Province In Northeast China Research Articles

Spatiotemporal Evolution of Urban Shrinkage and Its Impact on Urban Resilience in Three Provinces of Northeast China

Currently, Chinese cities are experiencing both overall growth and localized shrinkage. Therefore, it becomes crucial to quantify urban shrinkage and explore the transformation and sustainable development of shrinking cities from the perspective of urban resilience. This study focuses on the three provinces of Northeast China, which are representative areas of urban shrinkage, as its research subjects. Employing the analytic hierarchy process, a comprehensive evaluation system for urban shrinkage is constructed based on three dimensions: population, economy, and space. Furthermore, urban resilience is scientifically measured from four aspects: economy, society, ecology, and infrastructure. The study analyzes the spatiotemporal evolution characteristics of urban shrinkage and urban resilience in the three northeastern provinces from 2012 to 2018. It also examines the impact of urban shrinkage on urban resilience through regression analysis and mediation models. The results indicate the following: (1) Half of the cities in the three northeastern provinces experienced shrinkage, although the extent of shrinkage decreased with the implementation of the Northeast China revitalization strategy. Population-related shrinkage was the most extensive and continued to expand, while economy-related shrinkage was the most severe, and space-related shrinkage was the least severe. (2) The resilience of shrinking cities was lower than the average level. Population-shrinking cities and economy-shrinking cities exhibited low levels of economic resilience, and the gap between them continued to widen. Space-shrinking cities generally had low infrastructure resilience. (3) The urban shrinkage index had a significant positive impact on the urban resilience index, mediated through intermediary variables, such as innovation capability and cultural development. Notably, both the direct and indirect effects of innovation capability were the greatest. Population-related shrinkage had the largest impact on urban resilience, while more intermediary variables of economy-related shrinkage passed the significance test.

Fine-Resolution Forest Height Estimation by Integrating ICESat-2 and Landsat 8 OLI Data with a Spatial Downscaling Method for Aboveground Biomass Quantification

Rapid and accurate estimation of forest aboveground biomass (AGB) with fine details is crucial for effective forest monitoring and management, where forest height plays a key role in AGB quantification. In this study, we propose a random forest (RF)-based down-scaling method to map forest height and biomass at a 15-m resolution by integrating Landsat 8 OLI and Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) LiDAR data. ICESat-2 photon data are used to derive canopy parameters along 15-m segments, which are considered sample plots for the extrapolation of discrete forest height. Fourteen variables associated with spectral features, textual features and vegetation index are extracted from pan-sharpened Landsat 8 images. A regression function is established between these variables and ICESat-2-derived forest height to produce a 15-m continuous forest height distribution data based on the 30-m forest height product using the RF algorithm. Finally, a wall-to-wall forest AGB at 15-m spatial resolution is achieved by using an allometric model specific to the forest type and height. The Jilin Province in northeast China is taken as the study area, and the forest AGB estimation results reveal a density of 61.15 Mg/ha with a standard deviation of 89.46 Mg/ha. The R2 between our predicted forest heights and the ICESat-2-derived heights reaches 0.93. Validation results at the county scale demonstrate reasonable correspondence between the estimated AGB and reference data, with consistently high R2 value exceeding 0.65. This downscaling method provides a promising scheme to estimate spatial forest AGB with fine details and to enhance the accuracy of AGB estimation, which may facilitate carbon stock measurement and carbon cycle studies.

Moisture sources of summer heavy precipitation in two spatial patterns over Northeast China during 1979–2021

AbstractThis study classifies the spatial distribution of heavy precipitation in summer (June–August) from 1979 to 2021 in the three provinces of Northeast China (TPNC) into two patterns by using the self‐organizing maps (SOM) neural network, and then quantitatively analyzes their moisture transport channels and sources using the Lagrangian model. The results show that the summer heavy precipitation in TPNC can be divided into the northern and southern patterns according to the distribution of the heavy precipitation. Both patterns of heavy precipitation are affected by the low‐level vortex west of TPNC, but the strength and shape of the low vortex are different. The northern pattern is mainly influenced by the westerly flow in the vortex in the mid‐high latitudes, which transports moisture from the upstream westerly region into TPNC. The southern pattern is mainly affected by the southerly jet stream southeast of TPNC, which conveys a large amount of moisture from the East Asian summer monsoon region into TPNC. In terms of the summer climatological mean, the northern pattern has a higher precipitation recycling rate, while the southern pattern has a lower recycling rate.

