Skip to main content
SpringerLink
Log in

A Sequential Canonical Cascade Model of Social Biogeography: Plants, Parasites, and People

  • Research Article
  • Published:
Evolutionary Psychological Science Aims and scope Submit manuscript

Abstract

This sequential canonical cascade model of social biogeography is an extension of an integrated model of human cognitive ecology (Cabeza de Baca and Figueredo Intelligence 47:63–71, 2014) that predicted state-level life history and cognitive abilities in Mexico. We integrate such population-level factors by utilizing a sample of 66 recognized national polities for which sufficiently complete information was available on all the variables modeled. These national polities were limited to those found in Europe, Asia, and Africa. The Americas and Australia were excluded to avoid sampling parts of the world that had recently undergone massive colonizations by human and nonhuman animals and plants from other zoogeographic zones, which might have disrupted the evolutionarily expected relations between physical, community, and social human ecologies. Data were obtained from national census databases and international organizations, and only national polities with complete data were analyzed, meaning that no missing data were imputed based on values from nearby or otherwise similar polities. This integrated model of social biogeography proposes that abiotic climatic factors in the physical ecology as well as biotic factors in the community ecology produce variations in subsistence and natural resources that then impact biometric markers of life history, triggering changes in social equality, within-group and between-group peace, sexual equality, macroeconomic diversification, and human capital. These effects, in turn, ultimately produce changes in brain volume and aggregate cognitive abilities. The final equation in our cascade model explains 88 % of the variance in aggregate cognitive abilities by supplying more detailed information on socioecological conditions than previous work.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Alvarez-Uria, P., & Körner, C. (2007). Low temperature limits of root growth in deciduous and evergreen temperate tree species. Functional Ecology, 21(2), 211–218.

    Article  Google Scholar 

  • Archer, J. (2009). Does sexual selection explain human sex differences in aggression? Behavioral and Brain Sciences, 32(3–4), 249–266.

    Article  PubMed  Google Scholar 

  • Barro, R., & Lee, J.-W. (2013). A new data set of educational attainment in the world, 1950–2010. Journal of Development Economics, 104, 184–198. http://www.barrolee.com/data/dataexp.htm. Retrieved 11 July 2015.

    Article  Google Scholar 

  • Basu, A., Mukherjee, N., Roy, S., Sengupta, S., Banerjee, S., Chakraborty, M., et al. (2003). Ethnic India: a genomic view, with special reference to peopling and structure. Genome Research, 13, 2277–2290.

  • Baumeister, R. F., Ainsworth, S. E., & Vohs, K. D. (2016). Are groups more or less than the sum of their members? The moderating role of individual identification. Behavioral and Brain Sciences, 1–38. doi:10.1017/S0140525X15000618.

  • Beals, K. L., Smith, C. L., & Dodd, S. M. (1984). Brain size, cranial morphology, climate, and time machines. Current Anthropology, 25, 301–330.

    Article  Google Scholar 

  • Belsky, J., Steinberg, L., & Draper, P. (1991). Childhood experience, interpersonal development, and reproductive strategy: an evolutionary theory of socialization. Child Development, 62, 647–670.

    Article  PubMed  Google Scholar 

  • Berry, W. D. (1984). Nonrecursive causal models (quantitative applications in the social sciences). Thousand Oaks: Sage.

    Book  Google Scholar 

  • Bethony, J., Brooker, S., Albonico, M., Geiger, S. M., Loukas, A., Diemert, D., & Hotez, P. J. (2006). Soil-transmitted helminth infections: ascariasis, trichuriasis, and hookworm. The Lancet, 367(9521), 1521–1532.

  • Bourdieu, P. (1986). The forms of capital. In J. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241–258). New York: Greenwood.

    Google Scholar 

  • Buss, D. M., & Duntley, J. D. (2011). The evolution of intimate partner violence. Aggression and Violent Behavior, 16(5), 411–419.

    Article  Google Scholar 

  • Cabeza de Baca, T., & Figueredo, A. J. (2014). The cognitive ecology of Mexico: climatic and socio-cultural effects on life history strategies and cognitive abilities. Intelligence, 47, 63–71.

    Article  Google Scholar 

  • Campbell, A., & Cross, C. (2012). Women and aggression. In T. K. Shackelford & V. A. Weekes-Shackelford (Eds.), The Oxford handbook of evolutionary perspectives on violence, homicide, and war (pp. 197–217). New York: Oxford University Press.

    Google Scholar 

  • Caprioli, M. (2003). Gender equality and state aggression: the impact of domestic gender equality on state first use of force. International Interactions, 29(3), 195–214.

    Article  Google Scholar 

  • Caprioli, M. (2005). Primed for violence: the role of gender inequality in predicting internal conflict. International Studies Quarterly, 49(2), 161–178.

    Article  Google Scholar 

  • Cardon, Z. G., & Whitbeck, J. H. (2007). The rhizosphere: an ecological perspective. London: Academic.

    Google Scholar 

  • Centers for Disease Control and Prevention. (2016). Skin cancer rates by race and ethnicity. http://www.cdc.gov/cancer/skin/statistics/race.htm. Retrieved 3 October 2016.

  • Charnov, E. L. (1991). Evolution of life history variation among female mammals. Proceedings of the National Academy of Sciences of the United States of America, 88, 1134–1137.

    Article  PubMed  PubMed Central  Google Scholar 

  • Chavarria Minera, C. E., Figueredo, A. J., & Lunsford, L. G. (2015). Do slower life history strategies reduce sociodemographic sex differences? Journal of Methods and Measurement in the Social Sciences, 6(1), 1–13.

    Article  Google Scholar 

  • Chisholm, J. S., Ellison, P. T., Evans, J., Lee, P. C., Lieberman, L. S., Pavlik, Z., &Worthman, C. M. (1993). Death, hope, and sex: life-history theory and the development of reproductive strategies. Current Anthropology, 34(1), 1–24.

  • Climate Charts. (2015). www.climatecharts.com. Retrieved 2 January 2015.

  • Coley, P. D. (1986). Costs and benefits of defense by tannins in a neotropical tree. Oecologia, 70(2), 238–241.

