Ecology

Seawater surface pH (total scale), Ωarag and temperatures (SST) showed a strong gradient at the entrance into the bay (Fig. 2a, b, e) and the seawater pH range (7.65–8.02) observed within the bay was equivalent to the ocean pH value from present to the value expected by the end of this century (IPCC 2013, RCP 8.5)29. The mean daytime seawater temperature within the bay was significantly warmer (31.8 ± 0.6 °C, mean ± S.D.) and had lower pH (7.83 ± 0.06), lower Ωarag, (2.44 ± 0.34) and higher pCO2 (619 ± 104 μatm) compared to parameters outside the bay (30.4 ± 0.1 °C, 8.02 ± 0.02, 391 ± 31 μatm, 3.63 ± 0.14, Wilcoxon-test, p  More

1.Gamow, G. Biography of Physics (Harper, 1961).2.Cang, Z., Mu, L. & Wei, G.-W. PLoS Comput. Biol. 14, e1005929 (2018).Article 

Google Scholar 
3.Reimann, M. W. et al. Front. Comput. Neurosci. 11, 48 (2017).Article 

Google Scholar 
4.Angulo, M. T., Kelley, A., Montejano, L., Song, C. & Saavedra, S. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-021-01462-8 (2021).Article 

Google Scholar 
5.Ghrist, R. Bull. Am. Math. Soc. 45, 61–75 (2008).Article 

Google Scholar 
6.Chesson, P. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).Article 

Google Scholar 
7.Friedman, J., Higgins, L. M. & Gore, J. Nat. Ecol. Evol. 1, 0109 (2017).Article 

Google Scholar 
8.Grilli, J., Barabás, G., Michalska-Smith, M. J. & Allesina, S. Nature 548, 210–213 (2017).CAS 
Article 

Google Scholar 
9.Grainger, T. N., Levine, J. M. & Gilbert, B. Trends Ecol. Evol. 34, 925–935 (2019).Article 

Google Scholar 
10.Gould, A. L. et al. Proc. Natl Acad. Sci. USA 115, E11951–E11960 (2018).CAS 
Article 

Google Scholar 
11.Letten, A. D. & Stouffer, D. B. Ecol. Lett. 22, 423–436 (2019).Article 

Google Scholar 
12.Fukami, T. Annu. Rev. Ecol. Evol. Syst. 46, 1–23 (2015).Article 

Google Scholar  More

1.Fitzsimmons, K. M., Gonzalez-Alanis, P. & Martinez-Garcia, R. Why tilapia is becoming the most important food fish on the planet? In Proceedings of the 9th International Symposium on tilapia in Aquaculture, Shanghai Ocean University, Shanghai, China, 22-24 April 2011 8–16 (2011).2.FAO. The State of World Fisheries and Aquaculture. Meeting the sustainable development goals. Rome. Licence. CC BY-NC-SA 3.0 IGO (Food and Agriculture Organisation, 2018).3.ADB. An impact evaluation of the development of genetically improved farmed tilapia and their dissemination in selected countries. The Asian Development Bank, Manila, Philippines 90 (Asian Development Bank, 2004).4.Macaranas, J. M., Taniguchi, N., Pante, M. J. R., Capili, J. B. & Pullin, R. S. V. Electrophoretic evidence for extensive hybrid gene introgression into commercial Oreochromis niloticus (L.) stocks in the Philippines. Aquac. Res. 17, 249–258 (1986).CAS 
Article 

Google Scholar 
5.ADB. An impact evaluation of the development of genetically improved farmed tilapia and their dissemination in selected countries. The Asian Development Bank, Manila, Philippines 137 (Asian Development Bank, 2005).6.Bradbeer, S. J. et al. Limited hybridization between introduced and critically endangered indigenous tilapia fishes in Northern Tanzania. University of Bristol. Hydrobiologia https://doi.org/10.1007/s10750-018-3572-5b (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
7.Shechonge, A. et al. Losing cichlid fish biodiversity: Genetic and morphological homogenization of tilapia following colonization by introduced species. Conserv. Genet. 19(5), 1199–1209 (2018).8.Gupta, M. V & Acosta, B. O. A review of global tilapia farming practices. Aquac. Asia 9, 7–12 (2004). 9.Eknath, A., Dey, M. M., Rye, M. & Gjerde, B. Selective breeding of Nile tilapia for Asia. In Proceedings of the 6th World Congress on Genetics Applied to Livestock Production, Armidale, Australia, University of New England. 27, 89–96 (1998).10.Ponzoni, R. W. et al. Genetic improvement of Nile tilapia (Oreochromis niloticus) with special reference to the work conducted by the WorldFish Center with the GIFT strain. Rev. Aquac. 3, 27–41 (2011).Article 

Google Scholar 
11.WorldFish. Genetically Improved Farmed Tilapia (GIFT). Key facts ongoing and future research. FactSheet. https://digitalarchive.worldfishcenter.org/bitstream/handle/20.500.12348/66/3880_2015-31.pdf?sequence=1&isAllowed=y (2015).
12.Bolivar, R. Estimation of response to within-family selection for growth in Nile tilapia (Oreochromis niloticus). PhD. Dissertation, Dalhousie University, Halifax, N.S. Canada. 166 (1998).13.Tayamen, M. M. Nationwide dissemination of GET-EXCEL tilapia in the Philippines. In Proceeding of the Sixth International Symposium on Tilapia in Aquaculture. Bureau of Fisheries and Aquatic Resources, Manila, Philippines, and American Tilapia Association, Charles Town, West Virginia (ed. Bolivar, R,B., Mair, G.C and Fitzsimmons, K.) 74–85 (2004).14.Zimmerman, S. & Natividad, J. M. Comparative pond performance evaluation of GenoMar Supreme Tilapia GST 1 and GST 3 groups. In Proceeding of the Sixth International Symposium on Tilapia in Aquaculture. Bureau of Fisheries and Aquatic Resources, Manila, Philippines, and American Tilapia Association, Charles Town, West Virginia (ed. Bolivar, R.B., Mair, G.C and Fitzsimmons, K.) 89 (2004).
15.Thodesen, J. et al. Genetic improvement of tilapias in China: Genetic parameters and selection responses in growth, survival and external color traits of red tilapia (Oreochromis spp.) after four generations of multi-trait selection. Aquaculture 416–417, 354–366 (2013).Article 

Google Scholar 
16.Ansah, Y. B., Frimpong, E. A. & Hallerman, E. M. Genetically-improved tilapia strains in Africa: Potential benefits and negative impacts. Sustain. 6, 3697–3721 (2014).Article 

Google Scholar 
17.Charo-karisa, H. Selection for growth of Nile tilapia (Oreochromis niloticus L.) in low-input environments. PhD Thesis, Wageningen University, The Netherlands (2006). 18.Kohinoor, A. H. M., Modak, P. C. & Hussain, M. G. Growth and production performance of red tilapia and Nile tilapia (Oreochromis niloticus L.) under low-input culture system. Bangladesh J. Fish Res. 3, 11–17 (1999).
Google Scholar 
19.Vadhel, N. et al. Red Tilapia: A candidate euryhaline species for aqua farming in Gujarat. J. Fish. 11(1), 048–050 (2017).
Google Scholar 
20.Felix, E., Avwemoya, F. E. & Abah, A. Some methods of monosex tilapia production: A review. Int. j. fish. aquat. res. 4(2), 42–49 (2019). 21.Fuentes-silva, C., Soto-zarazúa, G. M., Torres-pacheco, I. & Flores-rangel, A. Male tilapia production techniques: A mini-review. Afr. J. Biotechnol. 12, 5496–5502 (2013).
Google Scholar 
22.Wohlfarth, G. W. The unexploited potential of tilapia hybrids in aquaculture. Aquacult Fish Manage, 25, 781–788 (1994).23.Lahav, M. & Lahav, E. The development of all-male tilapia hybrids in Nir David. Bamidgeh. Isr. J. Aquac. 42, 58–61 (1990).
Google Scholar 
24.Siddiqui, A. Q. & Al-harbi, A. H. Evaluation of three species of tilapia, red tilapia and a hybrid tilapia as culture species in Saudi Arabia. Aquaculture 8486, 145–157 (1995).Article 

Google Scholar 
25.Gjerde, B. et al. Growth and survival in two complete diallele crosses with five stocks of Rohu carp (Labeo rohita). Aquaculture 209, 103–115 (2002).Article 

Google Scholar 
26.Mbiru, M. et al. Comparative performance of mixed-sex and hormonal sex-reversed Nile tilapia Oreochromis niloticus and hybrids (Oreochromis niloticus × Oreochromis urolepis hornorum) cultured in concrete tanks. Aquac. Int. 24, 557–566 (2015).Article 
CAS 

Google Scholar 
27.Marengoni, N. G. et al. Morphological traits and growth performance of monosex male tilapia GIFT strain and Saint Peter®. Semin. Agrar. 36, 3399–3410 (2015).Article 

Google Scholar 
28.Eknath, A. E. & Acosta, B. O. Genetic improvement of farmed tilapias (GIFT) project: Final report, March to December 1997. International Center for Living Aquatic Resources Management (ICLARM), Makati City, Philippines 75 (1988). 29.Dan, N. C. & Little, D. C. The culture performance of monosex and mixed-sex new-season and overwintered fry in three strains of Nile tilapia (Oreochromis niloticus) in northern Vietnam. Aquaculture 184, 221–231. https://doi.org/10.1016/S0044-8486(99)00329-4 (2000).Article 

Google Scholar 
30.Kohinoor, A. H. M., Rahman, M. & Islam, S. Upgradation of genetically improved farmed tilapia (GIFT) strain by family selection in Bangladesh. Int. J. Fish. Aquat. Stud. 4, 650–654 (2016).
Google Scholar 
31.Ridha, M. Preliminary study on growth, feed conversion and production in non-improved and improved strains of the Nile tilapia Oreochromis niloticus. Fisheries and Marine Environment Department, Kuwait Institute for scientific Research, Salmiyah 22017, Kuwait (2016).32.Santos, B., Mareco, E. & Silva, M. Growth curves of Nile tilapia (Oreochromis niloticus) strains cultivated at different temperatures. Acta Sci. Anim. Sci. 35, 235–242 (2013).
Google Scholar 
33.Eknath, A. E. et al. Genetic improvement of farmed tilapias: Composition and genetic parameters of a synthetic base population of Oreochromis niloticus for selective breeding. Aquaculture 273, 1–14 (2007).CAS 
Article 

Google Scholar 
34.Sukmanomon, S. et al. Genetic changes, intra- and inter-specific introgression in farmed Nile tilapia (Oreochromis niloticus) in Thailand. Aquaculture 324–325, 44–54 (2012).Article 

Google Scholar 
35.Anane-taabeah, G., Frimpong, E. A. & Hallerman, E. Aquaculture-mediated invasion of the Genetically Improved Farmed Tilapia (GIFT) into the Lower Volta Basin of Ghana. Diversity (Basel) 11, 188 (2019).CAS 
Article 

Google Scholar 
36.Trinh, T. Q., Agyakwah, S. K., Khaw, H. L., Benzie, J. A. H. & Attipoe, F. K. Y. Performance evaluation of Nile tilapia (Oreochromis niloticus) improved strains in Ghana. Aquaculture 530, 735938 (2021).CAS 
Article 

Google Scholar 
37.Canonico, G., Oceanic, N. & Arthington, A. H. The effects of introduced tilapias on native biodiversity. Aquat. Conserv. Mar. Freshw. Ecosyst. 15, 463–483 (2005).Article 

Google Scholar 
38.Lind, C. E., Brummett, R. E. & Ponzoni, R. W. Exploitation and conservation of fish genetic resources in Africa: Issues and priorities for aquaculture development and research. Rev. Aquac. 4, 125–141 (2012).Article 

Google Scholar 
39.URT. Ministry Livestock and Fisheries.Annual Report, Dodoma, Tanzania (United Republic of Tanzania, 2019).40.URT. Ministry of Livestock and Fisheries. Annual Report, Dodoma, Tanzania (United Republic of Tanzania, 2018).41.Mbiru, M. et al. Characterizing the genetic structure of introduced Nile tilapia (Oreochromis niloticus) strains in Tanzania using double digest RAD sequencing. Int. Aquac. https://doi.org/10.1007/s10499-019-00472-5 (2019).Article 

Google Scholar 
42.Kajungiro, R. A. et al. Population structure and genetic diversity of Nile Tilapia (Oreochromis niloticus) strains cultured in Tanzania. Front. Genet. 10, 1–12. https://doi.org/10.3389/fgene.2019.01269 (2019).Article 

Google Scholar 
43.Rothuis, A. et al. Aquaculture in East Africa: A regional approach. Wageningen, LEI Wageningen UR (University & Research Centre), LEI Report. IMARES C153/14| LEI. 14–120 (2014).44.URT. Vice President’s Office, Division of Environment: National Adaptation Programme of Action(NAPA, 2007).45.ATLAS. Climate change in Tanzania: Country risk profile. Task Order No. AID-OAA-I-14-00013 1–5 (Climate Change Adaptation, Thought Leadership and Assessments, 2018).46.Kassambara, A. ggpubr: ‘ggplot2’ Based Publication Ready Plot. 2019. https://rdrr.io/cran/ggpubr 2020/03/24 (2019).47.Shapiro, S. S. & Wilk, M. B. An analysis of variance test for normality (complete samples). Biometrika 52, 591–611 (1965).MathSciNet 
MATH 
Article 

