Northeast China Research Articles

Short-Term Artificial Revegetation with Herbaceous Species Can Prevent Soil Degradation in a Black Soil Erosion Gully of Northeast China

Short-Term Artificial Revegetation with Herbaceous Species Can Prevent Soil Degradation in a Black Soil Erosion Gully of Northeast China

Phenotypic and genetic characterization of children with Wilson Disease from Northeast China

BackgroundWilson disease (WD) is an autosomal recessive inherited disease caused by ATP7B variants and characterized by copper metabolism defects. However, children with WD are often asymptomatic, making the clinical diagnosis difficult. Therefore, more accurate methods are required for clinical diagnosis. The objective of this study was to highlight the phenotypic and genetic characteristics of children with WD in northeast China.MethodsWe retrospectively analyzed the clinical data and gene sequencing results of 65 children with WD from January 1, 2014, to December 31, 2022, at the Shengjing Hospital of China Medical University. All data refer to the time of diagnosis before treatment.ResultsThe median age at diagnosis was 5 years (range 1.2–15 years). In 50 cases (50/65, 76.9%) patients, routine physical examinations revealed only abnormal liver function. However, they had a significantly negative (p < 0.05) Kayser–Fleischer ring (KF). Children with acute liver failure had significantly increased 24 h urinary copper excretion (p < 0.05). We detected 46 genetic variants of ATP7B, including seven novel variants. The most frequent variant was p.R778L with an allele frequency of 38.7%. Phenotype-genotype correlation analysis suggested that p.R778L was significantly associated with lower serum ceruloplasmin levels and higher zinc levels (p < 0.05). The loss-of-function (LOF) variant was associated with significantly lower albumin levels (p < 0.05).ConclusionMost children with WD are asymptomatic, which makes early diagnosis of WD difficult. Therefore, clinical and laboratory characteristics as well as genetic testing are essential. p.R778L is the most frequent variant of ATP7B in China and may play an important role in lowering serum ceruloplasmin levels.

Interdecadal changes in interannual variability of June temperature over Northeast China induced by decadal shifts in the North Atlantic teleconnection

Interdecadal changes in interannual variability of June temperature over Northeast China induced by decadal shifts in the North Atlantic teleconnection

Spatial distribution, source apportionment, and risk assessment of perfluoroalkyl substances in urban soils of a typical densely urbanized and industrialized city, Northeast China

As an important capital city of intensive urbanization and industrialization in Northeast China, Changchun has experienced extremely rapid development, with diverse sectors such as automobile manufacturing, equipment manufacturing, optoelectronics, and pharmaceutical decoration. However, data on the levels and profiles of perfluoroalkyl substances (PFASs) in urban soils of Changchun is limited. This study investigated 17 PFASs across various functional zones within the main urban area of Changchun. ∑PFAS concentrations in the soils ranged from 0.236 to 6.483 ng/g, averaging 1.820 ng/g. Perfluorocarboxylic acids (PFCAs) were more prevalent than perfluorosulfonic acids (PFSAs), and short-chain PFASs (C ≤ 6) were the predominant residues. PFAS concentrations varied across functional zones, with commercial markets exhibiting the highest levels, followed by industrial areas, residential areas, suburban zones, and transportation areas. Molecular diagnostic ratio and PCA-MLR analysis identified industrial production processes of consumer goods and wastewater treatment plants as the primary sources of soil PFAS contamination. There were no obvious health risks of soil ∑PFASs, while soil PFOS and PFHxS may have an impact on the richness and diversity of soil microbial communities in some certain locations. This study provides new data on PFAS residues in soils influenced by diverse contamination sources within a key industrial city in Northeast China, offering valuable insights for prioritizing remediation and restoration efforts.

