Genome-wide association study for cashmere traits in Inner Mongolia cashmere goat population reveals new candidate genes and haplotypes.

BACKGROUND: The cashmere goat industry is one of the main pillars of animal husbandry in Inner Mongolia Autonomous Region, and plays an irreplaceable role in local economic development. With the change in feeding methods and environment, the cashmere produced by Inner Mongolia cashmere goats shows a tendency of coarser, and the cashmere yield can not meet the consumption demand of people. However, the genetic basis behind these changes is not fully understood. We measured cashmere traits, including cashmere yield (CY), cashmere diameter (CD), cashmere thickness (CT), and fleece length (FL) traits for four consecutive years, and utilized Genome-wide association study of four cashmere traits in Inner Mongolia cashmere goats was carried out using new genomics tools to infer genomic regions and functional loci associated with cashmere traits and to construct haplotypes that significantly affect cashmere traits. RESULTS: We estimated the genetic parameters of cashmere traits in Inner Mongolia cashmere goats. The heritability of cashmere yield, cashmere diameter, and fleece length traits of Inner Mongolia cashmere goats were 0.229, 0.359, and 0.250, which belonged to the medium heritability traits (0.2 ~ 0.4). The cashmere thickness trait has a low heritability of 0.053. We detected 151 genome-wide significantly associated SNPs with four cashmere traits on different chromosomes, which were very close to the chromosomes of 392 genes (located within the gene or within ± 500 kb). Notch3, BMPR1B, and CCNA2 have direct functional associations with fibroblasts and follicle stem cells, which play important roles in hair follicle growth and development. Based on GO functional annotation and KEGG enrichment analysis, potential candidate genes were associated with pathways of hair follicle genesis and development (Notch, P13K-Akt, TGF-beta, Cell cycle, Wnt, MAPK). We calculated the effective allele number of the Inner Mongolia cashmere goat population to be 1.109-1.998, the dominant genotypes of most SNPs were wild-type, the polymorphic information content of 57 SNPs were low polymorphism (0 < PIC < 0.25), and the polymorphic information content of 79 SNPs were moderate polymorphism (0.25 < PIC < 0.50). We analyzed the association of SNPs with phenotypes and found that the homozygous mutant type of SNP1 and SNP3 was associated with the highest cashmere yield, the heterozygous mutant type of SNP30 was associated with the lowest cashmere thickness, the wild type of SNP76, SNP77, SNP78, SNP80, and SNP81 was associated with the highest cashmere thickness, and the wild type type of SNP137 was associated with the highest fleece length. 21 haplotype blocks and 68 haplotype combinations were constructed. Haplotypes A2A2, B2B2, C2C2, and D4D4 were associated with increased cashmere yield, haplotypes E2E2, F1F1, G5G5, and G1G5 were associated with decreased cashmere fineness, haplotypes H2H2 was associated with increased cashmere thickness, haplotypes I1I1, I1I2, J1J4, L5L3, N3N2, N3N3, O2O1, P2P2, and Q3Q3 were associated with increased cashmere length. We verified the polymorphism of 8 SNPs by KASP, and found that chr7_g.102631194A > G, chr10_g.82715068 T > C, chr1_g.124483769C > T, chr24_g.12811352C > T, chr6_g.114111249A > G, and chr6_g.115606026 T > C were significantly genotyped in verified populations (P < 0.05). CONCLUSIONS: In conclusion, the genetic effect of single SNP on phenotypes is small, and SNPs are more inclined to be inherited as a whole. By constructing haplotypes from SNPs that are significantly associated with cashmere traits, it will help to reveal the complex and potential causal variations in cashmere traits of Inner Mongolia cashmere goats. This will be a valuable resource for genomics and breeding of the cashmere goat.

Ancestry analysis using a self-developed 56 AIM-InDel loci and machine learning methods.

Insertion/deletion (InDel) polymorphisms can be used as one of the ancestry-informative markers in ancestry analysis. In this study, a self-developed panel consisting of 56 ancestry-informative InDels was used to investigate the genetic structures and genetic relationships between Chinese Inner Mongolia Manchu group and 26 reference populations. The Inner Mongolia Manchu group was closely related in genetic background to East Asian populations, especially the Han Chinese in Beijing. Moreover, populations from northern and southern East Asia displayed obvious variations in ancestral components, suggesting the potential value of this panel in distinguishing the populations from northern and southern East Asia. Subsequently, four machine learning models were performed based on the 56 AIM-InDel loci to evaluate the performance of this panel in ancestry prediction. The random forest model presented better performance in ancestry prediction, with 91.87% and 99.73% accuracy for the five and three continental populations, respectively. The individuals of the Inner Mongolia Manchu group were assigned to the East Asian populations by the random forest model, and they exhibited closer genetic affinities with northern East Asian populations. Furthermore, the random forest model distinguished 87.18% of the Inner Mongolia Manchus from the East Asian populations, suggesting that the random forest model based on the 56 ancestry-informative InDels could be a potential tool for ancestry analysis.

