that the role of consciousness as an evolutionary factor is increasing. One of the megatrends of evolution is the growth of complexity. Eric Chaisson's model of free energy rate density is a quantitative criterion stating that the more complexly organized a system is, the higher is the ratio of energy per unit time to its own mass (Chaisson 2001). Under that logic, the brain is the most complex entity that has been created by biological evolution without technological interference, because of the number of connections between neurons, and all further development and growth of complexity is associated with the creation of the anthro-posphere (a peculiar realm of the Earth's spheres, which is created and changed by humans).

At the beginning of the last century, Russian cosmists Nikolay Fyodorov and Konstantin Tsiolkovsky wrote about the possibility of the transformation of consciousness into the factor of cosmic evolution. According to Fyodorov, chaos dominates in the Universe, and it can be overcome by bringing people together to cope with global challenges. In other words, overcoming of chaos involves scientific management of nature and space exploration (Fyodorov 1982[1903]). Tsiolkovsky (2001[1903]) introduced the idea of human settlement of outer space and developed the first spacecraft project.

Chaisson claims that humanity that has become a powerful evolutionary factor on the planet is on the verge of becoming a significant factor in the evolution of the Universe in general. Thus, he concludes that ‘we have an obligation, a moral responsibility to survive, especially if we are alone in the Universe’ (Chaisson 2005: 101).

Nazaretyan comes to a similar conclusion, arguing that ‘for the creative mind, there are no absolute limits for the mass and energy process control and the potential prospect of its development is associated with an expanding influence on cosmic evolution’. He also argues that physical laws cannot constrain the engineering creativity (Nazaretyan 2009: 12). Less optimistically, Fred Spier thinks that ‘if biological evolution continues in the same direction in which it took place over the past billions of years, our species can disappear very soon ... if we as a species can survive longer, it is only thanks to our extremely developed intelligence’ (Spier 2010: 93). According to him, the ability of human mind to influence rising complexity is limited by the extent of the Earth and near-Earth space, because interplanetary travels require prohibitive expenses. Flights to other planetary systems are impossible, because they would take centuries, and traveling faster than the speed of light contradicts the common-known laws of physics (Ibid.: 93).
The opinions of the interviewees can be classified in four general forecast scenarios. According to the first one, there will be a complete change of civilization (a transition to a new stage of evolution, some changes in the political world system and so on). The second scenario presupposes the beginning of a descending stage of evolution (the general deterioration of living conditions, the fragmentation of society). The third scenario predicts the probable extinction of humans and of most life forms. And there is a fourth scenario advocated by Andrey Korotayev according to which, the World System is now escaping the blow-up regime in which it has been developing over the recent centuries, and this makes it probable that by the mid-twenty-second century, the World System complexity will more or less stabilize at a certain level at least for a few centuries. This scenario implies that it is not in the future that we will witness a complete change of civilization, but it is already happening (e.g., Korotayev 2010). Note that all the positive scenarios imply the necessity to regulate global processes.

The attempts to regulate global processes are unprecedented; until the twentieth century nobody had ever tried them. And at the present stage of social evolution, there exist supranational structures that can serve the basis for global governance. But they have a long way to go.

## References

**Chaisson E. 2001.** *The Rise of Complexity in Nature*. Cambridge, MA: Harvard University Press.

**Chaisson E. 2005.** *Cosmic Evolution: Synthesizing Evolution, Energy and Ethics*. *Filosofskiye nauki* 5: 92–104.

**Fyodorov N. F. 1982.** *Works*. Moscow: Nauka. In Russian (Федоров Н. Ф. *Сочинения*. М.: Наука).

**Huntington S. 1993.** *The Clash of Civilizations: And the Remaking of World Order*. New York, NY: Simon and Shuster.

**Korotayev A. V. 2010.** New Technologies and Scenarios of Future, Is the Singularity Near? *History and Complexity Studies* / Ed. by S. Malkov and A. Korotayev, pp. 183–191. Moscow: Librokom/URSS, pp. 183–191. In Russian (Коротаев А. В. Новые технологии и сценарии будущего, или сингулярность уже рядом? *История и синергетика* / Ред. С. Ю. Малков, А. В. Коротаев, с. 183–191. М.: Либроком/УРСС).

**Kurzweil R. 2005.** *The Singularity is Near: When Humans Transcend Biology*. New York, NY: Penguin Group.

**Nazaretyan A. P. 2008.** *Civilization Crises within the Context of Big (Universal) History: Self-Organization, Psychology, and Futurology*. Moscow: PerSe.
*In Russian* (Назаретян А. П. Цивилизационные кризисы в контексте Универсальной Истории: самоорганизация, психология и футурология. М.: Пер СЭ).

**Nazaretyan A. P. 2009.** Meaning FORMATION AS A GLOBAL ISSUE OF OUR TIME: THE SYNERGISTIC VIEW. *Voprosy filosofii* 5: 3–18. *In Russian* (Назаретян А. П. Смыслообразование как глобальная проблема современности: синергетический взгляд. Вопросы философии 5: 3–18).

Panov A. D. 2005. The Completion of the Planetary Cycle of Evolution. *Filosofskiye nauki* 5: 42–49. In Russian (Панов А. Д. Завершение планетарного цикла эволюции. Философские науки 5: 42–49).

Snooks G. D. 1996. *The Dynamic Society: Exploring the Source of Global Change*. London: Routledge.

Snooks G. D. 2005. Why is History Getting Faster? Measurement and Explanation. *Filosofskiye nauki* 4: 51–68.

Spier F. 2010. *Do Cosmic Perspectives Await the Civilization of the Earth?* (about the book by F. Spier ‘Big History and the Future of Humanity’). *Istoricheskaya psikhologiya i sotsiologiya istorii* 2: 92–97. In *Russian* (Спир Ф. Ожидают ли цивилизацию Земли космические перспективы? [о книге Ф. Спира «Универсальная история и будущее человечества»]. *Историческая психология и социология истории* 2: 92–97).

Tsiolkovsky K. E. 2001. *Cosmic Philosophy*. Moscow: Editorial URSS. In *Russian* (Циолковский К. Э. Космическая философия. М.: УРСС).
Appendix 1

List of articles from the *Journal of Globalization Studies*
used for our content analysis

**Ardalan K. 2010.** Globalization and Finance: Four Paradigmatic Views. *Journal of Globalization Studies* 1(2): 41–67.

**Dreher A., Gaston N., Martens P., and van Boxem L. 2010.** Measuring Globalization – Opening the Black Box. A Critical Analysis of Globalization Indices. *Journal of Globalization Studies* 1(1): 166–185.

**Eisenstadt S. 2010.** Contemporary Globalization and New Civilizational Formations. *Journal of Globalization Studies* 1(2): 3–11.

**Grinin L., and Korotayev A. 2010.** Will the Global Crises Lead to Global Transformations? 1. The Global Financial System: Pros and Cons. *Journal of Globalization Studies* 1(1): 70–89.

**Grinin L., and Korotayev A. 2010.** Will the Global Crises Lead to Global Transformations? 2. The Coming Epoch of New Coalitions. *Journal of Globalization Studies* 1(2): 166–183.

**Heshmati A., and Lee S. 2010.** The Relationship between Globalization, Economic Growth and Income Inequality. *Journal of Globalization Studies* 1(2): 87–116.

**Klimenko V., and Tereshin A. 2010.** World Energy and Climate in the Twenty-First Century in the Context of Historical Trends: Clear Constraints to the Future Growth. *Journal of Globalization Studies* 1(2): 27–40.

**Nazaretyan A. 2010.** Life's Meaning as a Global Problem of Modernity: A View from Big History and Complexity Studies Perspective. *Journal of Globalization Studies* 1(2): 147–165.

**Özbudun S. 2010.** (Re)Connecting Global and Local Anthropologies – Minutes from a Panel. *Journal of Globalization Studies* 1(2): 190–194.

**Reuveny R. 2010.** On Free Trade, Climate Change, and the WTO. *Journal of Globalization Studies* 1(1): 90–103.

**Rockmore T. 2010.** Social Contradiction, Globalization and 9/11. *Journal of Globalization Studies* 1(1): 58–69.

**Rodrigue B. H., and Stasko D. J. 2010.** Changing the Future with the Past: Global Enlightenment through Big History. *Journal of Globalization Studies* 1(2): 128–146.

**Tausch A. 2010.** Towards Yet Another Age of Creative Destruction? *Journal of Globalization Studies* 1(1): 104–130.

**Thompson W. 2010.** The Lead Economy Sequence in World Politics (From Sung China to the United States): Selected Counterfactuals. *Journal of Globalization Studies* 1(1): 6–28.
**Vásquez W. 2010.** Fiscal Composition and Economic Growth in Central America under Global Economic Liberalization. *Journal of Globalization Studies* 1(2): 68–86.

**Yanling X. 2010.** A Multidimensional Perspective of the Antiglobalization and Alterglobalization Trend of Thought. *Journal of Globalization Studies* 1(1): 150–165.

**Yeoman I. 2010.** Tomorrow's Tourist: Fluid and Simple Identities. *Journal of Globalization Studies* 1(2): 118–127.

## Appendix 2

### List of articles from Vek globalizatsii used for our content analysis

**Abylgaziev I. I., and Ilyin I. V. 2009.** Processes of Globalization and the Problem of the New World Order). *Vek globalizatsii* 2: 40–60. *In Russian* (Абългазиев И. И., Ильин И. В. Процессы глобализации и проблема нового мироустройства. *Век глобализации* 2: 40–60).

**Akaev A. A., and Akaeva B. A. 2011.** Challenges of Global Demographic Transition and the Urgency of Strategic Decisions. *Vek globalizatsii* 1: 44–66. *In Russian* (Акаев А. А., Акаева Б. А. Вызовы глобального демографического перехода и неотложность стратегических решений. *Век глобализации* 1: 44–66).

**Akaev A. A., and Sadovnichiy V. A. 2009.** On the Dynamics of the World-Economic Development in the Light of the New Forecasting Approach. *Vek globalizatsii* 2: 3–16. *In Russian* (Акаев А. А., Садовничий В. А. О динамике мирохозяйственного развития в свете нового подхода к прогнозированию. *Век глобализации* 2: 3–16).

**Aleshkovsky I. A. 2011.** The Trends of International Migration in Modern Russia in the Context of Globalization. *Vek globalizatsii* 1: 159–181. *In Russian* (Алешковский И. А. Тенденции международной миграции населения в современной России в условиях глобализации. *Век глобализации* 1: 159–181).

**Aleshkovsky I. A., and Iontsev V. A. 2008.** The Trends of World Migration in the Globalized World. *Vek globalizatsii* 2: 77–87. *In Russian* (Алешковский И. А., Ионцев В. А. Тенденции международной миграции в глобализирующемся мире. *Век глобализации* 2: 77–87).

**Astvatsaturov A. E., Basilaia M. A. 2009.** Globalization and the Elements of Cosmocharmony. *Vek globalizatsii* 2: 71–80. *In Russian* (Аствацатуров А. Е., Басилаia М. А. Глобализация и начала космогармонии. *Век глобализации* 2: 71–80).

**Berger Y. M. 2009.** Chinese Model of Globalization. *Vek globalizatsii* 1: 91–97. *In Russian* (Бергер Я. М. Китайская модель глобализации. *Век глобализации* 1: 91–97).

**Buryanov S. A. 2009.** Freedom of Conscience as a Global Value. On the Way to Political Unity and the Solving of Global Problems. *Vek globalizatsii* 1: 133–
151. *In Russian* (Бурьянов С. А. Свобода совести как глобальная ценность. На пути к политическому единству и решению глобальных проблем. *Век глобализации* 1: 133–151).

Chesnokov V. S. 2010. S. A. Podolinsky: The Concept of Social Energy. *Vek globalizatsii* 2: 181–187. In Russian (Чесноков В. С. С. А. Подолинский: концепция социальной энергетики. *Век глобализации* 2: 181–187).

Chumakov A. N. 2008. The Modern World: On the Threshold of Fundamental Transformations. *Vek globalizatsii* 2: 88–94. In Russian (Чумаков А. Н. Современный мир: на пороге фундаментальных трансформаций. *Век глобализации* 2: 88–94).

Chumakov A. N. 2010. Global World: The Problem of Governance. *Vek globalizatsii* 2: 3–15. In Russian (Чумаков А. Н. Глобальный мир: проблема управления. *Век глобализации* 2: 3–15).

Danilov-Danilyan V. I. 2008. Global Problem of the Sweet Water Shortage. *Vek globalizatsii* 1: 45–56. In Russian (Данилов-Данильян В. И. Глобальная проблема дефицита пресной воды. *Век глобализации* 1: 45–56).

Denisov S. A. 2010. The Retreat of ‘the Third Wave’ of Democratization in the World. *Vek globalizatsii* 1: 173–186. In Russian (Денисов С. А. Отступление «третьяй волны» демократизации в мире. *Век глобализации* 1: 173–186).

Djozhkin V. V., Snakin V. V., and Popova L. V. 2008. Regenerative Natural Management – the Basis of Sustainable Development. *Vek globalizatsii* 2: 95–113. In Russian (Дёжкин В. В., Снакин В. В., Попова Л. В. Восстановительное природопользование – основа устойчивого развития. *Век глобализации* 2: 95–113).

Dobrovolsky G. V. 2008. Soil Degeneration – a Danger of Global Ecological Crisis. *Vek globalizatsii* 2: 54–65. In Russian (Добровольский Г. В. Деградация почв – угроза глобального экологического кризиса. *Век глобализации* 2: 54–65).

Ecimovic T. 2011. The Corporate and Individual Social Responsibility (C&ISR) as a Part of the Sustainable Future of Humankind. *Vek globalizatsii* 1: 95–109. In Russian (Ечимович Т. Корпоративная и индивидуальная социальная ответственность как составляющие устойчивого будущего развития. *Век глобализации* 1: 95–109).

Fedotova M. A. 2010. Venture Capital Investment as the Fundamental Factor of Innovative Development. *Vek globalizatsii* 2: 115–126. In Russian (Федотова М. А. Венчурное инвестирование как основополагающий фактор инновационного развития. *Век глобализации* 2: 115–126).

Gadzhieva V. 2010. Global Crisis: Causes, Directions and Solutions. *Vek globalizatsii* 1: 106–110. In Russian (Гаджиева В. Глобальный кризис: причины, направления, пути решения. *Век глобализации* 1: 106–110).

Global systemic crisis, and model of the world. 2009. *Vek globalizatsii* 1: 55–62. In Russian (Глобально-системный кризис и модели мироустройства (круглый стол) *Век глобализации* 1: 55–62).
**Gorelov A. A. 2009.** Globalization as an Objective Trend of World Development. *Vek globalizatsii* 1: 79-90. *In Russian* (Горелов А. А. Глобализация как объективная тенденция мирового развития. Век глобализации* 1: 79-90).

**Grinin L. E. 2008.** Globalization and the Transformation Processes of National Sovereignty. *Vek globalizatsii* 1: 86-97. *In Russian* (Гринин Л. Е. Глобализация и процессы трансформации национального суверенитета. Век глобализации* 1: 86-97).

**Grinin L. E. 2008.** Unwanted Child of Globalization. Notes on the Crisis. *Vek globalizatsii* 2: 46-53. *In Russian* (Гринин Л. Е. Нежеланное дитя глобализации. Век глобализации* 2: 46-53).

**Grinin L. E. 2009.** Will Global Crisis Lead to Global Transformations? *Vek globalizatsii* 2: 117-140. *In Russian* (Гринин Л. Е. Приведет ли глобальный кризис к глобальным изменениям? Век глобализации* 2: 117-140).

**Grinin L. E. 2011.** The Origins of Globalization: The World-System Analysis. *Vek globalizatsii* 1: 80-94. *In Russian* (Гринин Л. Е. Истоки цивилизации: мирсистемный анализ. Век глобализации* 1: 80-94).

**Grubets M. 2010.** The Presuppositions of the Intercultural Dialogue on Human Rights. *Vek globalizatsii* 1: 126-144. *In Russian* (Грубец М. Предпосылки межкультурного диалога о правах человека. Век глобализации* 1: 126-144).

**Gurevich P. S. 2009.** Russia's Image in the Process of Globalization. *Vek globalizatsii* 2: 178-191. *In Russian* (Гуревич П. С. Имидж России в процессе глобализации. Век глобализации* 2: 178-191).

**Gurevich P. S. 2010.** Kibерnavt as a Symbol of Global World. *Vek globalizatsii* 2: 139-153. *In Russian* (Гуревич П. С. Кибернавт как символ глобального мира. Век глобализации* 2: 139-153).

**Intellectual Capital as the Most Important Factor of the Economic Development:** Interview with M. A. Eskanderov. 2010. *Vek globalizatsii* 1: 39-44. *In Russian* (Интеллектуальный капитал как важнейший фактор экономического развития. Интервью с М. А. Эскандеровым. Век глобализации* 1: 39-44).

**Ivakhnyuk I. V. 2011.** International Migration as a Development Resource (Remarks for the Global Debate. *Vek globalizatsii* 1: 67-79. *In Russian* (Ивахнюк И. В. Международная миграция как ресурс развития (замечания в связи с глобальной дискуссией). Век глобализации* 1: 67-79).

**Kalachev B. F. 2008.** Movement of Narcogenes: From Space to Earth and to the Universe again. *Vek globalizatsii* 2: 114-128. *In Russian* (Калачев Б. Ф. Движение наркогенов: из Космоса на Землю и вновь по Вселенную. Век глобализации* 2: 114-128).

**Kamusella T. 2009.** Central Europe from a Linguistic Viewpoint. *Vek globalizatsii* 2: 81-91. *In Russian* (Камуселла Т. Центральная Европа с лингвистической точки зрения. Век глобализации* 2: 81-91).

**Kapitsa S. P. 2008.** Demographic Revolution and Russia. *Vek globalizatsii* 1: 128-143. *In Russian* (Капица С. П. Демографическая революция и Россия. Век глобализации* 1: 128-143).
**Karyakin Yu. F. 2010.** Not to be Late! (One Premise Gives an Infinity of Consequences. *Vek globalizatsii* 1: 111–125. *In Russian* (Карякин Ю. Ф. Не опоздать! (Одна посылка – бесконечность следствий). *Век глобализации* 1: 111–125).

