ABSTRACT
Corneal transplantation is a common treatment for corneal diseases. Secondary glaucoma after corneal transplantation is the second leading cause of failure of keratoplasty. This article reviews the mechanism and treatment of secondary glaucoma after corneal transplantation.
ABSTRACT
The main bioavailable phenolics from of Gongju (GJ) and their mechanism for hepato-protection remain unclear. To select the GJ phenolics with high bioavailability, chrysanthemum digestion and Caco-2 cells were used and their hepato-protective potential were examined by using AML-12 cells. The digestive recovery and small intestinal transit rate of the main phenolic compounds ranged from 28.52 to 69.53% and 6.57% â¼ 15.50%, respectively. Among them, chlorogenic acid, 3,5-dicaffeoylquinic acid, and 1,5-dicaffeoylquinic acid, showed higher small intestinal transit rates and digestive recoveries. Furthermore, we found that by increasing intracellular Catalase (CAT) and Superoxide dismutase (SOD) viability and lowering Malondialdehyde (MDA) level (P < 0.05), 3,5-dicaffeoylquinic acid significantly mitigated the oxidative damage of AML-12 liver cells more than the other two phenolics. Our results demonstrated that 3,5-dicaffeoylquninic acid was the primary phenolic compounds in GJ that effectively reduced liver damage, providing a theoretical basis for the development of GJ as a potentially useful resource for hepatoprotective diet.
Subject(s)
Chrysanthemum , Oxidative Stress , Phenols , Chrysanthemum/chemistry , Humans , Phenols/chemistry , Phenols/pharmacology , Oxidative Stress/drug effects , Plant Extracts/pharmacology , Plant Extracts/chemistry , Superoxide Dismutase/metabolism , Cell Line , Malondialdehyde/metabolism , Caco-2 Cells , Catalase/metabolism , Antioxidants/pharmacology , Antioxidants/chemistryABSTRACT
The effects of rising atmospheric CO2 concentrations (Ca) with climate warming on intrinsic water-use efficiency and radial growth in boreal forests are still poorly understood. We measured tree-ring cellulose δ13C, δ18O, and tree-ring width in Larix dahurica (larch) and Betula platyphylla (white birch), and analyzed their relationships with climate variables in a boreal permafrost region of northeast China over past 68 years covering a pre-warming period (1951-1984; base period) and a warm period (1985-2018; warm period). We found that white birch but not larch significantly increased their radial growth over the warm period. The increased intrinsic water-use efficiency in both species was mainly driven by elevated Ca but not climate warming. White birch but not larch showed significantly positive correlations between tree-ring δ13C, δ18O and summer maximum temperature as well as vapor pressure deficit in the warm period, suggesting a strong stomatal response in the broad-leaved birch to temperature changes. The climate warming-induced radial growth enhancement in white birch is primarily associated with a conservative water-use strategy. In contrast, larch exhibits a profligate water-use strategy. It implies an advantage for white birch over larch in the warming permafrost regions.
Subject(s)
Betula , Larix , Permafrost , Water , Larix/growth & development , Larix/physiology , Betula/growth & development , Betula/physiology , Water/metabolism , China , Climate Change , Taiga , Global WarmingABSTRACT
To evaluate the release and activity of Indian jujube phenolics in vivo, its peel and pulp were subjected to simulated digestions. The phenolics content and antioxidant activity of the digested samples were determined. The results showed that the total phenolics/flavonoids in the peel were respectively 4.63 and 4.48 times higher than that in the pulp. The release of phenolics and flavonoids respectively increased by 79.75% and 39.98% in the peel and 86.34% and 23.54% in the pulp after the intestinal digestion. The correlation between the total phenolics/flavonoids and antioxidant activity was higher in the peel (r > 0.858, p < 0.01) than that in the pulp. The phenolics profiles of the peel were almost the same after the digestion, and four phenolics including naringenin tri-glycoside, quercetin-3-O-[(2-hexosyl)-6-rhamnosyl] -hexoside, quercetin-3-O-pentosylhexoside and quercetin-3-O-(2-pentosyl -rhamnoside)-4'-O-rhamnoside were found to be the main flavonoids of Indian jujube peel, and they showed high recovery (>89.88%) during the digestion, implying that these phenolics may play a vital role in the function of Indian jujubes.
