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Platypalpus Macquart is reported in Inner Mongolia, China for the first time. Four new species are found: P. flavipilosus sp. nov., P. longus sp. nov., P. shengi sp. nov. and P. shuimogouanus sp. nov. This paper provides a description of the four species and a key to the genus in Inner Mongolia. [ABSTRACT FROM AUTHOR]

In pastoral society, the reproduction of livestock is directly related to the survival and prosperity of herders. The key to domestic animal reproduction lies in the cognitive bond between mother livestock and their young. Herdsmen use various tools and techniques to help develop this cognitive bond. These human mediation tools have various characteristics such as 'restorative' or 'destructive'. The lamb bag, a widely used tool in pastoral society, has both 'restorative' and 'destructive' natures. Based on ethnographic data collected in Inner Mongolia, China, this paper first introduces the production method of lamb bags, then describes their structure, function and the multi-dimensional relationships generated during the application process, and finally discusses the cultural implications of 'restorative' and 'destructive' human mediation in pastoral culture. [ABSTRACT FROM AUTHOR]

Prospecting for and exploiting buried mineral deposits is currently challenging. Given their high precision and resolution, reflection seismic methods might be useful in such applications involving deep mineral deposits. However, there are few open seismic datasets available from mineral deposit exploration, especially in hardrock environments. The world‐class Caosiyao porphyry Molybdenum deposit (1.76 Mt) in the Jining area of Inner Mongolia, China, is largely covered by loess layers, which poses challenges to its exploration. Seismic reflection surveys were conducted to help delineate the deep granite porphyry intrusions and associated orebodies. This paper presents the raw seismic reflection dataset from three profiles on the Caosiyao deposit area, which can be used as a standard dataset for reflection seismic processing in shallow coverage and hardrock areas. Situated at the juxtaposition of the Khondalite Belt and the Trans‐North China Orogen in the northern North China Craton, the Jining region hosts considerable known porphyry Mo deposits. As such, this open dataset can assist in research on deep geological structures and hence increase prospecting efficiency in geologically similar areas. [ABSTRACT FROM AUTHOR]

Metal migration and precipitation in hydrothermal fluids are important topics in economic geology. The Hongling polymetallic deposit comprises one of the most important parts of the Huanggangliang–Ganzhuermiao polymetallic metallogenic belt, which is in eastern Inner Mongolia. Except for lead–zinc skarn, minor cassiterite in the skarn and disseminated W–Sn mineralization in granitic rocks have also been found. The dominant Sn–W mineralization is in the northern part of the deposit, occurring as disseminated wolframite and cassiterite in aplite hosted in Mesozoic granite porphyry. The aplite together with pegmatite K-feldspar–quartz comprises vein dikes hosted in the granite porphyry, providing evidence for the transition from melt to fluid. The veins, dikes, and Sn–W mineralization in the aplite provide an opportunity to investigate fluid exsolution and the mechanics of metal precipitation. Based on field observations, the micrographic and scanning electron microscopy/energy dispersive spectroscopy (SEM/EDS) results of the vein dikes, chronology, and the whole-rock geochemistry of the host rock, together with the fluid inclusion results, this paper discusses the characteristics of the causative magma, the mechanics of fluid exsolution and W–Sn precipitation. Our results show that the causative magma is of highly fractionated A-type granite affinity and has an intrusive age of late Mesozoic (133.3 ± 0.86 Ma). The magmatic evolution during shallow emplacement led to immiscibility between highly volatile, high-silica, and W- and Sn-enriched melts from the parent magma, followed by fluid exsolution from the water-rich melt. The alkaline-rich fluid exsolution led to a change in the redox state of the magma and the chilling of the melt. Fluid boiling occurred soon after the fluid exsolution and was accompanied by the degassing of CO2. The boiling and escape of CO2 from the fluid led to changes in fluid redox and W and Sn precipitation; thus, the W and Sn mineralization are mostly hosted in causative intrusions or peripheral wall rocks, which can be used as indicators for Sn–W exploration in the area. [ABSTRACT FROM AUTHOR]

Simple Summary: In recent years, the shortage of cow stocks and the reduction of cow breeders in China have caused a shortage of cattle resources and a high price of calves, which has become a bottleneck restricting the further development of China's beef cattle industry. At present, there are few studies on the decision-making behavior of cow breeding in China. In order to explore the factors that affect the decision-making behavior on cow breeding by beef cattle farmers, this paper uses field survey data to make an empirical analysis through the Logit ISM model. The results show that the age of the breeder, the breeding year, the planting area of forage, market expectations, the loan amount, the breeding method policy publicity and policy subsidies are significant factors affecting the decision-making behavior of beef cattle farmers on cow breeding. The beef cattle industry is an important part of herbivorous animal husbandry and an important industry to enrich the dietary structure of residents and promote the income of farmers and herdsmen. The cow is an important foundation to support the healthy development of the beef cattle industry, which is related to the stability of cattle sources and the sustainable development of the industry. However, in recent years, the shortage of cows in our country has led to the shortage of cattle resources and the high price of calves, which has restricted the further development of our beef cattle industry. In order to explore the factors that affect the decision-making behavior behind cow breeding and to find the right policy to mobilize the enthusiasm for cow breeding, based on the field survey of five provinces (cities and regions), including Inner Mongolia Autonomous Region and Ningxia Hui Autonomous Region, this paper conducts an empirical analysis through the Logit ISM model. The results show that market expectation is the surface factor that directly affects the decision-making behavior of cow breeding. The influencing factors of the middle layer are policy propaganda, policy subsidies, breeding years, and feeding methods. The deep root factors are the age of the breeder, the amount of loan, and whether to plant feed crops. Based on this, this paper proposes that we should actively promote the importance of cow breeding, strengthen policy support for cow breeding, formulate scientific and reasonable subsidy policies for cows, innovate financial support methods to solve the problem of fund shortage of farmers, and develop forage resources and reduce the breeding cost of cows. [ABSTRACT FROM AUTHOR]

As a raw material for clean energy supply for the new generation, the soybean is conducive to the realization of global energy transition and sustainable development in the context of "carbon neutrality". However, global warming has been affecting soybean yields in recent years. How to clarify the correlation between meteorological factors and soybean yields, so as to ensure the security of soybean growth and development and the stability of renewable energy development, is a key concern of the government and academia. Based on the data of temperature, precipitation, sunshine duration and active accumulated temperature during the soybean growing season in Hulunbuir, Inner Mongolia Autonomous Region from 1951 to 2019, and soybean yield data of the city from 1985 to 2019, this paper adopted statistical methods such as the Trend Analysis Method, the Rescaled Range Analysis Method and so on to analyze the trends of yield changes, characteristics of abrupt changes and periodic patterns of climate factors and soybean yields in Hulunbuir. A Pearson Correlation Analysis and a Grey Relation Analysis were used to explore the correlation between climatic factors and soybean yields, followed by a comprehensive impact model of the combined effect of temperature and precipitation on soybean yields established by the Method of Integral Regression. The results showed that temperature and active accumulated temperature are the dominant factors affecting soybean yields in Hulunbuir, while the decrease in precipitation is unfavorable to the improvement of soybean yields. Meanwhile, temperature and precipitation have different effects on the growth and development of the soybean at different stages. The conclusion of this paper is of great practical significance for Hulunbuir to promote the sustainable development of clean energy. [ABSTRACT FROM AUTHOR]