**Kefeli I. F. 2011.** Global Geopolitics – Reality and Theoretical Knowledge of the 21st Century. *Vek globalizatsii* 1: 15–28. *In Russian* (Кефели И. Ф. Глобальная геополитика – реалии и теоретическое знание XXI в. *Век глобализации* 1: 15–28).

**Kefeli I. F., and Plebanek O. V. 2008.** Global Studies and Geopolitics (Symposium). *Vek globalizatsii* 1: 171–173. *In Russian* (Кефели И. Ф., Плебанек О. В. Глобалистика и геополитика (круглый стол). *Век глобализации* 1: 171–173).

**Khasbulatov R. I. 2008.** Global Financial Crisis: Causes and Consequences. *Vek globalizatsii* 2: 30–45. *In Russian* (Хасбулатов Р. И. Глобальный финансовый кризис: причины и последствия. *Век глобализации* 2: 30–45).

**Khasbulatov R. I. 2011.** Idols and Idolaters: The Collapse of Libertarianism. *Vek globalizatsii* 1: 3–14. *In Russian* (Хасбулатов Р. И. Идолы и идолопоклонники: крах либертаризма. *Век глобализации* 1: 3–14).

**Kolesnikov V. A. 2009.** From the Understanding of Globalized Reality to the New Vision of Education of the 21st Century. *Vek globalizatsii* 1: 70–78. *In Russian* (Колесников В. А. От осмысления глобализирующейся реальности – к новому видению образования XXI века. *Век глобализации* 1: 70–78).

**Krasikov K. I. 2008.** Humanism versus Globalization of Violation. *Vek globalizatsii* 2: 193–194. *In Russian* (Красиков В. И. Гуманизм versus глобализация насилия. *Век глобализации* 2: 193–194).

**Kuşuradi I. 2008.** Globalization of the Free Market from a Philosophical-Ethic Viewpoint. *Vek globalizatsii* 2: 21–29. *In Russian* (Кучуради И. Глобализация свободного рынка с философско-этической точки зрения. *Век глобализации* 2: 21–29).

**Kutyryov V. A. 2009.** The Clash of Cultures with Civilizations as a Ground and Reason for International Terrorism. *Vek globalizatsii* 2: 92–102. *In Russian* (Кутырёв В. А. Столкновение культур с цивилизацией как причина и почва международного терроризма. *Век глобализации* 2: 92–102).

**Leybin V. M. 2011.** Man as the Global and Unique Problem of Modernity. *Vek globalizatsii* 1: 130–139. *In Russian* (Лейбин В. М. Человек как глобально-уникальная проблема современности. *Век глобализации* 1: 130–139).

**Lukjanenko V. I., Khabarov M. V., and Lukjanenko A. V. 2009.** Homo Consumens – a Consuming Man. *Vek globalizatsii* 2: 149–159. *In Russian* (Лукьяненко В. И., Хабаров М. В., Лукьяненко А. В. Homo Consumens – человек потребляющий. *Век глобализации* 2: 149–159).

**Mamedov N. M. 2010.** Historical Process and the Concept of Sustainable Development. *Vek globalizatsii* 2: 33–46. *In Russian* (Мамедов Н. М. Исторический процесс и концепция устойчивого развития. *Век глобализации* 2: 33–46).
**Mantatov V. V. 2009.** Globalization, Sustainable Development and Society of the Future (on the Materials of the 22nd World Congress of Philosophy. *Vek globalizatsii* 1: 175–184. In *Russian* (Мантатов В. В. Глобализация, устойчивое развитие и общество будущего (по материалам XXII Всемирного философского конгресса). *Век глобализации* 1: 175–184).

**Markovich D. Zh. 2008.** Culture of Piece, Tolerance, and Interethnic Relationships. *Vek globalizatsii* 2: 155–163. In *Russian* (Маркович Д. Ж. Культура мира, толерантность и межэтнические отношения. *Век глобализации* 2: 155–163).

**Mazur I. I. 2008.** The Global Energy Security. *Vek globalizatsii* 1: 57–69. In *Russian* (Мазур И. И. Глобальная энергетическая безопасность. *Век глобализации* 1: 57–69).

**Mazur I. I. 2010.** The Arctic – Bifurcation in the Development of Global World. *Vek globalizatsii* 2: 93–104. In *Russian* (Мазур И. И. Арктика – точка бифуркации в развитии глобального мира. *Век глобализации* 2: 93–104).

**McCormic P. 2009.** Globalization and Cosmopolitism. Criteria, Approaches and Experience of Life. *Vek globalizatsii* 2: 61–70. In *Russian* (Маккормик П. Глобализация и космополитизм. Критерии, подходы и жизненный опыт. *Век глобализации* 2: 61–70).

**Mitrofanova A. V. 2008.** Religion in World Politics and the Problem of ‘Civilizations’. *Vek globalizatsii* 1: 109–119. In *Russian* (Митрофанова А. В. Религиозный фактор в мировой политике и проблема «цивилизаций». *Век глобализации* 1: 109–119).

**Pyrin A. G. 2009.** The Financial Crisis: A Philosophical Reflection. *Vek globalizatsii* 2: 141–148. In *Russian* (Пырин А. Г. Финансовый кризис: философская рефлексия (итоги круглого стола). *Век глобализации* 2: 141–148).

**Pyrin A. G. 2009.** Who is Who and What is What in Global Studies? *Vek globalizatsii* 1: 185–189. In *Russian* (Пырин А. Г. Кто есть кто и что есть что в глобалистике. *Век глобализации* 1: 185–189).

**Rezhabek B. G. 2008.** The Noosphere Theory of Vernadsky and the Search for the Way Out the Global Crises. *Vek globalizatsii* 1: 159–167. In *Russian* (Режабек Б. Г. Учение В. И. Вернадского о ноосфере и поиск пути выхода из глобальных кризисов. *Век глобализации* 1: 159–167).

**Robertson R. 2010.** The ‘Return’ of Religion and the Conflict of World Order. *Vek globalizatsii* 1: 30–38. In *Russian* (Робертсон Р. «Возвращение» религии и конфликтная ситуация мироустройства. *Век глобализации* 1: 30–38).

**Smitienko B. M. 2010.** Russia and the Ideas of the United Europe. *Vek globalizatsii* 1: 145–156. In *Russian* (Смитиенко Б. М. Россия и идеи объединенной Европы. *Век глобализации* 1: 145–156).

**Snakin V. V. 2010.** The Global Environmental Crisis: Resource and Evolutionary Aspects. *Vek globalizatsii* 2: 105–114. In *Russian* (Снакин В. В. Глобаль-
ный экологический кризис: ресурсный и эволюционный аспекты. *Век глобализации* 2: 105–114).

**Taran P. 2010.** Globalization and Labour Migration: The Necessity of Politics Based on Human Rights. *Vek globalizatsii* 1: 66–88. *In Russian* (Таран П. Глобализация и трудовая миграция: необходимость политики, основанной на правах человека. *Век глобализации* 1: 66–88).

**Tynyanova O. N. 2010.** National Sovereignty and State Boundary in the Epoch of Globalization. *Vek globalizatsii* 1: 89–105. *In Russian* (Тынянова О. Н. Национальный суверенитет и государственные границы в эпоху глобализации. *Век глобализации* 1: 89–105).

**Ursul A. D. 2008.** Global Processes, Security and Sustainable Development. *Vek globalizatsii* 1: 17–22. *In Russian* (Урсул А. Д. Глобальные процессы, безопасность и устойчивое развитие. *Век глобализации* 1: 17–22).

**Valieva K. A. 2009.** The Political Projection of Globalization in the European Space. *Vek globalizatsii* 1: 98–107. *In Russian* (Валиева К. А. Политическая проекция глобализации в европейском пространстве. *Век глобализации* 1: 98–107).

**Weber A. B. 2011.** Mankind Faces the Global Environmental Challenge. *Vek globalizatsii* 1: 110–121. *In Russian* (Вебер А. Б. Человечество перед глобальным экологическим вызовом. *Век глобализации* 1: 110–121).

**Yaskevich Ya. S. 2009.** The Economic Crisis and Value Rethinking of the Modern World: A Philosophical Reflection. *Vek globalizatsii* 1: 45–54. *In Russian* (Яскевич Я. С. Экономический кризис и ценностное переосмысление современного мироустройства: философская рефлексия. *Век глобализации* 1: 45–54).

**Yudin B. G. 2008.** Technoscience, Man, Society: Actuality of Humanitarian Expertise. *Vek globalizatsii* 2: 146–154. *In Russian* (Юдин Б. Г. Технонаука, человек, общество: актуальность гуманитарной экспертизы. *Век глобализации* 2: 146–154).
## II. BIG HISTORY'S PHASES, REGULARITIES, AND DIMENSIONS

8

# The Star-Galaxy Era of Big History in the Light of Universal Evolutionary Principles

Leonid E. Grinin

### Abstract

Big History provides a unique opportunity to consider the development of the Universe as a single process. Within Big History studies one can distinguish some common evolutionary laws and principles. However, it is very important to recognize that there are many more such integrating principles, laws, mechanisms and patterns of evolution at all its levels than it is usually supposed. In the meantime, we can find the common traits in development, functioning, and interaction of apparently rather different processes and phenomena of Big History. Of special importance is the point that many principles, patterns, regularities, and rules of evolution, which we tend to find relevant only for the biological and social levels of evolution, may be also applied to the cosmic phase of evolution. The present article attempts (within such a framework for the first time in the Big History framework) at combining Big History potential with the potential of Evolutionary Studies. It does not only analyze the history of the Cosmos. It studies similarities between evolutionary laws, principles, and mechanisms at various levels and phases of Big History. Such an approach opens up some new perspectives for our understanding of evolution and Big History, their driving forces, vectors, and trends; it creates a consolidated field for interdisciplinary research.

**Keywords:** Star-Galaxy Era, cosmic phase of Big History, laws of evolution, universal evolutionary principles, Universe, preadaptations, Evolutionary Studies, evolutionary selection, additive and substitutive models of evolution, large-scale structures of Universe, gas-dust clouds, non-uniformity concentration of matter, circulation of matter in the Universe, dark and light matter.

### Introduction

Big History provides unique opportunities to consider the development of the Universe as a single process, to detect vectors of changes of certain important characteristics of the Universe (such as complexity and
energy) at various phases of this development. However, one should note that the Big History studies tend to pay little attention to such an important aspect as the unity of principles, laws, and mechanisms of evolution at all its levels.<fnref n="1" /> I believe that combining the Big History potential with evolutionary approaches can open wider horizons in this respect (see Grinin *et al.* 2011). Indeed, common traits in development, functioning, and interaction can be found in apparently quite different processes and phenomena of Big History. In this respect the universality of evolution is expressed in those real similarities that are detected in many manifestations at all its levels.

This article is an attempt to combine Big History potential with the potential of Evolutionary Studies in order to achieve the following goals: 1) to apply the historical narrative principle to the description of the star-galaxy era of the cosmic phase of Big History; 2) to analyze both the cosmic history and similarities and differences between evolutionary laws, principles, and mechanisms at various levels and phases of Big History. As far as I know, nobody has approached this task in systemic way yet. It appears especially important to demonstrate that many evolutionary principles, patterns, regularities, and rules, which we tend to find relevant only for higher levels and main lines of evolution, can be also applied to cosmic evolution. Moreover, almost everything that we know about evolution may be detected in the cosmic history, whereas many of the evolutionary characteristics are already manifested here in a rather

<footnote n="1">¹ Of course, some authors analyze important general evolutionary mechanisms and patterns, which can be seen at all phases of Big History (see, e.g., David Christian's 'Swimming Upstream' and the conclusion of David Baker's 'Shoulders of Giants' in this volume). One can also mention Fred Spier (2010) and David Baker's '10⁵⁰⁰. The Darwinian Algorithm and a Possible Candidate for a "Unifying Theme" of Big History' (2013). However, we should state our position on Baker's general idea in that interesting paper. While also dealing with universal evolutionary principles like ours, Baker innovates by starting his article with analyzing the selection of universes within which there could appear some physical laws and parameters allowing the universes to evolve. Baker explores the selection mechanism among an enormous number (potentially 10⁵⁰⁰– a fabulous number even for modern cosmology) of universes in the 'multiverse'. We suppose that his algorithm with respect to the selection of universes could hardly be called properly Darwinian. He rather speaks about the evolutionary selection in general – that is not the selection of the fittest, but rather the selection of those capable to evolve – which is much wider than the Darwinian selection. The idea that such selection is not Darwinian is confirmed if one employs Christian's (this volume) and Smolin's (2008: 34, which Christian refers to) definitions of the Universal Darwinian mechanism. Such mechanism should obviously include a mechanism of reproduction. It is clear that there is not any mechanism of reproduction in the case of isolated universes. However, for a theory of the presence of Darwinian reproduction in the evolution of multiple universes see Smolin's earlier book *The Life of the Cosmos* (1997).</footnote>
clear and salient way. One should also bear in mind that the origin of galaxies, stars, and other ‘celestial objects’ is the lengthiest evolutionary process among all evolutionary processes in the Universe. Such an approach opens new perspectives for our understanding of evolution and Big History, of their driving forces, vectors, and trends, creating a consolidated field for the multidisciplinary research.

Our world is immensely diverse and unlimited in its manifestations. However, fundamentally it is a single world – that is why it is so important to study those fundamentals.

# I. THE FORMATION OF THE LARGE-SCALE STRUCTURE OF THE UNIVERSE

**Preconditions.** After the Big Bang, our Universe ‘lived’ for quite a long period of time without any stars, galaxies, clusters, and superclusters of galaxies (Khvan 2008: 302). The formation of modern structure of the Universe lasted for billions of years. However, the first stars and galaxies turn out to have emerged not later than 200–400 million years after the Big Bang. And what was the matter from which they had emerged?

Approximately 270,000 years after the Big Bang, a large phase transition occurred resulting in the emergence of matter in the form of atoms of hydrogen and helium. Later, they started to consolidate in new structures (see below). The main mass of this matter concentrated in gas-dust clouds that could have tremendous sizes (dozens parsecs, or even more).² For the first time we observe Nature in the role of a constructor. Before that, it had formed just the basic elements. Now one could observe the emergence of enormous structures from tiny particles and ‘specks of dust’. After that one could observe this constantly: large-scale structures are composed of myriads of minute particles and grains.

The formation of clouds (and later stars and galaxies) meant a concentration of matter on enormous scale, which could have been caused only by gravity. However, this only force is insufficient for structuring, because in ‘an absolutely homogenous universe the emergence of large-scale structures (galaxies and their clusters) is impossible’ (Dolgov et al. 1998: 12–13). Thus, certain seed grains are necessary – this is comparable with formation of rain drops that emerge around particles of dust or soot; or with formation of a pearl around grit. *Small fluctuations are often needed for the powerful forces to start working.* Actually, minor fluctuations (minute deviations from homogeneity) occurred in the Universe early on. Then the larger fluctuations happened. They could act as seed grains for the formation of galaxies and the matter concentrated around them

<footnote n="21">²¹ parsec ≈ 31 trillion km.</footnote>
on a much larger scale until the quantity started to transform into a new
quality. This is a perfect example of the point that *the non-uniformity (in
particular with respect to the distribution of matter, energy, etc.) is a universal
characteristic*. Any major evolutionary shift in biological and social sys-
tems is preceded by the concentration of certain forms, resources and
conditions in certain niches and places. Thus, in the major system the
common processes may proceed in their usual way, whereas in the con-
centration zone some peculiar processes start (this is what takes place in
star formation zones).

**Dark and light matter.** Nowadays it is generally accepted that dark matter plays an important role in the formation of the first galaxies, as it appeared capable of consolidating into clusters much earlier than the light (baryon) matter. The latter could not contract until the end of the hydrogen recombination (atom formation) due to radiation (270,000 years after the Big Bang). Only when hydrogen nuclei and electrons were able to merge and form atoms, whereas photons separated from the matter and flew away, the pressure of the radiation dramatically dropped. As a result, the light matter would fall in potential holes prepared for it by the dark matter. Though the dark matter was initially more capable to structuring than the light matter, the progress toward structuring turned out to be very short and leading to almost a dead-lock.<fnref n="3" /> Meanwhile, the evolutionary potential of the light matter was based on the ‘achievements of the dark matter’. Such a model of development is rather typical for evolution. For example, long before the transition to agriculture some gatherers of cereal plants invented many things (sickles, granaries, and grinding stones) that later turned to be rather useful for agriculturalists, whereas specialized hunter-gatherers turned out to be an evolutionary dead end.

**The epoch of formation of the large-scale structure of the Universe. First galaxies and stars.** There are rather diverse opinions on timing, process characteristics and sequence of formation of stars, galaxies, galaxy clusters and superclusters. There is a hypothesis that galaxy protoclusters were first to originate. However, a more commonly held hypothesis suggests that protogalaxies (in the form of giant condensed gas clouds) were the first to emerge within the structure of the Universe, and later they became the birthplace for separate stars and other structural elements (see, e.g., Gorbunov and Rubakov 2011).

<footnote n="3">³ However, as with any evolutionary dead end, this does not mean an absolute stagnation. At present, in galaxy halos the dark matter is structured in certain smaller structures (see, e.g., Diemand et al. 2008).</footnote>
However, in recent years new evidence has come to hand to sup-
port the idea that those were the stars that appeared first. This discovery
somehow modified the previous theories. At present, it is widely ac-
cepted that the stars were first to emerge, but those were the giant stars,
much more massive than most of the later-formed ones (May et al. 2008).
Because of the absence of carbon, oxygen and other elements that ab-
sorb the energy from condensing clouds, the process proceeded more
slowly in that epoch; thus, only giant clouds could condense producing
massive stars hundreds times larger than the Sun (Ibid.). Such giant stars
lived only a few million years (the larger is star, the shorter is its life).
In addition, the first stars contained a small amount of heavy elements.
Thus, more than one generation of stars could change, until the quantity
of heavy elements gradually increased. The emergence of 'heavy ele-
ments' from the 'dead star stellar remnants' resembles the formation of
fertile soil from the remnants of dead plants. The circulation of matter in
the Universe is always observed everywhere and at all levels.

In recent years we have witnessed the discovery of a few galaxies
that are claimed to be the oldest in the Universe. Meanwhile, the dates
of formation of the first galaxies are shifted closer and closer to the Big
Bang. The emergence of the first galaxies is dated to less than 400 mil-
lion years after the Big Bang; and there are even claims that some more
ancient galaxies have been discovered. They are claimed to have
emerged only 200 million years after the Big Bang (see European Com-
mission 2011). The evidence on the first stars refers to c. 150-200 million
years after the Big Bang – hence, stars and galaxies appear to have
emerged almost simultaneously.