    Article  Google Scholar 

  • Copping, L. T., Campbell, A., & Muncer, S. (2013). Impulsivity, sensation seeking and reproductive behaviour: a life history perspective. Personality and Individual Differences, 54, 908–912.

    Article  Google Scholar 

  • Costin, C. L. (2007). Craft production systems. In G. M. Feinman & T. D. Price (Eds.), Archaeology at the millennium (pp. 273–327). New York: Springer.

    Google Scholar 

  • Countries of the World (2015). http://www.photius.com/rankings/. Retrieved 2 January 2015.

  • Daly, M., & Wilson, M. (1988). Homicide. New Jersey: Adeine Transaction Publishers.

    Google Scholar 

  • Darwin, C. (1859/2005). On natural selection. New York: Penguin Books.

  • Davis, H. E. (2014). Variable education exposure and cognitive task performance among the Tsimane, forager-horticulturalists. Anthropology Theses & Dissertations, Paper 17, Department of Anthropology, University of New Mexico.

  • Davidson, R. K., Amundsen, H., Lie, N. O., Luyckx, K., Robertson, L. J., Verocai, G. G., et al. (2014). Sentinels in a climatic outpost: endoparasites in the introduced muskox (Ovibos moschatus wardi) population of Dovrefjell, Norway. International Journal for Parasitology: Parasites and Wildlife, 3(2), 154–160.

  • Dawson, J. O. (2016). Why tree leaves turn color in autumn. https://web.extension.illinois.edu/forestry/fall_colors.html. Retrieved August 1 2016.

  • Del Giudice, M., Gangestad, S. W., & Kaplan, H. S. (2015). Life history theory and evolutionary psychology. In D. M. Buss (Ed.), Handbook of evolutionary psychology (2nd ed., pp. 88–114). New York: Wiley.

    Google Scholar 

  • Diamond, J. (1997). Guns, germs, and steel: the fates of human societies. New York: Norton.

    Google Scholar 

  • Ellis, B. J., Figueredo, A. J., Brumbach, B. H., & Schlomer, G. L. (2009). Fundamental dimensions of environmental risk: the impact of harsh versus unpredictable environments on the evolution and development of life history strategies. Human Nature, 20, 204–298.

    Article  PubMed  Google Scholar 

  • Eppig, C., Fincher, C. L., & Thornhill, A. R. (2010). Parasite prevalence and the worldwide distribution of cognitive ability. Proceedings of the Royal Society of London B: Biological Sciences, 277, 3801–3808.

    Article  Google Scholar 

  • Eppig, C., Fincher, C. L., & Thornhill, A. R. (2011). Parasite prevalence and the distribution of intelligence among the states of the USA. Intelligence, 39, 155–160.

    Article  Google Scholar 

  • Figueredo, A. J., & Gorsuch, R. L. (2007). Assortative mating in the jewel wasp: 2. Sequential canonical analysis as an exploratory form of path analysis. Journal of the Arizona Nevada Academy of Science, 39(2), 59–64.

    Article  Google Scholar 

  • Figueredo, A. J., & Jacobs, W. J. (2010). Aggression, risk-taking, and alternative life history strategies: the behavioral ecology of social deviance. In M. Frias-Armenta & V. Corral-Verdugo (Eds.), Biopsychosocial perspectives on interpersonal violence (pp. 3–28). Hauppauge: Nova Science.

    Google Scholar 

  • Figueredo, A. J., McKnight, P. E., McKnight, K. M., & Sidani, S. (2000). Multivariate modeling of missing data within and across assessment waves. Addiction, 95(Supplement 3), S361–S380.

    Article  PubMed  Google Scholar 

  • Figueredo, A. J., Corral-Verdugo, V., Frıas-Armenta, M., Bachar, K. J., White, J., McNeill, P. L., et al. (2001). Blood, solidarity, status, and honor: the sexual balance of power and spousal abuse in Sonora, Mexico. Evolution and Human Behavior, 22(5), 295–328.

  • Figueredo, A. J., Vásquez, G., Brumbach, B. H., & Schneider, S. M. (2004). The heritability of life history strategy: the K-factor, covitality, and personality. Biodemography and Social Biology, 51, 121–143.

    Article  Google Scholar 

  • Figueredo, A. J., Vásquez, G., Brumbach, B. H., Schneider, S. M., Sefcek, J. A., Tal, I. R., et al. (2006). Consilience and life history theory: from genes to brain to reproductive strategy. Developmental Review, 26, 243–275.

  • Figueredo, A. J., Vásquez, G., Brumbach, B. H., & Schneider, S. M. (2007). The K-factor, covitality, and personality. Human Nature, 18, 47–73.

    Article  PubMed  Google Scholar 

  • Figueredo, A. J., Wolf, P. S. A., Olderbak, S. G., Gladden, P. R., Fernandes, H. B. F., Wenner, C., et al. (2014). The psychometric assessment of human life history strategy: a meta-analytic construct validation. Evolutionary Behavioral Sciences, 8, 148–185.

  • Figueredo, A. J., Patch, E. A., & Ceballos, C. E. G. (2015). A life history approach to the dynamics of social selection. In V. Zeigler-Hill et al. (Eds.), Evolutionary perspectives on social psychology (pp. 363–372). Switzerland: Springer International.

  • Fincher, C. L., & Thornhill, R. (2008a). A parasite-driven wedge: infectious diseases may explain language and other biodiversity. Oikos, 117, 1289–1297.

    Article  Google Scholar 

  • Fincher, C. L., & Thornhill, R. (2008b). Assortative sociality, limited dispersal, infectious disease and the genesis of the global pattern of religion diversity. Proceedings of the Royal Society of London B: Biological Sciences, 275, 2587–2594.

    Article  Google Scholar 

  • Fincher, C. L., & Thornhill, R. (2012). Parasite-stress promotes in-group assortative sociality: the cases of strong family ties and heightened religiosity. Behavioral and Brain Sciences, 35, 61–119.

    Article  PubMed  Google Scholar 

  • Fincher, C. L., & Thornhill, R. (2014). The parasite-stress theory of sociality, the behavioral immune system, and human social and cognitive uniqueness. Evolutionary Behavioral Sciences, 8, 257.