Increasing cross-border dust storm from Mongolia to China during 1987–2022

Mongolia and northern China have the highest frequency of dust weather in Northeast Asia. Dust transport from Mongolia to China is a major cause of dust weather in northern China. However, there has been limited research on the frequency changes of cross-border dust storms from Mongolia to China over the past few decades. Based on observational data, we analyzed the variation in cross-border dust storms between China and Mongolia during 1987–2022. The results indicate that, on average, approximately seven cross-border dust storm events occur annually between China and Mongolia, predominantly during the spring. The frequency of cross-border dust storms from Mongolia to China significantly increased from 2.2 events in P1 (1987–1999) to 7.5 events in P2 (2000−2022). Long-term trends suggest that rising dust emissions in east-central Mongolia largely contributed to this increase. The increase in cross-border dust storms from Mongolia to China in the spring was driven by more frequent cyclones in eastern Mongolia and Northeast China during P2. This is evidenced by a negative height anomaly and increased vorticity at 850 hPa over Northeast China. The cyclones were linked to the northward shift of the East Asian Polar Front Jet Stream (EAPJ) at 300 hPa between 50°N and 60°N. Additionally, surface conditions such as higher temperatures and decreased vegetation in Mongolia contributed to the increased frequency of cross-border dust storms from P1 to P2.

Changes in urban residential and agricultural sources induce a decrease in PM10 levels in cold clean area: A thirteen-year monitoring at the Longfengshan WMO/GAW regional background station in Northeast China

Atmospheric background monitoring provides insights into the long-term changes in atmospheric composition resulting from human activities on both global and regional scales. It is important to understand the local characteristics of key air pollutants to evaluate and manage air quality control policies effectively. This study analyzed 13 years of continuous data of PM10 (particulate matter with aerodynamic diameter ≤10 μm) concentration from the only atmospheric background station in Northeastern China, the Longfengshan (LFS) World Meteorological Organization (WMO)/Global Atmosphere Watch (GAW) regional station. The results revealed a significant decrease of 58.02% in PM10 concentrations in the LFS from 2007 to 2019, which was primarily influenced by transport from Changchun and Harbin. Over periods exceeding eight months, the correlation between PM10 levels at the LFS atmospheric background station and those in Changchun and Harbin became more pronounced. The observed decline in PM10 concentrations at the LFS atmospheric background station was largely attributed to reduced emissions from urban residential and agricultural sources. Emissions of carbon monoxide and ammonia from these sources, along with temperature and relative humidity (RH), significantly affected the PM10 concentrations. Using machine learning (ML) methods and PM10 data from the LFS atmospheric background station, this study effectively predicted PM10 concentrations in neighboring cities, demonstrating that the LFS atmospheric background station can effectively assess the trend of PM10 changes in Northeast China. This study quantified the influence of urban areas on atmospheric background stations, highlighting the effectiveness of existing environmental policies, and offering a reference for similar studies and forecasts in other regions.

Dynamics of indoor volatile organic compounds and seasonal ventilation strategies for residential buildings in Northeast China

This study utilized a questionnaire survey to collect data from 265 residents in Changchun, encompassing building characteristics, ventilation frequency and overall satisfaction with the indoor environment. Statistical analysis revealed significant disparities in ventilation frequency and satisfaction with indoor temperature. The survey results indicate that the primary mode of indoor air exchange amongst Changchun residents is window ventilation, accounting for 93%. Field tracking was conducted to measure indoor air concentrations of volatile organic compounds (VOCs) in residential buildings during winter and summer seasons. The study revealed a significant increase in the average indoor/outdoor (I/O) ratio of the targeted 25 VOC concentrations in winter, rising from 10.8 to 17.7. The findings underscore indoor sources as predominant contributors to the measured VOCs. Temperature, humidity and room functions are the main factors affecting VOC concentration. Higher temperatures and increased relative humidity both contributed to elevated indoor VOC levels. This study recommended the opening of more windows during high temperature and high humidity in summer, to maintain good indoor air quality and effectively age the emission of VOCs from furniture. This study contributes to the enhancement of the database on indoor air quality and effective ventilation strategies in cold regions for safeguarding public health.

Differential salt stress resistance in male and female Salix linearistipularis plants: insights from transcriptome profiling and the identification of the 4-hydroxy-tetrahydrodipicolinate synthase gene.

