In the journal Scientific Reports, a paper "Global population: from Super-Malthus behavior to Doomsday criticality" [Scientific Reports 14 (2024) 9853, has been just published. The first author is mgr Agata Angelika Sojecka, a Ph.D. student at the University of Economics in Katowice. The article is also available in OPEN Access.
Scientific Reports is a respected journal from the Nature family; Impact Factor IF = 4.5, and 140 points of the Ministry of Science and Higher Education. The paper is available as OPEN Access. Agata Angelika Sojecka is Doctoral School student, 4th year; Management Science.
The report discusses global population changes from the Holocene beginning to 2023, via two Super Malthus (SM) scaling equations. SM-1 is the empowered exponential dependence: P(t)=P0exp(t/τ)β, and SM-2 is the Malthus-type relation with the time-dependent growth rate r(t) or relaxation time τ(t)=1/r(t): P(t)=P0exp[r(t)*t ] = P0exp[t /τ(t)].
Global population data from a few sources were numerically filtered to obtain a 'smooth, analytic' dataset, allowing the distortions-sensitive and derivative-based analysis. The test recalling SM-1 equation revealed the essential crossover transformation near the year 1970 (population: ~3 billion): from the compressed exponential behavior (β >1) to the stretched exponential one (β <1). For SM-2 dependence, linear changes of τ(t) during the Industrial Revolutions period, since the year ~1700, led to the constrained critical behavior P(t)=P0exp[b't/(tC-t)], where tC ≈ 2216 is the extrapolated year of the infinite population. The link to the famous 'hyperbolic, Doomsday' equation [von Foerster et al. Science 132 (1960) 1291] is shown.
The results are discussed in the context of complex systems physics, the Weibull distribution in extreme value theory, and significant historical and prehistoric issues revealed by distortion-sensitive analysis. The importance of reliable determination of global population changes for effective global management in the current globalized world is stressed.
The report also indicates that global population changes can be non-monotonic, which yields a significant problem in long-term deterministic forecasting. Important was introducing the innovative way of data analysis sensitive to subtle deviations from model relations, which is related to the consistent use of the 'bottom up' methodology. In the first step, it determines the time-domains where a given scaling model-equation can be used for a given set of empirical data.
More information about the publication can be found on the website.
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