Search Results (30)

Flux contribution area analysis is a valuable method for identifying greenhouse gas flux sources and their spatiotemporal variations. Flux footprint models are commonly applied to determine the origin of flux observations and estimate the location, size, and relative contributions of different flux source regions. Based on eddy covariance observation data, this study utilized the Kljun model and ART Footprint Tool to analyze the source area dynamics of peatland CO₂ fluxes in the permafrost region of the Greater Khingan Mountains, examining the distribution characteristics of flux contribution areas across different seasons, and atmospheric conditions, while also assessing the influence of vegetation types on these areas. The results indicated that: (1) due to regional climate conditions and terrain, the predominant wind direction in all seasons was northeast-southwest, aligning with the main flux contribution direction; (2) when the flux contribution area reached 90%, the maximum source area distances under the stable and unstable atmospheric conditions were 393.3 and 185.6 m, respectively, with the range and distance of flux contribution areas being significantly larger under stable conditions; and (3) the peatland vegetation primarily consisted of trees, tall shrubs, dwarf shrubs, sedges, and mosses, among which shrub communities dominating flux contribution areas (55.6–59.1%) contribute the most to the flux contribution areas, followed by sedges (16.7–17.7%) and mosses (18.6–19.9%), while the influence of trees (0.4–0.6%) was minimal. Full article

Long-term intensive tillage has led to soil environment degradation, reduced fertility, and difficulty in increasing crop yield in the Mollisol region of northeast China. In order to improve the soil’shydrothermal environment and nutrient content, we conducted field experiments to investigate the effects of different tillage practices and the amount of straw mulching on soil hydrothermal environment and nutrient content in agricultural soils in seasonal permafrost areas. Four treatments were established: no-tillage without straw (NT0), no-tillage with half straw mulching (NT1), no-tillage with full straw mulching (NT2), and rotary tillage without straw (CK) as the control treatment. The results indicate that the no-tillage with straw mulching treatments increased the soil ammonium nitrogen (NH₄⁺-N) and nitrate nitrogen (NO₃⁻-N) content, accompanied by improvements in the soil’s water content and regulation of soil temperature changes, as compared to the CK treatment. Specifically, the soil’s NH₄⁺-N and NO₃⁻-N content in the NT2 treatment were significantly increased by 25.65% and 38.81%, respectively. Our study indicates that NT2 treatment is the most suitable tillage practice and straw-returning method in the Mollisol region of northeast China. This study can provide a theoretical basis and reference for the efficient utilization of farmland soil in seasonal permafrost areas. Full article

The permafrost in Northeast China is experiencing rapid degradation due to the influence of climate change and human activities, profoundly impacting the local ecological environment and engineering construction. Understanding the spatiotemporal dynamics of long-term permafrost in this region is crucial; however, systematic research on this topic remains scarce. This study combines meteorological station data, MODIS land surface temperature (LST) datasets, and borehole locations to apply the surface frost number (SFn) model. This approach enables the simulation and estimation of the spatial distribution and changes in the area of the surface frost number without vegetation effects (SFnv) and permafrost temperature (PT) in Northeast China from 1971 to 2020. The area of the SFnv > 0.49 within the permafrost region decreased substantially from approximately 44.353 × 10⁴ km² to 19.909 × 10⁴ km² between 1971 and 2020, with a notable change in 1988. The area of permafrost calculated using PT < 0 was slightly smaller, declining from 39.388 × 10⁴ km² to 29.852 × 10⁴ km². There was also a significant increase in the area with PT ranging from −1 °C to 0 °C, indicating a decline in permafrost stability. Approximately 10.926 × 10⁴ km² of stable permafrost has been transformed into semi-stable and unstable permafrost. Moreover, from 1982 to 2020, the NDVI was negatively correlated with the area of stable permafrost and positively correlated with the area of transitional or unstable permafrost. Vegetation cover decreased as transitional or unstable permafrost degraded. These findings provide valuable information for permafrost research and engineering development in cold regions, as well as for future planning and adaptation strategies. Full article