Lysine plays an essential role in the growth differences between male and female S. linearistipularis plants under salt stress. Furthermore, SlDHDPS is identified as a vital gene contributing to the differences in saline-alkali tolerance between male and female plants of S. linearistipularis. Soil salinization is a significant problem that severely restricts agricultural production worldwide. High salinity and low nutrient concentrations consequently prevent the growth of most plant species. Salix linearistipularis is the only woody plant (shrub) naturally distributed in the saline-alkali lands of the Songnen Plain in Northeast China, and it is one of the few plants capable of thriving in soils with extremely high salt and alkaline pH (>9.0) levels. However, insufficient attention has been given to the interplay between salt and nitrogen in the growth and development of S. linearistipularis. Here, the male and female plants of S. linearistipularis were subjected to salt stress with nitrogen-starvation or nitrogen-supplement treatments, and it was found that nitrogen significantly affects the difference in salt tolerance between male and female plants, with nitrogen-starvation significantly enhancing the salt stress tolerance of female plants compared to male plants. Transcriptional analyses showed 66 differentially expressed nitrogen-responsive genes in female and male roots, with most of them showing sexual differences in expression patterns under salinity stress. RNA-seq and RT-qPCR analysis demonstrated that six genes had an opposite salt-induced expression pattern in female and male roots. The expression of the 4-hydroxy-tetrahydrodipicolinate synthase encoding gene (SlDHDPS) in female roots was higher than that in male roots. Further treatment with exogenous lysine could significantly alleviate the inhibitory effect of salt stress on the growth of female and male plants. These results indicate that the SlDHDPS in the nitrogen metabolism pathway is involved in the resistance of S. linearistipularis to salt stress, which lays a foundation for further exploring the mechanism of nitrogen on salt tolerance of S. linearistipularis, and has a significant reference value for saline-alkali land management and sustainable agricultural development.

Association of baseline sleep duration and sleep quality with seizure recurrence in newly treated patients with epilepsy.

Although sleep duration and sleep quality are considered to be significant factors associated with epilepsy and seizure risk, findings are inconsistent, and their joint association remains uncertain. This study aimed to determine independent and joint associations of these two modifiable sleep features with seizure recurrence risk in newly treated patients with epilepsy (PWE). This is a prospective cohort study of newly treated PWE at a comprehensive epilepsy center in northeast China between June 2020 and December 2023. Self-reported sleep duration and sleep quality were collected at baseline. All patients were followed for 12 months for recurrent seizures. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) of seizure recurrence. Models fitted with restricted cubic spline were conducted to test for linear and nonlinear shapes of each association. A total of 209 patients were included, and 103 experienced seizure recurrence during follow-up. Baseline short sleep was significantly associated with greater risk of seizure recurrence (adjusted HR = 2.282, 95% confidence interval [CI] = 1.436-3.628, p < .001). Sleep duration (h/day) and recurrent seizure risk showed a significant nonlinear U-shaped association, with a nadir at 8 h/day. Baseline poor sleep quality was significantly associated with greater risk of seizure recurrence (adjusted HR = 1.985, 95% CI = 1.321-2.984, p < .001). Pittsburgh Sleep Quality Index score and seizure recurrence risk exhibited a positive linear association. Participants with a combination of poor quality-short sleep showed the highest risk of seizure recurrence (adjusted HR = 3.13, 95% CI = 1.779-5.507, p < .001) compared to the referent good quality-intermediate sleep group. Baseline sleep duration and sleep quality were independently and jointly associated with risk of seizure recurrence in newly treated PWE. Our results point to an important potential role of baseline sleep duration and sleep quality in shaping seizure risk.

Pore Structure and Fluid Distribution of Lower Cretaceous Jiufotang and Shahai Shales in the Ludong Sag, Northeast China

Pore Structure and Fluid Distribution of Lower Cretaceous Jiufotang and Shahai Shales in the Ludong Sag, Northeast China

Effects of biochar on the transformation and utilization of nitrogen fertilizer in the black soil region of Northeast China

Nitrogen (N) fertilizer is often used in production practice to effectively maintain crop productivity; however, low nitrogen use efficiency (Nue) has always been a problem. Specifically, the transformation and utilization of nitrogen fertilizer by biochar and the driving mechanisms remain unclear. We used four biochar application rates (0, 3750, 7500, and 11,250 kg·ha−1) and analyzed the effects of biochar on nitrogen fertilizer utilization, residue, and loss over three years using 15N isotope tracer technology. The results showed that (1) biochar improved the nitrogen use efficiency of maize plants, reduced total nitrogen loss, and increased the maize yield. Compared to the control treatment in the same year, the application of 7500 kg·ha−1 biochar increased the nitrogen use efficiency by 24.27 %, 27.77 %, and 35.82 %, and the yield increased by 21.1 %, 26.7 %, and 24.5 %, respectively. (2) Biochar increased the proportion of mineral nitrogen supplied by fertilizer in the mineral nitrogen pool. The application of 7500 kg·ha−1 biochar increased mineral nitrogen by 3.05 %, 3.22 %, and 3.8 %, respectively, compared to the control treatments in the same year. Biochar promoted the transformation of nitrogen in the 0–40 cm soil layer to three different soil nitrogen pools, especially the organic nitrogen pool. (3) Biochar significantly improved the soil bacterial community and increased the abundances of N transformation functional genes. The redundancy analysis (RDA) showed that the gdhA mineralization gene was the driving factor of nitrogen fertilizer transformation, contributing 43.6 % of the variance. In summary, the application of 7500 kg·ha−1 of biochar for two consecutive years was conducive to maintaining farmland soil fertility, while its use would not be recommended for more than three consecutive years.

