Search Results (75)

Forested wetlands in temperate mountain ecosystems play a critical role in carbon sequestration and biodiversity maintenance, yet their accurate delineation remains challenging due to spectral similarity with forests and anthropogenic interference. Here, we present an optimized two-stage Random Forest framework integrating 2019–2022 growing season datasets from Sentinel-1 C-SAR, ALOS-2 L-PALSAR, Sentinel-2 MSI, and Landsat-8 TIRS with environmental covariates. The methodology first applied NDBI thresholding (NDBI > 0.12) to exclude 94% of urban/agricultural areas through spectral masking, then implemented an optimized Random Forest classifier (ntree = 1200, mtry = 28) with 10-fold cross-validation, leveraging 42 features including L-band HV backscatter (feature importance = 47), Sentinel-2 SWIR (Band12; importance = 57), and land surface temperature gradients. This study pioneers a 10 m resolution forest swamp map in the Changbai Mountain wetlands, achieving 87.18% overall accuracy (Kappa = 0.84) with strong predictive performance (AUC = 0.89). Forest swamps showed robust classification metrics (PA = 80.37%, UA = 86.87%), driven by L-band SAR’s superior discriminative power (p < 0.05). Quantitative assessment demonstrated that L-band SAR increased classification accuracy in canopy penetration scenarios by 4.2% compared to optical-only approaches, while thermal-IR features reduced confusion with forests. Forested swamps occupied 229.95 km² (9% of protected areas), predominantly in transitional ecotones (720–850 m elevation) between herbaceous wetlands and forest. This study establishes that multi-sensor fusion enables operational wetland monitoring in topographically complex regions, providing a transferable framework for temperate mountain ecosystems. The dataset advances precision conservation strategies for these climate-sensitive habitats, supporting sustainable development goals targets for wetland protection through enhanced machine learning interpretability and anthropogenic interference mitigation. Full article

Despite traditional knowledge’s (TK’s) potential to mitigate climate-induced vulnerabilities across diverse climates, cold-region communities remain critically understudied. To bridge that gap, this study adopts the pressure–state–response (PSR) framework to analyze how Indigenous knowledge in China’s Jinjiang Chalet Village—a 300-year-old cold-region settlement—embodies dynamic resilience across ecological, climatic, social, and economic dimensions. Combining semi-structured interviews with Indigenous Elders, UAV-based multispectral analysis, and environmental simulations, we identify strategies rooted in sustainable wisdom: ecosystem stewardship, climate-responsive architecture, community governance, and adaptive economic practices. A key innovation lies in the Eco-Wisdom Laboratory—a pilot project operationalizing TK through modern passive design and participatory education, demonstrating how traditional woodcraft and microclimate management can be integrated with contemporary technologies to achieve scalable, low-carbon solutions. Crucially, we advance the concept of living inheritance by showcasing how such hybrid practices decolonize static preservation paradigms, enabling communities to codify TK into tangible, future-oriented applications. This study provides a replicable framework for embedding TK into global sustainability agendas, particularly for severe cold regions facing similar stressors. Our findings advocate for policy reforms centering Indigenous agency in climate adaptation planning, offering actionable insights for architects, policymakers, and educators working at the nexus of cultural heritage and ecological resilience. Full article

This study applied the fully coupled model WRF/WRF-Hydro to simulate land, air, and water cycles in the Changbai Mountain area (CMA) in Northeast China. This study evaluated the applicability of the coupled model in the region and analyzed the impact of regional climate change on the water cycle in the study area over the past half-century. The temperature in the Changbai Mountains increased significantly from 1975 to 2020. Precipitation, canopy water, and all types of evapotranspiration showed different increasing trends, whereas surface runoff showed a decreasing trend. The comparison revealed that precipitation, canopy water, canopy evaporation, and total evapotranspiration increased gradually in the low-latitude subbasins, whereas runoff decreased more rapidly. Runoff in the study area showed an annual double peak, which was due to snowmelt in spring and abundant precipitation in summer. Under the influence of climate change, the thawing time of frozen soil and snow cover in the study area will advance, leading to an increase in the spring runoff peak and earlier occurrence time. Our results provide a reference for the study of the water cycle process of the coupled model in cold mountainous areas and a scientific reference for the scientific response to climate change and the protection of regional water resource security. Full article

