Drought significantly constrains vegetation growth and reduces terrestrial carbon sinks.Currently,the spatiotemporal patterns and mechanisms of the differential impacts of soil and meteorological droughts on vegetatio...Drought significantly constrains vegetation growth and reduces terrestrial carbon sinks.Currently,the spatiotemporal patterns and mechanisms of the differential impacts of soil and meteorological droughts on vegetation productivity remain inadequately understood.In this study,we analyzed soil moisture(SM),vapor pressure deficit(VPD),and gross primary productivity(GPP)to investigate their spatiotemporal patterns and the combined effects on GPP over China.The results revealed that:(1)Soil drought and meteorological drought generally exhibited temporally synchronous trends across China.(2)GPP was predominantly affected by the combined and synchronous effects of both SM and VPD,although their effects displayed directional variability differences in certain regions.(3)SM demonstrated a greater relative importance on GPP than VPD across more than half of the regions in China,whereas deciduous broadleaf forests were the only vegetation type primarily affected by VPD.(4)Under the lag effects,both SM and VPD exhibited bidirectional Granger causality with GPP,with the interaction between VPD and GPP proving more pronounced than that of SM.Our research provides valuable insights into the mechanisms through which SM and VPD influence GPP,contributing to improved predictions vegetation productivity and implementing ecological restoration.展开更多
This paper created an evaluation index system for agricultural green resilience,consisting of five dimensions:resistibility,recoverability,adaptability,innovatability,and reconstructability.We used the entropy method ...This paper created an evaluation index system for agricultural green resilience,consisting of five dimensions:resistibility,recoverability,adaptability,innovatability,and reconstructability.We used the entropy method to measure the agricultural green resilience levels of 30 provinces(municipalities/autonomous regions)in China from 2007 to 2021 and employed spatial Markov chains and geographic detectors to reveal the dynamics and evolution of the patterns and influencing factors of the agricultural green resilience.The study shows that the level of agricultural green resilience in China displayed a slight upward trend from 2007 to 2021,but the overall level remained low.Spatially,a distribution pattern of“eastern China>central China>northeastern China>western China”was observed.The transfer process for agricultural green resilience exhibited a“path dependence”characteristic that maintained its initial state,while it also showed a“trickle-down effect.”This means that the regions adjacent to provinces(municipalities/autonomous regions)with higher levels of agricultural green resilience tend to have an increased probability of an upward movement in their ranking.However,such movements are not leapfrogging and only occur at the adjacent levels.The spatial differentiations in the agricultural green resilience levels are primarily driven by the technological innovation capacity and market maturity,with interactions between these factors exhibiting both dual-factor enhancements and nonlinear enhancements.Accordingly,efforts should be made to strengthen support for the less-developed regions,increase research and development investment in the agricultural sector,and improve the market systems for agricultural products to enhance agricultural green resilience.展开更多
The genetic regulation of hair density in animals remains poorly understood.The Dazu black goat,characterized by its black coarse hair and white skin,provides a unique model for dissecting coarse hair density(CHD).Usi...The genetic regulation of hair density in animals remains poorly understood.The Dazu black goat,characterized by its black coarse hair and white skin,provides a unique model for dissecting coarse hair density(CHD).Using high-resolution micro-camera imaging,this study analyzed 905 skin images,33 skin transcriptomes,272 whole-genome sequences,and 182 downloaded transcriptomes.Morphological assessment from juvenile to adult stages revealed the thickening of hair shafts accompanied by a progressive decline in density,largely attributable to rapid surface expansion of the trunk skin.Transcriptomic comparison between high-and low-CHD individuals identified 572 differentially expressed genes(DEGs).A genome-wide association study detected 25 significant single nucleotide polymorphisms(P<9.07e-8)and mapped 48 annotated genes,with the most prominent association signal located near GJA1 on chr9.15931585-18621011.Literature review and Venn analysis highlighted six genes(GJA1,GPRC5D,CD1D,CD207,TFAM,and CXCL12)with documented roles in skin and hair biology,and three genes(GJA1,GPRC5D,and ATP6V1B1)overlapped with DEGs.Multiple-tissue transcriptomic profiling,western blotting,immunohistochemical staining,and skin single-cell RNA sequencing confirmed that GJA1 and GPRC5D were highly and specifically expressed in skin,particularly within hair follicles.Expression was localized predominantly to follicular stem cells and dermal papilla cells,suggesting a significant role in folliculogenesis and structural maintenance.Cross-validation using four public datasets further demonstrated positive correlations between GJA1 and GPRC5D expression and hair follicle density.The innovative micro-camera application allowed the elucidation of spatiotemporal patterns and genes associated with CHD,thereby addressing a significant knowledge gap in animal hair density.展开更多