Identification and Classification of Urban Shrinkage in Northeast China

The phenomenon of shrinking cities is a significant challenge faced by many cities today. To more accurately identify the leading factors driving urban shrinkage and develop rational recommendations, precise identification and classification of urban shrinkage has become an indispensable part of the process. This paper focuses on the typical population loss region of China’s three northeastern provinces, using 497 identified physical cities as the basic research unit. Based on multi-source geographical big data and utilizing the geographically weighted regression (GWR) model, spatial modeling of population in the three provinces of northeast China was conducted, resulting in spatialized population data, followed by identification and classification of shrinking cities among the physical cities. Cities with a total population change rate of less than 0 are defined as shrinking cities. In cities where the total population change rate is greater than 0, cities with both a city shrinking area ratio and a decreased population ratio greater than 5% are defined as locally shrinking cities. Based on this, 90 (18.1%) shrinking cities and 118 (23.7%) locally shrinking cities were identified within the three provinces of northeast China. The phenomenon of urban shrinkage is distributed throughout various regions, mainly in smaller cities located near larger cities. According to the standards of the urban shrinkage classification model, the spatial pattern of population loss regions was divided into four types, identifying 13 (6.3%) global type, 111 (53.4%) concentrated type, 64 (30.7%) perforated type, and 20 (9.6%) edge type. Analysis of shrinking cities based on their classification revealed that the main reasons for urban shrinkage are the decline and dissolution of large industrial enterprises, abandonment and neglect of buildings, and unreasonable design planning in cities. Economic development and inward population flow can be promoted in shrinking cities by creating job opportunities, improving living standards, developing transportation, adjusting urban planning or concentrating urban population, as well as vigorously developing urban center areas. These measures can provide support for the revival and development of shrinking cities.

Assessing the impacts of rural residential land and cropland transition on agricultural production in Northeast China

AbstractTransitions between cropland and rural residential land (RRL) significantly impact both the amount of cropland and the yields obtained, whereas these impacts were overlooked in the previous studies. Taking accumulated Normalized Difference Vegetation Index during the growing season as a surrogate of productivity, this study assessed the impacts of RRL expansion and reclamation on agricultural production between 2009 and 2018 in Northeast China (NEC), a region contributing one‐fifth of the nation's total grain yield. Especially, the productivity gap between the RRL‐reclaimed and traditional cropland was explored and discussed. From 2009 to 2018, the NEC has experienced an intense expansion and reclamation in RRL, resulting in approximately 6.66 × 104 ha of cropland disappearing and 1.32 × 104 ha supplemented. Transitions in land use between RRL and cropland decreased the regional crop production by 0.08%, with the percentage slightly lower than that of cropland that was lost (0.09%). This was mainly attributed to the productivity gap between the reclaimed and occupied cropland from/to RRL, with the former higher than the latter. Even so, the cropland reclaimed from RRL was less productive than traditional cropland in three provinces in NEC, ranging from 1.6% to 3.9%. This productivity gap varied by crop type and province. After discussing the productivity limitations, suggestions for future land use policy in rural China have been put forward.

Multiple resistance of Echinochloa phyllopogon to synthetic auxin, ALS-, and ACCase-inhibiting herbicides in Northeast China

Echinochloa phyllopogon is a self-pollinating allotetraploid weed and a serious threat to global rice production. One sensitive and three multiple-resistant populations collected from two provinces of Northeast China were used to analyze the mechanism of multiple resistance of E. phyllopogon to penoxsulam, metamifop, and quinclorac. Compared with the sensitive population LN12, LN1 showed higher resistance to these three herbicides; LN24 showed medium resistance to penoxsulam and metamifop and higher resistance to quinclorac (274-fold); HLJ4 showed low resistance to penoxsulam and high resistance to metamifop and quinclorac. Target sequence analysis showed no mutations in acetolactate synthase or acetyl-CoA carboxylase genes. In-vitro enzyme activity analysis showed that the activity of the target enzyme of multiple herbicide-resistant populations was similar to that of the sensitive population. The P450 inhibitor, malathion, noticeably increased the sensitivity of LN1, LN24, and HLJ4 to penoxsulam, LN1 to metamifop, and HLJ4 to quinclorac. Under all four treatments, the GSTs activities of resistant and sensitive populations showed an increasing trend from day 1 to day 5, but the sensitivity and activity of GSTs were higher in the multiple-resistant population than that in the sensitive population LN12. This study identified the development of multiple-resistant E. phyllopogon populations that pose a serious threat to rice production in rice fields in Northeast China, preliminarily confirming that multiple-resistance was likely due to non-target-site resistance mechanisms. These populations of E. phyllopogon are likely to be more difficult to control.

