Spatiotemporal pattern of climate change in the China-Myanmar Economic Corridor from 1901 to 2018

The China-Myanmar Economic Corridor(CMEC) is an important part of China's Belt and Road Initiative and an important area for global ecology and biodiversity. In this study, the annual and seasonal spatiotemporal patterns of temperature and precipitation in the CMEC over the past century were investigated using linear tendency estimation, the Mann-Kendall mutation test, the T-test, and wavelet analysis based on the monthly mean climatic data from 1901 to 2018 released by the Climatic Research Unit(CRU) of the University of East Anglia, UK. The results show that the CMEC demonstrated a trend of warming and drying over the past 100 years, and the rate of change in Myanmar was stronger than that in Yunnan Province of China. The warming rate was 0.039 ℃/10a. Precipitation decreased at a rate of -6.1 mm/10a. From the perspective of spatial distribution, temperature was high in the central and southern, low in the north of the CMEC, and the high-temperature centers were mainly distributed in the southern plain and river valley. Precipitation decreased from west to east and from south to north of the CMEC. From the perspective of the rate of change, warming was stronger in central and northern CMEC than in southern and northeastern CMEC. The rate of precipitation decline was stronger in the central and western regions than in the eastern region. This study provides a scientific reference for the CMEC to address climate change and ensure sustainable social and economic development and ecological security.

Spatiotemporal Pattern of Cultivated Land Pressure and Its Influencing Factors in the Huaihai Economic Zone, China

Cultivated land pressure represents a direct reflection of grain security. Existing relevant studies rarely approached the spatiotemporal pattern of cultivated land pressure or the spatial heterogeneity of its influencing factors from the level of economic zones.Taking the Huaihai Economic Zone(HEZ), China for case analysis, this study investigated the spatiotemporal pattern of cultivated land pressure in diverse periods from 2000 to 2018 based on a modified cultivated land pressure index and spatial correlation models. On this basis, it explored the influencing factors of the spatial differentiation of cultivated land pressure in the late stage of the study using geographical detector as well as multi-scale geographically weighted regression model. The results indicated that: 1) in the study period, the global cultivated land pressure index of the study area decreased gradually, but cultivated land pressure increased locally in a significant way, especially in the central and southern Shandong Province;2) the spatial pattern of cultivated land pressure manifested global clustering features. Hot and secondary-hot spots presented a narrowing and clustering trend, whereas cold and secondary-cold spots manifested a spreading and clustering trend;3) average slope, the proportion of non-grain crops, population urbanization rate, and multiple cropping index have significant effects on the spatial differentiation of cultivated land pressure. The former three factors were positively correlated with cultivated land pressure, and the last factor was negatively correlated with cultivated land pressure;and 4) the amount of cultivated land has increased in the central and southern Shandong Province through land consolidation which, nonetheless, failed to improve the grain production. In regards to major grain producing areas similar to the HEZ in China, the authors suggest that great importance should be given to the balance of the quality and quantity of cultivated land, the optimization of agricultural production factors and the rational control of non-grain crops, thus providing a powerful guarantee for grain security in China.

Spatiotemporal Patterns of Urban PM2.5 Pollution in China

Air pollution is one of the top environmental concerns and causes of deaths and variousdiseases worldwide. In this paper, PM2.5 observation data at 1,497 automatic air quality-monitoringstations in 367 cities of China in 2015 were utilized, and the study on spatiotemporal distribution of PM2.5concentration found that the average annual concentration of PM2.5 in urban China in 2015 was 49.74 μg/m3and exceeded the annual average limit in 287 cities. PM2.5 concentrations were highest in winter and lowestin summer in most cities, but it reached the highest in spring in the cities around Taklimakan Desert. Therewere 320 fi ne days in 2015 and the maximum PM2.5 was prone to appear at night, the minimum was usuallyin the afternoon, but in the early morning in Lhasa, and the minimum in winter was even in the earlymorning, midday and afternoon in some cities. Higher concentrations of PM2.5 were found in the EastChina Plain and the cities around Taklimakan Desert, preceded by the Yangtze River Delta economic zone,Chengdu-Chongqing economic zone and Harbin-Changchun megalopolis, while the lower values coveredthe northwestern region of Xinjiang, Heilongjiang Xing’an Mountains region, northeast high latitudes ofInner Mongolia, southwest high altitudes in the border area of Sichuan, Yunnan, Qinghai-Tibet Plateau andthe southeast coastal areas.