## II. THE ERA OF THE STAR-GALAXY STRUCTURE
OF THE UNIVERSE

The whole history of the star-galaxy phase of cosmic evolution is basi-
cally the history of formation of various structures of different size, as
well as their merging into larger structures (but it is a history of their
disintegration as well).

1. The structure of the Universe

1.1. Some principles describing the basic structure of the Universe may be applied to different levels of evolution (below we will consider just two of them).

1) *The combination of antagonistic qualities.* For example, in the
structure of the Universe one can find the combination of uniformity
and non-uniformity. The uniformity is already manifested at the
inflation phase, when the Universe started inflating evenly in all dimensions. The uniformity has preserved till present, but only at the largest scale (of an order of magnitude of 100 megaparsecs³). For reference, the size of the largest galaxy clusters (such as our Local Group with the center in the Virgo constellation) is 40 megaparsecs at most (Gorbunov and Rubakov 2011). The non-uniformity of the Universe is manifested at scales smaller than 100 megaparsecs; and the smaller is the scale, the more salient is the unevenness. The combination of antagonistic qualities is a phenomenon that is rather characteristic for many other evolutionary levels.

2) *Density and sparsity can be traced everywhere, starting from the atomic structure, where the mass is concentrated in a tiny nucleus, while most of the atom is an empty space. There is a huge non-uniformity between the scale of the Universe and the space that the main mass of the light matter occupies within it. It is concentrated, first of all, in stars which actually occupy only a 10⁻²⁵ part of the total volume of the Universe (not taking into account the galaxy nuclei [Pavlov 2011: 43]). Not only the hard matter is distributed very unevenly throughout the Universe; the same is true of the gas. Much of this gas is concentrated in giant molecular clouds which are of many thousands of solar masses (Lipunov 2008: 37). The principles of uneven distribution of the matter mass at different evolutionary levels are rather similar. For example, at present the main mass of the Earth's population is concentrated in a rather small territory in comparison with the total territory where life on the Earth is possible.*

**1.2. The structure of the contemporary Universe**

The main structural elements of the Universe are galaxies, their clusters, and superclusters. All the structural elements are rather stable in terms of gravitation, though they can split, merge, and collide. Galaxies are integral structural entities with a rather complex structure which includes, in addition to regions and arms, a nucleus (core), semi-periphery (so called ‘disc’), and periphery (so called ‘halo’) (Baade 2002: 255). The halo consists of both single stars and various stellar clusters. The halo's radius (a few hundred thousand light years) is much larger than the radius of the galaxy's disc.<fnref n="4" />

<footnote n="4">⁴ There might be an invisible halo consisting of dark matter behind the visible halo. It may be found in many (if not all) galaxies, whereby the diameter of the dark halo might exceed the diameter of the visible halo by an order of magnitude (see Ryabov *et al.* 2008: 1131).</footnote>
According to Hubble, the galaxies are classified into spiral, elliptical, and irregular with various subtypes (Ibid.: 18–32); yet, by now one more galaxy type has been identified – the lenticular galaxies.

A galaxy contains around 100 to 200 billion stars. There are small (dwarf) galaxies with a few million stars, there are also giant galaxies consisting of up to a trillion stars. Our galaxy with its mass of about 10¹¹ solar masses is one of the largest ones. It contains 200–300 or even more billions of stars. However, the mass of our neighbor – the Great Andromeda Nebula – is about three times larger.

Stars are distributed rather unevenly throughout galaxies, stars are parts of various groups and clusters; some of them consist of just a few stars, but some clusters can contain a few million stars. For example, within our Galaxy more than 1,500 star clusters have been identified (Surdin 2001). There are many globular clusters – spherical clusters tightly bound by gravity and consisting of hundreds of thousands, as a rule, rather old stars.

Galaxies are complex and (to a considerable extent) self-regulating systems, within which some stars disintegrate, whereas new stars form from cosmic gas and dust. The circulation (which results in processes of renovation of matter and its mixing) takes place at all levels of the Universe – both spatially and at different levels of evolutional complexity.

An average galaxy cluster consists of 500–1000 galaxies. Galaxy clusters have a rather regular structure which is likely to include a massive nucleus in the center. Galaxy superclusters are entities consisting of 2–20 galaxy clusters and galaxy groups as well as of isolated galaxies. In general, there are known more than 20 superclusters, including our Local Group.

### 1.3. Generations of galaxies and stars

There are rather diverse opinions on the number of generations throughout the evolution of the Universe. In addition, there is no consensus on which galaxies should be regarded as old, and which galaxies should be considered young. The point is that within a single galaxy one can find stars and their aggregates that considerably differ in their type, age, and other parameters. For example, the age of our Milky Way galaxy is more than 12 billion years, but that is the age of just its halo while many stars in its branches are only two–five billion years or less. Yet, it appears possible to single out a few widely accepted basic ideas.

1) In the evolution of the Universe, there have been three (or at least two) generations of galaxies and stars. In general, old galaxies are smaller and dimmer. Their stars contain dozens of times smaller quantities of heavy elements than the Sun. The astronomers can hardly observe any star formation processes within such galaxies. There is also a hypothesis
that more dark mass is concentrated in old galaxies in comparison with
younger ones. The same way, older and younger stars differ from each
other in their size, luminosity, and chemical composition.

2) It is difficult to speak about a clear periodization of generations of galaxies, because of the ongoing process of formation of galaxies and stars. Galaxies need to constantly renew their composition in order to retain their identity. As Joseph Shklovsky maintains, in this respect galaxies are very similar to primary forests with its mix of tree ages (whereas the age of trees is much less than the age of the forest itself [Shklovsky 1984: 45]). The motility and variability of the celestial landscape resembles very much the motility of geological landscapes.

3) The formation of galaxies can proceed in different ways, for example, through the absorption of smaller galaxies by the larger ones. Another way is merging. Galaxies of younger generations can sometimes form through the accretion of a few small, weak and compact galaxies into a single galaxy. In this case they became 'building blocks' for galaxies. Finally, it may happen that two large galaxies collide. Such a collision may take billions of years and be accompanied with active star formation and emergence of very large and bright stars. Finally, galaxies may diverge again, but in this case they turn out to be very different from what they used to be before the collision, whereas one more galaxy may emerge out of the matter estranged from the both galaxies (see May et al. 2008: 142).

There are numerous analogies to those models of galaxy formation
in biological, geological, and, especially, social evolution. As stars and
galaxies are composed of more or less homogenous matter (that can be
divided or united rather easily), they somehow paradoxically resemble
societies that consist of people who can be included into other societies
through integration or capture. On the other hand, captures are also
attested among social animals (e.g., among ants see Genet 2007).

4) Galaxies are collections of different types of stars. However, there are certain peculiarities as regards the position of old and young stars within galaxies. Thus, within our galaxy the younger stars (such as the Sun which is a few billion years old) are generally larger, hotter and brighter. They are located toward the disc plane, and, especially, within the galaxy arms; whereas in the galaxy periphery (in its halo) one would find older stars more than 12 billion years old (which suggests the overall age of our galaxy). Yet, older and younger stars may be also located rather close to each other. Thus, one may find many old stars near the galaxy center (bulge), but there are also young stars that emerged from the matter produced by the disintegration of older stars. The highest
stellar density is found in the galaxy center where it reaches a few stars per cubic parsec.

On the one hand, the preservation of generations of stars and galaxies demonstrates an additive character of the evolution of abiotic systems, whereas we can see elements of substitutive model of evolution at biological phase and its full system at social phase of Big History. However, the capture of stars and galaxies with their subsequent integration and prolonged processes of collision of galaxies demonstrates that in abiotic natural systems one may still find some other models of evolution – connected with ‘wars’ and ‘submission of outsiders’.

The type of development through the emergence of different generations of individuals and species (preserving certain generic features, on the one hand, and accumulating important changes in their structure and characteristics, on the other) is rather widespread at all phases and levels of universal evolution. Within any biological class or order (e.g., perissodactyls) we can see how important characteristics vary and gradually change from one species to another, whereas due to those characteristics some species press out others and occupy better niches (see, e.g., Grinin, Markov, and Korotayev 2008). Various types of states and civilizations also rather vividly illustrate the progress: for example, more organized and developed states emerge through the absorption of the achievements of less developed generations of states, which one can illustrate using examples from the history of Ancient Rome, Byzantium, some Medieval European states and so on. The coexistence of different generations sometimes leads to the situation when younger and more advanced entities either transform the older ones or form a symbiosis with them (though in some places one may find ‘restrictions’ for older types and generations).

**1.4. Change of the chemical composition of the Universe**

Hydrogen has always been the most abundant element in the Universe chemical composition; yet, its share constantly decreased. This occurred (and occurs) because hydrogen is the main fuel for the nuclear fusion reactions that support life and luminosity of stars. Increasing temperatures inside the core of some stars were needed for the formation of new elements that were absent in the era of recombination. However, all of the fusion reactions that occur to produce elements larger than iron no longer release energy. Reactions of another type are needed for the formation of elements heavier than iron – those reactions consume more energy than release. That is why there are such relatively small amounts of heavy elements in the Universe. Yet, such peculiar reactions do take place – for example, in neutron stars and during explosions of supernovae. When supernovae explode, heavy elements are expelled through
the Universe with stellar winds and through the fall of the dispersed
matter on the surface of cosmic bodies (so-called accretion). As stars
turn to be the main centers of the synthesis of chemical elements, the
distribution of heavy elements in the Universe is very inhomogeneous.

The emergence of heavy elements and their concentration in certain
bodies and compositions are extremely important processes, which lead
to an enormous increase in the number of matter combinations, and con-
sequently have an evolutionary potential; in particular, they lead to the
start of the full-scale chemical, biochemical, and biological processes. In
certain respects, such a slow and uneven accumulation of new structural
elements (heavy elements) resembles the process of an accumulation of
valuable mutations in biological evolution, or the accumulation of valu-
able innovations in social evolution (all of them bring the expansion of the
evolutionary potential and increase the rates of evolutionary changes).

## 2. The Evolution of Galaxies and Stars

### 2.1. Processes of the formation of galaxies and stars

Until quite recently, the processes of star formation were entirely con-
cealed from an external observer; however, at present due to the techno-
logical progress one can observe some aspects of those processes in many
parts of our galaxy. Those observations confirm the theory of stellar for-
mation from cold clusters that are heated by gravitation and pressure.

Briefly, this process may be described as follows. Within giant hydro-
gen and helium clouds, some heterogeneities emerge, which launch (un-
der certain conditions) the gravitation processes that start to collect that
mass into spherical forms. Sometimes a direct formation of a giant mass
of gas clouds takes place, from which a galaxy or a star cluster later
emerges. In this case the cloud fragmentation may occur and thus, more
and more gas-cloud spheres (there could be hundreds of millions, or even
hundreds of billions of them) emerge, which can gradually transform into
protostars. This process continues up to the point when the gas density
becomes so high that each new fragment already has a mass of a star
(Surkova 2005: 49). Then the gravity starts impeding further fragmenta-
tion. This process is denoted as 'cascade fragmentation'. It is remarkable
that it resembles certain processes in social evolution – for example, the
fragmentation of large early states into separate parts that decentralize up
to the point when further division becomes unreasonable (e.g., in certain
periods there were dozens and hundreds of independent states in the ter-
ritories of Germany or France).

As enormous gas/dust clouds appear unstable, they disintegrate into
large bundles, so the formation of stars proceeds in groups. This phenome-
non is of interest not only with respect to stellar evolution. The group
formation is rather typical for evolution in general (in this way popula-
tions and sometimes new species emerge; chiefdoms, city-states, and
sometimes political parties emerge in groups, and so on).

The further process of the star formation is connected with the point
that the initial compression heated the gas to a rather high temperature
that, on the one hand, prevents the further compression of the gas, and,
on the other hand, eventually contributes to the onset of the nuclear fu-
sion reaction (Hawking 2001: 63–64).

**2.2. Diversity of stars and galaxies**

Diversity is an absolutely required condition of evolutionary develop-
ment. And this condition is fully realized within cosmic evolution. As
has been mentioned above, galaxies differ in their types, age, size, and
structure. In particular, a galactic structure is to a large degree deter-
mined by the initial conditions of its formation (e.g., by the character of
rotation of the original gas clump from which a galaxy is formed). Stars
differ in mass, temperature, chemical composition, luminosity, age, and
other characteristics. Those differences may vary greatly. For example,
with respect to masses, stars range in mass from about 0.1 to 100 or more
solar masses. It is rather natural that the number of smaller entities is
orders of magnitude larger;<fnref n="5" /> actually, the same phenomenon may be
observed, for example, in Zoology or Political Geography where the
number of small animals or countries is much larger than that of large
ones.

**2.3. The life-cycle of a star: Stages of stellar birth, aging, and death**

**Protostars.** As mentioned above, stars emerge through the condensation and compression of gas clouds under the influence of gravitational forces. This is a protostar phase. In comparison with the subsequent life of a star, the period of its slow contraction seems rather short; however, actually this is not a quick process as it continues sometimes up to 50 million years (Surkova 2005: 50). During this period of time, there is a tremendous rise in the temperature at the core of the protostar, the temperature may grow up to 8–10 million Kelvin, and, as a result, thermonuclear reactions become possible. The protostar becomes a young star. However, an external observer will only be able to see it in a few hundred thousand (or even a few million) years when the cocoon of gas and dust surrounding the protostar dissipates.

<footnote n="5">⁵ Thus, for every ten million red dwarfs we find only 1,000 giants and one supergiant (Surkova 2005: 26).</footnote>
Actually, we deal with a sort of miracle – a giant shining incandescent body, which is capable of living for billions of years, emerges from an absolutely amorphous, lacking any structure, opaque, and cold mass of gas mist. In other words, we deal here with a vivid example of self-organization that takes place under the influence of gravitation and thermodynamic laws. In particular, an intensive contraction leads to heating, which increases the internal pressure, which, eventually, stops the compression process.

One may also note that the emergence of stars and galaxies must have a certain trigger that creates turbulence and heterogeneity. Those triggers and catalyzers are the inherent components of evolutionary mechanisms that may be found in many processes: in chemical and geological processes, within biological evolution with respect to fast formation of species, or within social evolution with respect to state formation (see Grinin 2011 for more details). The supernova shock wave, the collision of a molecular cloud with spiral arms of a galaxy and other events can become such a trigger of the star formation (Surkova 2005: 50).

Another (the longest) macrophase is the main sequence star. During this phase of the stellar lifetime, nuclear-fusion reactions that burn hydrogen to helium in the core, keep the star shining. That is why the duration of the main sequence phase depends mainly on the stellar mass. The more massive is the star, the shorter its lifespan on the main sequence (as with a larger mass the 'fuel combustion' processes run more intensively). A star preserves its size and form due to the mutual struggle of two forces: the gravity that tries to compress the star and the gas pressure produced as a result of nuclear reactions and powerful heating. There is a dynamic equilibrium between temperature and gas pressure. With growing temperature, the gas expands and works against the gravitation forces, which results in cooling of the star; this way the thermal balance is kept. In the lifetime of stars and galaxies, as well as at all other levels of evolution, we find numerous cases and different forms of the interaction between two opposite processes which make it possible for 'individuals' to live. The processes of assimilation and dissimilation support vital activities within biological organisms; the processes of animal reproduction and their extermination by predators support the population balance; interaction between processes of production and consumption is the basis of the reproduction of social systems, and so on.

**Red giants.** The new phase of stellar evolution is connected with the exhaustion of hydrogen supplies. The gas pressure (that maintained the star balance when necessary fuel was available) decreases and the stellar core compresses. This leads to a new increase in temperature. A star
starts to burn heavier elements and thus, the stellar composition signifi-
cantly changes. Simultaneously with the compression of the core, the
star's outer layers expand. In general, the star inflates and expands a
few hundred times, and it transforms into a red giant. This phase lasts
for about one tenth of the 'active lifetime' of a star, when the processes
of nuclear fusion go on in its depths.

**Star death: three cases.** The next phase is the transformation of a red giant or supergiant. Actually, the new form depends on stellar mass and a number of other characteristics such as the stellar rotation and velocity, the degree of its magnetization, and so on. The following three outcomes are considered most typical. They depend on stellar mass (but the limit value estimates vary significantly, and so below I will mention the main alternative values after the slash).<fnref n="6" /> Stars with the masses smaller than 1.2–1.4/3 solar masses transform from red giants into the so-called ‘white dwarfs’, when the star sheds its outer envelope to form a planetary nebula with an extremely contracted core (down to the size of the Earth). The further compression does not occur because of the so-called degenerate electron gas pressure that does not depend on temperature. As a result, the white dwarf is rather stable. However, due to the lack of hydrogen and helium, thermonuclear fusions can no longer proceed within such a star. A white dwarf is very hot when it is formed; yet, afterwards the star cools and transforms into a ‘black dwarf’, that is, it becomes a cold dead cosmic body.

For stars with an initial mass of more than 1.2–1.4/3, but less than
2.4–3/7–10 solar masses, their slow and gradual aging results in an ‘in-
farct’, that is a collapse. After the depletion of hydrogen and the decrease
of the internal gas pressure (that used to balance the gravity), under the
influence of gravity the core gets extremely compressed (by dozens thou-
sand times – up to the radius of ten kilometers) just in less than a sec-
ond. Almost simultaneously the external layers of the star are blown
away with a huge speed as a result of shock wave. This supernova
shines brighter than millions of ordinary stars, but for a very short pe-
riod of time. This explosion expels the stellar material into interstellar
medium and thus, there occurs the formation of considerable quantities
of heavy (heavier than iron) elements that afterwards concentrate in
various celestial bodies. The remaining core contracts to become a neu-
tron star. In its size, such a star is 5 billion times smaller than the Sun,

<footnote n="6">⁶ According to one of classifications (that might be more correct than the one reproduced below), it appears possible to subdivide all the stars just in two classes: a) massive stars (with a mass exceeding c. 10 solar masses), producing neutron stars and black holes, and b) non-massive ones producing white dwarfs (Lipunov 2008: 99).</footnote>
but it is hundreds of thousands of times brighter because the tempera-
ture on its surface is 1000–1500 times higher than on the Sun (Lipunov
2008: 133).

