Blog / September 21, 2022
By James Thornton, Mountain Research Initiative
Mountain regions cover a considerable proportion of the land surface, provide several crucial ecosystem services—such as water—to downstream societies, and typically support high biodiversity. These regions are also, however, susceptible to many natural hazards, especially as mountain systems respond rapidly to ongoing climate change.
As such, reliable data on human populations living in and near the world’s mountains are critical for informed decision-making around environmental protection, disaster response, and climate change mitigation and adaptation, among other things.
Estimating mountain populations requires two kinds of data: gridded population data and data delineating mountain regions. Researchers have used a wide variety of different datasets and approaches, but the impacts of using different input datasets on the results has not been systematically assessed. In addition, some previous studies have lacked transparency regarding the datasets and methods used. This situation makes it hard for users of these estimates to interpret them and make informed decisions.
A recent study published in the open access journal PLOS ONE seeks to address these common oversights. In the study, GEO Mountains in collaboration with GEO’s Human Planet Initiative (who provided one of the population datasets, the Global Human Settlement Layer) and several other organisations present an open and comparative analysis of input dataset choices on mountain population estimates at both global and regional scales.
The study confirmed considerable variability in global mountain population estimates (ranging from 0.344 billion to 2.289 billion in 2015). This variability is dominated by the choice of mountain delineation, with the influence of population dataset choice being secondary.
The findings also allow the most (densely) populated, most urbanized, and most protected mountain sub-regions, as well as hotspots of change, to be identified. These analyses highlighted that 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.
Furthermore, the paper assesses the influences of topographic, climatic, and other potential drivers of mountain populations densities. The insights from this component of the study could help improve future mountain population projections. For instance, while relatively high mountain population densities can occur across a broad range of conditions, population density is most strongly related to climatic metrics such as annual mean temperature, and these associations appear to have strengthened through time.
GEO Mountains and partners also produced a full Knowledge Package, published on the GEO Knowledge Hub (GKH) containing the code, input, and output datasets used. This open access package should enable other stakeholders to efficiently repeat, update, extend, or adapt the analysis.
Advancing sustainable development, adapting to climate change, minimizing natural hazard risks, and protecting mountain ecosystems are urgent, global priorities. This study’s new approach strengthens transparency and increases the potential for better research and policymaking in these areas.
To learn more about how this collaboration across the GEO Work Programme has the potential to benefit real-world policy applications, click here.
Citation: Thornton JM, Snethlage MA, Sayre R, Urbach DR, Viviroli D, et al. (2022) Human populations in the world’s mountains: Spatio-temporal patterns and potential controls. PLOS ONE 17(7): e0271466. https://doi.org/10.1371/journal.pone.0271466
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