Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing
Siberian taiga is subject to intensive logging and natural resource exploitation, which promote the proliferation of informal roads: trails and unsurfaced service roads neither recognized nor maintained by the government. While transportation development can improve connectivity between communities...
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ftmdpi:oai:mdpi.com:/2071-1050/15/3/1751/ 2023-08-20T04:06:20+02:00 Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing Arina O. Morozova Kelsey E. Nyland Vera V. Kuklina agris 2023-01-17 application/pdf https://doi.org/10.3390/su15031751 EN eng Multidisciplinary Digital Publishing Institute Sustainable Urban and Rural Development https://dx.doi.org/10.3390/su15031751 https://creativecommons.org/licenses/by/4.0/ Sustainability; Volume 15; Issue 3; Pages: 1751 informal roads Evenki indigenous knowledge development unsupervised classification spatial autocorrelation analysis Text 2023 ftmdpi https://doi.org/10.3390/su15031751 2023-08-01T08:20:36Z Siberian taiga is subject to intensive logging and natural resource exploitation, which promote the proliferation of informal roads: trails and unsurfaced service roads neither recognized nor maintained by the government. While transportation development can improve connectivity between communities and urban centers, new roads also interfere with Indigenous subsistence activities. This study quantifies Land-Cover and Land-Use Change (LCLUC) in Irkutsk Oblast, northwest of Lake Baikal. Observations from LCLUC are used in spatial autocorrelation analysis with roads to identify and examine major drivers of transformations of social–ecological–technological systems. Spatial analysis results are informed by interviews with local residents and Indigenous Evenki, local development history, and modern industrial and political actors. A comparison of relative changes observed within and outside Evenki-administered lands (obshchina) was also conducted. The results illustrate: (1) the most persistent LCLUC is related to change from coniferous to peatland (over 4% of decadal change); however, during the last decade, extractive and infrastructure development have become the major driver of change leading to conversion of 10% of coniferous forest into barren land; (2) anthropogenic-driven LCLUC in the area outside obshchina lands was three times higher than within during the980s and 1990s and more than 1.5 times higher during the following decades. Text Evenki taiga MDPI Open Access Publishing Evenki ENVELOPE(132.817,132.817,59.683,59.683) Sustainability 15 3 1751 |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
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informal roads Evenki indigenous knowledge development unsupervised classification spatial autocorrelation analysis |
spellingShingle |
informal roads Evenki indigenous knowledge development unsupervised classification spatial autocorrelation analysis Arina O. Morozova Kelsey E. Nyland Vera V. Kuklina Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing |
topic_facet |
informal roads Evenki indigenous knowledge development unsupervised classification spatial autocorrelation analysis |
description |
Siberian taiga is subject to intensive logging and natural resource exploitation, which promote the proliferation of informal roads: trails and unsurfaced service roads neither recognized nor maintained by the government. While transportation development can improve connectivity between communities and urban centers, new roads also interfere with Indigenous subsistence activities. This study quantifies Land-Cover and Land-Use Change (LCLUC) in Irkutsk Oblast, northwest of Lake Baikal. Observations from LCLUC are used in spatial autocorrelation analysis with roads to identify and examine major drivers of transformations of social–ecological–technological systems. Spatial analysis results are informed by interviews with local residents and Indigenous Evenki, local development history, and modern industrial and political actors. A comparison of relative changes observed within and outside Evenki-administered lands (obshchina) was also conducted. The results illustrate: (1) the most persistent LCLUC is related to change from coniferous to peatland (over 4% of decadal change); however, during the last decade, extractive and infrastructure development have become the major driver of change leading to conversion of 10% of coniferous forest into barren land; (2) anthropogenic-driven LCLUC in the area outside obshchina lands was three times higher than within during the980s and 1990s and more than 1.5 times higher during the following decades. |
format |
Text |
author |
Arina O. Morozova Kelsey E. Nyland Vera V. Kuklina |
author_facet |
Arina O. Morozova Kelsey E. Nyland Vera V. Kuklina |
author_sort |
Arina O. Morozova |
title |
Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing |
title_short |
Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing |
title_full |
Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing |
title_fullStr |
Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing |
title_full_unstemmed |
Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing |
title_sort |
taiga landscape degradation evidenced by indigenous observations and remote sensing |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
https://doi.org/10.3390/su15031751 |
op_coverage |
agris |
long_lat |
ENVELOPE(132.817,132.817,59.683,59.683) |
geographic |
Evenki |
geographic_facet |
Evenki |
genre |
Evenki taiga |
genre_facet |
Evenki taiga |
op_source |
Sustainability; Volume 15; Issue 3; Pages: 1751 |
op_relation |
Sustainable Urban and Rural Development https://dx.doi.org/10.3390/su15031751 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/su15031751 |
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Sustainability |
container_volume |
15 |
container_issue |
3 |
container_start_page |
1751 |
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1774717348463247360 |