Google Scholar 
48.Evans, J. Straightforward Statistics for the Behavioral Sciences (Brooks/Cole Publishing, 1996).
Google Scholar 
49.Cohen, J. Statistical Power Analysis for the Behavioral Sciences 2nd edn. (Routledge, 1988).MATH 

Google Scholar 
50.Fox, J. & Weisberg, S. car: Companion to Applied Regression. Third Edition, Sage. Version 3.0–7 (2019). 51.Lenth, R., Singmann, H., Love, J., Buerkner, P. & Herve, M. emmeans: Estimated marginal means, aka least-squares means. R Package version 3.5.3. http://CRAN.R-project.org/package=emmeans, https://doi.org/10.1080/00031305.1980.10483031. (2020).52.Dey, M. M. et al. Performance and nature of genetically improved farmed tilapia: A bioeconomic analysis. Aquac. Econ. Manag. 4, 1–2 (2000).Article 

Google Scholar 
53.Sifa, L., Chenhong, L. & Dey, M. Cold tolerance of three strains of Nile tilapia, Oreochromis niloticus, in China. Aquaculture 213, 123–129 (2002).Article 

Google Scholar 
54.Cnaani, A., Gall, G. A. E. & Hulata, G. Cold tolerance of tilapia species and hybrids. Aquac. Int. 8, 289–298 (2000).Article 

Google Scholar 
55.Nandlal, S., Morris, C. W., Lagibalavu, M. & Ledua, E. A comparative evaluation of two tilapia strains in Fiji, 35–41. In Proceeding of the Fish Genetics Research in Member Countries and Institutions of the International Network on Genetics in Aquaculture. ICLARM Conf. Proc, 2-5 March 1999, Kuala Lumpur, Malaysia (eds. Gupta, M. V. & Acosta, B. O.) 64, (179), 35–42 (2001).56.Hussain, M. G. et al. Genetic evaluation of GIFT and existing strains of nile tilapia, Oreochromis niloticus L., under on-station and on-farm conditions in Bangladesh. Asian Fish. Sci. 13, 117–126 (2000).
Google Scholar 
57.Hopkins, K. Reporting fish growth: A review of the basics. J. World Aquac. Soc. 33, 173–179 (1992).Article 

Google Scholar 
58.Bhujel, R. C. On-farm feed management practices for Nile tilapia in Thailand. In On-Farm Feeding and Feed Management in Aquaculture. FAO Fisheries and Aquaculture Technical Paper No. 583. Rome. (ed. Hasan, M. R. & New, M. B.) 159–189 (2013).59.Volpato, G. & Fernandes, M. Social control of growth in fish. Braz. J. Med. Biol. Res. 27, 797–810 (1994).
Google Scholar 
60.Enquist, M. & Jakobsson, S. Decision making and assessment in the fighting behaviour of Nannacara anomala (Cichlidae, Pisces). Ethology 72, 143–153 (1986).Article 

Google Scholar 
61.Boscolo, C. N. P., Morais, R. N. & Freitas, E. G. Same-sized fish groups increase aggressive interaction of sex-reversed males Nile tilapia GIFT strain. Appl. Anim. Behav. Sci. 135, 154–159 (2011).Article 

Google Scholar 
62.Ebtehag Kamel, A. R. Evaluation of reproductive performance of tilapia strains and some of their crosses. J. Arab. Aquac. Soc. 6, 119–138 (2011).
Google Scholar 
63.Thoa, N. P., Ninh, N. H., Hoa, N. T., Knibb, W. & Diep, N. H. Additive genetic and heterotic effects in a 4 × 4 complete diallel cross-population of Nile tilapia (Oreochromis niloticus, Linnaeus, 1758) reared in different water temperature environments in different water temperature environments in Northern Viet. Aquac. Res. 47, 708–720 (2016).Article 
CAS 

Google Scholar 
64.Ridha, M. T. Comparative study of growth performance of three strains of Nile tilapia, Oreochromis niloticus, L., at two stocking densities. Aquac. Res. 37, 172–179 (2006).Article 

Google Scholar 
65.Khan, S., Hossain, M. & Science, P. Production and economics of GIFT strain of tilapia (Oreochromis niloticus) in small seasonal ponds. Progress. Agric. 19(1), 97–104 (2008).Article 

Google Scholar 
66.Alam, M. B., Islam, M. A., Marine, S. S., Rashid, A. & Hossain, M. A. Growth performances of GIFT tilapia (Oreochromis niloticus) in Cage culture at the Old Brahmaputra river using different densities. J. SylhetAgril. Univ. 1(2), 265–271 (2014).
Google Scholar 
67.Matthew, M. T. et al. Growth performance evaluation of four wild strains and one current farmed strain of Nile tilapia in Uganda. Int. J. Fish. Aquat. Stud. 4, 594–598 (2016).
Google Scholar 
68.Shoko, A. P., Limbu, S. M., Mrosso, H. D. J., Mkenda, A. F. & Mgaya, Y. D. Effect of stocking density on growth, production and economic benefits of mixed sex Nile tilapia (Oreochromis niloticus) and African sharptooth catfish (Clarias gariepinus) in polyculture and monoculture. Aquac. Res. https://doi.org/10.1111/are.12463 (2014).Article 

Google Scholar 
69.Hasan, S. J., Mian, S., Rashid, A. H. & Rahmatullah, S. M. Effects of stocking density on growth and production of GIFT Tilapia (Oreochromis niloticus). Bangladesh. Fish. Res. 14, 45–53 (2010).
Google Scholar 
70.Rahman, M. M., Mondal, D. K., Amin, M. R. & Muktadir, M. G. Impact of stocking density on growth and production performance of monosex tilapia (Oreochromis niloticus) in ponds. Asian J. Med. Biol. Res. 2, 471–476 (2016).Article 

Google Scholar 
71.Li, S. et al. Improving growth performance and caudal fin stripe pattern in selected F6–F8 generations of GIFT Nile tilapia (Oreochromis niloticus L.) using mass selection. Aquac. Res. 37, 1165–1171 (2006).CAS 
Article 

Google Scholar 
72.Dos Santos, B., Vander Silva, V. V., De, M. V., Mareco, E. A. & Salomão, R. A. S. Performance of Nile tilapia Oreochromis niloticus strains in Brazil: A comparison with Philippine strain. J. Appl. Anim. Res. 47, 72–78 (2019).Article 

Google Scholar 
73.Reis Neto, V. et al. Genetic parameters and trends of morphometric traits of GIFT tilapia under selection for weight gain. Sci. Agric. 71, 259–265 (2014).Article 

Google Scholar 
74.Gilbert, H. R. & Gregory, P. W. Some features of growth and development of Hereford cattle. J. Anim. Sci. 11, 3–16 (1952).Article 

Google Scholar 
75.Russell, W. S. T. The growth of Ayrshire cattle: An analysis of linear body measurements. J. Anim. Sci. 21, 217–226 (1975).Article 

Google Scholar 
76.Montoya-lópez, A., Moreno-arias, C., Tarazona-morales, A., Olivera-Angel, M. & Betancur, J. Body shape variation between farms of tilapia (Oreochromis sp.) in Colombian Andes using landmark based geometric morphometrics. Lat. Am. J. Aquat. Res. 47, 194–200 (2019).Article 

Google Scholar 
77.Bœuf, G. & Payan, P. How should salinity influence fish growth?. Comp. Biochem. Physiol. C Toxicol. Pharmacol. 130(4), 411–423 (2001).PubMed 
Article 
PubMed Central 

Google Scholar 
78.Azevedo, R. V. et al. Responses of Nile tilapia to different levels of water salinity Rafael. Lat. Am. J. Aquat. Res. 43, 828–835 (2015).
Google Scholar 
79.Nguyen, H. N., Khaw, L. H., Ponzoni, R. W., Hamzah, A. & Kamaruzzaman, N. Can sexual dimorphism and body shape be altered in Nile tilapia (Oreochromis niloticus) by genetic means?. Aquaculture 272S1, S38–S46 (2007).Article 

Google Scholar 
80.Imre, I., McLaughlin, R. L. & Noakes, D. L. G. Phenotypic plasticity in brook charr: Changes in caudal fin induced by water flow. J. Fish Biol. 61, 1171–1181 (2002).Article 

Google Scholar 
81.Costa, C. et al. Genetic and environmental influences on shape variation in the European sea bass (Dicentrarchus labrax). Biol. J. Linn. Soc. 101, 427–436 (2010).Article 

Google Scholar 
82.Vehanen, T. & Huusko, A. Brown trout Salmo trutta express different morphometrics due to divergence in the rearing environment. J. Fish Biol. 79, 1167–1181 (2011).CAS 
PubMed 
Article 

Google Scholar 
83.Ndiwa, T. C., Nyingi, D. W., Claude, J. & Agnèse, J.-F. Morphological variations of wild populations of Nile tilapia (Oreochromis niloticus) living in extreme environmental conditions in the Kenyan Rift-Valley. Environ. Biol. Fishes. https://doi.org/10.1007/s10641-016-0492-y (2016).Article 

Google Scholar 
84.Khaw, L. H., Ponzoni, R. W., Hamzah, A., Abu-bakar, K. R. & Bijma, P. Genotype by production environment interaction in the GIFT strain of Nile tilapia (Oreochromis niloticus). Aquaculture 326–329, 53–60 (2012).Article 

Google Scholar 
85.Kosai, P., Sathavorasmith, P., Jiraungkoorskul, K. & Jiraungkoorskul, W. Morphometric characters of Nile Tilapia
(Oreochromis niloticus) in Thailand. Walailak Jour. Sci. and Tech. 11(10), 857–863 (2014). More

1.Ellis, B. J., Figueredo, A. J., Brumbach, B. H. & Schlomer, G. L. Fundamental dimensions of environmental risk—The impact of harsh versus unpredictable environments on the evolution and development of life history strategies. Hum. Nat. 20, 204–268. https://doi.org/10.1007/s12110-009-9063-7 (2009).Article 
PubMed 

Google Scholar 
2.Reznick, D. A., Bryga, H. & Endler, J. A. Experimentally induced life-history evolution in a natural population. Nature 346, 357–359. https://doi.org/10.1038/346357a0 (1990).ADS 
Article 

Google Scholar 
3.Pianka, E. R. On r- and K-selection. Am. Nat. 104, 592–597. https://doi.org/10.1086/282697 (1970).Article 

Google Scholar 
4.Stearns, S. C. Life-history tactics: A review of the ideas. Q. Rev. Biol. 51, 3–47. https://doi.org/10.1086/409052 (1976).CAS 
Article 
PubMed 

Google Scholar 
5.Flegr, J. Two distinct types of natural selection in turbidostat-like and chemostat-like ecosystems. J. Theor. Biol. 188, 121–126. https://doi.org/10.1006/jtbi.1997.0458 (1997).Article 

Google Scholar 
6.Bowyer, R. T., Person, D. K. & Pierce, B. M. Detecting top-down versus bottom-up regulation of ungulates by large carnivores: Implications for conservation of biodiversity. In Large Carnivores and the Conservation of Biodiversity (eds. Ray, J. C et al.) 342–361 (Island Press, 2005).7.Jones, M. E. et al. Life-history change in disease-ravaged Tasmanian devil populations. Proc. Natl. Acad. Sci. USA 105, 10023–10027. https://doi.org/10.1073/pnas.0711236105 (2008).ADS 
Article 
PubMed 

Google Scholar 
8.Scheele, B. C. et al. Disease-associated change in an amphibian life-history trait. Oecologia 184, 825–833. https://doi.org/10.1007/s00442-017-3911-7 (2017).ADS 
Article 
PubMed 

Google Scholar 
9.Thornhill, J. A., Jones, J. T. & Kusel, J. R. Increased oviposition and growth in immature Biomphalaria glabrata after exposure to Schistosoma mansoni. Parasitology 93, 443–450. https://doi.org/10.1017/S0031182000081166 (1986).Article 
PubMed 

Google Scholar 
10.Polak, M. & Starmer, W. T. Parasite-induced risk of mortality elevates reproductive effort in male Drosophila. Proc. R. Soc. B 265, 2197–2201. https://doi.org/10.1098/rspb.1998.0559 (1998).CAS 
Article 
PubMed 

Google Scholar 
11.Chadwick, W. & Little, T. J. A parasite-mediated life-history shift in Daphnia magna. Proc. R. Soc. B 272, 505–509. https://doi.org/10.1098/rspb.2004.2959 (2005).Article 
PubMed 

Google Scholar 
12.Schwanz, L. E. Chronic parasitic infection alters reproductive output in deer mice. Behav. Ecol. Sociobiol. 62, 1351–1358. https://doi.org/10.1007/s00265-008-0563-y (2008).Article 

Google Scholar 
13.Promislow, D. E. L. & Harvey, P. H. Living fast and dying young: A comparative analysis of life-history variation among mammals. J. Zool. 220, 417–437. https://doi.org/10.1111/j.1469-7998.1990.tb04316.x (1990).Article 

Google Scholar 
14.Hill, K. Life history theory and evolutionary anthropology. Evol. Anthropol. 2, 78–88. https://doi.org/10.1002/evan.1360020303 (1993).CAS 
Article 

Google Scholar 
15.Charlesworth, B. Evolution in Age-Structured Populations 2nd edn. (Cambridge University Press, 1994).Book 

Google Scholar 
16.Nettle, D. & Frankenhuis, W. E. Life-history theory in psychology and evolutionary biology: One research programme or two?. Philos. Trans. R. Soc. B 375, 9. https://doi.org/10.1098/rstb.2019.0490 (2020).Article 

Google Scholar 
17.Del Giudice, M. Rethinking the fast-slow continuum of individual differences. Evol. Hum. Behav. 41, 536–549. https://doi.org/10.1016/j.evolhumbehav.2020.05.004 (2020).Article 