ABSTRACT
The simulation optimization method was used to the identification of light nonaqueous phase liquid (LNAPL) groundwater contamination source (GCS) with the help of a hypothetical case in this study. When applying the simulation optimization method to identify GCS, it was a common technical means to establish surrogate model for the simulation model to participate in the iterative calculation to reduce the calculation load and calculation time. However, it was difficult for a single modeling method to establish surrogate model with high accuracy for the LNAPL contamination multiphase flow simulation model (MFSM). To give full play to advantages of single surrogate model and improve the accuracy of the surrogate model to the MFSM, a combination of deep belief neural network (DBNN) and long short-term memory (LSTM) neural network was used to establish artificial intelligence ensemble surrogate model (AIESM) for the MFSM. At the same time, to reduce the influence of noise in observed concentrations on the accuracy of the identification results, empirical mode decomposition (EMD) and wavelet analysis methods were used to denoise the observed concentrations, and their noise reduction effects were compared. The observed concentrations with better noise reduction effect and the observed concentrations without denoising were used to construct the objective function, and constraints of the optimization model were determined meanwhile. Then, the objective function and the constraints were integrated to build the optimization model to identify GCS and simulation model parameters. Applying the AIESM instead of the MFSM to embed in the optimization model and participate in the iterative calculation. Finally, the genetic algorithm (GA) was used to solve the optimization model to obtain the identification results of GCS and simulation model parameters. The results showed that compared with the single DBNN and LSTM surrogate models, AIESM obtained the highest accuracy and could replace the MFSM to participate in the iterative calculation, thereby reducing the calculation load and calculation time by more than 99%. Comparing with the wavelet analysis, EMD could reduce the noise in the concentrations more effectively, improved the accuracy of the approximated concentrations to the actual values, and increased the accuracy of the GCSs identification results by 1.45%.
Subject(s)
Deep Learning , Groundwater , Artificial Intelligence , Neural Networks, Computer , Computer SimulationABSTRACT
PURPOSE: This article aims to summarize the incidence of these complications through a meta-analysis, analyze the causes of complications and provide clinical promotion and recommendations. METHODS: Databases and retrieval platform including PubMed, Web of science, Springer link, Cochrane clinical trials, ProQuest, ScienceDirect, Europe PMC, Wiley online, OVID, Clinical trials, CNKI and WanFang, and supplement the literature through Google Scholar, collect all the unilateral biportal endoscopy (UBE) controlled trials and non-controlled trials of UBE in the treatment of lumbar spinal stenosis (LSS). The search time limit is from January 1, 2000 to December 25, 2021. After two reviewers independently screened the literature, extracted data and evaluated the risk of bias in the included studies, meta-analysis was performed using Stata 15.1 software. RESULTS: Finally, 24 studies were included, including 999 patients. The results of a single-arm rate meta-analysis showed that the overall complication rate of UBE treatment of LSS was 6.27% [95% CI (0.0412, 0.0876)], and the incidence of dural tear was 2.49% [95% CI (0.0133, 0.0390)], the incidence of transient paresthesia was 0.14% [95% CI (0.0000, 0.0072)], the incidence of postoperative spinal epidural hematoma was 0.27% [95% CI (0.0000, 0.0096)], the incidence of postop headache, inadequate decompression, root injury and infection was 0.00%. CONCLUSION: Current evidence shows that the complication rate of UBE in the treatment of LSS is low, mainly due to dural tears. Limited by the number and quality of included studies, the above conclusions still need to be confirmed by more studies.