If stellar mass exceeds the limit of 3/7-10 solar masses, after hydro-
gen is burnt out it will start collapsing and explode (though sometimes
it may collapse without an explosion), but the force of compression will
be unlimited, as the gravity becomes enormous because of the huge
mass and absence of internal forces that can prevent the collapse. The
action of the gravitational force which is balanced by nothing leads to
the situation when the stellar diameter becomes infinitesimally small.
According to theoretical calculations, the star is transformed into a black
hole whose gravity fields are strong for light to escape.

III. UNIVERSAL EVOLUTIONARY PRINCIPLES
IN THE STAR-GALAXY ERA

1. Life, Death, and Catastrophes in the Evolutionary Aspect

The lifetime of stars in terms of maintaining and breaking the dy-
namic equilibrium

First of all, there is a thermal equilibrium, when the rate of energy pro-
duced in the core (through thermonuclear fusions) balances the loss of
energy through the emission of radiation into space. This equilibrium is
broken when hydrogen fuel is gone. The reserves are apparently com-
pensated when a star starts using another type of energy. This may oc-
cur through the contraction of the star which begins fusing helium into
carbon, thus producing many times more energy for every atom; after-
wards heavier elements may be used as fuel, and each heavier element
will produce more and more energy per atom. Meanwhile, the core of
the star begins to increase in temperature. There is equilibrium in terms
of pressure of different forces and preservation of a certain form and
size of the star. Within the main sequence phase, the balance is main-
tained as the gravity pulls all the stellar matter inward, toward the core,
while gas pressure pushes heat and light away from the center. This
pressure exists until the reserves of nuclear fuel are exhausted (Efremov
2003: 97). With respect to red giants one may speak about equilibrium of
another kind in two dimensions. In the core the temperature grows due to
contraction and thermonuclear reactions of higher levels (described above)
start; as a result of those reactions the temperature may grow up to 100 mil-
lion Kelvin. That is why a stronger gravity is balanced by a stronger (due to
temperature) gas pressure. In the meantime, within the shell the equilib-
rium is achieved through the multifold expansion of the outer layers.
In neutron stars and white dwarfs, the subsequent phases of the stellar lifetime, there is their peculiar equilibrium.

**The problem of the individual's death. Death as an opportunity for life to go on.** Stellar life and death can hardly leave anybody indif- ferent. Actually, within the Big History framework, this is the first time when we come across the problem of a life cycle of individual objects in such an explicitly expressed form. On the one hand, the star's fate, life- span, and type of death depend on initial parameters, as if they were 'genetically programmed' (and, hence, they may be forecasted); on the other hand, they may be altered by some contingencies. Thus, the star's fate is not 'fatal', indeed. Binary star systems increase highly the vari- ability of the individual star fates; as Lipunov (2008: 252) puts it, we deal here with a kind of 'quadratic evolution'. What is more, it is actu- ally possible to speak about differences in the 'individual' stellar behav- ior or 'within a group', because the interaction of two, three, and more stars may lead to very significant differences and unusual results that cannot emerge within the development trajectory of individual stars. In fact, similar patterns are observed at other levels of evolution, when be- havior of pairs or groups of individuals produces outcomes radically different from the ones observed with respect to the behavior of an in- dividual not interacting with others.

Finally, the meaning of individual's death for evolution may be dif- ferent. Up to a certain degree one may observe a direct correlation be- tween the 'strength' of death, the power of the stellar explosion, and the formation of conditions for a new evolutionary search. Stellar explo- sions affect the dynamics of their environment; consequently, they may help create unusual conditions that contribute to the emergence of cer- tain developmental deviations. Within tens of thousands years the zone of explosion expands to a vast area of interstellar medium (covering the distances of dozens of parsecs); in this area one can see the formation of new physical conditions (in particular, temperature, density of cosmic rays and magnetic fields strength). Such a disturbance enriches the re- spective zone with cosmic rays and brings changes to chemical compo- sition (Shklovsky 1984: 209). The explosions also contribute to star for- mation. Thus, a star does not die in vain. One can draw here an interest- ing analogy with extinctions in biological evolution which contribute to new directions of speciation. The stellar destruction can be also com- pared with the disintegration of large empires with all the subsequent repercussions. The disintegration of a large empire leads to a cascade of new states forming both in the place of the empire and even beyond its
borders. Historical detonation contributes to politogenesis the same way
as the cosmic detonation contributes to star formation.

**Synthesis of gradualism and catastrophism.** With respect to cosmic evolution one may observe a combination of two principles that provoke endless discussions in geology and biology. The subject of those discussions is what principle prevails in evolution. Are we dealing mostly with slow gradual changes, eventually leading to major changes (gradualism)? Or, does the development mostly proceed through sharp revolutionary breakthroughs which in biology are often connected with catastrophes? Within star-galaxy evolution the combination of both principles is more than just evident. Here, as at no other evolutionary level, both modes of evolution are organically combined in individual fates of the stars. The main sequence phase of stellar evolution (when the fusing of hydrogen occurs) demonstrates the gradual character and the importance of slow and prolonged processes. However, catastrophes of various scales can take place within the lifetime of any star. For some stars, such radical changes may manifest in major – but still local – changes (such as shedding the outer layers), whereas for other stars these might be tremendous catastrophes when stars die, figuratively speaking, ‘brightly’ and ‘heroically’, illuminating the Universe, leaving a billion-year-long footprint of light. The latter, that is the extraordinary phenomena and events, both among the stars and among humans are less numerous than the former, that is the common ones.

**2. Some Evolutionary Ideas in Connection with the Star-Galaxy Phase of Evolution of the Universe**

In the evolutionary process of formation of stars, galaxies, nebulae, and cosmic clouds one can distinguish a number of important evolutionary principles and laws that are not evident. Their detection is important for understanding the unity of principles of development of the Universe. Those principles and observations are grouped below into several blocks.

**2.1. Evolution proceeds with constant creation and destruction of objects**

Nature, when creating, destroying, and renewing various objects, 'tests' many versions, some of which turn out to be more effective and have more chances to succeed in terms of evolution. For such a situation of selection within constant destruction and creation process, it appears possible to apply a rather appropriate notion of creative destruction introduced by Josef Schumpeter (1994).

* 'Evolution is stronger than individual objects'. Cosmic processes are accompanied by constant emergence, development, change, and
death of various objects (stars, galaxies, and so on). Thus, here one can
point as relevant the principle that was expressed by Pierre Teilhard de
Chardin (1987) with respect to life in the following way: 'life is stronger
than organisms', that is, life goes on exactly because organisms are mor-
tal. The same is relevant to stellar evolution. We may say here that the
cosmos is stronger than stars and galaxies; and in general, evolution is
stronger than individual objects.

* **Rotation and keeping balance** take place due to constant destruction (or transition to new phases in the lifecycle) of some objects and the emergence of others. This keeps balance and creates conditions for development, because development is a result of change of generations and species.

* **In every end there is a beginning.** Star-evolutionary 'relay race'. The material of dead objects becomes building blocks for the formation of new objects. This represents the circulation of matter and energy in nature; on the other hand, this represents a sort of 'relay race'.<fnref n="7" /> The latter allows using the results of long-lasting processes (in particular, the accumulation of heavy elements).<fnref n="8" /> Thus, we deal here with the above mentioned 'creative destruction' – the creation of new objects due to the destruction of the old ones, which ensures continuity and provides new forms with space for advancement (e.g., the change of generations of biological organisms always results in certain transformations). The change of rulers may not necessarily lead to radical social changes; however, each new ruler is somehow different from his predecessor, as a result the accumulation of historical experience occurs.

* **New generations of organisms and taxa are a mode of qualitative development.** One may also detect generations of taxa, which already have significant evolutionary and systemic differences. Thus, generations of stars differ in terms of their size, chemical composition, and other characteristics. Only through the change of several generations of objects this class of objects acquires some features that, nevertheless, are considered to be typical for the whole class of objects.

## 2.2. Individuality as a way to increase evolutionary diversity

* **Individual fates within evolution.** It appears possible to maintain that with the formation of stars one observes the emergence of individ-

<footnote n="7">⁷ For more details on the 'rule of evolutionary relay race' see Grinin, Markov, and Koro-tayev 2008.</footnote>

<footnote n="8">⁸ For example, the Solar System emerged from the remnants of a supernova explosion. It is believed that due to this fact there are so many heavy and super-heavy elements on the Earth and other planets.</footnote>
ual objects in nature, ‘individuals’ that, on the one hand, are rather simi-
lar, but have rather different individual fates much depending on cir-
cumstances of their birth and various contingencies. For example, stars
with small masses (in which nuclear fusion occurs at a slow rate) can
use all of their fuel (i.e., remain in the main sequence) for many billions
of years. On the other hand, blue giants (in which the rate of fuel con-
sumption is rapid and which lose most part of their mass due to their
instability) burn out hundreds of times faster.

The stars can end their lives in a rather different way. Some of them,
having lost one or a few outer layers, would cool, slowly transforming
into cold bodies; some others may contract a few dozen times, or may
end their lives with huge explosions blowing their matter into open
space. Finally, a star may become a black hole that does not allow any
matter to come out of its immensely compressed depths.

* Ontogenesis and phylogenesis. The evolution proceeds at various levels: through the development of its certain branch, a certain class, species and so on (and sometimes even at the level of an individual organism). In addition, applying biological terminology, at every level of evolution we find a combination of processes of ontogenesis and phylogenesis. Of course, within star-galaxy evolution the phylogenesis is represented much weaker than in the evolution of life. Nevertheless, it still appears possible to speak about the history of transformation of certain types of galaxies and stars, and, hence, up to a certain extent the cosmic phylogenesis does occur (see as above with respect to change of a few generations of stars and galaxies that differ from each other as regards their size, structure, and composition).

* Required and excessive variation as conditions of a search for new evolutionary trajectories. Within the processes described above one can observe the formation of the taxonomic diversity of space objects; we may even speak about occupying the evolutionary 'niches'. There emerge different types of stars and galaxies (see above). Such diversity is extremely important. Only the achievement of a necessary level of taxonomic and other diversity allows a search for ways to new evolutionary levels. This is sometimes denoted as the rule of necessary and excessive diversity (see Grinin, Markov, and Korotayev 2008: 68–72; for more details see also Panov 2008).

* **Norm, averages, and deviation from a norm.** Only when we find a sufficient diversity, it appears possible to speak about norm, average level, exceptions, and outliers. Scientists have long known that the breakthroughs to new forms usually happen at the periphery, and in those systems that diverge from the previous mainstream.
* Continuity, which actually means the emergence of a continuum of forms, sizes, life spans, and lifecycles, is rather characteristic for space objects. Thus, the stars can be presented as a continuum from heavier to lighter ones (whereas the latter become hardly distinguishable from planets). The types of planetary systems uniformly cover a wide range of parameters. There is also a sequence of phases in the transformation of cosmic clouds into stars: condensation of clouds – formation of protostars – formation of young stars, and up to the death of stars. The continuum of forms and sizes of objects may be observed at geological, biological, and social phases of the evolution.

**2.3. Object, environment, competition, development systems, and self preservation**

* **The relations between structure and environment.** Multilevel systems (galaxy – galaxy cluster – galaxy supercluster) act as systems of a higher order for stars, and, simultaneously, they create an environment that produces an enormous influence on those stars. A star directly interacts with its immediate environment (e.g., with neighboring stars because of the strong gravity which affects the movement of both stars), whereas with the distant environment the interaction proceeds at higher levels. Within star-galaxy evolution the role of environment is generally less important than at other evolutionary levels, because single stars are separated by great distances and that is why collide rather infrequently. On the other hand, one should not underestimate the role of the environment. For example, the role of the immediate environment is very important in systems of double, triple, or multiple stars. For a small galaxy the influence of neighboring larger galaxy may turn out to be fatal, if it leads to its absorption. *External factors* play the major role in *changes* (e.g., a large cosmic body can pass by a giant molecular clouds, there can occur a star explosion, and so on) and may trigger the process of formation of stars and galaxies (by launching the gas contraction process). Collisions of cosmic bodies may create new cosmic bodies – for example, there is a hypothesis that the Moon emerged as a result of the collision of some large objects with the Earth.

With the development of a certain form of evolution, its own laws and environment gain a growing influence on the development of its objects and subjects. For example, both abiotic nature and the biotic environment influence biological organisms. However, within a complex ecological environment, it is the intraspecies and interspecies competition that may have larger influence than any other natural factors, whereas within a complex social environment it is just the social surrounding that affects individuals and social systems more than the nat-
ural forces do. Thus, with the formation of star-galaxy structure of the Universe there emerged macro-objects which start to interact with environments which are larger by many orders of magnitude.

* The urge toward self-preservation and origins of the struggle for resources. Stars, galaxies, and planets (as well as other cosmic bodies) have their definite, quite structured, and preserved form. The 'struggle' for the preservation of those forms, the capacity to live and shine, the use of different layers to minimize energy losses lead to a slow but evident evolutionary development. This way the atomic composition of the Universe changes, whereas the diversity of variations of the existence of matter increases. On the one hand, the emergence of structures that strive for their preservation creates a wide range of interaction between the system and its environment; on the other hand, this creates a basis for the 'evolutionary search' and evolutionary advancement. This evolutionary paradox – the struggle for the self-preservation is the most important source for development – can be observed here in its full-fledged form. However, star-galaxy evolution demonstrates the emergence of this driving force which will become very important in biological evolution; and it appears to be the most important driving force in social evolution. This is the struggle for resources that among stars and galaxies may proceed in the form of weakening of another object or its destruction (e.g., through a direct transfer of energy and matter from one body to another), in the form of 'incorporation', 'capturing', that is 'annexation' of stars and star clusters by larger groups. We have already mentioned above galactic coalescences. Thus, some astronomers maintain that throughout a few billions of years our galaxy has 'conquered, robbed, and submitted' hundreds of small galaxies, as there are some evident 'immigrants' within our galaxy, including the second brightest star in the northern sky, Arcturus (Gibson and Ibata 2007: 30). It is widely accepted that emergence and expansion of a black hole may lead to the 'eating' of the matter of the nearby stars and galaxies. However, the 'eating capacity' of the black holes is greatly exaggerated in popular literature. In systems of double stars or in star-planet systems one may also observe such a form of interaction as the exchange of energy and resources.

## 2.4. Multilinearity

Multilinearity is one of the most important characteristics of evolution. Unfortunately, it does not get sufficient attention, and there is a tendency to reduce evolution to a single line – the one that has produced the highest complexity level, which is often interpreted as the main line of evolu-
tion. However, at every stage of evolutionary development one can find an inter-action of a few lines that can have rather different futures. In other words, in addition to the main evolutionary line one can always identify a number of lateral ones. Firstly, they contribute to the increasing diversity; sec-ondly, they allow expanding the range of search opportunities to move to new levels of development; thirdly, the lateral lines may partly enter the main evolutionary stream, enriching it. We quite often deal with two or more coexisting and comparable lines of development whose conver-gence may lead to a quantitative breakthrough and synergetic effect. Var-ious lines of development may transform into each other. Elsewhere we have written a lot on the issue of social evolution in this context (see, e.g., Grinin and Korotayev 2009; Grinin and Korotayev 2011; Bondarenko, Grinin, and Korotayev 2011; Grinin 2011).

* **Classical forms and their analogues.** The main and lateral lines of evolution may be considered in two dimensions: 1) horizontal (as regards complexity and functions), 2) vertical (concerning the version that would be realized later at higher evolutionary phases). It appears also possible to speak about classical versions and their analogues. Thus, various forms of aggregation and specialization of unicellulars can be regarded as analogues of multicellulars (see Eskov 2006), whereas various complex stateless polities can be regarded as state analogues (see Grinin and Korotayev 2006; Grinin and Korotayev 2009; Grinin 2011 for more detail). Classical forms and their analogues can transform into each other; however, these are just the analogues that tend to transform into classical forms, rather than the other way round (the latter may be regarded as a forced adaptation to sharply changing conditions, and sometimes even as a direct degeneration).

* **Stars and molecular clouds: two parallel forms of existence of cosmic matter.** In this respect we may consider stars and galaxies as the main line of evolution and the giant clouds as its lateral lines; the former may be denoted as 'classical forms', and the latter may be designated as 'analogues'. On the one hand, those forms actually transform into each other. Galaxies and stars emerge from giant molecular clouds, whereas stars through explosions and shedding their envelopes may transform into gas-dust cloud. On the other hand, giant molecular clouds are able to concentrate; the energy exchange occurs within them, and thus, in terms of gravity and structural complexity they are quite comparable to stars and galaxies. They generally have a rather complex 'Russian nesting doll' structure, whereby smaller and denser condensations are placed within larger and sparser ones (see Surkova 2005: 48). The Russian-doll structure is also typical for higher levels of evolution. Thus, smaller groups of social and gregarious animals constitute larger groups
and tend to reproduce their structure. The same refers to social evolu-
tion, in particular to the non-centralized entities: for example, the tribal
formations, whose constituent parts (lineages, clans, and sub-tribes) of-
ten reproduce the structure (and structural principles) of the tribe. That
is why tribes can easily split and merge when necessary. The same is
true of herds of gregarious animals.

**Conclusion: The Formation of Various Evolutionary Lines  
at the Microworld Level**

**Astrophysical and astrochemical evolution.** Almost from the very be-
ginning of the development of the Universe (when the temperature
reached thousands of Kelvin) chemical evolution emerges as accompa-
nying physical and astrophysical evolution. Of course, chemical evolu-
tion also occurs within stars with the emergence of heavier elements.
However, that was rather the formation of the basis for chemical evolu-
tion, because chemical processes involve the reactions which lead to the
emergence of new substances. Such processes proceed, first of all, with-
in gas-dust clouds where molecules emerge. Hydrogen molecules are
absolutely prevalent quantitatively; however, molecules of water and
some other substances also emerged. Chemical evolution goes on also
on planets (where it combines with geological, or rather planetary evo-
lution) as well as on small celestial bodies (asteroids and meteorites).