Ensuring a harmonious coexistence between man and nature is crucial for China’s economic and social development.However,with increasing industrialization and urbanization,there is a growing mismatch between China’s ...Ensuring a harmonious coexistence between man and nature is crucial for China’s economic and social development.However,with increasing industrialization and urbanization,there is a growing mismatch between China’s ecological resilience(ER)and economic level(EL)of development,which poses a notable social threat.Currently,the link between ER and EL in China remains unclear,especially in terms of spatial dislocation(SD),referring to the disconnect between the locations where environmental impacts occur and those where economic benefits or activities are concentrated.Therefore,this paper aims to provide theoretical support and an empirical basis for policy-based solutions to address this gap.Based on the SD theory,this study systematically discusses the temporal changes,spatial patterns,and SD characteristics of China’s ER and EL using spatial auto-correlation and barycentric analysis to analyze data from 30 provinces covering the period 2011-2021.The key results are as follows.China’s ER shows a general trend of growth;however,its distribution is uneven.The spatial pattern generally decreases from the southeastern coastal provinces to the northwest.Moreover,a gradually increasing positive correlation is observed between the ER and EL,but this correlation varies by region,with some showing regional linkages and others developing independently.Finally,the dislocation index of ER and EL presents divergent results based on region-the eastern and central regions primarily show a high level of dislocation,whereas the western and northeastern regions show a low level of dislocation.The results provide a comprehensive overview of the spatiotemporal patterns in the association between ER and EL in China.The results emphasize that to balance sustainable regional development and ecological governance,a region-specific approach must be employed,prioritizing innovation-driven strategies for high ER in more developed regions and market-oriented strategies in less developed regions.展开更多
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 ...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.展开更多
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 pub...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.展开更多
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...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.展开更多
This study analyzes the spatiotemporal patterns and driving factors of forest fires in Liangshan Prefecture based on fire data from 2016 to 2024 using statistical methods.The results indicate:1)From 2016 to 2024,fores...This study analyzes the spatiotemporal patterns and driving factors of forest fires in Liangshan Prefecture based on fire data from 2016 to 2024 using statistical methods.The results indicate:1)From 2016 to 2024,forest fires in Liangshan Prefecture occurred predominantly between January and May(140 incidents),accounting for 97.90%of the total.March recorded the highest number of fires(48 incidents),representing 33.57%.Within a 24-hour period,113 fires occurred between 12:00 PM and 9:00 PM,constituting 79.02%of all incidents.2)Spatially,Mianning County recorded the highest number of forest fires(28 incidents,19.58%),followed by Xichang,Muli,and Yanyuan with 22,23,and 20 incidents,respectively.Human activities,particularly agricultural burning,outdoor smoking,and other causes,were the dominant factors,collectively accounting for 41%of incidents.3)Forest fires predominantly occurred at elevations between 1500 and 3000 meters(132 fires,92.31%),on slopes with gradients of 5-25 degrees(81 fires,56.65%),on west-facing aspects(northwest,west,southwest)(72 fires,53.14%),in areas with NDVI values between 0.51 and 0.8(79 incidents,55.24%),within 500-2000 m residential buffer zones(151 incidents,98.60%),and within 500 m road buffer zones(103 incidents,72.03%).4)Among meteorological factors,the 20-day average temperature(0.3041),80-day maximum temperature(0.3487),20-day minimum temperature(0.2594),20-day minimum relative humidity(−0.3132),70-day maximum wind speed(0.1885),and 70-day peak wind speed(0.1965)showed the strongest correlations with forest fire burned area.Burned area also exhibited a positive correlation with the Meteorological Drought Index(MCI)on the day of the fire(0.1990).This study confirms the lagged and persistent effects of meteorological factors on forest fire occurrence,providing key scientific evidence for constructing regional fire prediction models that integrate multi-scale meteorological indicators.展开更多
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 o...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.展开更多
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 a...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.展开更多
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 invest...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.展开更多
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 p...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.展开更多