Mapping crop damage by wild boars using multi‐scale risk modeling in Northeast China

AbstractBalancing development and conservation is one of the major challenges for modern societies. Negative human–wildlife interactions, especially crop raiding by wildlife, greatly undermine this objective. Jilin Province in Northeast China encompasses ecosystems of high biodiversity value but endures serious losses in crop yields due to wild boars (Sus scrofa). Mitigation measures have been hindered by knowledge gaps in wild boar damage patterns. Our objective was to investigate how wild boar damage responded to human‐dominated landscapes, evaluating landscape patterns of damage at multiple ecological scales, thus providing a provincial map of damage risk to assist with damage mitigation. We used 1,144 coordinates of wild boar damage from 2009 to 2013 to train multi‐scale risk models with the maximum entropy algorithm. Damage risk was highest on gentle slopes and in heterogenous landscapes composed of fragmented plantations and cropland, with high edge density among small discontinuous patches, and with dense settlements in countryside areas with sporadic road networks. Scale had a substantial effect on relationships between damage and landscapes. We recommend mitigating the conflict risk by improving the compensation system and reducing the damage frequency through repelling, electric fencing, and dissuasive feeding.

Identifying the evolution of ecological poverty alleviation efficiency and its influencing factors: evidence from counties in Northeast China.

Ecological poverty alleviation (EPA) is an effective strategy to address the vicious circle of poverty and environmental destruction in poor areas. However, it remains controversial whether this strategy has really succeeded in this respect. Previous research investigated the impact of a certain factor on EPA, and only few studies integrated them to explore their differential effects, thereby overlooking the complexity of EPA. Therefore, this study quantified the overall efficiency of the EPA strategies of 28 poor counties in three provinces of Northeast China from 2005 to 2018 by using a super-efficiency slacks-based measure model. This model can take into account undesirable outputs; as such, it has significant advantages in measuring the coordination among economic and social development and environmental protection. The Tobit model was used to explore the factors influencing EPA efficiency. The results show that, first, the majority of counties investigated had an EPA efficiency below the overall national average. Second, as for the factors influencing EPA efficiency, it was found that (1) GDP per capita and investment in environmental governance favored EPA efficiency, as they are conducive to stimulating regional consumption dynamics and achieving green economic development; (2) science and technology expenditure and urbanization were not conducive to EPA efficiency; and (3) industrial structure and trade had insignificant effects on EPA efficiency, due to the small scale of industry and the inadequacy of the policy system. This study assessed EPA efficiency from a holistic perspective, and addressed the controversies over EPA's influencing factors, thereby providing an effective method to conduct regional EPA assessment and improve EPA performance in poor regions of China.

Drought Risk Assessment in China Based on Water Resources System

Based on the risk theory, drought hazard, drought exposure and drought vulnerability were evaluated by precipitation, water consumption and water supply, respectively. A model of drought risk assessment method was thus proposed and it is finally applied in China. The results showed that the drought hazard index in the eastern monsoon region was higher, the drought exposure index in the Yangtze River Economic Belt, north China Plain, Heilongjiang Province, Inner Mongolia Autonomous Region and Xinjiang Autonomous Region was higher, the drought vulnerability in the southern region is higher. The middle and lower reaches of the Yangtze River, north China Plain, southwest China, Heilongjiang province in northeast China and Xinjiang Autonomous Region in northwest China are at high risk of drought.