Understanding the species diversity distribution of lycophytes and ferns is crucial for identifying biodiversity hotspots and conservation planning. Northeast China, a biodiversity-sensitive area affected by climate change, lacks comprehensive information on diversity and distribution patterns of these plants. To address this gap, we sorted out all naturally distributed lycophyte and fern species recorded in the region, analyzed their diversity, frequency, and threatened status. Correlation and regression analyses were also conducted with geographic gradients at the county level. Our study identified a total of 143 taxa (species and intraspecific taxa) belonging to 48 genera of 19 families of lycophytes and ferns in Northeast China, with terrestrial (85 spp.) and epilithic (55 spp.) life forms dominating. Species with frequencies below 10.00% comprised 75.52% of the total. Notably, five species were listed as threatened in the Red List of China’s Biodiversity, highlighting the urgency for conservation measures. Overall, species diversity decreased from low to high latitudes, but increased with maximum elevation and elevation range. High diversity areas were concentrated mainly in Da Hinggan Mountains, Xiao Hinggan Mountains, and Changbai Mountains, which correspond to the main mountainous terrain of Northeast China. Changbai Mountains exhibited the highest diversity, establishing itself as a pivotal diversity center for lycophytes and ferns in the region. Exploring the diversity and distribution of lycophytes and ferns is crucial for understanding their interactions with environmental gradients, and thereby supporting significant biodiversity conservation efforts in Northeast China. Full article

The sustainable management of state-owned forest regions is significant for improving the nationally determined contribution and achieving carbon neutrality. The administrative area of key state-owned forest regions in northeast China and Inner Mongolia, hereafter referred to as forest regions, spans a forested area of 27.16 million hectares and a forest coverage rate of 82.97%. This represents China’s largest state-owned forest resource base, with extensive and concentrated forest areas. However, despite this vast forest coverage, the region’s forest stand density remains below the national and global average, underscoring the need for improved carbon sequestration performance. This study used the Stochastic Frontier Analysis (SFA) method to measure the carbon sequestration efficiency of key state-owned forest regions in northeast China and Inner Mongolia. A spatiotemporal Geographically and Temporally Weighted Regression model (GTWR) was employed to reveal the spatiotemporal non-stationarity of the driving mechanism of carbon sequestration efficiency. Finally, the benchmarking management method was applied to predict the carbon sequestration potential. The results indicated that the carbon sequestration efficiency of forest regions exhibited an overall increasing trend over time, with significant spatial and temporal heterogeneity among forest industry enterprises (forest farms). Specifically, the carbon sequestration efficiency ranked from highest to lowest is as follows: Greater Khingan Forestry Group, Inner Mongolia Forestry Industry Group, Longjiang Forestry Industry Group, Changbai Mountain Forestry Industry Group, Jilin Forestry Industry Group, and Yichun Forestry Industry Group. Furthermore, carbon sequestration efficiency was driven by both natural and socioeconomic factors, but the effects of these factors were spatiotemporally non-stationary. Generally, enterprise output value, labor compensation, tending, and accumulated temperature had positive effects on carbon sequestration efficiency, while capital structure, altitude, and precipitation had negative effects. Finally, our findings revealed that the carbon sequestration potential of forest regions is substantial. If technical efficiency is improved, the carbon sequestration potential of forest regions could expand by 0.86 times the current basis, reaching 31.29 mtCO₂ by 2030. These results underscore the importance of respecting the differences and conditionality of forest development paths and promoting the sustainable management of key state-owned forest regions through scientific approaches, which is crucial for achieving carbon neutrality goals. Full article

Changbai Mountain is located in China’s northeastern seasonal stable snow zone and is a high-latitude water tower. The changes in snow cover have a great influence on the hydrological process and ecological balance. This study quantitatively analyzed the spatio-temporal variation in snow cover in the Changbai Mountain region and its driving factors based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. To improve the accuracy of snow cover analysis, a simple cloud removal algorithm was applied, and the locally optimal NDSI threshold was investigated. The results showed that the snow-covered area (SCA) in the Changbai Mountain region exhibited strong seasonality, with the largest SCA found in January. The SCA during the winter season showed an insignificant increasing trend ($83.88{\mathrm{km}}^2$) from 2001 to 2022. The variability in SCA observed from November to the following March has progressively decreased in recent years. The snow cover days (SCD) showed high spatial variation, with areas with decreased and increased SCD mainly found in the southern and northern regions, respectively. It was also revealed that temperature is the primary hydrometeorological factor influencing the snow variation in the study domain, particularly during the spring season or in high-elevation areas. The examined large-scale teleconnection indices showed a relatively weak correlation with SCA, but they may partially explain the abnormally low snow cover phenomenon in the winter of 2018–2019. Full article