    Article  Google Scholar 

  • Fincher, C. L., Thornhill, R., Murray, D. R., & Schaller, M. (2008). Pathogen prevalence predicts human cross-cultural variability in individualism/collectivism. Proceedings of the Royal Society B: Biological Sciences, 275, 1279–1285.

    Article  PubMed  PubMed Central  Google Scholar 

  • Finnish Social Science Data Archive. (2015). http://www.fsd.uta.fi/en/data/catalogue/FSD2420/meF2420e.html. Retrieved 2 January 2015.

  • Fürstenberg-Hägg, J., Zagrobelny, M., & Bak, S. (2013). Plant defense against insect herbivores. International Journal of Molecular Sciences, 14(5), 10242–10297.

  • Gat, A. (2010). Why war? Motivations for fighting in the human state of nature. In P. M. Kappeler & J. B. Silk (Eds.), Mind the gap (pp. 197–220). Berlin: Springer.

    Chapter  Google Scholar 

  • Gini, C. (1912). “Italian: Variabilità e mutabilità” ‘Variability and mutability’, C. Cuppini, Bologna, 156 pp. Reprinted in Memorie di metodologica statistica (Ed. Pizetti E, Salvemini, T). Rome: Libreria Eredi Virgilio Veschi (1955).

  • Gladden, P. R., Sisco, M., & Figueredo, A. J. (2008). Sexual coercion and life-history strategy. Evolution and Human Behavior, 29(5), 319–326.

    Article  Google Scholar 

  • Gladden, P. R., Figueredo, A. J., Andrejzak, D. J., Jones, D. N., & Smith-Castro, V. (2013). Reproductive strategy and sexual conflict: slow life history strategy inhibits negative androcentrism. Journal of Methods and Measurement in the Social Sciences, 4(1), 48–71.

    Google Scholar 

  • Gorsuch, R. L. (1983). Factor analysis. Hillsdale: Erlbaum.

    Google Scholar 

  • Gorsuch, R. L. (1991). UniMult: for univariate and multivariate data analysis. Altadena, CA: UniMult.

    Google Scholar 

  • Gorsuch, R. L. (2005). Continuous parameter estimation model: Expanding the standard statistical paradigm. Journal of the Science Faculty of Chiang Mai University, 32(1), 11–21.

  • Gorsuch, R. L. (2016). UniMult for uni- and multi-variate data analysis. Altadena, CA: UniMult. http://www.unimult.com/index.php

  • Gorsuch, R. L., & Figueredo, A.J. (1991). Sequential canonical analysis as an exploratory form of path analysis. Paper. American Evaluation Association Conference, Chicago, Illinois.

  • Goschin, Z., Constanti, D. L., Roman, M., & Ileanu, B. V. (2009). Specialization and concentration patterns in the Romanian economy. Journal of Applied Quantitative Methods, 4(1), 95–110. http://www.jaqm.ro/issues/volume-4,issue-1/pdfs/goschin_contantin_roman.pdf. Retrieved 2 January 2015.

    Google Scholar 

  • Gottfredson, L. S. (2006). Social consequences of group differences in cognitive ability (consequencias sociais das diferencas de grupo em habilidade cognitiva). In C. E. Flores-Mendoza & R. Colom (Eds.), Introducau a psicologia das diferencas individuais (pp. 433–456). Porto Allegre: ArtMed Publishers.

    Google Scholar 

  • Hanihara, K. (1991). Dual structure model for the population history of the Japanese. Nichibunken Japan Review, 2, 1–33.

    Google Scholar 

  • Heston, A., Summers, R., & Aten, B. (2011). Penn World Table version 3.6. Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania 2009. http://www.pwt.econ.upenn.edu/php_site/pwt63/pwt63_retrieve.php. Retrieved 11 July 2015.

  • Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570–10575. Central Intelligence Agency. The World Factbook 2012-13. Central Intelligence Agency, 2013.

  • Hoste, H., Jackson, F., Athanasiadou, S., Thamsborg, S. M., & Hoskin, S. O. (2006). The effects of tannin-rich plants on parasitic nematodes in ruminants. Trends in Parasitology, 22(6), 253–261.

  • Hotez, P. J., Brindley, P. J., Bethony, J. M., King, C. H., Pearce, E. J., & Jacobson, J. (2008). Helminth infections: the great neglected tropical diseases. The Journal of Clinical Investigation, 18(4), 1311–1321.

    Article  Google Scholar 

  • Hudson, V. M., & den Boer, A. M. (2012). A feminist evolutionary analysis of the relationship between violence against and inequitable treatment of women, and conflict within and between human collectives, including nation-states. In T. K. Shackelford & V. A. Weekes-Shackelford (Eds.), The Oxford handbook of evolutionary perspectives on violence, homicide, and war (pp. 301–322). New York: Oxford University Press.

    Google Scholar 

  • Khan, T. O. (2013). Forest soils: Properties and management. Springer. doi:10.1007/978-3-319-02541-4

  • Keeley, L. H. (1997). War before civilization. New York: Oxford University Press.

    Google Scholar 

  • Krugman, P. (1991). Geography and trade. Cambridge: MIT Press.

    Google Scholar 

  • Krugman, P. (1998). What’s new about the new economic geography? Oxford Review of Economic Policy, 14, 7–17.

    Article  Google Scholar 

  • LABORSTA. (2015). http://laborsta.ilo.org/. Retrieved 2 January 2015.

  • LeBlanc, S. A., & Register, K. E. (2004). Constant battles: why we fight. New York: Macmillan.

    Google Scholar 

  • Leslie, S., Winney, B., Hellenthal, G., Davison, D., Boumertit, A., Day, T., et al. (2015). The fine-scale genetic structure of the British population. Nature, 519, 309–314.

  • Letendre, K., Fincher, C. L., & Thornhill, R. (2012). Parasite stress, collectivism, and human warfare. In T. Shackelford & V. Weekes-Shackelford (Eds.), The Oxford handbook of evolutionary perspectives on violence, homicide, and war (pp. 351–371). New York: Oxford University Press.

    Google Scholar 

  • Lisonbee, L. D., Villalba, J. J., Provenza, F. D., & Hall, J. O. (2009). Tannins and self-medication: implications for sustainable parasite control in herbivores. Behavioural Processes, 82(2), 184–189.

