Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility ar...Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning.展开更多
Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in...Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in Ukraine,particularly in the context of the 2022 Russia-Ukraine conflict.We provide the first comprehensive assessment of both conflict-and non-conflict-related factors that influenced the distribution and productivity of Ukraine’s cropland from 2013 to 2023.In addition,we propose a novel method using machine learning models to isolate the impact of conflict on cropland.Our findings reveal that,prior to the conflict,the spatial pattern of Ukraine’s mean cultivation rate was primarily shaped by natural factors—such as climate,soil properties,and elevation—whereas socio-economic factors(e.g.,GDP and population size)exerted a weaker influence.Interannual dynamics in productive cropland area were largely driven by climate variability.The onset of conflict in 2022 dramatically altered this landscape,with nearly half of the cropland grid cells experiencing a conflict-induced reduction.Notably,almost half of the interannual reduction in productive cropland in 2022 was attributed to climate change.Remarkably,in 2023,the return of displaced populations and favorable climatic conditions in many oblasts contributed to a positive trend in cropland reclamation.Despite this,the total area of productive cropland in 2023 remained below expected levels,due to ongoing conflict and localized droughts.Finally,we highlight the urgent need to adopt a two-pronged approach that addresses both the immediate impacts of conflict and the ongoing threats posed by climate change to ensure the resilience and sustainability of agricultural systems in post-conflict areas.展开更多
Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoti...Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.展开更多
This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data fr...This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH_(3)VCDs in the YRD between 2014 and 2020.The spatial distribution analysis revealed higher NH_(3)concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural activities.NH_(3)VCDs in the YRD region increased significantly(65.18%)from 2008 to 2020.The highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to 2020.Agricultural emissions dominated NH_(3)VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones.Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH_(3)VCDs.The rise in NH_(3)VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO_(2),as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model.The concentration changes of acidic gases contribute to over 80%of the interannual variations in NH_(3)VCDs.This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases.Effective emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD.展开更多
The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ec...The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.展开更多
Seagrass beds are crucial coastal ecosystems,functioning as vital blue carbon sinks and natural ecological barriers.However,these ecosystems are increasingly threatened by global climate events,coastal development,and...Seagrass beds are crucial coastal ecosystems,functioning as vital blue carbon sinks and natural ecological barriers.However,these ecosystems are increasingly threatened by global climate events,coastal development,and water eutrophication,making them some of the most endangered ecosystems worldwide.In the Yellow Sea and Bohai Sea regions,seagrass bed assessment and monitoring have been largely overlooked.Thus,strengthening research efforts is necessary to identify current distribution patterns and long-term changes in seagrass bed resources.This study focused on a seagrass bed in Sanggou Bay,Rongcheng,using remote sensing(RS)and geographic information system technologies to analyze multisource satellite data from the US Landsat and Chinese resource satellite series.By combining RS indexes with historical survey data,large-scale temporal and geographic distribution data for seagrass beds were obtained in the study area from 1985 to 2022.The spatial distribution and evolution trends of the seagrass bed were analyzed using a water depth inversion model,and the factors driving its degradation were identified.Results indicated that the seagrass bed area in Sanggou Bay fluctuated between 100 and 140 km^(2) from 1985 to 2010.During 2010–2013,dynamic changes in the seagrass bed area increased,with a considerable decrease in its overall size.After 2014,changes were minimal,indicating a notably stable state.Seagrass bed degradation in Sanggou Bay is influenced by high-intensity human activities,pollution from coastal land sources,raft cultures,underwater terrain conditions,and sedimentary environmental factors.The findings offer essential insights for developing seagrass restoration and protection strategies in Sanggou Bay and contribute to the broader scientific efforts for coastal ecosystem conservation and rehabilitation.展开更多
