Search Results (15)

The relationship between ozone (O₃) exposure and gestational diabetes mellitus (GDM) in twin pregnancies remains unexplored. This study aimed to investigate the association between O₃ exposure and GDM risk in twin pregnancies, and to explore the synergistic effects of O₃ exposure with other maternal factors. A total of 428 pregnancies recruited from a prospective twin cohort were included. Cox proportional hazard models with distributed lag non-linear models (DLNMs) were applied to examine the associations between O₃ exposure and the risk of GDM and to identify the critical windows. The multiplicative and additive interaction were further analyzed to test the synergistic effects. A 10 μg/m³ increase in average O₃ exposure during the 12 weeks before pregnancy was associated with a 26% higher risk of GDM. The critical windows were identified in the period from the 3rd week before gestation to the 2nd gestational week as well as from the 17th to 19th gestational week. There were synergistic effects between high O₃ exposure during preconception and advanced maternal age, and a history of preterm birth/abortion/stillbirth. Periconceptional O₃ exposure could increase the risk of GDM in twin pregnancy women, and the synergism of O₃ exposure with certain GDM risk factors was observed. Full article

Onychostoma macrolepis is not only a protected Cyprinid species in the wild but also an emerging commercial aquaculture fish in China. The objective of this research was to genetically modify the genes associated with commercial traits by CRISPR/Cas9 for the protection and utilization of the germplasm resources of O. macrolepis. To that end, one-cell stage embryos were obtained via hormone-induced ovulation and artificial insemination in O. macrolepis. Eight genes related to body color, growth, intermuscular bone, and sex differentiation were mutated in O. macrolepis using the CRISPR/Cas9 system by microinjection of gRNA/Cas9 mRNA. The optimal dose of gRNA/Cas9 mRNA was determined by injection of different concentrations of tyr (tyrosinase)-gRNA/Cas9 and examination of the mutation rate and hatching rate of embryos. Indels were detected by T7 endonuclease I digestion and Sanger sequencing. F0 mutants with high mutation rates were selected for phenotype analyses. Disruption of body color gene tyr, mpv17 (mitochondrial inner membrane protein MPV17), and csf1ra (colony-stimulating factor 1 receptor, a) resulted in obvious phenotype with decreased or even absence of melanophores, iridophores, and xanthophores, respectively. Mutation of mstnb (myostatin b) led to improved growth performance. Mutation of mc4r (melanocortin 4 receptor) led to no obvious phenotype. Mutation of runx2b (RUNX family transcription factor 2b) and bmp6 (bone morphogenetic protein 6) resulted in decreased or absence of intermuscular bones, as revealed by alizarin red S staining. Mutation of cyp19a1a (cytochrome P450, family 19, subfamily A, polypeptide 1a) resulted in ovarian degeneration as revealed by gonadal histological examination. Therefore, this study successfully obtained mutants with obvious phenotypes of genes associated with body color, growth, intermuscular bone, and sex differentiation by CRISPR/Cas9 in O. macrolepis. Full article

Water pollution is the main cause of global ecological degradation and seriously affects people’s water supply. In order to respond to the water environmental protection policy and provide management departments with a basis for refining water quality, this paper uses the environmental Gini coefficient (EGC) method based on four indicators, such as water environmental capacity, population, land area, and gross domestic production (GDP), to represent social, economic, and environmental factors, respectively. After the optimization, for COD, the EGC based on the land area was 0.30, EGC based on population was 0.21, EGC based on environment capacity was 0.02, and the EGC based on GDP was 0.45, and the sum of EGC was 0.962. From this result, we can observe that the change in the Gini coefficient of each indicator is not very considerable. Hence, the most significant change in the Gini coefficient was that of GDP, with a higher rate than the other criteria. Then, the COD, AND, and TP discharge allocation models were constructed to obtain the total allocated discharge permit for the Lushui Basin. The results show that the total discharge permit allocations of COD, AN, and TP for the Lushui Basin are 51,483.304, 843.119, and 340.926 tons/year, respectively. Based on GIS spatial analysis technology, the distribution of unfair factors that cause pollution inequity is investigated. Finally, reduction measures were proposed to implement environmental supervision and improve water environmental management. Full article