Effects of water replenishment on lake water quality and trophic status: An 11-year study in cold and arid regions.

Water replenishment is an important measure for maintaining and improving the aquatic environmental quality of lakes. The problems of water quality deterioration and water shortage can be alleviated by introducing water of higher quality. However, the mechanism of water replenishment in the improvement of the water quality and trophic status of lakes remains unclear. This study investigated water replenishment in Wuliangsuhai Lake (WLSHL) from 2011 to 2021 by collecting seasonal water samples and conducting laboratory analyses. Water replenishment was found to be capable of significantly improving lake water quality and alleviating eutrophication. It is worth noting that single long-term water replenishment measures have limitations in improving the water quality and trophic status. The whole process was divided into three stages according to the water quality and trophic status, namely the buffer period, decline period, and stable period. During the buffer period, the water quality and trophic status showed only slight improvement because of the small amount of water replenishment and the low proportion of higher-quality water from the Yellow River. In the decline period, with increasing water replenishment, the proportion of higher-quality water from the Yellow River gradually increased, leading to the most significant and stable degree of improvement. In the stable period, increases in the amount of water replenishment had little effect on improving the water quality and trophic status, which is attributable to the balance between internal pollutants (lake water-sediment), and the balance between internal-external pollutants (lake water-irrigation return flow + Yellow River water). On the premise of stable water quality, with eutrophication control as the management goal, the optimal water replenishment would be approximately 10.58 ×108 m3. Further necessary measures for solving aquatic environmental problems include the combination of sediment dredging, optimization of the water replenishment route, and implementation of quality management in water replenishment.

Anthropogenic and climate impacts on carbon stocks of grassland ecosystems in Inner Mongolia and adjacent region.

Up to date, most studies reported that degradation is worsened in the grassland ecosystems of Inner Mongolia and adjacent regions as a result of intensified grazing. This seems to be scientific when considering the total forage or total above-ground biomass as a degradation indicator, but it does not hold true in terms of soil organic carbon density (SOCD). In this study, we quantified the changes of grassland ecosystem carbon stock in Inner Mongolia and adjacent regions from the 1980s to 2000s and identified the major drivers influencing these variations, using the National Grassland Resource Inventory and Soil Survey Dataset in 1980s and the Inventory data during 2002 to 2009 covering 624 sampling plots concerned vegetal traits and edaphic properties across the study region. The result indicated that the above-, below-ground and total vegetation biomass declined from the 1980s to 2000s by ∼ 10 %. However, total forage production increased by 6.72 % when considering livestock intake. SOCD remained stable despite a 67 % increase in grazing intensity. A generalized linear model (GLIM) analysis suggested that an increase in grazing intensity from the 1980s to 2000s could only explain 1.04 % of the total biomass change, while changes in precipitation and temperature explained 17.7 % (p < 0.05) of total vegetation biomass (TVB) change. Meanwhile, SOCD change during 1980s - 2000s could be explained 10.08 % by the soil texture (p < 0.05) and <1.6 % by changes in climate and livestock. This implies that the impacts of climate change on grassland biomass are more significant than those of grazing utilization, and SOCD was resistant to both climate change and intensified grazing. Overall, intensified grazing did not result in significant negative impacts on the grassland carbon stocks in the study region during the 1980s and 2000s. The grassland ecosystems possess a mechanism to adjust their root-shoot ratio, enabling them to maintain resilience against grazing utilization.

Comparison of genomic prediction methods for early growth traits of Inner Mongolia cashmere goats based on multi trait models.

