Permafrost Landscape Research in the Northeast of Eurasia

Fedorov, A.A.

doi:10.3390/earth3010028

Cited by 8 publications

(2 citation statements)

References 47 publications

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“…In general, each region of the world has adopted different landscape typology, depending on regional or local characteristics of ecosystems, landscape concepts, and taxonomic organization approaches, or adapted to the needs of land management. On the territory of Yakutia (Eastern Siberia), the concept of permafrost landscapes has long been used in a system with a heuristic structure, divided into horizontal and vertical subsystems according to certain distinctive features inherent in its components [15,16]. One of the unique features of these landscapes is the presence of permafrost, which is reflected in the typology.…”

Section: Introductionmentioning

confidence: 99%

“…There are many studies in the field of landscape structure, change, and dynamics based on the modeling of remote sensing data and GIS-based analysis [13,16,22]. The issues of improving the methods of mapping and modeling remote sensing data are mainly aimed at the accuracy and efficiency of determining the landscape structure and land cover change [24].…”

Section: Introductionmentioning

confidence: 99%

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Distribution and Structure Analysis of Mountain Permafrost Landscape in Orulgan Ridge (Northeast Siberia) Using Google Earth Engine

Zakharov

Gadal

Kamičaitytė

et al. 2022

Land

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An analysis of the landscape spatial structure and diversity in the mountain ranges of Northeast Siberia is essential to assess how tundra and boreal landscapes may respond to climate change and anthropogenic impacts in the vast mountainous permafrost of the Arctic regions. In addition, a precise landscape map is required for knowledge-based territorial planning and management. In this article, we aimed to explore and enhanced methods to analyse and map the permafrost landscape in Orulgan Ridge. The Google Earth Engine cloud platform was used to generate vegetation cover maps based on multi-fusion classification of Sentinel 2 MSI and Landsat 8 OLI time series data. Phenological features based on the monthly median values of time series Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), and Normalized Difference Moisture Index (NDMI) were used to recognize geobotanical units according to the hierarchical concept of permafrost landscapes by the Support Vector Machine (SVM) classifier. In addition, geomorphological variables of megarelief (mountains and river valleys) were identified using the GIS-based terrain analysis and landform classification of the ASTER GDEM scenes mosaic. The resulting environmental variables made it possible to categorize nine classes of mountain permafrost landscapes. The result obtained was compared with previous permafrost landscape maps, which revealed a significant difference in distribution and spatial structure of intrazonal valleys and mountain tundra landscapes. Analysis of the landscape structure revealed a significant distribution of classes of mountain Larix-sparse forests and tundra. Landscape diversity was described by six longitudinal and latitudinal landscape hypsometric profiles. River valleys allow boreal–taiga landscapes to move up to high-mountainous regions. The features of the landscape structure and diversity of the ridge are noted, which, along with the specific spatial organization of vegetation and relief, can be of key importance for environmental monitoring and the study of regional variability of climatic changes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distribution and Structure Analysis of Mountain Permafrost Landscape in Orulgan Ridge (Northeast Siberia) Using Google Earth Engine

Zakharov

Gadal

Kamičaitytė

et al. 2022

Land

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Permafrost-thaw lake development in Central Yakutia: sedimentary ancient DNA and element analyses from a Holocene sediment record