Spatiotemporal patterns in urbanization efficiency within the Yangtze River Economic Belt between 2005 and 2014

The question of how to generate maximum socio-economic benefits while at the same time minimizing input from urban land resources lies at the core of regional ecological civilization construction. We apply stochastic frontier analysis （SFA） in this study to municipal input-output data for the period between 2005 and 2014 to evaluate the urbanization efficiency of 110 cities within the Yangtze River Economic Belt （YREB） and then further assess the spatial association characteristics of these values. The results of this study initially reveal that the urbanization efficiency of the YREB increased from 0.34 to 0.53 between 2005 and 2014, a significant growth at a cumulative rate of 54.07%. Data show that the efficiency growth rate of cities within the upper reaches of the Yangtze River has been faster than that of their counterparts in the middle and lower reaches, and that there is also a great deal of ad- ditional potential for growth in urbanization efficiency across the whole area. Secondly, results show that urbanization efficiency conforms to a ＂bar-like＂ distribution across the whole area, gradually decreasing from the east to the west. This trend highlights great intra-provincial differences, but also striking inter-provincial variation within the upper, middle, and lower reaches of the Yangtze River. The total urbanization efficiency of cities within the lower reaches of the river has been the highest, followed successively by those within the middle and upper reaches. Finally, values for Moran＇s / within this area remained higher than zero over the study period and have increased annually; this result indicates a positive spatial correlation between the urbanization efficiency of cities and annual increments in agglomeration level. Our use of the local indicators of spatial association （LISA） statistic has enabled us to quantify characteristics of ＂small agglomeration and large dispersion＂. Thus, ＂high- high＂ （H-H） agglomeration areas can be seen to have spread outwards from around Zhejiang Province and the city of Shanghai, while areas characterized by ＂low-low＂ （L-L） patterns are mainly concentrated in the north of Anhui Province and in Sichuan Province. The framework and results of this research are of considerable significance to our understanding of both land use sustainability and balanced development.

Spatiotemporal patterns of winter wheat phenology and its climatic drivers based on an improved pDSSAT model

Acquiring spatiotemporal patterns of phenological information and its drivers is essential for understanding the response of crops to climate change and implementing adaptation measures.However,current approaches to obtain phenology and analyse its drivers have deficiencies such as sparse observations,excessive dependence of remote sensing inversion on sensors,and inevitable difficulties in upscaling site-based crop models into larger regions.Based on the Wang-Engel temperature response function,we improved the Crop Estimation through Resource and Environment Synthesis-Wheat(CERES-Wheat)model.First,we calibrated the model at the regional scale and evaluated its performance.Furthermore,the spatiotemporal changes in winter wheat phenology in China from 2000 to 2015 were analysed.The results showed that the improved model significantly enhanced the simulation accuracy of the anthesis and maturity dates by averages of 13%and 12%in most planting areas,especially in the Yunnan-Guizhou Plateau(YG)with improvements of 26%and 28%.The simulated phenology of winter wheat grown in a colder environment(e.g.,the average temperatures during the vegetative growth period range from 0 to 5℃ and from 15 to 20°C,and the reproductive growth period ranges from 10 to 15°C)also notably improved.These results confirmed that the original temperature response function indeed had limitations.Further analyses revealed that the key phenological dates and growth periods over the past 16 years were dominantly advanced and shortened.Specifically,the anthesis date,vegetative growth period(VGP),and reproductive growth period(RGP)indicated obviously spatial characteristics.For example,the anthesis date and VGP in the North China Plain(NCP)and the Middle-Lower Yangtze Plain(YZ)and the RGP in northwestern China(NW)showed opposite trends of delay and prolongation as comparing with the dominant patterns.Sensitivity analysis indicated that the key phenological dates and growth periods were advanced and shortened as the minimum(T_(min))and maximum temperatures(T_(max))rose,while they were postponed and prolonged with the increased precipitation.However,their responses to solar radiation did not show spatial consistency.Additionally,we found that the sensitivity of phenology to climatic factors differed across subregions.In particular,phenology in southwestern China and YG was more sensitive to T_(min),T_(max),and solar radiation than in the NCP and NW.Moreover,the sensitivity to precipitation in NW was higher than that in YZ.Totally,the improved crop model could provide more refined spatial characteristics of phenology at a large scale and benefit to explore its drivers more objectively.Furthermore,our results highlight that different planting areas should adopt suitable adaptation measures to cope with climate change impacts.Ultimately,the improved model is promising to enhance the accuracy of yield prediction and provide powerful tools for assessing regional climate change impact and adaptability.

