Ecol. 180, 23–37 (1994).
Google Scholar  More

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

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

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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

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

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

Mercury additions to the study catchmentMETAALICUS was conducted on the Lake 658 catchment at the Experimental Lakes Area (ELA; now IISD-ELA), a remote area in the Precambrian Shield of northwestern Ontario, Canada (49° 43′ 95″ N, 93° 44′ 20″ W) set aside for whole-ecosystem research31. The Lake 658 catchment includes upland (41.2 ha), wetland (1.7 ha) and lake surface (8.4 ha) areas. Lake 658 is a double basin (13 m depth), circumneutral, headwater lake, with a fish community consisting of forage (yellow perch (P. flavescens) and blacknose shiner (Notropis heterolepis)), benthivorous (lake whitefish (C. clupeaformis) and white sucker (Catostomus commersonii)), and piscivorous (northern pike (E. lucius)) fishes. The lake is closed to fishing.Hg addition methods used in METAALICUS have been described in detail elsewhere19,32,33. In brief, three Hg spikes, each enriched with a different stable Hg isotope, were applied separately to the lake surface, upland and wetland areas. Upland and wetland spikes were applied once per year (when possible; Fig. 1a) by fixed-wing aircraft (Cessna 188 AGtruck). Mercury spikes (as HgNO3) were diluted in acidified water (pH 4) in a 500 l fiberglass tank and sprayed with a stainless-steel boom on upland (approximately 79.9% 200Hg) and wetland (approximately 90.1% 198Hg) areas. Spraying was completed during or immediately before a rain event, with wind speeds less than 15 km h−1 to minimize drift of spike Hg outside of target areas. Aerial spraying of upland and wetland areas left a 20-m buffer to the shoreline, which was sprayed by hand with a gas-powered pump and fire hose to within about 5 m of the lake32. Average net application rates of isotopically labelled Hg to the upland and wetland areas were 18.5 μg m−2 yr−1 and 17.8 μg m−2 yr−1, respectively.The average net application rate for lake spike Hg was 22.0 μg m−2 yr−1. For each lake addition, inorganic Hg enriched with approximately 89.7% 202Hg was added as HgNO3 from four 20-l carboys filled with acidified lake water (pH 4). Nine lake additions were conducted bi-weekly at dusk over an 18-week (wk) period during the open-water season of each year (2001–2007) by injecting at 70-cm depth into the propeller wash of trolling electric motors of two boats crisscrossing each basin of the lake32,33. It was previously demonstrated with 14C additions to an ELA lake that this approach evenly distributed spike added in the evening by the next morning34.We did not attempt to simulate Hg in rainfall for isotopic lake additions because it is impossible to simulate natural rainfall concentrations (about 10 ng l−1) in the 20-l carboys used for additions. Instead, our starting point for the experiment was to ensure that the spike was behaving as closely as possible to ambient surface water Hg very soon after it entered the lake. Several factors support this assertion. By the next morning each spike addition had increased epilimnetic Hg concentrations by only 1 ng l−1 202Hg. Average ambient concentrations were 2 ng l−1. Thus, while the Hg concentrations in the carboys were high (2.6 mg l−1), the receiving waters were soon at trace levels. Furthermore, we investigated if the additions altered the degree of bioavailability or photoreactivity of Hg(ii) in the receiving surface water. We examined the bioavailability of spike Hg(ii) as compared to ambient Hg in the lake itself using a genetically engineered bioreporter bacterium35. On seven occasions, epilimnetic samples were collected on the day before and within 12 h of spike additions. The spike was added to the lake as Hg(NO3)2, which is bioavailable to the bioreporter bacterium (detection limit = 0.1 ng Hg(ii) l−1), but we never saw bioavailable ambient or spike Hg(ii) in the lake, presumably because it was quickly bound to dissolved organic carbon (DOC). This indicates that, in terms of bioavailability, the spike Hg was behaving like ambient Hg soon after additions. Photoreactivity in the surface water was examined on seven occasions, by measuring the % of total Hg(ii) that was dissolved gaseous Hg for spike and ambient Hg, either 24 h or 48 h after the lake was spiked36. There was no significant difference (paired t-test, P > 0.05), demonstrating that by then the lake spike was behaving in the same way as ambient Hg during gaseous Hg production.Lake, food web and fish samplingWater samples were collected from May to October every four weeks at the