Simple Summary: In this paper, two new genera with two new species of Dermaptera are described from the Middle Jurassic Jiulongshan Formation of Daohugou, Inner Mongolia, China. The discovery of these two new species enriches the comparatively meagre fossil record of Dermaptera, particularly from the Middle Jurassic. The description of Applanatiforceps angustus is another brick laid in the foundation of protodiplatyid diversity, and the new genus Ekpagloderma gracilentum highlights the diversity of cercal forms among Aglyptodermatinae and the remarkable homogeneity of the general morphology of groups within this clade. Two new genera and species of Dermaptera are described from the Middle Jurassic Jiulongshan Formation of Daohugou, Inner Mongolia, China: Applanatiforceps angustus gen. et sp. nov. in the archidermapteran family Protodiplatyidae, and Ekpagloderma gracilentum gen et sp. nov. in the eodermapteran family Semenoviolidae. Applanatiforceps shares the typical characters of the extinct suborder Archidermaptera (e.g., pentamerous meta tarsi, filiform and multimerous cerci) and externalized ovipositor. The family identity of the Protodiplatyidae can be further distinguished by comparing this new genus with other genera of the Protodiplatyidae. As a result of its large compound eyes, tegmina without venation, body sparsely setose, legs rather short and slender, and shape of the veinless tegmina, Ekpagloderma is classified in the subfamily Aglyptodermatinae. Ekpagloderma not only has the typical features of the Aglyptodermatinae, but also exhibits a more primitive slender segmented cerci, which is different from all other genera of Eodermaptera. In fact, the diversity of Eodermaptera as known today indicates some of the challenges in understanding the suborder and whether or not it is monophyletic as historically construed, or if the separation of Turanodermaptera is justified. [ABSTRACT FROM AUTHOR]

Simple Summary: Osmylopsychopidae, an extinct family of Neuroptera, is closely related to the extant Psychopsidae. The sporadic records of this family and limited preservation of fossil specimens have hindered the understanding of the evolution of Osmylopsychopidae. In this paper, one new genus with four new species of Osmylopsychopidae are described from the Middle Jurassic Jiulongshan Formation of northeastern China. These newly discovered osmylopsychopids with a forewing length of ca. 10 mm (implying small body size), clearly distinguished from the traditional sense of Osmylopsychopidae, suggest that Osmylopsychopidae possibly underwent a significant diversification during the Mesozoic. One new genus with four new species sharing the similar character of a forewing length of ca. 10 mm, namely, Minipsychops spasulus gen. et sp. nov., Minipsychops polychotomus sp. nov., Minipsychops densus sp. nov., and Minipsychops unicus sp. nov., are described from the Middle Jurassic Jiulongshan Formation of Daohugou, Inner Mongolia in China. These new insects can be attributed to Osmylopsychopidae for their distinctive configuration of costal space and the venations of RP1 and Cu. Compared with the typically medium to large body sizes of known osmylopsychopids, these new Middle Jurassic taxa of a particularly miniaturized lineage not only enrich the species diversity of Osmylopsychopidae, but also enhance our understanding of the historical evolution of these poorly known lacewings. [ABSTRACT FROM AUTHOR]

Studying surface geochemical anomalies is important for detecting the presence of mineral deposits. However, distinguishing inconspicuous geochemical anomalies is a challenge for geochemists. This paper studies geochemical quantitative prediction for Pb–Zn metallic mineral deposits by identifying inconspicuous surface geochemical anomalies mainly associated with the Permian and Jurassic strata in the middle-southern Da Hinggan Mountains metallogenic belt. Some new methods are employed to highlight weak surface geochemical anomalies. The weak surface geochemical anomalies of Pb and Zn are effectively highlighted by the average contrast values of Pb–Zn–Ag–Cd. The similarity coefficient with the large typical discovered deposits is used to identify new Pb–Zn mineralized anomalies and delineate new prospecting target areas. The denudation degree of mineral deposit is determined by the ratio of (W × Sn)/(As × Sb). The analogy method and areal productivity method are employed for resource prediction. Thirty-six prediction areas with Pb–Zn resources of 307.73 million tons are delineated. Five prediction areas are verified, and some new mineral deposits are proven by drilling. The verification results show that the predicted resources are very reasonable and credible. This paper is a successful case of quantitative prediction assessment of mineral resource potential, which can be used as a reference for future prospecting activities. [ABSTRACT FROM AUTHOR]

In this paper, recent research on terrestrial ecosystem predictability using the conditional nonlinear optimal parameter perturbation (CNOP-P) method is summarized. The main findings include the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, the identification of key physical parameters that lead to large uncertainties in terrestrial ecosystem modeling and prediction, and the evaluation of the simulation ability and prediction skill of terrestrial ecosystems by reducing key physical parameter errors. The study areas included the Inner Mongolia region, north–south transect of eastern China, and Qinghai–Tibet Plateau region. The periods of the studies were from 1961 to 1970 for the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, and from 1951 to 2000 for the identification of the most sensitive combinations of physical parameters. Climatic Research Unit (CRU) data were employed. The numerical results indicate the important role of nonlinear changes in climate variability due to the occurrences of extreme events characterized by CNOP-P in the abrupt grassland ecosystem equilibrium state and formation of carbon sinks in China. Second, the most sensitive combinations of physical parameters to the uncertainties in simulations and predictions of terrestrial ecosystems identified by the CNOP-P method were more sensitive than those obtained by traditional methods (e.g., one-at-a-time (OAT) and stochastic methods). Furthermore, the improvement extent of the simulation ability and prediction skill of terrestrial ecosystems by reducing the errors of the sensitive physical parameter combinations identified by the CNOP-P method was higher than that by the traditional methods. [ABSTRACT FROM AUTHOR]