Climate change resulting from CO_2 emissions has become an important global environmental issue in recent years.Improving carbon emission performance is one way to reduce carbon emissions.Although carbon emission perf...Climate change resulting from CO_2 emissions has become an important global environmental issue in recent years.Improving carbon emission performance is one way to reduce carbon emissions.Although carbon emission performance has been discussed at the national and industrial levels,city-level studies are lacking due to the limited availability of statistics on energy consumption.In this study,based on city-level remote sensing data on carbon emissions in China from 1992–2013,we used the slacks-based measure of super-efficiency to evaluate urban carbon emission performance.The traditional Markov probability transfer matrix and spatial Markov probability transfer matrix were constructed to explore the spatiotemporal evolution of urban carbon emission performance in China for the first time and predict long-term trends in carbon emission performance.The results show that urban carbon emission performance in China steadily increased during the study period with some fluctuations.However,the overall level of carbon emission performance remains low,indicating great potential for improvements in energy conservation and emission reduction.The spatial pattern of urban carbon emission performance in China can be described as"high in the south and low in the north,"and significant differences in carbon emission performance were found between cities.The spatial Markov probabilistic transfer matrix results indicate that the transfer of carbon emission performance in Chinese cities is stable,resulting in a"club convergence"phenomenon.Furthermore,neighborhood backgrounds play an important role in the transfer between carbon emission performance types.Based on the prediction of long-term trends in carbon emission performance,carbon emission performance is expected to improve gradually over time.Therefore,China should continue to strengthen research and development aimed at improving urban carbon emission performance and achieving the national energy conservation and emission reduction goals.Meanwhile,neighboring cities with different neighborhood backgrounds should pursue cooperative economic strategies that balance economic growth,energy conservation,and emission reductions to realize low-carbon construction and sustainable development.展开更多
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 precipita...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.展开更多
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 relations...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.展开更多
Studying the spatiotemporal distribution characteristics and coupling coordination relationship of urban and rural resilience is of substantial theoretical and practical significance to improving the ability of urban ...Studying the spatiotemporal distribution characteristics and coupling coordination relationship of urban and rural resilience is of substantial theoretical and practical significance to improving the ability of urban and rural areas to resist risk and for promoting their coordinated development.This study establishes a comprehensive evaluation index system of urban and rural resilience that encom-passes industrial,social,and ecological subsystems as well as stability,sensitivity,and adaptability.For each of the prefecture-level city in Northeast China,we evaluated its urban and rural resilience and determined the coupling coordination level between them using data spanning 2010,2015,and 2020.The resilience levels of both urban and rural areas in Northeast China are continuously improving.The high-value area of urban resilience is mainly located in the central cities of Northeast China,and prominent in urban agglomeration areas,while rural resilience is predominantly high in the north and low in the south.The high-value area of the coupling coordination degree is mainly distributed in the arc-shaped zone extending from south to north in the eastern part of Northeast China,with the level of coupling coordination increased overall.Non-parametric testing revealed significant differences in urban industrial stability,urban in-dustrial adaptability,rural industrial stability,rural social adaptability,and rural ecological stability among types of cities differing in their coupling coordination development.Our findings provide a reference for enhancing urban and rural resilience and their coordin-ated development path in Northeast China.展开更多
In the context of climate change,the acceleration of the global water cycle has led to the emergence of abrupt transitions between drought and flood events,presenting a new challenge for flood and drought disaster mit...In the context of climate change,the acceleration of the global water cycle has led to the emergence of abrupt transitions between drought and flood events,presenting a new challenge for flood and drought disaster mitigation.Abrupt transitions between drought and flood refer to a phenomenon in which an extreme drought event quickly shifts to an extreme flood event,or vice versa,within a relatively short time span.This phenomenon disrupts the traditional spatiotemporal distribution patterns of water-related disasters,reflecting not only the extreme unevenness in the distribution of water resources but also the rapid alternation of the water cycle's evolution(He et al.,2016).Moreover,due to its suddenness,extremity,and complexity,it poses severe threats to human societies and ecosystems.Scientifically addressing abrupt transitions between drought and flood has thus become a new challenge in flood and drought disaster prevention.展开更多