The process of eliminating absolute poverty is inevitable for China’s social and economic transformation. However, there are currently few studies on the relationship between land use transformation (LUT) and rural income under different stages of poverty governance. This study, therefore, uses spatial autocorrelation analysis and a multiscale geographic weighted regression (MGWR) model to explore the mechanisms of LUT on rural income and its spatiotemporal heterogeneity in Yunnan Province during the comprehensive poverty alleviation (CPA) period and the targeted poverty alleviation (TPA) period at the county scale. The results demonstrate that: (1) the numbers of both low-income and high-income counties continued to decrease, while the number of middle-high-income counties increased, and rural income demonstrated a positive spatial correlation. (2) Most of the variables in the dominant recessive increased in the CPA and decreased in the TPA period. As for recessive morphology, the ecological function variables decreased first and then increased. (3) The driving force of dominant morphology is strong and sustained, and the driving force of recessive morphology is gradually enhanced. The results are vital for consolidating the results of poverty eradication and bridging rural revitalization. They may also provide useful references for sustainable land use and effective poverty alleviation in other developing countries. Full article

Absolute poverty has historically been solved in China, and the focus on poor areas has shifted to addressing relative poverty. To realize the organic combination of the rural revitalization strategy and relative poverty governance, multi-dimensional relative poverty identification and governance path research at the village scale in an alpine-gorge region is required. For this study, the Nujiang Lisu Autonomous Prefecture’s research area in a typical alpine-gorge was chosen. This paper constructed an evaluation index system for the rural regional system based on location conditions, ecological environment, productive resources, economic base, and public service, based on the theory of multi-dimensional regional poverty and the human–land relationship. The level of poverty, types of poverty, and spatial distribution characteristics of 255 administrative villages were systematically analyzed, and poverty governance paths were proposed. The results show that: (1) There were 215 multi-dimensional relative poverty villages in Nujiang Prefecture, accounting for 84.31% of the total. The relatively poor villages with poverty grades I and II, which are classified as mild poverty, account for 77.21% of all poor villages; this demonstrated that the relatively poor villages in Nujiang Prefecture had a high potential for poverty alleviation. (2) There are 19 different types of constraints in poor villages. Grades III and IV poor villages were mostly found in high-altitude areas. The economic foundation was very weak, the infrastructure was imperfect, the land use type was relatively single, and traffic conditions were relatively backward. (3) The priority model accounted for 16.67% of relative poverty governance, the steady improvement accounted for 28.79%, and key support accounted for 54.54%. Relative poverty governance paths for various counties have been proposed, including rural revitalization priority demonstration, ecological environment governance, eco-tourism, modern agriculture + mountain agroforestry, and improved people’s livelihood and well-being. The findings provided scientific support and direction for future research on the mode and course of relative poverty governance in poor villages in the alpine-gorge area, as well as the rural revitalization strategy’s implementation. Full article

Developing landslide susceptibility modeling is essential for detecting landslide-prone areas. Recently, deep learning theories and methods have been investigated in landslide modeling. However, their generalization is hindered because of the limited size of landslide data. In the present study, a novel deep learning-based landslide susceptibility assessment method named deep random neural network (DRNN) is proposed. In DRNN, a random mechanism is constructed to drop network layers and nodes randomly during landslide modeling. We take the Lushui area (Southwest China) as the case and select 12 landslide conditioning factors to perform landslide modeling. The performance evaluation results show that our method achieves desirable generalization performance (Kappa = 0.829) and outperforms other network models such as the convolution neural network (Kappa = 0.767), deep feedforward neural network (Kappa = 0.731), and Adaboost-based artificial neural network (Kappa = 0.732). Moreover, the robustness test shows the advantage of our DRNN, which is insensitive to variations in training data size. Our method yields an accuracy higher than 85% when the training data size stands at only 10%. The results demonstrate the effectiveness of the proposed landslide modeling method in enhancing generalization. The proposed DRNN produces accurate results in terms of delineating landslide-prone areas and shows promising applications. Full article