The significant interest in the islands in the Russian Arctic has been in terms of available oil reserves, which determine the direction of economic development and associated environmental risks for this sector of the Arctic in the near future. Kotelny Island is the largest island of the New Siberian Islands Archipelago included in the protected zone of the Lena Delta Nature Reserve, which is located at 76° N, washed from the west by the Laptev Sea, washed from the east by the East Siberian Sea in a permafrost zone, and characterized by harsh climatic conditions defined by the northeast winds that prevail in vegetative season. January sees temperatures ranging from −32 to −35 °C, and July from +6 to +8 °C, which causes a short growing season. Samples were taken between August 3 and 8, 2018 in 12 freshwater bodies where 210 taxa were revealed. Aquatic communities were dominated by zygnematophycean and diatom algae, grouped in the basins of two rivers and associated with the position on the island’s landscape, which suggests the influence of cold north-east winds, leading to the avoidance of habitats in open and high places, which was revealed by statistical methods and also confirms the high individuality of taxa composition. Bioindication methods showed that water bodies are slightly alkaline, with low ion concentrations, with the presence of sulfides in low-lying habitats, and average saturation with organic matter. The mesotrophic status of the studied water bodies was evaluated through an assessment and the type of nutrition in the communities of algae and cyanobacteria indicates they formed there as true autotrophs, which corresponds to the status of a protected area and can serve as a reference level for monitoring anthropogenic impact. Full article

Surface freezing and thawing processes pose significant influences on surface water and energy balances, which, in turn, affect vegetation growth, soil moisture, carbon cycling, and terrestrial ecosystems. At present, the changes in surface freezing and thawing states are hotspots of ecological research, but the variations of surface frozen days (SFDs) are less studied, especially in the permafrost areas covered with boreal forest, and the influence of the environmental factors on the SFDs is not clear. Utilizing the Advanced Microwave Scanning Radiometer for EOS (AMSRE) and Microwave Scanning Radiometer 2 (AMSR2) brightness temperature data, this study applies the Freeze–Thaw Discriminant Function Algorithm (DFA) to explore the spatiotemporal variability features of SFDs in the Northeast China Permafrost Zone (NCPZ) and the relationship between the permafrost distribution and the spatial variability characteristics of SFDs; additionally, the Optimal Parameters-based Geographical Detector is employed to determine the factors that affect SFDs. The results showed that the SFDs in the NCPZ decreased with a rate of −0.43 d/a from 2002 to 2021 and significantly decreased on the eastern and western slopes of the Greater Khingan Mountains. Meanwhile, the degree of spatial fluctuation of SFDs increased gradually with a decreasing continuity of permafrost. Snow cover and air temperature were the two most important factors influencing SFD variability in the NCPZ, accounting for 83.9% and 74.8% of the spatial variation, respectively, and SFDs increased gradually with increasing snow cover and decreasing air temperature. The strongest explanatory power of SFD spatial variability was found to be the combination of air temperature and precipitation, which had a coefficient of 94.2%. Moreover, the combination of any two environmental factors increased this power. The findings of this study can be used to design ecological environmental conservation and engineer construction policies in high-latitude permafrost zones with forest cover. Full article

Climate warming has resulted in significant changes in permafrost in Northeast China, leading to notable alterations in soil organic carbon (SOC) stocks. These changes are crucial for both the global carbon cycle and climate change, as well as directly impacting the sustainable development of ecosystems. In order to examine the SOC dynamics and the impact of permafrost changes on SOC, we investigate the changes of permafrost extent based on a regression model and TTOP (top temperature of permafrost) model and the relationship between land use and land cover (LULC), SOC stocks, and permafrost changes in Northeast China. The results showing a shrinking permafrost area from 37.43 × 10⁴ km² to 16.48 × 10⁴ km² during the period from the 1980s to the 2010s in Northeast China, and the SOC stock decreased by 24.18 Tg C from the 1980s to the 1990s and then rapidly increased by 102.84 Tg C in the 2000s. Permafrost degradation speeds up the succession of LULC, impacting about 90% of the SOC in permafrost regions. The relationship between permafrost changes and SOC in Northeast China shows that permafrost degradation significantly reduces SOC stocks in the short term but increases SOC stocks in the long term, and that LULC play a crucial role in regulating this relationship. The goals of this study are to acquire an understanding of permafrost status and deepening insights into the dynamics of SOC. Simultaneously, the study aims to furnish valuable scientific references for shaping policies on sustainable land use and management in the future, all the while advancing the cause of ecological equilibrium and sustainable development in Northeast China and other areas. Full article