deepest point of Lake 658. Water was pumped from six depths through acid-cleaned Teflon tubing into acid-cleaned Teflon or glass bottles. Water samples were filtered in-line using pre-ashed quartz fibre filters (Whatman GFQ, 0.7 µm). Subsequently, Hg species were measured in the filtered water samples (dissolved Hg and MeHg) and in particles collected on the quartz fibre filter (particulate Hg and MeHg).From 2001 to 2012, Lake 658 sediments were sampled at 4 fixed sites up to 5 times per year. Sampling frequency was highest in 2001, with monthly sampling from May to September, and declined over the course of the study. Fixed sites were located at depths of 0.5, 2, 3 and 7 m. A sediment survey of up to 12 additional sites was also conducted once or twice each year. Survey sites were selected to represent the full range of water depths in both basins. Cores were collected by hand by divers, or by subsampling sediments collected using a small box corer. Cores were capped and returned to the field station for processing within a few hours. For each site, three separate cores were sectioned and composited in zipper lock bags for a 0- to 2-cm depth sampling horizon, and then frozen at −20 °C.Bulk zooplankton and Chaoborus samples were collected from Lake 658 for MeHg analysis. Zooplankton were collected during the day from May to October (bi-weekly: 2001–2007; monthly: 2008–2015). A plankton net (150 μm, 0.5 m diameter) was towed vertically through the water column from 1 m above the lake bottom at the deepest point to the surface of the lake. Samples were frozen in plastic Whirl-Pak bags after removal of any Chaoborus using acid-washed tweezers. Dominant zooplankton taxa in Lake 658 included calanoid copepods (Diaptomus oregonensis) and Cladocera (Holopedium glacialis, Daphnia pulicaria and Daphnia mendotae). Chaoborus samples were collected monthly in the same manner at least 1 h after sunset. After collection, Chaoborus were picked from the sample using forceps and frozen in Whirl-Pak bags. Chaoborus were not separated by species for MeHg analyses, but both C. flavicans and C. punctipennis occur in the lake. Profundal chironomids were sampled at the deepest part of the lake using a standard Ekman grab sampler. Grab material was washed using water from a nearby lake and individual chironomids were picked by hand.All work with vertebrate animals was approved by Animal Care Committees (ACC) through the Canadian Council on Animal Care (Freshwater Institute ACC for Fisheries and Oceans Canada, 2001–2013; University of Manitoba ACC for IISD-ELA, 2014–2015). Licenses to Collect Fish for Scientific Purposes were granted annually by the Ontario Ministry of Natural Resources and Forestry. Prior to any Hg additions, a small-mesh fence was installed at the outlet of Lake 658 to the downstream lake to prevent movement of fish between lakes. Sampling for determination of MeHg concentrations (measured as total mercury (THg), see below) occurred each autumn (August–October; that is, the end of the growing season in north temperate lakes) for all fish species in Lake 658, and for northern pike and yellow perch in nearby reference Lake 240 (Extended Data Tables 2, 3). Fish collections occurred randomly throughout the lakes. Forage fish (YOY and 1+ yellow perch, and blacknose shiner) were captured using small mesh gillnets (6–10 mm) set for 90% of the Hg in muscle tissue from yellow perch in Lake 658 is MeHg40,41, here we report fish mercury data as MeHg.THg concentrations (ambient, lake spike, upland spike and wetland spike) in fish muscle samples were quantified by ICP-MS39. Samples were digested with HNO3/H2SO4 (7:3 v/v) and heated at 80 °C until brown NOx gases no longer formed. The THg in sample digests was reduced by SnCl2 to Hg0 which was then quantified by ICP-MS (Thermo-Finnigan Element2) using a continuous flow cold vapour generation technique41. To correct for procedural recoveries, all samples were spiked with 201HgCl2 prior to sample analysis. Samples of CRMs (DORM2 (2001–2011), DORM3 (2012–2013), DORM4 (2014–2015); National Research Council of Canada) were submitted to the same procedures; measured THg concentrations in the reference materials were not statistically different from certified values (P > 0.05). Detection limit for each of the spikes was 0.5% of ambient Hg.Calculations and statistical methodsAnalyses were completed with Statistica (6.1, Statsoft) and Sigmaplot (11.0, Systat Software). We present wet weight (w.w.) MeHg concentrations for all samples, except sediments which are dry weight (d.w.) concentrations. For zooplankton, Chaoborus, and profundal chironomids, d.w. MeHg concentrations were multiplied by a standard proportion (0.15) to yield w.w. concentrations for each sample42. The resulting w.w. concentrations were averaged over