The data acquisition technologies used in power systems have been continuously improving,thus laying the solid foundation for data-driven operation analysis of power systems.However,existing methods for analyzing the ...The data acquisition technologies used in power systems have been continuously improving,thus laying the solid foundation for data-driven operation analysis of power systems.However,existing methods for analyzing the relationship between operational variables mainly depend on the mathematical model and element parameters of the power system.Therefore,a thorough data-based analysis method is required to investigate the spatiotemporal characteristics of power system operation,especially for new types of power systems.The causal inference method,which has been successfully applied in many fields,is a powerful tool for investigating the interaction of data variables.In this study,a causal inference method is proposed based on supervisory control and data acquisition(SCADA)data for investigating the spatiotemporal causal relationships in power systems.Initially,a multiple data-sequence regression model is proposed to analyze the relationship of operation data variables.Next,the linear non-Gaussian acyclic model(LiNGAM)is used to calculate the causal index of the operational variables,and its limitations are analyzed.Furthermore,a new causal index of“full variable amplitude LiNGAM(FVA-LiNGAM)”is proposed by incorporating prior causal direct knowledge and considering the effect of real variable amplitude.Using the FVA-LiNGAM causal index,the causal relationship of operation variables can be investigated with higher spatiotemporal accuracy than that of the original LiNGAM index.Taking a real SCADA data subset of a provincial power system as an example,the validity of the FVA-LiNGAM causal index is verified.The variation patterns in spatiotemporal causality are explored using actual SCADA data sequences.The result shows that there indeed exists some spatiotemporal causality variation patterns between the operating variables of the power system.展开更多
The vulnerable ecosystem of the arid and semiarid region in Central Asia is sensi- tive to precipitation variations. Long-term changes of the seasonal precipitation can reveal the evolution rules of the precipitation ...The vulnerable ecosystem of the arid and semiarid region in Central Asia is sensi- tive to precipitation variations. Long-term changes of the seasonal precipitation can reveal the evolution rules of the precipitation climate. Therefore, in this study, the changes of the sea- sonal precipitation over Central Asia have been analyzed during the last century （1901-2013） based on the latest global monthly precipitation dataset Global Precipitation Climatology Centre （GPCC） Full Data Reanalysis Version 7, as well as their relations with El Ni~_o- Southern Oscillation （ENSO）. Results show that the precipitation in Central Asia is mainly concentrated in spring and summer seasons, especially in spring. For the whole study period, increasing trends were found in spring and winter, while decreasing trends were detected in summer and fall. Inter-annual signals with 3-7 years multi-periods were derived to explain the dominant components for seasonal precipitation variability. In terms of the dominant spatial pattern, Empirical orthogonal function （EOF） results show that the spatial distribution of EOF-1 mode in summer is different from those of the other seasons during 1901-2013. Moreover, significant ENSO-associated changes in precipitation are evident during the fall, winter, spring, and absent during summer. The lagged associations between ENSO and seasonal precipitation are also obtained in Central Asia. The ENSO-based composite analy- ses show that these water vapor fluxes of spring, fall and winter precipitation are mainly generated in Indian and North Atlantic Oceans during El Nino. The enhanced westerlies strengthen the western water vapor path for Central Asia, thereby causing a rainy winter.展开更多
基金National Key Research and Development Program,No.2021xjkk0303。
文摘Drought significantly constrains vegetation growth and reduces terrestrial carbon sinks.Currently,the spatiotemporal patterns and mechanisms of the differential impacts of soil and meteorological droughts on vegetation productivity remain inadequately understood.In this study,we analyzed soil moisture(SM),vapor pressure deficit(VPD),and gross primary productivity(GPP)to investigate their spatiotemporal patterns and the combined effects on GPP over China.The results revealed that:(1)Soil drought and meteorological drought generally exhibited temporally synchronous trends across China.(2)GPP was predominantly affected by the combined and synchronous effects of both SM and VPD,although their effects displayed directional variability differences in certain regions.(3)SM demonstrated a greater relative importance on GPP than VPD across more than half of the regions in China,whereas deciduous broadleaf forests were the only vegetation type primarily affected by VPD.(4)Under the lag effects,both SM and VPD exhibited bidirectional Granger causality with GPP,with the interaction between VPD and GPP proving more pronounced than that of SM.Our research provides valuable insights into the mechanisms through which SM and VPD influence GPP,contributing to improved predictions vegetation productivity and implementing ecological restoration.