In the permafrost zone, the vegetation growth condition is closely related to the permafrost occurrence state. Changbai Mountain is the highest peak in Northeast China and is also a permafrost distribution area, where the vegetation shows an obvious vertical distribution pattern, and the alpine timberline has a clear boundary. The intersecting zone of alpine timberline is an ecologically fragile area that can be used as an external signal amplifier and is an important site for monitoring climate change. In this study, the surface frost number and alpine timberline in the Changbai Mountain area were analyzed through combining ground and remote-sensing data, using the freezing number model and support vector machine method. The results show that the distribution characteristics of alpine timberline and permafrost at elevation are correlated, there is a response mechanism of alpine timberline to the degradation of permafrost, and the upward migration rate of alpine timberline has increased in the last 20 years. The continuous degradation of permafrost will change the environment of vegetation growth, which, in turn, will affect the global carbon cycle process. Focusing on the state of permafrost will help us to understand climate change in depth, and we can respond to a series of impacts caused by ecological changes in cold regions in advance. Full article

The high-resolution permafrost distribution maps have a closer relationship with engineering applications in cold regions because they are more relative to the real situation compared with the traditional permafrost zoning mapping. A particle swarm optimization algorithm was used to obtain the index η with 30 m resolution and to characterize the distribution probability of permafrost at the field scale. The index consists of five environmental variables: slope position, slope, deviation from mean elevation, topographic diversity, and soil bulk density. The downscaling process of the surface frost number from a resolution of 1000 m to 30 m is achieved by using the spatial weight decomposition method and index η. We established the regression statistical relationship between the surface frost number after downscaling and the temperature at the freezing layer that is below the permafrost active layer base. We simulated permafrost temperature distribution maps with 30 m resolution in the four periods of 2003–2007, 2008–2012, 2013–2017, and 2018–2021, and the permafrost area is, respectively, 28.35 × 10⁴ km², 35.14 × 10⁴ km², 28.96 × 10⁴ km², and 25.21 × 10⁴ km². The proportion of extremely stable permafrost (<−5.0 °C), stable permafrost (−3.0~−5.0 °C), sub-stable permafrost (−1.5~−3.0 °C), transitional permafrost (−0.5~−1.5 °C), and unstable permafrost (0~−0.5 °C) is 0.50–1.27%, 6.77–12.45%, 29.08–33.94%, 34.52–39.50%, and 19.87–26.79%, respectively, with sub-stable, transitional, and unstable permafrost mainly distributed. Direct and indirect verification shows that the permafrost temperature distribution maps after downscaling still have high reliability, with 83.2% of the residual controlled within the range of ±1 °C and the consistency ranges from 83.17% to 96.47%, with the identification of permafrost sections in the highway engineering geological investigation reports of six highway projects. The maps are of fundamental importance for engineering planning and design, ecosystem management, and evaluation of the permafrost change in the future in Northeast China. Full article

High-resolution permafrost mapping is an important direction in permafrost research. Arxan is a typical area with permafrost degradation and is situated on the southern boundary of the permafrost region in Northeast China. With the help of Google Earth Engine (GEE), the maximum entropy classifier (MaxEnt) is used for permafrost mapping using the land surface temperature (LST) of different seasons, deviation from mean elevation (DEV), solar radiation (SR), normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) as the characteristic variables. The prior data of permafrost distribution were primarily based on 201 borehole data and field investigation data. A permafrost probability (PP) distribution map with a resolution of 30 m was obtained. The receiver operating characteristic (ROC) curve was used to test the distribution results, with an area under the curve (AUC) value of 0.986. The results characterize the distribution of permafrost at a high resolution. Permafrost is mainly distributed in the Greater Khingan Mountains (GKM) in the research area, which run from the northeast to the southwest, followed by low-altitude area in the northwest. According to topographic distribution, permafrost is primarily found on slope surfaces, with minor amounts present in peaks, ridges, and valleys. The employed PP distribution mapping method offers a suggestion for high-resolution permafrost mapping in permafrost degradation areas. Full article

Thermokarst lakes in permafrost regions are highly dynamic due to drainage events triggered by climate warming. This study focused on mapping lake drainage events across the Northeast Siberian coastal tundra from 2000 to 2020 and identifying influential factors. An object-based lake analysis method was developed to detect 238 drained lakes using a well-established surface water dynamics product. The LandTrendr change detection algorithm, combined with continuous Landsat satellite imagery, precisely dated lake drainage years with 83.2% accuracy validated against manual interpretation. Spatial analysis revealed the clustering of drained lakes along rivers and in subsidence-prone Yedoma regions. The statistical analysis showed significant warming aligned with broader trends but no evident temporal pattern in lake drainage events. Our machine learning model identified lake area, soil temperature, summer evaporation, and summer precipitation as the top predictors of lake drainage. As these climatic parameters increase or surpass specific thresholds, the likelihood of lake drainage notably increases. Overall, this study enhanced the understanding of thermokarst lake drainage patterns and environmental controls in vulnerable permafrost regions. Spatial and temporal dynamics of lake drainage events were governed by complex climatic, topographic, and permafrost interactions. Integrating remote sensing with field studies and modeling will help project lake stability and greenhouse gas emissions under climate change. Full article