Google Scholar 
18.Lammers, C., Ireland, M., Resnick, M. & Blum, R. Influences on adolescents’ decision to postpone onset of sexual intercourse: A survival analysis of virginity among youths aged 13 to 18 years. J. Adolesc. Health 26, 42–48. https://doi.org/10.1016/s1054-139x(99)00041-5 (2000).CAS 
Article 
PubMed 

Google Scholar 
19.Wilson, M. & Daly, M. Life expectancy, economic inequality, homicide, and reproductive timing in Chicago neighbourhoods. BMJ 314, 1271–1274 (1997).CAS 
Article 

Google Scholar 
20.Bereczkei, T. & Csanaky, A. Stressful family environment, mortality, and child socialisation: Life-history strategies among adolescents and adults from unfavourable social circumstances. Int. J. Behav. Dev. 25, 501–508. https://doi.org/10.1080/01650250042000573 (2001).Article 

Google Scholar 
21.Nettle, D. Dying young and living fast: Variation in life history across English neighborhoods. Behav. Ecol. 21, 387–395. https://doi.org/10.1093/beheco/arp202 (2010).Article 

Google Scholar 
22.Griskevicius, V., Delton, A. W., Robertson, T. E. & Tybur, J. M. Environmental contingency in life history strategies: The influence of mortality and socioeconomic status on reproductive timing. J. Pers. Soc. Psychol. 100, 241–254. https://doi.org/10.1037/a0021082 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
23.Sheppard, P., Pearce, M. S. & Sear, R. How does childhood socioeconomic hardship affect reproductive strategy? Pathways of development. Am. J. Hum. Biol. 28, 356–363. https://doi.org/10.1002/ajhb.22793 (2016).Article 
PubMed 

Google Scholar 
24.Belsky, J., Steinberg, L. & Draper, P. Childhood experience, interpersonal development, and reproductive strategy: An evolutionary theory of socialization. Child Dev. 62, 647–670. https://doi.org/10.1111/j.1467-8624.1991.tb01558.x (1991).CAS 
Article 
PubMed 

Google Scholar 
25.Rickard, I. J., Frankenhuis, W. E. & Nettle, D. Why are childhood family factors associated with timing of maturation? A role for internal prediction. Perspect. Psychol. Sci. 9, 3–15. https://doi.org/10.1177/1745691613513467 (2014).Article 
PubMed 

Google Scholar 
26.Chua, K. J., Lukaszewski, A. W., Grant, D. M. & Sng, O. Human life history strategies: Calibrated to external or internal cues?. Evol. Psychol. 15, 1474704916677342. https://doi.org/10.1177/1474704916677342 (2017).Article 
PubMed 

Google Scholar 
27.Adamo, S. A. Evidence for adaptive changes in egg laying in crickets exposed to bacteria and parasites. Anim. Behav. 57, 117–124. https://doi.org/10.1006/anbe.1998.0999 (1999).CAS 
Article 
PubMed 

Google Scholar 
28.Giehr, J., Grasse, A. V., Cremer, S., Heinze, J. & Schrempf, A. Ant queens increase their reproductive efforts after pathogen infection. R. Soc. Open Sci. 4, 170547. https://doi.org/10.1098/rsos.170547 (2017).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
29.Sorci, G., Clobert, J. & Michalakis, Y. Cost of reproduction and cost of parasitism in the common lizard, Lacerta vivipara. Oikos 76, 121–130. https://doi.org/10.2307/3545754 (1996).Article 

Google Scholar 
30.Oppliger, A., Christe, P. & Richner, H. Clutch size and malarial parasites in female great tits. Behav. Ecol. 8, 148–152. https://doi.org/10.1093/beheco/8.2.148 (1997).Article 

Google Scholar 
31.Sanz, J. J., Arriero, E., Moreno, J. & Merino, S. Interactions between hemoparasite status and female age in the primary reproductive output of pied flycatchers. Oecologia 126, 339–344. https://doi.org/10.1007/s004420000530 (2001).ADS 
Article 
PubMed 

Google Scholar 
32.Westendorp, R. G. J. & Kirkwood, T. B. L. Human longevity at the cost of reproductive success. Nature 396, 743–746. https://doi.org/10.1038/25519 (1998).ADS 
CAS 
Article 
PubMed 

Google Scholar 
33.Thomas, F., Teriokhin, A. T., Renaud, F., De Meeus, T. & Guégan, J. F. Human longevity at the cost of reproductive success: Evidence from global data. J. Evol. Biol. 13, 409–414. https://doi.org/10.1046/j.1420-9101.2000.00190.x (2000).Article 

Google Scholar 
34.Figueredo, A. J., Vasquez, G., Brumbach, B. H. & Schneider, S. M. R. The heritability of life history strategy: The K-factor, covitality, and personality. Soc. Biol. 51, 121–143 (2004).PubMed 

Google Scholar 
35.Figueredo, A. J., Vasquez, G., Brumbach, B. H. & Schneider, S. M. R. The K-factor, covitality, and personality—A psychometric test of life history theory. Hum. Nat. 18, 47–73. https://doi.org/10.1007/bf02820846 (2007).Article 
PubMed 

Google Scholar 
36.Hill, S. E., Boehm, G. W. & Prokosch, M. L. Vulnerability to disease as a predictor of faster life history strategies. Adapt. Hum. Behav. Physiol. 2, 116–133. https://doi.org/10.1007/s40750-015-0040-6 (2016).Article 

Google Scholar 
37.Uggla, C. & Mace, R. Local ecology influences reproductive timing in Northern Ireland independently of individual wealth. Behav. Ecol. 27, 158–165. https://doi.org/10.1093/beheco/arv133 (2016).Article 

Google Scholar 
38.Waynforth, D. Life-history theory, chronic childhood illness and the timing of first reproduction in a British birth cohort. Proc. R. Soc. B 279, 2998–3002. https://doi.org/10.1098/rspb.2012.0220 (2012).Article 
PubMed 

Google Scholar 
39.Mace, R. Evolutionary ecology of human life history. Anim. Behav. 59, 1–10. https://doi.org/10.1006/anbe.1999.1287 (2000).CAS 
Article 
PubMed 

Google Scholar 
40.Low, B. S., Simon, C. P. & Anderson, K. G. An evolutionary ecological perspective on demographic transitions: Modeling multiple currencies. Am. J. Hum. Biol. 14, 149–167. https://doi.org/10.1002/ajhb.10043 (2002).Article 
PubMed 

Google Scholar 
41.Galor, O. The demographic transition: Causes and consequences. Cliometrica 6, 1–28. https://doi.org/10.1007/s11698-011-0062-7 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
42.Protsiv, M., Ley, C., Lankester, J., Hastie, T. & Parsonnet, J. Decreasing human body temperature in the United States since the industrial revolution. Elife 9, e49555. https://doi.org/10.7554/eLife.49555 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
43.Novotná, M. et al. Toxoplasma and reaction time: Role of toxoplasmosis in the origin, preservation and geographical distribution of Rh blood group polymorphism. Parasitology 135, 1253–1261. https://doi.org/10.1017/s003118200800485x (2008).Article 
PubMed 

Google Scholar 
44.Flegr, J., Novotná, M., Lindová, J. & Havlíček, J. Neurophysiological effect of the Rh factor. Protective role of the RhD molecule against Toxoplasma-induced impairment of reaction times in women. Neuroendocrinol. Lett. 29, 475–481 (2008).PubMed 

Google Scholar 
45.Flegr, J., Preiss, M. & Klose, J. Toxoplasmosis-associated difference in intelligence and personality in men depends on their Rhesus blood group but not ABO blood group. PLoS One 8, e61272. https://doi.org/10.1371/journal.pone.0061272 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
46.Flegr, J., Šebánková, B., Příplatová, L., Chvátalová, V. & Kaňková, Š. Lower performance of Toxoplasma-infected, Rh-negative subjects in the weight holding and hand-grip tests. PLoS One 13, e0200346. https://doi.org/10.1371/journal.pone.0200346 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
47.Flegr, J., Klose, J., Novotná, M., Berenreitterová, M. & Havlíček, J. Increased incidence of traffic accidents in Toxoplasma-infected military drivers and protective effect RhD molecule revealed by a large-scale prospective cohort study. BMC Infect. Dis. https://doi.org/10.1186/1471-2334-9-72 (2009).Article 
PubMed 
PubMed Central 

Google Scholar 
48.Flegr, J., Geryk, J., Volný, J., Klose, J. & Černochová, D. Rhesus factor modulation of effects of smoking and age on psychomotor performance, intelligence, personality profile, and health in Czech soldiers. PLoS One 7, e4947810. https://doi.org/10.1371/journal.pone.0049478 (2012).CAS 
Article 

Google Scholar 
49.Flegr, J., Hoffmann, R. & Dammann, M. Worse health status and higher incidence of health disorders in Rhesus negative subjects. PLoS One 10, e0141362. https://doi.org/10.1371/journal.pone.0141362 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
50.Flegr, J. Heterozygote advantage probably maintains Rhesus factor blood group polymorphism: Ecological regression study. PLoS One 11, e0147955. https://doi.org/10.1371/journal.pone.0147955 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
51.Flegr, J., Kuba, R. & Kopecký, R. Rhesus-minus phenotype as a predictor of sexual desire and behavior, wellbeing, mental health, and fecundity. PLoS One 15, e0236134. https://doi.org/10.1371/journal.pone.0236134 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
52.Kaňková, Š., Flegr, J., Toman, J. & Calda, P. Maternal RhD heterozygous genotype is associated with male biased secondary sex ratio. Early Hum. Dev. 140, 104864. https://doi.org/10.1016/j.earlhumdev.2019.104864 (2020).Article 
PubMed 

Google Scholar 
53.Flegr, J. & Dama, M. Does the prevalence of latent toxoplasmosis and frequency of Rhesus-negative subjects correlate with the nationwide rate of traffic accidents?. Folia Parasitol. 61, 485–494 (2014).CAS 
Article 

Google Scholar 
54.Halmin, M. et al. Length of storage of red blood cells and patient survival after blood transfusion: A binational cohort study. Ann. Intern. Med. 166, 248–256. https://doi.org/10.7326/m16-1415 (2017).Article 
PubMed 

Google Scholar 
55.Jacobsen, B. K., Oda, K., Knutsen, S. F. & Fraser, G. E. Age at menarche, total mortality and mortality from ischaemic heart disease and stroke: The Adventist Health Study, 1976–88. Int. J. Epidemiol. 38, 245–252. https://doi.org/10.1093/ije/dyn251 (2009).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
56.Lakshman, R. et al. Early age at menarche associated with cardiovascular disease and mortality. J. Clin. Endocrinol. Metab. 94, 4953–4960. https://doi.org/10.1210/jc.2009-1789 (2009).CAS 
Article 
PubMed 

Google Scholar 
57.Canoy, D. et al. Age at menarche and risks of coronary heart and other vascular diseases in a large UK cohort. Circulation 131, 237–244. https://doi.org/10.1161/circulationaha.114.010070 (2015).Article 
PubMed 

Google Scholar 
58.Macsali, F. et al. Early age at menarche, lung function, and adult asthma. Am. J. Respir. Crit. Care Med. 183, 8–14. https://doi.org/10.1164/rccm.200912-1886OC (2011).Article 
PubMed 

Google Scholar 
59.Stöckl, D. et al. Age at menarche is associated with prediabetes and diabetes in women (aged 32–81 years) from the general population: The KORA F4 Study. Diabetologia 55, 681–688. https://doi.org/10.1007/s00125-011-2410-3 (2012).Article 
PubMed 

Google Scholar 
60.Brinton, L. A., Schairer, C., Hoover, R. N. & Fraumeni, J. F. Menstrual factors and risk of breast cancer. Cancer Investig. 6, 245–254. https://doi.org/10.3109/07357908809080645 (1988).CAS 
Article 

Google Scholar 
61.Kvale, G. & Heuch, I. Menstrual factors and breast cancer risk. Cancer 62, 1625–1631. https://doi.org/10.1002/1097-0142(19881015)62:8%3c1625::aid-cncr2820620828%3e3.0.co;2-k (1988).CAS 
Article 
PubMed 

Google Scholar 
62.Adair, L. S. Size at birth predicts age at menarche. Pediatrics 107, e59. https://doi.org/10.1542/peds.107.4.e59 (2001).CAS 
Article 
PubMed 

Google Scholar 
63.Romundstad, P. R. et al. Birth size in relation to age at menarche and adolescent body size: Implications for breast cancer risk. Int. J. Cancer 105, 400–403. https://doi.org/10.1002/ijc.11103 (2003).CAS 
Article 
PubMed 

Google Scholar 
64.Sloboda, D. M., Hart, R., Doherty, D. A., Pennell, C. E. & Hickey, M. Age at menarche: Influences of prenatal and postnatal growth. J. Clin. Endocrinol. Metab. 92, 46–50. https://doi.org/10.1210/jc.2006-1378 (2007).CAS 
Article 
PubMed 

Google Scholar 
65.Rich-Edwards, J. W. et al. Birth weight and risk of cardiovascular disease in a cohort of women followed up since 1976. BMJ 315, 396–400. https://doi.org/10.1136/bmj.315.7105.396 (1997).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
66.Andersen, A. M. N. & Osler, M. Birth dimensions, parental mortality, and mortality in early adult age: A cohort study of Danish men born in 1953. Int. J. Epidemiol. 33, 92–99. https://doi.org/10.1093/ije/dyg195 (2004).Article 
PubMed 