Economic Cooperation of Krasnoyarsk Krai (Territory) with Chinese Regions at the Beginning of the XXI Century (Based on Records of the Krasnoyarsk Krai State Archive)

The article deals with the development of economic cooperation between Krasnoyarsk Krai (Territory) and the regions of China in the first decade of the XXI century. The relevance of the study is in the need to draw on the historical experience of Russia-China relations for the successful development of economic cooperation between the Russian Federation and the People's Republic of China at the present stage. Currently, China is a priority strategic partner for Russia and a key focus of its foreign policy. Problems of interregional cooperation are in the focus of the study. Krasnoyarsk Krai has been cooperating most closely in economic sphere with three provinces of Northeast China, Xinjiang Uygur Autonomous Region and Inner Mongolia Autonomous Region, developing cooperation with southern regions of China. At the beginning of the 21st century, Russia's regions developed international cooperation, building on the experience of the previous decade, but in a new historical context. The authors, for the first time ever, introduce the records that they discovered at the Krasnoyarsk Krai State Archive. These documents show the mutual interest of Russian and Chinese regions in developing cooperation in different sectors of the economy and reflect the problems that hampered the development of economic cooperation, the case of Krasnoyarsk Krai in the first decade of the XXI century.

Remote sensing monitoring of maize and paddy rice planting area using GF-6 WFV red edge features

In order to obtain the high-resolution crop planting information of Liaoning Province in Northeast China and to explore the crop extraction ability of the red edge features of GF-6 satellite at the provincial scale. Five red edge features of RE1, RE2, NDRE, NDVIre1 and NDVI710 were extracted from four periods of GF-6 WFV images from May to September 2020, according to the temporal changes of the ground objects, multiple decision tree models were constructed and the random forest method was used to extract the planting area of maize and paddy rice in the study area. The results showed that the woodland and grassland could be extracted with NDRE, NDVIre1 and NDVI710 in mid-early June, while the water and construction land could be extracted with NDRE, NDVIre1 and RE2 from late July to late September. Maize is more conducive to remote sensing monitoring in the late stage of the growing season, such as heading stage and maturing stage, while paddy rice is more easily identified by image in the late transplanting stage and early reviving stage. In terms of spatial distribution, maize and paddy rice are mainly planted in areas with relatively flat terrain, gentle slope, high temperature and abundant precipitation, the maize is widely distributed in plain, mountainous and hilly areas, and paddy rice is mainly planted in the Liaohe Plain. The overall accuracy and kappa coefficient based on the verification sample points were 97.6% and 0.952, respectively. The user accuracy and producer accuracy of maize were 99.5% and 97.5%, and the user accuracy and producer accuracy of paddy rice were 100% and 97.8%, respectively. The extraction area of maize and paddy rice in Liaoning Province were 2787.39 × 103 hm2 and 487.75 × 103 hm2, respectively. Compared with the statistical yearbook data, the extraction accuracy of maize and paddy rice reached 96.7% and 93.7% respectively. The results indicated that only based on GF-6 WFV temporal red edge features, maize and paddy rice in Liaoning Province can be accurately identified. This method is technically feasible and can achieve high resolution and high precision classification results on a large provincial scale.

Evaluating Community Capability to Prevent and Control COVID-19 Pandemic in Shenyang, China: An Empirical Study Based on a Modified Framework of Community Readiness Model.

Community plays a crucial role in the successful prevention and control of the COVID-19 pandemic in China. However, evaluation of community capability to fight against COVID-19 is rarely reported. The present study provides a first attempt to assess community capability to combat COVID-19 in Shenyang, the capital city of Liaoning province in Northeast China, based on a modified framework of a community readiness model. We conducted semi-structured interviews with ninety key informants from fifteen randomly selected urban communities to collect the data. The empirical results indicate that the overall level of community capability for epidemic prevention and control in Shenyang was at the stage of preparation. The specific levels of the fifteen communities ranged from the stages of preplanning to preparation to initiation. Concerning the level of each dimension, community knowledge about the issue, leadership, and community attachment exhibited significant disparities between communities, while there were slight differences among communities on community efforts, community knowledge of efforts, and community resources. In addition, leadership demonstrated the highest overall level among all the six dimensions, followed by community attachment and community knowledge of efforts. Community resources displayed the lowest level, followed by community efforts. This study not only extends the application of the modified community readiness model to evaluate community capability of epidemic prevention in the Chinese community context, but also offers practical implications for enhancing Chinese communities' capabilities to deal with various future public health emergencies.

Evaluation of the level of quality development of the manufacturing industry in the Northeast

This paper takes the manufacturing industry in the three northeastern provinces as the research object. It establishes an index system based on the connotation of high-quality development of the manufacturing industry from six aspects: development efficiency, green development, innovation-driven, quality brand, people's livelihood sharing, and openness, and measures it used the entropy-weight-TOPSIS method. The results show that, on the whole, the manufacturing industry in Northeast China has been steadily improving, and there are differences in the level of high-quality development of the manufacturing industry among the three provinces in Northeast China, showing that Liaoning is the highest, Jilin the second highest and Heilongjiang the lowest. From each subdivision dimension, there are also differences in the indicators of high-quality development of the manufacturing industry in the three provinces.