Vegetation not only plays a critical role in regulating regional climate,hydrological cycles,carbon sequestration,and oxygen release,but also is directly linked to ecosystem stability and regional sustainable developm...Vegetation not only plays a critical role in regulating regional climate,hydrological cycles,carbon sequestration,and oxygen release,but also is directly linked to ecosystem stability and regional sustainable development.In this study,based on the data of kNDVI in Jiangsu Province(an economically developed coastal region in eastern China)from 2002 to 2022,the spatial and temporal dynamics of vegetation in the province were systematically analyzed by using the Theil-Sen slope estimation and Mann-Kendall trend test methods.The results indicate that vegetation coverage in Jiangsu Province generally followed a trend of"fluctuation in the early period and improvement in the later period"from 2002 to 2022.Spatially,kNDVI changes exhibited clear heterogeneity,with an overall pattern of"decline in the south,increase in the north,and stability in the central region".Based on the 21-year mean of kNDVI,it is found that vegetation conditions were relatively better in northern and central Jiangsu,while lower mean of kNDVI was observed in southern Jiangsu(e.g.,Suzhou,Wuxi,and Changzhou),reflecting the pressure of accelerating urbanization on green space coverage.Further investigation into the driving factors of changes in vegetation reveals that social factors had the strongest influence,with a path coefficient of-0.86,followed by topographic and climatic factors.This spatial differentiation pattern and the identified driving factors highlight ongoing conflicts between the economic development and ecological conservation in Jiangsu Province.In the future,land use structure should be optimized based on local conditions,and coordinated development between ecological restoration and urban expansion should be strengthened.展开更多
The impact of climate change on vegetation ecosystems is a prominent focus in global climate change research.The climate change affects vegetation growth and ecosystem stability in the upper reaches of the Yellow Rive...The impact of climate change on vegetation ecosystems is a prominent focus in global climate change research.The climate change affects vegetation growth and ecosystem stability in the upper reaches of the Yellow River(UYR).However,the spatiotemporal patterns and driving mechanisms of vegetation growth status(VGS)in the region remain poorly understood.Based on the hydrological model PLS,an innovative WEP-CHC model was developed by integrating regional environmental and vegetation growth characteristics.Furthermore,combined with the PLS-SEM model and other methods,this study systematically investigated the spatiotemporal patterns and driving mechanisms of VGS in the UYR.The results indicated that:①VGS exhibited significant spatiotemporal variation trends within the study area.In the study period of 1970–2020,the GPP onset time was significantly advanced(p<0.05)while the GPP peak value was significantly increased.Spatial analysis revealed significant spatial complexity in the GPP onset time and peak values across the region.②Soil freeze-thaw conditions significantly influenced VGS(p<0.05).The complete thawing time of permafrost was closely coincided with the GPP onset time,with a correlation coefficient exceeding 0.84.After controlling soil freeze-thaw effects using partial correlation analysis,it was found that better initial soil hydrothermal conditions would lead to better VGS;③The model constructed with annual hydrothermal conditions(AHC),soil freeze-thaw period(SFTP),vegetation growth season(VGS),initial soil hydrothermal conditions(ISHC),and annual solar radiation conditions(ASRC),demonstrated good explanatory power for vegetation growth.The R^(2)values of PLS-SEM were above 0.76 in all five subregions.However,their effects on VGS varied significantly across subregions.Overall,AHC and SFTP were the dominant factors in all subregions.Furthermore,the impacts of ISHC and VGC were statistically insignificant,whereas the effects of ASRC exhibited high complexity.This study not only provides new insights into the current state of hydrological-ecological coupling in the UYR but also offers a new tool for ecological conservation and sustainable water management in other cold regions and similar watersheds worldwide.展开更多
As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification...As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region.展开更多
Due to the multiple impacts of global climate change and anthropogenic disturbances,regional ecological landscapes have been developing towards fragmentation.How to quantitatively measure regional ecological landscape...Due to the multiple impacts of global climate change and anthropogenic disturbances,regional ecological landscapes have been developing towards fragmentation.How to quantitatively measure regional ecological landscape fragmentation and identify its key drivers is an important foundation for regional biodiversity conservation and ecosystem restoration.Taking the Guanzhong Plain Urban Agglomeration(GPUA),China as the research object,this paper proposes a comprehensive framework that integrates landscape pattern index,principal component analysis,random forest(RF)and other methods to quantitatively analyze the spatial and temporal evolution of ecological landscape fragmentation and its driving factors.The results show that:1)cropland,forestland and grassland showed significant spatial differentiation in the landscape pattern index,and the change of their mean values indicated that cropland and forestland show a trend of‘little decrease-continuous increase’.Spatially,the northwestern and southeastern regions showed significant fragmentation and prominent spatial heterogeneity.2)From 2010 to 2020,the landscape fragmentation of cropland and forestland increased by 71%and 20%,respectively,while that of grassland decreased by 33%,indicating that the degree of landscape fragmentation of cropland changed more drastically than that of other ecological land.3)It was found that slope was the most important factor affecting landscape fragmentation of ecological land.In addition,road density had a significant effect on landscape fragmentation of cropland and forestland,but the min-distance between patches and the county center had an important effect on landscape fragmentation of grassland.This study can provide theoretical references for urban agglomeration planning and sustainable landscape management on a regional scale.展开更多