In this research, a numerical model for simulating dam break floods was developed utilizing ArcGIS 10.8, 3ds Max 2021, and Flow-3D v11.2 software, with the aim of accurately representing the dam break disaster at Tianchi Lake in Changbai Mountain. The study involved the construction of a Triangulated Irregular Network (TIN) terrain surface and the application of 3ds Max 2021 to enhance the precision of the three-dimensional terrain data, thereby optimizing the depiction of the region’s topography. The finite volume method, along with multi-block grid technology, was employed to model the dam break scenario at Tianchi Lake. To evaluate the severity of the dam break disaster, the research integrated land use classifications within the study area with the simulated flood depths resulting from the dam break, applying the natural breaks method for hazard level classification. The findings indicated that the computational fluid dynamics (CFD) numerical model developed in this study significantly enhanced both the efficiency and accuracy of the simulations. Furthermore, the disaster assessment methodology that incorporated land use types facilitated the generation of inundation maps and disaster zoning maps across two scenarios, thereby effectively assessing the impacts of the disaster under varying conditions. Full article

Forest defoliating pests are significant global forest disturbance agents, posing substantial threats to forest ecosystems. However, previous studies have lacked systematic analyses of the continuous spatiotemporal distribution characteristics over a complete 3–5 year disaster cycle based on remote sensing data. This study focuses on the Dendrolimus superans outbreak in the Changbai Mountain region of northeastern China. Utilizing leaf area index (LAI) data derived from Sentinel-2A satellite images, we analyze the extent and dynamic changes of forest defoliation. We comprehensively examine the spatiotemporal patterns of forest defoliating pest disasters and their development trends across different forest types. Using the geographical detector method, we quantify the main influencing factors and their interactions, revealing the differential impacts of various factors during different growth stages of the pests. The results show that in the early stage of the Dendrolimus superans outbreak, the affected area is extensive but with mild severity, with newly affected areas being 23 times larger than during non-outbreak periods. In the pre-hibernation stage, the affected areas are smaller but more severe, with a cumulative area reaching up to 8213 hectares. The spatial diffusion characteristics of the outbreak follow a sequential pattern across forest types: Larix olgensis, Pinus sylvestris var. mongolica, Picea koraiensis, and Pinus koraiensis. The most significant influencing factor during the pest development phase was the relative humidity of the year preceding the outbreak, with a q-value of 0.27. During the mitigation phase, summer precipitation was the most influential factor, with a q-value of 0.12. The combined effect of humidity and the low temperatures of 2020 had the most significant impact on both the development and mitigation stages of the outbreak. This study’s methodology achieves a high-precision quantitative inversion of long-term disaster spatial characteristics, providing new perspectives and tools for real-time monitoring and differentiated control of forest pest infestations. Full article

Conservational tillage (NT) is widely recognized globally for its efficacy in mitigating soil loss due to wind and water erosion. However, a systematic large-scale estimate of NT’s impact on soil loss reduction in Northeast, China’s primary granary, remains absent. This study aimed to investigate the spatial and temporal variability of soil erosion under NT compared to conventional tillage (CT) in the black soil region and to analyze the underlying mechanisms driving these erosions. The Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) models were employed, incorporating previously published plot/watershed data to estimate the potential reduction of water and wind erosion by NT in this region. Results indicated that under CT practices, water- and wind-induced soil losses were widely distributed in the arable land of Northeast China, with intensities of 2603 t km⁻² a⁻¹ and 34 t km⁻² a⁻¹, respectively. Furthermore, the erosive processes of water and wind erosion were significantly reduced by 56.4% and 91.8%, respectively, under NT practices compared to CT. The highest efficiency in soil conservation using NT was observed in the mountainous regions such as the Changbai Mountains and Greater Khingan Mountains, where water erosion was primarily driven by cropland slopes and wind erosion was driven by the wind speed. Conversely, the largest areas of severe erosion were observed in the Songnen Plain, primarily due to the significant proportion of arable land in this region. In the plain regions, water-induced soil loss was primarily influenced by precipitation, with light and higher levels of erosion occurring more frequently on long gentle slopes (0–3°) than on higher slope areas (3–5°). In the temporal dimension, soil loss induced by water and wind erosion ceased during the winter under both tillage systems due to snow cover and water freezing in the soil combined with the extremely cold climate. Substantial reductions were observed under NT from spring to autumn compared to CT. Ultimately, the temporal and spatial variations of soil loss under CT and NT practices were established from 2010 to 2018 and then projected onto a cropland map of Northeast China. Based on this analysis, NT is recommended as most suitable practice in the southern regions of Northeast China for maintaining soil health and crop yield production, while its suitability decreases in the northern and eastern regions. Full article