Subject(s)
Hematoma, Epidural, Spinal , Spinal Stenosis , Humans , Spinal Stenosis/surgery , Lumbar Vertebrae/surgery , Decompression, Surgical/adverse effects , Decompression, Surgical/methods , Endoscopy/adverse effects , Endoscopy/methods , Hematoma, Epidural, Spinal/etiology , Treatment OutcomeABSTRACT
The phenolics are the main bioactive substances of Huangshan Gongju, a famous chrysanthemum of China, but their digestive characteristics are still unknown. To explore the digestive properties of Huangshan Gongju phenolics, the flower was extracted and subjected to simulated digestions, and their phenolic profile and activity were analyzed. The results indicated that the total phenolics content and antioxidant activity of the extract varied with the simulated digestion steps, and they generally decreased in the oral and small intestine digestions but increased in the gastric digestion, and high correlations were detected between the total phenolics content and antioxidant activity (0.873 < r < 0.979, p < .01). The change of phenolic profile during the simulated digestions was similar to that of total phenolics content, and six individual phenolics were identified and quantified, and three of them, including chlorogenic acid, apigenin-7-O-rutinoside, and apigenin-7-O-6â³-acetylglucoside showed higher recovery (>64.29%), implying they may be the main functional phenolics of Huangshan Gongju. PRACTICAL APPLICATIONS: This study proved that most phenolics in Huangshan Gongju were relatively stable during digestion. The finding may guarantee the application of Huangshan Gongju in the field of functional foods.
Subject(s)
Antioxidants , Chrysanthemum , Phenols , Plant Extracts , DigestionABSTRACT
Hydrological processes in mid-latitude mountainous regions are greatly affected by changes in vegetation cover that induced by the climate change. However, studies on hydrological processes in mountainous regions are limited, because of difficulties in building and maintaining basin-wide representative hydrological stations. In this study, a new method, remote sensing technology for monitoring river discharge by combining satellite remote sensing, unmanned aerial vehicles and hydrological surveying, was used for evaluating the runoff processes in the Changbai Mountains, one of the mid-latitude mountainous regions in the eastern part of Northeast China. Based on this method, the impact of vegetation cover change on hydrological processes was revealed by combining the data of hydrological processes, meteorology, and vegetation cover. The results showed a decreasing trend in the monitored river discharge from 2000 to 2021, with an average rate of -5.13 × 105 m3 yr-1. At the monitoring section mainly influenced by precipitation, the precipitation-induced proportion of changes in river discharge to annual average river discharge and its change significance was only 6.5 % and 0.23, respectively, showing the precipitation change was not the cause for the decrease in river discharge. A negative impact of evapotranspiration on river discharge was found, and the decrease in river discharge was proven to be caused by the increasing evapotranspiration, which was induced by the drastically increased vegetation cover under a warming climate. Our findings suggested that increases in vegetation cover due to climate change could reshape hydrological processes in mid-latitude mountainous regions, leading to an increase in evapotranspiration and a subsequent decrease in river discharge.
Subject(s)
Hydrology , Remote Sensing Technology , China , Climate Change , RiversABSTRACT
The location and release history of groundwater contaminant sources (GCSs) are usually unknown after groundwater contamination is detected, thereby greatly hindering the design of contamination remediation schemes and contamination risk assessments. Many previous studies have used prior information such as the observed contaminant concentrations (OCC) to obtain information of GCSs, and various methods have been proposed for identifying GCSs, including simulation optimization (S/O) and ensemble Kalman filter (EnKF) methods. For the first time, the present study compared the suitability of the S/O and EnKF methods for GCSs identification based on two case studies by specifically considering the calculation time and effectiveness of GCS identification. The results showed that EnKF could reduce the calculation time required by more than 62% compared with S/O. However, the time saved did not compensate for the poor accuracy of the GCSs identification results. When the simulated contaminant concentrations (SCC) were used for GCSs identification, the MRE of the identification results with the S/O and EnKF methods were 2.79% and 5.09% in case one, respectively, and were 4.75% and 6.72% in case two. When the OCC were used for GCSs identification, the MRE of the identification results with the S/O and EnKF methods were 27.77% and 110.74% in case one, respectively, and 27.53% and 60.61% in case two. The identification results obtained using the EnKF method were not credible and the superior performance of the S/O method was obvious, thereby indicating that the EnKF method is much less suitable for actual GCSs identification compared with the S/O method.