Zeolite reduces N leaching and runoff loss while increasing rice yields under alternate wetting and drying irrigation regime

Emerging studies provide promising evidence that applying zeolite combined with water-saving irrigation could effectively retain soil nutrients and increase rice yields. However, the effects of this water-nitrogen management strategy on soil nitrogen (N) loss through leaching and runoff are unclear under field conditions. Herein, we explored the dynamics of N concentrations, quantified soil N losses through leachate and runoff, and investigated the response of reducing N loss on rice yield. A three-year field experiment (2018−2020) was conducted in Donggang city of Liaoning Province in northeast China. The field experiment used a split-plot design, including two irrigation regimes [continuously flooded irrigation (CF) and alternate wetting and drying irrigation (AWD)] as main plots, and two zeolite applications (Z0, no zeolite; Z10, 10 t ha−1 zeolite) as sub-plots, so as to quantify their effects on TN, NH4+-N, NO3−-N loss, and rice yield. Averaged across 3 years, our results showed that AWD reduced the volume of irrigation, leachate, and runoff by 22.2%, 20.8%, and 18.9%, respectively, compared with CF. AWD also decreased the losses of total N (TN), NH4+-N, and NO3−-N by 25.5%, 17.5%, and 11.1% in leachate and by 22.9%, 18.3%, and 26.3% in runoff, respectively, compared with CF. Compared to Z0, Z10 reduced the losses of TN, NH4+-N, and NO3−-N by 16.0%, 16.9%, and 19.4% in leachate and by 10.0%, 14.0%, and 5.9% in runoff, respectively. N output through leaching and runoff under AWD and Z10 was decreased by 2.1% and 2.2%, respectively, compared with CF and Z0. No significant difference was found in rice yield between CF and AWD, whereas rice yields increased 3.3% under Z10 compared with Z0. Altogether, our results highlight that the combination of zeolite and AWD can simultaneously produce more rice yield and reduce soil N losses.

Exploring the potential of multi-source unsupervised domain adaptation in crop mapping using Sentinel-2 images

ABSTRACT Accurate crop mapping is critical for agricultural applications. Although studies have combined deep learning methods and time-series satellite images to crop classification with satisfactory results, most of them focused on supervised methods, which are usually applicable to a specific domain and lose their validity in new domains. Unsupervised domain adaptation (UDA) was proposed to solve this limitation by transferring knowledge from source domains with labeled samples to target domains with unlabeled samples. Particularly, multi-source UDA (MUDA) is a powerful extension that leverages knowledge from multiple source domains and can achieve better results in the target domain than single-source UDA (SUDA). However, few studies have explored the potential of MUDA for crop mapping. This study proposed a MUDA crop classification model (MUCCM) for unsupervised crop mapping. Specifically, 11 states in the U.S. were selected as the multi-source domains, and three provinces in Northeast China were selected as individual target domains. Ten spectral bands and five vegetation indexes were collected at a 10-day interval from time-series Sentinel-2 images to build the MUCCM. Subsequently, a SUDA model Domain Adversarial Neural Network (DANN) and two direct transfer methods, namely, the deep neural network and random forest, were constructed and compared with the MUCCM. The results indicated that the UDA models outperformed the direct transfer models significantly, and the MUCCM was superior to the DANN, achieving the highest classification accuracy (OA>85%) in each target domain. In addition, the MUCCM also performed best in in-season forecasting and crop mapping. This study is the first to apply a MUDA to crop classification and demonstrate a novel, effective solution for high-performance crop mapping in regions without labeled samples.

