2018
DOI: 10.1007/s11629-018-4916-3
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Mapping mountain areas: learning from Global, European and Norwegian perspectives

Abstract: Abstract:Defining the spatial extent of mountain areas has long been a challenge. In the present century, the availability of digital elevation models (DEMs) incorporated into geographic information systems (GIS) has allowed the definition of mountain areas based on topographic and other criteria. This paper presents the various delineations of mountains that have been prepared at three scales -global, regional (Europe), and national -and explores the reasons and processes leading to these delineations, and ho… Show more

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Cited by 25 publications
(20 citation statements)
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References 38 publications
(42 reference statements)
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“…There is no unified definition of what can be considered a mountain ecosystem neither in France nor globally (Price et al 2019). Defining the precise object of concern in the mountain NEA required creating an ad-hoc perimeter.…”
Section: Geographic Scopementioning
confidence: 99%
“…There is no unified definition of what can be considered a mountain ecosystem neither in France nor globally (Price et al 2019). Defining the precise object of concern in the mountain NEA required creating an ad-hoc perimeter.…”
Section: Geographic Scopementioning
confidence: 99%
“…Alessa et al () present diverse examples of successful SES work in mountains but with a focus on the western United States. Data‐oriented global mountain syntheses have focused on the elevational distributions of protected areas in mountains using high‐resolution digital elevation models (Elsena et al, ), the mapping and classification of mountains (Körner et al, ; Price et al, ; Sayre et al, ), continental‐scale syntheses of observed alpine flora changes over time (Gottfried et al, ), estimates of future changes to biophysical aspects of the cryosphere (Huss et al, ), and trade‐offs in clusters of ES over time (Locatelli et al, ). No concerted efforts have synthesized the complex threats to MtSES worldwide or highlighted opportunities to address these challenges, partly due to the diverse sociocultural, political, and economic contexts in which mountains occur.…”
Section: Introductionmentioning
confidence: 99%
“…During last few decades, there were many efforts to define mountainous areas and to map the occurrence of these areas globally (Kapos et al, 2000;Körner et al, 2011Körner et al, , 2017Elsen and Tingley, 2015;Antonelli et al, 2018;Price et al, 2019). The resulting classification system, which has been employed in many studies (Elsen and Tingley, 2015;Price et al, 2019), is based on elevation (>300 m asl) and ruggedness criteria, and indicates that mountain areas occupy approximately 21-24% of the global land area (Kapos et al, 2000;Meybeck et al, 2001).…”
Section: Environmental Variation Along Montane Elevational Gradientsmentioning
confidence: 99%
“…During last few decades, there were many efforts to define mountainous areas and to map the occurrence of these areas globally (Kapos et al, 2000;Körner et al, 2011Körner et al, , 2017Elsen and Tingley, 2015;Antonelli et al, 2018;Price et al, 2019). The resulting classification system, which has been employed in many studies (Elsen and Tingley, 2015;Price et al, 2019), is based on elevation (>300 m asl) and ruggedness criteria, and indicates that mountain areas occupy approximately 21-24% of the global land area (Kapos et al, 2000;Meybeck et al, 2001). However, because the criteria previously used to define mountain areas allowed the inclusion of areas (e.g., plateaus, hilly lowland terrain) that seem inappropriate in a mountain biodiversity context, the methodology was improved and refined by applying a finer spatial resolution and considering local elevation range (maximal elevation difference among neighboring grid points: 200 m across 3 × 3 grid points of 30 within each grid cell; see Körner et al, 2011 for more detail) (Körner et al, 2011(Körner et al, , 2017Price et al, 2019).…”
Section: Environmental Variation Along Montane Elevational Gradientsmentioning
confidence: 99%
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