Using gradually regression analysis to establish the driving force model of utilized change of cultivated land in Gonghe County, and using path analysis, correlation analysis, partial correlation analysis and system d...Using gradually regression analysis to establish the driving force model of utilized change of cultivated land in Gonghe County, and using path analysis, correlation analysis, partial correlation analysis and system dynamics method to inspect the effect of driving changing on cultivated land change under different change situations. Driving factors, action mechanism and process of utilized change of cultivated land were analyzed from the county territory scale level. At last, some corresponding policies and measures were put forward.展开更多
The contribution rate of ecosystem service value variation was used to analyze the effects of land use changes on the changes of ecosystem service value in Xingguo County during 1996-2005.Grey integrated correlation w...The contribution rate of ecosystem service value variation was used to analyze the effects of land use changes on the changes of ecosystem service value in Xingguo County during 1996-2005.Grey integrated correlation was employed to explore the contribution level of the indicators such as total population,urbanization level,proportion of primary industry and investment of social fixed assets on ecosystem service value,and the correlation analysis was also carried out.The results showed that the ecosystem service value in Xingguo County during 1996-2005 mainly was woodland,and the decrease of woodland area was the major reason for the sustained reduction of ecosystem service value.With the further increase of market demand and the incentives of local government,the garden area rapidly increased during 2001-2005,and the influence degree of garden towards the changes of ecosystem service value was only second to woodland,ranking No.2.Four socio-economic indicators had different correlation degree with ecosystem service value during the different research periods.Total population,urbanization level and proportion of primary industry had high correlation degree with ecosystem service value,whereas the influence degree of various socio-economic indicators on ecosystem service value was equal with each other day by day.Urbanization level,investment of social fixed assets and total population had significant negative correlation with ecosystem service value,while the proportion of primary industry had positive correlation with ecosystem service value.展开更多
Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 k...Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy ifeld, soil and livestock breeding, this paper ifrstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index （LMDI） model. The results show：（1） The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy ifeld, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39%of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; （2） There is an obvious difference among regions：the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84%from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into ifve types, namely agricultural materials dominant type, paddy ifeld dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; （3） Compared with 1995, efifciency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively;while economy factor increase carbon emissions by 113.16%.展开更多
The rapid development in Beijing, the capital of China, has resulted in serious air pollution problems. Meanwhile great efforts have been made to improve the air quality, especially since 1998. The variation in air qu...The rapid development in Beijing, the capital of China, has resulted in serious air pollution problems. Meanwhile great efforts have been made to improve the air quality, especially since 1998. The variation in air quality under the interaction of pollution and control in this mega city has attracted much attention. We analyzed the changes in ambient air quality in Beijing since the 1980’s using the Daniel trend test based on data from long-term monitoring stations. The results showed that different pollutants displayed three trends： a decreasing trend, an increasing trend and a flat trend. SO2, dustfall, B[a]P, NO2 and PM10 fit decreasing trend pattern, while NOx showed an increasing trend, and CO, ozone pollution, total suspended particulate （TSP）, as well as Pb fit the flat trend. The cause of the general air pollution in Beijing has changed from being predominantly related to coal burning to mixed traffic exhaust and coal burning related pollution. Seasonally, the pollution level is typically higher during the heating season from November to the following March. The interaction between pollution sources change and implementation of air pollution control measures was the main driving factor that caused the variation in air quality. Changes of industrial structure and improved energy effciency, the use of clean energy and preferred use of clean coal, reduction in pollution sources, and implementation of advanced environmental standards have all contributed to the reduction in air pollution, particularly since 1998.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
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