Evaluation of geographically weighted logistic model and mixed effect model in forest fire prediction in northeast China

IntroductionForest fires seriously threaten the safety of forest resources and human beings. Establishing an accurate forest fire forecasting model is crucial for forest fire management.MethodsWe used different meteorological and vegetation factors as predictors to construct forest fire prediction models for different fire prevention periods in Heilongjiang Province in northeast China. The logistic regression (LR) model, mixed-effect logistic (mixed LR) model, and geographically weighted logistic regression (GWLR) model were developed and evaluated respectively.ResultsThe results showed that (1) the validation accuracies of the LR model were 77.25 and 81.76% in spring and autumn fire prevention periods, respectively. Compared with the LR model, both the mixed LR and GWLR models had significantly improved the fit and validated results, and the GWLR model performed best with an increase of 6.27 and 10.98%, respectively. (2) The three models were ranked as LR model < mixed LR model < GWLR model in predicting forest fire occurrence of Heilongjiang Province. The medium-and high-risk areas of forest fire predicted by the GWLR model were distributed in western and eastern parts of Heilongjiang Province in spring, and western part in autumn, which was consistent with the observed data. (3) Driving factors had strong temporal and spatial heterogeneities; different factors had different effects on forest fire occurrence in different time periods. The relationship between driving factors and forest fire occurrence varied from positive to negative correlations, whether it’s spring or autumn fire prevention period.DiscussionThe GWLR model has advantages in explaining the spatial variation of different factors and can provide more reliable forest fire predictions.

Parental Psychological Flexibility and Children’s Behavior Problems in Rural Areas in Northeast China: The Mediation of Children’s Emotion Regulation

Children's behavior problems are not conducive to their sustainable development. Therefore, it is of great value to explore the mechanism of relevant influencing factors on the behavior problems of rural preschoolers. This study aimed to reveal the direct effect of parental psychological flexibility on children's behavior problems and the mediating effect of children's emotion regulation. Based on simple random sampling, 355 caregivers (male = 31.25 years, SD = 9.78; 74.08% females; 9.01% bachelor degree) were recruited from eight rural kindergartens in three provinces in northeast China. With questionnaires, caregivers reported their parental psychological flexibility and assessed their children's emotion regulation and behavior problems. SPSS 25.0 software was used for statistical data analysis. The results support our hypotheses, suggesting that parental psychological flexibility, emotional stability, and emotional regulation negatively predicted children's externalizing and internalizing behavior problems. Meanwhile, emotional stability and regulation partially mediated the relationship between parental psychological flexibility and children's externalizing and internalizing behavior problems. These findings provide a new perspective for preventing and intervening in preschoolers' behavior problems.

Young MSM changed temporal HIV-1 epidemic pattern in Heilongjiang Province, China.

Human immunodeficiency virus type 1 (HIV-1) epidemic in China is featured by geographical diversity of epidemic patterns. Understanding the characteristics of regional HIV-1 epidemic allows carrying out targeted prevention and controlling measures. This seven-year cross-sectional study was conducted in Heilongjiang, one province of Northeast China, where newly diagnosed infection is fast increasing yearly, but temporal HIV-1 epidemic trend is largely unknown. Information of 1,006 newly diagnosed HIV-1-infected participants were collected before antiretroviral therapy during 2010-2016 in Heilongjiang province. HIV-1 genotype was identified based on the viral gag and env gene sequences. Recent infection was determined by Limiting-Antigen Avidity assays. Comparison analyses on the median ages, CD4 counts, proportions of stratified age groups and CD4 count groups, and rates of recent HIV-1 infection among different population and sampling times were performed to understand temporal HIV-1 epidemic features. Homosexual contact among men who have sex with men (MSM) was the main transmission route and CRF01_AE was the most dominant HIV-1 genotype. During 2010-2016, the HIV-1 epidemic showed three new changes: the median age continued to decline, the cases with a CD4 count more than 500 cells/μl (CD4hi cases) disproportionally expanded, and the recent HIV-1 infection rate steadily increased. MSM cases determined the temporal trend of HIV-1 epidemic here. Increase of young MSM cases (aged <30 years) made the main contribution to the younger age trend of MSM cases. These young MSM exhibited a higher median CD4 count, a higher proportion of CD4hi cases, and a higher rate of recent HIV-1 infection than cases aged 30 years and more. MSM infected by CRF01_AE virus mostly affected HIV-1 epidemic patterns among MSM population. Young MSM have become a new hotspot and vulnerable group for HIV-1 transmission in Heilongjiang Province, Northeast China. The rapid increase in the number of young MSM cases, mainly those with CRF01_AE infection, changed temporal HIV-1 epidemic pattern here. Measures for prevention and control of HIV-1 infection among this population are urgently needed in the future.