Inner Mongolia cashmere goat is an excellent livestock breed formed through long-term natural selection and artificial breeding, and is currently a world-class dual-purpose breed producing cashmere and meat. Multi trait animal model is considered to significantly improve the accuracy of genetic evaluation in livestock and poultry, enabling indirect selection between traits. In this study, the pedigree, genotype, environment, and phenotypic records of early growth traits of Inner Mongolia cashmere goats were used to build multi trait animal model., Then three methods including ABLUP, GBLUP, and ssGBLUP wereused to estimate the genetic parameters and genomic breeding values of early growth traits (birth weight, weaning weight, average daily weight gain before weaning, and yearling weight). The accuracy and reliability of genomic estimated breeding value are further evaluated using the five fold cross validation method. The results showed that the heritability of birth weight estimated by three methods was 0.13-0.15, the heritability of weaning weight was 0.13-0.20, heritability of daily weight gain before weaning was 0.11-0.14, and the heritability of yearling weight was 0.09-0.14, all of which belonged to moderate to low heritability. There is a strong positive genetic correlation between weaning weight and daily weight gain before weaning, daily weight gain before weaning and yearling weight, with correlation coefficients of 0.77-0.79 and 0.56-0.67, respectively. The same pattern was found in phenotype correlation among traits. The accuracy of the estimated breeding values by ABLUP, GBLUP, and ssGBLUP methods for birth weight is 0.5047, 0.6694, and 0.7156, respectively; the weaning weight is 0.6207, 0.6456, and 0.7254, respectively; the daily weight gain before weaning was 0.6110, 0.6855, and 0.7357 respectively; and the yearling weight was 0.6209, 0.7155, and 0.7756, respectively. In summary, the early growth traits of Inner Mongolia cashmere goats belong to moderate to low heritability, and the speed of genetic improvement is relatively slow. The genetic improvement of other growth traits can be achieved through the selection of weaning weight. The ssGBLUP method has the highest accuracy and reliability in estimating genomic breeding value of early growth traits in Inner Mongolia cashmere goats, and is significantly higher than that from ABLUP method, indicating that it is the best method for genomic breeding of early growth weight in Inner Mongolia cashmere goats.

Exploring environment-specific regulation: Characterizing bacterioplankton community dynamics in a typical lake of Inner Mongolia, China.

Lakes serve as heterogeneous ecosystems with rich microbiota. Although previous studies on bacterioplankton have advanced our understanding, there are gaps in our knowledge concerning variations in the taxonomic composition and community assembly processes of bacterioplankton across different environment conditions. This study explored the spatial dynamics, assembly processes, and co-occurrence relationships among bacterioplankton communities in 35 surface water samples collected from Hulun Lake (a grassland-type lake), Wuliangsuhai Lake (an irrigated agricultural recession type lake), and Daihai Lake (an inland lake with mixed farming and grazing) in the Inner Mongolia Plateau, China. The results indicated a significant geographical distance decay pattern, with biomarkers (Proteobacteria and Bacteroidota) exhibiting differences in the contributions of different bacteria branches to the lakes. The relative abundance of Proteobacteria (42.23%) were high in Hulun Lake and Wuliangsuhai Lake. Despite Actinobacteriota was most dominant, Firmicutes accounted for approximately 17.07% in Daihai Lake, suggested the potential detection of anthropogenic impacts on bacteria within the agro-pastoral inland lake. Lake heterogeneity caused bacterioplankton responses to phosphorus, chlorophyll a, and salinity in Hulun Lake, Wuliangsuhai Lake, and Daihai Lake. Although bacterioplankton community assembly processes in irrigated agricultural recession type lake were more affected by dispersal limitation than those in grassland-type lake and inland lake with mixed farming and grazing (approximately 52.7% in Hulun Lake), dispersal limitation and undominated processes were key modes of bacterioplankton community assembly in three lakes. This suggested stochastic processes exerted a greater impact on bacterioplankton community assembly in a typical Inner Mongolia Lake than deterministic processes. Overall, the bacterioplankton communities displayed the potential for collaboration, with lowest connectivity observed in irrigated agricultural recession type lake, which reflected the complex dynamic patterns of aquatic bacteria in typical Inner Mongolia Plateau lakes. These findings enhanced our understanding of the interspecific relationships and assembly processes among microorganisms in lakes with distinct habitats.

The genus Platypalpus Macquart (Diptera, Hybotidae, Tachydromiinae) from Inner Mongolia, China, with the description of four new species.

Platypalpus Macquart is reported in Inner Mongolia, China for the first time. Four new species are found: P.flavipilosussp. nov., P.longussp. nov., P.shengisp. nov. and P.shuimogouanussp. nov. This paper provides a description of the four species and a key to the genus in Inner Mongolia.

Genotypic and Phenotypic Characteristics of Lactic Acid Bacteria Associated with Forage Plants in the Native Grassland of Western Inner Mongolia and Their Application for Alfalfa Silage Fermentation.