Comparing spatiotemporal patterns in Eurasian FPAR derived from two NDVI-based methods

A long-term,consistent Fraction of Absorbed Photosynthetically Active Radiation(FPAR)product is necessary to study the spatial and temporal patterns of vegetation dynamics associated with climatic changes and human activities.In this study,Eurasia was selected as the study area.The relationship between FPAR and simple infrared/red ratio relationship(SR FPAR),and that between Moderate Resolution Imaging Spectroradiometer(MODIS)FPAR and a Normalised Difference Vegetation Index(NDVI)look-up table(LUT FPAR)were employed to estimate FPAR from 1982 to 2006 by different land cover types,focusing on the comparisons of spatiotemporal FPAR patterns between the two FPAR datasets.The results showed high agreement between MODIS standard FPAR and estimated FPAR in seasonal dynamics with peak values in July.The LUT FPAR was close to MODIS standard FPAR and larger than SR FPAR.The SR and LUT FPAR showed the same spatial distribution and inter-annual variation patterns and were primarily determined by land cover types.An overall increasing trend in FPAR was observed from 1982 to 2006,with reductions from 1991 to 1994 and 2000 to 2002.The inter-annual dynamics in evergreen broadleaf forests showed a decreasing trend over 25 years,while non-forest vegetation FPAR values had slow,stable growth in inter-annual variation.

Spatial and temporal patterns of the sensitivity of radial growth response by Picea schrenkiana to regional climate change in the Tianshan Mountains

Climate change significantly impacts forest ecosystems in arid and semi-arid regions.However,spatiotemporal patterns of climate-sensitive changes in individual tree growth under increased climate warming and precipitation in north-west China is unclear.The dendrochronological method was used to study climate response sensitivity of radial growth of Picea schrenkiana from 158 trees at six sites during 1990-2020.The results show that climate warming and increased precipitation significantly promoted the growth of trees.The response to temperature first increased,then decreased.However,the response to increased precipitation and the self-calibrating Palmer Drought Severity Index(scPDSI)increased significantly.In most areas of the Tianshan Mountains,the proportion of trees under increased precipitation and scPDSI positive response was relatively high.Over time,small-diameter trees were strongly affected by drought stress.It is predicted that under continuous warming and increased precipitation,trees in most areas of the Tianshan Mountains,especially those with small diameters,will be more affected by precipitation.

Existence of spatiotemporal patterns in the reaction-diffusion predator-prey model incorporating prey refuge

The pattern formation in reaction-diffusion system has long been the subject of interest to the researchers in the domain of mathematical ecology because of its universal exis- tence and importance. The present investigation deals with a spatial dynamics of the Beddington-DeAngelis predator-prey model in the presence of a constant proportion of prey refuge. The model system representing boundary value problem under study is subjected to homogeneous Neumann boundary conditions. The asymptotic stability including the local and the global stability and the bifurcation as well of the unique pos- itive homogeneous steady state of the corresponding temporal model has been analyzed. The Turing instability region in two-parameter space and the condition of diffusion- driven instability of the spatiotemporal model are investigated. Based on the appro- priate numerical simulations, the present model dynamics in Turing space appears to get influenced by prey refuge while it exhibits diffusion-controlled pattern formation growth to spots, stripe-spot mixtures, labyrinthine, stripe-hole mixtures and holes repli- cation. The results obtained appear to enrich the findings of the model system under consideration.