基金supported by the Research on the Mechanisms and Policies for the Collaborative Promotion of High-Quality Development in the Private Enterprises of Fujian Province Through Digital Finance and Green Finance(FJ2024MGCA021)a key project of basic theory research in philosophy and social sciences guided by Marxism in universities in Fujian Province and Research on the Mechanism and Pathways for Empowering Green Innovation in Fujian Province Through the Deep Integration of Digital Economy and Real Economy(FJKX-2023XKB003)a Science and Technology Innovation Think Tank Research Project of Fujian Association for Science and Technology.
文摘This paper created an evaluation index system for agricultural green resilience,consisting of five dimensions:resistibility,recoverability,adaptability,innovatability,and reconstructability.We used the entropy method to measure the agricultural green resilience levels of 30 provinces(municipalities/autonomous regions)in China from 2007 to 2021 and employed spatial Markov chains and geographic detectors to reveal the dynamics and evolution of the patterns and influencing factors of the agricultural green resilience.The study shows that the level of agricultural green resilience in China displayed a slight upward trend from 2007 to 2021,but the overall level remained low.Spatially,a distribution pattern of“eastern China>central China>northeastern China>western China”was observed.The transfer process for agricultural green resilience exhibited a“path dependence”characteristic that maintained its initial state,while it also showed a“trickle-down effect.”This means that the regions adjacent to provinces(municipalities/autonomous regions)with higher levels of agricultural green resilience tend to have an increased probability of an upward movement in their ranking.However,such movements are not leapfrogging and only occur at the adjacent levels.The spatial differentiations in the agricultural green resilience levels are primarily driven by the technological innovation capacity and market maturity,with interactions between these factors exhibiting both dual-factor enhancements and nonlinear enhancements.Accordingly,efforts should be made to strengthen support for the less-developed regions,increase research and development investment in the agricultural sector,and improve the market systems for agricultural products to enhance agricultural green resilience.
基金supported by the National Key Research and Development Program of China(2022YFD1300202)Collection,Utilization,and Innovation of Animal Resources by Research Institutes and Enterprises of Chongqing(Cqnyncw-kqlhtxm),Chongqing Modern Agricultural Industry Technology System(CQMAITS202413)National Training Program of Innovation and Entrepreneurship for Undergraduates(S202310635040)。
文摘The genetic regulation of hair density in animals remains poorly understood.The Dazu black goat,characterized by its black coarse hair and white skin,provides a unique model for dissecting coarse hair density(CHD).Using high-resolution micro-camera imaging,this study analyzed 905 skin images,33 skin transcriptomes,272 whole-genome sequences,and 182 downloaded transcriptomes.Morphological assessment from juvenile to adult stages revealed the thickening of hair shafts accompanied by a progressive decline in density,largely attributable to rapid surface expansion of the trunk skin.Transcriptomic comparison between high-and low-CHD individuals identified 572 differentially expressed genes(DEGs).A genome-wide association study detected 25 significant single nucleotide polymorphisms(P<9.07e-8)and mapped 48 annotated genes,with the most prominent association signal located near GJA1 on chr9.15931585-18621011.Literature review and Venn analysis highlighted six genes(GJA1,GPRC5D,CD1D,CD207,TFAM,and CXCL12)with documented roles in skin and hair biology,and three genes(GJA1,GPRC5D,and ATP6V1B1)overlapped with DEGs.Multiple-tissue transcriptomic profiling,western blotting,immunohistochemical staining,and skin single-cell RNA sequencing confirmed that GJA1 and GPRC5D were highly and specifically expressed in skin,particularly within hair follicles.Expression was localized predominantly to follicular stem cells and dermal papilla cells,suggesting a significant role in folliculogenesis and structural maintenance.Cross-validation using four public datasets further demonstrated positive correlations between GJA1 and GPRC5D expression and hair follicle density.The innovative micro-camera application allowed the elucidation of spatiotemporal patterns and genes associated with CHD,thereby addressing a significant knowledge gap in animal hair density.
