Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have dev...Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.展开更多
Since China announced its goal of becoming carbon-neutral by 2060, carbon neutrality has become a major target in the development of China's urban agglomerations. This study applied the Future Land Use Simulation(...Since China announced its goal of becoming carbon-neutral by 2060, carbon neutrality has become a major target in the development of China's urban agglomerations. This study applied the Future Land Use Simulation(FLUS) model to predict the land use pattern of the ecological space of the Beibu Gulf urban agglomeration, in 2060 under ecological priority, agricultural priority and urbanized priority scenarios. The Integrated Valuation of Ecosystem Services and Trade-offs(In VEST) model was employed to analyse the spatial changes in ecological space carbon storage in each scenario from 2020 to 2060. Then, this study used a Geographically Weighted Regression(GWR) model to determine the main driving factors that influence the changes in land carbon sinking capacity. The results of the study can be summarised as follows: firstly, the agricultural and ecological priority scenarios will achieve balanced urban expansion and environmental protection of resources in an ecological space. The urbanized priority scenario will reduce the carbon sinking capacity. Among the simulation scenarios for 2060, carbon storage in the urbanized priority scenario will decrease by 112.26 × 10^(6) t compared with that for 2020 and the average carbon density will decrease by 0.96 kg/m^(2) compared with that for 2020. Carbon storage in the agricultural priority scenario will increase by 84.11 × 10^(6) t, and the average carbon density will decrease by 0.72 kg/m^(2). Carbon storage in the ecological priority scenario will increase by 3.03 × 10^(6) t, and the average carbon density will increase by 0.03 kg/m^(2). Under the premise that the population of the town will increases continuously, the ecological priority development approach may be a wise choice.Secondly, slope, distance to river and elevation are the most important factors that influence the carbon sink pattern of the ecological space in the Beibu Gulf urban agglomeration, followed by GDP, population density, slope direction and distance to traffic infrastructure.At the same time, urban space expansion is the main cause of the changes of this natural factors. Thirdly, the decreasing trend of ecological space is difficult to reverse, so reasonable land use policy to curb the spatial expansion of cities need to be made.展开更多
The abandonment of cultivated land in southern China was gradually obvious.This research aims to provide a reference for solving the abandonment of cultivated land in hilly regions and promote rural development in Chi...The abandonment of cultivated land in southern China was gradually obvious.This research aims to provide a reference for solving the abandonment of cultivated land in hilly regions and promote rural development in China.We examined Longnan county located in the hilly regions of southern China as an example,where abandoned cultivated land is very common.We analyzed its land use data with a field survey to identify the abandoned cultivated land and geospatial characteristics.From the two aspects of social and natural factors,we analyzed the factors driving cultivated land abandonment with the help of Geodetector.The results showed that in 2019,the total area of the abandoned cultivated land in Longnan county was 4,962.35 hm^(2),covering 39.51% of this region.Among the topographic factors,the abandonment rate is positively correlated with elevation and slope gradient,but not with slope direction.Among the land parcel conditions,the abandonment rate is positively correlated with the access to road network and cultivation distance from settlement.At the county level,the abandonment of cultivated land in study area was affected by multiple factors,among which,the direct factor was the reduction in the labor force,such as the decrease of farming laborers and the increase of female population,which made farming unsustainable.Changes in production factors also promoted transformations in farmers’motivation to engage in production,such as the decrease of grain crops and the increase of cash crops,which was the indirect factor affecting cultivated land abandonment.The development of the rural nonagricultural industry affected farmers’enthusiasm,such as the decrease of farming households,which was the fundamental factor leading to cultivated land abandonment in this area.展开更多
Droughts are recurrent in southwest China due to the fragility and sensitivity of the karst environment.These events have serious impacts on local agricultural output,ecological diversity,and social stability.Understa...Droughts are recurrent in southwest China due to the fragility and sensitivity of the karst environment.These events have serious impacts on local agricultural output,ecological diversity,and social stability.Understanding spatiotemporal variations and driving factors of drought in this area is of extreme importance for effective mitigation measures.The karst areas situated in southwest China were spatially divided into seven sub-regions according to the topography and degree of karst development.Drought indices,including vegetation condition index(VCI),temperature condition index(TCI),vegetation health index(VHI),normalized vegetation water supply index(NVSWI),and temperature vegetation drought index(TVDI),were calculated from MODIS data during 2000 and 2018for each sub-region,and drought patterns were examined.The results show that droughts were found to be concentrated in sub-regions such as karst basin,karst plateau,karst gorge,and karst depression areas.Furthermore,there were more drought conditions in karst areas than in non-karst areas.In addition,improvements to drought situation in the study period are significant(p<0.05),and mitigation areas respectively account for 80.1%(NVSWI),74.2%(VCI),74.2%(VHI),30.1%(TCI)and 33.2%(TVDI)of the study area,while drought expands slightly(<3.4%)in areas undergoing urban construction.Pearson's correlation coefficients between drought indices and temperature are generally above 0.5 in all sub-regions.However,the correlation coefficients between drought indices and precipitation mostly fall within the range of 0.3-0.4,indicating a weaker correlation.Our explanation for the spatiotemporal patterns of drought is that karst phenomena are the natural basis of drought and agricultural production is one of important driving forces.Positive changes of drought conditions have benefited from efforts to control rocky desertification and restore ecosystems over the past years.展开更多
Objective:To explore and analyze the evaluation and driving factors of postoperative psychological pain inpatients with oral and maxillofacial malignant tumors.Methods:Relevant data were collected from 80 patients wit...Objective:To explore and analyze the evaluation and driving factors of postoperative psychological pain inpatients with oral and maxillofacial malignant tumors.Methods:Relevant data were collected from 80 patients with oral and maxillofacial malignant tumors who attended the outpatient clinic for follow-up consultations between May 2021 to May 2023.The patients used the psychological distress thermometer(DT)to circle words that best described their experiences in the past week,assigning a numerical value(0-10)to indicate their pain level on each day.The scoring results were employed to assess the psychological pain in these patients.A self-developed patient basic information questionnaire was utilized to record demographic details.Logistic regression analysis was employed to evaluate patients two weeks after surgery,focusing on the assessment of psychological distress and the identification and location of driving factors.Results:Following evaluation,the results revealed that the average postoperative DT score for the 80 patients with oral and maxillofacial malignant tumors was 4.53±1.98 points.Scores<4 points indicated no psychological pain(Group N)in 48 cases,while scores≥4 points indicated psychological pain(Group Y)in 32 cases.The differences in postoperative DT scores among patients with varying educational levels,fears and worries about disease progression,economic problems,sleep problems,level of hope,and oral pain were statistically significant(P<0.05).Multiple linear regression analysis results indicated that education level,fear and worry about disease progression,economic problems,sleep problems,level of hope,and oral pain are driving factors of postoperative psychological pain in patients with oral and maxillofacial malignant tumors(P<0.05).Conclusion:The postoperative psychological pain level in patients with oral and maxillofacial malignant tumors is at a moderate level.Educational level,fear and worry about disease progression,economic problems,sleep problems,level of hope,and oral pain were identified as driving factors for postoperative psychological pain in these patients.展开更多