Trend of surface solar radiation over China in relation to changing synoptic patterns

A comprehensive understanding of the relationship between atmospheric circulations and variations in surface solar radiation (SSR) is important for effectively utilizing solar resources and assessing climate change impacts. Here, we identify four synoptic patterns by T-mode principal component analysis method during 1980–2020 associated with the spatio-temporal variations of SSR in China, including geopotential height anomalies of west-high-east-low (Type 1), north-high-south-low (Type 2), east-low-west-high (Type 3), and north-low-south-high (Type 4). For the whole summer, there are more days of Type 1 and Type 2, accounting for 28.74 % and 28.58 % respectively. In particular, Type 1 experiences positive anomalies in cloud cover, water vapor and significantly reduced SSR reaching the Earth’s surface. Type 2 pattern is characterized with low (high) anomalies of SSR over the Yangtze River Basin (Northeast China). And the north of the Yangtze River Basin is controlled by a northerly dry and cold airflow, leading to low cloudiness and precipitation with increased SSR reaching the ground in Type 3. Type 4 pattern exhibits a negative (positive) SSR anomalies in the Yellow River Basin (the Yangtze River Basin and Northeast China). Notably, the reduction of summer SSR in China since the 1980s is largely explained by the long-term changes of Type 2 and Type 4 synoptic patterns. These findings improve the understanding of the relationship between atmospheric circulations and SSR, and provide a scientific basis for policy planning of solar energy and dual-carbon targets in China.

Variation in worldwide incidence of Guillain-Barré syndrome: a population-based study in urban China and existing global evidence.

Geographical variation existed in the incidences of Guillain-Barré syndrome (GBS), but no national population-based study has evaluated the incidences of GBS in China. This study aimed to estimate the incidence of GBS in urban China and evaluate the worldwide variation in the incidence of GBS. Firstly, we did a population-based study to calculate the incidence of GBS in urban China based on the National Urban Medical Insurance database from 2013 to 2017. To identify GBS cases, natural language processing was used first for handling the lengthy and unstructured diagnostic information and then checked by prestigious neurologists. Secondly, a systematic review and meta-analysis were performed to analyze the incidence of GBS worldwide. Up to July 4, 2022, Medline, Embase, and Web of Science were retrieved to identify the population-based studies regarding the incidence of GBS. The basic information and the statistics regarding incidence were extracted. Quality assessment considered sample representativeness, condition assessment, and statistical methods. A total of 1.44 billion person-years in insurance data was covered, with 3,534 GBS cases identified. The annual incidences of GBS in urban China between 2013 and 2017 ranged from 0.41 (95% CI: 0.27 to 0.58) to 0.58 (95% CI: 0.38 to 0.82) per 100,000 person-years. The incidence was the highest in Northwest China and the lowest in Northeast China. The meta-analysis included 122 articles. The quality assessment showed that the quality scores of 43.3% of studies were ≥ 0.75 (the total score is 1). The global incidence of GBS was 1.12 (95% CI: 0.98 to 1.27) per 100,000 person-years. The incidences in West Europe, South Asia, and North Europe were higher, while the incidences in Australia and New Zealand, Southeast Asia, and North Africa were lower. The incidence of enteric infections was positively associated with the incidence of GBS (coefficient=0.0000185, P=0.007). The incidence in Europe, Australia, and America rose significantly from 1960 to 2020 (coefficient=0.01, t=2.52, P=0.015). There is a clear regional variation of the GBS incidence at both national and global levels. Careful control of enteric infections should be conducted to reduce the disease burden.