each open water season to determine annual means. For fish muscle biopsies, d.w. MeHg concentrations were multiplied by individual d.w. proportions to yield w.w. MeHg concentrations for each sample. To avoid any size-related biases, we calculated standardized annual MeHg concentrations (ambient and lake spike) for northern pike and lake whitefish by determining best-fit relationships between FL and MeHg concentrations for each year (quadratic polynomial, except for a linear fit for lake whitefish in 2004), and using the resulting regression equations to estimate MeHg concentrations at a standard FL43 (the mean FL of all fish sampled for each species: northern pike, 475 mm; lake whitefish, 530 mm). Square root transformation of raw northern pike data was required to satisfy assumptions of normality and homoscedasticity prior to standardization. The resulting data represent standardized concentrations of lake spike and ambient MeHg for each species each year.We used the ratio of lake spike and ambient Hg in each sample as a measure of the amount by which Hg concentrations were changed with the addition of isotopically enriched Hg:$${rm{P}}{rm{e}}{rm{r}}{rm{c}}{rm{e}}{rm{n}}{rm{t}},{rm{i}}{rm{n}}{rm{c}}{rm{r}}{rm{e}}{rm{a}}{rm{s}}{rm{e}}={[{rm{l}}{rm{a}}{rm{k}}{rm{e}}{rm{s}}{rm{p}}{rm{i}}{rm{k}}{rm{e}}{rm{H}}{rm{g}}]}_{i}/{[{rm{a}}{rm{m}}{rm{b}}{rm{i}}{rm{e}}{rm{n}}{rm{t}}{rm{H}}{rm{g}}]}_{i}times 100$$
(1)
where [lake spike Hg]i is the concentration of lake spike MeHg in sample i, and [ambient Hg]i is the concentration of ambient MeHg in sample i. For northern pike and lake whitefish, we calculated the mean annual relative increase from all individuals (not the size-standardized concentration data).Biomagnification factors (BMF) were calculated to describe differences in Hg concentrations between predator and prey5:$${rm{BMF}}={log }_{10}({[{rm{MeHg}}]}_{{rm{p}}{rm{r}}{rm{e}}{rm{d}}{rm{a}}{rm{t}}{rm{o}}{rm{r}}}/{[{rm{MeHg}}]}_{{rm{p}}{rm{r}}{rm{e}}{rm{y}}})$$
(2)
where [MeHg]predator is the mean (forage fish) or standardized (large-bodied fish) concentration of MeHg in the predator (ng g−1 w.w.) and [MeHg]prey is the mean concentration of MeHg in the prey (ng g−1 w.w.). MeHg concentration of prey items were averaged from samples collected throughout the open-water season immediately prior to autumn sampling of fish species to represent an integrated exposure for calculation of BMF. We used a dominant prey item to represent the diet of each fish species. For age 1+ yellow perch, northern pike, and lake whitefish, dominant prey items were zooplankton, forage fishes (YOY and 1+ yellow perch, and blacknose shiner) and Chaoborus, respectively.To assess loss of lake spike MeHg by northern pike during the recovery period (2008–2015), we calculated28 whole body burdens (in μg) of lake spike MeHg for the standardized population and for individuals that had been sampled in autumn 2007 (t0 is the final time spike Hg was added to the lake) and again in at least one subsequent year during annual autumn sampling (n = 16 fish, of which 1–9 individuals were recaptured annually from 2008–2015). This calculation of MeHg burden is a relative measure of whole fish Hg content because MeHg is higher in muscle tissue than in other tissue types28,40. For the standardized population data, we used best-fit relationships between FL (in mm) and body weight (in g; quadratic polynomial) to determine body weight at the standard FL. We multiplied this body weight by standard ambient and spike MeHg concentrations (in ng g−1 w.w.) in muscle tissue for each year to determine body burdens over time (in ng). For individual fish, we multiplied spike MeHg concentration (in ng g−1 w.w.) by body weight (in g) to yield individual body burdens (in ng). To account for differences among individuals and between individuals and the population, we normalized the data to examine the mean proportion of original (t0) lake spike MeHg burden present in northern pike each year of the recovery period (2008–2015).$${rm{change}},{rm{in}},{rm{burden}},{rm{from}},{t}_{0}={{rm{burden}}}_{{rm{tx}}}/{{rm{burden}}}_{{rm{t}}0}$$
(3)
We used a best fit regression (exponential decay, beginning in the second year of recovery) to estimate the half-life (50% of original burden) of lake spike MeHg for the population.Northern pike and lake whitefish ages were determined by cleithra and otoliths, respectively, if mortality had occurred, but most ages were quantified using fin rays collected from live fish44 (K. H. Mills, DFO or North/South Consultants). Northern pike of the sizes selected for biopsy sampling had a median age of 3 years (range: 2–12 years; n = 305); the median age of lake whitefish was 17 years (range: 3–38 years; n = 86).Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this paper. More