基金funded by the National Natural Science Foundation of China[Grant No.71963030]a subproject of China’s third comprehensive scientific expedition to Xinjiang[Grant No.SQ2021xjkk01800]+1 种基金a major science and technology project in the Xinjiang Uygur Autonomous Region[Grant No.2022A01003]a scientific research innovation project for excellent doctoral students of Xinjiang University[Grant No.XJU2022BS010].
文摘Ensuring a harmonious coexistence between man and nature is crucial for China’s economic and social development.However,with increasing industrialization and urbanization,there is a growing mismatch between China’s ecological resilience(ER)and economic level(EL)of development,which poses a notable social threat.Currently,the link between ER and EL in China remains unclear,especially in terms of spatial dislocation(SD),referring to the disconnect between the locations where environmental impacts occur and those where economic benefits or activities are concentrated.Therefore,this paper aims to provide theoretical support and an empirical basis for policy-based solutions to address this gap.Based on the SD theory,this study systematically discusses the temporal changes,spatial patterns,and SD characteristics of China’s ER and EL using spatial auto-correlation and barycentric analysis to analyze data from 30 provinces covering the period 2011-2021.The key results are as follows.China’s ER shows a general trend of growth;however,its distribution is uneven.The spatial pattern generally decreases from the southeastern coastal provinces to the northwest.Moreover,a gradually increasing positive correlation is observed between the ER and EL,but this correlation varies by region,with some showing regional linkages and others developing independently.Finally,the dislocation index of ER and EL presents divergent results based on region-the eastern and central regions primarily show a high level of dislocation,whereas the western and northeastern regions show a low level of dislocation.The results provide a comprehensive overview of the spatiotemporal patterns in the association between ER and EL in China.The results emphasize that to balance sustainable regional development and ecological governance,a region-specific approach must be employed,prioritizing innovation-driven strategies for high ER in more developed regions and market-oriented strategies in less developed regions.
基金National Natural Science Foundation of China,No.41501593,No.41601592National Program on Key Research Project,No.2016YFA0602500
文摘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.
基金National Key Research and Development Plan of China,No.2019YFA0606901The Second Tibetan Plateau Scientific Expedition and Research Program(STEP),No.2019QZKK0608+1 种基金The Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA23100303The Fundamental Research Funds for the Central Universities,No.2019NTST01。
文摘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.
基金Supported by Guizhou Province Science and Technology Fund(LKT[2012]07,25).
文摘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.
基金supported by the 2024 Science and Technology Plan Project of Sichuan Province[grant number 2024YFTX0016]the Undergraduate Innovation and Entrepreneurship Training Program[grant number S202510621001].