et al. 2023

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In Central Yakutia (Siberia) livelihoods of local communities depend on alaas (thermokarst depression) landscapes and the lakes within. Development and dynamics of these alaas lakes are closely connected to climate change, permafrost thawing, catchment conditions, and land use. To reconstruct lake development throughout the Holocene we analyze sedimentary ancient DNA (sedaDNA) and biogeochemistry from a sediment core from Lake Satagay, spanning the last c. 10,800 calibrated years before present (cal yrs BP). SedaDNA of diatoms and macrophytes and microfossil diatom analysis reveal lake formation earlier than 10,700 cal yrs BP. The sedaDNA approach detected 42 amplicon sequence variants (ASVs) of diatom taxa, one ASV of Eustigmatophyceae (Nannochloropsis), and 12 ASVs of macrophytes. We relate diatom and macrophyte community changes to climate-driven shifts in water level and mineral and organic input, which result in variable water conductivity, in-lake productivity, and sediment deposition. We detect a higher lake level and water conductivity in the Early Holocene (c. 10,700–7000 cal yrs BP) compared to other periods, supported by the dominance of Stephanodiscus sp. and Stuckenia pectinata. Further climate warming towards the Mid-Holocene (7000–4700 cal yrs BP) led to a shallowing of Lake Satagay, an increase of the submerged macrophyte Ceratophyllum, and a decline of planktonic diatoms. In the Late Holocene (c. 4700 cal yrs BP–present) stable shallow water conditions are confirmed by small fragilarioid and staurosiroid diatoms dominating the lake. Lake Satagay has not yet reached the final stage of alaas development, but satellite imagery shows an intensification of anthropogenic land use, which in combination with future warming will likely result in a rapid desiccation of the lake.

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Simulating long-term wildfire impacts on boreal forest structure in Central Yakutia, Siberia, since the Last Glacial Maximum

Glückler,

Gloy,

Dietze

et al. 2024

fire ecol

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Background Wildfires are recognized as an important ecological component of larch-dominated boreal forests in eastern Siberia. However, long-term fire-vegetation dynamics in this unique environment are poorly understood. Recent paleoecological research suggests that intensifying fire regimes may induce millennial-scale shifts in forest structure and composition. This may, in turn, result in positive feedback on intensifying wildfires and permafrost degradation, apart from threatening human livelihoods. Most common fire-vegetation models do not explicitly include detailed individual-based tree population dynamics, but a focus on patterns of forest structure emerging from interactions among individual trees may provide a beneficial perspective on the impacts of changing fire regimes in eastern Siberia. To simulate these impacts on forest structure at millennial timescales, we apply the individual-based, spatially explicit vegetation model LAVESI-FIRE, expanded with a new fire module. Satellite-based fire observations along with fieldwork data were used to inform the implementation of wildfire occurrence and adjust model parameters. Results Simulations of annual forest development and wildfire activity at a study site in the Republic of Sakha (Yakutia) since the Last Glacial Maximum (c. 20,000 years BP) highlight the variable impacts of fire regimes on forest structure throughout time. Modeled annual fire probability and subsequent burned area in the Holocene compare well with a local reconstruction of charcoal influx in lake sediments. Wildfires can be followed by different forest regeneration pathways, depending on fire frequency and intensity and the pre-fire forest conditions. We find that medium-intensity wildfires at fire return intervals of 50 years or more benefit the dominance of fire-resisting Dahurian larch (Larix gmelinii (Rupr.) Rupr.), while stand-replacing fires tend to enable the establishment of evergreen conifers. Apart from post-fire mortality, wildfires modulate forest development mainly through competition effects and a reduction of the model’s litter layer. Conclusion With its fine-scale population dynamics, LAVESI-FIRE can serve as a highly localized, spatially explicit tool to understand the long-term impacts of boreal wildfires on forest structure and to better constrain interpretations of paleoecological reconstructions of fire activity.

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Permafrost Landscape Research in the Northeast of Eurasia

Cited by 8 publications

References 47 publications

Distribution and Structure Analysis of Mountain Permafrost Landscape in Orulgan Ridge (Northeast Siberia) Using Google Earth Engine

Distribution and Structure Analysis of Mountain Permafrost Landscape in Orulgan Ridge (Northeast Siberia) Using Google Earth Engine

Permafrost-thaw lake development in Central Yakutia: sedimentary ancient DNA and element analyses from a Holocene sediment record

Simulating long-term wildfire impacts on boreal forest structure in Central Yakutia, Siberia, since the Last Glacial Maximum

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