China’s largest high-latitude permafrost distribution zone is in Northeast China. With the intensification of global warming and engineering construction, the carbon stored in permafrost will gradually thaw and be released in the form of methane gas. However, research on the changes in methane concentration and emission sources in this area is still unclear. In this paper, the AIRS (Atmospheric Infrared Sounder) data carried by the Aqua satellite were used to analyze the distribution and change trends in the overall methane concentration in the near-surface troposphere in Northeast China from 2003 to 2022. These data, combined with national meteorological and on-site monitoring data, were used to study the methane emission characteristics and sources in the permafrost area in Northeast China. The results show that the methane concentration in the near-surface troposphere of Northeast China is mainly concentrated in the permafrost area of the Da and Xiao Xing’an Mountains. From 2003 to 2022, the methane concentration in the near-surface troposphere of the permafrost area in Northeast China showed a rapid growth trend, with an average linear trend growth rate of 4.787 ppbv/a. In addition, the methane concentration in the near-surface troposphere of the permafrost area shows a significant bimodal seasonal variation pattern. The first peak appears in summer (June–August), with its maximum value appearing in August, and the second peak appears in winter (December–February), with its maximum value appearing in December. Combined with ground surface methane concentration monitoring, it was found that the maximum annual ground surface methane concentration in degraded permafrost areas occurred in spring, causing the maximum average growth rate in methane concentration, also in spring, in the near-surface troposphere of permafrost areas in Northeast China (with an average value of 6.05 ppbv/a). The growth rate of methane concentration in the southern permafrost degradation zone is higher than that in the northern permafrost stable zone. In addition, with the degradation of permafrost, the geological methane stored deep underground (methane hydrate, coal seam, etc., mainly derived from the accumulation of ancient microbial origin) in the frozen layer will become an important source of near-surface troposphere methane in the permafrost degradation area. Due to the influence of high-permeability channels after permafrost degradation, the release rate of methane gas in spring is faster than predicted, and the growth rate of methane concentration in the near-surface troposphere of permafrost areas can be increased by more than twice. These conclusions can provide a data supplement for the study of the carbon cycle in permafrost areas in Northeast China. Full article

This study was conducted in the territory of the industrial site of the Udachny Mining and Processing Division (Yakutia, northeast Russia). The objects of study were permafrost soils and two species of shrubs (Betula middendorffii T. and Duschekia fruticose R.). Soil and plant samples were analyzed using atomic absorption spectrometry for the presence of PTEs (Pb, Ni, Mn, Cd, Co, Cr, Zn, Cu, and As). The bioaccumulation factor (BAF), frequency of occurrence (Hi), pollution index (PI), and pollution load index (PLI) were calculated. The PI and PLI are calculated for both soil and two plant species for the first time in this study. The results showed that the soils have a high Ni, Cr, Co, As, and Mn content. It has been established that high soil pollution naturally leads to an increase in the concentration of elements in the leaves of shrubs. The soils and vegetation are dominated by elements associated with trap magmatism—Cr, Co, Cu, and dolerite dikes—Mn and Zn. For Betula middendorffii, the PLI was classified as unpolluted to moderately polluted, and Duschekia fruticosa. was classified as unpolluted. The high level of contamination is typical for areas located near industrial sites, such as waste dumps, kimberlite pipes, tailings ponds, and roads. The BAF results confirmed that the leaves of Betula middendorffii are able to accumulate more PTEs and have the highest level of resistance to PTE contamination in mining environments. This analysis showed that the consistent application of the PI, PLI, and BAF indices is very efficient in the ecological and biogeochemical assessment of the situation in industrial development areas. Full article

