A hierarchical inventory of the world’s mountains for global comparative mountain science

Snethlage, Mark A.; Geschke, Jonas; Ranipeta, Ajay; Jetz, Walter; Yoccoz, Nigel G.; Körner, Christian; Spehn, Eva; Fischer, Markus; Urbach, Davnah

doi:10.1038/s41597-022-01256-y

Cited by 37 publications

(37 citation statements)

References 25 publications

(31 reference statements)

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“…We calculated SDG 15.4.1 using a site-based methodology close to the o cial one 13 and an own areabased approach. Both calculations attributed GMBA mountain ranges 11 to each KBA and resulted in values for entire countries and subnational reporting units. Our code is based on methods by Birdlife International (https://github.com/BirdLifeInternational/kba-overlap).…”

Section: Methodsmentioning

confidence: 99%

“…Mountains are a textbook example in this context. They host exceptionally rich and functionally important biodiversity 8,9 ; differ in their species' diversity, spatial distribution 10 , and levels of endemism across latitudinal, longitudinal, and elevational gradients; and represent distinct social-ecological systems and landscape units 11 that fall under different jurisdictions within and across countries. As such, they constitute pertinent conservation units and are acknowledged as a conservation priority 12 in the face of accelerating global change.…”

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confidence: 99%

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Assessing the protection of Key Biodiversity Areas in mountains at conservation-relevant scales

Geschke

Snethlage

et al. 2022

Preprint

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Indicators of biodiversity protection at the national level are used to assess progress toward global goals. However, they provide little information at scales relevant for conservation and management. Hence we provide an area-based alternative to the current indicator calculated at the level of individual mountain ranges, which is directly relevant for assessing progress toward SDG 15.4.1. This allows identifying mountain areas in need of enhanced conservation efforts, within and across countries.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Assessing the protection of Key Biodiversity Areas in mountains at conservation-relevant scales

Geschke

Snethlage

et al. 2022

Preprint

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“…Here, we used the IPCC AR6 Working Group II regions, which are very similar to those defined by Hewitson et al [57]. The latest version of the Global Mountain Biodiversity Assessment's (GMBA's) Mountain Inventory (v2) [58,59], which provides named mountain range extent polygons within a hierarchical system, was also used for aggregation purposes. In the specific incoming GMBA layer used, external boundaries were buffered beyond the maximum combined extent of K1, K2, and K3 by approximately 5 km.…”

Section: Data: Selection and Preparationmentioning

confidence: 99%

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

et al. 2022

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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.

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“…The digital elevation model (DEM) and slope data were from NASA SRTM datasets, with a spatial resolution of 30 m. The annual records of the HFP were from the Figshare repository from 2000 to 2018, which combined eight variables related to human activities (built environment, population density, nighttime lights, cropland, pasture, roads, railways, and navigable waterways) at a spatial resolution of 1000 m [30,37]. The mountain dataset was from the Global Mountain Biodiversity Assessment (GMBA) Mountain Inventory v2, which provided a new inventory of mountain range locations and developed ranges [38,39]. The Global Inland Water dataset was from the NASA LP DAAC, USGS/EROS Center, which showed inland surface water bodies, including fresh and saline lakes, rivers, and reservoirs, in the year 2000 with a spatial resolution of 30 m.…”

Section: Data Resourcesmentioning

confidence: 99%

Spatiotemporal Patterns and Driving Factors of Ecological Vulnerability on the Qinghai-Tibet Plateau Based on the Google Earth Engine

Zhao

Zhang

et al. 2022

Remote Sensing

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With the background of climate change and intensified human activities, environmental problems are becoming increasingly prominent on the Qinghai-Tibet Plateau (QTP). For the development of efficient environmental policies and protection measures, quick and accurate assessments of the spatiotemporal patterns in ecological vulnerability are crucial. Based on the Google Earth Engine (GEE) platform, we used Moderate Resolution Imaging Spectroradiometer (MODIS), Shuttle Radar Topography Mission (SRTM), and human footprint (HFP) datasets to analyze the spatiotemporal distributions and main driving factors of the remote sensing ecological vulnerability index (RSEVI) for the QTP. Moreover, spatial autocorrelation analysis and the standard deviational ellipse (SDE) were used to analyze the spatiotemporal characteristics. Our results showed that the RSEVI gradually increased from the southeast to the northwest of the QTP. From 2000 to 2018, the potential vulnerability area increased by 6.59 × 104 km2, while the extreme vulnerability area decreased by 1.84 × 104 km2. Moran’s I value of the RSEVI was greater than 0 and increased, indicating that the aggregation degree was increasing. The gravity center was located in Nagqu, Tibet, and shifted to the northwest from 2000 to 2015 and to the southeast from 2015 to 2018. The SDE rotated in a counterclockwise direction. The three most important driving factors of ecological vulnerability were wetness, land surface temperature (LST), and the normalized difference vegetation index (NDVI), indicating that climate and vegetation were the dominant factors. Moreover, this study developed a promising method for the ecological vulnerability assessment of large-scale and long time series datasets, and it provides theoretical support for the ecological conservation and sustainable development of the QTP under global change.

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A hierarchical inventory of the world’s mountains for global comparative mountain science

Cited by 37 publications

References 25 publications

Assessing the protection of Key Biodiversity Areas in mountains at conservation-relevant scales

Assessing the protection of Key Biodiversity Areas in mountains at conservation-relevant scales

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

Spatiotemporal Patterns and Driving Factors of Ecological Vulnerability on the Qinghai-Tibet Plateau Based on the Google Earth Engine

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