[Objective] The aim was to provide theoretical basis for the study of underground water dynamic changes in Songnen Plain in Jilin Province.[Method] The dynamic changes and driving factors for the underground water in ...[Objective] The aim was to provide theoretical basis for the study of underground water dynamic changes in Songnen Plain in Jilin Province.[Method] The dynamic changes and driving factors for the underground water in Songnen Plain in Jilin Province was expounded.[Result] Since 1960s,the temperature in the Songnen Plain in Jilin Province increased gradually.The average temperature increased 2℃;precipitation reduced gradually.Especially,the trend of precipitation reduction in west area was more distinct;in the meantime,the development of underground water augmented gradually and reached 2 800 million m3 in 2008.Driven by many factors,regional underground water level had distinct changes.Potential water position reduced greatly in northwest fan-shaped area.The one in other places were stable and even increased in certain parts;confined water position decreased quickly in general and it increased in certain parts.[Conclusion] The general deterioration trend of underground water environment was inevitable.But,the deterioration process can be eased through scientific planning and regional underground water resources so as to realize sustainable utilization of regional underground water resources.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
Zoige Plateau wetlands are located in the northeastern corner of the Qinghai-Tibet Plateau.The landscape pattern evolution processes in the Zoige Plateau and their driving factors were identified by analyzing the dyna...Zoige Plateau wetlands are located in the northeastern corner of the Qinghai-Tibet Plateau.The landscape pattern evolution processes in the Zoige Plateau and their driving factors were identified by analyzing the dynamic changes in landscape modification and conversion and their dynamic rates of alpine wetlands over the past four decades.The results showed that the landscape conversion between wetlands and non-wetlands mainly occurred during the period from 1966 to 1986.The marsh wetland area converted from lake and river wetlands was larger because of swamping compared to other wetland landscapes.Meanwhile,the larger area of marsh wetlands was also converted to lake wetlands more than other types of wetlands.The modification processes mainly occurred among natural wetland landscapes in the first three periods.Obvious conversions were observed between wetland and nonwetland landscapes(i.e.,forestland,grassland,and other landscapes) in the Zoige Plateau.These natural wetland landscapes such as river,lake and marsh wetlands showed a net loss over the past four decades,whereas artificial wetland landscapes(i.e.,paddy field and reservoir and pond wetlands) showed a net decrease.The annual dynamic rate of the whole wetland landscape was 0.72%,in which the annual dynamic rate of river wetlands was the highest,followed by lake wetlands,while marsh wetlands had the lowest dynamic rate.The integrated landscape dynamic rate showed a decreasing trend in the first three periods.The changes in wetland landscape patterns were comprehensively controlled by natural factors and human activities,especially human activities play an important role in changing wetland landscape patterns.展开更多
For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological...For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological index(RSEI)was calculated for the Lijiang River Basin in Guangxi Zhuang Autonomous Region for 1991,2001,2011,and 2021.Spatial autocorrelation analysis was employed to investigate spatiotemporal variations in the ecological environmental quality of the Lijiang River Basin.Furthermore,geographic detectors were used to quantitatively analyze influencing factors and their interaction effects on ecological environmental quality.The results verified that:1)From 1991 to 2021,the ecological environmental quality of the Lijiang River Basin demonstrated significant improvement.The area with good and excellent ecological environmental quality in proportion increased by 19.69%(3406.57 km^(2)),while the area with fair and poor ecological environmental quality in proportion decreased by 10.76%(1860.36 km^(2)).2)Spatially,the ecological environmental quality of the Lijiang River Basin exhibited a pattern of low quality in the central region and high quality in the periphery.Specifically,poor ecological environmental quality characterized the Guilin urban area,Pingle County,and Lingchuan County.3)From 1991 to 2021,a significant positive spatial correlation was observed in ecological environmental quality of the Lijiang River Basin.Areas with high-high agglomeration were predominantly forests and grasslands,indicating good ecological environmental quality,whereas areas with low-low agglomeration were dominated by cultivated land and construction land,indicating poor ecological environmental quality.4)Annual average precipitation and temperature exerted the most significant influence on the ecological environmental quality of the basin,and their interactions with other factors had the great influence.This study aimed to enhance understanding of the evolution of the ecological environment in the Lijiang River Basin of Guangxi Zhuang Autonomous Region and provide scientific guidance for decision-making and management related to ecology in the region.展开更多
基金The National Key Research and Development Program of China,No.2023YFC3206601。
文摘Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning.
基金supported in part by the National Natural Science Foundation of China(Grants No.41971284 and 42371321)the Key Research and Development Program of Hubei Province(Grant No.2025BAB024).