文摘This study analyzes the spatiotemporal patterns and driving factors of forest fires in Liangshan Prefecture based on fire data from 2016 to 2024 using statistical methods.The results indicate:1)From 2016 to 2024,forest fires in Liangshan Prefecture occurred predominantly between January and May(140 incidents),accounting for 97.90%of the total.March recorded the highest number of fires(48 incidents),representing 33.57%.Within a 24-hour period,113 fires occurred between 12:00 PM and 9:00 PM,constituting 79.02%of all incidents.2)Spatially,Mianning County recorded the highest number of forest fires(28 incidents,19.58%),followed by Xichang,Muli,and Yanyuan with 22,23,and 20 incidents,respectively.Human activities,particularly agricultural burning,outdoor smoking,and other causes,were the dominant factors,collectively accounting for 41%of incidents.3)Forest fires predominantly occurred at elevations between 1500 and 3000 meters(132 fires,92.31%),on slopes with gradients of 5-25 degrees(81 fires,56.65%),on west-facing aspects(northwest,west,southwest)(72 fires,53.14%),in areas with NDVI values between 0.51 and 0.8(79 incidents,55.24%),within 500-2000 m residential buffer zones(151 incidents,98.60%),and within 500 m road buffer zones(103 incidents,72.03%).4)Among meteorological factors,the 20-day average temperature(0.3041),80-day maximum temperature(0.3487),20-day minimum temperature(0.2594),20-day minimum relative humidity(−0.3132),70-day maximum wind speed(0.1885),and 70-day peak wind speed(0.1965)showed the strongest correlations with forest fire burned area.Burned area also exhibited a positive correlation with the Meteorological Drought Index(MCI)on the day of the fire(0.1990).This study confirms the lagged and persistent effects of meteorological factors on forest fire occurrence,providing key scientific evidence for constructing regional fire prediction models that integrate multi-scale meteorological indicators.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.41977405,42061144003).
文摘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.
基金the National Basic Research Program of China(contract:2009CB723902)Key Project of Digital Earth Science Platform CEODE(contract:Y01002101A)National Natural Science Foundation of China(contract:40801127).
文摘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.
文摘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.
基金funded by the Natural Science Foundation of China (Grant No. 42271030)Fujian Provincial Funds for Distinguished Young Scientists (Grant No. 2022J06018)Applied Basic Research Programs of Yunnan province (Grant No. 202001BB050073)。
文摘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.
基金Fundamental Research Funds for the Central UniversitiesNo.19lgzd09+2 种基金Guangdong Special Support ProgramPearl River S&T Nova Program of GuangzhouNo.201806010187
文摘Climate change resulting from CO_2 emissions has become an important global environmental issue in recent years.Improving carbon emission performance is one way to reduce carbon emissions.Although carbon emission performance has been discussed at the national and industrial levels,city-level studies are lacking due to the limited availability of statistics on energy consumption.In this study,based on city-level remote sensing data on carbon emissions in China from 1992–2013,we used the slacks-based measure of super-efficiency to evaluate urban carbon emission performance.The traditional Markov probability transfer matrix and spatial Markov probability transfer matrix were constructed to explore the spatiotemporal evolution of urban carbon emission performance in China for the first time and predict long-term trends in carbon emission performance.The results show that urban carbon emission performance in China steadily increased during the study period with some fluctuations.However,the overall level of carbon emission performance remains low,indicating great potential for improvements in energy conservation and emission reduction.The spatial pattern of urban carbon emission performance in China can be described as"high in the south and low in the north,"and significant differences in carbon emission performance were found between cities.The spatial Markov probabilistic transfer matrix results indicate that the transfer of carbon emission performance in Chinese cities is stable,resulting in a"club convergence"phenomenon.Furthermore,neighborhood backgrounds play an important role in the transfer between carbon emission performance types.Based on the prediction of long-term trends in carbon emission performance,carbon emission performance is expected to improve gradually over time.Therefore,China should continue to strengthen research and development aimed at improving urban carbon emission performance and achieving the national energy conservation and emission reduction goals.Meanwhile,neighboring cities with different neighborhood backgrounds should pursue cooperative economic strategies that balance economic growth,energy conservation,and emission reductions to realize low-carbon construction and sustainable development.
基金funded by the National Natural Science Foundation of China(No.31971460 and 32271646)the National Key Research and Development Program of China(2021YFD2200401)。
文摘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.
基金This work was supported by the National Natural Science Foundation of China project(No 41671183).
文摘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.