Google Scholar 
67.Gluckman, P. D. & Hanson, M. A. Evolution, development and timing of puberty. Trends Endocrinol. Metab. 17, 7–12. https://doi.org/10.1016/j.tem.2005.11.006 (2006).CAS 
Article 
PubMed 

Google Scholar 
68.Kulin, H. E., Bwibo, N., Mutie, D. & Santner, S. J. The effect of chronic childhood malnutrition on pubertal growth and development. Am. J. Clin. Nutr. 36, 527–536. https://doi.org/10.1093/ajcn/36.3.527 (1982).CAS 
Article 
PubMed 

Google Scholar 
69.Khan, A. D., Schroeder, D. G., Martorell, R., Haas, J. D. & Rivera, J. Early childhood determinants of age at menarche in rural Guatemala. Am. J. Hum. Biol. 8, 717–723. https://doi.org/10.1002/(sici)1520-6300(1996)8:6%3c717::aid-ajhb3%3e3.0.co;2-q (1996).Article 
PubMed 

Google Scholar 
70.Leenstra, T. et al. Prevalence and severity of malnutrition and age at menarche; cross-sectional studies in adolescent schoolgirls in western Kenya. Eur. J. Clin. Nutr. 59, 41–48. https://doi.org/10.1038/sj.ejcn.1602031 (2005).CAS 
Article 
PubMed 

Google Scholar 
71.Walker, R. et al. Growth rates and life histories in twenty-two small-scale societies. Am. J. Hum. Biol. 18, 295–311. https://doi.org/10.1002/ajhb.20510 (2006).Article 
PubMed 

Google Scholar 
72.Idler, E. L. & Kasl, S. V. Self-ratings of health: Do they also predict change in functional ability. J. Gerontol. B 50, S344–S353. https://doi.org/10.1093/geronb/50B.6.S344 (1995).CAS 
Article 

Google Scholar 
73.O’Sullivan, L. F. & Byers, E. S. College students’ incorporation of initiator and restrictor roles in sexual dating interactions. J. Sex Res. 29, 435–446. https://doi.org/10.1080/00224499209551658 (1992).Article 

Google Scholar 
74.Smith, C. A. Factors associated with early sexual activity among urban adolescents. Soc. Work 42, 334–346. https://doi.org/10.1093/sw/42.4.334 (1997).CAS 
Article 
PubMed 

Google Scholar 
75.Mercer, C. H. et al. Changes in sexual attitudes and lifestyles in Britain through the life course and over time: findings from the National Surveys of Sexual Attitudes and Lifestyles (Natsal). Lancet 382, 1781–1794. https://doi.org/10.1016/s0140-6736(13)62035-8 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
76.Kalick, S. M., Zebrowitz, L. A., Langlois, J. H. & Johnson, R. M. Does human facial attractiveness honestly advertise health? Longitudinal data on an evolutionary question. Psychol. Sci. 9, 8–13. https://doi.org/10.1111/1467-9280.00002 (1998).Article 

Google Scholar 
77.Jones, B. C. et al. Facial symmetry and judgements of apparent health: Support for a “good genes” explanation of the attractiveness-symmetry relationship. Evol. Hum. Behav. 22, 417–429. https://doi.org/10.1016/s1090-5138(01)00083-6 (2001).Article 

Google Scholar 
78.Woodley of Menie, M. A. et al. Slow and steady wins the race: K positively predicts fertility in the USA and Sweden. Evol. Psychol. Sci. 3, 109–117. https://doi.org/10.1007/s40806-016-0077-1 (2017).79.Kington, R., Lillard, L. & Rogowski, J. Reproductive history, socioeconomic status, and self-reported health status of women aged 50 years or older. Am. J. Public Health 87, 33–37. https://doi.org/10.2105/ajph.87.1.33 (1997).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
80.Doblhammer, G. & Oeppen, J. Reproduction and longevity among the British peerage: The effect of frailty and health selection. Proc. R. Soc. B 270, 1541–1547. https://doi.org/10.1098/rspb.2003.2400 (2003).Article 
PubMed 

Google Scholar 
81.Lawlor, D. A. et al. Is the association between parity and coronary heart disease due to biological effects of pregnancy or adverse lifestyle risk factors associated with child-rearing? Findings from the British women’s heart and health study and the British regional heart study. Circulation 107, 1260–1264. https://doi.org/10.1161/01.cir.0000053441.43495.1a (2003).Article 
PubMed 

Google Scholar 
82.Parikh, N. I. et al. Parity and risk of later-life maternal cardiovascular disease. Am. Heart J. 159, 215–221. https://doi.org/10.1016/j.ahj.2009.11.017 (2010).Article 
PubMed 

Google Scholar 
83.Ryan, C. P. et al. Reproduction predicts shorter telomeres and epigenetic age acceleration among young adult women. Sci. Rep. 8, 11100. https://doi.org/10.1038/s41598-018-29486-4 (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
84.Kaňková, Š., Šulc, J. & Flegr, J. Increased pregnancy weight gain in women with latent toxoplasmosis and RhD-positivity protection against this effect. Parasitology 137, 1773–1779. https://doi.org/10.1017/s0031182010000661 (2010).Article 
PubMed 

Google Scholar 
85.Case, A., Fertig, A. & Paxson, C. The lasting impact of childhood health and circumstance. J. Health Econ. 24, 365–389. https://doi.org/10.1016/j.jhealeco.2004.09.008 (2005).Article 
PubMed 

Google Scholar 
86.Kuh, D. J. L. & Wadsworth, M. E. J. Physical health-status at 36 years in a British national birth cohort. Soc. Sci. Med. 37, 905–916. https://doi.org/10.1016/0277-9536(93)90145-t (1993).CAS 
Article 
PubMed 

Google Scholar 
87.Eide, E. R. & Showalter, M. H. Estimating the relation between health and education: What do we know and what do we need to know?. Econ. Educ. Rev. 30, 778–791. https://doi.org/10.1016/j.econedurev.2011.03.009 (2011).Article 

Google Scholar 
88.Behrman, J. R. & Rosenzweig, M. R. Returns to birthweight. Rev. Econ. Stat. 86, 586–601. https://doi.org/10.1162/003465304323031139 (2004).Article 

Google Scholar 
89.Black, S. E., Devereux, P. J. & Salvanes, K. G. From the cradle to the labor market? The effect of birth weight on adult outcomes. Q. J. Econ. 122, 409–439. https://doi.org/10.1162/qjec.122.1.409 (2007).Article 

Google Scholar 
90.Almond, D. Is the 1918 influenza pandemic over? Long-term effects of in utero influenza exposure in the post-1940 US population. J. Polit. Econ. 114, 672–712. https://doi.org/10.1086/507154 (2006).Article 

Google Scholar 
91.Almond, D., Edlund, L. & Palme, M. Chernobyl’s subclinical legacy: Prenatal exposure to radioactive fallout and school outcomes in Sweden. Q. J. Econ. 124, 1729–1772. https://doi.org/10.1162/qjec.2009.124.4.1729 (2009).Article 
MATH 

Google Scholar 
92.Nilsson, J. P. The Long-Term Effects of Early Childhood Lead Exposure: Evidence from the Phase-Out of Leaded Gasoline. (Uppsala University and Institute for Labor Market Policy Evaluation (IFAU), 2009).93.Bleakley, H. Disease and development: Evidence from hookworm eradication in the American South. Q. J. Econ. 122, 73–117. https://doi.org/10.1162/qjec.121.1.73 (2007).Article 
PubMed 
PubMed Central 

Google Scholar 
94.Rees, D. I. & Sabia, J. J. The effect of migraine headache on educational attainment. J. Hum. Resour. 46, 317–332 (2011).
Google Scholar 
95.Kessler, R. C., Foster, C. L., Saunders, W. B. & Stang, P. E. Social consequences of psychiatric disorders, I. Educational attainment. Am. J. Psychiatry 152, 1026–1032 (1995).CAS 
Article 

Google Scholar 
96.Miech, R. A., Caspi, A., Moffitt, T. E., Wright, B. R. E. & Silva, P. A. Low socioeconomic status and mental disorders: A longitudinal study of selection and causation during young adulthood. Am. J. Sociol. 104, 1096–1131. https://doi.org/10.1086/210137 (1999).Article 

Google Scholar 
97.Flegr, J. & Horáček, J. Negative effects of latent toxoplasmosis on mental health. Front. Psychiatry. https://doi.org/10.3389/fpsyt.2019.01012 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
98.Kopecký, R., Boschetti, S. & Flegr, J. Effect of being religious on wellbeing in a predominantly atheist country: Explorative study on wellbeing, fitness, physical and mental health. PsyArXiv https://doi.org/10.31234/osf.io/3kr6n (2019).99.Flegr, J. & Horáček, J. Toxoplasma-infected subjects report an obsessive-compulsive disorder diagnosis more often and score higher in obsessive-compulsive inventory. Eur. Psychiatry. 40, 82–87. https://doi.org/10.1016/j.eurpsy.2016.09.001 (2017).CAS 
Article 
PubMed 

Google Scholar 
100.Cohen, J. Statistical Power Analysis for the Behavioral Sciences. Revised edn. (Academic Press, 1977).101.Armelagos, G. J., Goodman, A. H. & Jacobs, K. H. The origins of agriculture: Population growth during a period of declining health. Popul. Environ. 13, 9–22. https://doi.org/10.1007/bf01256568 (1991).Article 

Google Scholar 
102.Lallo, J. W., Armelagos, G. J. & Mensforth, R. P. The role of diet, disease, and physiology in the origin of porotic hyperostosis. Hum. Biol. 49, 471–483 (1977).CAS 
PubMed 

Google Scholar 
103.Goodman, A. H., Armelagos, G. J. & Rose, J. C. Enamel hypoplasias as indicators of stress in three prehistoric populations from Illinois. Hum. Biol. 52, 515–528 (1980).CAS 
PubMed 

Google Scholar 
104.Angel, J. L. Porotic hyperostosis, anemias, malarias, and marshes in the prehistoric Eastern Mediterranean. Science 153, 760–763 (1966).ADS 
CAS 
Article 

Google Scholar 
105.Eaton, S. B., Eaton, S. B. & Konner, M. J. Paleolithic nutrition revisited: A twelve-year retrospective on its nature and implications. Eur. J. Clin. Nutr. 51, 207–216. https://doi.org/10.1038/sj.ejcn.1600389 (1997).CAS 
Article 
PubMed 

Google Scholar 
106.Flegr, J. & Kuba, R. The relation of Toxoplasma infection and sexual attraction to fear, danger, pain, and submissiveness. Evol. Psychol. https://doi.org/10.1177/1474704916659746 (2016).Article 

Google Scholar 
107.Penke, L. & Asendorpf, J. B. Beyond global sociosexual orientations: A more differentiated look at sociosexuality and its effects on courtship and romantic relationships. J. Pers. Soc. Psychol. 95, 1113–1135. https://doi.org/10.1037/0022-3514.95.5.1113 (2008).Article 
PubMed 

Google Scholar 
108.Sýkorová, K. & Flegr, J. Dataset to the study ‘Faster life history strategy manifests itself by lower age at menarche, higher sexual desire, and earlier reproduction in people with worse health’. igshare https://doi.org/10.6084/m9.figshare.12100623.v1 (2020).109.R Core Team. R: A language and environment for statistical computing. http://www.R-project.org/ . Accessed September 2018. (2019).110.Rosseel, Y. lavaan: An R package for structural equation modeling. J. Stat. Softw. 48, 1–36 (2012).Article 

Google Scholar 
111.Epskamp, S. semPlot: Unified visualizations of structural equation models. Struct. Equ. Model. 22, 474–483. https://doi.org/10.1080/10705511.2014.937847 (2015).MathSciNet 
Article 

Google Scholar  More

1.Foster, M. S. Rhodoliths between rocks and soft places. J. Phycol. 37, 659–667. https://doi.org/10.1046/j.1529-8817.2001.00195.x (2001).Article 

Google Scholar 
2.Riosmena-Rodríguez, R., Nelson, W. & Aguirre, J. Rhodolith/mäerl beds: A global perspective (Springer, 2017). https://doi.org/10.1007/978-3-319-29315-8.Book 

Google Scholar 
3.Nelson, W. A. Calcified macroalgae—critical to coastal ecosystems and vulnerable to change: a review. Mar. Freshw. Res. 60, 787–801. https://doi.org/10.1071/MF08335 (2009).CAS 
Article 

Google Scholar 
4.Amado-Filho, G. M. et al. Rhodolith beds are major CaCO3 bio-factories in the tropical South West Atlantic. PLoS ONE 7, e35171. https://doi.org/10.1371/journal.pone.0035171 (2012).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
5.Smith, S. V. & Mackenzie, F. T. The role of CaCO3 reactions in the contemporary oceanic CO2 cycle. Aquat. Geochem. 22, 153–175. https://doi.org/10.1007/s10498-015-9282-y (2015).Article 

Google Scholar 
6.Amado-Filho, G.M., Bahia, R.G., Pereira-Filho, G.H. & Longo, L.L. South Atlantic rhodolith beds: Latitudinal distribution, species composition, structure and ecosystem functions, threats and conservation status. In Rhodolith/mäerl beds: A global perspective (eds, Riosmena-Rodríguez, R. et al.), Switzerland: Springer International Publishing; https://doi.org/10.1007/978-3-319-29315-8_12 (2017).7.Carvalho, V. F. et al. Environmental drivers of rhodolith beds and epiphytes community along the South Western Atlantic coast. Mar. Environ. Res. 154, 104827. https://doi.org/10.1016/j.marenvres.2019.104827 (2020).CAS 
Article 
PubMed 