Unregulated livestock breeding and grazing can degrade grasslands and damage the ecological environment. The combination of remote sensing and artificial intelligence techniques is a more convenient and powerful means to acquire livestock information in a large area than traditional manual ground investigation. As a mainstream remote sensing platform, unmanned aerial vehicles (UAVs) can obtain high-resolution optical images to detect grazing livestock in grassland. However, grazing livestock objects in UAV images usually occupy very few pixels and tend to gather together, which makes them difficult to detect and count automatically. This paper proposes the GLDM (grazing livestock detection model), a lightweight and high-accuracy deep-learning model, for detecting grazing livestock in UAV images. The enhanced CSPDarknet (ECSP) and weighted aggregate feature re-extraction pyramid modules (WAFR) are constructed to improve the performance based on the YOLOX-nano network scheme. The dataset of different grazing livestock (12,901 instances) for deep learning was made from UAV images in the Hadatu Pasture of Hulunbuir, Inner Mongolia, China. The results show that the proposed method achieves a higher comprehensive detection precision than mainstream object detection models and has an advantage in model size. The m A P of the proposed method is 86.47%, with the model parameter 5.7 M. The average recall and average precision can be above 85% at the same time. The counting accuracy of grazing livestock in the testing dataset, when converted to a unified sheep unit, reached 99%. The scale applicability of the model is also discussed, and the GLDM could perform well with the image resolution varying from 2.5 to 10 cm. The proposed method, the GLDM, was better for detecting grassland grazing livestock in UAV images, combining remote sensing, AI, and grassland ecological applications with broad application prospects. [ABSTRACT FROM AUTHOR]

With the centralization of wind power development, power-prediction technology based on wind power clusters has become an important means to reduce the volatility of wind power, so a large-scale power-prediction method of wind power clusters is proposed considering the prediction stability. Firstly, the fluctuating features of wind farms are constructed by acquiring statistical features to further build a divided model of wind power clusters using fuzzy clustering algorithm. Then the spatiotemporal features of the data of wind power are obtained using a spatiotemporal attention network to train the prediction model of wind power clusters in a large scale. Finally, the stability of predictive performance of wind power is analyzed using the comprehensive index evaluation system. The results show that the RMSE of wind power prediction is lower than 0.079 at large-scale wind farms based on the prediction method of wind power proposed in this paper using experience based on the data of 159 wind farms in the Nei Monggol Autonomous Region in China and the extreme error is better than 25% for the total capacity of wind farms, which indicates high stability and accuracy. [ABSTRACT FROM AUTHOR]

Grasshoppers can greatly interfere with agriculture and husbandry, and they will breed and grow rapidly in suitable habitats. Therefore, it is necessary to extract the distribution of the grasshopper potential habitat (GPH), analyze the spatial-temporal characteristics of the GPH, and detect the different effects of key environmental factors in the meadow and typical steppe. To achieve the goal, this study took the two steppe types of Xilingol (the Inner Mongolia Autonomous Region of China) as the research object and coupled them with the MaxEnt and multisource remote sensing data to establish a model. First, the environmental factors, including meteorological, vegetation, topographic, and soil factors, that affect the developmental stages of grasshoppers were obtained. Secondly, the GPH associated with meadow and typical steppes from 2018 to 2022 were extracted based on the MaxEnt model. Then, the spatial-temporal characteristics of the GPHs were analyzed. Finally, the effects of the habitat factors in two steppe types were explored. The results demonstrated that the most suitable and moderately suitable areas were distributed mainly in the southern part of the meadow steppe and the eastern and southern parts of the typical steppe. Additionally, most areas in the town of Gaorihan, Honggeergaole, Jirengaole, as well as the border of Wulanhalage and Haoretugaole became more suitable for grasshoppers from 2018 to 2022. This paper also found that the soil temperature in the egg stage, the vegetation type, the soil type, and the precipitation amount in the nymph stage were significant factors both in the meadow and typical steppes. The slope and precipitation in the egg stage played more important roles in the typical steppe, whereas the aspect had a greater contribution to the meadow steppe. These findings can provide a methodical guide for grasshopper control and management and for further ensuring the security of agriculture and husbandry. [ABSTRACT FROM AUTHOR]

Groundwater is a primary freshwater resource for human consumption and an essential source for industry and agriculture. Therefore, understanding its spatial and temporal trends and drivers is crucial for governments to take appropriate measures to manage water resources. This paper uses Gravity Recovery and Climate Experiment (GRACE) satellite data and the Global Land Data Assimilation System (GLDAS) to derive groundwater storage anomalies (GWSAs) and to analyze the spatial and temporal trends of GWSA in different regions of China (Xinjiang, Tibet, Inner Mongolia, North China Plain, South China, and Northeast China). It used groundwater-level observation data to verify the accuracy of GWSA estimates and analyzed the drivers of regional GWSA changes. The results showed that: (1) GWSA in South China increased at a rate of 4.79 mm/a from 2003 to 2016, and GWSA in other regions in China showed a decreasing trend. Among them, the decline rates of GWSA in Xinjiang, Tibet, Inner Mongolia, North China Plain, and Northeast China were −6.24 mm/a, −3.33 mm/a, −3.17 mm/a, −7.35 mm/a, and −0.75 mm/a, respectively. (2) The accuracy of the annual-scale GWSA estimates was improved after deducting gravity losses due to raw coal quality, and the correlation coefficient between GWSA and groundwater levels monitored by observation wells increased. (3) In Xinjiang, the annual water consumed by raw coal mining, industrial, and agricultural activities had a greater impact on GWSA than rainfall and temperature, so these human activities might be the main drivers of the continued GWSA decline in Xinjiang. Water consumption by raw coal mining and industry might be the main drivers of the continued decline in GWSA in Inner Mongolia and the North China Plain. The increase in groundwater storage in South China was mainly due to the recharge of rainfall. [ABSTRACT FROM AUTHOR]

• This paper analyzes whether the financial support for grassland ecological protection and restoration has improved the vegetation coverage of grassland. • There is a nonlinear relationship between financial support for ecological restoration and grassland vegetation coverage. • Different fiscal expenditure structure has a heterogeneous response. • The degree of fiscal decentralization has a significant positive regulatory effect on the ecological benefits. Grassland ecological restoration is an important cornerstone to maintain the sustainable development of grassland ecosystem. One of the goals of financial support for grassland ecological protection and restoration is whether the ecological benefits of grassland are fully realized, and grassland vegetation coverage is the main index to measure the ecological benefits. This paper aims to analyze whether the financial support for grassland ecological protection and restoration has improved the vegetation coverage of grassland. and then verify whether there is room for improvement in the fiscal effect of grassland ecological protection and restoration? Based on the panel data of 54 animal husbandry and semi-agricultural and semi-animal husbandry counties in Inner Mongolia Autonomous Region of China, this paper adopts a bidirectional fixed effect model and cross-fixed effect model to introduce natural factors affecting grassland vegetation coverage into the model and systematically examines the financial effects of ecological benefits of financial support for grassland ecological protection and restoration. The main findings are as follows: (1) there is a nonlinear relationship between financial support for grassland ecological protection and restoration and grassland vegetation coverage when natural factors are taken into account in the model. (2) different fiscal expenditure structure has a heterogeneous response to the impact of grassland ecological protection and restoration on ecological benefits. (3) the degree of fiscal decentralization and the relative performance of the government have a significant positive moderating effect on the ecological benefits of fiscal support for grassland ecological protection and restoration. [ABSTRACT FROM AUTHOR]