Virome analysis of ticks and tick-borne viruses in Heilongjiang and Jilin Provinces, China

Ticks transmit diverse human and animal pathogens, leading to an increasing number of public health concerns. In the forest area of northeast China, the spread of tick-borne diseases (TBDs) is severe; however, little is known about the tick virome composition and evolution. Herein, we investigate the geographical distribution of tick species and related viruses in Heilongjiang and Jilin Provinces in Northeast China. To reveal the diversity of tick-borne viruses in parts of Heilongjiang and Jilin, ticks were collected at 9 collection points in these provinces in 2018. Morphology and molecular biology were used to identify tick species, and 1411 ticks from nine sampling sites were collected and analysed by next-generation sequencing (NGS). Four Ixodidae were identified, including Ixodes persulcatus, Haemaphysalis japonica, Dermacentor silvarum, and Haemaphysalis concinna. After removal of host genome sequences, 13,003 high-quality NGS reads were obtained and annotated as viruses. Further phylogenetic analysis based on amplicons revealed that these viral sequences belong to Beiji nairovirus, Alongshan virus, bovine parvovirus-2, and tick-associated circovirus; some distinct sequences are closely related to Songling virus, Changping tick virus, Norway luteo-like virus 2, and Norway partiti-like virus 1. In summary, this study describes the prevalence of local ticks and variety of tick-borne viruses in northeastern China, providing a basis for further research on tick-borne viruses in the future.

Inquiring the inter-relationships amongst grain-filling, grain-yield, and grain-quality of Japonica rice at high latitudes of China.

The widespread impacts of projected global and regional climate change on rice yield have been investigated by different indirect approaches utilizing various simulation models. However, direct approaches to assess the impacts of climatic variabilities on rice growth and development may provide more reliable evidence to evaluate the effects of climate change on rice productivity. Climate change has substantially impacted rice production in the mid-high latitudes of China, especially in Northeast China (NEC). Climatic variabilities occurring in NEC since the 1970s have resulted in an obvious warming trend, which made this region one of the three major rice-growing regions in China. However, the projections of future climate change have indicated the likelihood of more abrupt and irregular climatic changes, posing threats to rice sustainability in this region. Hence, understanding the self-adaptability and identifying adjustive measures to climate variability in high latitudes has practical significance for establishing a sustainable rice system to sustain future food security in China. A well-managed field study under randomized complete block design (RCBD) was conducted in 2017 and 2018 at two study sites in Harbin and Qiqihar, located in Heilongjiang province in NEC. Four different cultivars were evaluated: Longdao-18, Longdao-21 (longer growth duration), Longjing-21, and Suijing-18 (shorter growth duration) to assess the inter-relationships among grain-filling parameters, grain yield and yield components, and grain quality attributes. To better compare the adaptability mechanisms between grain-filling and yield components, the filling phase was divided into three sub-phases (start, middle, and late). The current study evaluated the formation and accumulation of the assimilates in superior and inferior grains during grain-filling, mainly in the middle sub-phase, which accounted for 59.60% of the yield. The grain yields for Suijing-18, Longjing-21, Longdao-21, and Longdao-18 were 8.02%, 12.78%, 17.19%, and 20.53% higher in Harbin than those in Qiqihar, respectively in 2017, with a similar trend observed in 2018. At Harbin, a higher number of productive tillers was noticed in Suijing-18, with averages of 17 and 15 in 2017 and 2018, respectively. The grain-filling parameters of yield analysis showed that the filling duration in Harbin was conducive to increased yield but the low dry weight of inferior grains was a main factor limiting the yield in Qiqihar. The average protein content values in Harbin were significantly higher (8.54% and 9.13%) than those in Qiqihar (8.34% and 9.14%) in 2017 and 2018, respectively. The amylose content was significantly higher in Harbin (20.03% and 22.27%) than those in Qiqihar (14.44% and 14.67%) in 2017 and 2018, respectively. The chalkiness percentage was higher in Qiqihar, indicating that Harbin produced good quality rice. This study provides more direct evidence of the relative changes in rice grain yield due to changes in grain-filling associated with relative changes in environmental components. These self-adaptability mechanisms to climatic variability and the inter-relationships between grain-filling and grain yield underscore the urgent to investigate and explore measures to improve Japonica rice sustainability, with better adaptation to increasing climatic variabilities. These findings may also be a reference for other global rice regions at high latitudes in addressing the impacts of climate change on future rice sustainability.