Google Scholar 
8.Legrand, E. et al. Species interactions can shift the response of a maerl bed community to ocean acidification and warming. Biogeosciences 14, 5359–5376. https://doi.org/10.5194/bg-14-5359-2017 (2017).ADS 
CAS 
Article 

Google Scholar 
9.Legrand, E. et al. Grazers increase the sensitivity of coralline algae to ocean acidification and warming. J. Sea Res. 148–149, 1–7. https://doi.org/10.1016/j.seares.2019.03.001 (2019).Article 

Google Scholar 
10.Legrand, E., Martin, S., Leroux, C. & Riera, P. Using stable isotope analysis to determine the effects of ocean acidification and warming on trophic interactions in a maerl bed community. Mar. Ecol. https://doi.org/10.1111/maec.12612 (2020).Article 

Google Scholar 
11.Burdett, H. L., Perna, G., McKay, L., Broomhead, G. & Kamenos, N. A. Community-level sensitivity of a calcifying ecosystem to acute in situ CO2 enrichment. Mar. Ecol. Prog. Ser. 587, 73–80. https://doi.org/10.3354/meps12421 (2018).ADS 
CAS 
Article 

Google Scholar 
12.Sordo, L., Santos, R., Barrote, I. & Silva, J. High CO2 decreases the long-term resilience of the free-living coralline algae Phymatolithon lusitanicum. Ecol. Evol. 8, 4781–4792. https://doi.org/10.1002/ece3.4020 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
13.Sordo, L., Santos, R., Barrote, I. & Silva, J. Temperature amplifies the effect of high CO2 on the photosynthesis, respiration, and calcification of the coralline algae Phymatolithon lusitanicum. Ecol. Evol. 9, 11000–11009. https://doi.org/10.1002/ece3.5560 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
14.Qui-Minet, Z. M. et al. Combined effects of global climate change and nutrient enrichment on the physiology of three temperate maerl species. Ecol. Evol. 9, 13787–13807. https://doi.org/10.1002/ece3.5802 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
15.Schubert, N. et al. Rhodolith primary and carbonate production in a changing ocean: the interplay of warming and nutrients. Sci. Total Environ. 676, 455–468. https://doi.org/10.1016/j.scitotenv.2019.04.280 (2019).ADS 
CAS 
Article 
PubMed 

Google Scholar 
16.Martin, S. & Hall-Spencer, J.M. Effects of ocean warming and acidification on rhodolith/mäerl beds. In Rhodolith/mäerl beds: A global perspective (eds. Riosmena-Rodríguez, R. et al.). Switzerland: Springer International Publishing; https://doi.org/10.1007/978-3-319-29315-8_3 (2017).17.Roleda, M. Y., Boyd, P. W. & Hurd, C. L. Before ocean acidification: calcifier chemistry lessons. J. Phycol. 48(4), 840–843. https://doi.org/10.1111/j.1529-8817.2012.01195.x (2012).CAS 
Article 
PubMed 

Google Scholar 
18.Dupont, S. & Pörtner, H. O. A snapshot of ocean acidification research. Mar. Biol. 160, 1765–1771. https://doi.org/10.1007/s00227-013-2282-9 (2013).CAS 
Article 

Google Scholar 
19.Cyronak, T., Schulz, K. G. & Jokiel, P. L. The Omega myth: what really drives lower calcification rates in an acidifying ocean. ICES J. Mar. Sci. 73(3), 558–562. https://doi.org/10.1093/icesjms/fsv075 (2016).Article 

Google Scholar 
20.Falkenberg, L. J., Dupont, S. & Bellerby, R. G. Approaches to reconsider literature on physiological effects of environmental change: examples from ocean acidification research. Front. Mar. Sci. 5, 453. https://doi.org/10.3389/fmars.2018.00453 (2018).Article 

Google Scholar 
21.Cornwall, C. E., Comeau, S. & McCulloch, M. T. Coralline algae elevate pH at the site of calcification under ocean acidification. Global Change Biol. 23, 4245–4256. https://doi.org/10.1111/gcb.13673 (2017).ADS 
Article 

Google Scholar 
22.Cornwall, C. E. et al. Resistance of corals and coralline algae to ocean acidification: physiological control of calcification under natural pH variability. Proc. Roy. Soc. B 285(1884), 20181168. https://doi.org/10.1098/rspb.2018.1168 (2018).CAS 
Article 

Google Scholar 
23.Comeau, S., Cornwall, C. E., De Carlo, T. M., Krieger, E. & McCulloch, M. Similar controls on calcification under ocean acidification across unrelated coral reef taxa. Global Change Biol. 24, 4857–4868. https://doi.org/10.1111/gcb.14379 (2018).ADS 
Article 

Google Scholar 
24.Comeau, S. et al. Flow-driven micro-scale pH variability affects the physiology of corals and coralline algae under ocean acidification. Sci. Rep. 9, 1–12. https://doi.org/10.1038/s41598-019-49044-w (2019).Article 

Google Scholar 
25.Comeau, S. et al. Resistance to ocean acidification in coral reef taxa is not gained by acclimatization. Nat. Clim. Chang. 9(6), 477–483. https://doi.org/10.1038/s41558-019-0486-9 (2019).ADS 
CAS 
Article 

Google Scholar 
26.Liu, Y. W., Sutton, J. N., Ries, J. B. & Eagle, R. A. Regulation of calcification site pH is a polyphyletic but not always governing response to ocean acidification. Sci. Adv. 6(5), aax1314. https://doi.org/10.1126/sciadv.aax1314 (2020).ADS 
CAS 
Article 

Google Scholar 
27.Donald, H. K., Ries, J. B., Stewart, J. A., Fowell, S. E. & Foster, G. L. Boron isotope sensitivity to seawater pH change in a species of Neogoniolithon coralline red alga. Geochim. Cosmochim. Acta 217, 240–253. https://doi.org/10.1016/j.gca.2017.08.021 (2017).ADS 
CAS 
Article 

Google Scholar 
28.Hofmann, L. C., Schoenrock, K. M. & de Beer, D. Arctic coralline algae elevate surface pH and carbonate in the dark. Front. Plant Sci. 9, 1416. https://doi.org/10.3389/fpls.2018.01416 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
29.Hurd, C. L. et al. Metabolically induced pH fluctuations by some coastal calcifiers exceed projected 22nd century ocean acidification: a mechanism for differential susceptibility. Global Change Biol. 17, 3254–3262. https://doi.org/10.1111/j.1365-2486.2011.02473.x (2011).ADS 
Article 

Google Scholar 
30.Cornwall, C. E. et al. Diffusion boundary layers ameliorate the negative effects of ocean acidification on the temperate coralline macroalga Arthrocardia corymbosa. PLoS ONE 9, e97235. https://doi.org/10.1371/journal.pone.0097235 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
31.Hofmann, L. C., Koch, M. & de Beer, D. Biotic control of surface pH and evidence of light-induced H+ pumping and Ca2+-H+ exchange in a tropical crustose coralline alga. PLoS ONE 1, e0159057. https://doi.org/10.1371/journal.pone.0159057 (2016).CAS 
Article 

Google Scholar 
32.McNicholl, C., Koch, M. S. & Hofmann, L. C. Photosynthesis and light-dependent proton pumps increase boundary layer pH in tropical macroalgae: A proposed mechanism to sustain calcification under ocean acidification. J. Exp. Mar. Biol. Ecol. 521, 151208. https://doi.org/10.1016/j.jembe.2019.151208 (2019).Article 

Google Scholar 
33.Hurd, C. L. & Pilditch, C. A. Flow-induced morphological variations affect diffusion boundary-layer thickness of Macrocystis pyrifera (Heterokontophyta, Laminariales). J. Phycol. 47, 341–351. https://doi.org/10.1111/j.1529-8817.2011.00958.x (2011).Article 
PubMed 

Google Scholar 
34.Foster, M.S., Amado-Filho, G.M., Kamenos, N.A., Riosmena-Rodríguez, R. & Steller D.L. Rhodoliths and rhodolith beds. In Research and Discoveries: The Revolution of Science Through SCUBA (eds, Lang, M.A. et al.). Washington, D.C, USA: Smithsonian Institution Scholarly Press (2013).35.Melbourne, L. A., Denny, M. W., Harniman, R. L., Rayfield, E. J. & Schmidt, D. N. The importance of wave exposure on the structural integrity of rhodoliths. J. Exp. Mar. Biol. Ecol. 503, 109–119. https://doi.org/10.1016/j.jembe.2017.11.007 (2018).Article 

Google Scholar 
36.Farias, J. N., Riosmena-Rodríguez, R., Bouzon, Z., Oliveira, E. C. & Horta, P. A. Lithothamnion superpositum (Corallinales; Rhodophyta): First description for the Western Atlantic or rediscovery of a species?. Phycol. Res. 58, 210–216. https://doi.org/10.1111/j.1440-1835.2010.00581.x (2010).Article 

Google Scholar 
37.Vieira-Pinto, T. et al. Lithophyllum species from Brazilian coast: range extension of Lithophyllum margaritae and description of Lithophyllum atlanticum sp. nov. (Corallineales, Corallinophycidae, Rhodophyta). Phytotaxa 190, 355–369. https://doi.org/10.11646/phytotaxa.190.1.21 (2014).Article 

Google Scholar 
38.Sissini, M. N. et al. Mesophyllum erubescens (Corallinales, Rhodophyta)-so many species in one epithet. Phytotaxa 190, 299–319. https://doi.org/10.11646/phytotaxa.190.1.18 (2014).Article 

Google Scholar 
39.de Beer, D. & Larkum, A. Photosynthesis and calcification in the calcifying algae Halimeda discoidea studied with microsensors. Plant Cell Environ. 24, 1209–1217. https://doi.org/10.1046/j.1365-3040.2001.00772.x (2001).Article 

Google Scholar 
40.Hurd, C. L. Slow-flow habitats as refugia for coastal calcifiers from ocean acidification. J. Phycol. 51, 599–605. https://doi.org/10.1111/jpy.12307 (2015).CAS 
Article 
PubMed 

Google Scholar 
41.Nash, M. C., Diaz-Pulido, G., Harvey, A. S. & Adey, W. Coralline algal calcification: A morphological and process-based understanding. PLoS ONE 14, e0221396. https://doi.org/10.1371/journal.pone.0221396 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
42.Burdett, H. L., Hennige, S. J., Francis, F. T. Y. & Kamenos, N. A. The photosynthetic characteristics of red coralline algae, determined using pulse amplitude modulation (PAM) fluorometry. Bot. Mar. 5, 499–509. https://doi.org/10.1515/bot-2012-0135 (2012).CAS 
Article 

Google Scholar 
43.Noisette, F., Egilsdottir, H., Davoult, D. & Martin, S. Physiological responses of three temperate coralline algae from contrasting habitats to near-future ocean acidification. J. Exp. Mar. Biol. Ecol. 448, 179–187. https://doi.org/10.1016/j.jembe.2013.07.006 (2013).CAS 
Article 

Google Scholar 
44.Martin, S., Cohu, S., Vignot, C., Zimmerman, G. & Gattuso, J. P. One-year experiment on the physiological response of the Mediterranean crustose coralline alga, Lithophyllum cabiochae, to elevated pCO2 and temperature. Ecol. Evol. 3(3), 676–693. https://doi.org/10.1002/ece3.475 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
45.Johnson, M. D., Moriarty, V. W. & Carpenter, R. C. Acclimatization of the crustose coralline alga Porolithon onkodes to variable pCO2. PLoS ONE 9(2), e87678. https://doi.org/10.1371/journal.pone.0087678 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
46.Cornwall, C. E. et al. A coralline alga gains tolerance to ocean acidification over multiple generations of exposure. Nat. Clim. Chang. 10, 143–146. https://doi.org/10.1038/s41558-019-0681-8 (2020).ADS 
CAS 
Article 

Google Scholar 
47.Cornwall, C. E. et al. Diurnal fluctuations in seawater pH influence the response of a calcifying macroalga to ocean acidification. Proc. Roy. Soc. London Series B 280, 20132201. https://doi.org/10.1098/rspb.2013.2201 (2013).CAS 
Article 

Google Scholar 
48.Boyd, P. W. et al. Biological responses to environmental heterogeneity under future ocean conditions. Global Change Biol. 22(8), 2633–2650. https://doi.org/10.1111/gcb.13287 (2016).ADS 
Article 

Google Scholar 
49.Noisette, F. & Hurd, C. Abiotic and biotic interactions in the diffusive boundary layer of kelp blades create a potential refuge from ocean acidification. Funct. Ecol. 32(5), 1329–1342. https://doi.org/10.1111/1365-2435.13067 (2018).Article 

Google Scholar 
50.Johnson, M. D. et al. pH variability exacerbates effects of ocean acidification on a Caribbean crustose coralline alga. Front. Mar. Sci. 6, 150. https://doi.org/10.3389/fmars.2019.00150 (2019).Article 

Google Scholar 
51.Borowitzka, M. A. Photosynthesis and calcification in the articulated coralline red algae Amphiroa anceps and A foliacea. Mar. Biol. 62, 17–23. https://doi.org/10.1007/BF00396947 (1981).CAS 
Article 

Google Scholar 
52.Chisholm, J. R. Calcification by crustose coralline algae on the northern Great Barrier Reef Australia. Limnol. Oceanogr. 45(7), 1476–1484. https://doi.org/10.4319/lo.2000.45.7.1476 (2000).ADS 
CAS 
Article 