文摘Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in Ukraine,particularly in the context of the 2022 Russia-Ukraine conflict.We provide the first comprehensive assessment of both conflict-and non-conflict-related factors that influenced the distribution and productivity of Ukraine’s cropland from 2013 to 2023.In addition,we propose a novel method using machine learning models to isolate the impact of conflict on cropland.Our findings reveal that,prior to the conflict,the spatial pattern of Ukraine’s mean cultivation rate was primarily shaped by natural factors—such as climate,soil properties,and elevation—whereas socio-economic factors(e.g.,GDP and population size)exerted a weaker influence.Interannual dynamics in productive cropland area were largely driven by climate variability.The onset of conflict in 2022 dramatically altered this landscape,with nearly half of the cropland grid cells experiencing a conflict-induced reduction.Notably,almost half of the interannual reduction in productive cropland in 2022 was attributed to climate change.Remarkably,in 2023,the return of displaced populations and favorable climatic conditions in many oblasts contributed to a positive trend in cropland reclamation.Despite this,the total area of productive cropland in 2023 remained below expected levels,due to ongoing conflict and localized droughts.Finally,we highlight the urgent need to adopt a two-pronged approach that addresses both the immediate impacts of conflict and the ongoing threats posed by climate change to ensure the resilience and sustainability of agricultural systems in post-conflict areas.
基金Supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0102)the China Scholarship Council Program(202406190114)。
文摘Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.
基金supported by the Joint Funds of the National Natural Science Foundation of China(No.U21A2027)the New Cornerstone Science Foundation through the XPLORER PRIZE(2023-1033).
文摘This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to 2020.Utilizing data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH_(3)VCDs in the YRD between 2014 and 2020.The spatial distribution analysis revealed higher NH_(3)concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural activities.NH_(3)VCDs in the YRD region increased significantly(65.18%)from 2008 to 2020.The highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to 2020.Agricultural emissions dominated NH_(3)VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones.Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH_(3)VCDs.The rise in NH_(3)VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO_(2),as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model.The concentration changes of acidic gases contribute to over 80%of the interannual variations in NH_(3)VCDs.This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases.Effective emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD.
基金funded by the Central University D Project(HFW230600022)National Natural Science Foundation of China(71973021)+1 种基金National Natural Science Foundation Youth Funding Project(72003022)Heilongjiang Province University Think Tank Open Topic(ZKKF2022173).
文摘The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(No.2022QNLM 050302-4)the Geological Survey Project of the China Geological Survey(No.DD20230071)+1 种基金the China Geological Survey Project‘Investigation and Monitoring of the Coastal Geological Environment of the Yangtze River Estuary’(No.DD20242714)the cooperation fund of Collaborative Research on Marine Geological Environment and Hazards in the Yangtze River Delta and Red River Delta.
文摘Seagrass beds are crucial coastal ecosystems,functioning as vital blue carbon sinks and natural ecological barriers.However,these ecosystems are increasingly threatened by global climate events,coastal development,and water eutrophication,making them some of the most endangered ecosystems worldwide.In the Yellow Sea and Bohai Sea regions,seagrass bed assessment and monitoring have been largely overlooked.Thus,strengthening research efforts is necessary to identify current distribution patterns and long-term changes in seagrass bed resources.This study focused on a seagrass bed in Sanggou Bay,Rongcheng,using remote sensing(RS)and geographic information system technologies to analyze multisource satellite data from the US Landsat and Chinese resource satellite series.By combining RS indexes with historical survey data,large-scale temporal and geographic distribution data for seagrass beds were obtained in the study area from 1985 to 2022.The spatial distribution and evolution trends of the seagrass bed were analyzed using a water depth inversion model,and the factors driving its degradation were identified.Results indicated that the seagrass bed area in Sanggou Bay fluctuated between 100 and 140 km^(2) from 1985 to 2010.During 2010–2013,dynamic changes in the seagrass bed area increased,with a considerable decrease in its overall size.After 2014,changes were minimal,indicating a notably stable state.Seagrass bed degradation in Sanggou Bay is influenced by high-intensity human activities,pollution from coastal land sources,raft cultures,underwater terrain conditions,and sedimentary environmental factors.The findings offer essential insights for developing seagrass restoration and protection strategies in Sanggou Bay and contribute to the broader scientific efforts for coastal ecosystem conservation and rehabilitation.
