A new study reveals the impact of data choices in quantifying global and regional mountain populations and their associations with environmental factors in a transparent, reproducible, and comparative way.

Many applications require reliable data on human population dynamics in and near the world’s mountains, and such statistics are routinely cited in both research and policy contexts. However, the impacts of using alternative input datasets remain unclear, and the methods used have not always been completely transparent.

A new study, published today in the Open Access journal PLOS ONE, addresses these limitations by presenting a transparent, reproducible, and comparative analysis that enables data users to better understand the implications of making alternative input dataset choices. The study was prepared by an interdisciplinary team of collaborators from organisations including the Mountain Research Initiative (MRI), the US Geological Survey (USGS), the University of Zurich, and the Global Mountain Biodiversity Assessment (GMBA), and contributed to the population statistics presented in the IPCC Sixth Assessment Report Cross-Chapter Paper on Mountains (Working Group II). The output datasets are freely shared and enable the most (densely) populated, most urbanized, and most highly protected mountain sub-regions to be rapidly identified.

Climatic, topographic, and other potential influences

Spatio-temporal patterns in population and urban population distributions were not only quantified and described, but associations between population density and climatic, topographic, and other potential influences were also explored.

Main conclusions

The study’s main conclusions are that:

  • Variability in global mountain population estimates is considerable (ranging from 0.344 billion to 2.289 billion in 2015), and this variability is dominated by the choice of mountain delineation, with the influence of population dataset choice being secondary;
  • Population increased at least twofold in ∼35% of mountain sub-regions over the 40-year period from 1975 to 2015;
  • In many mountain regions, population increases have been associated with strong urbanization, in terms of both extent and urban population;
  • In parts of Africa especially, mean population densities in mountainous regions are notably higher than population densities more generally, suggesting that mountains provide favourable living conditions for people in certain hot and/or dry climatic zones, and;
  • Whilst relatively high mountain population densities can occur across a broad range of climatic and topographic conditions, population density is most strongly related to climatic metrics such as annual mean temperature, and these associations appear to have strengthened through time.


Potential applications

Given the urgency of achieving more sustainable development, adapting to climate change, mitigating natural risks, and protecting important ecosystems in mountains, the robust estimates presented are expected to benefit future research, policy, and practice related to mountain socio-ecological systems. For instance, policymakers can now better account for the variability in the number of people who may be affected by, and themselves affect, changes in these systems.

Future research directions

Insights from this research could contribute to efforts to better predict the future evolution of mountain populations under multiple plausible future climatic, demographic, economic, and land use scenarios. Indeed, future research on this topic should focus on ensuring that the specific characteristics of mountainous regions are well represented. Finally, the scripts developed are also shared and could be adapted in various contexts to efficiently calculate spatial statistics over arbitrary complex and/or large geometries, including in non-mountain applications; a further benefit of the “Open Science” approach taken.

Read the article

Full Research Article:  Thornton, J.M., Snethlage, M.A., Sayre, R., Urbach, D.R., Viviroli, D., Ehrlich, D., Muccione, V., Wester, P., Insarov, G. and Adler, C. (2022). Human populations in the world’s mountains: spatio-temporal patterns and potential controls. PLOS ONE. doi: 10.1371/journal.pone.0271466

Cover image by hpgruesen.

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