Taiga Landscape Degradation Evidenced by Indigenous Observations and Remote Sensing

Arina O. Morozova (), Kelsey E. Nyland and Vera V. Kuklina
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Arina O. Morozova: Department of Geography, The George Washington University, Washington, DC 20052, USA
Kelsey E. Nyland: Department of Geography, The George Washington University, Washington, DC 20052, USA
Vera V. Kuklina: Department of Geography, The George Washington University, Washington, DC 20052, USA

Sustainability, 2023, vol. 15, issue 3, 1-17

Abstract: 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.

Keywords: informal roads; Evenki; indigenous knowledge; development; unsupervised classification; spatial autocorrelation analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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