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      Deforestation and world population sustainability: a quantitative analysis

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          Abstract

          In this paper we afford a quantitative analysis of the sustainability of current world population growth in relation to the parallel deforestation process adopting a statistical point of view. We consider a simplified model based on a stochastic growth process driven by a continuous time random walk, which depicts the technological evolution of human kind, in conjunction with a deterministic generalised logistic model for humans-forest interaction and we evaluate the probability of avoiding the self-destruction of our civilisation. Based on the current resource consumption rates and best estimate of technological rate growth our study shows that we have very low probability, less than 10% in most optimistic estimate, to survive without facing a catastrophic collapse.

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          If extraterrestrial intelligent beings exist and have reached a high level of technical development, one by-product of their energy metabolism is likely to be the large-scale conversion of starlight into far-infrared radiation. It is proposed that a search for sources of infrared radiation should accompany the recently initiated search for interstellar radio communications.
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                Author and article information

                Contributors
                gaquino@turing.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                6 May 2020
                6 May 2020
                2020
                : 10
                : 7631
                Affiliations
                [1 ]ISNI 0000 0001 2179 0636, GRID grid.412182.c, Departamento de Ingeniería Eléctrica-Electrónica, Universidad de Tarapacá, ; Arica, Chile
                [2 ]ISNI 0000 0004 5903 3632, GRID grid.499548.d, The Alan Turing Institute, ; London, UK
                [3 ]ISNI 0000 0004 0407 4824, GRID grid.5475.3, University of Surrey, ; Guildford, UK
                [4 ]ISNI 0000 0001 2191 6040, GRID grid.15874.3f, Goldsmiths, University of London, ; London, UK
                Article
                63657
                10.1038/s41598-020-63657-6
                7203172
                32376879
                ec194875-d3cc-4f54-aaa7-c1664f2a6ce1
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 November 2019
                : 2 April 2020
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                © The Author(s) 2020

                Uncategorized
                population dynamics,statistical physics, thermodynamics and nonlinear dynamics,applied mathematics,environmental impact

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