Background: Desertification is one of the main obstacles to global sustainable development. Monitoring, evaluating and mastering its driving factors are very important for the prevention and control of desertification. As one of the largest deserts in China, the development of desertification in Otindag Sandy Land (OSL) resulted in the reduction in land productivity and serious ecological/environmental consequences. Although many ecological restoration projects have been carried out, the vegetation restoration of OSL and the impact mechanism of climate and human activities on desertification remain unclear. Methods: Taking OSL as the research area, this paper constructs the desertification index by using the remote sensing images and meteorological and socio-economic data, between 1986 and 2016, and analyzes the spatio-temporal evolution process and driving factors of desertification by using trend analysis and spearman rank correlation. Results: The results showed that: (1) Desertification in the OSL has fluctuated greatly during the past 30 years. Desertification recovered between 1986 and 1990, expanded and increased between 1990 and 2000, reduced between 2000 and 2004, developed rapidly between 2004 and 2007, and recovered again between 2007 and 2016; (2) The desertification of OSL is dominated by a non-significant change trend, accounting for 73.27%. In the significant change trend, the area of desertification rising trend is 20.32%, which is mainly located in the north and east, and the area of declining trend is 6.41%, which is mainly located in the southwest; (3) Desertification is the result of the superposition of climate and human activities. Climate change is the main influencing factor, followed by human activities, and the superposition effects of the two are spatio-temporal differences. Conclusions: These results shed light on the development of desertification in OSL and the relative importance and complex interrelationship between human activities and climate in regulating the process of desertification. Based on this, we suggest continuing to implement the ecological restoration policy and avoid the destruction of vegetation by large-scale animal husbandry in order to improve the situation of desertification. [ABSTRACT FROM AUTHOR]

In this paper, field spectroradiometer and aboveground biomass (AGB) data were acquired at the harvest stage at two sites in semiarid grasslands in Inner Mongolia, China. Four forms of commonly used vegetation indices (VIs) using all possible combinations of narrow-band first derivative (FDR) and raw reflectance (RR) were calculated, and the best FDR-VIs and RR-VIs were chosen by a linear regression analysis against AGB. The stepwise multiple linear regression (SMLR) models using the optimal FDR-VIs, RR-VIs, and both FDR-VIs and RR-VIs as input variables were developed for estimating the AGB. Results demonstrated that the estimation performance using the best FDR-VIs were comparable with the best RR-VIs, while the accuracy has been further improved by combining the best FDR-VIs and RR-VIs (maximum decrease in RMSE of 44% and minimum RMAE of 4.7%). The approach was found to be an important step for more accurate and effective grassland AGB estimation. [ABSTRACT FROM AUTHOR]

Aeromagnetic gradient data have higher horizontal resolution on shallow sources, a magnetic anomaly that can better reflect the features of deeper sources. Therefore, we used a joint survey of aeromagnetic and gradient data to obtain the distribution of sources with different depths. In this paper, we propose an intersection constraint weighting (ICW) method based on aeromagnetic and gradient data for original and gradient anomalies with inconsistent high-low variation characteristics. The ICW method can effectively improve the resolution of inversion results and can more accurately obtain the distribution of magnetic bodies via cross-gradient by gradually adding a gradient component and applying a normalized property weighting function. Our theoretical model tests indicate that the distribution of the recovered magnetic susceptibility model of the ICW method was similar to that of the true model. In addition, the anomaly containing noise with different signal-to-noise ratios verified that the ICW method had a stronger anti-noise ability than other methods. We also inverted real data in the Zhurihe area of the Inner Mongolia Autonomous Region in northern China. The inversion result showed that the main trend of high magnetic bodies was in the northeast direction, that the shallowest depth of high magnetic bodies was 100 m, and that the greatest depth was 960 m. [ABSTRACT FROM AUTHOR]

Simple Summary: Grasshoppers are among the most dangerous agricultural pests of China. However, the monitoring, prediction and control of grasshoppers are complex and difficult. Therefore, it is crucial to detect the key factors affecting the spatial distribution of grasshopper occurrence, understand the role of the environmental factors in grasshopper occurrence, and study whether different laws exist between different grass types. Here we conduct a species–environmental matching model integrated by Maxent model and remote sensing data to identify the spatial distribution of grasshopper occurrence in Inner Mongolia of China, analyze the related environmental variables and detect the most relevant environmental factors for grasshopper occurrence both in typical steppe and meadow steppe. Grasshoppers mainly threaten natural grassland vegetation and crops. Therefore, it is of great significance to understand the relationship between environmental factors and grasshopper occurrence. This paper studies the spatial distribution and key factors of grasshopper occurrence in two grass types by integrating a machine learning model (Maxent) and remote sensing data within the major grasshopper occurrence areas of Inner Mongolia, China. The modelling results demonstrate that the typical steppe has larger suitable area and more proportion for grasshopper living than meadow steppe. The soil type, above biomass, altitude and temperature mainly determine the grasshopper occurrence in typical steppe and meadow steppe. However, the contribution of these factors in the two grass types is significantly different. In addition, related vegetation and meteorological factors affect the different growing stages of grasshoppers between the two grass types. This study clearly defines the different effects of key environmental factors (meteorology, vegetation, soil and topography) for grasshopper occurrence in typical steppe and meadow steppe. It also provides a methodology to guide early warning and precautions for grasshopper pest prevention. The findings of this study will be helpful for future management measures, to ensure grass ecological environment security and the sustainable development of grassland. [ABSTRACT FROM AUTHOR]

Plant carbon (C) input via litter decomposition is essential for forming soil organic C (SOC). Previous studies have investigated the fate of litter C through one-time litter addition, while litter input could be recurrent, e.g., gradual litter input from above-ground plant material in diverse ecosystems. This paper investigates how litter input's frequency (single vs. repeated) and amount (low vs. high) affect the SOC formation and the associated microbial community composition and activity in a controlled microcosm experiment. After incubating the 13C-labeled litter (Stipa krilovii) for 80 days with the fresh field soil collected from a semi-arid steppe in Inner Mongolia, China, we measured newly formed SOC, microbial biomass C (MBC), and microbial phospholipid fatty acid (PLFA) indicated by 13C-labeling. The repeated litter addition resulted in 19.92% greater and 12.45% more efficient SOC formation than the single addition. Repeated litter addition also increased C use efficiency (CUE, + 76.71%), indicating more substrate C allocated for microbial growth than respiration. It also enhanced the fungi to bacteria ratio by 47.40% (based on 13C-PLFA) and maintained relatively stable microbial assimilation of litter C (based on 13C-MBC). These findings were consistent regardless of litter amounts. Our results indicate that the uninterrupted litter input to the soil in natural ecosystems benefits SOC formation and highlights soil fungi's critical role in promoting SOC formation. This study suggests that incorporating plant C input frequency into SOC dynamic models may improve the predictions of C cycling. [ABSTRACT FROM AUTHOR]