Spatiotemporal patterns of the daily relative risk of COVID-19 in China

The coronavirus disease 2019(COVID-19)pandemic continues to threaten lives and the economy around the world.Estimating the risk of COVID-19 can help in predicting spreading trends,identifying risk areas,and making public health decisions.In this study,we proposed a comparative risk assessment method to estimate comprehensive and dynamic COVID-19 risks by considering the pandemic severity and the healthcare system pressure and then employing the z-order curve and fractal theory.We took the COVID-19 cases from January 19-March 10,2020 in China as our research object.The results and analysis revealed that(1)the proposed method demonstrated its feasibility to assess and illustrate pandemic risk;(2)the temporal patterns of the daily relative risk indices of 31 provinces were clustered into four groups(high-value,fluctuating-increase,inverted U-shaped,and low-stable);(3)the spatial distribution of the relative pandemic risk indicated a significant circular pattern centered on Hubei Province;and(4)healthcare system capacity is the key to reducing relative pandemic risk,and cases imported from abroad should be given more attention.The methods and results of this study will provide a methodological basis and practical guidance for regional pandemic risk assessment and public health decision-making.

Influence of a large dam on the longitudinal patterns of fish assem- blages in Qingyi Stream

Using seasonally collected data(2009-2010) from 15 sampling sites that represent first- to fifth-order streams within the Qingyi watershed,we examined the spatio-temporal patterns of fish assemblages along two longitudinal gradients to explore the effects of a large dam on fish assemblages at the watershed scale.No significant variation was observed in either species richness or assemblage structure across seasons.Species richness significantly varied according to stream order and gradient.Dam construction appeared to decrease species richness upstream substantially,while a significant decrease between gradients only occurred within fourth-order streams.Along the gradient without the large dam,fish assemblage structures presented distinct separation between two neighboring stream orders,with the exception of fourth-order versus fifth-order streams.However,the gradient disrupted by a large dam displayed the opposite pattern in the spatial variation of fish assemblages related with stream orders.Significant between-gradient differences in fish assemblage structures were only observed within fourth-order streams.Species distributions were determined by local habitat environmental factors,including elevation,substrate,water depth,current discharge,wetted width,and conductivity.Our results suggested that dam construction might alter the longitudinal pattern in fish species richness and assemblage structure in Qingyi Stream,despite the localized nature of the ecological effect of dams.

Fine-scale activity patterns of large-and medium-sized mammals in a deciduous broadleaf forest in the Qinling Mountains,China

The composition of animal species and interactions among them are widely known to shape ecological communities and fine-scale(e.g.,<1 km)monitoring of animal communities is essential for understanding the relationships among animals and plants.Although the co-existence of large-and medium-sized species has been studied across different scales,research on fine-scale interactions of herbivores in deciduous broadleaf forests is limited.Camera trapping of large-and medium-sized mammals was carried out over a 1 year period within a 25 ha deciduous broadleaf forest dynamics plot in the Qinling Mountains,China.Fourteen species of large-and medium-sized mammals,including six carnivores,six ungulates,one primate and one rodent species were found.Kernel density estimations were used to analyse the diel or 24 h activity patterns of all species with more than 40 independent detections and general linear models were developed to explore the spatial relationships among the species.The combination of overlapping diel activity patterns and spatial associations showed obvious niche separation among six species:giant panda(Ailuropoda melanoleuca David),takin(Budorcas taxicolor Hodgson),Reeves’s muntjac(Muntiacus reevesi Ogilby),tufted deer(Elaphodus cephalophus Milne-Edwards),Chinese serow(Capricornis milneedwardsii David)and wild boar(Sus scrofa Linnaeus).Long-term fine-scale monitoring is useful for providing information about the co-existence of species and their interactions.The results demonstrate the importance for fine-scale monitoring of animals and plants for improving understanding of species interactions and community dynamics.