Google Scholar 
53.Martin, S., Castets, M.-D. & Clavier, J. Primary production, respiration and calcification of the temperate free-living coralline alga Lithothamnion corallioides. Aquat. Bot. 85, 121–128. https://doi.org/10.1016/j.aquabot.2006.02.005 (2006).CAS 
Article 

Google Scholar 
54.McNicholl, C. et al. Ocean acidification effects on calcification and dissolution in tropical reef macroalgae. Coral Reefs 39, 1635–1647. https://doi.org/10.1007/s00338-020-01991-x (2020).Article 

Google Scholar 
55.Kamenos, N. A. et al. Coralline algal structure is more sensitive to rate, rather than the magnitude, of ocean acidification. Global Change Biol. 19, 3621–3628. https://doi.org/10.1111/gcb.12351 (2013).ADS 
Article 

Google Scholar 
56.Vogel, N. et al. Calcareous green alga Halimeda tolerates ocean acidification conditions at tropical carbon dioxide seeps. Limnol. Oceanogr. 60, 263–275. https://doi.org/10.1002/lno.10021 (2015).ADS 
Article 

Google Scholar 
57.Vogel, N., Meyer, F. W., Wild, C. & Uthicke, S. Decreased light availability can amplify negative impacts of ocean acidification on calcifying coral reef organisms. Mar. Ecol. Prog. Ser. 521, 49–61. https://doi.org/10.3354/meps11088 (2015).ADS 
CAS 
Article 

Google Scholar 
58.McNicholl, C. & Koch, M. S. Irradiance, photosynthesis and elevated pCO2 effects on net calcification in tropical reef macroalgae. J. Exp. Mar. Biol. Ecol. 535, 151489. https://doi.org/10.1016/j.jembe.2020.151489 (2021).Article 

Google Scholar 
59.Schoenrock, K. M. et al. Influences of salinity on the physiology and distribution of the Arctic coralline algae, Lithothamnion glaciale (Corallinales, Rhodophyta). J. Phycol. 54, 690–702. https://doi.org/10.1111/jpy.12774 (2018).CAS 
Article 
PubMed 

Google Scholar 
60.MAArE. Projeto de monitoramento ambiental da Reserva Biológica Marinha do Arvoredo e entorno. Florianópolis, Brazil: ICMBio/UFSC (2017).61.Kaandorp, J. A. & Kübler, J. E. The algorithmic beauty of seaweeds, sponges and corals (Springer, Heidelberg, 2001). https://doi.org/10.1007/978-3-662-04339-4.Book 
MATH 

Google Scholar 
62.Leal, R. N., Bassi, D., Posenato, R. & Amado-Filho, G. M. Tomographic analysis for bioerosion signatures in shallow-water rhodoliths from the Abrolhos Bank Brazil. J. Coast. Res. 279, 306–309. https://doi.org/10.2112/11T-00006.1 (2012).Article 

Google Scholar 
63.Teichert, S. Hollow rhodoliths increase Svalbard’s shelf biodiversity. Sci. Rep. 4, 1–5. https://doi.org/10.1038/srep06972 (2014).CAS 
Article 

Google Scholar 
64.Torrano-Silva, B. N., Ferreira, S. G. & Oliveira, M. C. Unveiling privacy: Advances in microtomography of coralline algae. Micron 72, 34–38. https://doi.org/10.1016/j.micron.2015.02.004 (2015).Article 
PubMed 

Google Scholar 
65.Laforsch, C. et al. A precise and non-destructive method to calculate the surface area in living scleractinian corals using x-ray computed tomography and 3D modeling. Coral Reefs 27, 811–820. https://doi.org/10.1007/s00338-008-0405-4 (2008).ADS 
Article 

Google Scholar 
66.Limaye, A. Drishti: a volume exploration and representation tool. In Developments in X-Ray Tomography VIII, San Diego, California, USA: SPIE Proc. 85060X; https://doi.org/10.1117/12.935640 (2012).67.Ahrens, J., Geveci, B. & Law, C. ParaView: An End-User Tool for Large Data Visualization. In Visualization Handbook (eds CD Hansen, CR Johnson) Oxford, UK: Elsevier; https://doi.org/10.1016/B978-012387582-2/50038-1 (2005).68.Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682. https://doi.org/10.1038/nmeth.2019 (2012).CAS 
Article 
PubMed 

Google Scholar 
69.Rueden, C. T. et al. Image J2: ImageJ for the next generation of scientific image data. BMC Bioinformatics 18, 529. https://doi.org/10.1186/s12859-017-1934-z (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
70.Revsbech, N. P. An oxygen microsensor with a guard cathode. Limnol. Oceanogr. 34, 474–478. https://doi.org/10.4319/lo.1989.34.2.0474 (1989).ADS 
CAS 
Article 

Google Scholar 
71.de Beer, D. et al. A microsensor for carbonate ions suitable for microprofiling in freshwater and saline environments. Limnol. Oceanogr. Methods 6, 532–541. https://doi.org/10.4319/lom.2008.6.532 (2008).Article 

Google Scholar 
72.Jørgensen, B. B. & Revsbech, N. P. Diffusive boundary layers and the oxygen uptake of sediments and detritus 1. Limnol. Oceanogr. 30, 111–122. https://doi.org/10.4319/lo.1985.30.1.0111 (1985).ADS 
Article 

Google Scholar 
73.Smith, S.V. & Kinsey, D.W. Calcification and organic carbon metabolism as indicated by carbon dioxide. In Coral Reefs: Research Methods. Monographs on Oceanographic Methodology (eds. Stoddart, D. & Johannes, R.). Paris: UNESCO (1978)74.Hansson, I. & Jagner, D. Evaluation of the accuracy of Gran plots by means of computer calculations: application to the potentiometric titration of the total alkalinity and carbonate content in sea water. Anal. Chim. Acta 75, 363–373. https://doi.org/10.1016/S0003-2670(01)82503-4 (1973).Article 

Google Scholar 
75.Bradshaw, A. L., Brewer, P. G., Sharer, D. K. & Williams, R. T. Measurements of total carbon dioxide and alkalinity by potentiometric titration in the GEOSECS program. Earth Planet. Sci. Lett. 55, 99–115. https://doi.org/10.1016/0012-821X(81)90090-X (1981).ADS 
CAS 
Article 

Google Scholar 
76.Stimson, J. & Kinzie, R. A. The temporal pattern and rate of release of zooxanthellae from the reef coral Pocillophora damicornis (Linnaeus) under nitrogen-enrichment and control conditions. J. Exp. Mar. Biol. Ecol. 153, 63–74. https://doi.org/10.1016/S0022-0981(05)80006-1 (1991).Article 

Google Scholar 
77.Naumann, M. S., Niggl, W., Laforsch, C., Glaser, C. & Wild, C. Coral surface area quantification-evaluation of established techniques by comparison with computer tomography. Coral Reefs 28, 109–117. https://doi.org/10.1007/s00338-008-0459-3 (2009).ADS 
Article 

Google Scholar 
78.Veal, C. J., Holmes, G., Nunez, M., Hoegh-Guldberg, O. & Osborn, J. A comparative study of methods for surface area and three-dimensional shape measurements of coral skeletons. Limnol. Oceanogr. Methods 8, 241–253. https://doi.org/10.4319/lom.2010.8.241 (2010).Article 

Google Scholar  More

Physico-chemical conditionsSampling was performed at 6 stations representing the physical and chemical characteristics of the investigated area (Supplementary Table S1). Thermohaline properties were the result of horizontal advection of above-average salinities driven by a North Ionian cyclonic gyre controlled by the Adriatic Ionian Bimodal Oscillating System46. September and the whole summer of 2016 was characterized by extremely high temperatures, and precipitation in the climatologic expected range. A cyclone with a cold front followed by a strong Bora wind passed over the Adriatic a week before the cruise, in the period between the 16th and 20th of September 2016. Heat and mass exchange in the air-sea boundary layer were responsible for the characteristic vertical thermohaline profiles measured in late summer. Over the investigated area, the mixed layer depth located between 20 and 25 m was horizontally homogenous. The coldest water mass (temperature 12.94 °C, salinity 38.68) was located at the bottom of Jabuka Pit.Abundance of bacteria, autotrophic picoplankton and AAPBacterial abundances ranged between 0.05 and 0.46 × 106 cell mL−1 in all three areas, with a slightly higher average value in Jabuka Pit (0.31 × 106 cell mL−1). The bacterial abundances were the highest in the upper layers down to the 50 m deep layer and showed a decreasing trend towards the bottom (Supplementary Table S2). The portion of HNA bacteria ranged from 37.8 to 73.12% (on average 51.27%), with the prevalence of HNA over the LNA group below the epipelagic layer.Marine Synechococcus dominated the autotrophic picoplankton community with abundances ranging from 0.08 to 23.86 × 103 cell mL−1. The presence of Prochlorococcus cells was also detected in all samples in a range from a few cells to 1.33 × 103 cell mL−1. Picoeukaryotes also showed a similar range from a few cells to 0.83 × 103 cell mL−1. The highest abundances of picophytoplankton were measured in the upper 50 m, with the exception of the Palagruža Sill (PS) area, where an increase in abundance was observed at 100 m depth. Bacterial production ranged from 0.2 × 104 to 0.36 × 104 cell mL−1 h−1, with increased values in the shallow layers and a mostly uniform vertical distribution in the water column (Supplementary Table S2).AAP bacteria abundance ranged from 0.9 × 103 to 22.3 × 103 cell mL−1, thus constituting 0.42% to 6.83% of the bacteria. Their highest average contribution was observed in the South Adriatic Pit (4.11%), while on the vertical scale, their highest contribution was observed in the upper 20 m of the seawater (see Supplementary Table S2).Relationship between the picoplankton community and environmental parametersBased on biological characteristics (total prokaryotes, Synechococcus, Prochlorococcus, picoeukaryotes, heterotrophic nanoflagellates, aerobic anoxygenic phototrophs, high and low nucleic acid bacteria, bacterial production), we distinguished five picoplanktonic clusters (PIC-BMUs) and then searched for explanations of the observed patterns (Fig. 2A,B). The mean values of biological and physico-chemical parameters for each cluster are shown in Table 1.Figure 2(A) Bar plot representation of biotic (black) and abiotic (grey) parameters for neural gas best-matching units (picoplankton-PIC-BMUs) with relative frequency appearance for each neuron. TP-total prokaryotes, SYN-Synechococcus, PROCHL-Prochlorococcus, PE-picoeukaryotes, HNF-heterotrophic nanoflagellates, AAP-aerobic anoxygenic phototrophs, AAP%-portion of AAP, HNA% percentage of high nucleic acid content bacteria, LNA%-percentage of low nucleic acid content bacteria-LNA%, BP-bacterial production. (B) Water column distribution of Neural gas best-matching units (BMU, labels with numbers, and stained with a different colour for clearance, coloured non-labelled squares shows clarity) for measuring stations (SAP1-3, PS1-2 and JP1). The software MATLAB. version 7.10.0 (R2018). Natick, Massachusetts: The MathWorks Inc. (2018) (https://www.mathworks.com/) was used to generate the figure.Full size imageTable 1 Characteristics of biological (abundances of total prokaryotes-TP, Synechococcus-SYN, Prochlorococcus-PROCHL, picoeukaryotes-PE, heterotrophic nanoflagellates-HNF, aerobic anoxygenic phototrophs(AAP); contributions (%) of AAP, High nucleic acid content bacteria-HNA and Low nucleic acid content bacteria-LNA%; and bacterial production-BP) and environmental factors in the sampling terms assigned to the neural gas clusters.Full size tablePIC-BMU1 described a very rare pattern, found in only two samples from 10 m depth in Palaguža Sill and Jabuka Pit. They were characterised by the highest abundances of total prokaryotes with a dominance of HNA and elevated AAP abundance. These samples were unique in terms of hydrological parameters, as they represented an N-limited environment (TIN  More

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

Google Scholar 
Alberdi A, Aizpurua O, Bohmann K, Zepeda-Mendoza ML, Gilbert MTP (2016) Do vertebrate gut metagenomes confer rapid ecological adaptation? Trends Ecol Evol 31:689–699PubMed 
Article 
PubMed Central 

Google Scholar 
Amaral WZ, Lubach GR, Proctor A, Lyte M, Phillips GJ, Coe CL (2017) Social influences on Prevotella and the gut microbiome of young monkeys. Psychosom Med 79:888–897PubMed 
PubMed Central 
Article 

Google Scholar 
Amato KR, Sanders GJ, Song SJ, Nute M, Metcalf JL, Thompson LR et al. (2019) Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes. ISME J 13:576–587CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57:289–300
Google Scholar 
Björk JR, Dasari M, Grieneisen L, Archie EA (2019) Primate microbiomes over time: longitudinal answers to standing questions in microbiome research. Am J Primatol 81:e22970PubMed 
PubMed Central 
Article 

Google Scholar 
Brooks JW (2016) Postmortem changes in animal carcasses and estimation of the postmortem interval. Vet Pathol 53:929–940CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP (2016) DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Callahan BJ, Wong J, Heiner C, Oh S, Theriot CM, Gulati AS et al. (2019) High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. Nucleic Acids Res 47:e103CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Clayton JB, Vangay P, Huang H, Ward T, Hillmann BM, Al-Ghalith GA et al. (2016) Captivity humanizes the primate microbiome. Proc Natl Acad Sci U S A 113:10376–10381CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cryan JF, Dinan TG (2012) Mind-altering microorganisms: the impact of the gut microbiota on brain and behaviour. Nat Rev Neurosci 13:701–712CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S et al. (2010) Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A 107:14691–14696PubMed 
PubMed Central 
Article 

