Human population dynamics revisited with the logistic model: How much can be modeled and predicted?

Marchetti, C.; Meyer, Perrin S.; Ausubel, Jesse H.

doi:10.1007/bf02438865

Cited by 19 publications

(23 citation statements)

References 17 publications

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“…This hypothesis is also considered for all the rates in Marchetti, Meyer, and Ausubel (1996), Micó and Caselles (1998), and Chowdhury and Allen (2001). The work by Caselles et al (2008) introduces a more detailed hypothesis: dependence on a well-being variable (specifically the HDI) of the birth and death rates.…”

Section: Demographic and Well-being Modelmentioning

confidence: 99%

“…The work by Marchetti et al (1996) demonstrates that fertility and death rates can be fitted by a sum of logistic functions. Our data show a joint tendency to complete cycles (see Figures A5 to A8 in online Appendix A).…”

Section: Demographic and Well-being Modelmentioning

confidence: 99%

“…The mathematical structures of the fitted functions corresponding to the emigration rate and immigration rate are also those indicated by Marchetti et al (1996) for time rates, that is, logistic functions (or sums of them). The structure considered for the time-dependence of the input variables, mentioned when describing well-being indices, is the sum of the logistic functions.…”

Section: Gender-related Development Indexmentioning

confidence: 99%

“…The structure considered for the time-dependence of the input variables, mentioned when describing well-being indices, is the sum of the logistic functions. Logistic functions can be interpreted in a saturation of resources and their use in demography has proved most useful (Marchetti et al, 1996).…”

Section: Gender-related Development Indexmentioning

confidence: 99%

See 3 more Smart Citations

A Stochastic Model for Population and Well-Being Dynamics

García

Micó

Caselles

et al. 2014

The Journal of Mathematical Sociology

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This article presents a stochastic dynamic model to study the demographic evolution per sexes and the corresponding well-being of a general human population. The main model variables are population per sexes and well-being. The considered well-being variable is the Gender-Related Development Index (GDI), a United Nations index. The model's objectives are to improve future well-being and to reach a stable population in a country. The application case consists of adapting, validating, and using the model for Spain in the 2000-2006 period. Some instance strategies have been tested in different scenarios for the 2006-2015 period to meet these objectives by calculating the reliability of the results. The optimal strategy is ''government invests more in education and maintains the present health investment tendency.''

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Section: Demographic and Well-being Modelmentioning

confidence: 99%

Section: Demographic and Well-being Modelmentioning

confidence: 99%

Section: Gender-related Development Indexmentioning

confidence: 99%

Section: Gender-related Development Indexmentioning

confidence: 99%

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A Stochastic Model for Population and Well-Being Dynamics

García

Micó

Caselles

et al. 2014

The Journal of Mathematical Sociology

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“…Concerns over human carrying capacity can be traced back to Malthus' portrayal of human population growth restrained by available food supplies (Seidl and Tisdell, 1999), but modern studies mainly focus on the population that can be sustained by regional, national, and global agricultural potential productivity (Cao et al, 1995;Harris and Kennedy, 1999;Hopfenberg, 2003;Yue et al, 2008). Models have been developed to estimate Earth's carrying capacity (Cohen, 1995;Marchetti et al, 1996;Meyer and Ausubel, 1999), but there is little agreement about the most appropriate model.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Beijing's human carrying capacity from the perspective of water resource constraints

Yingxuan

Chen

Zhou

et al. 2010

Journal of Environmental Sciences

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As the demands on limited water resources intensify, concerns are being raised about the human carrying capacity of these resources. However, few researchers have studied the carrying capacity of regional water resources. Beijing, the second-largest city in China, faces a critical water shortage that will limit the city's future development. We developed a method to quantify the carrying capacity of Beijing's water resources by considering water-use structures based on the proportions of water used for agricultural, industrial, and domestic purposes. We defined a reference structure as 45:22:33 (% of total, respectively), an optimized structure as 40:20:40, and an ideal structure as 50:15:35. We also considered four domestic water quotas: 55, 75, 95, and 115 m 3 /(person·yr). The urban carrying capacity of 10-12 million was closest to Beijing's actual 2003 population for all three water-use structures with urban domestic water use of 75 m 3 /(person·yr). However, after accounting for our underlying assumptions, the adjusted carrying capacity is closer to 5-6 million. Thus, Beijing's population in 2003 was almost twice the adjusted carrying capacity. Based on this result, we discussed the ecological and environmental problems created by Beijing's excessive population and propose measures to mitigate these problems.

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An ecological theory of changing human population dynamics

Henderson

Loreau

2019

People and Nature

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The dependence of humans on nature has come into focus as the human population continues to grow, resources diminish and production technology stagnates – threatening human well‐being on a global scale. Numerous previous models describe human population dynamics, in relation to a multitude of different factors. However, there are no consistent driving factors of human demography through history, which makes predicting future changes more challenging. Here, we review the literature on human population growth from empirical data and previous models, which allows us to highlight key trends in demography and land cover changes. We then establish an ecologically driven theory of demographic change that uses resource accessibility as a proxy for socio‐economic factors. The theory combines multiple concepts to represent 12 millennia of past population dynamics through simple human–nature relationships. Furthermore, the model allows us to compare different scenarios related to technological progress and land cover change, for which we find that the peak human population is highly dependent on whether technological developments continue at an exponential growth rate, or if and when there is a saturation point. Likewise, agriculture is shown to be helpful for growing the population, but nature is ultimately needed to maintain the human population. A plain language summary is available for this article.

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Human population dynamics revisited with the logistic model: How much can be modeled and predicted?

Cited by 19 publications

References 17 publications

A Stochastic Model for Population and Well-Being Dynamics

A Stochastic Model for Population and Well-Being Dynamics

Evaluating Beijing's human carrying capacity from the perspective of water resource constraints

An ecological theory of changing human population dynamics

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