Distribution centers are quite important for logistics. In order to save costs, reduce energy consumption and deal with increasingly uncertain demand, it is necessary for distribution centers to select the location strategically. In this paper, a two-stage model based on an improved clustering algorithm and the center-of-gravity method is proposed to deal with the multi-facility location problem arising from a real-world case. First, a distance function used in clustering is redefined to include both the spatial indicator and the socio-economic indicator. Then, an improved clustering algorithm is used to determine the optimal number of distribution centers needed and the coverage of each center. Third, the center-of-gravity method is used to determine the final location of each center. Finally, the improved method is compared with the traditional clustering method by testing data from 12 cities in Inner Mongolia Autonomous Region in China. The comparison result proves the proposed method's effectiveness. [ABSTRACT FROM AUTHOR]

Coal is one of the fundamental fossil energy supporting the world's economy. The synergistic development between efficient coal mining and ecological environment protection is the inevitable requirement for the preservation of global harmony. As the world's largest coal producer, China has conducted a strategic shift from east to west in terms of the exploitation of its energy resources, posing a serious threat to the fragile ecological environment of the western region. In particular, the surface subsidence caused by coal mining is the root of the ecological deteriotation and the destruction of ground structures. However, it is difficult to reveal the law of large-scale surface subsidence in western mining areas merely by conventional measurement methods such as leveling, on account of the high intensity of coal seam mining, the weakness of the lithology of overlying rock and the large thickness of wind-blown sand strata. In view of this, small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology was used in this study to obtain the time series of surface vertical displacement during the whole mining process of the 2401 working face in the Yingpanhao coal mine, Inner Mongolia. Based on the deformation data, the dynamic evolution characteristics of surface subsidence under high intensity mining in the western mining area were analyzed exhaustively. It was found that the surface subsidence is characterized by an extensive coverage range (48.52 km2) with minimal ground settlement (250 mm) in the study area. Meanwhile, the boundary shape of the subsidence basin followed a "circular-parallelogram-trapezoid" changeable process and the coverage area of the basin experienced three stages: a linear increasing period, a temporary stagnation period, and a re-expansion period. Furthermore, there existed an abnormal uplift phenomenon on the east side of the open-off cut in the 2401 working face. Combined with the structure of overlying strata, this paper carried out a preliminary analysis on the reasons of the abovementioned phenomenon. The research results are of vital realistic significance for ground buildings and ecological environmental protection in the aeolian sand mining area in Western China. [ABSTRACT FROM AUTHOR]

This paper presents scientific analyses of the wall paintings in Wudang Lamasery, which is located in the Baotou area of Inner Mongolia, China. Raman spectroscopy was used to analyze the pigments of the mural of the Lam rim Hall. The results show that vermilion, red lead, chrome yellow, emerald green and synthetic ultramarine were used. The existence of synthetic pigments provides a clue for the date the mural was painted. [ABSTRACT FROM AUTHOR]

Coal bump, a common dynamic disaster in mining of deep coal resources, its assessing and predicting is an important component in safety management. This paper presents a model to assess and predict coal bump risk based on multiparameter indices. A new energy accumulation index S was proposed by considering acoustic emission and electromagnetic emission signal characteristics in mine shocks. Combined with indices E (energy of microseisms) and N (frequency of microseisms) of microseismic monitoring, a static and dynamic coal bump risk assessment and prediction model was established. We studied coal bump events that occurred during extraction in 311305 working face of Bayangale coal mine in Inner Mongolia, China. We obtained the acoustic emission and electromagnetic emission signal distribution and change law, using principal component analysis method and density ellipse to establish the index S. A typical precursory of coal bumps is that AE and EME strength has obvious fluctuation period of 3-4 days, index S showing an obvious decreasing trend, while the time-series curve of the microseismic energy is relatively stable, and the vibration frequency curve has a significant upward trend. After predict the potential coal bump risk and its area of occurrence, large diameter drilling (Φ150 mm) on-site was used to relief pressure concertation in coal seam and roof. The results demonstrate that this model based on multiparameter indices is capable of quantitatively prewarning rock burst risk. [ABSTRACT FROM AUTHOR]

[Display omitted] • Predict the evolution of land use and landscape ecological risk. • Couple landscape ecological risk and ecological security network. • Construct an ecological security network for multiple future development scenarios. • Explore sustainable development scenario for Northeast China. • Make recommendations for ecological security network optimization. The expansion of human activities has significantly increased ecological risks, which threaten the security of ecosystems. This paper takes Northeast China, a national typical ecological barrier region, as a case study to explore the evolution of the ecological environment under various future development scenarios. Considering the complexity of ecological assessments, a comprehensive approach integrating various methods is employed. This includes the Patch-based Land Use Simulation (PLUS) model, Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, a landscape ecological risk assessment index system, the Space Minimum Cumulative Resistance (MCR) model, among others. These methods are used to dynamically assess changes in land use, landscape ecological risk (LER), and the layout of ecological networks. An integrated framework is proposed for identifying, constructing, and optimizing the ecological security network (ESN). The results show that the LER in Northeast China presents a "high in the middle, low around" distribution characteristic. High risk areas are mainly distributed in water bodies and construction lands with high landscape fragmentation and isolation, while low risk areas are primarily in the Northeast forest belt and Inner Mongolia grassland areas with lower landscape vulnerability and separation. From 2000 to 2020, the LER in the Northeast China has increased, primarily manifested in the Greater and Lesser Khingan Range areas in the northern part of the study region. Forecast results indicate significant differences in the evolution of LERs and the layout of the ESN under different socio-economic development scenarios. Under the ecological protection (EP) scenario, the average LER in Northeast China is 0.2215. The area of ecological source lands is 302,405.56 km2, the length of ecological corridors is 179,024.71 km, with 339 ecological nodes and 410 ecological breakpoints identified. Compared with the natural development (ND) and urban construction (UC) scenarios, the EP scenario in Northeast China shows the lowest LER and the most ideal layout of the ESN. This study provides a reference for future land resource optimization and ecological restoration in Northeast China. [ABSTRACT FROM AUTHOR]