The Hengduan mountain area,located in the upper reaches of the Yangtze River of China,is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and ...The Hengduan mountain area,located in the upper reaches of the Yangtze River of China,is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and western China as a whole.This paper introduces the gravity center model used to analyze the spatial-temporal variation patterns of vegetation Net Primary Productivity(NPP)from 2000 to 2015,which were determined by the use of MOD17 A3 NPP products.Additionally,the dominant driving factors of the spatial–temporal changes of vegetation NPP of the Hengduan Mountain area were quantitatively determined with a geographical detector over 2000-2015.The results revealed that:(1)From 2000 to 2015,there was an increasing trend of vegetation NPP in the Hengduan mountain area.Throughout the whole study region,the vegetation NPP with a mean value of 611.37 gC·m^(-2)·a^(-1) indicated a decreasing trend from southeast to northwest in terms of spatial distribution.(2)The gravity centers of vegetation NPP in 2000-2015 were mainly concentrated in Zhongdian County.During the study period,the gravity center of vegetation NPP moved northward,which indicated that the increment and increasing rate of vegetation NPP in the northern parts were greater than that of the southern areas.(3)The vegetation NPP showed a moderately positive correlation with temperature,accumulated temperature(>10℃),and sunshine,while there was an overall negative relationship between NPP and precipitation.(4)The dominant factors and interactive dominant factors changed in different subregions over different segments of the study period.The dominant factors of most sub-regions in Hengduan mountain were natural factors,and the climate change factors played an increasingly greater role over the 16 years of the study period.展开更多
Land use/land cover(LULC) is an important part of exploring the interaction between natural environment and human activities and achieving regional sustainable development. Based on the data of LULC types(cropland, fo...Land use/land cover(LULC) is an important part of exploring the interaction between natural environment and human activities and achieving regional sustainable development. Based on the data of LULC types(cropland, forest land, grassland, built-up land, and unused land) from 1990 to 2015, we analysed the intensity and driving factors of land use/cover change(LUCC) in the Yarlung Zangbo River,Nyang Qu River, and Lhasa River(YNL) region, Qinghai-Tibet Plateau of China, using intensity analysis method, cross-linking table method, and spatial econometric model. The results showed that LUCC in the YNL region was nonstationary from 1990 to 2015, showing a change pattern with "fast-slow-fast" and "U-shaped". Built-up land showed a steady increase pattern, while cropland showed a steady decrease pattern. The gain of built-up land mainly came from the loss of cropland. The transition pattern of LUCC in the YNL region was relatively single and stable during 1990–2015. The transition pattern from cropland and forest land to built-up land was a systematic change process of tendency and the transition pattern from grassland and unused land to cropland was a systematic change process of avoidance. The transition process of LUCC was the result of the combined effect of natural environment and social economic development in the YNL region. This study reveals the impact of ecological environment problems caused by human activities on the land resource system and provides scientific support for the study of ecological environment change and sustainable development of the Qinghai-Tibet Plateau.展开更多
Rapid industrialization and urbanization have led to the most serious habitat degradation in China,especially in the loess hilly area of the Yellow River Basin,where the ecological environment is relatively fragile.Th...Rapid industrialization and urbanization have led to the most serious habitat degradation in China,especially in the loess hilly area of the Yellow River Basin,where the ecological environment is relatively fragile.The contradiction between economic development and ecological environment protection has aroused widespread concern.In this study,we used the habitat quality of Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST-HQ)model at different scales to evaluate the dynamic evolution characteristics of habitat quality in Lanzhou City,Gansu Province of China.The spatiotemporal variations of habitat quality were analyzed by spatial autocorrelation.A Geographical Detector(Geodetector)model was used to explore the driving factors that influencing the spatial differentiation of habitat quality,including natural factors,socio-economic factors,and ecological protection factors.The results showed that the habitat quality index of Lanzhou City decreased from 0.4638 to 0.4548 during 2000-2018.The areas with reduced the habitat quality index were mainly located in the Yellow River Basin and Qinwangchuan Basin,where are the main urban areas and the new economic development areas,respectively.The spatial distribution of habitat quality presented a trend of high in the surrounding areas and low in the middle,and showed a significant positive spatial autocorrelation.With the increase of study scale,the spatial distribution of habitat quality changed from concentrated to dispersed.The spatial differentiation of habitat quality in the study area was the result of multiple factors.Among them,topographic relief and slope were the key factors.The synergistic enhancement among these driving factors intensified the spatial differentiation of habitat quality.The findings of this study can provide a scientific basis for land resources utilization and ecosystem restoration in the arid and semi-arid land.展开更多
As an important natural resource,forest land plays a key role in the maintenance of ecological security.However,variations of forest land in the agropastoral ecotone of northern China(AENC)have attracted little attent...As an important natural resource,forest land plays a key role in the maintenance of ecological security.However,variations of forest land in the agropastoral ecotone of northern China(AENC)have attracted little attention.Taking the AENC as an example and based on remote-sensing images from 2000,2010 to 2020,we explored the spatiotemporal variation of forest land and its driving factors using the land-use transfer matrix,spatial autocorrelation analysis and spatial error model.The results showed that from 2000 to 2020,the total area of forest land in the AENC increased from 75,547.52 to 77,359.96 km^(2) and the changes were dominated by the transformations among forest land,grassland and cropland,which occurred mainly in areas with the elevation of 500-2000 m and slope of 15°-25°.There was obvious spatial agglomeration of forest land in the AENC from 2000 to 2020,with hot spots of forest land gathered in the southern marginal areas of the Yanshan Mountains and the low mountainous and hilly areas of the Loess Plateau.The sub-hot spots around hot spots moved southward,the sub-cold spots spread to the surrounding areas and the cold spots disappeared.The spatiotemporal variation of forest land resulted from the interactions of natural environment,socioeconomic and policy factors from 2000 to 2020.The variables of average annual precipitation,slope,terrain relief,ecological conversion program and afforestation policy for barren mountains affected the spatial pattern of forest land positively,while those of annual average temperature,slope and road network density influenced it negatively.展开更多
Vegetation coverage recovery after the Wenchuan earthquake has important implications for preventing post-seismic geohazards and soil erosion.However,spatiotemporal changes in vegetation coverage recovery and its driv...Vegetation coverage recovery after the Wenchuan earthquake has important implications for preventing post-seismic geohazards and soil erosion.However,spatiotemporal changes in vegetation coverage recovery and its driving factors have not been sufficiently studied in the quake-hit areas.This paper aims to analyze vegetation coverage recovery and its driving factors in the quake-hit areas using monadic linear regression,coefficient of variation,and geographical detector.First,we used Moderate-resolution Imaging Spectroradiometer(MODIS)data to calculate the vegetation coverage from 2008 to 2018 in the quake-hit areas.Second,we assessed the trend and stability of vegetation recovery in the quake-hit areas based on vegetation coverage.Finally,combined with topography,climate,soil type,vegetation type,and human activities in the quake-hit areas,the driving factors affecting vegetation coverage recovery were analyzed.The results showed that the vegetation coverage level in the quake-hit areas recovered about 90%of that before the earthquake.Vegetation coverage recovery was mainly improved in a stepwise manner:increasing and then stabilizing,then increasing and stabilizing again.Elevation,soil type,and road density were the main factors affecting vegetation coverage recovery,and the interaction among all factors positively strengthened their impacts on vegetation coverage recovery.In addition,the results also revealed the categories that were conducive to vegetation coverage recovery among the same environmental factors and can provide a scientific reference for vegetation coverage recovery in the quake-hit areas.展开更多