This study was conducted to investigate the genotypic and phenotypic characteristics of lactic acid bacteria (LAB) associated with forage plants in the native grassland of western Inner Mongolia and to evaluate their effects on alfalfa silage fermentation. Forage plants and their spontaneous fermentation silages were analysed using culture-based techniques for LAB isolation; the phenotypic properties and 16S rDNA and pheS or rpoA gene sequences of the isolates were evaluated; alfalfa was ensiled with four additive combinations: Lactiplantibacillus plantarum subsp. plantarum (GI19), Lact. plantarum subsp. plantarum and Pediococcus pentosaceus (GI19+GI51), GI19 and 20 g/kg fresh matter of sucrose (GI19+S), and GI19+GI51+S, for 60 d. A total of 73 strains belonging to 16 species were isolated. All isolates grew at 5-45 °C and in 3.0% NaCl, and most of them grew in 6.5% NaCl. Enterococcus faecalis and Lact. plantarum were 26.03% and 17.81% of the total isolates, respectively. All additives improved the silage quality, while GI19+S was more effective for alfalfa ensiling with a higher lactic acid content and lower pH, undesirable microorganism counts, and acetic acid and NH3-N contents than remnant additives. In conclusion, the LAB species were diverse, and most of them possessed good cryotolerance and osmotolerance; GI19+S was the optimal inoculant for alfalfa fermentation improvement.

Genetic diversity and population structure in five Inner Mongolia cashmere goat populations using whole-genome genotyping.

OBJECTIVE: As a charismatic species, cashmere goats have rich genetic resources. In the Inner Mongolia Autonomous Region, there are three cashmere goat varieties named and approved by the state. These goats are renowned for their high cashmere production and superior cashmere quality. Therefore, it is vitally important to protect their genetic resources as they will serve as breeding material for developing new varieties in the future. METHODS: Three breeds including Inner Mongolia cashmere goats (IMCG), Hanshan White cashmere goats (HS), and Ujimqin white cashmere goats (WZMQ) were studied. IMCG were of three types: Aerbas (AEBS), Erlangshan (ELS), and Alashan (ALS). Nine DNA samples were collected for each population, and they were genomically re-sequenced to obtain high-depth data. The genetic diversity parameters of each population were estimated to determine selection intensity. Principal component analysis, phylogenetic tree construction and genetic differentiation parameter estimation were performed to determine genetic relationships among populations. RESULTS: Samples from the 45 individuals from the five goat populations were sequenced, and 30,601,671 raw single nucleotide polymorphisms (SNPs) obtained. Then, variant calling was conducted using the reference genome, and 17,214,526 SNPs were retained after quality control. Individual sequencing depth of individuals ranged from 21.13× to 46.18×, with an average of 28.5×. In the AEBS, locus polymorphism (79.28) and expected heterozygosity (0.2554) proportions were the lowest, and the homologous consistency ratio (0.1021) and average inbreeding coefficient (0.1348) were the highest, indicating that this population had strong selection intensity. Conversely, ALS and WZMQ selection intensity was relatively low. Genetic distance between HS and the other four populations was relatively high, and genetic exchange existed among the other four populations. CONCLUSION: The Inner Mongolia cashmere goat (AEBS type) population has a relatively high selection intensity and a low genetic diversity. The IMCG (ALS type) and WZMQ populations had relatively low selection intensity and high genetic diversity. The genetic distance between HS and the other four populations was relatively high, with a moderate degree of differentiation. Overall, these genetic variations provide a solid foundation for resource identification of Inner Mongolia Autonomous Region cashmere goats in the future.

Accuracy of Genomic prediction for fleece traits in Inner Mongolia Cashmere goats.

The fleece traits are important economic traits of goats. With the reduction of sequencing and genotyping cost and the improvement of related technologies, genomic selection for goats has become possible. The research collect pedigree, phenotype and genotype information of 2299 Inner Mongolia Cashmere goats (IMCGs) individuals. We estimate fixed effects, and compare the estimates of variance components, heritability and genomic predictive ability of fleece traits in IMCGs when using the pedigree based Best Linear Unbiased Prediction (ABLUP), Genomic BLUP (GBLUP) or single-step GBLUP (ssGBLUP). The fleece traits considered are cashmere production (CP), cashmere diameter (CD), cashmere length (CL) and fiber length (FL). It was found that year of production, sex, herd and individual ages had highly significant effects on the four fleece traits (P < 0.01). All of these factors should be considered when the genetic parameters of fleece traits in IMCGs are evaluated. The heritabilities of FL, CL, CP and CD with ABLUP, GBLUP and ssGBLUP methods were 0.26 ~ 0.31, 0.05 ~ 0.08, 0.15 ~ 0.20 and 0.22 ~ 0.28, respectively. Therefore, it can be inferred that the genetic progress of CL is relatively slow. The predictive ability of fleece traits in IMCGs with GBLUP (56.18% to 69.06%) and ssGBLUP methods (66.82% to 73.70%) was significantly higher than that of ABLUP (36.73% to 41.25%). For the ssGBLUP method is significantly (29% ~ 33%) higher than that with ABLUP, and which is slightly (4% ~ 14%) higher than that of GBLUP. The ssGBLUP will be as an superiors method for using genomic selection of fleece traits in Inner Mongolia Cashmere goats.