In contrast with biological and social forms which from their very
start displayed substantially higher levels of organization of the matter,
the chemical form (that emerged a rather short time after the physical
form) did not represent a higher form of evolution for a rather long pe-
riod of time. That is not to say that chemical evolution is not important
in the framework of general stellar and galactic evolution; however, be-
fore the emergence of the Earth-like planet, the physical and chemical
forms of organization of matter should be regarded as equally impor-
tant; note also that they constantly transform into each other. The devel-
opment of astrochemical evolution is not limited by the formation of
simple nonorganic molecules. The processes of formation of molecules
proceed further towards the formation of organic substances. More than
hundred types of organic molecules have been detected in space (see
Surdin 2001; Surdin and Lamzin 1992; Shklovsky 1984). Naturally, this
facilitated the emergence of life in a rather significant way.

**The Formation of ‘Preadaptations’ as Points of Future Evolutionary Growth.** Within the star-galaxy era the chemical form of development may be regarded as a ‘preadaptation’ for new levels of evolution. Let us note that in biology the term ‘preadaptation’ denotes those adaptations that may turn out to be useful in a different environment and to give sig-
nificant advantages to those species that have them<fnref n="9" /> – and generally – to give an impulse to the formation of new taxa. Within the Big History framework, the principle of 'preadaptation' means that at the level where a preadaptation emerges, it generally plays insignificant role; however, at a new evolutionary level such 'innovations' generally give evolutionary impulses.<fnref n="10" /> Respectively, chemical compounds (as is common for preadaptations) do not mean much for cosmic evolution, they were rather 'in reserve' to reveal all their significance at the level of planetary evolution.

I would like to finish this article with a note on one more peculiarity of preadaptations. Appropriate conditions are necessary for their formation. Within biological evolution, the preadaptations often emerge in peculiar environments. Thus, it is supposed that the transformation of fins of the fleshy-finned fish (from which Amphibia descended) into primitive legs occurred within the environment of shallow waters that often dried out. In a similar way, within star-galaxy evolution the emergence of complex chemical compounds can take place only within certain structures of cosmic clouds that made their existence possible as they protected the molecules from cosmic radiation.

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# Mathematical Modeling of Biological and Social Phases of Big History

Andrey V. Korotayev and Alexander V. Markov

## Abstract

The present article demonstrates that changes in biodiversity through the Phanerozoic correlate with a hyperbolic model (widely used in demography and macrosociology) much more strongly than with exponential and logistic models (traditionally used in population biology and extensively applied to fossil biodiversity as well). The latter models imply that changes in diversity are guided by a first-order positive feedback (more ancestors – more descendants) and/or a negative feedback arising from resource limitation. The hyperbolic model implies a second-order positive feedback. The authors demonstrate that the hyperbolic pattern of the world population growth arises from a second-order positive feedback between the population size and the rate of technological growth (this can also be identified with the collective learning mechanism). The feedback between the diversity and community structure complexity can also contribute to the hyperbolic character of biodiversity. This suggests that some mechanisms vaguely resembling the collective learning might have operated throughout the biological phase of Big History. Our findings suggest that we can trace rather similar macropatterns within both the biological and social phases of Big History which one can describe in a rather accurate way with very simple mathematical models.

**Keywords:** biological phase of Big History, social phase of Big History, mathematical modeling, collective learning, positive feedback, biodiversity, demography, sociology, paleontology, geology, hyperbolic growth.

In 2005, in the town of Dubna, near Moscow, at what seems to have been the first ever international conference devoted specifically to Big History studies, the two authors of the present article – sociologist/anthropologist Andrey Korotayev and biologist/paleontologist Alexander Markov – one after another demonstrated two diagrams.<fnref n="1" /> One of those diagrams illustrated the dynamics of the population of China between 700 BCE and 1851 CE, the other illustrated the dynamics

<footnote n="1">¹ We would like to emphasize that we saw each other at that session for the first time, so we had no chance to arrange in advance the demonstration of those two diagrams.</footnote>
of marine Phanerozoic biodiversity during the last 542 million years (see
Fig. 1):

<figure><img src="image_6.png" /><figcaption>**Fig. 1.** Similarity of the dynamics of Phanerozoic marine biodiversity and long-term population dynamics of China: **a** – Population dynamics of China (million people, 700 BCE – 1851 CE), based on estimates in Korotayev, Malkov, and Khaltourina (2006b: 47–88); **b** – Global change in marine biodiversity (number of genera, N) through the Phanerozoic based on empirical data surveyed in Markov and Korotayev (2007a)</figcaption></figure>
Nevertheless, one can hardly ignore the striking similarity between two diagrams depicting the development of rather different systems (human population, on the one hand, and biota, on the other) at different time scales (hundreds of years, on the one hand, and millions of years, on the other) studied by different sciences (Historical Demography, on the one hand, and Paleontology, on the other) using different sources (demographic estimates, on the one hand, and paleontological chronicles, on the other hand). What are the causes of this similarity in the development dynamics of rather different systems?

* * *

In 1960, von Foerster, Mora, and Amiot published a striking discovery in the journal *Science*. They showed that between 1 and 1958 CE the world's population (N) dynamics can be described in an extremely accurate way with an astonishingly simple equation:<fnref n="2" />

$$N_t = \frac{C}{t_0 - t}, \qquad (1)$$

where $N_t$ is the world population at time $t$, and $C$ and $t_0$ are constants, with $t_0$ corresponding to an absolute limit ('singularity' point) at which N would become infinite.

Of course, von Foerster and his colleagues did not imply that one day the world population would actually become infinite. The real implication was that prior to 1960 the world population growth for many centuries had followed a pattern which was about to come to an end and to transform into a radically different pattern. Note that this prediction started to come true only a few years after the 'Doomsday' paper had been published, because *after the early 1970s the World System growth in general (and world population growth in particular) began to diverge more and more from the blow-up regime, and now it is not hyperbolic any more with its pattern being closer to a logistic one* (see, e.g., Korotayev, Malkov, and Khaltourina 2006a, where we present a compact mathematical model that describes both the hyperbolic development of the World System in the period prior to the early 1970s, and its withdrawal from the blow-up regime in the subsequent period; see also Korotayev 2009).

<footnote n="2">² To be exact, the equation proposed by von Foerster and his colleagues looked as follows:
$$N_t = \frac{C}{(t_0 - t)^{0.99}}$$
However, as von Hoerner (1975) and Kapitza (1999) showed, it can be simplified as $N_t = \frac{C}{t_0 - t}$.</footnote>
Parameter $t_0$ was estimated by von Foerster and his colleagues as 2026.87, which corresponded to November 13, 2006; this allowed them to give their article an attractive and remarkable title – ‘Doomsday: Friday, 13 November, A.D. 2026’.

The overall correlation between the curve generated by the von Foerster equation and the most detailed series of empirical estimates looks as follows (see Fig. 2).

<figure><img src="image_7.png" /><figcaption>**Fig. 2.** Correlation between empirical estimates of world population (in millions, AD 1000–1970) and the curve generated by the von Foerster equation</figcaption></figure>

*Note:* black markers correspond to empirical estimates of the world population by McEvedy and Jones (1978) for the interval between 1000 and 1950 and the U.S. Bureau of the Census (2014) for 1950–1970. The grey curve has been generated by the von Foerster equation (1).

The formal characteristics are as follows: $R = 0.998$; $R^2 = 0.996$; $p = 9.4 \times 10^{-17} \approx 1 \times 10^{-16}$. For readers unfamiliar with mathematical statistics we can explain that $R^2$ can be regarded as a measure of the fit between the dynamics generated by a mathematical model and the empirically observed situation, and can be interpreted as the proportion of the variation accounted for by the respective equation. Note that 0.996 also can be expressed as 99.6 per cent.<fnref n="3" /> Thus, the von Foerster equation

<footnote n="3">³ The second characteristic ($p$, standing for ‘probability’) is a measure of the correlation's statistical significance. A bit counter-intuitively, the lower the value of $p$, the higher the statistical significance of the respective correlation. This is because $p$ indicates the probability that the observed correlation could be accounted solely by chance. Thus, $p = 0.99$</footnote>
accounts for an astonishing 99.6 per cent of all the macrovariation in the world population, from 1000 CE through 1970, as estimated by McEvedy and Jones (1978) and the U.S. Bureau of the Census (2014).<fnref n="4" />

Note also that the empirical estimates of world population align in an extremely accurate way along the hyperbolic curve, which convincingly justifies the designation of the pre-1970s world population growth pattern as ‘hyperbolic’.

To start with, the von Foerster equation $N_t = \frac{C}{t_0 - t}$ is just a solution

of the following differential equation (see, e.g., Korotayev, Malkov, Khaltourina 2006a: 119–20):

$$ \frac{dN}{dt} = \frac{N^2}{C}. \qquad (2) $$

This equation can be also written as:

$$ \frac{dN}{dt} = aN^2, \qquad (3) $$

where $a = \frac{1}{C}$.

What is the meaning of this mathematical expression, $\frac{dN}{dt} = aN^2$? In

our case, $dN/dt$ denotes an absolute population growth rate at a certain moment of time. Thus, this equation shows that at any moment of time an absolute population growth rate should be proportional to the square of population at this moment.

Note that this significantly demystifies the problem of the world population hyperbolic growth. Now to explain this hyperbolic growth, we should just explain why for many millennia the absolute rate

<footnote>indicates an extremely low statistical significance, as it means that there are 99 chances out of 100 that the observed correlation is the result of a coincidence, and, thus, we can be quite confident that there is no systematic relationship (at least, of the kind that we study) between the two respective variables. On the other hand, $p = 1 \times 10^{-16}$ indicates an extremely high statistical significance for the correlation, as it means that there is only one chance out of 10000000000000000 that the observed correlation is the result of pure coincidence (in fact, a correlation is usually considered as statistically significant with $p < 0.05$).</footnote>

<footnote n="4">⁴ In fact, with slightly different parameters ($C = 164890.45$; $t_0 = 2014$) the fit ($R^2$) between the dynamics generated by the von Foerster equation and the macrovariation of world population for CE 1000–1970 as estimated by McEvedy and Jones (1978) and the U.S. Bureau of the Census (2014) reaches 0.9992 (99.92 per cent), whereas for 500 BCE – 1970 CE this fit increases to 0.9993 (99.93 per cent) (with the following parameters: $C = 171042.78$; $t_0 = 2016$).</footnote>
of world population growth tended to be proportional to the square of
population.

The main mathematical models of the hyperbolic pattern of the
world's population growth (Taagapera 1976, 1979; Kremer 1993; Cohen
1995; Podlazov 2004; Tsirel 2004; Korotayev 2005, 2007, 2008, 2009, 2012;
Korotayev, Malkov, and Khaltourina 2006a: 21–36; Khaltourina,
Malkov, and Korotayev 2006; Golosovsky 2010; Korotayev and Malkov
2012) are based on the following two assumptions:

1) ‘the Malthusian (1978 [1978]) assumption that population is limited by the available technology, so that the growth rate of population is proportional to the growth rate of technology’ (Kremer 1993: 681–682).<fnref n="5" /> This statement seems rather convincing. Indeed, throughout most of human history the world population was limited by the technologically determined ceiling of land carrying capacity. For example, with foraging subsistence technologies the Earth could hardly support more than 8 million people, because the amount of naturally available useful biomass on the planet is limited, and the world population could overgrow this limit only when people started to apply various means to artificially increase the amount of available biomass, that is with a transition from foraging to food production. However, the extensive agriculture can only support a limited number of people, and world population further growth became possible only with the intensification of agriculture and other technological improvements (see, e.g., Turchin 2003; Korotayev, Malkov, and Khaltourina 2006a, 2006b; Korotayev and Khaltourina 2006).

However, it is well known that the technological level is not a con-
stant, but a variable (see, e.g., Grinin 2007a, 2007b, 2012). And in order to
describe its dynamics the second basic assumption is employed:

2) ‘High population spurs technological change because it increases the number of potential inventors…<fnref n="6" /> In a larger population there will be proportionally more people lucky or smart enough to come up with new ideas’ (Kremer 1993: 685), thus, ‘the growth rate of technology is proportional to total population’.<fnref n="7" /> In fact, here Kremer uses the main

<footnote n="5">⁵ In addition to this, the absolute growth rate is proportional to the population number – with a given relative growth rate a larger population will increase more in absolute numbers than a smaller one.</footnote>

<footnote n="6">⁶ ‘This implication flows naturally from the non-rivalry of technology… The cost of inventing a new technology is independent of the number of people who use it. Thus, holding constant the share of resources devoted to research, an increase in population leads to an increase in the probability of technological change’ (Kremer 1993: 681); note that in the framework proposed by David Christian (2005) this corresponds precisely to the pattern of collective learning.</footnote>

<footnote n="7">⁷ Note that ‘the growth rate of technology’ means here the relative growth rate (i.e. the level to which technology will grow in a given unit of time in proportion to the level observed at</footnote>
assumption of the Endogenous Technological Growth theory (Kuznets 1960; Grossman and Helpman 1991; Aghion and Howitt 1998; Simon 1977, 2000; Komlos and Nefedov 2002; Jones 1995, 2005, etc.). To our knowledge, this supposition was first put forward by Simon Kuznets (1960), so we will denote a corresponding type of dynamics as 'Kuznetsian', while the systems in which the 'Kuznetsian' population-technological dynamics combines with the 'Malthusian' demographic one will be denoted as 'Malthusian-Kuznetsian'. In general, we find this assumption rather plausible – in fact, it is quite probable that, ceteris paribus, within a given period of time, a billion people will make approximately a thousand times more inventions than a million people.

This assumption was expressed by Kremer mathematically in the following way:

$$ \frac{dT}{dt} = kNT \quad (4) $$

Actually, this equation just says that the absolute technological growth rate at a given moment of time ($dT/dt$) is proportional to the technological level ($T$) observed at this moment (the wider is the technological base, the more inventions could be made on its basis), and, on the other hand, it is proportional to the population ($N$) (the larger the population, the larger the number of potential inventors).<fnref n="8" />

The resultant models provide a rather convincing explanation of *why* throughout most of human history the world population followed the hyperbolic pattern with an absolute population growth rate tending to be proportional to $N^2$. For example, why would the growth of population from, say, 10 million to 100 million, result in the hundredfold growth of $dN/dt$? The above mentioned models explain this rather convincingly. The point is that the growth of world population from ten to a hundred million implies that human subsistence technologies also grew approximately ten times (given that it will prove, after all, to be able to support a ten times larger population). On the other hand, the tenfold population growth also implies a tenfold growth of the number of potential inventors, and, consequently, a tenfold increase in a relative technological growth rate. Hence, the absolute technological growth rate would grow $10 \times 10 = 100$ times (as Equation 4 shows that an order of magnitude larger number of people with an order of magnitude broader technological basis would likely make two orders of magnitude more inven-

<footnote>the beginning of this period).</footnote>

<footnote n="8">⁸ Kremer did not test this hypothesis empirically in a direct way. Note, however, that our own empirical test of this hypothesis has supported it (see Korotayev, Malkov, Khal-tourina 2006b: 141–146).</footnote>
tions). And as throughout the Malthusian epoch the world population (N) tended to the technologically determined carrying capacity ceiling of the Earth, we have good reason to expect that $dN/dt$ will also grow just about 100 times.

In fact, one can demonstrate (see, e.g., Korotayev, Malkov, and Khaltourina 2006a, 2006b; Korotayev and Khaltourina 2006) that the hyperbolic pattern of the world's population growth can be explained by the nonlinear second order positive feedback mechanism that was shown long ago to generate just the hyperbolic growth, known also as the 'blow-up regime' (see, e.g., Kurdyumov 1999). In our case this nonlinear second order positive feedback looks as follows: more people – more potential inventors – a faster technological growth – a faster growth of the Earth's carrying capacity – a faster population growth – with more people you also have more potential inventors – hence, faster technological growth, and so on (see Fig. 3).

<figure><img src="image_8.png" /><figcaption>Fig. 3. Cognitive scheme of the nonlinear second order positive feedback between technological development and demographic growth</figcaption></figure>

Note that the relationship between technological development and demographic growth cannot be analyzed through any simple cause-and-effect model, as we observe a true dynamic relationship between these two processes – each of them is both the cause and the effect of the other.

Note also that the process discussed above should be identified with the process of collective learning (on the notion of 'collective learning' see first of all Christian 2005: 146–148; see also David Christian's and David Baker's contributions to the present volume). Respectively, the mathematical models of the World System development discussed in this article can be interpreted as mathematical models of the influence of collective learning on the global social evolution. Thus, a rather peculiar hyperbolic shape of the acceleration of the global development observed prior to the early 1970s may be regarded just as a product of the global collective learning. Elsewhere we have also shown (Korotayev, Malkov, and
Khaltourina 2006a: 34–66) that for the period prior to the 1970s the World System economic and demographic macrodynamics driven by the above mentioned positive feedback loops can be described mathematically in a rather accurate way with the following extremely simple mathematical model:

$$ \frac{dN}{dt} = aSN, \qquad (5) $$

$$ \frac{dS}{dt} = bNS, \qquad (6) $$

while the world GDP (G) can be calculated using the following equation:

$$ G = mN + SN, \qquad (7) $$

where G is the world GDP, N is population, and S is the produced surplus per capita, over the subsistence amount (m) that is minimally necessary to reproduce the population with a zero growth rate in a Malthusian system (thus, S = g - m, where g denotes per capita GDP); a and b are parameters.

Note that the mathematical analysis of the basic model (not presented here) suggests that up to the 1970s the amount of S (per capita surplus produced at the given level of World System development) should be proportional, in the long run, to the World System's population: S = kN. Our statistical analysis of the available empirical data has confirmed this theoretical proportionality (Korotayev, Malkov, and Khaltourina 2006a: 49–50). Thus, in the right-hand side of equation (6) S can be replaced with kN, and as a result we arrive at the following equation:

$$ \frac{dN}{dt} = kaN^2. \qquad (3) $$

As we remember, the solution of this type of differential equations is

$$ N_t = \frac{C}{(t_0 - t)}, \qquad (1) $$

and this produces simply a hyperbolic curve.