Flash drought is characterized by rapid onset and short-duration drought conditions caused by a combination of factors, including high evaporation, high temperature, and prolonged periods of little to no precipitation, leading to a sudden and severe decrease in soil moisture levels. In comparison to conventional drought, it is more susceptible to the effects of global warming and has the potential to become a common drought phenomenon in the coming years, necessitating further research. In this paper, we focused on flash drought events, specifically in forest parts of northeastern China that are included within the Greater Khingan Mountains (GKM), Lesser Khingan Mountains (LKM), and Changbai Mountains (CM), using daily soil moisture data as well as SPOT- VEGETATION NDVI satellite data from 2000 to 2020 and determined their impact on the forest NDVI. Our major findings are as follows. (1) The forest within GKM had the maximum area being affected by flash drought events. (2) The frequency ranged from 1 to 2 times, whereas the total duration varied between 20 and 55 days over the study area in a 21-year period. (3) Flash drought was most common in the plant-growing seasons. (4) The flash drought events had a negative influence on the forest NDVI. Our study contributes to a deeper understanding of the flash drought dynamics in forest areas of northeast China for flash drought monitoring, prediction, and management strategies in this region. Full article

The vertical structure of forests, including the measurement of canopy height, helps researchers understand forest characteristics such as density and growth stages. It is one of the key variables for estimating forest biomass and is crucial for accurately monitoring changes in forest carbon storage. However, current technologies face challenges in achieving cost-effective, accurate measurement of canopy height on a widespread scale. This study introduces a method aimed at extracting accurate forest canopy height from The Global Ecosystem Dynamics Investigation (GEDI) data, followed by a comprehensive large-scale analysis utilizing this approach. Before mapping, verifying and analyzing the accuracy and sensitivity of parameters that may affect the precision of GEDI data extraction, such as slope, aspect, and vegetation coverage, can aid in assessment and decision-making, enhancing inversion accuracy. Consequently, a random forest method based on parameter sensitivity analysis is developed to break through the constraints of traditional issues and achieve forest canopy height inversion. Sensitivity analysis of influencing parameters surpasses the uniform parameter calculation of traditional methods by differentiating the effects of various land use types, thereby enhancing the precision of height inversion. Moreover, potential factors affecting the accuracy of GEDI data, such as vegetation cover density, terrain complexity, and data acquisition conditions, are thoroughly analyzed and discussed. Subsequently, large-scale forest canopy height estimation is conducted by integrating vegetation cover Normalized Difference Vegetation Index (NDVI), sun altitude angle and terrain data, among other variables, and accuracy validation is performed using airborne LiDAR data. With an R² value of 0.64 and an RMSE of 8.62, the mapping accuracy underscores the resilience of the proposed method in delineating forest canopy height within the Changbai Mountain forest domain. Full article

Due to global warming and increased human activity, the wild population of Thuja koraiensis Nakai (T. koraiensis) has dropped, placing it in danger. An understanding of the response of T. koraiensis to climate change and the determination of priority conservation areas are tremendously critical for proper conservation. Using sixty-nine T. koraiensis distribution points and seven environmental factors, the Maxent model was used to predict potentially suitable areas and spatial variation patterns of T. koraiensis and the Marxan conservation planning model was used to evaluate conservation gap areas. Research shows that the dominant environmental factors affecting the distribution of potentially suitable areas for T. koraiensis included elevation, precipitation of the driest month, isothermality and precipitation of the wettest quarter. Under the current climatic conditions, highly suitable areas for T. koraiensis are mainly distributed in the Changbai Mountains within Samjiyon County and Baishan City, the Hamgyong Mountains within the western part of Hamgyong-Bukto Province, and the T’aeback-Sanmaek Mountains within Gangwon-do, Kumgangsan Special Administrative Region and Kangwon-do. Under future climate conditions, suitable areas for T. koraiensis show a decreasing trend, and the suitable area will be reduced to higher elevations, and the Hamgyong Mountains may become a refuge. Based on GAP analysis, 69.69% of the priority conservation areas of T. koraiensis are located outside of the nature reserve, and these conservation gap areas are primarily in the southern part of the Changbai Mountains and Kangwon-do. Full article