Google Scholar 
Dill-McFarland KA, Neil KL, Zeng A, Sprenger RJ, Kurtz CC, Suen G et al. (2014) Hibernation alters the diversity and composition of mucosa-associated bacteria while enhancing antimicrobial defence in the gut of 13-lined ground squirrels. Mol Ecol 23:4658–4669CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Donaldson GP, Lee SM, Mazmanian SK (2016) Gut biogeography of the bacterial microbiota. Nat Rev Microbiol 14:20–32CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Dubois S, Fenwick N, Ryan EA, Baker L, Baker SE, Beausoleil NJ et al. (2017) International consensus principles for ethical wildlife control. Conserv Biol J Soc Conserv Biol 31:753–760Article 

Google Scholar 
Earl JP, Adappa ND, Krol J, Bhat AS, Balashov S, Ehrlich RL et al. (2018) Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes. Microbiome 6:190PubMed 
PubMed Central 
Article 

Google Scholar 
Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ericsson AC, Johnson PJ, Lopes MA, Perry SC, Lanter HR (2016) A microbiological map of the healthy equine gastrointestinal tract. PLoS ONE 11:e0166523PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
García-Amado MA, Michelangeli F, Gueneau P, Perez ME, Domínguez-Bello MG (2007) Bacterial detoxification of saponins in the crop of the avian foregut fermenter Opisthocomus hoazin. J Anim Feed Sci 16:82–85Article 

Google Scholar 
Gomez A, Petrzelkova KJ, Burns MB, Yeoman CJ, Amato KR, Vlckova K et al. (2016) Gut microbiome of coexisting BaAka pygmies and Bantu reflects gradients of traditional subsistence patterns. Cell Rep 14:2142–2153CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Gomez A, Petrzelkova K, Yeoman CJ, Vlckova K, Mrázek J, Koppova I et al. (2015) Gut microbiome composition and metabolomic profiles of wild western lowland gorillas (Gorilla gorilla gorilla) reflect host ecology. Mol Ecol 24:2551–2565CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Gorvitovskaia A, Holmes SP, Huse SM (2016) Interpreting Prevotella and bacteroides as biomarkers of diet and lifestyle. Microbiome 4:15PubMed 
PubMed Central 
Article 

Google Scholar 
Gregorová S, Forejt J (2000) PWD/Ph and PWK/Ph inbred mouse strains of Mus m. musculus subspecies–a valuable resource of phenotypic variations and genomic polymorphisms. Folia Biol 46:31–41
Google Scholar 
Gu S, Chen D, Zhang J-N, Lv X, Wang K, Duan L-P et al. (2013) Bacterial community mapping of the mouse gastrointestinal tract. PLoS ONE 8:e74957Heimesaat MM, Boelke S, Fischer A, Haag L-M, Loddenkemper C, Kühl AA et al. (2012) Comprehensive postmortem analyses of intestinal microbiota changes and bacterial translocation in human flora associated mice. PloS ONE 7:e40758CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hird SM (2017) Evolutionary biology needs wild microbiomes. Front Microbiol 8:725Iljazovic A, Roy U, Gálvez EJC, Lesker TR, Zhao B, Gronow A et al. (2020) Perturbation of the gut microbiome by Prevotella spp. enhances host susceptibility to mucosal inflammation. Mucosal Immunol 14:113–124PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Ingala MR, Simmons NB, Wultsch C, Krampis K, Speer KA, Perkins SL (2018) Comparing microbiome sampling methods in a wild mammal: fecal and intestinal samples record different signals of host ecology, evolution. Front Microbiol 9:803Karasov WH, Douglas AE (2013) Comparative digestive physiology. Compr Physiol 3:741–783PubMed 
PubMed Central 

Google Scholar 
Kartzinel TR, Hsing JC, Musili PM, Brown BRP, Pringle RM (2019) Covariation of diet and gut microbiome in African megafauna. Proc Natl Acad Sci U S A 116:23588–23593CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kohl KD, Dearing MD (2016) The woodrat gut microbiota as an experimental system for understanding microbial metabolism of dietary toxins. Front Microbiol 7:1165Kohl KD, Luong K, Dearing MD (2015) Validating the use of trap-collected feces for studying the gut microbiota of a small mammal (Neotoma lepida). J Mammal 96:90–93Article 

Google Scholar 
Kohl KD, Varner J, Wilkening JL, Dearing MD (2018) Gut microbial communities of American pikas (Ochotona princeps): Evidence for phylosymbiosis and adaptations to novel diets. J Anim Ecol 87:323–330PubMed 
Article 
PubMed Central 

Google Scholar 
Kreisinger J, Bastien G, Hauffe HC, Marchesi J, Perkins SE (2015) Interactions between multiple helminths and the gut microbiota in wild rodents. Philos Trans R Soc B Biol Sci 370:20140295Kreisinger J, Čížková D, Vohánka J, Piálek J (2014) Gastrointestinal microbiota of wild and inbred individuals of two house mouse subspecies assessed using high-throughput parallel pyrosequencing. Mol Ecol 23:5048–5060CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Kreisinger J, Kropáčková L, Petrželková A, Adámková M, Tomášek O, Martin J-F et al. (2017) Temporal stability and the effect of transgenerational transfer on fecal microbiota structure in a long distance migratory bird. Front Microbiol 8:50Laukaitis CM, Critser ES, Karn RC (1997) Salivary androgen-binding protein (ABP) mediates sexual isolation in Mus musculus. Evol Int J Org Evol 51:2000–2005CAS 
Article 

Google Scholar 
Lawrence K, Lam K, Morgun A, Shulzhenko NLöhr C (2019) Effect of temperature and time on the thanatomicrobiome of the cecum, ileum, kidney, and lung of domestic rabbits. J Vet Diagn Invest 31. https://doi.org/10.1177/1040638719828412Legendre P, Anderson MJ (1999) Distance-based redundancy analysis: testing multispecies responses in multifactorial ecological experiments. Ecol Monogr 69:1–24Article 

Google Scholar 
Li D, Chen H, Mao B, Yang Q, Zhao J, Gu Z et al. (2017) Microbial biogeography and core microbiota of the rat digestive tract. Sci Rep 7:45840PubMed Central 
Article 
CAS 

Google Scholar 
Maslanik T, Tannura K, Mahaffey L, Loughridge AB, Benninson L, Ursell L et al. (2012) Commensal bacteria and MAMPs are necessary for stress-induced increases in IL-1β and IL-18 but not IL-6, IL-10 or MCP-1. PLoS ONE 7:e50636CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Matsuo Y, Komiya S, Yasumizu Y, Yasuoka Y, Mizushima K, Takagi T et al. (2020) Full-length 16S rRNA gene amplicon analysis of human gut microbiota using MinIONTM nanopore sequencing confers species-level resolution. bioRxiv. https://doi.org/10.1101/2020.05.06.078147McKenzie VJ, Song SJ, Delsuc F, Prest TL, Oliverio AM, Korpita TM et al. (2017) The effects of captivity on the mammalian gut microbiome. Integr Comp Biol 57:690–704PubMed 
PubMed Central 
Article 

Google Scholar 
McMurdie PJ, Holmes S (2014) Waste not, want not: why rarefying microbiome data is inadmissible. PLOS Comput Biol 10:e1003531PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Menke S, Meier M, Sommer S (2015) Shifts in the gut microbiome observed in wildlife faecal samples exposed to natural weather conditions: lessons from time-series analyses using next-generation sequencing for application in field studies. Methods Ecol Evol 6:1080–1087Article 

Google Scholar 
Miller AW, Oakeson KF, Dale C, Dearing MD (2016) Microbial community transplant results in increased and long-term oxalate degradation. Micro Ecol 72:470–478CAS 
Article 

Google Scholar 
Pafčo B, Čížková D, Kreisinger J, Hasegawa H, Vallo P, Shutt K et al. (2018) Metabarcoding analysis of strongylid nematode diversity in two sympatric primate species. Sci Rep 8:5933Palm NW, de Zoete MR, Cullen TW, Barry NA, Stefanowski J, Hao L et al. (2014) Immunoglobulin A coating identifies colitogenic bacteria in inflammatory bowel disease. Cell 158:1000–1010CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Pechal JL, Schmidt CJ, Jordan HR, Benbow ME (2018) A large-scale survey of the postmortem human microbiome, and its potential to provide insight into the living health condition. Sci Rep 8:5724PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Pollock J, Glendinning L, Wisedchanwet T, Watson M (2018) The madness of microbiome: attempting to find consensus “best practice” for 16S microbiome studies. Appl Environ Microbiol 84:e02627–17PubMed 
PubMed Central 
Article 

Google Scholar 
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P et al. (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Google Scholar 
Rosshart SP, Vassallo BG, Angeletti D, Hutchinson DS, Morgan AP, Takeda K et al. (2017) Wild mouse gut microbiota promotes host fitness and improves disease resistance. Cell 171:1015–1028.e13CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Round JL, Mazmanian SK (2009) The gut microbiome shapes intestinal immune responses during health and disease. Nat Rev Immunol 9:313–323CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Scher JU, Sczesnak A, Longman RS, Segata N, Ubeda C, Bielski C et al. (2013) Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2:e01202PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Sommer F, Ståhlman M, Ilkayeva O, Arnemo JM, Kindberg J, Josefsson J et al. (2016) The gut microbiota modulates energy metabolism in the hibernating brown bear Ursus arctos. Cell Rep 14:1655–1661CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Stalder GL, Pinior B, Zwirzitz B, Loncaric I, Jakupović D, Vetter SG et al. (2019) Gut microbiota of the European Brown Hare (Lepus europaeus). Sci Rep 9:2738CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Stanley D, Geier MS, Chen H, Hughes RJ, Moore RJ (2015) Comparison of fecal and cecal microbiotas reveals qualitative similarities but quantitative differences. BMC Microbiol 15:51PubMed 
PubMed Central 
Article 

Google Scholar 
Stearns JC, Lynch MDJ, Senadheera DB, Tenenbaum HC, Goldberg MB, Cvitkovitch DG et al. (2011) Bacterial biogeography of the human digestive tract. Sci Rep 1:170CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Stothart MR, Palme R, Newman AEM (2019) It’s what’s on the inside that counts: stress physiology and the bacterial microbiome of a wild urban mammal. Proc R Soc B Biol Sci 286:20192111Article 

Google Scholar 
Suzuki TA, Martins FM, Nachman MW (2019) Altitudinal variation of the gut microbiota in wild house mice. Mol Ecol 28:2378–2390CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Suzuki TA, Nachman MW (2016) Spatial heterogeneity of gut microbial composition along the gastrointestinal tract in natural populations of house mice (EG Zoetendal, Ed.). PLoS ONE 11:e0163720PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Tanca A, Manghina V, Fraumene C, Palomba A, Abbondio M, Deligios M et al. (2017) Metaproteogenomics reveals taxonomic and functional changes between cecal and fecal microbiota in mouse. Front Microbiol 8:391Tang Q, Jin G, Wang G, Liu T, Liu X, Wang B et al. (2020) Current sampling methods for gut microbiota: a call for more precise devices. Front Cell Infect Microbiol 10:151Tang W, Zhu G, Shi Q, Yang S, Ma T, Mishra SK et al. (2019) Characterizing the microbiota in gastrointestinal tract segments of Rhabdophis subminiatus: dynamic changes and functional predictions. MicrobiologyOpen 8:e789Trevelline BK, Fontaine SS, Hartup BK, Kohl KD (2019) Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc R Soc B Biol Sci 286:20182448Article 

Google Scholar 
Tuomisto S, Karhunen PJ, Pessi T (2013) Time-dependent post mortem changes in the composition of intestinal bacteria using real-time quantitative PCR. Gut Pathog 5:35Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444:1027–1031PubMed 
Article 
PubMed Central 

Google Scholar 
Vasemägi A, Visse M, Kisand V (2017) Effect of Environmental Factors and an Emerging Parasitic Disease on Gut Microbiome of Wild Salmonid Fish. mSphere 2:e00418–17PubMed 
PubMed Central 
Article 

Google Scholar 
Videvall E, Strandh M, Engelbrecht A, Cloete S, Cornwallis C (2017) Measuring the gut microbiome in birds: Comparison of faecal and cloacal sampling. Mol Ecol Resour 18:424–434PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
Vlčková K, Shutt-Phillips K, Heistermann M, Pafčo B, Petrželková KJ, Todd A et al. (2018) Impact of stress on the gut microbiome of free-ranging western lowland gorillas. Microbiol Read Engl 164:40–44Article 
CAS 

Google Scholar 
Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wang J, Linnenbrink M, Künzel S, Fernandes R, Nadeau M-J, Rosenstiel P et al. (2014) Dietary history contributes to enterotype-like clustering and functional metagenomic content in the intestinal microbiome of wild mice. Proc Natl Acad Sci U S A 111:E2703–2710CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Warne RW, Kirschman L, Zeglin L (2017) Manipulation of gut microbiota reveals shifting community structure shaped by host developmental windows in amphibian larvae. Integr Comp Biol 57:786–794PubMed 
Article 
PubMed Central 