Plasticity-induced characteristic changes of pattern dynamics and the related phase transitions in small-world neuronal networks

Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters （e.g., external stimuli）, and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks （LBSW networks） under spike-timing-dependent plasticity （STDP）. By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions （SOPTs）： repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.

Hollow hexagonal pattern with surface discharges in a？dielectric barrier discharge

The hollow hexagonal pattern involved in surface discharges is firstly investigated in a？dielectric barrier discharge system. The spatiotemporal structures of the pattern are studied using an intensified charge-coupled device and photomultiplier. Instantaneous images taken by an intensified charge-coupled device and optical correlation measurements show that the surface discharges are induced by volume discharges. The optical signals indicate that the discharge filaments constituting the hexagonal frame discharge randomly at the first current pulse or the second pulse, once？or twice. There is no？interleaving of several sub-lattices, which indicates that the ‘memory＇ effect is no longer in force due to surface discharges. By using the emission spectrum method, both the molecule vibration temperature？and electron density of the surface discharges are larger than that of the volume discharges.

Spatial-temporal patterns and evolution of carbon storage in China's terrestrial ecosystems from 1980 to 2020

Analyzing the changes in carbon storage in terrestrial ecosystems caused by land use changes is a crucial part of exploring the carbon cycle. In addition, enhancing carbon storage in terrestrial ecosystems is an effective and environmentally friendly measure to sequester anthropogenic carbon emissions, which is significant for achieving carbon neutrality and curbing global climate change. This paper uses land use data and carbon density tables with the In VEST model to obtain a carbon storage distribution map of China. It further applies land use response elasticity coefficients, Theil index multi-stage nested decomposition, and spatial autocorrelation analysis to examine the spatial-temporal patterns, causes of changes, and evolution characteristics of carbon storage in terrestrial ecosystems from 1980 to 2020. The results show that the temporal changes in China's carbon storage generally present an inverted S-curve, with an initial rapid decline followed by a slower decrease. Spatially, it features high levels in the northeast, low levels in the northwest, and a uniform distribution in the central and southern regions.The disturbance of land use type changes on terrestrial ecosystem carbon storage has been effectively mitigated. The significant reduction in grassland area in the Southwest region is the main source of carbon storage loss during the study period, and the encroachment of construction land on arable land in large urban agglomerations is one of the important causes of carbon storage loss. The Theil index multi-stage nested decomposition results indicate that the overall difference in carbon storage in China has decreased, while differences among cities within provinces and among counties within cities have increased. The influence of natural factors on the distribution of carbon storage is weakening, whereas the impact of human activities is becoming more profound, enhancing its influence on the spatial distribution of carbon storage in China. From 1980 to 2000, the carbon density in coastal metropolises generally showed a declining trend. From 2000 to 2020, the carbon density in the central urban areas of eastern coastal city clusters gradually showed an upward trend and continued to expand outward, revealing to some extent the“Environmental Kuznets Curve” characteristic in the development process of urban carbon storage. Therefore, in future ecological construction, the government should fully consider the impact of land management planning on carbon storage in different regions, promote the efficient use and standardized management of land, and strive to cross the “Environmental Kuznets Curve” inflection point of carbon storage as soon as possible.

Spatio-temporal Characteristics of Disturbance of Land Use Change on Major Ecosystem Function Zones in China

In recent years, because of increasing human activities, ecosystems have been substantially disturbed and their service functions have been greatly compromised. Based on the effect of land use changes on the major ecosystem services, we estimated the ecosystem comprehensive anthropogenic disturbance index(ECADI) and analyzed the spatio-temporal characteristics of changes in the ECADI in China from 1990 to 2010. The average ECADI of the major ecosystem function zones in China in 2010 is approximately 0.382. The ECADI of Northeast China and North China is slightly higher than that of Northwest China and Southwest China. Most zones have slight changes in the ECADI. The average increases of ECADI in the major ecosystem function zones in China from 1990 to 2000 and from 2000 to 2010 are 0.0024 and 0.0002, respectively. The increase is mainly due to reclamation and urbanization, whereas the decrease is due to the implementation of ecosystem protection policies. During the last 20 years, the ECADI of water resources conservation zones increased first, and then stopped. The ECADI of soil conservation zones increased first, and then declined. The ECADI of sandstorm prevention zones, biodiversity conservation zones and flooding mitigation zones increased continuously. Our results may provide proposals to the government regarding land use planning and ecosystem protection plans in the major ecosystem zones. The major ecosystem function zones in the western part of China have been protected effectively. However, the major ecosystem function zones in the eastern part of China require more protection in the future.