Converting wind energy into ammonia (WtA) has been recognized as a promising pathway to produce “green” ammonia compared with traditional coal-based technologies. As the key part of WtA, Power-to-Ammonia (PtA) has great potential to facilitate the usage of wind generation. This paper proposes a co-planning approach for regional wind resources-based ammonia industry and the electric network (EN). To this end, PtA is first modeled as a flexible power load of power systems with spatial and temporal constraints on hydrogen supply chains (HSC). Then a novel co-planning model of WtA and EN is established to optimize the WtA configuration and the EN expansion. An alternating direction method of multipliers (ADMM) based algorithm is introduced to effectively solve this model. Real data of Inner Mongolia Province in China is adopted to verify the effectiveness and significance of the proposed approach. It is shown that the siting and operation flexibility of PtA with HSC can reduce the expansion burden of EN. The co-planning of WtA and EN can significantly enhance wind power utilization and reduce total investment costs. Furthermore, feasibility analysis on WtA in comparison with coal-to-ammonia (CtA) and ultra-high voltage transmission (UHV) provides helpful guidelines for the realization of WtA. [ABSTRACT FROM AUTHOR]

Whether there is a transition underway, from a warm-dry climate to a warm-wet climate in Northwest China remains a controversial and scientifically significant issue. Will this trend continue in the future? Another hot issue is whether the climate in Northwest China will continue to be warm and humid over the next few decades. In this paper, eight CMIP6 models were employed to investigate temperature and precipitation changes under five principal Shared Socioeconomic Pathway (SSP) scenarios (from 2015 to 2099) to project the future warming and humidification in Northwest China using the SPEI (standardized precipitation evapotranspiration index) method. The results revealed that (1) the simulated temperature and precipitation of eight CMIP6 models were consistent with that of observed data during 1961-2014, which showed an increase of approximately 28.2 mm, while simulated data revealed an increase of approximately 9.4 mm. The annual precipitation gradually decreased from Eastern Inner Mongolia and the Southern Northwest Mongolia region (.700 mm) to the Central Northwest Mongolia region (,100 mm) from 1961 to 2014; (2) the MME significantly overestimated the temperature and slightly underestimated the precipitation in Northwest Mongolia. The temperature difference between the simulated and observed data was approximately 0.4 °C. The observed data showed an increase of approximately 0.9 °C from 1961 to 2014, whereas the simulated data revealed an increase of approximately 0.7 °C; (3) in the SSP5-8.5 scenario, the percentage of precipitation anomalies at 1.5, 2, 3, and 4 °C were 166.64, 190.58, 226.44, and 274.56%, respectively; thus, alleviating the drought situation while facilitating the warm-dry to warm-wet climate transition; (4) the water balance between rising temperatures and increased evapotranspiration resulting from increased precipitation suggested that not all sites will be wet in the future. There was still a drying trend in some areas, where drought was more severe under the high emissions scenario than the low emissions scenario. [ABSTRACT FROM AUTHOR]

Tamusu mudstone, located in Inner Mongolia, is being recognized to be the potential host formation in deep HLW disposal across China. This paper describes diverse laboratory experiments performed using the fractured Tamusu mudstone, with concern to the study of the combined mechanical and thermal effects on its hydraulic properties, as well as its self-sealing effect. A single rough fracture is generated down the sample diameter direction before the sample's installation. Considering a heating-cooling cycle, the evolution of the samples' hydraulic properties under different stress conditions has been monitored. The hydraulic conductivity is proved to be not only related to the temperature-induced water viscosity and density variation but also the change of stress state. At the same thermal conditions, the increase of confining pressure (or deviatoric stress) may weaken the flow capacity of the fractures and thus reduce the permeability. The non-coincidence for the curve of permeability versus temperature at the heating and cooling stage indicates that the permeability alterations in the fractures are irreversible. Fracture zone changes were observed by X-ray computer tomography (CT) before and after the tests. The self-sealing behavior, which may be beneficial from high confining pressure, was detected for fractured Tamusu mudstone. Morphologies of fracture surfaces were detected by the 3D scanning technique, which shows that the fracture surface roughness, due to the alteration of asperity contacts and void spaces under high stress, may take an important part of the responsibility to the change of permeability. [ABSTRACT FROM AUTHOR]

Cone‐producing gymnosperms are important elements of the Mesozoic floras. Studying their cone organizations can potentially help us understand the evolutionary trends of seed plants through time and the origin of angiosperms. In this paper, we present a new and an undetermined species of Ixostrobus Raciborski, a fossil genus representing male cones of the Czekanowskiales from the Middle Jurassic Daohugou locality in Inner Mongolia, China. The holotype specimen of the new species was studied using the neutron tomography (NT) technique. The cone shows higher neutron attenuation than the surrounding matrix. To detect the different organic compounds, a volume rendering of tomographic reconstruction with false colour spectrum of relative neutron attenuation is presented. The highest concentration of organic material is in the axis and some parts of the sacs, the rest of the cone has lower concentration, and the surrounding matrix has the lowest concentration. It seems that the remnant organic materials are regularly differentiated in different parts of the cone probably because of the preservation and different taphonomic process of different type of cells. In addition to revealing more detailed morphological features of the cone by NT reconstruction, the application of NT is potentially important for detecting remnant organic materials preserved in fossil plants. [ABSTRACT FROM AUTHOR]

Integrating renewable electricity and green hydrogen with CO 2 utilization to produce chemicals has drawn much attention due to its low carbon emission characteristics. The goal of this paper is to investigate the environmental sustainability of producing a steady hourly output of methanol by utilizing electricity and hydrogen produced via renewable energy resources, and CO 2 captured from a coal-fired power plant located in Inner Mongolia, China. Six renewable energy-based electricity and hydrogen systems are considered based on photovoltaic, wind turbines and combinations thereof, including battery and grid technologies. The environmental impact indicators of these system are compared comprehensively through life cycle assessment approach, including not only global warming potential but also fossil fuel depletion, water & soil & air pollution indices and human health index. The results indicate that the most environmentally friendly system is Case B2 which uses photovoltaic to produce hydrogen and electricity, with battery for energy storage and excess electricity sold back to grid. It shows apparently the best sustainability performance in global warming potential, which is 0.105 kg CO 2 -eq per kg methanol. In general, the proposed six systems outperform conventional methanol production systems in terms of global warming potential and abiotic depletion potential, with reductions ranging from 74% to 92% and 51.1%–73.8% respectively, but they have high levels in other environmental sustainability indicators such as human toxicity, eutrophication potential, and ozone layer depletion potential due to the photovoltaic electricity generation unit. The findings highlight that it is essential to consider a comprehensive range of environmental sustainability indicators when developing renewable energy-based methanol systems on a large scale. [Display omitted] • Component capacity of the integrated system is optimized. • Comprehensive life cycle environmental impact assessment is conducted. • GWP of proposed route is 74 %–92% lower than fossil-based route. • PV manufacturing is critical in most environmental impact indicators. • HTP, ODP and EP indicators of proposed route are much high. [ABSTRACT FROM AUTHOR]