文摘Vegetation not only plays a critical role in regulating regional climate,hydrological cycles,carbon sequestration,and oxygen release,but also is directly linked to ecosystem stability and regional sustainable development.In this study,based on the data of kNDVI in Jiangsu Province(an economically developed coastal region in eastern China)from 2002 to 2022,the spatial and temporal dynamics of vegetation in the province were systematically analyzed by using the Theil-Sen slope estimation and Mann-Kendall trend test methods.The results indicate that vegetation coverage in Jiangsu Province generally followed a trend of"fluctuation in the early period and improvement in the later period"from 2002 to 2022.Spatially,kNDVI changes exhibited clear heterogeneity,with an overall pattern of"decline in the south,increase in the north,and stability in the central region".Based on the 21-year mean of kNDVI,it is found that vegetation conditions were relatively better in northern and central Jiangsu,while lower mean of kNDVI was observed in southern Jiangsu(e.g.,Suzhou,Wuxi,and Changzhou),reflecting the pressure of accelerating urbanization on green space coverage.Further investigation into the driving factors of changes in vegetation reveals that social factors had the strongest influence,with a path coefficient of-0.86,followed by topographic and climatic factors.This spatial differentiation pattern and the identified driving factors highlight ongoing conflicts between the economic development and ecological conservation in Jiangsu Province.In the future,land use structure should be optimized based on local conditions,and coordinated development between ecological restoration and urban expansion should be strengthened.
基金funded by the National Key R&D Program(2021YFC3200203,2023YFC3206303)the Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)National Natural Science Foundation of China(52394233,52122902).
文摘The impact of climate change on vegetation ecosystems is a prominent focus in global climate change research.The climate change affects vegetation growth and ecosystem stability in the upper reaches of the Yellow River(UYR).However,the spatiotemporal patterns and driving mechanisms of vegetation growth status(VGS)in the region remain poorly understood.Based on the hydrological model PLS,an innovative WEP-CHC model was developed by integrating regional environmental and vegetation growth characteristics.Furthermore,combined with the PLS-SEM model and other methods,this study systematically investigated the spatiotemporal patterns and driving mechanisms of VGS in the UYR.The results indicated that:①VGS exhibited significant spatiotemporal variation trends within the study area.In the study period of 1970–2020,the GPP onset time was significantly advanced(p<0.05)while the GPP peak value was significantly increased.Spatial analysis revealed significant spatial complexity in the GPP onset time and peak values across the region.②Soil freeze-thaw conditions significantly influenced VGS(p<0.05).The complete thawing time of permafrost was closely coincided with the GPP onset time,with a correlation coefficient exceeding 0.84.After controlling soil freeze-thaw effects using partial correlation analysis,it was found that better initial soil hydrothermal conditions would lead to better VGS;③The model constructed with annual hydrothermal conditions(AHC),soil freeze-thaw period(SFTP),vegetation growth season(VGS),initial soil hydrothermal conditions(ISHC),and annual solar radiation conditions(ASRC),demonstrated good explanatory power for vegetation growth.The R^(2)values of PLS-SEM were above 0.76 in all five subregions.However,their effects on VGS varied significantly across subregions.Overall,AHC and SFTP were the dominant factors in all subregions.Furthermore,the impacts of ISHC and VGC were statistically insignificant,whereas the effects of ASRC exhibited high complexity.This study not only provides new insights into the current state of hydrological-ecological coupling in the UYR but also offers a new tool for ecological conservation and sustainable water management in other cold regions and similar watersheds worldwide.
基金the National Natural Science Foundation of China(Grant No.42301336)the Open Research Fund of Henan Provincial Key Laboratory of Hydrosphere and Watershed Water Security(Grant No.HWWSF202302).
文摘As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region.
基金Under the auspices of National Natural Science Foundation of China(No.42271214)Key Research Program of Gansu Province(No.23ZDKA0004)Natural Science Foundation of Gansu Province(No.25JRRA212,21JR7RA281,22JR11RA149,24JRR A250)。
文摘Due to the multiple impacts of global climate change and anthropogenic disturbances,regional ecological landscapes have been developing towards fragmentation.How to quantitatively measure regional ecological landscape fragmentation and identify its key drivers is an important foundation for regional biodiversity conservation and ecosystem restoration.Taking the Guanzhong Plain Urban Agglomeration(GPUA),China as the research object,this paper proposes a comprehensive framework that integrates landscape pattern index,principal component analysis,random forest(RF)and other methods to quantitatively analyze the spatial and temporal evolution of ecological landscape fragmentation and its driving factors.The results show that:1)cropland,forestland and grassland showed significant spatial differentiation in the landscape pattern index,and the change of their mean values indicated that cropland and forestland show a trend of‘little decrease-continuous increase’.Spatially,the northwestern and southeastern regions showed significant fragmentation and prominent spatial heterogeneity.2)From 2010 to 2020,the landscape fragmentation of cropland and forestland increased by 71%and 20%,respectively,while that of grassland decreased by 33%,indicating that the degree of landscape fragmentation of cropland changed more drastically than that of other ecological land.3)It was found that slope was the most important factor affecting landscape fragmentation of ecological land.In addition,road density had a significant effect on landscape fragmentation of cropland and forestland,but the min-distance between patches and the county center had an important effect on landscape fragmentation of grassland.This study can provide theoretical references for urban agglomeration planning and sustainable landscape management on a regional scale.