Anthropogenic activities have altered ecosystem service functions in the karst mountainous areas. The implementation of ecological restoration projects by the government, the behavior, attitude, and willingness of farmers to participate in their implementation, the application of pesticides and fertilizers, in addition to other socio-economic activities, have had a significant impact on the ecosystem services (ESS) of the region. Taking Guangnan County, a typical karst mountainous area in Yunnan Province, as an example, this study analyzes the evolutionary characteristics of six types of ESS and the driving mechanism of the change in ESS from the anthropogenic macro and micro perspective using questionnaire surveys and the multivariate logistic model. The results showed that (1) ecological restoration projects in the past 20 years have promoted an overall ecological transformation in the typical karst mountainous areas of the Yunnan Province (2) from the macro perspective, and the implementation of such ecological projects is beneficial in increasing soil conservation, carbon sequestration, habitat support, and cultural services. The reduction in agricultural population is beneficial in improving habitat support services, and the increase in the annual average tourism income and the tertiary industry is beneficial in increasing cultural services. Among them, the impact of hydraulic engineering on water production and the tertiary industry on cultural services are the most significant, with the change in the human disturbance index having the most substantial impact on soil conservation, carbon sequestration, and habitat support (3) at the micro level. Increasing pesticide and fertilizer application, willingness and use by farmers has a positive impact on food supply and a negative impact on habitat quality. An increase in the number and willingness of farmers participating in restoring farmland to forests and water conservancy projects was observed. This has a positive impact on soil conservation, water production, and carbon sequestration. Among them, the application of chemical fertilizers and pesticides has the most significant impact on food supply and habitat support, and the willingness to implement the projects on restoring farmlands to forests has the most significant impact on carbon sequestration. The willingness to implement terracing has the greatest impact on water production and soil conservation, and aesthetic value has the greatest impact on cultural services. Full article

Constructing an ecological security pattern is vital to guaranteeing regional ecological security. The terrain and geomorphology of the alpine valley are complex and sensitive, meaning it is difficult to construct ecological security patterns. Therefore, the study takes Nujiang Prefecture as the study area and builds an “Importance–Sensitivity–Connectivity” (Importance of ecosystem service, eco-environmental sensitivity, and landscape connectivity) framework to carry on the comprehensive evaluation of the ecological security and identification of ecological sources. Furthermore, we constructed an ecological resistance surface using land-use type. Using the minimum cumulative resistance (MCR) model, the study identifies the ecological corridors and nodes to build ecological security patterns to optimize the ecological spatial structure of Nujiang Prefecture. The results showed that (1) the importance of ecosystem services was higher in the west and lower in the east. The high-sensitive areas of the ecological environment were distributed discontinuously along the banks of the Nujiang and the Lantsang River, and the areas with high landscape connectivity were distributed in patches in the Gaoligong Mountain Nature Reserve and the Biluo Snow Mountain. (2) The overall ecological security was in a good state, and the ecologically insecure areas were primarily distributed in Lanping County and the southeast region of Lushui City. (3) The primary ecological source area was identified to be 3281.35 km² and the secondary ecological source area to be 4224.64 km². (4) In total, 26 primary ecological corridors, 39 secondary ecological corridors, and 82 ecological nodes were identified. Full article

The ecological barrier is a complex ecosystem that couples the human–nature relationship, and the ecologically critical area is an irreplaceable area with a special value in the ecosystem. Therefore, protecting the ecologically critical area is vital for maintaining and improving regional ecological security. Limited research has been conducted on the evolution of ecologically critical areas, and none of the studies have considered the spatiotemporal heterogeneity of the driving factors for different evolution modes and types. Therefore, this research adopts the ecologically critical index, landscape expansion index, and the random forest model to analyze the pattern, driving factors, and its spatial-temporal heterogeneity to the evolution modes and specific types of ecologically critical areas in the Sichuan–Yunnan ecological barrier area in the last 15 years. The results showed that: (1) the ecologically critical areas in the Sichuan–Yunnan ecological barrier have changed dramatically, with the area reduction being 61.06%. Additionally, the spatial distribution characteristics of the ecologically critical area from north to south include planar, point, and linear forms. (2) The evolution trend of the ecologically critical area is ‘degradation–expansion–degradation’. Spread is the predominant type of expansion mode, whereas atrophy is the predominant type of degradation mode, indicating that the evolution mainly occurs at the edge of the original ecologically critical areas. (3) In general, precipitation, area of forest, area of cropland, and GDP have contributed significantly to the evolution of ecologically critical areas. However, the same driving factor has different effects on the expansion and degradation of these areas. Expansion is driven by multiple factors at the same time but is mainly related to human activities and land use change, whereas for degradation, climate and policy are the main driving factors. The present research aimed to quantitatively identify the evolution modes and specific types of ecologically critical areas and explore the spatiotemporal heterogeneity of driving factors. The results can help decision-makers in formulating ecological protection policies according to local conditions and in maintaining and enhancing the regional ecological functions, thereby promoting the sustainable development of society-economy-ecology. Full article