Hydrological Connectivity Response of Typical Soil and Water Conservation Measures Based on SIMulated Water Erosion Model: A Case Study of Tongshuang Watershed in the Black Soil Region of Northeast China

The black soil region of Northeast China is the largest commercial grain production base in China, accounting for about 25% of the total in China. In this region, the water erosion is prominent, which seriously threatens China’s food security. It is of great significance to effectively identify the erosion-prone points for the prevention and control of soil erosion on the slope of the black soil region in Northeast China. This article takes the Tongshuang small watershed (Heilongjiang Province in China) as an example, which is dominated by hilly landforms with mainly black soil and terraces planted with corn and soybeans. Based on the 2.5 cm resolution Digital Elevation Model (DEM) reconstructed by unmanned aerial vehicles (UAVs), we explore the optimal resolution for hydrological simulation research on sloping farmland in the black soil region of Northeast China and explore the critical water depth at which erosion damage occurs in ridges on this basis. The results show that the following: (1) Compared with the 2 m resolution DEM, the interpretation accuracy of field roads, wasteland, damaged points, ridges and cultivated land at the 0.2 m resolution is increased by 4.55–27.94%, which is the best resolution in the study region. (2) When the water depth is between 0.335 and 0.359 m, there is a potential erosion risk of ridges. When the average water depth per unit length is between 0.0040 and 0.0045, the ridge is in the critical range for its breaking, and when the average water depth per unit length is less than the critical range, ridge erosion damage occurs. (3) When local erosion damage occurs, the connectivity will change abruptly, and the remarkable change in the index of connectivity (IC) can provide a reference for predicting erosion damage.

Spatial variation of soil organic carbon density in the black soil region of Northeast China under the influence of erosion and deposition

Soil erosion of the Songnen typical Black Soil Region (BSR) in Northeast China where contains higher soil organic carbon is serious, resulting in soil organic carbon spatial redistribution. To study the spatial redistribution pattern of cropland SOC caused by erosion, 115 cropland sample points were selected in the Songnen typical BSR, and soil samples were collected along the entire soil profile. The soil organic carbon density (SOCD) of the soil layer and profile were calculated, and the carbon storage (CS) was calculated for the erosion and deposition areas. The average soil organic carbon density (SOCDav) of the 115 cropland soil profiles (1 m) ranged from 1.5 to 4.5 kg/m2, and the total soil organic carbon density (SOCDt) of the soil profile (1 m) ranged from 10 to 20 kg/m2. The SOCD of each soil layer (20 cm) decreased vertically in a logarithmical manner from the top, and was divided into four groups with thickness through systematic clustering, which were 30–60 cm, 60–100 cm, less than 300 cm and greater than 350 cm. The SOCDt in the area north of the Songhua River and the area west of Nen River (The Greater Khingan Mountains area) ranged from 2.5 to 59.3 kg/m2, with an average is 14.1 kg/m2, and the first sample point group (30–60 cm) was mainly located in this area which had an average slope of 3.2° and an average black soil thickness of 24.6 cm. The SOCDt in the area north of the Songhua River and the area east of the Nen River ranged from 11 to 90 kg/m2, with an average of 28.6 kg/m2, the third and the fourth sample point group (greater than 100 cm) were both mainly located in this area which had an average slope of 2° and an average black soil thickness of 61 cm. The SOCDt in the area south of the Songhua River ranged from 1.6 to 28.7 kg/m2, with an average of 13.8 kg/m2, and the second sample point group (60–100 cm) was mainly located in this area which had an average slope of 2.4° and an average black soil thickness of 58.7 cm. The results showed that soil erosion occurred on steeper slopes, resulting in thinner soil layers, whereas soil deposition occurred on lower grade slopes, resulting in thicker soil layers. Kriging interpolation in ArcGIS showed that the Cs in the erosion and deposition areas of the Songnen typical BSR was 459.7 and 1234.7 Tg, respectively, and the total Cs was 1.6944 Tg (1 Tg = 1012 g).

Multimodal Deep Learning Network for Differentiating Between Benign and Malignant Pulmonary Ground Glass Nodules.