As, according to our model, S can be approximated as kN, its long-term dynamics can be approximated with the following equation:

$$ S = \frac{kC}{t_0 - t}. $$

Thus, the long-term dynamics of the most dynamic component of the world GDP, SN, 'the world surplus product', can be approximated as follows:
$$SN = \frac{kC^2}{(t_0 - t)^2}. \qquad (8)$$

Of course, this suggests that the long-term world GDP dynamics up to the early 1970s must be approximated better by a quadratic hyperbola than by a simple one; and, as we could see below (see Fig. 4), this approximation works very effectively indeed:

<figure><img src="image_9.png" /><figcaption>Fig. 4. World GDP Dynamics, 1–1973 CE (in billions of 1990 international dollars, PPP): the fit between predictions of a quadratic-hyperbolic model and the observed data</figcaption></figure>

Note: R = .9993, R² = .9986, p << .0001. The black markers correspond to Maddison's (2001) estimates (Maddison's estimates of the world per capita GDP for 1000 CE has been corrected on the basis of [Meliantsev 2004]). The grey solid line has been generated by the following equation:

$$G = \frac{17749573.1}{(2006 - t)^2}.$$

Thus, up to the 1970s the hyperbolic growth of the world population was accompanied by the quadratic-hyperbolic growth of the world GDP, just as our model suggests. Note that the hyperbolic growth of the world population and the quadratic-hyperbolic growth of the world GDP are tightly interconnected processes, actually two sides of the same coin, two dimensions of one process propelled by the nonlinear second
order positive feedback loops between the technological development and demographic growth (see Fig. 5).

<figure><img src="image_10.png" /><figcaption>Fig. 5. Cognitive Scheme of the Generation of Quadratic-Hyperbolic Trend of the World Economic Growth by the Nonlinear Second Order Positive Feedback between Technological Development and Demographic Growth</figcaption></figure>

We have also demonstrated (Korotayev, Malkov, and Khaltourina 2006a: 67–80) that the dynamics of the World System population's literacy (l) is rather accurately described by the following differential equation:

$$ \frac{dl}{dt} = aSl (1-l), \qquad (9) $$

where l is the proportion of the population that is literate, S is per capita surplus, and a is a constant. In fact, this is a version of the autocatalytic model. It has the following sense: the increasing literacy is proportional to the fraction of the population that is literate, l (potential teachers), to the fraction of the population that is illiterate, (1 - l) (potential pupils), and to the amount of per capita surplus S, since it can be used to support educational programs (in addition to this, S reflects the technological level T that implies, among other things, the level of development of educational technologies). Note that, from a mathematical point of view, Equation 9 can be regarded logistic where saturation is reached at literacy level l = 1, and S is responsible for the speed with which this level is approached.
It is important to emphasize that with low values of l (which correspond to most part of human history except for the recent decades), the increasing rate of the world literacy generated by this model (against the background of hyperbolic growth of S) can be approximated rather accurately as hyperbolic (see Fig. 6).

<figure><img src="image_11.png" /><figcaption>**Fig. 6.** World Literacy Dynamics, 1 – 1980 CE (%): the fit between predictions of the hyperbolic model and the observed data</figcaption></figure>

*Note:* R = 0.997, R² = 0.994, *p* << 0.0001. Black dots correspond to UNESCO/World Bank (2014) estimates for the period after 1970, and to Meliantsev's (2004) estimates for the earlier period. The grey solid line has been generated by the following equation:

$$l_t = \frac{3769.264}{(2040 - t)^2}$$

The best-fit values of parameters C (3769.264) and t₀ (2040) have been calculated with the least squares method.

The overall number of literate people is proportional both to the literacy level and to the overall population. As both of these variables experienced a hyperbolic growth until the 1960s/1970s, one has sufficient grounds to expect that until recently the overall number of literate people in the world (L)<fnref n="9" /> grew not just hyperbolically, but rather in a quadratic-hyperbolic way (as the world GDP did). Our empirical test has confirmed this – the quadratic-hyperbolic model describes the growth of

<footnote n="9">⁹ Since literacy appeared, almost all of the Earth's literate population has lived within the World System; hence, the literate population of the Earth and the literate population of the World System have been almost perfectly synonymous.</footnote>
the literate population of the planet with an extremely good fit indeed (see Fig. 7).

<figure><img src="image_12.png" /><figcaption>Fig. 7. World Literate Population Dynamics, 1–1980 CE (L, millions): the fit between predictions of the quadratic-hyperbolic model and the observed data</figcaption></figure>

Note: R = 0.9997, R² = 0.9994, p << 0.0001. The black dots correspond to UNESCO/World Bank (2014) estimates for the period since 1970, and to Meliantsev's (2004) estimates for the earlier period; we have also taken into account the changes of age structure on the basis of UN Population Division (2014) data. The grey solid line has been generated by the following equation:

$$L_t = \frac{4958551}{(2033 - t)^2}$$

The best-fit values of parameters C (4958551) and t₀ (2033) have been calculated with the least squares method.

Similar processes are observed with respect to world urbanization, whose macro dynamics appears to be described by the differential equation:

$$\frac{du}{dt} = bSu(u_{\lim} - u),$$

where u is the proportion of the population that is urban, S is per capita surplus produced with the given level of the World System's technological development, b is a constant, and $u_{\lim}$ is the maximum possible proportion of the urban population. Note that this model implies that during the blow-up regime of the 'Malthusian-Kuznetsian' era, the hyperbolic growth of world urbanization must have been accompanied by a quadratic-hyperbolic growth of the urban population of the world, which is supported by our empirical tests (see Figs 8–9).
<figure><img src="image_13.png" /><figcaption>Fig. 8. World Megaurbanization Dynamics (% of the world population living in cities with > 250 thousand inhabitants), 10000 BCE – 1960 CE: the fit between predictions of the hyperbolic model and empirical estimates</figcaption></figure>

Note: R = 0.987, R² = 0.974, p << 0.0001. The black dots correspond to Chandler's (1987) estimates, UN Population Division (2014), Modelski (2003), and Gruebler (2006). The grey solid line has been generated by the following equation:

$$u_t = \frac{403.012}{(1990 - t)}$$

The best-fit values of parameters C (403.012) and t₀ (1990) have been calculated with the least squares method. For comparison, the best fit (R²) obtained here for the exponential model is 0.492.
<figure><img src="image_14.png" /><figcaption>Fig. 9. Dynamics of World Urban Population Living in Cities with more than 250,000 Inhabitants (mlns), 10000 BCE – 1960 CE: the fit between predictions of the quadratic-hyperbolic model and the observed data</figcaption></figure>

Note: R = 0.998, R² = 0.996, p << 0.0001. The black markers correspond to estimates of Chandler (1987) and UN Population Division (2014). The grey solid line has been generated by the following equation:

$$U_t = \frac{912057.9}{(2008 - t)^2}$$

The best-fit values of parameters C (912057.9) and t₀ (2008) have been calculated with the least squares method. For comparison, the best fit (R²) obtained here for the exponential model is 0.637.

Within this context it is hardly surprising that the general macro dynamics of the size of the largest settlement within the World System is also quadratic-hyperbolic (see Fig. 10).
<figure><img src="image_15.png" /><figcaption>Fig. 10. Dynamics of Size of the Largest Settlement of the World (thousands of inhabitants), 10000 BCE – 1950 CE: the fit between predictions of the quadratic-hyperbolic model and the observed data</figcaption></figure>

Note: R = 0.992, R² = 0.984, p << 0.0001. The black markers correspond to estimates of Modelski (2003) and Chandler (1987). The grey solid line has been generated by the following equation:

$$U_{\max t} = \frac{104020618.573}{(2040 - t)^2}$$

The best-fit values of parameters C (104020618.5) and t₀ (2040) have been calculated with the least squares method. For comparison, the best fit (R²) obtained here for the exponential model is 0.747.

As has been demonstrated by cross-cultural anthropologists (see, e.g., Naroll and Divale 1976; Levinson and Malone 1980: 34), for pre-agrarian, agrarian, and early industrial cultures the size of the largest settlement is a rather effective indicator of the general sociocultural complexity of a social system. This, of course, suggests that in the ‘Malthusian-Kuznetsian’ era the World System's general sociocultural complexity also increased, in a generally quadratic-hyperbolic way.

As we have noted in the beginning, the dynamics of marine biodiversity is strikingly similar to the population dynamics in China, the country with the best-known demographic history.

The similarity probably stems from the fact that both curves are produced by the interference of the same three components (general
hyperbolic trend, as well as cyclical and stochastic dynamics). In fact, there is a lot of evidence that some aspects of biodiversity dynamics are stochastic (Raup *et al.* 1973; Sepkoski 1994; Markov 2001a; Markov 2001b; Cornette and Lieberman 2004), while others are periodic (Raup and Sepkoski 1984; Rohde and Müller 2005). On cyclical and stochastic components of the long-term population dynamics of China (as well as other complex agrarian societies) see, e.g., Korotayev and Khaltourina 2006; Korotayev, Malkov, and Khaltourina 2006b; Chu and Lee 1994; Nefedov 2004; Turchin 2003, 2005a, 2005b; Turchin and Korotayev 2006; Turchin and Nefedov 2009; Usher 1989; Komlos and Nefedov 2002; Grinin, Korotayev and Malkov 2008; Grinin *et al.* 2009; Grinin 2007c; Korotayev 2006; Korotayev, Khaltourina, and Bozhevolnov 2010; Korotayev *et al.* 2010; van Kessel-Hagesteijn 2009; Abel 1980; Braudel 1973; Goldstone 1991; Grinin, Korotayev 2012 *etc*.).

In fact, similarly to what we have observed with respect to the world population dynamics, even before the start of its intensive modernization, the population dynamics of China was characterized by a pronounced hyperbolic trend – as we can see below (see Figs 11 and 12), the hyperbolic model describes traditional Chinese population dynamics *much* more accurately than either linear or exponential models do:

<figure><img src="image_16.png" /><figcaption>**Fig. 11.** Population Dynamics of China (million people), 57–1851 CE: fit with linear and exponential models</figcaption></figure>

*Note*: based on calculations in Korotayev, Malkov, and Khaltourina 2006b: 47–88.
<figure><img src="image_17.png" /><figcaption>Fig. 12. Population Dynamics of China (million people), 57–1851 CE: fit with a hyperbolic model</figcaption></figure>

The hyperbolic model turns out to describe mathematically the population dynamics of China in an especially accurate way with respect to the modern period (see Fig. 13).

<figure><img src="image_18.png" /><figcaption>Fig. 13. Population Dynamics of China (million people), 57–2003 CE: fit with a hyperbolic model</figcaption></figure>

Note: based on calculations in Korotayev, Malkov, and Khaltourina 2006b: 47–88.
In a rather similar way the hyperbolic model turns out to describe the marine biodiversity (measured by number of genera) through the Phanerozoic much more accurately than the exponential one (see Fig. 14):

<figure><img src="image_19.png" /><figcaption>**Fig. 14.** Global Change in Marine Biodiversity (Number of Genera, N) through Phanerozoic</figcaption></figure>

*Note*: based on empirical data surveyed in Markov and Korotayev (2007).

When measured in terms of species number the fit between the empirically observed marine biodiversity dynamics and the hyperbolic model becomes even better (see Fig. 15):

<figure><img src="image_20.png" /><figcaption>**Fig. 15.** Global Change in Marine Biodiversity (Number of Species, N) through Phanerozoic</figcaption></figure>

*Note*: based on empirical data surveyed in Markov and Korotayev (2007b).
The hyperbolic model describes the continental biodiversity in an especially accurate way (see Fig. 16).

<figure><img src="image_21.png" /><figcaption>Fig. 16. Global Change in Continental Biodiversity (Number of Genera, N) through Phanerozoic</figcaption></figure>

Note: based on empirical data surveyed in Markov and Korotayev 2007b.

However, the highest fit between the hyperbolic model and the empirical data is observed when the hyperbolic model is used to describe the dynamics of total (marine and continental) global biodiversity (see Fig. 17).

<figure><img src="image_22.png" /><figcaption>Fig. 17. Global Change in Total (Marine + Continental) Biodiversity (Number of Genera, N) through Phanerozoic</figcaption></figure>

Note: based on empirical data surveyed in Markov and Korotayev 2007b.
As we see, the hyperbolic dynamics is most prominent when both ma-
rine and continental biotas are considered together. This fact can be in-
terpreted as a proof of the integrated nature of the biosphere.

But why throughout the Phanerozoic did the global biodiversity
tend to follow the hyperbolic trend (similarly to what we observed
within social World System in general and China in particular)?

As we have noted above, in macrosociological models, the hyperbolic pattern of the world population growth arises from a non-linear second-order positive feedback (more or less identical with the mechanism of collective learning) between the demographic growth and technological development (more people – more potential inventors – faster technological growth – the carrying capacity of the Earth grows faster – faster population growth – more people – more potential inventors, and so on).

Based on the analogy with macrosociological models and diverse
paleontological data, we suggest that the hyperbolic character of biodi-
versity growth can be similarly accounted for by a non-linear second-
order positive feedback<fnref n="10" /> between the diversity growth and community
structure complexity (more genera – higher alpha diversity – the com-
munities become more stable and ‘buffered’– average life span of genera
grows; extinction rate decreases – faster diversity growth – more gen-
era – higher alpha diversity, and so on).

The growth of genus richness through the Phanerozoic was mainly
due to the increase of average longevity of genera and gradual accumu-
lation of long-lived (stable) genera in the biota. This pattern reveals it-
self in the decrease of extinction rate. Interestingly, in both biota and
humanity, growth was facilitated by the decrease in mortality rather
than by the increase in birth rate. The longevity of newly arising genera
was growing in a stepwise manner. The most short-lived genera ap-
peared during the Cambrian; more long-lived genera appeared in Or-
dovician to Permian; the next two stages correspond to the Mesozoic
and Cenozoic (Markov 2001a, 2002).We suggest that diversity growth
can facilitate the increase in genus longevity via the progressive step-
wise changes in the structure of communities.

Most authors agree that there were three major biotic changes that
resulted in fundamental reorganization of community structure during
the Phanerozoic: Ordovician radiation, end-Permian extinction, and
end-Cretaceous extinction (Bambach 1977; Sepkoski *et al.* 1981; Sepkoski
1988, 1992; Markov 2001a; Bambach *et al.* 2002). Generally, after each

<footnote n="10">¹⁰ One wonders if it cannot be regarded as a (rather imperfect) analogue of the collective learning mechanism that plays such an important role within the social macroevolution.</footnote>
major crisis the communities became more complex, diverse and stable. The stepwise increase of alpha diversity (average number of species or genera in a community) through the Phanerozoic was demonstrated by Bambach (1977) and Sepkoski (1988). Although Powell and Kowalewski (2002) argued that the observed increase in alpha diversity might be an artifact caused by several specific biases that influenced the taxonomic richness of different parts of the fossil record, there is evidence that these biases largely compensated each other, so that the observed increase in alpha diversity was probably underestimated rather than overestimated (Bush and Bambach 2004).

Another important symptom of progressive development of communities is the increase in evenness of distribution of species (or genus) abundances. In the primitive, pioneer or suppressed communities, this distribution is strongly uneven (community is overwhelmingly dominated by a few very abundant species). In more advanced, climax or flourishing communities, this distribution is more even (Magurran 1988). The former type of community is generally more vulnerable. Evenness of distribution of species richness in communities increased substantially during the Phanerozoic (Powell and Kowalewski 2002; Bush and Bambach 2004). Most probably there was also an increase in habitat utilization, total biomass and rate of trophic flow in biota through the Phanerozoic (Powell and Kowalewski 2002).

The more complex the community, the more stable it is due to the development of effective interspecies interactions and homeostatic mechanisms based on the negative feedback principle. In a complex community, when the abundance of a species decreases, many factors arise that facilitate its recovery (e.g., there will be more food and fewer predators). Even if a species becomes extinct, its vacant niche may 'recruit' another species, most probably a related one that may acquire morphological similarity with its predecessor and thus, the taxonomists will assign it to the same genus. So a complex community can facilitate the stability (and longevity) of its components, such as niches, taxa and morphotypes. This effect reveals itself in the phenomenon of 'coordinated stasis': the fossil record shows many examples of persistence of particular communities for many million years while the rates of extinction and taxonomic turnover are minimized (Brett *et al.* 1996, 2007).

Selective extinction leads to accumulation of 'extinction-tolerant' taxa in the biota (Sepkoski 1991b). Although there is evidence that mass extinctions can be non-selective in some aspects (Jablonski 2005), they are obviously highly selective with respect to the ability of taxa to endure unpredictable environmental changes. This can be seen, for in-
stance, from the selectivity of the end-Cretaceous mass extinction with
respect to the time of the first occurrence of genera. In younger cohorts
the extinction level was higher compared to the older cohorts (see
Markov and Korotayev 2007a: Fig. 2). The same pattern can be observed
during the periods of 'background' extinction as well (Markov 2000).
This means that genera differ in their ability to survive the extinction
events, and that in the course of time the extinction-tolerant genera ac-
cumulate in each cohort. Thus, taxa generally become more stable and
long-lived in the course of evolution, apart from the effects of communi-
ties. The communities composed of more stable taxa would be, in turn,
more stable themselves, thus creating a positive feedback.

The stepwise change of dominant taxa plays a major role in biotic
evolution. This pattern is maintained not only by the selectivity of ex-
tinction (discussed above), but also by the selectivity of the recovery
after crises (Bambach et al. 2002). The taxonomic structure of the Phanero-
zoic biota was changing in a stepwise way, as demonstrated by the concept
of three sequential 'evolutionary faunas' (Sepkoski 1992). There were also
stepwise changes in the proportion of major groups of animals with differ-
ent ecological and physiological parameters. There was a stepwise growth
in proportion of motile genera compared to non-motile; 'physiologically
buffered' genera compared to 'unbuffered', and predators compared to
prey (Bambach et al. 2002). All these trends should have facilitated the
stability of communities (e.g., diversification of predators implies that
they become more specialized; a specialized predator regulates its prey's
abundance more effectively than a non-specialized predator).

There is also another possible mechanism of the second-order posi-
tive feedback between the diversity and its growth rate. Recent research
has demonstrated a shift in typical relative-abundance distributions in
paleocommunities after the Paleozoic (Wagner *et al.* 2006). One possible
interpretation of this shift is that the community structure and the inter-
actions between species in the communities became more complex.
In the post-Paleozoic communities, new species probably increase eco-
logical space more efficiently, either by facilitating opportunities for ad-
ditional species or by niche construction (Wagner *et al.* 2006; Solé *et al.*
2002; Laland *et al.* 1999). This possibility makes the mechanisms under-
lying the hyperbolic growth of biodiversity and human population even
more similar, because the total ecological space of the biota is analogous
to the 'carrying capacity of the Earth' in demography. As far as new
species can increase ecological space and facilitate opportunities for ad-
ditional species entering the community, they are analogous to the 'in-
mentors' of the demographic models whose inventions increase the carrying capacity of the Earth.

