Landscape ecological risk assessment and its driving factors in the Weihe River basin,China

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.

Prediction and driving factors of forest fire occurrence in Jilin Province,China

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.

Dynamic Development Characteristics and Driving Factors of High Quality Development Level in China’s Five Major Urban Agglomerations

High-quality development is the primary task of comprehensively building a socialist,modern country,as well as the primary task of building urban agglomerations in China.Based on the five development concepts,this paper used the entropy method to measure the High Quality Development Index(HQDI)of the five major urban agglomerations.The results showed that the HQDI of the five major urban agglomerations shows a fluctuating upward trend.First,using the Dagum Gini coefficient to explore the sources of HQDI development differences in urban agglomerations,we found that the main source of HQDI differences in urban agglomerations was inter-regional differences,while intra-regional differences were not important.Second,kernel density estimation was used to test the dynamic evolution trend of HQDI within urban agglomerations.There was a polarisation phenomenon in the HQDI of urban agglomerations,such as the Pearl River Delta urban agglomeration and the Chengdu-Chongqing urban agglomeration.But overall,the degree of imbalance had decreased.Third,using geographic detectors to examine the driving factors of HQDI in urban agglomerations,we found that the main driving forces for improving HQDI in urban agglomerations were economic growth,artificial intelligence technology and fiscal decentralisation.All the interaction factors had greater explanatory power for the spatial differentiation of HQDI,which can be divided into two types:two-factor improvement and non-linear improvement.This study is conducive to improving and enriching the theoretical system for evaluating the high quality development of urban agglomerations,and provides policy references for promoting the high quality development of urban agglomerations.

Analysis of the Spatiotemporal Variation Characteristics and Driving Factors of Land Vegetation GPP in a Certain Region of Asia

Gross primary productivity (GPP) of vegetation is a critical indicator of ecosystem growth and carbon sequestration. The spatiotemporal variation characteristics of land vegetation GPP trends in a specific region of Asia from 2001 to 2020 were analyzed by Sen and MK trend analysis methods in this study .Moreover , a GPP change attribution model was established to explore the driving influences of factors such as Leaf Area Index (LAI), Land Surface Temperature (LST), Vapor Pressure Deficit (VPD), Soil Moisture, Solar Radiation and Wind Speed on GPP. The results indicate that summer GPP values are significantly higher than those in other months, accounting for 60.8% of the annual total GPP;spring and autumn contribute 18.91% and 13.04%, respectively. In winter, due to vegetation being nearly dormant, the contribution is minimal at 7.19%. Spatially, GPP shows a decreasing trend from southeast to northwest. LAI primarily drives the spatial and seasonal variations of regional GPP, while VPD, surface temperature, solar radiation, and soil moisture have varying impacts on GPP across different dimensions. Additionally, wind speed exhibits a minor contribution to GPP across different dimensions.

Spatiotemporal variations of drought and driving factors based on multiple remote sensing drought indices:A case study in karst areas of southwest China

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.

Evaluation of Postoperative Psychological Distress and Its Driving Factors in Patients with Oral and Maxillofacial Malignant Tumors

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.

Multi-scenario Simulation for 2060 and Driving Factors of the Eco-spatial Carbon Sink in the Beibu Gulf Urban Agglomeration, China

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.

Characteristics and driving factors of abandoned cultivated land in the hilly regions of southern China:A case study in Longnan,Jiangxi Province

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.

Response of Ecosystem Service Value Based on Land Use Changes and Analysis of its Driving Factors in Typical Hilly Region with Red Soil

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.

Quantitatively determine the dominant driving factors of the spatial–temporal changes of vegetation NPP in the Hengduan Mountain area during 2000-2015

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.

Analysis of the Groundwater System Change and Driving Factors in Songnen Plain in Jilin Province

[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.

Landscape Pattern Evolution Processes of Alpine Wetlands and Their Driving Factors in the Zoige Plateau of China

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.

Study of the intensity and driving factors of land use/cover change in the Yarlung Zangbo River, Nyang Qu River, and Lhasa River region, Qinghai-Tibet Plateau of China

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.

Spatiotemporal variations and driving factors of habitat quality in the loess hilly area of the Yellow River Basin:A case study of Lanzhou City,China

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.

Spatiotemporal variation of forest land and its driving factors in the agropastoral ecotone of northern China

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.

Study on the driving factors and regulation mode for coal production capacity

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.

Spatiotemporal changeof vegetationcoverage recovery and its driving factors in the Wenchuan earthquake-hit areas

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.

Spatial variability and driving factors of soil multifunctionality in drylands of China

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.

The driving factors and their interactions of fire occurrence in Greater Khingan Mountains, China

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.

Driving factors of forest landscape change in Yiluo River basin

The expansion of agriculture is posited as one of the main dynamics of forest landscape change globally, and the robust modeling of these processes is important for policy as well as academic concern. This paper concerns a relatively small area of Yiluo River catchment where considerable attention has been paid to slow down the process of the expansion of agriculture into the remaining natural forests. In the present study, we reconstructed the former forest landscape structure and elucidated the landscape change during a period of about 15 years. Three sets （1987, 1996 and 2002） of maps derived from Landsat-5 images were used for analyses. The result showed that there was a decrease in the area of the forest landscape from 995.60 km2 in 1987 to 650.50 km2 in 2002. Then we examined the degree to which forest landscape conversion could be attributed to a set of factors identified as significant at broader scales, namely topography, distribution of the village clusters （centroids）, distance from villages （centroids）, and distance from forest edge （1987）. By using ＂spatial analysis＂ in Arc/gis 8.3, the correlation between forest landscape change and driving factors was constructed. This study found that forest landscape conversion in this region was largely explained by elevation, slope and proximity to village.