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Frequent outbreaks of cyanobacterial blooms have become one of the most challenging water ecosystem issues and a critical concern in environmental protection. To overcome the poor stability of traditional detection algorithms, this paper proposes a method for detecting cyanobacterial blooms based on a deep-learning algorithm. An improved vegetation-index method based on a multispectral image taken by an Unmanned Aerial Vehicle (UAV) was adopted to extract inconspicuous spectral features of cyanobacterial blooms. To enhance the recognition accuracy of cyanobacterial blooms in complex scenes with noise such as reflections and shadows, an improved transformer model based on a feature-enhancement module and pixel-correction fusion was employed. The algorithm proposed in this paper was implemented in several rivers in China, achieving a detection accuracy of cyanobacterial blooms of more than 85%. The estimate of the proportion of the algae bloom contamination area and the severity of pollution were basically accurate. This paper can lay a foundation for ecological and environmental departments for the effective prevention and control of cyanobacterial blooms.
Subject(s)
Cyanobacteria , Deep Learning , Ecosystem , Environmental Monitoring/methods , EutrophicationABSTRACT
Current increases in not only the intensity and frequency but also the duration of drought events could affect the growth, physiology, and mortality of trees. We experimentally studied the effects of drought duration in combination with fertilization on leaf water potential, gas exchange, growth, tissue levels of non-structural carbohydrates (NSCs), tissue NSC consumption over-winter, and recovery after drought release in oak (Quercus petraea) and beech (Fagus sylvatica) saplings. Long drought duration (>1 month) decreased leaf water potential, photosynthesis, and NSC concentrations in both oak and beech saplings. Nitrogen fertilization did not mitigate the negative drought effects on both species. The photosynthesis and relative height increment recovered in the following rewetting year. Height growth in the rewetting year was significantly positively correlated with both pre- and post-winter root NSC levels. Root carbon reserve is critical for tree growth and survival under long-lasting drought. Our results indicate that beech is more sensitive to drought and fertilization than oak. The present study, in a physiological perspective, experimentally confirmed the view that the European beech, compared to oak, may be more strongly affected by future environmental changes.
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Regions at high latitudes and high altitudes are undergoing a more pronounced winter warming than spring warming, and such asymmetric warming will affect chilling and forcing processes and thus the spring phenology of plants. We analyzed winter chilling and spring forcing accumulation in relation to the spring phenology of three tree species (Ulmus pumila, Populus simonii, and Syringa oblata) growing in a cold region (CR) compared with trees in a warmer reference region (WR), using the Dynamic Model and the Growing Degree Hour (GDH) model. We tested that forcing rather than chilling affects the spring phenology of trees in CR (hypothesis I), and that trees in CR have both lower mean chilling and forcing temperature and thus longer accumulation periods than trees in WR (hypothesis II). The modeling results confirmed that chilling and forcing occur simultaneously during the early spring when temperature gradually increases. In line with our hypotheses, forcing played a crucial role in spring phenology in CR, but chilling and forcing combined to determine spring phenology in WR. The temperature during the chilling and forcing periods was lower and the accumulation period started earlier and ended later in CR than in WR. Moreover, the chilling accumulation was broken into two periods by the low deep winter temperature in CR, and that interruption will be removed by future strong winter warming. Future asymmetric warming, with a stronger temperature increase in winter than in spring, could decrease the forcing accumulation effects and increase the chilling effects on the spring phenology of plants in CR. This change in the balance between chilling and forcing will lead to a shift in plant phenology, which will further have major impacts on biogeochemical cycles and on ecosystem functions and services.