Rocky desertification in ecologically-fragile karst areas limit regional socio-economic development in the face of significant human–earth conflict. Coordination of ecological restoration and agricultural development is critical for sustainable development in karst areas. From the perspective of the human–earth areal system, the framework of sustainable agricultural development was proposed in typically karst areas. We integrated principles of ecological vulnerability, resource and environmental carrying capacity, agricultural foundation, suitability of agricultural land, and the farmers’ willingness. In this study, we found the ecological vulnerability of Guangnan County was slight, but the proportion of moderate and severe vulnerability areas was high, with significant differences between the two sides of the line “Zhe (Zhetu)-Lian (Liancheng)-Yang (Yang Liu-jing)-Ban (Banbang)”. Then, we divided Guangnan County into three ecologically vulnerable zones. Following that, we proposed sustainable agricultural models for various zones. In slightly to mildly vulnerable zones, we propose constructing economic–ecological agricultural models, including woody oil, plateau characteristic fruiting forest, ecological tea plantations, suburban agriculture, and cultural–ecological tourism. In moderately to severely vulnerable zones, we recommend developing a stereoscopic agriculture model that combines planting and breeding, vegetation restoration, and herbivorous animal husbandry. In extremely vulnerable zones, we suggest constructing an ecologically natural restoration model and an agricultural ecological–tourism model. Our research provides references for ecological restoration, agricultural development, poverty alleviation consolidation, and rural revitalization in ecologically vulnerable karst areas of southeast Yunnan and similar regions. Full article

In recent years, the severe deterioration of water quality and eutrophication in the Yangtze River has brought much trouble to people’s lives. Because of this, numerous management departments have paid more and more attention to the treatment of the water environment. In order to respond to water environmental protection policy and provide management departments with a basis for refining water quality, this paper takes the Zhuzhou section of Yangtze River-Lushui watershed as its research object. First, we used the Water Quality Analysis Simulation Program (WASP) model as a tool, and obtained the pollution load using the FLUX method formula. During the calibration process, the sensitivity analysis method, the orthogonal design method, and the trial and error method were used. Then, we verified the results by using water quality monitoring data published by Zhuzhou Ecological Environment Bureau. Following that, the water environmental capacity of the Lushui River in normal, wet and dry periods was calculated using the WASP model: the chemical oxygen demand (COD) was 14,072.94 tons/yr, 17,147.7 tons/yr and 10,998.18 tons/yr, respectively; ammonia nitrogen (AN) was 469.098 tons/yr, 571.59 tons/yr and 366.606 tons/yr, respectively; and total phosphorus (TP) was 93.8196 tons/yr, 114.318 tons/yr and 73.3212 tons/yr, respectively. The results show that the WASP model is applicable and reliable and can be used as an effective tool for water quality prediction and management in this area. Full article

Harmful cyanobacterial blooms pose a risk to human health worldwide. To enhance understanding on the bloom-forming mechanism, the spatiotemporal changes in cyanobacterial diversity and composition in two eutrophic lakes (Erhai Lake and Lushui Reservoir) of China were investigated from 2010 to 2011 by high-throughput sequencing of environmental DNA. For each sample, 118 to 260 cpcBA-IGS operational taxonomic units (OTUs) were obtained. Fifty-two abundant OTUs were identified, which made up 95.2% of the total sequences and were clustered into nine cyanobacterial groups. Although the cyanobacterial communities of both lakes were mainly dominated by Microcystis, Erhai Lake had a higher cyanobacterial diversity. The abundance of mixed Nostocales species was lower than that of Microcystis, whereas Phormidium and Synechococcus were opportunistically dominant. The correlation between the occurrence frequency and relative abundance of OTUs was poorly fitted by the Sloan neutral model. Deterministic processes such as phosphorus availability were shown to have significant effects on the cyanobacterial community structure in Erhai Lake. In summary, the Microcystis-dominated cyanobacterial community was mainly affected by the deterministic process. Opportunistically dominant species have the potential to replace Microcystis and form blooms in eutrophic lakes, indicating the necessity to monitor these species for drinking water safety. Full article