Effects of freeze-thaw on bank soil mechanical properties and bank stability.

Riverbank instability in the seasonally frozen zone is primarily caused by freeze-thaw erosion. Using the triaxial freeze-thaw test on the bank of Shisifenzi Bend in the Yellow River section of Inner Mongolia, we investigated the changes in the mechanical properties of the soil at different freezing temperatures and freeze-thaw times, and analyzed the bank's stability before and after freezing based on the finite element strength reduction method. The results showed that the elastic modulus, cohesion, internal friction angle and shear strength of the soil tended to decrease with the increase in the number of freeze-thaw cycles and the decrease in freezing temperature. After 10 freezing cycles at - 5 â„ƒ, - 10 â„ƒ, - 15 â„ƒ and - 20 â„ƒ, the modulus of elasticity of soil decreased by 40.84 ~ 68.70%, the cohesion decreased by 41.96 ~ 56.66%, the shear strength decreased by 41.92 ~ 57.32%, respectively. Moreover, the stability safety coefficient of bank slope decreased by 18.58% after freeze-thaw, indicating that the freeze-thaw effect will significantly reduce the stability of bank slope, and the bank slope is more likely to be destabilized and damaged after freeze-thaw.

Phenological characteristics of net ecosystem carbon exchange of Stipa krylovii steppe in Inner Mongolia, China and its remote sensing monitoring.

To accurately monitor the phenology of net ecosystem carbon exchange (NEE) in grasslands with remote sensing, we analyzed the variations in NEE and its phenology in the Stipa krylovii steppe and discussed the remote sensing vegetation index thresholds for NEE phenology, with the observational data from the Inner Mongolia Xilinhot National Climate Observatory's eddy covariance system and meteorological gradient observation system during 2018-2021, as well as Sentinel-2 satellite data from January 1, 2018 to December 31, 2021. Results showed that, from 2018 to 2021, NEE exhibited seasonal variations, with carbon sequestration occurring from April to October and carbon emission in other months, resulting in an overall carbon sink. The average Julian days for the start date (SCUP) and the end date (ECUP) of carbon uptake period were the 95th and 259th days, respectively, with an average carbon uptake period lasting 165 days. Photosynthetically active radiation showed a negative correlation with daily NEE, contributing to carbon absorption of grasslands. The optimal threshold for capturing SCUP was a 10% threshold of the red-edge chlorophyll index, while the normalized difference vegetation index effectively reflected ECUP with a threshold of 75%. These findings would provide a basis for remote sensing monitoring of grassland carbon source-sink dynamics.

Surveillance of tick-borne bacteria infection in ticks and forestry populations in Inner Mongolia, China.

Ticks are one of the most important vectors that can transmit pathogens to animals and human beings. This study investigated the dominant tick-borne bacteria carried by ticks and tick-borne infections in forestry populations in Arxan, Inner Mongolia, China. Ticks were collected by flagging from May 2020 to May 2021, and blood samples were collected from individuals at high risk of acquiring tick-borne diseases from March 2022 to August 2023. The pooled DNA samples of ticks were analyzed to reveal the presence of tick-borne bacteria using high-throughput sequencing of the 16S rDNA V3-V4 region, and species-specific polymerase chain reaction (PCR) related to sequencing was performed to confirm the presence of pathogenic bacteria in individual ticks and human blood samples. All sera samples were examined for anti-SFGR using ELISA and anti-B. burgdorferi using IFA and WB. A total of 295 ticks (282 Ixodes persulcatus and 13 Dermacentor silvarum) and 245 human blood samples were collected. Rickettsia, Anaplasma, Borrelia miyamotoi, and Coxiella endosymbiont were identified in I. persulcatus by high-throughput sequencing, while Candidatus R. tarasevichiae (89.00%, 89/100), B. garinii (17.00%, 17/100), B. afzelii (7.00%, 7/100), and B. miyamotoi (7.00%, 7/100) were detected in I. persulcatus, as well the dual co-infection with Candidatus R. tarasevichiae and B. garinii were detected in 13.00% (13/100) of I. persulcatus. Of the 245 individuals, B. garinii (4.90%, 12/245), R. slovaca (0.82%, 2/245), and C. burnetii (0.41%, 1/245) were detected by PCR, and the sequences of the target genes of B. garinii detected in humans were identical to those detected in I. persulcatus. The seroprevalence of anti-SFGR and anti-B. burgdorferi was 5.71% and 13.47%, respectively. This study demonstrated that Candidatus R. tarasevichiae and B. garinii were the dominant tick-borne bacteria in I. persulcatus from Arxan, and that dual co-infection with Candidatus R. tarasevichiae and B. garinii was frequent. This is the first time that B. miyamotoi has been identified in ticks from Arxan and R. solvaca has been detected in humans from Inner Mongolia. More importantly, this study demonstrated the transmission of B. garinii from ticks to humans in Arxan, suggesting that long-term monitoring of tick-borne pathogens in ticks and humans is important for the prevention and control of tick-borne diseases.