The evaluation of regional water resource carrying capacity has been repeatedly conducted to provide a scientific basis for the local water resource management and the sustainable development, in particular in the water-limited regions. However, the definition of regional water resource carrying capacity and its evaluation method are still arguable. Through a case study of Inner Mongolia, located in the arid and semi-arid northern China, this paper developed an improved method to calculate regional water resource carrying capacity by the combination of the water supply-demand analysis and the S-shaped curve threshold analysis. The spatial and temporal patterns of the regional water resource carrying capacity in Inner Mongolia during 2000–2019 was evaluated at three scales, namely the province scale, the basin scale and the city scale. The results showed that the average regional water resource carrying capacity of the whole province was 0.25 (the full mark is 1.00); at the basin scale, the Yellow River Basin had the lowest regional water resource carrying capacity (0.17) among all the basins, showing that the utilization of the water resources was unreasonable; at the city scale, the average regional water resource carrying capacities in Hulunbuir and Xilingol were both over 0.25, while those in Alxa, BayanNur and Wuhai were below 0.1; Hulunbuir had 25.48 billion m3 water surplus, while BayanNur suffered from an average water deficit of 4.51 billion m3 from 2000 to 2019. This paper has provided a reasonable way to measure the regional water resource carrying capacity using an improved method by incorporating S-shaped curve threshold analysis, which may have a wider application for the clustering and optimization of regional water management. In addition, the spatial and temporal patterns of regional water carrying capacity are beneficial for policymakers in the implementation of the effective water usage. • Regional water resource carrying capacity is evaluated by water supply-demand analysis and temporal threshold analysis. • The evaluation method is improved by considering temporal threshold at different regional scales. • "S"-shaped logistic curves are used to simulate the temporal pattern of water resource carrying capacity. • Spatial and temporal water resource carrying capacity analysis benefits policymakers. [ABSTRACT FROM AUTHOR]

The development of coal resources is necessary, but it has a huge negative impact on land, ecology, and the environment. With the increasing awareness of environmental protection and the requirements of related regulations, the design and practice of reclamation projects run through the mining life cycle and continue for a long time after the coal production. High-precision monitoring of mining disturbance and reclamation, quantifying the degree and time of vegetation disturbance and restoration, is of great significance to minimize the environmental effect of mining. Remote sensing, widely used as efficient monitoring tool, but there is not enough research on disturbance and reclamation monitoring taking into account large-scale areas and high temporal and spatial accuracy. Especially when mining sites remain unknown, how to distinguish the disturbance of coal mining and other human activities affecting the surface land cover has become a challenge. Therefore, this paper proposed a method to reconstruct the time series of mining disturbance and reclamation in a large area by using the POI (point of interest) and Landsat time series images using multiple buffer analysis methods. The process includes: (1) Retrieval of POI in the study area based on the public mining list using Python crawler, and buffering 100 km for preliminary extraction of potential mining areas; (2) Using spectral index mask and random forest algorithm to accurately extract the exposed coal on the Google Earth Engine (GEE) platform; (3) Buffering 10 km to identify the occurrence of disturbance and reclamation, using pixel-based temporal trajectory identification of LandTrendr algorithm under GEE. The method successful detect the change points of surface coal mining disturbance and reclamation in eastern Inner Mongolia of China. The results show that: (1) The method can effectively identify the extent of surface coal mining disturbance and reclamation, and the overall extraction accuracy is 81%. (2) Surface coal mining disturbance in eastern Inner Mongolia was concentrated in 2006–2011. By 2020, the total disturbed area is 627.8 km2, with an average annual disturbance of 18.5 km2, and the annual maximum disturbance to the ground reached 64.6 km2 in 2008. With the total reclaimed area being 236.3 km2, the reclamation rate is about 37.6%. This study provides a systematic solution and process for monitoring the disturbance and reclamation of surface coal mining in a large range with little known about the mines' location. It can effectively identify the mining disturbance and reclamation process which can also be extended to other areas, providing a quantitative assessment of mining disturbance and reclamation, which can support further ecological restoration decision-making. [Display omitted] • A remote sensing procedure of surface coal mine classification, disturbance and reclamation monitoring is developed. • Landsat, random forest, web scraping, and Google Earth Engine has been used to detect 73 surface coal mining sites. • 0.94% of the total study area has been disturbed by surface mining. • The developed procedure is able to reveal the surface coal mine reclamation pattern. [ABSTRACT FROM AUTHOR]

• DPSIRM model was used to evaluate the ecological security of Xilingol grassland. • Remote sensing, meteorology, socio-economic and survey data are used in this paper. • We use grid GIS method to obtain more accurate evaluation results. • We analyzed the spatial-temporal evolution characteristics of ecological security. • Changes in the center of gravity in different security levels are also explored. The quantitative evaluation of the ecological security can reflect the changes in the quality of ecological environment and provide a scientific basis for the formulation of land-use policy and for the construction of the ecological environment. In this study, we selected Xilingol League in Inner Mongolia, China, as the research area, and established the driving force-pressure-state-impact-response-management (DPSIRM) model to evaluate grassland ecological security. The results were as follows: (1) During 2005–2015, the overall trend of ecological security level in the study area increased, with the western region being relatively ecologically insecure and the eastern region being more secure. (2) The spatial distribution trend of ecological security level from west to east was " very serious alerts " → " serious alerts " → " moderate alerts " → " light alerts "→ " no alert ". (3) The " very serious alerts " and " serious alerts " are mainly concentrated in Sonid Left Banner and Sonid Right Banner, but from the perspective of spatial migration of ecological security, unsafe and less safe tend to shift to the northeast. This study provides a new idea for grassland ecological security evaluation research, has important practical significance for understanding the ecological security level of Xilingol grassland area, and will guide the reasonable development and utilization of Xilingol grassland. [ABSTRACT FROM AUTHOR]

Permafrost in Northeastern China has significantly degraded due to global warming, deforestation and urbanization in the last few decades. The frost heave and thaw subsidence induced by freeze-thaw cycles of deep seasonal frozen ground have caused serious damage to infrastructures. The Shiwei-Labudalin (Shi-La) Highway is an important infrastructure connecting Shiwei town and Labudalin town of Argun city, Inner Mongolia, which passes through the areas covered by deep seasonal frozen ground or isolated patchy permafrost. In this paper, we mapped the long-term linear displacement trend and amplitude of seasonal displacement of the Shi-La Highway and its nearby areas, with an ascending Sentinel-1 dataset acquired from September 2016 to April 2020. Seasonal displacement amplitudes of 5–20 mm are widely detected in low-lying areas (e.g., the basin of the Gen and Derbugan rivers). The time lags between frozen ground displacement and temperature variations generally range from 10 to 80 days while larger values of 100–120 days caused by soil moisture or land cover difference are also observed. Linear creep displacement rates greater than −20 mm/yr are detected on mountainous slopes and sections of the Shi-La Highway in the line-of-sight (LOS) direction. Our results provide a method for evaluating highway stability in cold regions, which is helpful to highway route selection and design in Northeastern China. • Map displacement of frozen ground in northern Inner Mongolia using InSAR. • Freeze-thaw related and creep movement were identified on Shi-La highway. • Time lags between displacement and temperature are 10–120 days in flat areas. [ABSTRACT FROM AUTHOR]

