Evidence map›Paper›PMID 35857800›Full record

ArticlePloS one2022

Human populations in the world's mountains: Spatio-temporal patterns and potential controls.

James M Thornton, Mark A Snethlage, Roger Sayre, Davnah R Urbach, Daniel Viviroli, Daniele Ehrlich, Veruska Muccione, Philippus Wester, Gregory Insarov, Carolina Adler

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

James M ThorntonMountain Research Initiative, University of Bern, Bern, Switzerland.ORCID 0000-0002-1447-1554
Mark A SnethlageGlobal Mountain Biodiversity Assessment, University of Bern, Bern, Switzerland.
Roger SayreU.S. Geological Survey, Reston, VA, United States of America.
Davnah R UrbachGlobal Mountain Biodiversity Assessment, University of Bern, Bern, Switzerland.
Daniel ViviroliDepartment of Geography, University of Zurich, Zurich, Switzerland.
Daniele EhrlichJoint Research Center, European Commission, Ispra, Italy.
Veruska MuccioneDepartment of Geography, University of Zurich, Zurich, Switzerland.
Philippus WesterInternational Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal.
Gregory InsarovInstitute of Geography, Russian Academy of Sciences, Moscow, Russia.ORCID 0000-0003-0790-075X
Carolina AdlerMountain Research Initiative, University of Bern, Bern, Switzerland.ORCID 0000-0002-8787-2797

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changing climate and human demographics in the world's mountains will have increasingly profound environmental and societal consequences across all elevations. Quantifying current human populations in and near mountains is crucial to ensure that any interventions in these complex social-ecological systems are appropriately resourced, and that valuable ecosystems are effectively protected. However, comprehensive and reproducible analyses on this subject are lacking. Here, we develop and implement an open workflow to quantify the sensitivity of mountain population estimates over recent decades, both globally and for several sets of relevant reporting regions, to alternative input dataset combinations. Relationships between mean population density and several potential environmental covariates are also explored across elevational bands within individual mountain regions (i.e. "sub-mountain range scale"). Globally, mountain population estimates vary greatly-from 0.344 billion (<5% of the corresponding global total) to 2.289 billion (>31%) in 2015. A more detailed analysis using one of the population datasets (GHS-POP) revealed that in ∼35% of mountain sub-regions, population increased at least twofold over the 40-year period 1975-2015. The urban proportion of the total mountain population in 2015 ranged from 6% to 39%, depending on the combination of population and urban extent datasets used. At sub-mountain range scale, population density was found to be more strongly associated with climatic than with topographic and protected-area variables, and these relationships appear to have strengthened slightly over time. Such insights may contribute to improved predictions of future mountain population distributions under scenarios of future climatic and demographic change. Overall, our work emphasizes that irrespective of data choices, substantial human populations are likely to be directly affected by-and themselves affect-mountainous environmental and ecological change. It thereby further underlines the urgency with which the multitudinous challenges concerning the interactions between mountain climate and human societies under change must be tackled.

Indexed as

Climate ChangeEcosystemHumansPopulation Density

Identifiers

PMID35857800
PMCPMC9299344

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.