Google Scholar 
Weldon L, Abolins S, Lenzi L, Bourne C, Riley EM, Viney M (2015) The gut microbiota of wild mice. PLoS ONE 10:e0134643PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Wu GD, Chen J, Hoffmann C, Bittinger K, Chen Y-Y, Keilbaugh SA et al. (2011) Linking long-term dietary patterns with gut microbial enterotypes. Science 334:105–108CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Yan W, Sun C, Zheng J, Wen C, Ji C, Zhang D et al. (2019) Efficacy of fecal sampling as a gut proxy in the study of chicken gut microbiota. Front Microbiol 10:2126Yasuda K, Oh K, Ren B, Tickle TL, Franzosa EA, Wachtman LM et al. (2015) Biogeography of the intestinal mucosal and lumenal microbiome in the rhesus macaque. Cell Host Microbe 17:385–391CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zemanova MA (2019) Poor implementation of non-invasive sampling in wildlife genetics studies. Rethink Ecol 4:119–132Article 

Google Scholar 
Zemanova MA (2020) Towards more compassionate wildlife research through the 3Rs principles: moving from invasive to non-invasive methods. Wildl Biol 2020. https://doi.org/10.2981/wlb.00607Zhao W, Wang Y, Liu S, Huang J, Zhai Z, He C et al. (2015) The dynamic distribution of porcine microbiota across different ages and gastrointestinal tract segments. PLoS ONE 10:e0117441PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Zilber-Rosenberg I, Rosenberg E (2008) Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution. FEMS Microbiol Rev 32:723–735CAS 
PubMed 
Article 
PubMed Central 

Google Scholar  More

1.Simões, R. A., Reis, L. G., Bento, J. M., Solter, L. F. & Delalibera, I. Jr. Biological and behavioral parameters of the parasitoid Cotesia flavipes (Hymenoptera: Braconidae) are altered by the pathogen Nosema sp. (Microsporidia: Nosematidae). Biol. Control 63, 164–171 (2012).Article 

Google Scholar 
2.Frago, E., Dicke, M. & Godfray, H. C. J. Insect symbionts as hidden players in insect–plant interactions. Trends Ecol. Evol. 27, 705–711 (2012).Article 

Google Scholar 
3.Himler, A. G. et al. Rapid spread of a bacterial symbiont in an invasive whitefly is driven by the fitness benefits and female bias. Science 332, 254–256 (2011).ADS 
CAS 
Article 

Google Scholar 
4.Lu, M., Wingfield, M. J., Gillette, N. & Sun, J. H. Do novel genotypes drive the success of an invasive bark beetle–fungus complex? Implications for potential reinvasion. Ecology 92, 2013–2019 (2011).Article 

Google Scholar 
5.Vilcinskas, A., Stoecker, K., Schmidtberg, H., Röhrich, C. R. & Vogel, H. Invasive harlequin ladybird carries biological weapons against native competitors. Science 340, 862–863 (2013).ADS 
CAS 
Article 

Google Scholar 
6.Zhao, L. et al. A native fungal symbiont facilitates the prevalence and development of an invasive pathogen–native vector symbiosis. Ecology 94, 2817–2826 (2013).Article 

Google Scholar 
7.Solter, L. F., Becnel, J. J. & Vávra, J. Research methods for entomopathogenic microsporidia and other protists. Manual of Techniques in Invertebrate Pathology 329–371 (2012).8.Maddox, J. V. Protozoan diseases. Epizootiol. Insect Dis. 1, 417–452 (1987).
Google Scholar 
9.Latchininsky, A. V. & VanDyke, K. A. Grasshopper and locust control with poisoned baits: a renaissance of the old strategy?. Outlooks Pest Manag. 17, 105–111 (2006).Article 

Google Scholar 
10.Sweeney, A. W. & Becnel, J. J. Potential of microsporidia for the control of mosquitoes. Parasitol. Today. 7, 217–220 (1991).CAS 
Article 

Google Scholar 
11.Capella-Gutierrez, S., Marcet-Houben, M. & Gabaldon, T. Phylogenomics supports microsporidia as the earliest diverging clade of sequenced fungi. BMC Biol. 10, 47–52 (2012).Article 

Google Scholar 
12.Tokarev, Y. S. et al. A formal redefinition of the genera Nosema and Vairimorpha (Microsporidia: Nosematidae) and reassignment of species based on molecular phylogenetics. J. Invertebr. Pathol. 169, 107279 (2020).CAS 
Article 

Google Scholar 
13.Tooke, F. G. C. The Eucalyptus Snout beetle, Gonipterus scutellatus Gyll. A study of its ecology and control by biological means Union of South Africa, Department of Agriculture. Entomol. Mem. 3, 1–184 (1955).
Google Scholar 
14.Mapondera, T. S., Burgess, T., Matsuki, M. & Oberprieler, R. G. Identification and molecular phylogenetics of the cryptic species of the Gonipterus scutellatus complex (Coleoptera: Curculionidae: Gonipterini). Aust. J. Entomol. 51, 175–188 (2012).Article 

Google Scholar 
15.Valente, C. et al. Economic outcome of classical biological control: a case study on the Eucalyptus snout beetle, Gonipterus platensis, and the parasitoid Anaphes nitens. Ecol Econ. 149, 40–47 (2018).Article 

Google Scholar 
16.Ansari, M. J., Al-Ghamdi, A., Nuru, A., Khan, K. A. & Alattal, Y. Geographical distribution and molecular detection of Nosema ceranae from indigenous honeybees of Saudi Arabia. Saudi J. Biol. Sci 24, 983–991 (2017).Article 

Google Scholar 
17.Ovcharenko, M., Świątek, P., Ironside, J. & Skalski, T. Orthosomella lipae sp. n. (Microsporidia) a parasite of the weevil, Liophloeus lentus Germar, 1824 (Coleoptera: Curculionidae). J. Invertebr. Pathol. 112, 33–40 (2013).Article 

Google Scholar 
18.Weiser, J. A new microsporidian from the bark beetle Pityokteines curvidens Germar (Coleoptera, Scolytidae) in Czechoslovakia. J. Invertebr. Pathol. 3, 324–329 (1961).
Google Scholar 
19.Malone, L. A. A new pathogen, Microsporidium itiiti n. sp. (Microsporida), from the Argentine Stem Weevil, Listronotus bonariensis (Coleoptera, Curculionidae). J. Protozool. 32, 535–541 (1985).Article 

Google Scholar 
20.Purrini, K. & Weiser, J. Ultrastructural study of the microsporidian Chytridiopsis typographi (Chytridiopsida: Microspora) infecting the bark beetle, Ips typographus (Scolytidae: Coleoptera), with new data on spore dimorphism. J. Invertebr. Pathol. 45, 66–74 (1985).Article 

Google Scholar 
21.Yaman, M., Radek, R., Aslan, I. & Erturk, O. Characteristic features of Nosema phyllotretae Weiser 1961, a microsporidian parasite of Phyllotreta atra (Coleoptera: Chrysomelidae) in Turkey. Zool. Stud. Taipei. 44, 368 (2005).
Google Scholar 
22.Zhu, F. et al. A new isolate of Nosema sp. (Microsporidia, Nosematidae) from Phyllobrotica armata Baly (Coleoptera, Chrysomelidae) from China. Jour J. Invertebr. Pathol. 106, 339–342 (2011).CAS 
Article 

Google Scholar 
23.Andreadis, T. G., Takaoka, H., Otsuka, Y. & Vossbrinck, C. R. Morphological and molecular characterization of a microsporidian parasite, Takaokaspora nipponicus n. gen. n. sp. from the invasive rock pool mosquito, Ochlerotatus japonicus japonicus. J. Invertebr. Pathol. 114, 161–172 (2013).CAS 
Article 

Google Scholar 
24.Sapir, A. et al. Microsporidia-nematode associations in methane seeps reveal basal fungal parasitism in the deep sea. Front. Microbiol. 5, 43–52 (2014).Article 

Google Scholar 
25.Solter, L. F., Maddox, J. V. & McManus, M. L. Host specificity of microsporidia (Protista: Microspora) from European populations of Lymantria dispar (Lepidoptera: Lymantriidae) to indigenous North American Lepidoptera. J. Invertebr. Pathol. 69, 135–150 (1997).CAS 
Article 

Google Scholar 
26.Knell, J. D., Allen, G. E. & Hazard, E. I. Light and electron microscope study of Thelohania solenopsae n. sp. (Microsporida: Protozoa) in the red imported fire ant Solenopsis invict. J. Invertebr. Pathol. 29, 192–200 (1977).CAS 
Article 

Google Scholar 
27.Henry, J. E., & Oma, E. A. Pest control by Nosema locustae, a pathogen of grasshoppers and crickets. Microbial Control of Pests and Plant Diseases 1970–1980 (1981).28.Vávra, J. & Maddox, J. V. Methods in microsporidiology. In Biology of the Microsporidia 281–319 (Springer, Boston, 1976).
Google Scholar 
29.Simões, R. A., Feliciano, J. R., Solter, L. F. & Delalibera, I. Jr. Impacts of Nosema sp. (Microsporidia: Nosematidae) on the sugarcane borer, Diatraea saccharalis (Lepidoptera: Crambidae). J. Invertebr. Pathol. 129, 7–12 (2015).Article 

Google Scholar 
30.Inglis, G. D., Lawrence, A. M. & Davis, F. M. Impact of a novel species of Nosema on the southwestern corn borer (Lepidoptera: Crambidae). J. Econ. Entomol. 96, 12–20 (2003).CAS 
Article 

Google Scholar 
31.Zheng, H. Q. et al. Spore loads may not be used alone as a direct indicator of the severity of Nosema ceranae infection in honey bees Apis mellifera (Hymenoptera: Apidae). J. Econ. Entomol. 107, 2037–2044 (2014).Article 

Google Scholar 
32.Goettel, M. S., Inglis, G. D. & Lacey, L. A. Manual of Techniques in Invertebrate Pathology (Academic Press, 2012).
Google Scholar 
33.Canning, E. U., Curry, A., Cheney, S., Lafranchi-Tristem, N. J., Haque, M. A. Vairimorpha imperfecta n. sp., a microsporidian exhibiting an abortive octosporous sporogony in Plutella xylostella L. (Lepidoptera: Yponomeutidae). Parasitology 119, 273–286 (1999).34.Tsai, S. J., Lo, C. F., Soichi, Y. & Wang, C. H. The characterization of microsporidian isolates (Nosematidae: Nosema) from five important lepidopteran pests in Taiwan. J. Invertebr. Pathol. 83, 51–59 (2003).CAS 
Article 

Google Scholar 
35.Cai, S. F., Lu, X. M., Qiu, H. H., Li, M. Q. & Feng, Z. Z. Phagocytic uptake of Nosema bombycis (Microsporidia) spores by insect cell lines. J. Integr. Agric. 11, 1321–1326 (2012).Article 

Google Scholar 
36.Dong, S., Shen, Z., Xu, L. & Zhu, F. Sequence and phylogenetic analysis of SSU rRNA gene of five microsporidia. Curr. Microbiol. 60, 30 (2010).CAS 
Article 

Google Scholar 
37.Becnel, J. J. & Andreadis, T. G. Microsporidia in insects. The microsporidia and microsporidiosis 447-501 (1999).38.Knell, R. J. & Webberley, K. M. Sexually transmitted diseases of insects: Distribution, evolution, ecology and host behaviour. Biol. Rev. 79, 557–581 (2004). (PERMANECE)39.Bell, H. A., Down, R. E., Kirkbride‐Smith, A. E. & Edwards, J. P. Effect of microsporidian infection in Lacanobia oleracea (Lep., Noctuidae) on prey selection and consumption by the spined soldier bug Podisus maculiventris (Het., Pentatomidae). J. Appl. Entomol. 128(8), 548–553 (2004).40.Dakhel, W. H., Latchininsky, A. V. & Jaronski, S. T. Efficacy of two entomopathogenic fungi, Metarhizium brunneum, strain F52 alone and combined with Paranosema locustae against the migratory grasshopper, Melanoplus sanguinipes, under laboratory and greenhouse conditions. Insects 10(4), 94–102 (2019).Article 

Google Scholar 
41.Guo, Y., An, Z. & Shi, W. Control of grasshoppers by combined application of Paranosema locustae and an insect growth regulator (IGR) (cascade) in rangelands in China. J. Econ. Entomol. 105(6), 1915–1920 (2012).Article 

Google Scholar 
42.Lockwood, J. A., Bomar, C. R. & Ewen, A. B. The history of biological control with Nosema locustae: Lessons for locust management. Int. J. Trop. Insect Sci. 19(4), 333–350 (1999).Article 

Google Scholar 
43.Larem, A., Fritsch, E., Undorf-Spahn, K., Kleespies, E. G. & Jehle, J. A. Interaction of Phthorimaea operculella granulovirus with a Nosema sp. microsporidium in larvae of Phthorimaea operculella. J. Invertebr. Pathol. 160, 76–86 (2019).Article 

Google Scholar 
44.Tokarev, Y. S., Grizanova, E. V., Ignatieva, A. N. & Dubovskiy, I. M. Greater wax moth Galleria mellonella (Lepidoptera: Pyralidae) as a resistant model host for Nosema pyrausta (Microsporidia: Nosematidae). J. Invertebr. Pathol. 157, 1–3 (2018).Article 

Google Scholar 
45.Coombs, N. J., Gough, A. C. & Primrose, J. N. Optimisation of DNA and RNA extraction from archival formalin-fixed tissue. Nucleic Acids Res. 27, e12-I (1999).46.Huang, W. F., Tsai, S. J., Lo, C. F., Soichi, Y. & Wang, C. H. The novel organization and complete sequence of the ribosomal RNA gene of Nosema bombycis. Fungal Genet. Biol 41, 473–481 (2004).CAS 
Article 

Google Scholar 
47.Karnovsky, M. J. A formaldehyde glutaraldehyde fixative of high osmolality for use in electron microscopy. J. Cell. Biol. 27, 1A-149A (1965).Article 

Google Scholar  More