基金Supported by the National Social Science Fund(06XMZ014)~~
文摘Using gradually regression analysis to establish the driving force model of utilized change of cultivated land in Gonghe County, and using path analysis, correlation analysis, partial correlation analysis and system dynamics method to inspect the effect of driving changing on cultivated land change under different change situations. Driving factors, action mechanism and process of utilized change of cultivated land were analyzed from the county territory scale level. At last, some corresponding policies and measures were put forward.
基金Supported by Natural Science Foundation of Jiangxi Province"Research on Optimization Model of Land Use in Southern Hilly Region with Red Soil in Jiangxi Province based on Ecological Security Evaluation"(2008GQH0057)Educational Commission of Jiangxi Province"Research on Scenario Simulation of Land Use Security Pattern in Southern Hilly Region with Red Soil in Jiangxi Province" (GJJ09557)Innovative Experimental Projects of National University Students"Research on Land Use Ecological Security Assessment in Hilly Region with Red Soil based on GIS-Xingguo County in Jiangxi Province as an Example"(101042124)~~
文摘The contribution rate of ecosystem service value variation was used to analyze the effects of land use changes on the changes of ecosystem service value in Xingguo County during 1996-2005.Grey integrated correlation was employed to explore the contribution level of the indicators such as total population,urbanization level,proportion of primary industry and investment of social fixed assets on ecosystem service value,and the correlation analysis was also carried out.The results showed that the ecosystem service value in Xingguo County during 1996-2005 mainly was woodland,and the decrease of woodland area was the major reason for the sustained reduction of ecosystem service value.With the further increase of market demand and the incentives of local government,the garden area rapidly increased during 2001-2005,and the influence degree of garden towards the changes of ecosystem service value was only second to woodland,ranking No.2.Four socio-economic indicators had different correlation degree with ecosystem service value during the different research periods.Total population,urbanization level and proportion of primary industry had high correlation degree with ecosystem service value,whereas the influence degree of various socio-economic indicators on ecosystem service value was equal with each other day by day.Urbanization level,investment of social fixed assets and total population had significant negative correlation with ecosystem service value,while the proportion of primary industry had positive correlation with ecosystem service value.
基金supported by the National Natural Science Foundation of China (71273105)the Fundamental Research Funds for the Central Universities,China (2013YB12)
文摘Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy ifeld, soil and livestock breeding, this paper ifrstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index （LMDI） model. The results show：（1） The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy ifeld, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39%of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; （2） There is an obvious difference among regions：the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84%from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into ifve types, namely agricultural materials dominant type, paddy ifeld dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; （3） Compared with 1995, efifciency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively;while economy factor increase carbon emissions by 113.16%.
基金supported by the State Key Program of National Natural Science Foundation of China (No.41030744)the Specialized Research Fund of State Key Laboratory of Urban and Regional Ecology
文摘The rapid development in Beijing, the capital of China, has resulted in serious air pollution problems. Meanwhile great efforts have been made to improve the air quality, especially since 1998. The variation in air quality under the interaction of pollution and control in this mega city has attracted much attention. We analyzed the changes in ambient air quality in Beijing since the 1980’s using the Daniel trend test based on data from long-term monitoring stations. The results showed that different pollutants displayed three trends： a decreasing trend, an increasing trend and a flat trend. SO2, dustfall, B[a]P, NO2 and PM10 fit decreasing trend pattern, while NOx showed an increasing trend, and CO, ozone pollution, total suspended particulate （TSP）, as well as Pb fit the flat trend. The cause of the general air pollution in Beijing has changed from being predominantly related to coal burning to mixed traffic exhaust and coal burning related pollution. Seasonally, the pollution level is typically higher during the heating season from November to the following March. The interaction between pollution sources change and implementation of air pollution control measures was the main driving factor that caused the variation in air quality. Changes of industrial structure and improved energy effciency, the use of clean energy and preferred use of clean coal, reduction in pollution sources, and implementation of advanced environmental standards have all contributed to the reduction in air pollution, particularly since 1998.