  • Low, B. S. (2003). Ecological and social complexities in human monogamy. In U. H. Reichard & C. Boesch (Eds.), Monogamy: mating strategies and partnerships in birds, humans and other mammals (pp. 161–176). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • Luc, M., Sikora, R. A., & Bridge, J. (Eds.). (2005). Plant parasitic nematodes in subtropical and tropical agriculture (2nd ed.). Oxford, UK: CABI Publishing.

    Google Scholar 

  • Lynn, R. (1991). The evolution of racial differences in intelligence. Mankind Quarterly, 32(1), 109.

  • Lynn, R. (2006). Race differences in intelligence: an evolutionary analysis. Augusta, GA: Washington Summit Publishers.

    Google Scholar 

  • Lynn, R., & Vanhanen, T. (2002). IQ and the wealth of nations. Westport: Praeger.

    Google Scholar 

  • Lynn, R., & Vanhanen, T. (2006). IQ and global inequality. Augusta, GA: Washington Summit Publishers.

    Google Scholar 

  • MacArthur, R. H., & Wilson, E. O. (1967). The theory of island biogeography. Princeton: Princeton University Press.

    Google Scholar 

  • Mace, R. (2000). Evolutionary ecology of human life history. Animal Behaviour, 59, 1–10.

    Article  PubMed  Google Scholar 

  • Marietta College. (2016). Marietta College Department of Biology and Environmental Science’s biomes of the world. http://w3.marietta.edu/∼biol/biomes/biome_main.htm. Retrieved 24 June 2016.

  • Marsh, W. M., & Kaufman, M. M. (2013). Physical geography: Great systems and global environments. New York: Cambridge University Press.

  • Martin, P. R., & McKay, J. K. (2004). Latitudinal variation in genetic divergence of populations and the potential for future speciation. Evolution, 58(5), 938–945.

  • Martínez-Cruz, B., Harmant, C., Platt, D. E., Haak, W., Manry, J., Ramos-Luis, E., et al. (2012). Evidence of pre-Roman tribal genetic structure in Basques from uniparentally inherited markers. Molecular Biology and Evolution, 29, 2211–2222.

  • Mather, M. E., Frank, H. J., Smith, J. M., Cormier, R. D., Muth, R. M., & Finn, J. T. (2012). Assessing freshwater habitat of adult anadromous alewives using multiple approaches. Marine and Coastal Fisheries, 4(1), 188–200.

    Article  Google Scholar 

  • McKnight, P. E., McKnight, K. M., Sidani, S., & Figueredo, A. J. (2007). Missing data: a gentle introduction. New York: Guilford.

    Google Scholar 

  • Meisenberg, G., & Woodley, M. A. (2013). Global behavioral variation: a test of differential-K. Personality & Individual Differences, 55, 273–278.

    Article  Google Scholar 

  • Miller, E. M. (1994a). Optimal adjustment of mating effort to environmental conditions: a critique of Chisholm’s application of life history theory, with comments on race differences in male paternal investment strategies. Mankind Quarterly, 34(4), 297–316.

    Google Scholar 

  • Miller, E. M. (1994b). Paternal provisioning versus mate seeking in human populations. Personality and Individual Differences, 17(2), 227–255.

    Article  Google Scholar 

  • Min, B. R., & Hart, S. P. (2003). Tannins for suppression of internal parasites. Journal of Animal Science, 81(14), E102–E109.

  • Moreno-Estrada, A., Gignoux, C. R., Fernández-López, J. C., Zakharia, F., Sikora, M., Contreras, A. V., et al. (2014). The genetics of Mexico recapitulates Native American substructure and affects biomedical traits. Science, 344(6189), 1280–1285.

  • Morin, X., Augspurger, C., & Chuine, I. (2007). Process‐based modeling of species’ distributions: what limits temperate tree species’ range boundaries? Ecology, 88(9), 2280–2291.

    Article  PubMed  Google Scholar 

  • Murray, D. R., & Schaller, M. (2010). Historical prevalence of infectious diseases within 230 geopolitical regions: a tool for investigating origins of culture. Journal of Cross-Cultural Psychology, 41, 99–108.

    Article  Google Scholar 

  • Novak, S., & Hatch, M. (2009). Intimate wounds: craniofacial trauma in women and female chimpanzees. In M. N. Muller & R. W. Wrangham (Eds.), Sexual coercion in primates and humans: an evolutionary perspective on male aggression against females. Cambridge: Harvard University Press.

    Google Scholar 

  • Nunn, C. L. (2011). The comparative approach in evolutionary anthropology and biology. Chicago: University of Chicago Press.

    Book  Google Scholar 

  • Pianka, E. R. (1970). On r and K selection. American Naturalist, 104, 592–597.

    Article  Google Scholar 

  • Piazza, A., Cappello, N., Olivetti, E., & Rendine, S. (1988). A genetic history of Italy. Annals of Human Genetics, 52, 203–213.

    Article  PubMed  Google Scholar 

  • Pollet, T. V., Tybur, J. M., Frankenhuis, W. E., & Rickard, I. J. (2014). What can cross-cultural correlations teach us about human nature? Human Nature, 25, 410–429.

    Article  PubMed  Google Scholar 

  • Popper, K. (1962). Conjectures and refutations: the growth of scientific knowledge. New York: Basic Books.

    Google Scholar 

  • Qi, X., Cui, C., Peng, Y., Zhang, X., Yang, Z., Zhong, H., et al. (2013). Genetic evidence of paleolithic colonization and neolithic expansion of modern humans on the Tibetan plateau. Molecular Biology and Evolution, 30, 1761–1778.

  • Ricardo, D. (1817). On the principles of political economy and taxation. London: John Murray, Albemarle-Street.

    Google Scholar 

  • Rindermann, H., Woodley, M. A., & Stratford, J. (2012). Haplogroups as evolutionary markers of cognitive ability. Intelligence, 40, 362–375.

    Article  Google Scholar 

  • Ruehle, J. L. (1973). Nematodes and forest trees—types of damage to tree roots. Annual Review of Phytopathology, 11(1), 99–118.