Exponential and logistic models of biodiversity imply several possible ways in which the rates of origination and extinction may change through time (Sepkoski 1991a). For instance, exponential growth can be derived from constant per-taxon extinction and origination rates the latter being higher than the former. However, actual paleontological data suggest that origination and extinction rates did not follow any distinct trend through the Phanerozoic, and their changes over time look very much like chaotic fluctuations (Cornette and Lieberman 2004). Therefore, it is more difficult to find a simple mathematical approximation for origination and extinction rates than for the total diversity. In fact, the only critical requirement of the exponential model is that the difference between the origination and extinction through time should be proportional to the current diversity level:

$$ (N_o - N_e)/\Delta t \approx kN, \qquad (11) $$

where $N_o$ and $N_e$ are the numbers of genera with, respectively, first and last occurrences within the time interval $\Delta t$, and $N$ is mean diversity level in the interval. The same is true for the hyperbolic model. It does not predict the exact way in which origination and extinction should change, but it does predict that their difference should be roughly proportional to the square of the current diversity level:

$$ (N_o - N_e)/\Delta t \approx kN^2. \qquad (12) $$

In demographic models discussed above, the hyperbolic growth of the world population was not decomposed into separate trends of birth and death rates. The main driving force of this growth is presumably the increase of the Earth's carrying capacity and the way this capacity is realized – either by decreasing death rate, or by increasing birth rate, or both – depends upon many factors and may vary from time to time.

The same is probably true for biodiversity. The overall shape of the diversity curve depends mostly on the differences in the mean rates of diversity growth in the Paleozoic (low), Mesozoic (moderate), and Cenozoic (high). The Mesozoic increase was mainly due to lower extinction rate (compared to the Paleozoic), while the Cenozoic increase was largely due to higher origination rate (compared to the Mesozoic) (see Markov and Korotayev 2007a: 316, Figs 3a, 3b). This probably means that the acceleration of diversity growth during the last two eras was driven by different mechanisms of positive feedback between diversity and its growth rate. Generally, the increment rate $((N_o - N_e)/\Delta t)$ was changing in a more regular way than the origination rate $N_o/\Delta t$ and extinction rate $N_e/\Delta t$. The large-scale changes in the increment rate cor-
relate better with $N^2$ than with $N$ (Ibid.: figs 3c and 3d), thus supporting
the hyperbolic rather than the exponential model.

Conclusion

In macrosociological models the hyperbolic pattern of the world popu-
lation growth arises from a non-linear second-order positive feedback
between the demographic growth and technological development
(more people - more potential inventors - faster technological growth -
the carrying capacity of the Earth grows faster - faster population
growth - more people - more potential inventors, and so on, which is
more or less identical with the working of the collective learning
mechanism). Based on the analogy with macrosociological models and
diverse paleontological data, we suggest that the hyperbolic character of
biodiversity growth can be similarly accounted for by a non-linear sec-
ond-order positive feedback between the diversity growth and commu-
nity structure complexity (which suggests the presence within the bio-
sphere of a certain analogue of the collective learning mechanism). The
feedback can work via two parallel mechanisms: 1) decreasing extinc-
tion rate (more taxa - higher is the alpha diversity, or mean number of
taxa in a community - communities become more complex and stable -
extinction rate decreases - more taxa, and so on), and 2) increasing
origination rate (new taxa facilitate niche construction; newly formed
niches can be occupied by the next 'generation' of taxa). The latter
makes the mechanisms underlying the hyperbolic growth of biodiver-
sity and human population even more similar, because the total eco-
space of the biota is analogous to the 'carrying capacity of the Earth' in
demography. As far as new species can increase ecospace and facilitate
opportunities for additional species entering the community, they are
analogous to the 'inventors' in the demographic models whose inven-
tions increase the carrying capacity of the Earth. The hyperbolic growth
of the Phanerozoic biodiversity suggests that 'cooperative' interactions
between taxa can play an important role in evolution, along with gener-
ally accepted competitive interactions. Due to this 'cooperation' (~ 'col-
lective learning'?), the evolution of biodiversity acquires some features
of a self-accelerating process. The same naturally refers to coopera-
tion/collective learning as regards the global social evolution. The dis-
cussed above suggests that we can trace rather similar macropatterns
within both the biological and social phases of Big History that produce
rather similar curves in diagrams and that can be described in rather
accurate way with rather simple mathematical models.
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# The Dynamics of Evolution:
What Complexity Theory Suggests
for Big History's Approach to Biological
and Cultural Evolution

Ken Baskin

## Abstract

The twentieth century science, from physics to neurobiology, redefined our understanding of the world, overturning the linear worldview of Newtonian physics for a more dynamic image. Especially as illuminated by complexity theory, this worldview suggests a conception of evolution in which phenomena adapt to each other, at many scales, embedded in a continually expanding universe of interconnected agents. Given this conception, human culture has evolved to adapt to changing conditions which, thus far, have generated a social world whose complexity has increased to serve a larger, more technologically advanced, more highly interconnected population. To demonstrate this conception of evolution, one can examine the Axial Age and Modernity as cultural 'phase transitions,' periods of experimentation punctuating periods of relative stable social structures. Such an examination offers an insight into the potential for Big History to contribute to solutions of the many challenges that call for innovative adaptations across our world.

**Keywords:** relational evolution, world story, Axial Age, Modernity.

Big History often focuses on the increasing complexity in the cosmos, life on Earth, and human culture that evolution has produced. David Christian discusses 'the endless waltz of chaos and complexity' (2004: 511), and Fred Spier, 'the rise and demise of complexity at all scales' (2011: 21). Yet, with the possible exception of Eric Chaisson (2001), writers in our discipline have not examined the dynamics by which complexity increases. In this essay, I want to reframe this discussion, drawing on the principles of complexity theory, because, while Big History treats complexity as a *measure* of diversity and interaction, complexity theory treats it as a *dynamic* to be examined (Bondarenko 2007). My purpose is to explore how an understanding of this dynamic – and the conception of evolution it suggests – can become an intellectual tool for our discipline.
My argument is that evolution is a much ‘thicker’ process than traditional theory suggests. Such a conception of evolution can enable students of Big History to reconsider any number of issues and develop a deeper understanding of the dynamics of both biological and cultural evolution. To explore this argument, I want to touch on four major issues:

* two key principles of complexity theory;

* the conception of ‘relational’ evolution suggested therein;

* the resulting theory of historical evolution;

* an examination of the Axial Age and Modernity in terms of this theory, as periods of punctuation, and why this perspective can be so valuable.

In an essay of this length, I can only begin this exploration. In addition, I have little choice but to oversimplify a number of issues that deserve deeper consideration. So I want to ask the readers' indulgence for this obvious limitation. With that caveat, I turn to the dynamics explored in complexity theory.

## Complexity Theory Dynamics

Complexity theory emerged in the late 1970s, as researchers in fields, ranging from fluid dynamics to economics, armed with desktop computers, modelled their subjects on non-linear mathematics and began finding striking similarities across disciplines and scales (for a full discussion see Pagels 1988). Those similarities suggested a meta-discipline, complexity theory, which, for me, is best understood as the study of ‘the patterns that emerge as complex, multi-scaled phenomena evolve’ (Baskin 2013: 4). I prefer the word ‘phenomenon’, to the more generally used ‘system’, to describe the networks complexity theory studies, because, where the concept of systems suggests mechanical stability, that of phenomena (see Barad 2007) indicates more dynamic structures.

Two principles of complexity theory are critical to my argument – the structure of matter as nested networks and ‘attractors’. First, physical reality is composed of networks of agents embedded in networks at many scales, from atoms networked in molecules to organs networked in living bodies, and solar systems in galaxies. As a result, understanding the behaviour of an ant colony as phenomenon requires *at least* knowledge of the behaviour of the ants that are its micro-scale agents, the colony itself, and its macro-scale environment.

The second critical principle is the attractor, which represents the dynamic balance between the behaviour of the agents and the constraints of the environment. The term attractor comes from non-linear mathematics, describing the pattern in phase space into which the solutions to equa-
tions are drawn. Lorenz's 'Butterfly Attractor' is among the best known. In complexity theory, more generally, an attractor describes the pattern of behaviour, of all possible behaviours, that characterizes any phenomenon under specific conditions (Cohen and Stewart 1994: 204–207). Over time, a phenomenon's attractor will draw it to behave something like this figure, which I first scribbled as a 'back-of-the-cocktail-napkin' doodle when I was wrestling with complexity theory's basic principles.

<figure><img src="image_23.png" /><figcaption>Fig. 1. Life Cycle of an Attractor</figcaption></figure>

Put a chunk of ice in a pot on the stove and turn up the heat. It will remain solid until it approaches its melting point, then enter a turbulent phase transition, and transform into liquid. It will remain liquid until it approaches its boiling point, become turbulent again, and transform into gas. Phenomena, then, oscillate between turbulent phase transitions, in which their agents seek the behaviours that enable them to survive current conditions, and the stable states in which those behaviours form their characteristic attractors.

To my surprise, I soon realized that much human behaviour conforms to this pattern. Human psychological development, the economy's boom/bust cycle, and the rise and fall of human empires (Baskin 2008, 2009) – all conform to this pattern. It also reflects other thinker's analyses, from Foucault's evolution of Western *episteme* (1994) to Arighi's cycles of Western Capitalism (1994). At some point, I realized that this pattern also reflects the still-controversial theory of punctuated equilibrium (Gould 2002), and that I had probably been strongly affected by the discussions of it I had read.

The Life Cycle of an Attractor is meant to be what Bruno Latour (2005) calls a 'panorama' – overly neat and coherent, an approximation
of the networks it maps, not a mathematical or even literal representa-
tion. The panoramic map is not the territory, merely a guide for the ex-
plorer. Nonetheless, the behaviour of many evolving phenomena con-
forms to this figure, suggesting a model of evolution.

Evolution like Molasses

We live today in an environment in which a new worldview is emerg-
ing (see Laughlin 2005; Boje and Baskin 2010; Smolin 2013), and our un-
derstanding of evolution is changing to meet this new worldview. The
traditional conception of evolution, the 'neo-Darwinian' 'modern syn-
thesis' 'asserts that this history of life at all levels - including and even
beyond the level of speciation and species extinction events, embracing
all macroevolutionary phenomena - is fully accounted for by the proc-
esses that operate within populations and species' (Hoffman 1989: 39).
Like the Newtonian worldview in which it developed, neo-Darwinian
evolution is linear, focusing on cause-and-effect changes in distinct enti-
ties, a 'straight line of continuous transformation of one species into
the next' (Tattersall and Schwartz 2001: 33). Richard Dawkins' theory of the
'selfish gene', which reduces organisms to vehicles for their genes, is an
excellent example of this approach (Dawkins 1976).

Mainstream cultural evolution articulates a similar conception of
'evolutionism'. As Robert Carneiro (2003) notes, evolutionism has gone
in and out of favour with anthropologists since Herbert Spencer began
discussing the idea in the 1850s. Much of the disagreement about such
cultural evolution centred on the Newtonian sense of determinism often
associated with its 'stages' and 'directionality'. Carneiro insists that this
Newtonian reading misinterprets such thinkers as Leslie White and
Gordon Childe. With his more dynamic reading of evolutionism, for
example, Carneiro explains that, while cultural evolution has a direc-
tion, increasing social complexity - that is, movement toward more hi-
erarchical socio-political levels - 'a process can have a direction without
having a goal' (Ibid.: 163). He goes on to define cultural evolution as
'a series of adaptive readjustments, each adding to the structural com-
plexity of the society and often initiating a series of other internal
changes that further contribute to its evolution' (Ibid.: 199). Nonetheless,
Carneiro does not develop a fully dynamic interpretation of cultural
evolution.

With this traditional view of evolution, researchers made great
strides during the twentieth century. However, a more dynamic and
non-linear worldview is emerging today, and the conception of evolu-
tion itself is evolving. The point I want to make is not to criticize theo-
rists such as Dawkins or Carneiro; the traditional understanding of evo-
lution reflects the worldview in which it developed. As a new world-
view emerges, so does a different understanding of evolution. I shall
follow Lee Smolin (2013: xvi) in calling it 'relational' – that is, phenom-
ena are best described in the context of the networks of which they are
part. Many of my ideas are certainly not original. I draw on or inde-
pendently developed ideas, to name only a few, that include the 'punc-
tuated equilibrium' of Niles Eldredge and Stephen Jay Gould (2002),
Stuart Kauffman's 'adjacent possible' (2000: 150), Henri Claessen's
Complex Interaction Model, which incorporates many of the dynamics
of my model (Claessen 2000); and Mark Taylor's image of living things
as both 'genuinely creative' individuals and the 'product of the matrix
of relationships in which they exist' (Taylor 2007: 335). By organizing
such ideas with a complexity-oriented discourse I am trying to move
toward a fuller and a more coherent theory.

Consider the image most often used to express the traditional con-
ception of evolution – the ‘Tree of Life’ (e.g., Pyne and Pyne 2012: 269),
a static, two-dimensional image, beginning in its roots as the most
primitive form of life and growing to its apogee in Man. With dynamic
evolution, a more appropriate image might be molasses moving down-
hill, a colloid of many particles, affecting each other, and being affected
by both the hill and the weather. Relational evolution moves, then, at
multiple scales, along the balance between the demands of external
conditions and the conditions of a set of phenomena's internal net-
works. Over time (see Fig. 1), the still-weakly-connected agents of
an incipient phenomenon in a phase transition – whether the living
things in an ecosystem after an extinction event or the people in a social
network after a collapse – search for behaviours that enable them to
survive and thrive in current conditions. When those agents find suc-
cessful behaviours, they begin to practice them and continue as long as
the behaviours produce success.

Over time, they build relationships by practicing these behaviours,
and the longer they succeed, the deeper the relationships become and the
more the welfare of the agents comes to depend on those relationships. It
is this dependence on specific behaviours and relationships that gives any
attractor its power to constrain its agents' responses. Agents in the phe-
nomenon continue to adapt to external change, until, at some point,
those agents have become too wedded to their behaviours to adapt.
At this point, the phenomenon enters 'senescence', a concept Stan Salthe
(1993) developed to describe the evolution of ecosystems, and the
agents subsume environmental change to their characteristic patterns.
Finally, the external change becomes so great that agents can no longer
survive; so the attractor collapses. At that point, agents, often connected in less extensive networks, must either dissipate so that the phenomenon no longer exists as a functioning network or re-enter the phase transition so that it can develop another attractor. Clearly, other processes – ageing or the tendency to form self-reinforcing cycles – are also at work, often interacting with evolution. A fuller consideration would touch on them more.

Today, societies across the world seem in senescence. One sees evidence in the gridlock in American government or the corruption in Russia and China, in the economic crisis in the European Union or the chaos of the 'Arab Spring'. Overwhelmed by decades of rapid change, those in power depend so deeply on the old attractors that support their wealth, power and sense of self, that they cannot make the fundamental changes today's conditions demand.

Because phenomena evolve at many scales simultaneously, the agents that make up any network continually undergo what Francois Jullien (2011) describes as 'silent transformations'. The process of ageing goes on every moment of every day throughout our bodies, even though most people rarely note it. In this way, Jullien notes, we are not so much getting older as the ageing world is taking us with it. Most of these transformations are habitual, often programmed; others are essentially experiments by which agents strive to respond to changes in their environments, Kauffman's exploration in the adjacent possible (Kauffman 2000). In this way, a myriad of micro-scale changes among agents, often barely noticeable, are tested within the phenomenon, and those that survive become available for further development. Such micro-scale changes are only partially expressed in stable states; however, during a more chaotic phase transition the agents are freed to explore the full potential that these changes have inherent within them. In biological evolutionary theory, these tendencies are described as 'developmental canalization' and 'developmental plasticity', respectively (Hoffman 1989); similarly, Elman Service (1988) described this dynamic as the 'Law of Evolutionary Potential'. One advantage of a complexity-oriented conception of evolution is that it explains this dynamic in both organic and cultural evolution at a more detailed level.

In genetic theory, mutations build up in organisms when ecosystems are stable, and remain latent or not fully expressed until the more chaotic phase transitions, when organisms explore survival strategies (Cohen and Stewart 1994). Mammals first appeared about 210 million years ago; they remained 'mainly small, nocturnal, tree-dwelling creatures' (Leakey and Lewin 1995: 66), surviving in ecological niches in
which they could avoid dinosaur predators. They would then accumulate the mutations that would enable those that survived to dominate all the world's ecosystems, until the extinction event that removed the dinosaurs 65 million years ago. It was only in the ensuing ten-million-year phase transition that mammals could explore the full potential of their 140 million years of silent transformational mutations, in the wide-open ecosystems they now inhabited. Once again, I have oversimplified; any dynamic as complex as the emergence of mammal dominance deserves much fuller examination than is possible here.

In cultural evolution, innovations, such as writing, also develop through millions of silent transformations. Written notation appeared in a variety of times and places, as knots, notches, or pictographs, as an aide to memory (Fischer 2001). With growing populations, agricultural surpluses, and increased trade, such marks became invaluable for keeping records. Full writing systems appear to have emerged as a part of the process of state-formation, in order to manage increasingly great resource bases, in the late fourth century BCE in, first, Sumer, and, then, Egypt (Nissen 1988). Throughout the pre-axial period, however, the resulting literacy would remain what Assmann (2012) calls ‘sectorial’ – that is, used in the accounting, religious, and government sectors in which it emerged. Used more and more widely in such cultures, it was still constrained in a stable state where culture was predominantly communicated and managed orally. With the phase transitional Axial Age, people in such cultures as Greece, India, and China, freed of the constraints of their stable state, would experiment with writing and develop its most powerful potentialities. Literacy would become ‘cultural’, penetrating ‘into the central core of culture’ (Assmann 2012: 383), enabling the personal reflection that reading drove or the ‘religions of the book’, for instance (Ong 1982).