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 Chinese Geographic Investigation Bureau Financial Support Project(1212010813093)~~
文摘[Objective] The aim was to provide theoretical basis for the study of underground water dynamic changes in Songnen Plain in Jilin Province.[Method] The dynamic changes and driving factors for the underground water in Songnen Plain in Jilin Province was expounded.[Result] Since 1960s,the temperature in the Songnen Plain in Jilin Province increased gradually.The average temperature increased 2℃;precipitation reduced gradually.Especially,the trend of precipitation reduction in west area was more distinct;in the meantime,the development of underground water augmented gradually and reached 2 800 million m3 in 2008.Driven by many factors,regional underground water level had distinct changes.Potential water position reduced greatly in northwest fan-shaped area.The one in other places were stable and even increased in certain parts;confined water position decreased quickly in general and it increased in certain parts.[Conclusion] The general deterioration trend of underground water environment was inevitable.But,the deterioration process can be eased through scientific planning and regional underground water resources so as to realize sustainable utilization of regional underground water resources.
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financially supported by National Natural Science Foundation of China(Grant No. 51179006)China National Funds for Distinguished Young Scientists (Grant No.51125035)+2 种基金National Science Foundation for Innovative Research Group (Grant No. 51121003)the Program for New Century Excellent Talents in University (NECT-10-0235)the Fok Ying Tung Foundation (Grant No. 132009)
文摘Zoige Plateau wetlands are located in the northeastern corner of the Qinghai-Tibet Plateau.The landscape pattern evolution processes in the Zoige Plateau and their driving factors were identified by analyzing the dynamic changes in landscape modification and conversion and their dynamic rates of alpine wetlands over the past four decades.The results showed that the landscape conversion between wetlands and non-wetlands mainly occurred during the period from 1966 to 1986.The marsh wetland area converted from lake and river wetlands was larger because of swamping compared to other wetland landscapes.Meanwhile,the larger area of marsh wetlands was also converted to lake wetlands more than other types of wetlands.The modification processes mainly occurred among natural wetland landscapes in the first three periods.Obvious conversions were observed between wetland and nonwetland landscapes(i.e.,forestland,grassland,and other landscapes) in the Zoige Plateau.These natural wetland landscapes such as river,lake and marsh wetlands showed a net loss over the past four decades,whereas artificial wetland landscapes(i.e.,paddy field and reservoir and pond wetlands) showed a net decrease.The annual dynamic rate of the whole wetland landscape was 0.72%,in which the annual dynamic rate of river wetlands was the highest,followed by lake wetlands,while marsh wetlands had the lowest dynamic rate.The integrated landscape dynamic rate showed a decreasing trend in the first three periods.The changes in wetland landscape patterns were comprehensively controlled by natural factors and human activities,especially human activities play an important role in changing wetland landscape patterns.
基金supported by the Guangxi Natural Science Foundation(2020GXNSFAA297266)Doctoral Research Foundation of Guilin University of Technology(GUTQDJJ2007059)Guangxi Hidden Metallic Mineral Exploration Key Laboratory。
文摘For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological index(RSEI)was calculated for the Lijiang River Basin in Guangxi Zhuang Autonomous Region for 1991,2001,2011,and 2021.Spatial autocorrelation analysis was employed to investigate spatiotemporal variations in the ecological environmental quality of the Lijiang River Basin.Furthermore,geographic detectors were used to quantitatively analyze influencing factors and their interaction effects on ecological environmental quality.The results verified that:1)From 1991 to 2021,the ecological environmental quality of the Lijiang River Basin demonstrated significant improvement.The area with good and excellent ecological environmental quality in proportion increased by 19.69%(3406.57 km^(2)),while the area with fair and poor ecological environmental quality in proportion decreased by 10.76%(1860.36 km^(2)).2)Spatially,the ecological environmental quality of the Lijiang River Basin exhibited a pattern of low quality in the central region and high quality in the periphery.Specifically,poor ecological environmental quality characterized the Guilin urban area,Pingle County,and Lingchuan County.3)From 1991 to 2021,a significant positive spatial correlation was observed in ecological environmental quality of the Lijiang River Basin.Areas with high-high agglomeration were predominantly forests and grasslands,indicating good ecological environmental quality,whereas areas with low-low agglomeration were dominated by cultivated land and construction land,indicating poor ecological environmental quality.4)Annual average precipitation and temperature exerted the most significant influence on the ecological environmental quality of the basin,and their interactions with other factors had the great influence.This study aimed to enhance understanding of the evolution of the ecological environment in the Lijiang River Basin of Guangxi Zhuang Autonomous Region and provide scientific guidance for decision-making and management related to ecology in the region.