Protected areas are widely considered an essential strategy for biodiversity conservation. Dictyostelids are unique protists known to have important ecological functions in promoting soil and plant health through their top-down regulation of ecosystem processes, such as decomposition, that involve bacterial populations. But the relationship between dictyostelid diversity within protected areas remains poorly understood, especially on a large scale. Herein, we report data on the distribution of dictyostelids, identified with ITS + SSU rRNA molecular and morphology-based taxonomy, from soil samples collected in the Fanjing Mountain protected area of Guizhou Province, Southwest China. We compared the biodiversity data of dictyostelids in Fanjing Mountain with similar data from previously sampled sites in four other protected areas, including Changbai Mountain (CB), Gushan Mountain (GS), Baiyun Mountain (BY), and Qinghai–Tibet Plateau (QT) in China. We identified four species of dictyostelids belonging to three genera (Dictyostelium, Heterostelium, and Polysphondylium) and herein provide information on the taxonomy of these species. Two species (Heterostelium pallidum and Dictyostelium purpureum) are common and widely distributed throughout the world, but one species (Polysphondylium fuscans) was new to China. Our data indicate that there is no distinguishable significant correlation between the dictyostelid species studied and environmental factors. Overall, the similarity index between Baiyun Mountain in Henan Province and Fanjing Mountain in Guizhou Province, located at approximately the same longitude, is the highest, and the Jaccard similarity coefficients (Jaccard index) of family, genus, and species are 100%, 100%, and 12.5%, respectively. From a species perspective, species in the same climate zone are not closely related, but obvious geographical distributions are evident in different climate zones. This preliminary study provided evidence of the ecological adaptation of dictyostelids to different biological niches. Full article

The eco-agricultural park is a new comprehensive agricultural technology system integrating agricultural production, rural economic development, ecological environment protection, and efficient resource utilization. Therefore, an in-depth analysis of the ecosystem structure of eco-agricultural parks will help achieve the goal of coordinated symbiosis between human development and environmental protection. This study takes the research area of the Eco-agricultural Park of Jinchuan Town, Huinan County, a typical town in the Changbai Mountains of Northeast China. Based on field surveys, market research, farmer consultation, and related data collection, emergy theory and methods are used to construct an emergy model for the park. The value evaluation index system integrates the unique emergy index of the agricultural ecosystem with the traditional emergy index system to conduct a targeted evaluation of the park’s functional structure and sustainable development capabilities in order to improve the efficiency of material and energy use and provide technical reference for ecological construction and comprehensive development of agricultural industry in mountainous areas in northern China. The research results show that: (1) The annual input total emergy of the eco-agricultural park is 4.04E+24 sej/a, and the emergy of labor input, electricity input, and topsoil loss is relatively high. The park is in a labor-intensive stage. The annual output total emergy is 5.09E+24 sej/a, the park is dominated by planting and forestry industries. (2) The park’s emergy utilization intensity is high—production efficiency is high, economic development is advanced, and the system’s self-control, adjustment, and feedback functions are vital—and plays a significant role in promoting the development of the regional economy. However, the park relies more on investment from external resources, and production in the park puts pressure on the environment. (3) The current sustainable development capability of the study area is weak, and the factors affecting the sustainable development capability are mainly energy loss and uneven distribution of industrial areas in the park. Effective measures to promote the transformation of the park to develop technology-intensive industries and improve the sustainable development performance of the park were proposed. These include: adjusting the proportion of industries in the park; reducing high-energy external input emergy, such as industrial auxiliary emergy; reducing the loss of non-renewable natural resources through ecological engineering measures, such as reducing the depth of slope runoff in the park; and combining modern resource-based production technology and environmentally sound management methods to reduce energy loss and rational use of natural resources. Full article

There are few studies on the climate and glacial scale in the mountains east of the Qinghai–Tibet Plateau. So, we used glacial features to determine the range of the area’s paleoglaciers and the equilibrium line altitude (ELA) of theGlA modern and paleoglaciers in the Tianchi area of the Changbai Mountains. Then, the GlaRe toolbox 2015 () was used to reconstruct the surface of the paleoglaciers. The probable air temperature during the glacial advances of the LGM was calculated by applying the P-T and LR models. The results showed the following: (1) the change in ELA is 950 m in the Tianchi area of the Changbai Mountains; (2) glacial coverage in the Tianchi area of the Changbai Mountains during the LGM period was ~27.05 km² and the glacial volume was ~9.94 km³; and (3) the mean temperature in the Tianchi area of the Changbai Mountains during the LGM was 6.6–9.0 °C lower than today’s, and was the principal factor controlling the growth of glaciers. There is a difference in the climate change in monsoon-influenced mountains during the LGM, and this difference may be related to the precipitation in the mountains. Full article