Fire is an important disturbance in terms of forest management.A comprehensive understanding of the relationships between the spatial distribution of fire occurrence and its driving factors are critical for effective ...Fire is an important disturbance in terms of forest management.A comprehensive understanding of the relationships between the spatial distribution of fire occurrence and its driving factors are critical for effective forest fire management.To reveal biogeoclimatic and anthropogenic influences,this study introduced a geographical detector model to quantitatively examine the effects of multiple individual factors and their combinations on spatial patterns of fire occurrence in the Greater Khingan Mountains between 1980 and 2009.The geographical detector computes the explanatory power(q value)to measure the connection between driving factors and spatial distributions of fire occurrence.Kernel density estimation revealed the spatial variability of fire occurrence which was impacted by bandwidth.30 km might be the optimal bandwidth in this study.The biogeoclimatic and anthropogenic effects were explored using topography,climate,vegetation,and human activity factors as proxies.Our results indicated that solar radiation had the most influence on the spatial pattern of fire occurrence in the study area.Meanwhile,Normalized Difference Vegetation Index,temperature,wind speed,and vegetation type were determined as the major driving factors.For various groups of driving factors,climate variables were the dominant factors for the density of fire occurrence,while vegetation exerted a strong influence.The interactions between the driving factors had a more significant impact than a single factor.Individually,the factors in the topography and human activity groups exhibited weaker influences.However,their effects were enhanced when combined with climate and vegetation factors.This study improves our understanding of various driving factors and their combined influences on fire occurrences of the study area in a spatial context.The findings of this study verify that the geographical detector is applicable in revealing the driving factors of fire occurrence.展开更多
Coal production capacity regulation is a complex system involving economic growth,structural optimization,high-efficiency mining,and environmental protection.Based on its driving factors,this paper forms four regulati...Coal production capacity regulation is a complex system involving economic growth,structural optimization,high-efficiency mining,and environmental protection.Based on its driving factors,this paper forms four regulation modes representing different control orientations,establishes a system dynamics model,and predicts the regulation effects of single-factor and combined control mode.The result shows:(1) Except for the mechanization degree and recovery rate,the other nine individual production capacity control policies are all conducive to reducing coal production capacity and restraining the excessive growth of coal production capacity.(2) The effect of combined regulation mode on slowing down the growth of coal demand,regulating the excessive growth of coal production capacity and new capacity investment are obviously better than that of single policy.(3) The combined control modes have obvious differences in the suppression effect on coal production capacity:transformational development mode > technology-driven mode > structural optimization mode > efficiency improvement mode.Therefore,in the process of achieving optimal regulation of coal production capacity,attention should be paid to the preferential use of transformational development and technology-driven mode.At the same time,the comprehensive use of regulation and control methods should also be considered to improve the regulation effect and the regulation efficiency of coal production capacity.展开更多
Drylands are highly vulnerable to climate change and human activities.The drylands of China account for approximately 10.8%of global drylands,and China is the country most severely affected by aridity in Asia.Therefor...Drylands are highly vulnerable to climate change and human activities.The drylands of China account for approximately 10.8%of global drylands,and China is the country most severely affected by aridity in Asia.Therefore,studying the spatial variation characteristics in soil multifunctionality(SMF)and investigating the driving factors are critical for elucidating and managing the functions of dryland ecosystems in China.Based on the environmental factors(mean annual precipitation(MAP),mean annual temperature(MAT),solar radiation(Srad),soil acidity(pH),enhanced vegetation index(EVI),and cation exchange capacity(CEC))and aridity from the“dataset of soil properties for land surface modeling over China”,we used non-linear regression,ordinary least square(OLS)regression,structural equation model(SEM),and other analytical methods to investigate the relationships of SMF with environmental factors across different aridity levels in China.SMF in different dryland regions varied significantly and showed a patchy distribution,with SMF index values ranging from–1.21 to 2.42.Regions with SMF index values from–0.20 to 0.51 accounting for 63.0%of dryland area in China.OLS regression results revealed that environmental factors like MAP,MAT,Srad,pH,EVI,and CEC were significantly related to SMF(P<0.05).MAP and MAT were correlated to SMF at the whole aridity level(P<0.05).SEM results showed that the driving factors of SMF differed depending on the aridity level.Soil pH was the strongest driving factor of SMF when the aridity was less than 0.80(P<0.001).Both soil CEC and EVI had a positive effect on SMF when aridity was greater than 0.80(P<0.01),with soil CEC being the strongest driving factor.The importance ranking revealed that the relative importance contribution of soil pH to SMF was greatest when aridity was less than 0.80(66.9%).When aridity was set to greater than 0.80,the relative importance contributions of CEC and EVI to SMF increased(45.1%and 31.9%,respectively).Our findings indicated that SMF had high spatial heterogeneity in drylands of China.The aridity threshold controlled the impact of environmental factors on SMF.展开更多
A harmonious relationship between teachers and postgraduates presents the comprehensive value of psychological education,which guarantees training quality and acts as an effective carrier of mental health education of...A harmonious relationship between teachers and postgraduates presents the comprehensive value of psychological education,which guarantees training quality and acts as an effective carrier of mental health education of the postgraduates.Based on Bandura’s theory of reciprocal determinism and Austin’s input-output theory,this paper constructs a model concerning the value of psychological education in the tutor-student relationship.The path of realization is also explored in a structural equation model through a questionnaire survey of 1112 graduate supervisors and administrators in medical colleges.The experimental result indicates that(1)The interaction between teachers and postgraduates promotes the value of psychological education in the highest measure,among which the quality and frequency of tutor-student communication,mutual trust,and respect act as the key influencing indicators.(2)Tutor’s professional quality is considered as the fundamental driving force in the realization of psychological education value in the tutor-student relationship,the maximum mediating effect is observed in the developing path of tutor’s professional quality-interaction behavior between teachers and postgraduates-psychological growth of teachers and postgraduates.(3)The objective results obtained by teachers and postgraduates,such as the improvement of quality and quantity,positively promote the overall quality of life satisfaction of both sides,which improves the major psychological growth indicators.(4)In the path that affects the psychological growth of teachers and postgraduates,female groups mainly focusing on natural sciences pay more attention to the tutor-student emotional experience,while male and lower-grade groups pay more attention to behavioral interaction;In the path that affects the interaction between teachers and postgraduates,the tutor does not value the difference in the quality of graduate students,lower-grade and natural science professional groups pay more attention to institutional environment.展开更多
Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development.Based on land use data of the Weihe River...Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development.Based on land use data of the Weihe River basin in 2000,2010,and 2020,with the support of Aeronautical Reconnaissance Coverage Geographic Information System(ArcGIS),GeoDa,and other technologies,this study analyzed the spatial-temporal characteristics and driving factors of land use pattern and landscape ecological risk.Results showed that land use structure of the Weihe River basin has changed significantly,with the decrease of cropland and the increase of forest land and construction land.In the past 20 a,cropland has decreased by 7347.70 km2,and cropland was mainly converted into forest land,grassland,and construction land.The fragmentation and dispersion of ecological landscape pattern in the Weihe River basin were improved,and land use pattern became more concentrated.Meanwhile,landscape ecological risk of the Weihe River basin has been improved.Severe landscape ecological risk area decreased by 19,177.87 km2,high landscape ecological risk area decreased by 3904.35 km2,and moderate and low landscape ecological risk areas continued to increase.It is worth noting that landscape ecological risks in the upper reaches of the Weihe River basin are still relatively serious,especially in the contiguous areas of high ecological risk,such as Tianshui,Pingliang,Dingxi areas and some areas of Ningxia Hui Autonomous Region.Landscape ecological risk showed obvious spatial dependence,and high ecological risk area was concentrated.Among the driving factors,population density,precipitation,normalized difference vegetation index(NDVI),and their interactions are the most important factors affecting the landscape ecological risk of the Weihe River basin.The findings significantly contribute to our understanding of the ecological dynamics in the Weihe River basin,providing crucial insights for sustainable management in the region.展开更多
Investigations of runoff and sediment yield changes and their relationships with potential driving factors provide good insights for understanding the mechanisms of hydrological processes.This study attempted to prese...Investigations of runoff and sediment yield changes and their relationships with potential driving factors provide good insights for understanding the mechanisms of hydrological processes.This study attempted to present a comprehensive investigation on the spatiotemporal variations of sediment yield in the Loess Plateau using continuous observed data at 46 hydrological stations during 1961-2016,and its responses to changes of precipitation,land use/cover and vegetation cover were analyzed by using the Partial Least Squares-Structural Equation Model(PLS-SEM).The results indicated that sediment yield reduced pro-nouncedly during 1961-2016 in the Loess Plateau,and 77.9%of this variation was explained by the combined effects of precipitation,land-use change,vegetation dynamics and runoff reduction.Indirect effects of precipitation,land-use change,and vegetation cover on sediment yield were 0.242,-0.528 and-0.630(P<0.05),respectively,and direct effect of runoff on sediment yield was 0.833(P<0.05).According to the Pearson Correlation Coefficient,the strongest positive correlation existed between annual sediment yield and runoff(r=0.88,P<0.05),followed by vegetation cover(r=-0.47,P<0.05)and land-use change(i.e.forest land and grassland)suggesting their significant trapping effects on soil erosion.However,lower correlations were examined between sediment yield and precipitation indices(-0.14<r<0.34),and a relatively higher relationship was examined between sediment yield and heavy rainfall(P_(25))(r=034).Overall,changes in runoff and land-use/vegetation cover well explained varia-tions in sediment yield in the Loess Plateau.The findings are expected to provide scientific and technical support for future soil and water conservation planning in the Loess Plateau,and are valuable for sus-tainable water resources and sediment load management in the Yellow River Basin.展开更多
Grassland is the second largest terrestrial ecosystem and a fundamental land resource for human survival and development.Although grassland degradation is a recognized and crucial ecological problem,there is no consen...Grassland is the second largest terrestrial ecosystem and a fundamental land resource for human survival and development.Although grassland degradation is a recognized and crucial ecological problem,there is no consensus on the area,scope,and degree of its global degradation trends,making the implementation of Sustainable Development Goals(SDG)15.3 for achieving a land degradation-neutral world uncertain.This study quantitatively explored global grassland degradation trends from 2000 to 2020 by coupling vegetation growth and its response to climate change.Furthermore,the driving factors behind these trends were analyzed,especially in hotspots.Results show that the improvement in global grassland has been remarkable since 2000,with a 1.92 times larger area than degrading grassland,amounting to 372.47×10^(4) and 193.57×10^(4) km^(2),respectively.Africa and Asia lead in global grassland degradation and improvement,respectively.Globally,the combined effects of climate change and human activities are the main driving factors for grassland degradation and improvement,accounting for 84.72 and 87.76%,respectively.Notably,human activities played a crucial role in reversing the trend of grassland degradation in some hotspots.Finally,this study provides an essential scientific reference and support for realizing SDG 15.3 on global and regional scales.展开更多
Accurate and credible identification of the drivers of algal growth is essential for sustainable utilization and scientific management of freshwater.In this study,we developed a deep learning-based Transformer model,n...Accurate and credible identification of the drivers of algal growth is essential for sustainable utilization and scientific management of freshwater.In this study,we developed a deep learning-based Transformer model,named Bloomformer-1,for end-to-end identification of the drivers of algal growth without the needing extensive a priori knowledge or prior experiments.The Middle Route of the South-to-North Water Diversion Project(MRP)was used as the study site to demonstrate that Bloomformer-1 exhibited more robust performance(with the highest R^(2),0.80 to 0.94,and the lowest RMSE,0.22–0.43μg/L)compared to four widely used traditional machine learning models,namely extra trees regression(ETR),gradient boosting regression tree(GBRT),support vector regression(SVR),and multiple linear regression(MLR).In addition,Bloomformer-1 had higher interpretability(including higher transferability and understandability)than the four traditional machine learning models,which meant that it was trustworthy and the results could be directly applied to real scenarios.Finally,it was determined that total phosphorus(TP)was the most important driver for the MRP,especially in Henan section of the canal,although total nitrogen(TN)had the highest effect on algal growth in the Hebei section.Based on these results,phosphorus loading controlling in the whole MRP was proposed as an algal control strategy.展开更多
With the rapid socio-economic development and urban expansion,land subsidence has emerged as a major environmental issue,impeding the high-quality development of the plain area in eastern Zhengzhou City,Henan Province...With the rapid socio-economic development and urban expansion,land subsidence has emerged as a major environmental issue,impeding the high-quality development of the plain area in eastern Zhengzhou City,Henan Province,China.However,effective prevention and control of land subsidence in this region have been challenging due to the lack of comprehensive surface deformations monitoring and the quantitative analysis of the factors driving these deformations.In order to accurately identify the dominant factor driving surface deformations in the study area,this study utilized the Persistent Scattered Interferometric Synthetic Aperture Radar(PS-InSAR)technique to acquire the spatio-temporal distribution of surface deformations from January 2018 to March 2020.The acquired data was verified using leveling data.Subsequently,GIS spatial analysis was employed to investigate the responses of surface deformations to the driving factors.The findings are as follows:Finally,the geographical detector model was utilized to quantify the contributions of the driving factors and reveal the mechanisms of their interactions.The findings are as follows:(1)Surface deformations in the study area are dominated by land subsidence,concentrated mainly in Zhongmu County,with a deformation rate of−12.5–−37.1 mm/a.In contrast,areas experiencing surface uplift are primarily located downtown,with deformation rates ranging from 0 mm to 8 mm;(2)Groundwater level,lithology,and urban construction exhibit strong spatial correlations with cumulative deformation amplitude;(3)Groundwater level of the second aquifer group is the primary driver of spatially stratified heterogeneity in surface deformations,with a contributive degree of 0.5328.The contributive degrees of driving factors are significantly enhanced through interactions.Groundwater level and the cohesive soil thickness in the second aquifer group show the strongest interactions in the study area.Their total contributive degree increases to 0.5722 after interactions,establishing them as the primary factors influencing surface deformation patterns in the study area.The results of this study can provide a theoretical basis and scientific support for precise prevention and control measures against land subsidence in the study area,as well as contributing to research on the underlying mechanisms.展开更多
基金This research was funded by the National Natural Science Foundation of China(grant no.32271881).
文摘Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.