Subject(s)
Ecosystem , Trees , Climate Change , Cold Temperature , Seasons , TemperatureABSTRACT
Environmental factors that drive carbon storage are often used as an explanation for alpine treeline formation. However, different tree species respond differently to environmental changes, which challenges our understanding of treeline formation and shifts. Therefore, we selected Picea jezoensis and Betula ermanii, the two treeline species naturally occurring in Changbai Mountain in China, and measured the concentration of non-structural carbohydrates (NSC), soluble sugars and starch in one-year-old leaves, shoots, stems and fine roots at different elevations. We found that compared with P. jezoensis, the NSC and soluble sugars concentrations of leaves and shoots of B. ermanii were higher than those of P. jezoensis, while the starch concentration of all the tissues were lower. Moreover, the concentration of NSC, soluble sugars and starch in the leaves of B. ermanii decreased with elevation. In addition, the starch concentration of B. ermanii shoots, stems and fine roots remained at a high level regardless of whether the soluble sugars concentration decreased. Whereas the concentrations of soluble sugars and starch in one-year-old leaves, shoots and stems of P. jezoensis responded similarly changes with elevation. These findings demonstrate that compared with P. jezoensis, B. ermanii has a higher soluble sugars/starch ratio, and its shoots, stems and fine roots actively store NSC to adapt to the harsh environment, which is one of the reasons that B. ermanii can be distributed at higher altitudes.
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Daily surface soil temperature data from 360 weather stations in China during 1962-2011 were retrieved and analyzed. The data revealed two aspects of asymmetric soil warming. Firstly, there was asymmetry between day and night in terms of increases in soil temperature. The daily maximum surface soil temperature ( S T max ) and daily minimum surface soil temperature ( S T min ) increased at rates of 0.031 and 0.055 °C/year over the 50-year interval, respectively. As a consequence of the more rapid increases in S T min , the soil diurnal temperature range (SDTR) decreased at most stations (average rate of -0.025 °C/year), with the most profound decrease in winter (-0.08 °C/year). The solar duration (SD) was positively related to SDTR and is regarded as the key underlying cause of the decreasing SDTR. Secondly, there was asymmetry between the soil and air in the temperature increase. The differences between soil and air temperature ( T D ) were highest in summer (2.76 °C) and smallest in winter (1.55 °C), which decreased by 0.3 °C over the study interval, this meant agricultural practice plans based on air temperature alone may be severely limited. The difference between soil temperature and air temperature reduces at night. This would facilitate the wintering of perennials in areas near the zero-contour line.
Subject(s)
Climate Change , Soil , Temperature , Agriculture , China , Global Warming , Seasons , SunlightABSTRACT
Treeline responses to environmental changes describe an important phenomenon in global change research. Often conflicting results and generally too short observations are, however, still challenging our understanding of climate-induced treeline dynamics. Here, we use a state-of-the-art dendroecological approach to reconstruct long-term changes in the position of the alpine treeline in relation to air temperature at two sides in the Changbai Mountains in northeast China. Over the past 160 years, the treeline increased by around 80 m, a process that can be divided into three phases of different rates and drives. The first phase was mainly influenced by vegetation recovery after an eruption of the Tianchi volcano in 1702. The slowly upward shift in the second phase was consistent with the slowly increasing temperature. The last phase coincided with rapid warming since 1985, and shows with 33 m per 1°C, the most intense upward shift. The spatial distribution and age structure of trees beyond the current treeline confirm the latest, warming-induced upward shift. Our results suggest that the alpine treeline will continue to rise, and that the alpine tundra may disappear if temperatures will increase further. This study not only enhances mechanistic understanding of long-term treeline dynamics, but also highlights the effects of rising temperatures on high-elevation vegetation dynamics.
Subject(s)
Climate Change , Trees , Tundra , Altitude , China , Ecosystem , TemperatureABSTRACT
Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI products in China, which could provide useful information for the choice of NDVI products in subsequent studies of vegetation dynamics.