Provincial Maternal and Child Information System in Inner Mongolia, China: Descriptive Implementation Study.

BACKGROUND: After the implementation of 2- and 3-child policies, the rising proportion of high-age and high-risk pregnancies put enormous pressure on maternal and child health (MCH) services for China. This populous nation with an increasing population flow imperatively required the support of large-scale information systems for management. Municipal MCH information systems were commonly applied in developed cities of eastern provinces in China. However, implementation of provincial MCH information systems in relatively low-income areas is lacking. In 2020, the implementation of a regional maternal and child information system (RMCIS) in Inner Mongolia filled this gap. OBJECTIVE: This paper aimed to demonstrate the construction process and evaluate the implementation effect of an RMCIS in improving the regional MCH in Inner Mongolia. METHODS: We conducted a descriptive study for the implementation of an RMCIS in Inner Mongolia. Based on the role analysis and information reporting process, the system architecture design had 10 modules, supporting basic health care services, special case management, health support, and administration and supervision. Five-color management was applied for pregnancy risk stratification. We collected data on the construction cost, key characteristics of patients, and use count of the main services from January 1, 2020, to October 31, 2022, in Inner Mongolia. Descriptive analysis was used to demonstrate the implementation effects of the RMCIS. RESULTS: The construction and implementation of the RMCIS cost CNY 8 million (US $1.1 million), with a duration of 13 months. Between 2020 and 2022, the system recorded 221,772 registered pregnant women, with a 44.75% early pregnancy registry rate and 147,264 newborns, covering 278 hospitals and 225 community health care centers in 12 cities. Five-color management of high-risk pregnancies resulted in 76,975 (45.45%) pregnancies stratified as yellow (general risk), 36,627 (21.63%) as orange (relatively high risk), 156 (0.09%) as red (high risk), and 3888 (2.30%) as purple (infectious disease). A scarred uterus (n=28,159, 36.58%), BMI≥28 (n=14,164, 38.67%), aggressive placenta praevia (n=32, 20.51%), and viral hepatitis (n=1787, 45.96%) were the top factors of high-risk pregnancies (yellow, orange, red, and purple). In addition, 132,079 pregnancies, including 65,018 (49.23%) high-risk pregnancies, were registered in 2022 compared to 32,466 pregnancies, including 21,849 (67.30%) high-risk pregnancies, registered in 2020. CONCLUSIONS: The implementation of an RMCIS in Inner Mongolia achieved the provincial MCH data interconnection for basic services and obtained both social and economic benefits, which could provide valuable experience to medical administration departments, practitioners, and medical informatics constructors worldwide.

Spatial Variation in Responses of Plant Spring Phenology to Climate Warming in Grasslands of Inner Mongolia: Drivers and Application.

Plant spring phenology in grasslands distributed in the Northern Hemisphere is highly responsive to climate warming. The growth of plants is intricately influenced by not only air temperature but also precipitation and soil factors, both of which exhibit spatial variation. Given the critical impact of the plant growth season on the livelihood of husbandry communities in grasslands, it becomes imperative to comprehend regional-scale spatial variation in the response of plant spring phenology to climate warming and the effects of precipitation and soil factors on such variation. This understanding is beneficial for region-specific phenology predictions in husbandry communities. In this study, we analyzed the spatial pattern of the correlation coefficient between the start date of the plant growth season (SOS) and the average winter-spring air temperature (WST) of Inner Mongolia grassland from 2003 to 2019. Subsequently, we analyzed the importance of 13 precipitation and soil factors for the correlation between SOS and average WST using a random forest model and analyzed the interactive effect of the important factors on the SOS using linear mixing models (LMMs). Based on these, we established SOS models using data from pastoral areas within different types of grassland. The percentage of areas with a negative correlation between SOS and average WST in meadow and typical grasslands was higher than that in desert grasslands. Results from the random forest model highlighted the significance of snow cover days (SCD), soil organic carbon (SOC), and soil nitrogen content (SNC) as influential factors affecting the correlation between SOS and average WST. Meadow grasslands exhibited significantly higher levels of SCD, SOC, and SNC compared to typical and desert grasslands. The LMMs indicated that the interaction of grassland type and the average WST and SCD can effectively explain the variation in SOS. The multiple linear models that incorporated both average WST and SCD proved to be better than models utilizing WST or SCD alone in predicting SOS. These findings indicate that the spatial patterns of precipitation and soil factors are closely associated with the spatial variation in the response of SOS to climate warming in Inner Mongolia grassland. Moreover, the average WST and SCD, when considered jointly, can be used to predict plant spring phenology in husbandry communities.