基金Under the auspices of National Natural Science Foundation of China (No. 52268008, 51768001)。
文摘Since China announced its goal of becoming carbon-neutral by 2060, carbon neutrality has become a major target in the development of China's urban agglomerations. This study applied the Future Land Use Simulation(FLUS) model to predict the land use pattern of the ecological space of the Beibu Gulf urban agglomeration, in 2060 under ecological priority, agricultural priority and urbanized priority scenarios. The Integrated Valuation of Ecosystem Services and Trade-offs(In VEST) model was employed to analyse the spatial changes in ecological space carbon storage in each scenario from 2020 to 2060. Then, this study used a Geographically Weighted Regression(GWR) model to determine the main driving factors that influence the changes in land carbon sinking capacity. The results of the study can be summarised as follows: firstly, the agricultural and ecological priority scenarios will achieve balanced urban expansion and environmental protection of resources in an ecological space. The urbanized priority scenario will reduce the carbon sinking capacity. Among the simulation scenarios for 2060, carbon storage in the urbanized priority scenario will decrease by 112.26 × 10^(6) t compared with that for 2020 and the average carbon density will decrease by 0.96 kg/m^(2) compared with that for 2020. Carbon storage in the agricultural priority scenario will increase by 84.11 × 10^(6) t, and the average carbon density will decrease by 0.72 kg/m^(2). Carbon storage in the ecological priority scenario will increase by 3.03 × 10^(6) t, and the average carbon density will increase by 0.03 kg/m^(2). Under the premise that the population of the town will increases continuously, the ecological priority development approach may be a wise choice.Secondly, slope, distance to river and elevation are the most important factors that influence the carbon sink pattern of the ecological space in the Beibu Gulf urban agglomeration, followed by GDP, population density, slope direction and distance to traffic infrastructure.At the same time, urban space expansion is the main cause of the changes of this natural factors. Thirdly, the decreasing trend of ecological space is difficult to reverse, so reasonable land use policy to curb the spatial expansion of cities need to be made.
基金supported by the University Humanities and Social Sciences Project of Jiangxi Province(Grant No.JC20108 and GL20225)the National Natural Science Foundation of China(Grant No.42267068)。
文摘The abandonment of cultivated land in southern China was gradually obvious.This research aims to provide a reference for solving the abandonment of cultivated land in hilly regions and promote rural development in China.We examined Longnan county located in the hilly regions of southern China as an example,where abandoned cultivated land is very common.We analyzed its land use data with a field survey to identify the abandoned cultivated land and geospatial characteristics.From the two aspects of social and natural factors,we analyzed the factors driving cultivated land abandonment with the help of Geodetector.The results showed that in 2019,the total area of the abandoned cultivated land in Longnan county was 4,962.35 hm^(2),covering 39.51% of this region.Among the topographic factors,the abandonment rate is positively correlated with elevation and slope gradient,but not with slope direction.Among the land parcel conditions,the abandonment rate is positively correlated with the access to road network and cultivation distance from settlement.At the county level,the abandonment of cultivated land in study area was affected by multiple factors,among which,the direct factor was the reduction in the labor force,such as the decrease of farming laborers and the increase of female population,which made farming unsustainable.Changes in production factors also promoted transformations in farmers’motivation to engage in production,such as the decrease of grain crops and the increase of cash crops,which was the indirect factor affecting cultivated land abandonment.The development of the rural nonagricultural industry affected farmers’enthusiasm,such as the decrease of farming households,which was the fundamental factor leading to cultivated land abandonment in this area.
基金the Guangxi Natural Science Foundation(NO.2022GXNSFBA035639)the Natural Science Foundation of China(NO.42064003)the Guangxi Key Laboratory of Spatial Information and Geomatics Program(Gui KeNeng 19-050-11-23)。
文摘Droughts are recurrent in southwest China due to the fragility and sensitivity of the karst environment.These events have serious impacts on local agricultural output,ecological diversity,and social stability.Understanding spatiotemporal variations and driving factors of drought in this area is of extreme importance for effective mitigation measures.The karst areas situated in southwest China were spatially divided into seven sub-regions according to the topography and degree of karst development.Drought indices,including vegetation condition index(VCI),temperature condition index(TCI),vegetation health index(VHI),normalized vegetation water supply index(NVSWI),and temperature vegetation drought index(TVDI),were calculated from MODIS data during 2000 and 2018for each sub-region,and drought patterns were examined.The results show that droughts were found to be concentrated in sub-regions such as karst basin,karst plateau,karst gorge,and karst depression areas.Furthermore,there were more drought conditions in karst areas than in non-karst areas.In addition,improvements to drought situation in the study period are significant(p<0.05),and mitigation areas respectively account for 80.1%(NVSWI),74.2%(VCI),74.2%(VHI),30.1%(TCI)and 33.2%(TVDI)of the study area,while drought expands slightly(<3.4%)in areas undergoing urban construction.Pearson's correlation coefficients between drought indices and temperature are generally above 0.5 in all sub-regions.However,the correlation coefficients between drought indices and precipitation mostly fall within the range of 0.3-0.4,indicating a weaker correlation.Our explanation for the spatiotemporal patterns of drought is that karst phenomena are the natural basis of drought and agricultural production is one of important driving forces.Positive changes of drought conditions have benefited from efforts to control rocky desertification and restore ecosystems over the past years.
文摘Objective:To explore and analyze the evaluation and driving factors of postoperative psychological pain inpatients with oral and maxillofacial malignant tumors.Methods:Relevant data were collected from 80 patients with oral and maxillofacial malignant tumors who attended the outpatient clinic for follow-up consultations between May 2021 to May 2023.The patients used the psychological distress thermometer(DT)to circle words that best described their experiences in the past week,assigning a numerical value(0-10)to indicate their pain level on each day.The scoring results were employed to assess the psychological pain in these patients.A self-developed patient basic information questionnaire was utilized to record demographic details.Logistic regression analysis was employed to evaluate patients two weeks after surgery,focusing on the assessment of psychological distress and the identification and location of driving factors.Results:Following evaluation,the results revealed that the average postoperative DT score for the 80 patients with oral and maxillofacial malignant tumors was 4.53±1.98 points.Scores<4 points indicated no psychological pain(Group N)in 48 cases,while scores≥4 points indicated psychological pain(Group Y)in 32 cases.The differences in postoperative DT scores among patients with varying educational levels,fears and worries about disease progression,economic problems,sleep problems,level of hope,and oral pain were statistically significant(P<0.05).Multiple linear regression analysis results indicated that education level,fear and worry about disease progression,economic problems,sleep problems,level of hope,and oral pain are driving factors of postoperative psychological pain in patients with oral and maxillofacial malignant tumors(P<0.05).Conclusion:The postoperative psychological pain level in patients with oral and maxillofacial malignant tumors is at a moderate level.Educational level,fear and worry about disease progression,economic problems,sleep problems,level of hope,and oral pain were identified as driving factors for postoperative psychological pain in these patients.