  • Rushton, J. P. (1985). Differential K theory: the sociobiology of individual and group differences. Personality and Individual Differences, 6, 441–452.

    Article  Google Scholar 

  • Salmon, C., Figueredo, A. J., & Woodburn, L. (2009). Life history strategy and disordered eating behavior. Evolutionary Psychology, 7, 585–600.

    Article  Google Scholar 

  • Smuts, B. (1992). Male aggression against women. Human Nature, 3(1), 1–44.

    Article  PubMed  Google Scholar 

  • Smuts, B. (1995). The evolutionary origins of patriarchy. Human Nature, 6(1), 1–32.

    Article  PubMed  Google Scholar 

  • Stearns, S. C. (1992). The evolution of life histories. Oxford: Oxford University Press.

    Google Scholar 

  • Sun, L. (2003). Monogamy correlates, socioecological factors, and mating systems in beavers. In U. H. Reichard & C. Boesch (Eds.), Monogamy: mating strategies and partnerships in birds, humans and other mammals (pp. 138–146). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • Svenning, J. C., & Skov, F. (2004). Limited filling of the potential range in European tree species. Ecology Letters, 7(7), 565–573.

    Article  Google Scholar 

  • Swift, L. W., Jr., & Messer, J. B. (1971). Forest cuttings raise temperatures of small streams in the southern Appalachians. Journal of Soil and Water Conservation, 26(3), 111–116.

  • The Institute for Economics and Peace 2014. (2015). 2014 Global peace index: measuring peace and assessing country risk. https://docs.google.com/spreadsheets/d/14Fl6gcIqOLE5HNZQgwOWOgt-Ag-wCRpeaid04B80JvA/edit#gid=0. Retrieved 2 January 2015.

  • The Observatory of Economic Complexity. (2015). The atlas of economic complexity 2010. http://atlas.cid.harvard.edu/about/glossary/. Retrieved 2 January 2015.

  • The Observatory of Economic Complexity. (2015). The atlas of economic complexity 2010. Glossary. https://atlas.media.mit.edu/atlas/. Retrieved 2 January 2015.

  • Thornhill, A. R., Fincher, C. L., & Aran, D. (2009). Parasites, democratization, and the liberalization of values across contemporary countries. Biological Reviews, 84, 113–131.

    Article  PubMed  Google Scholar 

  • United Nations Development Programme. (2015). Human development report 2010. http://hdr.undp.org/en/content/gender-inequality-index-gii. Retrieved 2 January 2015.

  • United Nations, Department of Economic and Social Affairs, Population Division (2015a). World population prospects: the 2012 revision, volume I: comprehensive tables ST/ESA/SER.A/336. http://esa.un.org/unpd/wpp/Excel-Data/population.htm. Retrieved 2 January 2015.

  • United Nations, Department of Economic and Social Affairs, Population Division (2015b). World population prospects: the 2012 revision, volume II: demographic profiles (ST/ESA/SER.A/345). http://esa.un.org/unpd/wpp/Excel-Data/population.htm. Retrieved 2 January 2015.

  • Van de Vliert, E. (2013). Climato-economic habitats support patterns of human needs, stresses, and freedoms. Behavioral and Brain Sciences, 36(5), pp. 465–480.

  • van Schaik, C. P., & Isler, K. (2012). Life-history evolution. In J. C. Mitani, J. Call, P. M. Kappeler, R. Palombit, & J. B. Silk (Eds.), The evolution of primate societies (pp. 220–244). Chicago: University of Chicago Press.

    Google Scholar 

  • Vanhanen, T. (2009). The limits of democratization: climate, intelligence, and resource distribution. Augusta, GA: Washington Summit Publishers.

    Google Scholar 

  • Villalba, J. J., Provenza, F. D., Hall, J. O., & Lisonbee, L. D. (2010). Selection of tannins by sheep in response to gastrointestinal nematode infection. Journal of Animal Science, 88(6), 2189–2198.

  • Weatherbase. (2015). www.weatherbase.com. Retrieved 2 January 2015.

  • Wenner, C. J., Bianchi, J., Figueredo, A. J., Rushton, J. P., & Jacobs, W. J. (2013). Life history theory and social deviance: the mediating role of executive function. Intelligence, 41, 102–113.

    Article  Google Scholar 

  • Wertheim, H. F. L., Horby, P., & Woodall, J. P. (2012). Atlas of human infectious diseases. Hoboken: Wiley-Blackwell.

    Book  Google Scholar 

  • Wikipedia. (2015a). List of countries by average elevation. https://en.wikipedia.org/wiki/List_of_countries_by_average_elevation. Retrieved 2 January 2015.

  • Wikipedia. (2015b). List of countries by latitude. https://en.wikipedia.org/wiki/List_of_countries_by_latitude. Retrieved 2 January 2015.

  • Wikipedia (2016). Biome. https://en.wikipedia.org/wiki/Biome. Retrieved 24 June 2016.

  • Williams, G. C. (1957). Pleiotropy, natural selection, and the evolution of senescence. Evolution, 11, 398–411.

    Article  Google Scholar 

  • Wilson, K. B., Hanson, P. J., Mulholland, P. J., Baldocchi, D. D., & Wullschleger, S. D. (2001). A comparison of methods for determining forest evapotranspiration and its components: sap-flow, soil water budget, eddy covariance and catchment water balance. Agricultural and Forest Meteorology, 106(2), 153–168.

  • Woodley, M. A. (2011). The cognitive differentiation-integration effort hypothesis: a synthesis between the fitness indicator and life history models of human intelligence. Review of General Psychology, 15, 228–245.

    Article  Google Scholar 

  • Woodley, M. A., & Fernandes, H. B. (2014). Strategic and cognitive differentiation–integration effort in a study of 76 countries. Personality and Individual Differences, 57, 3–7.

    Article  Google Scholar 

  • Woodley, M. A. & Figueredo, A. J. (2013). Historical variability in heritable general intelligence: Its evolutionary origins and socio-cultural consequences. Buckingham, UK: University of Buckingham Press.

  • Woodley, M. A., Figueredo, A. J., Brown, S. D., & Ross, K. C. (2013). Four successful tests of the cognitive differentiation–integration effort hypothesis. Intelligence, 41, 832–842.

