School of Mathematics and Actuarial Science, University of Leicester, Leicester LE1 7RH, UK.
School of Mathematics, University of Birmingham, Birmingham B15 2TT, UK.
J R Soc Interface. 2021 Apr;18(177):20210034. doi: 10.1098/rsif.2021.0034. Epub 2021 Apr 28.
Spatial distribution of the human population is distinctly heterogeneous, e.g. showing significant difference in the population density between urban and rural areas. In the historical perspective, i.e. on the timescale of centuries, the emergence of densely populated areas at their present locations is widely believed to be linked to more favourable environmental and climatic conditions. In this paper, we challenge this point of view. We first identify a few areas at different parts of the world where the environmental conditions (quantified by the temperature, precipitation and elevation) show a relatively small variation in space on the scale of thousands of kilometres. We then examine the population distribution across those areas to show that, in spite of the approximate homogeneity of the environment, it exhibits a significant variation revealing a nearly periodic spatial pattern. Based on this apparent disagreement, we hypothesize that there may exist an inherent mechanism that may lead to pattern formation even in a uniform environment. We consider a mathematical model of the coupled demographic-economic dynamics and show that its spatially uniform, locally stable steady state can give rise to a periodic spatial pattern due to the Turing instability, the spatial scale of the emerging pattern being consistent with observations. Using numerical simulations, we show that, interestingly, the emergence of the Turing patterns may eventually lead to the system collapse.
人口的空间分布明显不均匀,例如,城乡人口密度存在显著差异。从历史的角度来看,即从几个世纪的时间尺度来看,人口密集地区出现在现在的位置,这被广泛认为与更有利的环境和气候条件有关。在本文中,我们挑战了这一观点。我们首先确定了世界上不同地区的几个区域,这些区域的环境条件(通过温度、降水和海拔来量化)在数千公里的范围内表现出相对较小的空间变化。然后,我们研究了这些区域的人口分布,以表明尽管环境大致均匀,但它表现出显著的变化,显示出近乎周期性的空间模式。基于这种明显的不一致,我们假设可能存在一种内在机制,即使在均匀的环境中也可能导致模式形成。我们考虑了一个人口统计经济动态的耦合数学模型,并表明其空间均匀、局部稳定的稳态可能由于图灵不稳定性而导致周期性的空间模式,出现的模式的空间尺度与观察结果一致。通过数值模拟,我们表明,有趣的是,图灵模式的出现最终可能导致系统崩溃。