基金supported by the Open fund of Key Laboratory of National Geographic Census and Monitoring,MNR(grant no.2020NGCM02)Open Research Fund of the Key Laboratory of Digital Earth Science,Chinese Academy of Sciences(grant no.2019LDE006)+8 种基金the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources(grant no.KF-2020-05001)Open fund of Key Laboratory of Land use,Ministry of Natural Resources(grant no.20201511835)Open Fund of Key Laboratory for Digital Land and Resources of Jiangxi Province,East China University of Technology(grant no.DLLJ202002)Open foundation of MOE Key Laboratory of Western China’s Environmental Systems,Lanzhou University and the fundamental Research funds for the Central Universities(grant no.lzujbky-2020-kb01)University-Industry Collaborative Education Program(grant no.201902208005)Open Fund of Key Laboratory of Meteorology and Ecological Environment of Hebei Province(grant no.Z202001H)Open Fund of Key Laboratory of Geomatics and Digital Technology of Shandong ProvinceOpen Fund of Key Laboratory of Geomatics Technology and Application Key Laboratory of Qinghai Province(grant no.QHDX-2019-04)Natural Science Foundation of Shandong Province(grant no.ZR2018BD001)。
文摘The Hengduan mountain area,located in the upper reaches of the Yangtze River of China,is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and western China as a whole.This paper introduces the gravity center model used to analyze the spatial-temporal variation patterns of vegetation Net Primary Productivity(NPP)from 2000 to 2015,which were determined by the use of MOD17 A3 NPP products.Additionally,the dominant driving factors of the spatial–temporal changes of vegetation NPP of the Hengduan Mountain area were quantitatively determined with a geographical detector over 2000-2015.The results revealed that:(1)From 2000 to 2015,there was an increasing trend of vegetation NPP in the Hengduan mountain area.Throughout the whole study region,the vegetation NPP with a mean value of 611.37 gC·m^(-2)·a^(-1) indicated a decreasing trend from southeast to northwest in terms of spatial distribution.(2)The gravity centers of vegetation NPP in 2000-2015 were mainly concentrated in Zhongdian County.During the study period,the gravity center of vegetation NPP moved northward,which indicated that the increment and increasing rate of vegetation NPP in the northern parts were greater than that of the southern areas.(3)The vegetation NPP showed a moderately positive correlation with temperature,accumulated temperature(>10℃),and sunshine,while there was an overall negative relationship between NPP and precipitation.(4)The dominant factors and interactive dominant factors changed in different subregions over different segments of the study period.The dominant factors of most sub-regions in Hengduan mountain were natural factors,and the climate change factors played an increasingly greater role over the 16 years of the study period.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research of China(2019QZKK0603)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20040200)Reconstruction of Historical Cultivated Land and Human Activities around the North Slope of Everest Area of China(42061023)。
文摘Land use/land cover(LULC) is an important part of exploring the interaction between natural environment and human activities and achieving regional sustainable development. Based on the data of LULC types(cropland, forest land, grassland, built-up land, and unused land) from 1990 to 2015, we analysed the intensity and driving factors of land use/cover change(LUCC) in the Yarlung Zangbo River,Nyang Qu River, and Lhasa River(YNL) region, Qinghai-Tibet Plateau of China, using intensity analysis method, cross-linking table method, and spatial econometric model. The results showed that LUCC in the YNL region was nonstationary from 1990 to 2015, showing a change pattern with "fast-slow-fast" and "U-shaped". Built-up land showed a steady increase pattern, while cropland showed a steady decrease pattern. The gain of built-up land mainly came from the loss of cropland. The transition pattern of LUCC in the YNL region was relatively single and stable during 1990–2015. The transition pattern from cropland and forest land to built-up land was a systematic change process of tendency and the transition pattern from grassland and unused land to cropland was a systematic change process of avoidance. The transition process of LUCC was the result of the combined effect of natural environment and social economic development in the YNL region. This study reveals the impact of ecological environment problems caused by human activities on the land resource system and provides scientific support for the study of ecological environment change and sustainable development of the Qinghai-Tibet Plateau.
基金This research was supported by the National Natural Science Foundation of China(41961029)the Gansu Construction Science and Technology Soft Science Project of China(JK2022-16).
文摘Rapid industrialization and urbanization have led to the most serious habitat degradation in China,especially in the loess hilly area of the Yellow River Basin,where the ecological environment is relatively fragile.The contradiction between economic development and ecological environment protection has aroused widespread concern.In this study,we used the habitat quality of Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST-HQ)model at different scales to evaluate the dynamic evolution characteristics of habitat quality in Lanzhou City,Gansu Province of China.The spatiotemporal variations of habitat quality were analyzed by spatial autocorrelation.A Geographical Detector(Geodetector)model was used to explore the driving factors that influencing the spatial differentiation of habitat quality,including natural factors,socio-economic factors,and ecological protection factors.The results showed that the habitat quality index of Lanzhou City decreased from 0.4638 to 0.4548 during 2000-2018.The areas with reduced the habitat quality index were mainly located in the Yellow River Basin and Qinwangchuan Basin,where are the main urban areas and the new economic development areas,respectively.The spatial distribution of habitat quality presented a trend of high in the surrounding areas and low in the middle,and showed a significant positive spatial autocorrelation.With the increase of study scale,the spatial distribution of habitat quality changed from concentrated to dispersed.The spatial differentiation of habitat quality in the study area was the result of multiple factors.Among them,topographic relief and slope were the key factors.The synergistic enhancement among these driving factors intensified the spatial differentiation of habitat quality.The findings of this study can provide a scientific basis for land resources utilization and ecosystem restoration in the arid and semi-arid land.
基金funded by the National Natural Science Foundation of China(41971238)the Ministry of Education Humanities and Social Youth Foundation of China(19YJCZH144)+1 种基金the Natural Science Foundation of Shandong Province,China(ZR2019QD006)the National College Student Innovation Training Project(S202010446004).
文摘As an important natural resource,forest land plays a key role in the maintenance of ecological security.However,variations of forest land in the agropastoral ecotone of northern China(AENC)have attracted little attention.Taking the AENC as an example and based on remote-sensing images from 2000,2010 to 2020,we explored the spatiotemporal variation of forest land and its driving factors using the land-use transfer matrix,spatial autocorrelation analysis and spatial error model.The results showed that from 2000 to 2020,the total area of forest land in the AENC increased from 75,547.52 to 77,359.96 km^(2) and the changes were dominated by the transformations among forest land,grassland and cropland,which occurred mainly in areas with the elevation of 500-2000 m and slope of 15°-25°.There was obvious spatial agglomeration of forest land in the AENC from 2000 to 2020,with hot spots of forest land gathered in the southern marginal areas of the Yanshan Mountains and the low mountainous and hilly areas of the Loess Plateau.The sub-hot spots around hot spots moved southward,the sub-cold spots spread to the surrounding areas and the cold spots disappeared.The spatiotemporal variation of forest land resulted from the interactions of natural environment,socioeconomic and policy factors from 2000 to 2020.The variables of average annual precipitation,slope,terrain relief,ecological conversion program and afforestation policy for barren mountains affected the spatial pattern of forest land positively,while those of annual average temperature,slope and road network density influenced it negatively.
基金This study is supported and funded by the National Natural Science Foundation of China(Grant No.42074021)Department of Science and Technology of Sichuan Province(Grant No.20ZDYF1142+3 种基金Grant No.2020JDTD0003)China Scholarship Council(CSC No.202007000081)Science and Technology Bureau of Nanchong City(Grant Nos.20YFZJ0029 and 19SXHZ0039)Linguo Yuan is funded by the National Program for Support of Top-notch Young Professionals.
文摘Vegetation coverage recovery after the Wenchuan earthquake has important implications for preventing post-seismic geohazards and soil erosion.However,spatiotemporal changes in vegetation coverage recovery and its driving factors have not been sufficiently studied in the quake-hit areas.This paper aims to analyze vegetation coverage recovery and its driving factors in the quake-hit areas using monadic linear regression,coefficient of variation,and geographical detector.First,we used Moderate-resolution Imaging Spectroradiometer(MODIS)data to calculate the vegetation coverage from 2008 to 2018 in the quake-hit areas.Second,we assessed the trend and stability of vegetation recovery in the quake-hit areas based on vegetation coverage.Finally,combined with topography,climate,soil type,vegetation type,and human activities in the quake-hit areas,the driving factors affecting vegetation coverage recovery were analyzed.The results showed that the vegetation coverage level in the quake-hit areas recovered about 90%of that before the earthquake.Vegetation coverage recovery was mainly improved in a stepwise manner:increasing and then stabilizing,then increasing and stabilizing again.Elevation,soil type,and road density were the main factors affecting vegetation coverage recovery,and the interaction among all factors positively strengthened their impacts on vegetation coverage recovery.In addition,the results also revealed the categories that were conducive to vegetation coverage recovery among the same environmental factors and can provide a scientific reference for vegetation coverage recovery in the quake-hit areas.