This study aimed to establish a multimodal deep-learning network model to enhance the diagnosis of benign and malignant pulmonary ground glass nodules [GGNs]. Retrospective data on pulmonary GGNs were collected from multiple centers across China, including North, Northeast, Northwest, South, and Southwest China. The data were divided into a training set and a validation set in an 8:2 ratio. In addition, a GGN dataset was also obtained from our hospital database and used as the test set. All patients underwent chest computed tomography [CT], and the final diagnosis of the nodules was based on postoperative pathological reports. The Residual Network [ResNet] was used to extract imaging data, the Word2Vec method for semantic information extraction, and the Self Attention method for combining imaging features and patient data to construct a multimodal classification model. Then, the diagnostic efficiency of the proposed multimodal model was compared with that of existing ResNet and VGG models and radiologists. The multicenter dataset comprised 1020 GGNs, including 265 benign and 755 malignant nodules, and the test dataset comprised 204 GGNs, with 67 benign and 137 malignant nodules. In the validation set, the proposed multimodal model achieved an accuracy of 90.2%, a sensitivity of 96.6%, and a specificity of 75.0%, which surpassed that of the VGG [73.1%, 76.7%, and 66.5%] and ResNet [78.0%, 83.3%, and 65.8%] models in diagnosing benign and malignant nodules. In the test set, the multimodal model accurately diagnosed 125 [91.18%] malignant nodules, outperforming radiologists [80.37% accuracy]. Moreover, the multimodal model correctly identified 54 [accuracy, 80.70%] benign nodules, compared to radiologists' accuracy of 85.47%. The consistency test comparing radiologists' diagnostic results with the multimodal model's results in relation to postoperative pathology showed strong agreement, with the multimodal model demonstrating closer alignment with gold standard pathological findings [Kappa=0.720, P<0.01]. The multimodal deep learning network model exhibited promising diagnostic effectiveness in distinguishing benign and malignant GGNs and, therefore, holds potential as a reference tool to assist radiologists in improving the diagnostic accuracy of GGNs, potentially enhancing their work efficiency in clinical settings.

The impact of economic agglomeration on China's urban public health.

This study aims to explore the impact of economic agglomeration on the urban prosperity through economies of scale and agglomeration, it may also affect the public health of the agglomeration area. This paper takes 280 cities in China as the research object, and explores the impact of economic agglomeration on public health through a two-way fixed effects model, instrumental variable method, and generalized moment estimation. The results indicate that: (1) the improvement of China's economic agglomeration can significantly promote urban public health, and economic agglomeration is a prerequisite for the improvement of urban public health, but there is no reverse causal relationship. (2) The enhancement of economic agglomeration in Northeast China has the greatest promotion effect on public health, followed by the eastern, western, and central regions; The economic agglomeration enhancement of the pilot medical group in closely connected cities has a greater promoting effect on public health than the pilot medical group in non-closely connected cities. (3) Empirical results based on micro sample data show that the improvement of economic agglomeration will also promote the increase of the number of public hospitals in cities. This study emphasizes the important role of economic accumulation in the improvement of urban public health and provides empirical support for future economic development policies and practices.

Classification of tomato seedling chilling injury based on chlorophyll fluorescence imaging and DBO-BiLSTM

IntroductionTomatoes are sensitive to low temperatures during their growth process, and low temperatures are one of the main environmental limitations affecting plant growth and development in Northeast China. Chlorophyll fluorescence imaging technology is a powerful tool for evaluating the efficiency of plant photosynthesis, which can detect and reflect the effects that plants are subjected to during the low temperature stress stage, including early chilling injury.MethodsThis article primarily utilizes the chlorophyll fluorescence image set of tomato seedlings, applying the dung beetle optimization (DBO) algorithm to enhance the deep learning bidirectional long short term memory (BiLSTM) model, thereby improving the accuracy of classification prediction for chilling injury in tomatoes. Firstly, the proportion of tomato chilling injury areas in chlorophyll fluorescence images was calculated using a threshold segmentation algorithm to classify tomato cold damage into four categories. Then, the features of each type of cold damage image were filtered using SRCC to extract the data with the highest correlation with cold damage. These data served as the training and testing sample set for the BiLSTM model. Finally, DBO algorithm was applied to enhance the deep learning BiLSTM model, and the DBO-BiLSTM model was proposed to improve the prediction performance of tomato seedling category labels.ResultsThe results showed that the DBO-BiLSTM model optimized by DBO achieved an accuracy, precision, recall, and F1 score with an average of over 95%.DiscussionCompared to the original BiLSTM model, these evaluation parameters improved by 9.09%, 7.02%, 9.16%, and 8.68%, respectively. When compared to the commonly used SVM classification model, the evaluation parameters showed an increase of 6.35%, 7.33%, 6.33%, and 6.5%, respectively. This study was expected to detect early chilling injury through chlorophyll fluorescence imaging, achieve automatic classification and labeling of cold damage data, and lay a research foundation for in-depth research on the cold damage resistance of plants themselves and exploring the application of deep learning classification methods in precision agriculture.