Regional Equity and Influencing Factor of Social Assistance in China

Social assistance is the last safety net in the social security system and plays a vital role in poverty alleviation in countries around the world. Promoting the equal financial assistance is meaningful to achieve equalization of social assistance. Based on the provincial panel data from 2002 to 2017, this paper analyzes the dynamic characteristics and main influencing factors of the equity of social assistance in China, using the Theil index and geographically weighted regression(GWR) model. The results suggest that the level of per capita social assistance expenditure(PSAE) in China keeps increasing year by year, but the changes in different regions and provinces are quite different. These changes not only significantly changed the spatial pattern of PSAE in China, but also greatly improved its spatial coupling with the deeply impoverished areas. Further analysis shows that the regional inequality of PSAE between provinces is obvious during the study period, and the inter-regional inequality is significantly higher than the intra-regional inequality.This makes inter-regional inequality become the main source of the regional inequality of PSAE in China for a long time. According to GWR results, there is obvious spatiotemporal heterogeneity in the influence intensity and direction of the per capita financial revenue,urbanization rate, urban unemployment rate, natural disaster-affected area, and transfer payment intensity on the PSAE. The urbanization rate and per capita financial revenue are the main driving factors of PSAE, and the impact intensity of per capita financial revenue tends to strengthen. The remaining three factors have a positive effect on PSAE, but the effect intensity is not high.

Simulation of Evapotranspiration Based on BEPS-TerrainLab V2.0 from 1990 to 2018 in the Dajiuhu Basin

Accurate estimations of evapotranspiration(ET)are essential for understanding land-atmosphere coupling and atmosphere-underlying surface energy and water vapor exchanges.Based on input data processing,this paper simulates the temporal and spatial variation of ET in the Dajiuhu Basin from 1990 to 2018 using the BEPS-Terrain Lab V2.0 model.Compared with the ET measured by an eddy covariance(EC)tower,the model explained 80.1%of the ET variation.From 1990 to 2018,the average annual ET in the Dajiuhu Basin was 1262.7 mm/yr indicating a downward trend(–27.12 mm/yr).In 2005,a sudden change point was observed based on the Mann-Kendall(MK)test and 3-year moving t-test.Around 2005,the downward trend in ET slowed and the proportional trend of ET to precipitation changed from upward trend to downward trend.Regarding spatial distribution,the ET in the basin’s central part was smaller than that in the basin’s surrounding area,the ET of the southern slope was higher than that of the northern slope,and the decrease in the ET rate on the sunny side was lower than that on the shady side.ET decreased as the elevation increased,with the fastest decrease observed between 2184 and 2384 m.For different landcover types,the average ET exhibited the following order:deciduous forest>mixed forest>wetland>grass>agriculture land.Decreased solar radiation is the main reason for the decreased ET in the Dajiuhu Basin,followed by increased wind speed and relative humidity,which together contribute 83.9%to the ET trend.This paper provides a theoretical basis for the study of ET changes and the mechanism of ET and provides a decision-making reference for water resource management in the Dajiuhu Basin and even the South-to-North Water Transfer Project.