ABSTRACT
Vegetation in the alpine tundra area of the Changbai Mountains, one of two alpine tundra areas in China, has undergone great changes in recent decades. The aggressive herb species Deyeuxia angustifolia (Komarov) Y. L. Chang, a narrow-leaf small reed, was currently encroaching upon the alpine landscape and threatening tundra biota. The alpine tundra of the Changbai Mountains has been experiencing a warmer climate and receiving a high load of atmospheric nitrogen deposition. In this study, we aimed to assess the respective roles of climate warming and atmospheric nitrogen deposition in promoting the upward encroachment of D. angustifolia. We conducted experiments for three years to examine the response of D. angustifolia and a native alpine shrub, Rhododendron chrysanthum, to the conditions in which temperature and nitrogen were increased. Treatments consisting of temperature increase, nitrogen addition, temperature increase combined with nitrogen addition, and controls were conducted on the D. angustifolia communities with three encroachment levels (low, medium, and high levels). Results showed that 1) D. angustifolia grew in response to added nutrients but did not grow well when temperature increased. R. chrysanthum showed negligible responses to the simulated environmental changes. 2) Compared to R. chrysanthum, D. angustifolia could effectively occupy the above-ground space by increasing tillers and growing rapidly by efficiently using nitrogen. The difference in nitrogen uptake abilities between the two species contributed to expansion of D. angustifolia. 3) D. angustifolia encroachment could deeply change the biodiversity of tundra vegetation and may eventually result in the replacement of native biota, especially with nitrogen addition. Our research indicated that nutrient perturbation may be more important than temperature perturbation in promoting D. angustifolia encroachment upon the nutrient- and species-poor alpine tundra ecosystem in the Changbai Mountains.
Subject(s)
Air Pollutants/analysis , Environmental Monitoring , Global Warming , Nitrogen/analysis , Poaceae/growth & development , Tundra , Biodiversity , China , Ecosystem , RainABSTRACT
Based on a concept of a smooth and steady landing of fragile objects without destruction via a soft cushion, we have developed a model for the soft landing of deformable lipid giant unilamellar vesicles (GUVs) on solid surfaces. The foundation for a successful soft landing is a solid substrate with a two-layer coating, including a bottom layer of positively charged lysozymes and an upper lipid membrane layer. We came to a clear conclusion that anionic GUVs when sedimented on a surface, the vesicle rupture occurs upon the direct contact with the positively charged lysozyme layer due to the strong coulombic interactions. In contrast, certain separation distances was achieved by the insertion of a soft lipid membrane cushion between the charged GUVs and the lysozyme layer, which attenuated the coulombic force and created a mild buffer zone, ensuring the robust capture of GUVs on the substrate without their rupture. The non-covalent bonding facilitated a fully reversible stimuli-responsive capture/release of GUVs from the biomimetic solid surface, which has never been demonstrated before due to the extreme fragility of GUVs. Moreover, the controllable capture/release of cells has been proven to be of vital importance in biotechnology, and similarity the present approach to capture/release cells is expected to open the previously inaccessible avenues of research.
Subject(s)
Muramidase/metabolism , Unilamellar Liposomes/chemistry , Animals , Cattle , Doxorubicin/chemistry , Doxorubicin/metabolism , Fluoresceins/chemistry , Microscopy, Fluorescence , Muramidase/chemistry , Serum Albumin, Bovine/chemistry , Serum Albumin, Bovine/metabolism , Static Electricity , Surface Properties , Unilamellar Liposomes/metabolismABSTRACT
Tree line ecotone in the Changbai Mountains has undergone large changes in the past decades. Tree locations show variations on the four sides of the mountains, especially on the northern and western sides, which has not been fully explained. Previous studies attributed such variations to the variations in temperature. However, in this study, we hypothesized that topographic controls were responsible for causing the variations in the tree locations in tree line ecotone of the Changbai Mountains. To test the hypothesis, we used IKONOS images and WorldView-1 image to identify the tree locations and developed a logistic regression model using topographical variables to identify the dominant controls of the tree locations. The results showed that aspect, wetness, and slope were dominant controls for tree locations on western side of the mountains, whereas altitude, SPI, and aspect were the dominant factors on northern side. The upmost altitude a tree can currently reach was 2140 m asl on the northern side and 2060 m asl on western side. The model predicted results showed that habitats above the current tree line on the both sides were available for trees. Tree recruitments under the current tree line may take advantage of the available habitats at higher elevations based on the current tree location. Our research confirmed the controlling effects of topography on the tree locations in the tree line ecotone of Changbai Mountains and suggested that it was essential to assess the tree response to topography in the research of tree line ecotone.