Dynamic monitoring of aboveground biomass in inner Mongolia grasslands over the past 23 Years using GEE and analysis of its driving forces.

Aboveground biomass (AGB) in grasslands directly reflects the net primary productivity, making it a sensitive indicator of grassland resource quality and ecological degradation. Accurately estimating AGB over large regions to reveal long-term AGB evolution trends remains a formidable challenge. In this study, we divided Inner Mongolia Autonomous Region (IMAR) grasslands into three study regions based on their spatial distribution of grassland types. We combined remote sensing data with ground-based sample data collected over the past 19 years from 6114 field plots using the Google Earth Engine platform. We constructed random forest (RF) and traditional regression AGB inversion models for each region and selected the best-performing model through accuracy assessment to estimate IMAR grassland AGB for the period 2000-2022. We also examined the trends in AGB changes and identified the driving forces affecting IMAR grasslands through the application of Theil-Sen estimation, Mann-Kendall trend analysis, and the Geodetector model. The main findings are as follows: (1) Compared with the univariate parametric traditional regression model, the AGB monitoring accuracy of the multivariate non-parametric RF model in the three study regions increased by 5.94%, 5.08% and 19.14%, respectively. (2) The average AGB per unit area of IMAR grasslands from 2000 to 2022 was 731.41 kg/hm2, with alpine meadow having the highest average AGB (1271.70 kg/hm2) and temperate grassland desertification having the lowest (469.06 kg/hm2). IMAR grasslands exhibited an overall increasing trend in AGB over the past 23 years (6.01 kg/hm2•yr), with the increasing trend covering 83.52% of the grassland area and the decreasing trend covering 16.48%. (3) Spatially, IMAR grassland AGB showed a gradual decline from northeast to southwest and exhibited an increasing trend with increasing longitude (45.423 kg/hm2 per degree) and latitude (71.9 kg/hm2 per degree). (4) Meteorological factors were the most significant factors affecting IMAR grassland AGB, with precipitation (five-year average q value of 0.61) being the most prominent. In the western part of IMAR, where precipitation is consistently limited throughout the year, the primary drivers of influence were human activities, with particular emphasis on the number of livestock (with a five-year average q value of 0.44). It is evident that reducing human activity disturbance and pressure in fragile grassland areas or implementing near-natural restoration measures will be beneficial for the sustainable development of grassland ecosystems. The results of this research hold substantial reference importance for the protection and restoration of grasslands, the supervision and administration of grassland resources, as well as the development of policies related to grassland management.

Impacts of reference population size and methods on the accuracy of genomic prediction for fleece traits in Inner Mongolia Cashmere Goats.

Introduction: Inner Mongolia Cashmere Goats (IMCGs) are famous for its cashmere quality and it's a unique genetic resource in China. Therefore, it is necessary to use genomic selection to improve the accuracy of selection for fleece traits in Inner Mongolia cashmere goats. The aim of this study was to determine the effect of methods (GBLUP, BayesA, BayesB, Bayesian LASSO, Bayesian Ridge Region) and the reference population size on accuracy of genomic selection in IMCGs. Methods: This study fully utilizes the pedigree and phenotype records of fleece traits in 2255 individuals, genotype of 50794 SNPs after quality control, and environmental data to perform genomic selection of fleece traits. Then GBLUP and Bayes series methods (BayesA, BayesB, Bayesian LASSO, Bayesian Ridge Region) were used to perform estimates of genetic parameter and genomic breeding value. And the accuracy of genomic estimated breeding value (GEBV) is evaluated using the five-fold cross validation method. And the analysis of variance and multiple comparison methods were used to determine the best method for genomic selection in fleece traits of IMCGs. Further the different reference population sizes (500, 1000, 1500, and 2000) was set. Then the best method was applied to estimate genome breeding values, and evaluate the impact of reference population sizes on the accuracy of genome selection for fleece traits in IMCGs. Results: It was found that the genomic prediction accuracy for each fleece trait in IMCGs by GBLUP method is highest, and it is significantly higher than that obtained by Bayesian method. The accuracy of breeding value estimation is 58.52% -68.49%. Also, it was found that the size of the reference population has a significant impact on the accuracy of genome prediction of fleece traits. When the reference population size is 2000, the accuracy of genomic prediction for each fleece trait is significantly higher than other levels, with accuracy of 55.47% -67.87%. This provides a theoretical basis for design a reasonable genome selection plan for Inner Mongolia cashmere goats in the later stag.