基金funded by the National Natural Science Foundation of China(Grant No.41601438)Fundamental Research Funds for the Central Universities(Grant NO.2412019FZ002)。
文摘Fire is an important disturbance in terms of forest management.A comprehensive understanding of the relationships between the spatial distribution of fire occurrence and its driving factors are critical for effective forest fire management.To reveal biogeoclimatic and anthropogenic influences,this study introduced a geographical detector model to quantitatively examine the effects of multiple individual factors and their combinations on spatial patterns of fire occurrence in the Greater Khingan Mountains between 1980 and 2009.The geographical detector computes the explanatory power(q value)to measure the connection between driving factors and spatial distributions of fire occurrence.Kernel density estimation revealed the spatial variability of fire occurrence which was impacted by bandwidth.30 km might be the optimal bandwidth in this study.The biogeoclimatic and anthropogenic effects were explored using topography,climate,vegetation,and human activity factors as proxies.Our results indicated that solar radiation had the most influence on the spatial pattern of fire occurrence in the study area.Meanwhile,Normalized Difference Vegetation Index,temperature,wind speed,and vegetation type were determined as the major driving factors.For various groups of driving factors,climate variables were the dominant factors for the density of fire occurrence,while vegetation exerted a strong influence.The interactions between the driving factors had a more significant impact than a single factor.Individually,the factors in the topography and human activity groups exhibited weaker influences.However,their effects were enhanced when combined with climate and vegetation factors.This study improves our understanding of various driving factors and their combined influences on fire occurrences of the study area in a spatial context.The findings of this study verify that the geographical detector is applicable in revealing the driving factors of fire occurrence.
基金support provided by National Social Science:China’s coal industry excess capacity and policy selection issues under the background of the new normal (Nos.16BJY054)。
文摘Coal production capacity regulation is a complex system involving economic growth,structural optimization,high-efficiency mining,and environmental protection.Based on its driving factors,this paper forms four regulation modes representing different control orientations,establishes a system dynamics model,and predicts the regulation effects of single-factor and combined control mode.The result shows:(1) Except for the mechanization degree and recovery rate,the other nine individual production capacity control policies are all conducive to reducing coal production capacity and restraining the excessive growth of coal production capacity.(2) The effect of combined regulation mode on slowing down the growth of coal demand,regulating the excessive growth of coal production capacity and new capacity investment are obviously better than that of single policy.(3) The combined control modes have obvious differences in the suppression effect on coal production capacity:transformational development mode > technology-driven mode > structural optimization mode > efficiency improvement mode.Therefore,in the process of achieving optimal regulation of coal production capacity,attention should be paid to the preferential use of transformational development and technology-driven mode.At the same time,the comprehensive use of regulation and control methods should also be considered to improve the regulation effect and the regulation efficiency of coal production capacity.
基金supported by the Xinjiang Outstanding Youth fund(2021D01E03)the National Natural Science Foundation of China(U2003214 and 41977099).
文摘Drylands are highly vulnerable to climate change and human activities.The drylands of China account for approximately 10.8%of global drylands,and China is the country most severely affected by aridity in Asia.Therefore,studying the spatial variation characteristics in soil multifunctionality(SMF)and investigating the driving factors are critical for elucidating and managing the functions of dryland ecosystems in China.Based on the environmental factors(mean annual precipitation(MAP),mean annual temperature(MAT),solar radiation(Srad),soil acidity(pH),enhanced vegetation index(EVI),and cation exchange capacity(CEC))and aridity from the“dataset of soil properties for land surface modeling over China”,we used non-linear regression,ordinary least square(OLS)regression,structural equation model(SEM),and other analytical methods to investigate the relationships of SMF with environmental factors across different aridity levels in China.SMF in different dryland regions varied significantly and showed a patchy distribution,with SMF index values ranging from–1.21 to 2.42.Regions with SMF index values from–0.20 to 0.51 accounting for 63.0%of dryland area in China.OLS regression results revealed that environmental factors like MAP,MAT,Srad,pH,EVI,and CEC were significantly related to SMF(P<0.05).MAP and MAT were correlated to SMF at the whole aridity level(P<0.05).SEM results showed that the driving factors of SMF differed depending on the aridity level.Soil pH was the strongest driving factor of SMF when the aridity was less than 0.80(P<0.001).Both soil CEC and EVI had a positive effect on SMF when aridity was greater than 0.80(P<0.01),with soil CEC being the strongest driving factor.The importance ranking revealed that the relative importance contribution of soil pH to SMF was greatest when aridity was less than 0.80(66.9%).When aridity was set to greater than 0.80,the relative importance contributions of CEC and EVI to SMF increased(45.1%and 31.9%,respectively).Our findings indicated that SMF had high spatial heterogeneity in drylands of China.The aridity threshold controlled the impact of environmental factors on SMF.
文摘A harmonious relationship between teachers and postgraduates presents the comprehensive value of psychological education,which guarantees training quality and acts as an effective carrier of mental health education of the postgraduates.Based on Bandura’s theory of reciprocal determinism and Austin’s input-output theory,this paper constructs a model concerning the value of psychological education in the tutor-student relationship.The path of realization is also explored in a structural equation model through a questionnaire survey of 1112 graduate supervisors and administrators in medical colleges.The experimental result indicates that(1)The interaction between teachers and postgraduates promotes the value of psychological education in the highest measure,among which the quality and frequency of tutor-student communication,mutual trust,and respect act as the key influencing indicators.(2)Tutor’s professional quality is considered as the fundamental driving force in the realization of psychological education value in the tutor-student relationship,the maximum mediating effect is observed in the developing path of tutor’s professional quality-interaction behavior between teachers and postgraduates-psychological growth of teachers and postgraduates.(3)The objective results obtained by teachers and postgraduates,such as the improvement of quality and quantity,positively promote the overall quality of life satisfaction of both sides,which improves the major psychological growth indicators.(4)In the path that affects the psychological growth of teachers and postgraduates,female groups mainly focusing on natural sciences pay more attention to the tutor-student emotional experience,while male and lower-grade groups pay more attention to behavioral interaction;In the path that affects the interaction between teachers and postgraduates,the tutor does not value the difference in the quality of graduate students,lower-grade and natural science professional groups pay more attention to institutional environment.
基金the National Natural Science Foundation of China(31971859)the Doctoral Research Start-up Fund of Northwest A&F University,China(Z1090121109)the Shaanxi Science and Technology Development Plan Project(2023-JC-QN-0197).