Rapid Urbanization Induced Extensive Forest Loss to Urban Land in the Guangdong-Hong Kong-Macao Greater Bay Area, China

China has experienced rapid urbanizations with dramatic land cover changes since 1978. Forest loss is one of land cover changes, and it induces various eco-environmental degradation issues. As one of China’s hotspot regions, the Guangdong-Hong KongMacao Greater Bay Area(GBA) has undergone a dramatic urban expansion. To better understand forest dynamics and protect forest ecosystem, revealing the processes, patterns and underlying drivers of forest loss is essential. This study focused on the spatiotemporal evolution and potential driving factors of forest loss in the GBA at regional and city level. The Landsat time-series images from 1987 to2017 were used to derive forest, and landscape metrics and geographic information system(GIS) were applied to implement further spatial analysis. The results showed that: 1) 14.86% of the total urban growth area of the GBA was obtained from the forest loss in1987–2017;meanwhile, the forest loss area of the GBA reached 4040.6 km2, of which 25.60%(1034.42 km2) was converted to urban land;2) the percentages of forest loss to urban land in Dongguan(19.14%), Guangzhou(18.35%) and Shenzhen(15.81%) were higher than those in other cities;3) the forest became increasingly fragmented from 1987–2007, and then the fragmentation decreased from2007 to 2017);4) the landscape responses to forest changes varied with the scale;and 5) some forest loss to urban regions moved from low-elevation and gentle-slope terrains to higher-elevation and steep-slope terrains over time, especially in Shenzhen and Hong Kong.Urbanization and industrialization greatly drove forest loss and fragmentation, and, notably, hillside urban land expansion may have contributed to hillside forest loss. The findings will help policy makers in maintaining the stability of forest ecosystems, and provide some new insights into forest management and conservation.

Ecosystem Health: Assessment Framework, Spatial Evolution, and Regional Optimization in Southwest China

Regional ecological health,the core of comprehensive ecosystem assessments,is an important foundation for regional exploration,environmental conservation,and sustainable development.The mountainous areas in southwest China are backward in economy,but industrialization and urbanization have been rapid in recent years.This study assessed the ecosystem health of the Sichuan and Yunnan provinces in China using a pressure-state-response(PSR)model.Spatiotemporal patterns of regional ecosystem health were analyzed from 2000 to 2016,including overall characteristics as well as local characteristics.Ecosystem health in most regions was improved over time(Y=0.0058 X–11.0132,R2=0.95,P<0.001),and areas with poorer ecosystem health decreased from half to one-third of the total area.Analysis of the primacy ratio and the variation coefficient confirmed that the gap in health scores between regions has gradually expanded since 2007,but there are more high quality regions overall(Z of Moran’s index<1.96,P>0.05).Overall,the regional ecosystems to the east of the Hu line-an imaginary line dividing east and west China into roughly equivalent parts-were healthier than those to the west.The pressure and state scores of ecosystems were determined by physiographic condition,and the response scores by government policies and social concern.The spatiotemporal patterns of ecosystem health were dominated to a greater extent by natural than anthropogenic factors,which explains why the shift in the patterns aligned with the direction of the Hu line.Dividing regions into key management areas based on natural geographical conditions and socioeconomic development could contribute to the formulation of a reasonable ecological and environmental protection policy,guaranteeing ecosystem services in the long run.

Identifying spatiotemporal traffic patterns in large-scale urban road networks using a modified nonnegative matrix factorization algorithm

The identification and analysis of spatiotemporal traffic patterns in road networks constitute a crucial process for sophisticated traffic management and control.Traditional methods based on mathematical equations and statistical models can hardly be applicable to large-scale urban road networks,where traffic states exhibit high degrees of dynamics and complexity.Recently,advances in data collection and processing have provided new opportunities to effectively understand spatiotemporal traffic patterns in large-scale road networks using data-driven methods.However,limited efforts have been exerted to explore the essential structure of the networks when conducting a spatiotemporal analysis of traffic characteristics.To this end,this study proposes a modified nonnegative matrix factorization algorithm that processes high-dimensional traffic data and provides an improved representation of the global traffic state.After matrix factorization,cluster analysis is conducted based on the obtained low-dimensional representative matrices,which contain different traffic patterns and serve as the basis for exploring the temporal dynamics and spatial structure of network congestion.The applicability and effectiveness of the proposed approach are examined in a road network of Beijing,China.Results show that the methods exhibit considerable potential for identifying and interpreting the spatiotemporal traffic patterns over the entire network and provide a systematic and efficient approach for analyzing the network-level traffic state.