    Article  Google Scholar 

  • Woodward, S. L. (2016) Biomes of the world. https://php.radford.edu/~swoodwar/biomes/?page_id=94. Retrieved August 2 2016.

  • World Bank 2014. (2015). http://data.worldbank.org/indicator/SP.ADO.TFRT. Retrieved 2 January 2015.

  • World Economic Forum. (2009a). The global gender gap report 2009. http://www3.weforum.org/docs/WEF_GenderGap_Report_2009.pdf. Retrieved 2 November 2009.

  • World Economic Forum. (2009b). The global gender gap report 2013. http://www3.weforum.org/docs/WEF_GenderGap_Report_2013.pdf. Retrieved 2 November 2009.

  • CIA World Factbook 2006 (2015). https://www.cia.gov/library/publications/download/download-2006. Retrieved 2 January 2015.

  • World Health Organization. (2015). World Health Organization (2014) DALY estimates, 2000–2012. http://www.who.int/healthinfo/global_burden_disease/estimates/en/index2.html. Retrieved 2 January 2015.

  • World Wildlife Federation—Discover Boreal and Temperate Forests (2016). Boreal & temperate forests. http://wwf.panda.org/about_our_earth/deforestation/importance_forests/boreal_temperate_forests/. Retrieved 24 June 2016.

  • Wrangham, R. W., Wilson, M. L., & Muller, M. N. (2006). Comparative rates of violence in chimpanzees and humans. Primates, 47(1), 14–26.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Psychology, University of Arizona, Tucson, AZ, USA

    Aurelio José Figueredo, Candace Jasmine Black & Rafael Antonio García

  2. Department of Psychology, School of Mind, Brain, and Behavior, College of Science, University of Arizona, Tucson, AZ, USA

    Aurelio José Figueredo

  3. Health Psychology, Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA

    Tomás Cabeza de Baca

  4. Department of Psychology, University of Arizona, Tucson, AZ, USA

    Heitor Barcellos Ferreira Fernandes

  5. Department of Psychology, University of New Brunswik, Fredericton, NB, Canada

    Mateo Peñaherrera

  6. Psychology Department, College of New Rochelle, New Rochelle, NY, USA

    Steven Hertler

  7. Department of Biochemistry, Ross University, Iselin, NJ, USA

    Gerhard Meisenberg

  8. Center Leo Apostel for Interdisciplinary Studies, Vrije Universiteit Brussel, Brussels, Belgium

    Michael Anthony Woodley of Menie

Authors
  1. Aurelio José Figueredo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tomás Cabeza de Baca
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Heitor Barcellos Ferreira Fernandes
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Candace Jasmine Black
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mateo Peñaherrera
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Steven Hertler
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rafael Antonio García
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Gerhard Meisenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Michael Anthony Woodley of Menie
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aurelio José Figueredo.

Appendices

Appendix 1: Measurement Model Specification

SAS 9.3 was utilized to construct the unit-weighted factors and estimate all bivariate Pearson’s product–moment correlation coefficients. All common factor scores were estimated using SAS PROC STANDARD and DATA by simple unit weighting (Gorsuch 1983): (1) All subscale scores were estimated as the means of the standardized scores for all non-missing items on each subscale and (2) all scale scores were estimated as the means of the standardized scores for all non-missing subscales on each scale (Figueredo et al. 2000; McKnight et al. 2007).

For efficiency of presentation, the description of the indicators used in these analyses is supplemented with the factor structure tables showing the unit-weighted loadings (see Appendix Table 2) of each set of indicators from its latent common factor, operationalized as part–whole correlations, each serving as convergent validity coefficients among the indicators (Gorsuch 1983). All but certain cognitive ecology factors were estimated using indicators dating from AD 2001 to 2015.

Measures of Physical Ecology

Mean national latitudes and elevations were obtained from Wikipedia (2015a, b). The primary data source for annual mean national humidities and temperatures was Climate Charts (2015), with some missing data imputed for mean annual temperatures from Weatherbase (2015). Based on these basic parameters:

  1. 1.

    A brumal factor was operationalized as the latent common factor indicated by a unit-weighted composite of lower mean annual temperatures, proportion of area of temperate climate, and a composite of latitude above the equator and altitude above sea level for each national polity, where this “Boreal Index” was calculated by the following formula from quantitative physical ecology:

Boreal Index = (Absolute Latitude/333, 000 m) + Altitude above Sea Level)/482, 803 m)

  1. 2.

    A hydrological factor was operationalized as the latent common factor indicated by a unit-weighted composite of the proportion of area of tropical-humid climate and the annual precipitation for each national polity.

Measures of Community Ecology

Temperate Broadleaf Deciduous Forest Biome (TBDF)

Three global biome maps with national boundaries were visually analyzed: (1) biome map (Wikipedia 2016); (2) map of biomes around the world (World Wildlife Federation—Discover Boreal and Temperate Forests 2016); and map of temperate forests (Marietta College 2016). Borders were matched against variously available regional and world maps for the biome maps with superimposed national boundaries wherein no nations were labeled. A Likert scale numerical coding scheme was adopted to facilitate quantitative analysis: assigning a 0, 1, 2, or 3, denoting no, some, most, or all TBDF coverage, respectively. These three maps had sufficient resolution to allow definite classification in all but 11 of 198 (66 countries × 3 maps) instances. Poor resolution or intersecting coordinate grids introduced uncertainty for Bulgaria, Japan, India, Turkey, and Croatia, but coding uncertainties recurred across maps only in the cases of Slovenia, Switzerland, and Austria. Nevertheless, at least one map proved definitive even in these three cases. A unit-weighted factor was constructed from these three convergent estimates, in which the three maps thus functioned as checks on one another, both within countries and for subtle globally mapped TBDF range variation.

Parasite Burden

The per capita disability-adjusted life years (DALY) for each national polity was obtained from the World Health Organization Site (2015). Historical infectious disease prevalences for each national polity were obtained from Murray and Schaller (2010). The logarithm of the unit-weighted composite of these two indicators was used for the analyses, consistent with the predictions of population biology.