文摘Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development.Based on land use data of the Weihe River basin in 2000,2010,and 2020,with the support of Aeronautical Reconnaissance Coverage Geographic Information System(ArcGIS),GeoDa,and other technologies,this study analyzed the spatial-temporal characteristics and driving factors of land use pattern and landscape ecological risk.Results showed that land use structure of the Weihe River basin has changed significantly,with the decrease of cropland and the increase of forest land and construction land.In the past 20 a,cropland has decreased by 7347.70 km2,and cropland was mainly converted into forest land,grassland,and construction land.The fragmentation and dispersion of ecological landscape pattern in the Weihe River basin were improved,and land use pattern became more concentrated.Meanwhile,landscape ecological risk of the Weihe River basin has been improved.Severe landscape ecological risk area decreased by 19,177.87 km2,high landscape ecological risk area decreased by 3904.35 km2,and moderate and low landscape ecological risk areas continued to increase.It is worth noting that landscape ecological risks in the upper reaches of the Weihe River basin are still relatively serious,especially in the contiguous areas of high ecological risk,such as Tianshui,Pingliang,Dingxi areas and some areas of Ningxia Hui Autonomous Region.Landscape ecological risk showed obvious spatial dependence,and high ecological risk area was concentrated.Among the driving factors,population density,precipitation,normalized difference vegetation index(NDVI),and their interactions are the most important factors affecting the landscape ecological risk of the Weihe River basin.The findings significantly contribute to our understanding of the ecological dynamics in the Weihe River basin,providing crucial insights for sustainable management in the region.
基金supported by the National Natural Science Foundation of China(Grant Nos.U2243211,42177323,42077076,41671279).
文摘Investigations of runoff and sediment yield changes and their relationships with potential driving factors provide good insights for understanding the mechanisms of hydrological processes.This study attempted to present a comprehensive investigation on the spatiotemporal variations of sediment yield in the Loess Plateau using continuous observed data at 46 hydrological stations during 1961-2016,and its responses to changes of precipitation,land use/cover and vegetation cover were analyzed by using the Partial Least Squares-Structural Equation Model(PLS-SEM).The results indicated that sediment yield reduced pro-nouncedly during 1961-2016 in the Loess Plateau,and 77.9%of this variation was explained by the combined effects of precipitation,land-use change,vegetation dynamics and runoff reduction.Indirect effects of precipitation,land-use change,and vegetation cover on sediment yield were 0.242,-0.528 and-0.630(P<0.05),respectively,and direct effect of runoff on sediment yield was 0.833(P<0.05).According to the Pearson Correlation Coefficient,the strongest positive correlation existed between annual sediment yield and runoff(r=0.88,P<0.05),followed by vegetation cover(r=-0.47,P<0.05)and land-use change(i.e.forest land and grassland)suggesting their significant trapping effects on soil erosion.However,lower correlations were examined between sediment yield and precipitation indices(-0.14<r<0.34),and a relatively higher relationship was examined between sediment yield and heavy rainfall(P_(25))(r=034).Overall,changes in runoff and land-use/vegetation cover well explained varia-tions in sediment yield in the Loess Plateau.The findings are expected to provide scientific and technical support for future soil and water conservation planning in the Loess Plateau,and are valuable for sus-tainable water resources and sediment load management in the Yellow River Basin.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences[Grant Numbers XDA 19090124]the National Natural Science Foundation of China:[Grant Number 42001386,42271407].
文摘Grassland is the second largest terrestrial ecosystem and a fundamental land resource for human survival and development.Although grassland degradation is a recognized and crucial ecological problem,there is no consensus on the area,scope,and degree of its global degradation trends,making the implementation of Sustainable Development Goals(SDG)15.3 for achieving a land degradation-neutral world uncertain.This study quantitatively explored global grassland degradation trends from 2000 to 2020 by coupling vegetation growth and its response to climate change.Furthermore,the driving factors behind these trends were analyzed,especially in hotspots.Results show that the improvement in global grassland has been remarkable since 2000,with a 1.92 times larger area than degrading grassland,amounting to 372.47×10^(4) and 193.57×10^(4) km^(2),respectively.Africa and Asia lead in global grassland degradation and improvement,respectively.Globally,the combined effects of climate change and human activities are the main driving factors for grassland degradation and improvement,accounting for 84.72 and 87.76%,respectively.Notably,human activities played a crucial role in reversing the trend of grassland degradation in some hotspots.Finally,this study provides an essential scientific reference and support for realizing SDG 15.3 on global and regional scales.
基金This research was Jointly funded by National Key R&D plan(No.2021YFC3200900)National Natural Science Foundation of China(No.31971477).
文摘Accurate and credible identification of the drivers of algal growth is essential for sustainable utilization and scientific management of freshwater.In this study,we developed a deep learning-based Transformer model,named Bloomformer-1,for end-to-end identification of the drivers of algal growth without the needing extensive a priori knowledge or prior experiments.The Middle Route of the South-to-North Water Diversion Project(MRP)was used as the study site to demonstrate that Bloomformer-1 exhibited more robust performance(with the highest R^(2),0.80 to 0.94,and the lowest RMSE,0.22–0.43μg/L)compared to four widely used traditional machine learning models,namely extra trees regression(ETR),gradient boosting regression tree(GBRT),support vector regression(SVR),and multiple linear regression(MLR).In addition,Bloomformer-1 had higher interpretability(including higher transferability and understandability)than the four traditional machine learning models,which meant that it was trustworthy and the results could be directly applied to real scenarios.Finally,it was determined that total phosphorus(TP)was the most important driver for the MRP,especially in Henan section of the canal,although total nitrogen(TN)had the highest effect on algal growth in the Hebei section.Based on these results,phosphorus loading controlling in the whole MRP was proposed as an algal control strategy.
基金supported by the China Geological Survey Project(Grant No.DD20189262Grant No.DD20211309)Basic Research Operations Project of the Institute of Hydrogeology and Environmental Geology,Chinese Academy of Geological Sciences(SK202206).
文摘With the rapid socio-economic development and urban expansion,land subsidence has emerged as a major environmental issue,impeding the high-quality development of the plain area in eastern Zhengzhou City,Henan Province,China.However,effective prevention and control of land subsidence in this region have been challenging due to the lack of comprehensive surface deformations monitoring and the quantitative analysis of the factors driving these deformations.In order to accurately identify the dominant factor driving surface deformations in the study area,this study utilized the Persistent Scattered Interferometric Synthetic Aperture Radar(PS-InSAR)technique to acquire the spatio-temporal distribution of surface deformations from January 2018 to March 2020.The acquired data was verified using leveling data.Subsequently,GIS spatial analysis was employed to investigate the responses of surface deformations to the driving factors.The findings are as follows:Finally,the geographical detector model was utilized to quantify the contributions of the driving factors and reveal the mechanisms of their interactions.The findings are as follows:(1)Surface deformations in the study area are dominated by land subsidence,concentrated mainly in Zhongmu County,with a deformation rate of−12.5–−37.1 mm/a.In contrast,areas experiencing surface uplift are primarily located downtown,with deformation rates ranging from 0 mm to 8 mm;(2)Groundwater level,lithology,and urban construction exhibit strong spatial correlations with cumulative deformation amplitude;(3)Groundwater level of the second aquifer group is the primary driver of spatially stratified heterogeneity in surface deformations,with a contributive degree of 0.5328.The contributive degrees of driving factors are significantly enhanced through interactions.Groundwater level and the cohesive soil thickness in the second aquifer group show the strongest interactions in the study area.Their total contributive degree increases to 0.5722 after interactions,establishing them as the primary factors influencing surface deformation patterns in the study area.The results of this study can provide a theoretical basis and scientific support for precise prevention and control measures against land subsidence in the study area,as well as contributing to research on the underlying mechanisms.