Extreme drought alters methane uptake but not methane sink in semi-arid steppes of Inner Mongolia.

Global climate change, particularly drought, is expected to alter grassland methane (CH4) oxidation, a key natural process against atmospheric greenhouse gas accumulation, yet the extent of this effect and its interaction with future atmospheric CH4 concentrations increases remains uncertain. To address this research gap, we measured CH4 flux during an imposed three-month rain-free period corresponding to a 100-year recurrence drought in soil mesocosms collected from 16 different Eurasian steppe sites. We also investigated the abundance and composition of methanotrophs. Additionally, we conducted a laboratory experiment to explore the impact of elevated CH4 concentration on the CH4 uptake capacity of grassland soil under drought conditions. We found that regardless of the type of grassland, CH4 flux was still being absorbed at its peak, meaning that all grasslands functioned as persistent CH4 sinks even when the soil water content (SWC) was <5 %. A bell-shaped relationship between SWC and CH4 uptake was observed in the soils. The average maximum CH4 oxidation rate in the meadow steppe was higher than that in the typical and desert steppe soils during extreme drought. The experimental elevation of atmospheric CH4 concentration counteracted the anticipated reduction in CH4 uptake related to physiological water stress on methanotrophic soil microbes under the drought stress. On the contrary, we found that across the regional scale, nitrogen, phosphorous, and total soil organic content played a crucial role in moderating the duration and magnitude of CH4 uptake with respect to SWC. USC-γ (Upland Soil Cluster γ) and JR-3 (Jasper Ridge Cluster) were the dominant group of soil methanotrophic bacteria in three types of grassland. However, the methanotrophic abundance, rather than the methanotrophic community composition, was the dominant microbiological factor governing CH4 uptake during the drought.

Origin and stability of pit lake water in Baiyinhua, Inner Mongolia, based on hydrochemistry and stable isotopes.

Isotope technology is widely used in geochemical mechanisms analysis; however, studies on the origin of pit lake water by isotopes in coal concentration areas in grassland are rare. In this study, 20 groups of water samples were collected, which were subjected to chemical analysis to determine the hydrogeochemical characteristics of pit lake water. The mechanisms of pit lake water formation and recharge-evaporation were ascertained through principal component analysis and the Rayleigh fractionation model. The results indicate that the phreatic water is least affected by evaporation, followed by confined water, surface water and pit lake water. The ionic composition of surface water, phreatic water and most of the confined water is mainly affected by leaching, some confined water can be recharged by surface or phreatic water; while the ionic composition of pit lake water is dominantly affected by evaporation (69.4 %) and is less affected by groundwater recharge (17.1 %) and human activities (11.5 %). The pit lake water is recharged by precipitation, phreatic water and the lateral runoff of confined water; however, the proportion of phreatic and confined water recharge is small. The evaporative loss of the pit lake water is 40-61 % of the initial water body.

Assessing grassland cultural ecosystem services supply and demand for promoting the sustainable realization of grassland cultural values.

Grasslands deliver essential provisioning and regulatory ecosystem services, concomitantly with indispensable cultural services that merit profound consideration. However, grassland cultural ecosystem services (GCES) face a conspicuous knowledge lacuna due to the lack of a unified research framework and quantitative methodology. This study endeavors to fill this gap by quantifying the potential supply and actual demand of GCES, concurrently scrutinizing spatial congruencies and disparities between GCES supply and demand in Inner Mongolia Autonomous Region (IMAR), China. To achieve this, we integrated social survey data, Point of Interest (POI) data, social media data, the Social Values for Ecosystem Services (SolVES) model and GIS Getis-Ord Gi* statistical analysis. Our analysis unveiled grid-scale spatial patterns of GCES supply and demand, furnishing a nuanced high-low ranking of GCES. It transpired that scenic travel holds the highest potential supply of GCES with a high-value area proportion of 46.0 %, while grassland recuperation ranks the lowest. Notably, road accessibility emerged as the most crucial factor influencing GCES patterns. Furthermore, we observed a substantial misalignment in the GCES supply-demand relationship, with 65.99 % of IMAR experiencing excess supply compared to demand and only 20.66 % achieving equilibrium. At a 95 % significance level, hot spots (excess supply) and cold spots (excess demand) accounted for 26.03 % and 22 %, respectively. We propose targeted suggestions that regions with oversupply of GCES should channel efforts toward augmenting road accessibility, whereas regions grappling with excess demand should prioritize the judicious allocation of resources to avert surpassing the environmental carrying capacity. Our study furnished insights for decision-makers to formulate sustainable development plans pertaining to grassland culture.