Measures of Social Ecology

Population density was estimated for each national polity by dividing the total population of each country by its total land area, as obtained from the CIA World Factbook (2006). The logarithm of the calculated population density was used for the analyses, consistent with the predictions of population biology.

Slow life history strategy (adjusted) was operationalized as the latent common factor indicated by a unit-weighted composite of the following five sociodemographic indicators:

  1. 1.

    Infant mortality (CIA World Factbook 2006), statistically adjusted for the specific effects of parasite burden, functions as an indicator of age-specific social and environmental harshness, which has been argued to represent a central force in the evolution of life history strategies (see Ellis et al. 2009).

  2. 2.

    Life expectancy (or longevity; CIA World Factbook 2006), statistically adjusted for the specific effects of parasite burden, has been argued to represent an intrinsic component of life history as it is related to morbidity–mortality and also reflects investments in somatic effort (e.g., Charnov 1991; van Schaik and Isler 2012; Williams 1957), being thus related to covitality (Figueredo et al. 2004, 2007).

  3. 3.

    Birth rate (CIA World Factbook 2006) functions as a measure of fertility, and thus mating effort. As such, it represents an important indicator of the well-known life history trade-off between mating and parental effort (MacArthur and Wilson 1967).

  4. 4.

    Teenage birth rate (or adolescent fertility rate; World Bank 2014) is the number of births per 1000 women aged 15–19 years. In addition to measuring fertility, teenage birth rate represents early investments in mating effort, and it is well known that this is intrinsically related to the overall life history speed (van Schaik and Isler 2012; Stearns 1992).

  5. 5.

    Operational sex ratio (tertiary OSR or adult sex ratio; United Nations, Department of Economic and Social Affairs, Population Division 2015a, b) is the number of males per 100 females in the population of reproductive age.

Social equality was operationalized as the latent common factor indicated by a unit-weighted composite of the following two socioeconomic indicators:

  1. 1.

    The GINI coefficient (Gini 1912; World Bank 2014) is intended to represent the income distribution of a nation’s residents and is the most commonly used measure of inequality. A low GINI represents a nation with a more equal income distribution.

  2. 2.

    The Power Resources Index (Vanhanen 2009; Finnish Social Science Data Archive 2015) is calculated by multiplying the Index of Occupational Diversification, the Index of Knowledge Distribution, and the Index of the Distribution of Economic Power Resources and then dividing the product by 10,000.

Within-group peace, indicating lower rates of conflict among individuals, was measured by a unit-weighted composite of the perceived crime rate, the homicide rate, the violent crime rate, the civilian access to weapons, and the perceived corruption rate (The Institute for Economics and Peace 2015).

Between-group peace was operationalized as the higher-order factor measured by a unit-weighted composite of the infra-national peace and the inter-national peace factors:

  1. 1.

    Infra-national peace, indicating lower rates of conflict among subnational polities, was measured by a unit-weighted composite of internal conflict, violent demonstrations, political instability, political terror, and internal conflict deaths rate (The Institute for Economics and Peace 2015).

  2. 2.

    Inter-national peace, indicating lower rates of conflict among national polities, was measured by a unit-weighted composite of military expenditures, armed personnel, heavy weapons, bad relations with neighbors, conflicts fought, external conflict deaths, hostility to foreigners, and willingness to fight in war (The Institute for Economics and Peace 2015).

Sexual equality was operationalized as the latent common factor indicated by a unit-weighted composite of the Gender Gap Index and the Gender Inequality Index for each national polity:

  1. 1.

    The Gender Gap Index (World Economic Forum 2009a, b) assesses how resources and opportunities are divided between male and female individuals within each national polity, as indicated by the four areas of economic participation and opportunity, educational attainment, political empowerment, and health and survival.

  2. 2.

    The Gender Inequality Index (United Nations Development Programme 2010, Human Development Report) is a composite measure estimating the loss of collective achievement within each national polity due to gender inequality, as indicated by the three dimensions of reproductive health, empowerment, and labor market participation.

Strategic differentiation (Figueredo et al. 2001) estimates the degree of diversification of resource allocation profiles among slower life history strategists within each national polity, operationalized as the effects of aggregate life history speed upon the CPEM-derived (see Gorsuch 2005) unit-weighted factor loadings of low birth rate, low teen pregnancy, low infant mortality, higher operational sex ratios, and higher life expectancies.

Measures of Cultural Ecology

Macroeconomic diversification was operationalized as the latent common factor measured by a unit-weighted composite of the Economic Complexity Index, the reverse-scored GDP Dissimilarity Index, and the reverse-scored Krugman Dissimilarity Index for each national polity. Operational definitions for each of these three macroeconomic indices were obtained from the Glossary of The Atlas of Economic Complexity 2010 (The Observatory of Economic Complexity 2015a, b) and from Goschin et al. (2009):

  1. 1.

    Economic Complexity Index (ECI; Hidalgo and Hausmann 2009; The Observatory of Economic Complexity 2015a, b) measures the internal economic differentiation, and hence the higher inter-individual specialization, within national polities, as assessed by the diversity of their exports to other polities.

  2. 2.

    GDP Dissimilarity Index (GDP-DI, based on the KDI; Krugman 1991, 1998) measures the dissimilarities between national polities in their relative distributions of their total GDPs among various macroeconomic sectors, and hence lower diversification of goods and services production within each of the national polities. GDP data were obtained for each national polity from the CIA World Factbook (2013), the World Bank (2014), and the Countries of the World (2015).

  3. 3.

    Krugman Dissimilarity Index (KDI; Krugman 1991, 1998) measures the dissimilarities between national polities in their relative labor force distributions among various macroeconomic sectors, and hence lower inter-individual occupational diversification within each of the national polities. KDI data were obtained for each national polity from the CIA World Factbook (2013) and the World Bank (2014).

Human capital factor was operationalized as the latent common factor indicated by a unit-weighted composite of three macroeconomic indicators within each national polity. Operational definitions for the construct of human capital were obtained from Bourdieu (1986):

  1. 1.

    Gross domestic savings rates (1975–2005 average; World Bank 2014) were calculated for each national polity as gross national income less total consumption, plus net transfers. Missing data were imputed from LABORSTA (2015).

  2. 2.