Extreme precipitation reduces the recent photosynthetic carbon isotope signal detected in ecosystem respiration in an old-growth temperate forest.

The successful utilization of stable carbon isotope approaches in investigating forest carbon dynamics has relied on the assumption that the carbon isotope compositions (δ13C) therein have detectable temporal variations. However, interpreting the δ13C signal transfer can be challenging, given the complexities involved in disentangling the effect of a single environmental factor, the isotopic dilution effect from background CO2 and the lack of high-resolution δ13C measurements. In this study, we conducted continuous in situ monitoring of atmospheric CO2 (δ13Ca) across a canopy profile in an old-growth temperate forest in northeast China during the normal year 2020 and the wet year 2021. Both years exhibited similar temperature conditions in terms of both seasonal variations and annual averages. We tracked the natural carbon isotope composition from δ13Ca to photosynthate (δ13Cp) and to ecosystem respiration (δ13CReco). We observed significant differences in δ13Ca between the two years. Contrary to in 2020, in 2021 there was a δ13Ca valley in the middle of the growing season, attributed to surges in soil CO2 efflux induced by precipitation, while in 2020 values peaked during that period. Despite substantial and similar seasonal variations in canopy photosynthetic discrimination (Δ13Ccanopy) in the two years, the variability of δ13Cp in 2021 was significantly lower than in 2020, due to corresponding differences in δ13Ca. Furthermore, unlike in 2020, we found almost no changes in δ13CReco in 2021, which we ascribed to the imprint of the δ13Cp signal on above-ground respiration and, more importantly, to the contribution of stable δ13C signals from soil heterotrophic respired CO2. Our findings suggest that extreme precipitation can impede the detectability of recent photosynthetic δ13C signals in ecosystem respiration in forests, thus complicating the interpretation of above- and below-ground carbon linkage using δ13CReco. This study provides new insights for unravelling precipitation-related variations in forest carbon dynamics using stable isotope techniques.

Analysis of Spatial Distribution of Ecosystem Services and Driving Factors in Northeast China

Northeast China is an important ecological barrier in China, and an in-depth understanding of the spatial distribution in ecosystem services （ESs）, and the driving factors is crucial for realizing the subsequent management and protection of ESs. In the study, we quantitatively assessed the characteristics of spatial distribution in ESs in Northeastern China using the InVEST, RWEQ, and RUSLE models and identified the driving factors of ESs spatial distribution in conjunction with the geodetector based on meteorological data, remote sensing data, and socio-economic data. The results showed that the spatial distribution of ESs in Northeast China had obvious spatial heterogeneity. The high values of habitat quality （HQ）, carbon sequestration （CS） services, and soil conservation （SC） services were mainly distributed in the northern part of the four eastern leagues of the Inner Mongolia Autonomous Region, the northern part of Heilongjiang Province, and the eastern part of Northeast China, which were high in fraction vegetation cover, and low values were mainly found in southwestern and eastern Heilongjiang Province, western Jilin Province, and western Liaoning Province. The high values of the water yield （WY） service and wind prevention and sand fixation （WPSF） service were distributed in the east of the Inner Mongolia Autonomous Region and the east of Liaoning Province. The high values of WY services and WPSF services were distributed in the eastern part of Northeast China and the four eastern provinces of the Inner Mongolia Autonomous Region. According to the geodetector results, slope had the strongest explanatory power for the spatial distribution of SC services with a q-value of 0.31, land use/cover change had the strongest explanatory power for the spatial distribution of HQ and CS services with q-values of 0.64 and 0.52, respectively, and fraction vegetation coverage and annual precipitation had the strongest explanatory power for the spatial distribution of WPSF and WY services with q-values of 0.24 and 0.64, respectively, and there were interactions among all the driving factors. The spatial distribution of ESs in Northeast China was mainly influenced by natural factors. The results will provide a scientific basis for subsequent management and enhancement of ESs in Northeast China.