The paper investigates how climate changes and socioeconomic transformations affected grassland productivity from 2000 to 2017 in counties in Inner Mongolia of China. The grassland productivity and climatic change variables included 162 readings (9 periods in the growing season × 18 years), while ten socioeconomic variables contained 18 yearly readings. The mismatch between the environmental observations and socioeconomic data compounds quantitative analysis of causal relations between them. We applied several time-series processing methods to generate five datasets. We fit them with conventional, dependent-lagged, and dynamic-lagged panel regression models to investigate which combinations augment causal relationships between grassland productivity, climate, and socioeconomic changes. The results confirmed that the conventional model with the original data failed to reveal causal relationships between these factors. The panel regression models with the original data tended to intensify the causal effects of climate factors on grassland productivity. The models with the transformed datasets disclosed more socioeconomic variables showing causal relationships with grassland productivity. The dependent-lagged model with the empirical mode decomposition transformed data produced the highest R-squared value and lowest prediction error. GDP, state fixed asset investment, highway construction, grain plantation, and livestock density were primary factors affecting grassland productivity. In brief, the integration of time-series data mining and time-lagged panel analysis effectively unveiled the causes of grassland deterioration under climate and socioeconomic changes. [Display omitted] • Augment causality hidden in env-socio-economic systems with data assimilation. • Assimilate temporal environmental and socioeconomic data into compatible time-series. • Experiment with four groups of computational data mining methods on data assimilation. • Compare combinations of data assimilation methods and lagged panel regression models. [ABSTRACT FROM AUTHOR]

• Based on cascade framework, the ECC index system is built. • ECC is evaluated at different scales in Xilingol League. • To find the driving factors of ECC at different scales in Xilingol League. • Explore sustainable development path of coal power exploitation regions. Coal is a vital resource in China. With limited coal and the deteriorating eco-environment, it is consensus to take the sustainable development road in coal power exploitation regions. Taking Xilingol League, Inner Mongolia as an example, based on the cascade framework constituted by the "Driver - Pressure - State - Impact - Response" (DPSIR) model, this paper aimed to analyze the ecological carrying capacity at the league (city) scale and at the banner (county) scale contrastively. It found that the overall change trend was a wide "V" type at the league (city) scale. Moreover, the ecological carrying capacity at the banner (county) scale showed that the north was superior to the central and south in 2005, 2011 and 2018. The principal component analysis (PCA) approach had been adopted to analyze the driving factors. Driving factors were economic development and coal and electricity development at the league (city) scale, as well as resource supply and urbanization development at the banner (county) scale. At the league (city) scale, the economic benefits of industrial development had improved people's living standards, and part of the funds could be used in the investment in ecological restoration, thus improving the ecological carrying capacity; at the banner (county) scale, most counties were still coal-dependent areas, and the number of resources had a more significant impact on the ecological carrying capacity. This study provided ideas for sustainable development in energy exploitation regions at different scales. [ABSTRACT FROM AUTHOR]

[Display omitted] • Field-portable exploration methods were systematically described in shallow overburden areas for vein-type fluorite deposits. • The advantages and disadvantages of field-portable fluorite exploration methods have been analyzed. • The Effectiveness of RS + VLF-EM + PRXF for exploration has been validated by trenching and drilling. Fluorite deposits are widespread throughout eastern China and commonly occur in vein systems. These vein-type fluorite deposits are the primary source of fluorine worldwide and were predominantly formed during the Mesozoic or Cenozoic periods. In the absence of ore outcrops, fluorite exploration is necessarily concentrated within the shallow overburden area. The Wuliji'Oboo fluorite deposit is an example of a medium–low temperature vein-type subsurface orebody in eastern Inner Mongolia. Five portable technology methods have been implemented within the study area, including multispectral remote sensing (RS) technology, very low-frequency electromagnetic measurement (VLF-EM), portable X-ray fluorescence analyses (PXRF), portable gamma-ray spectroscopy, and partial extraction geochemistry. This paper describes the application principles, influencing factors, and technical solutions for each method. By investigating various examples, the applications of portable technology methods and their associated limitations were evaluated. Combining geological research with multi-spectral RS techniques is essential for optimum fluorite ore body prediction, thus narrowing prospecting targets. First, the target area was scanned using VLF-EM to identify the distribution of potential anomalies. Second, PXRF was used to distinguish the mineralised anomaly. Finally, trenching and drilling were performed to verify the effectiveness of the combination of methods. This study establishes a geology-geophysics-geochemistry-remote sensing integrated exploration model that may provide theoretical and technical support for the prediction of fluorite ore bodies in large Quaternary shallow overburden areas. [ABSTRACT FROM AUTHOR]

• Dictionary learning is used to model gold prospectivity for gold exploration targeting. • The case study shows that the dictionary learning model is no inferior to the logistic regression model and superior to the one-class SVM model. Machine learning and deep learning anomaly detectors have been successfully used to map mineral prospectivity. However, the establishment of machine learning or deep learning anomaly detection models for mineral prospectivity mapping often requires the determination of a set of initialization parameters in the absence of ground truth data. Improper initialization parameters will degrade the performance of these mineral prospectivity mapping models. Different from most machine learning and deep learning algorithms, dictionary learning is a "white-box" algorithm involving only linear transformations, and building a dictionary learning model requires only an empirical definition of the total number of atoms. Therefore, in this paper, two dictionary learning anomaly detectors were established for mineral prospectivity modeling based on the least angle regression-Lasso (LARS-Lasso) algorithm and the iterative shrinkage-thresholding algorithm (ISTA). The following five-step procedure was proposed for mineral prospectivity modeling using the dictionary learning techniques: (a) an overcomplete dictionary is constructed based on the input data; (b) each data point is transformed into sparse coefficients according to the overcomplete dictionary; (c) the sparse representation of each data point is calculated based on the overcomplete dictionary and the sparse coefficients; and (d) the Euclidean norm of the difference between each data point and its sparse representation is calculated and used as the mineral potential of the data point. The dictionary learning models were established to model gold prospectivity in the Jinchanggouliang district, Inner Mongolia, China, and compared with the logistic regression model and one-class support vector machine model in gold exploration targeting. The result shows that (a) the performances of the dictionary learning models are no less than that of the logistic regression (LGR) model and better than that of the one-class support vector machine (OCSVM) model, and (b) the gold prospective areas differentiated by the established models are strongly consistent with geological and metallogenic characteristics in the study area. Therefore, the dictionary learning algorithms are high-performance mineral prospectivity modeling techniques. It is worth to further test the effectiveness of the dictionary learning algorithms for different types of mineral deposits in different areas in mineral exploration targeting. [ABSTRACT FROM AUTHOR]