    Educational levels (1950–2010 average) for each national polity were obtained from Barro and Lee (2013). Missing data were imputed from the World Bank (2014).

  3. 3.

    Gross domestic products (1985–2005 average) or the GDPs for each national polity were obtained from Heston et al. (2011).

Measures of Cognitive Ecology

Mean brain volumes for each national polity were obtained from Beals et al. (1984). Measurements were conducted by use of mechanical packing with mustard seeds. Male and female brain sizes were averaged for each national polity.

Cognitive abilities data were obtained from Lynn and Vanhanen (2006), which is an updated and expanded edition of Lynn and Vanhanen (2002). National mean aggregate IQs were most often measured with Raven’s progressive matrices, a non-verbal reasoning test, and for some countries, a variety of other tests were employed. None of the missing values imputed by Lynn and Vanhanen for national IQs were employed in the present analysis.

Table 2 Measurement models: indicators of latent common factors
Full size table

Appendix 2: Structural Model Specification

We utilized SEQCA to model a theoretically specified cascade model of effects using Unimult 2 statistical software (UM2; Gorsuch 2016). The sequence of criterion variables for the present study was theoretically specified as follows:

  1. 1.

    Temperate Broadleaf Deciduous Forest = β 31*Brumal + β 32*Hydrological + β 33*Brumal*Hydrological

  2. 2.

    Log(Parasite Burden) = β 41*Temperate Broadleaf Deciduous Forest + β 42*Brumal + β 43*Hydrological + β 44*Brumal*Hydrological

  3. 3.

    Log(Population Density) = β 51*Log(Parasite Burden) + β 52*Temperate Broadleaf Deciduous Forest + β 53*Brumal + β 54*Hydrological + β 55*Brumal*Hydrological

  4. 4.

    Slow Life History Strategy = β 61*Log(Population Density) + β 62*Log(Parasite Burden) + β 63*Temperate Broadleaf Deciduous Forest + β 64*Brumal + β 65*Hydrological + β 66*Brumal*Hydrological

  5. 5.

    Social Equality = β 71*Slow Life History Strategy + β 72*Log(Population Density) + β 73*Log(Parasite Burden) + β 74*Temperate Broadleaf Deciduous Forest + β 75*Brumal + β 76*Hydrological + β 77*Brumal*Hydrological

  6. 6.

    Within-Group Peace = β 81*Social Equality + β 82*Slow Life History Strategy + β 83*Log(Population Density) + β 84*Log(Parasite Burden) + β 85*Temperate Broadleaf Deciduous Forest + β 86*Brumal + β 87*Hydrological + β 88*Brumal*Hydrological

  7. 7.

    Between-Group Peace = β 91*Within-Group Peace + β 92*Social Equality + β 93*Slow Life History Strategy + β 94*Log(Population Density) + β 95*Log(Parasite Burden) + β 96*Temperate Broadleaf Deciduous Forest + β 97*Brumal + β 98*Hydrological + β 99*Brumal*Hydrological

  8. 8.

    Sexual Equality = β 101*Between-Group Peace + β 102*Within-Group Peace + β 103*Social Equality + β 104*Slow Life History Strategy + β 105*Log(Population Density) + β 106*Log(Parasite Burden) + β 107*Temperate Broadleaf Deciduous Forest + β 108*Brumal + β 109*Hydrological + β 1010*Brumal*Hydrological

  9. 9.

    Strategic Differentiation = β 111*Sexual Equality + β 122*Between-Group Peace + β 113*Within-Group Peace + β 114*Social Equality + β 115*Slow Life History Strategy + β 116*Log(Population Density) + β 117*Log(Parasite Burden) + β 118*Temperate Broadleaf Deciduous Forest + β 119*Brumal + β 1110*Hydrological + β 1111*Brumal*Hydrological

  10. 10.

    Macroeconomic Diversification = β 121*Strategic Differentiation + β 122*Sexual Equality + β 123*Between-Group Peace + β 124*Within-Group Peace + β 125*Social Equality + β 126*Slow Life History Strategy + β 127*Log(Population Density) + β 128*Log(Parasite Burden) + β 129*Temperate Broadleaf Deciduous Forest + β 1210*Brumal + β 1211*Hydrological + β 1212*Brumal*Hydrological

  11. 11.

    Human Capital = β 121*Macroeconomic Diversification + β 132*Strategic Differentiation + β 133*Sexual Equality + β 134*Between-Group Peace + β 135*Within-Group Peace + β 136*Social Equality + β 137*Slow Life History Strategy + β 138*Log(Population Density) + β 139*Log(Parasite Burden) + β 1310*Temperate Broadleaf Deciduous Forest + β 1311*Brumal + β 1312*Hydrological + β 1313*Brumal*Hydrological

  12. 12.

    Mean Brain Volume = β 141*Human Capital + β 142*Macroeconomic Diversification + β 143*Strategic Differentiation + β 144*Sexual Equality + β 145*Between-Group Peace + β 146*Within-Group Peace + β 147*Social Equality + β 148*Slow Life History Strategy + β 149*Log(Population Density) + β 1410*Log(Parasite Burden) + β 1411*Temperate Broadleaf Deciduous Forest + β 1412*Brumal + β 1413*Hydrological + β 1414*Brumal*Hydrological

  13. 13.

    Mean Aggregate IQ = β 151*Mean Brain Volume + β 152*Human Capital + β 153*Macroeconomic Diversification + β 154*Strategic Differentiation + β 155*Sexual Equality + β 156*Between-Group Peace + β 157*Within-Group Peace + β 158*Social Equality + β 159*Slow Life History Strategy + β 1510*Log(Population Density) + β 1511*Log(Parasite Burden) + β 1512*Temperate Broadleaf Deciduous Forest + β 1513*Brumal + β 1514*Hydrological + β 1515*Brumal*Hydrological

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Figueredo, A.J., Cabeza de Baca, T., Fernandes, H.B.F. et al. A Sequential Canonical Cascade Model of Social Biogeography: Plants, Parasites, and People. Evolutionary Psychological Science 3, 40–61 (2017). https://doi.org/10.1007/s40806-016-0073-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40806-016-0073-5

Keywords

Search

Navigation