Landslide susceptibility mapping is considered to be a prerequisite for landslide prevention and mitigation. However, delineating the spatial occurrence pattern of the landslide remains a challenge. This study investigates the potential application of the stacking ensemble learning technique for landslide susceptibility assessment. In particular, support vector machine (SVM), artificial neural network (ANN), logical regression (LR), and naive Bayes (NB) were selected as base learners for the stacking ensemble method. The resampling scheme and Pearson’s correlation analysis were jointly used to evaluate the importance level of these base learners. A total of 388 landslides and 12 conditioning factors in the Lushui area (Southwest China) were used as the dataset to develop landslide modeling. The landslides were randomly separated into two parts, with 70% used for model training and 30% used for model validation. The models’ performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) and statistical measures. The results showed that the stacking-based ensemble model achieved an improved predictive accuracy as compared to the single algorithms, while the SVM-ANN-NB-LR (SANL) model, the SVM-ANN-NB (SAN) model, and the ANN-NB-LR (ANL) models performed equally well, with AUC values of 0.931, 0.940, and 0.932, respectively, for validation stage. The correlation coefficient between the LR and SVM was the highest for all resampling rounds, with a value of 0.72 on average. This connotes that LR and SVM played an almost equal role when the ensemble of SANL was applied for landslide susceptibility analysis. Therefore, it is feasible to use the SAN model or the ANL model for the study area. The finding from this study suggests that the stacking ensemble machine learning method is promising for landslide susceptibility mapping in the Lushui area and is capable of targeting areas prone to landslides. Full article

Surveying the activity rhythms of sympatric herbivorous mammals is essential for understanding their niche ecology, especially for how they partition resources and their mechanisms of coexistence. Over a five-year period, we conducted infrared camera-trapping to monitor the activity rhythms of coexisting red serow (Capricornis rubidus) and Chinese serow (C. milneedwardsii milneedwardsii) in the remote mountainous region of Pianma, Mt. Gaoligong, Yunnan, China. Cameras captured images of red serow and Chinese serow on 157 and 179 occasions, respectively. We used circular kernel density models to analyze daily activity rhythms and how temporal variations in activity ensure their co-existence. Although their overall activity levels and patterns were similar, temporal activity and behavior partitioning among the two species occurred during the wet season. Compared with Chinese serows, red serows exhibited less variable daily activity levels, patterns, as well as feeding and vigilance behaviors between seasons. When the two species occasionally ranged together, red serows tended to alter their activity pattern while Chinese serows significantly increased their activity level. Red serow and Chinese serow are exploitative competitors but coexist by altering their daily activity rhythms when in contact and changing activity patterns during the wet season, enabling their coexistence. Full article

Understanding the driving factors of land-use spatio-temporal change is important for the guidance of rational land-use management. Based on land-use data, household surveys and social economic data in 2000, 2005, 2010, and 2015, this study adopted the Binary Logistic Regression Model (BLRM) to analyze the driving factors of land-use spatio-temporal change in a large artificial forest area in the Ximeng County, Yunnan province, in Southwest China. Seventeen factors were used to reflect the socio-economic and natural environment conditions in the study area. The results show a land use pattern composed of forestland, dry cropland, and rubber plantation in Ximeng County. Over the past fifteen years, the area of artificial forests increased rapidly due to the “Grain for Green” policy, which has led to increases in rubber plantations, tea gardens, eucalyptus forests, etc. In contrast, the area of natural forest and dry cropland decreased due to reclamations for farming and constructions. The BLRM approach helped to identify the main driving factors of land-use spatio-temporal change, which includes land-use policies (protection of basic farmlands and natural reserves), topography (elevation and slope), accessibility (distance to the human settlements), and potential productivity (fertility and irrigation). The study revealed the relationship between land-use spatio-temporal change and its driving factors in mountainous Southwest China, providing a decision-making basis for rational land-use management and optimal allocation of land resources. Full article