The accumulation of potentially toxic elements (PTEs) in agricultural soils is of particular concern in China, while its status, ecological risks, and human health hazards have been little studied in the permafrost areas of Northeast China. In this study, 75 agricultural soil samples (0–20 cm) were collected from the Arctic Village, Mo’he City, in the northernmost part of China. The average concentration (mean ± standard deviation) of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were 12.11 ± 3.66 mg/kg, 0.11 ± 0.08 mg/kg, 52.50 ± 8.83 mg/kg, 12.08 ± 5.12 mg/kg, 0.05 ± 0.02 mg/kg, 14.90 ± 5.35 mg/kg, 22.38 ± 3.04 mg/kg, and 68.07 ± 22.71 mg/kg, respectively. Correlation analysis, cluster analysis, and principal component analysis indicated that As, Cu, Ni, and Zn likely originated from geogenic processes, Hg and Pb from long-range atmospheric transport, Cd from planting activities, and Cr from Holocene alluvium. The geo-accumulation index and enrichment factor showed that As, Cd, Hg, and Zn are enriched in soils. The Nemerow pollution index showed that 66.67%, 24%, and 1.33% of soil samples were in slight, moderate, and heavy pollution levels, respectively, with Hg being the most important element affecting the comprehensive pollution index. The potential ecological risk index showed that 48.00% and 1.33% of soil samples were in the moderate ecological risk and high potential ecological risk levels, respectively. The non-carcinogenic and carcinogenic human health risk index for adults and children were both less than 1, which was within the acceptable range. This study revealed the accumulation pattern of PTEs in agricultural soils of permafrost regions and provided a scientific basis for research on ecological security and human health. Full article

The source region of the Yellow River (SRYR) is situated on the permafrost boundary in the northeast of the Qinghai-Tibet Plateau (QTP), which is an area highly sensitive to climate change. As a result of increasing global temperatures, the permafrost in this region has undergone significant degradation. In this study, we utilized Sentinel-1 to obtain ground surface deformation data in the SRYR from June 2017 to January 2022. We then analyzed the differences in terrain deformation under various environmental conditions. Our findings indicated an overall subsidence trend in the SRYR, with a long-term deformation velocity of −4.2 mm/a and seasonal deformation of 8.85 mm. Furthermore, the results showed that terrain deformation varied considerably from region to region, and that the Huanghe’ yan sub-basin with the highest permafrost coverage among all sub-basins significantly higher subsidence rates than other regions. Topography strongly influenced ground surface deformation, with flat slopes exhibiting much higher subsidence rates and seasonal deformation. Moreover, the ground temperature and ground ice richness played a certain role in the deformation pattern. This study also analyzed regional deformation details from eight boreholes and one profile line covering different surface conditions, revealing the potential for refining the permafrost boundary. Overall, the results of this study provide valuable insights into the evolution of permafrost in the SRYR region. Full article

This paper provides the results of a study on fungal species diversity in the active and permafrost layers of peatlands within frozen peatbogs in the flatland areas of the cryolitozone, European Northeast of Russia (forest-tundra zone, southern and northern tundra subzones). Fungal taxonomic list includes eighty-three species from seventeen genera and two forms of Mycelia sterilia. The phylum Mucoromycota is represented by fifteen species (18% of total isolate number), and these species exhibit the following distribution by genus: Mucor (four), Mortierella (seven), Umbelopsis (three), Podila (one). Ascomycota is represented by sixty-eight species from thirteen genera. The genus Penicillium dominates the species saturation (thirty-seven species, 44%). Soil microfungal complex is represented by rare species (51%), random species (32%), frequent species (15%), and dominant species (2%). In peat soils, dominant species are Penicillium canescens (72%) and non-pigmented (albino) Mycelia sterilia (61%); abundant species are Talaromyces funiculosus (41%), Pseudogymnoascus pannorum (36%), albino Mycelia sterilia (29%), Umbelopsis vinacea (25%), Mortierella alpina (17%), Penicillium decumbens (21%), P. spinulosum (20%), and P. canescens (17%). In active layers of peat soils, abundant species are Penicillium thomii (14%), Mycelia sterilia (13%), Penicillium spinulosum (13%), Penicillium simplicissimum (13%) in forest-tundra; Talaromyces funiculosus (21%), albino Mycelia sterilia (15%), Umbelopsis vinacea (14%) in southern tundra; Penicillium decumbens (23%), P. canescens (17%), P. thomii (13%) in northern tundra. In permafrost peat layers, abundant species are Penicillium spinulosum (17%), Talaromyces funiculosus (34%), and Umbelopsis vinacea (15%) in forest-tundra; Pseudogymnoascus pannorum (30%) and Mortierella alpina (28%) in southern tundra; Pseudogymnoascus pannorum (80%) in northern tundra. Full article