What makes relational evolution different from the neo-Darwinian approach is not the facts of evolution; many neo-Darwinians will agree with most of what I have thus far written here (e.g., Hoffman 1989). The difference is in the basic discourse, some would call it a paradigm that makes these agreed-upon facts significant. The discourse in traditional evolution focuses attention on the development of individual changes, the most extreme example being Dawkins' selfish genes (1976). A relational approach, on the other hand, focuses on both individual developments and the context of wide, deeply interconnected networks of evolving phenomena, perhaps even of the universe itself. Evolution therefore suggests the thickness of molasses. It occurs on many scales – biological evolution on the molecular, cellular, organic, species and eco-
system, geologic and climatic scales, and cultural evolution on the indi-
vidual, family, social organizational, cultural, ideological, technological
and economic scales. The interaction of all such changes creates evolu-
tionary patterns. In addition, the evolution of the inanimate Universe,
life on Earth, and human culture all affect each other. The first major
shift in human social evolution occurred after a development in inani-
mate evolution, the end of the Ice Age, which made more complex so-
cial structures necessary. Similarly, events in the evolution of life, the
domestication of grains and animals, for example, have contributed to
human social evolution. Thus, interactions between events in the three
forms of evolution further thicken the process.

This relational discourse suggests ways to re-examine a variety of issues in biological and culture evolution. For example, is evolution gradual, as neo-Darwinians believe, or subject to punctuated equilib- rium (e.g., Hoffman 1989)? So intense was the disagreement that, in *The Blind Watchmaker* (Dawkins 1986), Dawkins entitles a chapter ‘Punc- turing punctuationism’. Yet, a relational approach largely resolves the disagreement. On the micro-level, agential evolution, in genes or indi- vidual people, is gradual; however, when the stable state of the macro- level goes into phase transition, the environment, whether ecosystem or culture, punctuates its equilibrium, driving radical adaptive changes for survival purposes at the micro- and meso-levels. Both processes are es- sential to evolution; to focus on only one is to misrepresent the full complexity of the facts. Similarly, the suggestion that biological and cul- tural evolution are different because the biological is mostly ‘Darwinian’ and the cultural, mostly ‘Lamarkian’ (e.g., Grinin *et al.* 2011) shifts with relational evolution. The difference here is in the carriers of ‘genotypic’ information. In biological phenomena that carrier is DNA, embedded in the body; in cultural phenomena it is a variety of stories, narratives, and meta-narratives people in any culture tell each other (e.g., Lyotard 1984). Take into account these differences in how information is carried, and the mechanism of both types of evolution seem remarkably similar.

Toward a Dynamic Theory of Human Social Evolution

From this relational point of view, a panorama of human history over
the last 50,000 years might look something like this (first presented in
Baskin and Bondarenko 2011).
<figure><img src="image_24.png" /><figcaption>Fig. 2. Human history as 'punctuated equilibria'</figcaption></figure>

History is too messy and abundant, and, what we know with certainty, too limited, to assume that events should conform to our abstractions; so I left this figure imprecise. For example, the movement indicated in the figure is overly linear. For the most part, cultural stable states do not simply end and phase transitions begin; rather, societies often move back and forth between the two. Still, the basic pattern seems valid as a Latourian panorama, rather than attempt to articulate the truth.

This conception of cultural evolution has a significant explanatory power. For instance, the period from c. 3000 BCE to 1500 CE is often defined as the 'tribute' (Taintier 1988; Amin 2009) 'stage' of society. Yet, the social institutions in Greece, India and China, before and after the Axial Age, are clearly distinct – mythic religion vs. religions of the book, for example, or government by royal lineage vs. bureaucracy (e.g., Lewis 1990). The evolutionary model I am developing explains those differences as two cultural stable states that represent adaptations to different levels of complexity. This understanding was recently validated by its similarity to the more mathematically rigorous work of Korotayev and Grinin (2012: 34), in modeling the growth of urban populations.
<figure><img src="image_25.png" /><figcaption>Fig. 3. Dynamics of World Urban Population</figcaption></figure>

*Note:* In millions, for cities of more than 10,000, 4000 BCE–1990 CE, logarithmic scale.

Here we see that urban population remains essentially flat in pre-axial and post-axial stable states, while it increases exponentially in the Axial Age and Modernity. According to Korotayev and Grinin, such rapid population growth results largely from an acceleration in technological innovation. Viewed in terms of relational evolution, this acceleration of innovation reflects the phase transition and the enhanced ability to experiment with and to socially integrate the wide range of social mutations – manifested, for example, in the feedback loops of increased collective learning – that had already developed, as well as new innovations.

In the rest of this essay, I shall explore whether, as a relational theory of evolution suggests, the Axial Age and Modernity share similar dynamics. Space limitations make it impossible to explore key issues such as capitalism, imperialism, or developments outside Eurasia in any detail. If this theory does seem accurate, however, it should offer fascinating insights into such topics at another time.

At the heart of events in both cultural phase transitions is the transformation in the cultural 'phenotype', the institutional structures that enable continuing survival, which requires a new cultural 'genotype', the equivalent of organic DNA. Bondarenko and I call that cultural genotype a 'world story'. Such culture-defining sets of stories must answer a series of questions about survival including:
* How did we human beings get here?

* What is our purpose?

* Who are 'we' as a group, and how should we behave toward each other and our world?

* How should we manage the communities in which we live?

* Why, in a world full of fear and pain, should we not kill ourselves?

In this way, the world story of hunter-gatherers had to explain the 'profane', day-to-day issues of survival, from how to hunt and gather, house and clothe themselves to social relationships in groups that rarely exceeded 30 members; yet, it also had to explain the sense that 'sacred' forces 'incomprehensible, intractable but eminently efficacious' (Caillois 2001: 22), were continually moving things - from climate shifts to the animals they hunted and the flora they gathered. Such world stories are not merely 'religious' (see Nongbri 2013); they articulate a discourse that integrates spiritual concerns with social, economic and political questions, encoding any society's cultural attractor. Moreover, as Taylor (2007) notes of his expanded concept of religion, world stories function both to create the ground for social structure and to destabilize it, especially during times of cultural phase transition.

The world stories of the predominant pre-axial states (c. 3000 BCE – c. 800 BCE) focused on maintaining order amid the forces of chaos that threatened large societies dependent on agricultural surplus. In Sumeria, Egypt, and China, for example, controlling the sacred forces threatening large-scale agriculture, from drought and flood to the devastation of war, was central. In all of them, the king was conduit to the divine, whether as god himself or, more often, master of order-creating ritual. In Egypt, for example, the pharaoh had to practice the rituals that ensured *Ma'at*, both the triumph of order over chaos and justice for society at large (Assmann 2008, 2011). The resulting societies were institutionally integrated, so that worship, politics, and economics – as in the use of temples for grain collection and distribution (e.g., the story of Joseph administering the seven years of plenty and seven of famine, Genesis, 41) – function as parts of an order as integral and natural as the order and chaos they balance. This style of world story successfully governed these societies until c. 1000 BCE, when the combination of increased trade and wealth, a wider use of writing, and rapid improvements in warfare, especially the iron metallurgy that made weapons cheaper and more plentiful (McNeill 1982), as well as a doubling of world population between 3000 and 1000 BCE (Livi-Bacci 1992), demanded a new way of living in the world.
## The Axial Age

Pre-axial social structure began to break down in the Mediterranean world c. 1200 BCE, when the 'Sea People' (e.g., Sandars 1987) destroyed both Hittite and Mycenaean cultures and drained the power of Egypt during the twelfth century BCE. In China, the Zhou Dynasty began losing control of its territories by the middle of the tenth century BCE, eventually disintegrating into 170 competing kingdoms (Fairbank and Goldman 2006). Karl Jaspers (1953: 1) named the resulting transition the Axial Age (800-200 BCE), the 'axis in world history ... which has given birth' to everything that followed. The school that follows his lead (e.g., early Bellah 1976; Eisenstadt 1982; Armstrong 2006) explains the similar experiences in these states largely in terms of a spiritual transformation that, for them, happened unpredictably in unconnected cultures. Relational evolution, on the other hand, suggests that this period represents, as Assmann (2008, 2012) points out, cultural breakdowns followed by breakthroughs that drove total social transformations in societies that were experiencing the same sort of increase in complexity.

To adapt to it, people in these societies needed to recreate their institutions, from the pre-axial order that emphasized loyalty to one's lineage to a more formal connection and sense of obligation. In describing China's axial experience, Mark Lewis (1990: 246) notes that, just as warfare was transformed from a means of defending honor among aristocrats to the tightly organized extension of armies of hundreds of thousands directed by the will of a single man, the commander, 'all of society was re-imagined in terms of the hierarchical ties of superior and subordinate'. In Greece, this movement toward order and control appeared in the phalanx and later the troops of Philip of Macedon, as well as the bureaucratic empires that emerged from Alexander's conquests.

To transform their institutions in this way, they would first have to re-interpret their world by evolving new world stories. As Assmann (2011) notes of the Israelite experience, the new world stories evolved through roughly three phases. In each, people, freed of their older world-story attractors, behaved according to their evolving stories, experienced the results, and then changed the stories in response. Assmann identifies the phases of axial world story as 'foundational texts', 'religious texts', and 'commentary'. Rather than his 'religious texts' (for a discussion of some problems with this term, see Nongbri 2013), I shall use the term 'tragic/new world story texts', to include Timothy Reiss' understanding of tragedy. For him, the tragic reflects a 'sense of injustice' and 'the inevitable gap between the human known and knowable and all that escapes discourse', 'appearing at certain moments of seem-
ingly abrupt epistemic change ... making a new class of discourse possible' (Reiss 1980: 20, 2). Tragedy recognizes the terror that people experience as their old order no longer works.

For the sake of brevity, I shall focus on the axial experiences in Greece and China (for a treatment of the process in Israel, see Assmann 2011; for the Indian experience, several essays in Eisenstadt 1986).

Each culture's foundational texts articulate group identity as 'remembered past', mixing myth and history (Assmann 2011: 59), translating pre-axial mythos into a world where the cultural attractors have collapsed. The fear of chaos dominates all of them. In Greece that fear appears in the poetry of Hesiod and the epics of Homer, articulated in divine figures who eat their children and precipitate a decade-long war over a beauty contest. Faced with this chaotic and capricious world, Homer shows the aristocracies of the Greek states as fractious brothers, coming together to protect each other's honor, going to war over Helen and defeating the eastern enemy, Troy. The Greek *poleis* enacted this story when they cooperated to defeat the Persians in 490 and 480 BCE. Having achieved this success in enacting their foundational texts, these city-states acted like brothers again, fighting among themselves over political and economic control in alliances led by Athens and Sparta. The devastation of the Peloponnesian Wars would drive Greece's Golden Age of tragic/new world story texts.

In China, the foundational texts are also about taming chaos, although the High God of the Shang Dynasty (Di) had been translated into the concept of Heaven (Schwartz 1985). Order was Heaven's gift so that the key issue would be why people introduce disorder by deviating from it. The actors in China's axial foundational texts are not divinities, but early 'sages', such as Yu, who invented irrigation and water control after the Great Flood of the Yellow River, or the kings Yao and Shu, who exemplified an ordered practice of public rule (Ibid.; Lewis 1990). The ideal inherent in this foundational myth was of order through strong kingship in an extremely hierarchical, united China. Partly as a result, the central theme of China's Axial Age was the movement from fragmentation to unity, from chaos to order. In this way, in the Spring and Autumn period (771-476 BCE) early Axial Age China witnessed a constant state of war – one account lists 540 interstate wars and more than 130 civil wars in one 295 year period (Lewis 1990: 36) – intensifying the fear of chaos that had existed previously. By the end of the Spring-and-Autumn period, warfare had reduced the number of competing states from 170 to seven. It would also stimulate the tragic/religious texts that appeared in late axial China.
In the axial societies, the terror provoked by these wars would com-
bine with the increased integration of writing beyond the scribes and
formal keepers of social order to encourage a level of reflection previously
unknown (see Assmann 2012). Literacy facilitated the rise of individual-
ism, as reading, an individual activity, begins to replace communal story-
telling, and it became possible for people to become more reflective with
a text in front of them (Ong 1982). The tragic / new world story texts in
these societies would be one result of this increased reflection.

In Greece, those texts appeared first in the tragedies of Aeschylus,
Sophocles, and Euripides, which span the fifth century BCE, from the
beginning of the Persian Wars in 499 BCE to the end of the Peloponne-
sian Wars in 404 BCE. The tragedies demonstrated how even good peo-
ple become caught up in chaotic forces, no matter how hard they resist.
These texts demonstrate Reiss' (1980: 21) 'moment of rupture', as people
recognize that the old ways do not work, and that the order provided
by reason can be disrupted by dark sacred forces.

The new world story to explain this chaos and terror emerges in
Greece from its tradition of philosophy, with all the experimental vari-
ety one would expect in a period of phase transition: the Pythagoreans
(fifth and sixth centuries BCE) insisted on the ultimate reality of num-
bers; Heraclitus (fl. 550) saw reality as a constant change; and the atom-
ists, such as Democritus (fl. 410), viewed reality 'as a lifeless piece of
machinery' (Lindberg 2007: 29-30). All this intellectual searching culmi-
nated in the philosophy of Plato (427-328 BCE) and Aristotle's practical
application (384-322 BCE).

Having lived through the devastation of the Peloponnesian Wars,
Plato knew first hand that human-induced chaos had to be controlled.
To do so, his philosophy emphasizes rationality, insisting that the world
was created by a rational spirit, the Demiurge (see Timaeus), based on
the abstract Forms of things, their true reality. Chaos crept into the
world, not because of the Forms, but the material with which the Demi-
urge worked (e.g., Bellah 2011). Because, as the Parable of the Cave (Re-
public) indicates, most citizens never understand the reality of Forms,
they are governed by emotions and appetites, and government must
prevent those emotions and appetites overwhelming citizens' reason. To
make such government work, Plato replaced the heroic leaders of
Homer with his theoros, the philosopher who 'loves the spectacle
of truth' (Nightingale 2004: 98). The theoros would allow most citizens to
have their 'unfalsifiable' mythic beliefs (mythos), but they themselves
would live by the rational, 'falsifiable' logos. Plato recognized that such a
rationally governed life was only for a very few. For the rest, he sug-
gested that the gods, goddesses, and narratives of the old world story
would be sufficient.

Aristotle, born after this devastation, 'was able calmly to look
around the new world that Plato had opened up and explore its many
possibilities, without rancor' (Bellah 2011: 395-396). Plato's Demiurge
would become Aristotle's 'Unmoved Mover', a divinity of pure thought,
beyond our world of matter, and the cosmos it created contained both
the chaotic, ever changing world below the Moon and the unchanging
Heavens (Freely 2012: 28), rotating in perfect circles. Humans created
chaos only because they would not allow the pure intellect of the divine
to guide them. To avoid chaos, the *polis* must train citizens in using their
reason. Aristotle's many other studies continued to apply his own ra-
tional principle to one field of study after another, answering the ques-
tions behind any world story. His *Ethics*, for example, explored how the
individual could achieve *eudaimonia* to live the life of *theoria*. In these
and other explorations, Aristotle would 'sketch out most of the fields of
inquiry that would preoccupy later thinkers' (Bellah 2011: 395).

The Chinese experience with tragic/new world story texts mani-
fested itself as the philosophical flowering of the ‘hundred schools’,
which arose in the century leading to the Warring States period (403–
221 BCE). These schools reflected the wide variety of thought respond-
ing to the violence of the Spring-and-Autumn period, as articulated by
the *shih*, the growing class of often-wandering scholars dispossessed
from their noble lineages (Schwartz 1985). All of them were trying to
understand the same tragic dilemma: If order was the gift of Heaven,
why was chaos so widespread? Why had men lost ‘the Way of Heaven’?
Three of these schools would define the positions that would be negoti-
ated into China’s post-axial world story. For the Confucians, the issue
was social: the Zhou had already achieved a ‘universal, all-embracing,
ethicopolitical order’ (Ibid.: 65). Only by re-establishing that order could
social order be recaptured. To do so, Confucius (551–479 BCE) and his
followers focused on living life according to the ritual formulas for one’s
position and on education as a means for both individuals and society at
large to understand the ‘Way’ of humans in society. For the Daoists,
the issue was more personal: the overly civilized order of the Confucians
had made it impossible for people to behave naturally, in consonance
with the Way and the Heaven-given laws of change (Graham 1989). Only
by the individual learning the Way and acting according to it could order
be returned. Finally, the Legalists believed that the problem was the pas-
sionate, unruly nature of human beings and that order required clear,
harshly enforced laws so that people knew exactly what behavior
would be expected and what would happen if they did not conform (Feng 1976). Throughout the Warring States period, the intensity of war-fare increased, as armies reached several hundred thousand men (Lewis 1990). By 300 BCE, even Mencius (c. 372-289 BCE), the strongest Chinese believer in human goodness, recognized that the only way to social order was unity (Schwartz 1985). With a complex cosmology already in place (Ibid.: 350-382), these three perspectives would become more and more closely intertwined throughout China's commentary period.

Assmann (2011: 269) describes the period of commentary as 'an in-dispensable accompaniment to the cultural transformation ... keeping those texts alive by bridging the ever widening gap between them and the changing reality of life'. In this way, as Alexander spread Hellenism, Rome rose in the West, and the Qin united China at the end of the Axial Age, as population and wealth increased, and technology accelerated, new ways of governing and behaving in increasingly complex societies could be articulated and enacted.

In Greece, this commentary would play itself out in philosophy and science, continuing its evolution through the Hellenistic period and later. The rationalist commentary that began with Plato and Aristotle continued through the work of thinkers such as the Cynics and Neo-Platonists in the Hellenistic period, early scientific thinkers such as Ptolemy and, later, the Fathers of the Church, such as Augustine and Origen (e.g., Gillespie 2008). Significantly, their central assumptions were set in place by Plato and Aristotle, including the analysis of the world as distinct 'things', the concept of a soul separate from the body, the idea of an Unmoved Mover, and the emphasis on moral distinctions. All these assumptions would be integrated into the world stories of the Roman Empire and, later, that of Western culture.

The Chinese commentary period seems to have been underway in the fourth century BCE. Throughout it, the Chinese thinkers of all schools would borrow from each other to develop the most effective philosophies for aiding kings in the seven states in their efforts to unite the country. The Legalist Han Fei (d. 233 BCE), for example, briefly the chief minister for the King of Qin as he was uniting China, borrowed from Daoist *Laotzi*'s ideas about the Way and *wu-wei*, probably best translated as effortless action (Slingerland 2003), to provide a meta-physical basis for his emphasis on punishment (Graham 1989). In spite of a reaction against the extreme Legalistic policies of the First Emperor, so that it lost its position as a school of philosophy, the concepts of Legalism remained key assumptions for the Chinese government. Neo-Confucianism, with its emphasis on right behavior and education, in-