Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central Asia
Satellite images and digital elevation models provide an excellent database to analyze forest distribution patterns and forest limits in the mountain regions of semiarid central Asia on the regional scale. For the investigation area in the northern Tien Shan, a strong relationship between forest dis...
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doaj-1bc459fd11104b09805c976f4f2e818d2020-11-25T01:07:31ZengCopernicus PublicationsBiogeosciences1726-41701726-41892015-05-0112102893290510.5194/bg-12-2893-2015Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central AsiaM. Klinge0J. Böhner1S. Erasmi2Institute of Geography, University of Göttingen, Goldschmidtstr. 5, 37077 Göttingen, GermanyInstitute of Geography, University of Hamburg, Bundesstraße 55, 20146 Hamburg, GermanyInstitute of Geography, University of Göttingen, Goldschmidtstr. 5, 37077 Göttingen, GermanySatellite images and digital elevation models provide an excellent database to analyze forest distribution patterns and forest limits in the mountain regions of semiarid central Asia on the regional scale. For the investigation area in the northern Tien Shan, a strong relationship between forest distribution and climate conditions could be found. Additionally areas of potential human impact on forested areas are identified at lower elevations near the edge of the mountains based on an analysis of the differences in climatic preconditions and the present occurrence of forest stands. <br><br> The distribution of spruce (<i>Picea schrenkiana</i>) forests is hydrologically limited by a minimum annual precipitation of 250 mm and thermally by a minimum monthly mean temperature of 5 °C during the growing season. While the actual lower forest limit increases from 1600 m a.s.l. (above sea level) in the northwest to 2600 m a.s.l. in the southeast, the upper forest limit rises in the same direction from 1800 m a.s.l. to 2900 m a.s.l.. In accordance with the main wind directions, the steepest gradient of both forest lines and the greatest local vertical extent of the forest belt of 500 to 600 m to a maximum of 900 m occur at the northern and western mountain fronts. <br><br> The forests in the investigation area are strongly restricted to north-facing slopes, which is a common feature in semiarid central Asia. Based on the presumption that variations in local climate conditions are a function of topography, the potential forest extent was analyzed with regard to the parameters slope, aspect, solar radiation input and elevation. All four parameters showed a strong relationship to forest distribution, yielding a total potential forest area that is 3.5 times larger than the present forest remains of 502 km<sup>2</sup>.http://www.biogeosciences.net/12/2893/2015/bg-12-2893-2015.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
M. Klinge J. Böhner S. Erasmi |
spellingShingle |
M. Klinge J. Böhner S. Erasmi Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central Asia Biogeosciences |
author_facet |
M. Klinge J. Böhner S. Erasmi |
author_sort |
M. Klinge |
title |
Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central Asia |
title_short |
Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central Asia |
title_full |
Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central Asia |
title_fullStr |
Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central Asia |
title_full_unstemmed |
Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central Asia |
title_sort |
modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central asia |
publisher |
Copernicus Publications |
series |
Biogeosciences |
issn |
1726-4170 1726-4189 |
publishDate |
2015-05-01 |
description |
Satellite images and digital elevation models provide an excellent database
to analyze forest distribution patterns and forest limits in the mountain
regions of semiarid central Asia on the regional scale. For the investigation
area in the northern Tien Shan, a strong relationship between forest
distribution and climate conditions could be found. Additionally areas of
potential human impact on forested areas are identified at lower elevations
near the edge of the mountains based on
an analysis of the differences in climatic preconditions and the present
occurrence of forest stands.
<br><br>
The distribution of spruce (<i>Picea schrenkiana</i>) forests is
hydrologically limited by a minimum annual precipitation of 250 mm and
thermally by a minimum monthly mean temperature of 5 °C during the
growing season. While the actual lower forest limit increases from 1600 m a.s.l. (above sea level) in the northwest to 2600 m a.s.l. in the southeast,
the upper forest limit rises in the same direction from 1800 m a.s.l. to
2900 m a.s.l.. In accordance with the main wind directions, the steepest
gradient of both forest lines and the greatest local vertical extent of the
forest belt of 500 to 600 m to a maximum of 900 m occur at the northern and
western mountain fronts.
<br><br>
The forests in the investigation area are strongly restricted to north-facing slopes, which is a common feature in semiarid central Asia. Based on
the presumption that variations in local climate conditions are a function of
topography, the potential forest extent was analyzed with regard to the
parameters slope, aspect, solar radiation input and elevation. All four
parameters showed a strong relationship to forest distribution, yielding a
total potential forest area that is 3.5 times larger than the present forest
remains of 502 km<sup>2</sup>. |
url |
http://www.biogeosciences.net/12/2893/2015/bg-12-2893-2015.pdf |
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