基金Under the auspices of National Natural Science Foundation of China(No.42171198,42001117)Science and Technology Development Plan Project of Jilin Province(No.YDZJ202201ZYTS493)。
文摘Studying the spatiotemporal distribution characteristics and coupling coordination relationship of urban and rural resilience is of substantial theoretical and practical significance to improving the ability of urban and rural areas to resist risk and for promoting their coordinated development.This study establishes a comprehensive evaluation index system of urban and rural resilience that encom-passes industrial,social,and ecological subsystems as well as stability,sensitivity,and adaptability.For each of the prefecture-level city in Northeast China,we evaluated its urban and rural resilience and determined the coupling coordination level between them using data spanning 2010,2015,and 2020.The resilience levels of both urban and rural areas in Northeast China are continuously improving.The high-value area of urban resilience is mainly located in the central cities of Northeast China,and prominent in urban agglomeration areas,while rural resilience is predominantly high in the north and low in the south.The high-value area of the coupling coordination degree is mainly distributed in the arc-shaped zone extending from south to north in the eastern part of Northeast China,with the level of coupling coordination increased overall.Non-parametric testing revealed significant differences in urban industrial stability,urban in-dustrial adaptability,rural industrial stability,rural social adaptability,and rural ecological stability among types of cities differing in their coupling coordination development.Our findings provide a reference for enhancing urban and rural resilience and their coordin-ated development path in Northeast China.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFC3209800)the National Natural Science Foundation of China(Grant No.52279011).
文摘In the context of climate change,the acceleration of the global water cycle has led to the emergence of abrupt transitions between drought and flood events,presenting a new challenge for flood and drought disaster mitigation.Abrupt transitions between drought and flood refer to a phenomenon in which an extreme drought event quickly shifts to an extreme flood event,or vice versa,within a relatively short time span.This phenomenon disrupts the traditional spatiotemporal distribution patterns of water-related disasters,reflecting not only the extreme unevenness in the distribution of water resources but also the rapid alternation of the water cycle's evolution(He et al.,2016).Moreover,due to its suddenness,extremity,and complexity,it poses severe threats to human societies and ecosystems.Scientifically addressing abrupt transitions between drought and flood has thus become a new challenge in flood and drought disaster prevention.
基金supported by the National Natural Science Foundation of China(51877034).
文摘The data acquisition technologies used in power systems have been continuously improving,thus laying the solid foundation for data-driven operation analysis of power systems.However,existing methods for analyzing the relationship between operational variables mainly depend on the mathematical model and element parameters of the power system.Therefore,a thorough data-based analysis method is required to investigate the spatiotemporal characteristics of power system operation,especially for new types of power systems.The causal inference method,which has been successfully applied in many fields,is a powerful tool for investigating the interaction of data variables.In this study,a causal inference method is proposed based on supervisory control and data acquisition(SCADA)data for investigating the spatiotemporal causal relationships in power systems.Initially,a multiple data-sequence regression model is proposed to analyze the relationship of operation data variables.Next,the linear non-Gaussian acyclic model(LiNGAM)is used to calculate the causal index of the operational variables,and its limitations are analyzed.Furthermore,a new causal index of“full variable amplitude LiNGAM(FVA-LiNGAM)”is proposed by incorporating prior causal direct knowledge and considering the effect of real variable amplitude.Using the FVA-LiNGAM causal index,the causal relationship of operation variables can be investigated with higher spatiotemporal accuracy than that of the original LiNGAM index.Taking a real SCADA data subset of a provincial power system as an example,the validity of the FVA-LiNGAM causal index is verified.The variation patterns in spatiotemporal causality are explored using actual SCADA data sequences.The result shows that there indeed exists some spatiotemporal causality variation patterns between the operating variables of the power system.
基金International Cooperation Fund of Ecological Effects of Climate Change and Land Use/Cover Change in Arid and Semiarid Regions of Central Asia in the Most Recent 500 Years,No.41361140361The Western Scholars of the Chinese Academy of Sciences,No.2015-XBQN-B-20+1 种基金National Natural Science Foundation of China,No.41471340,No.41605055Hong Kong Baptist University Faculty Research,No.FRG2/17-18/030
文摘The vulnerable ecosystem of the arid and semiarid region in Central Asia is sensi- tive to precipitation variations. Long-term changes of the seasonal precipitation can reveal the evolution rules of the precipitation climate. Therefore, in this study, the changes of the sea- sonal precipitation over Central Asia have been analyzed during the last century （1901-2013） based on the latest global monthly precipitation dataset Global Precipitation Climatology Centre （GPCC） Full Data Reanalysis Version 7, as well as their relations with El Ni~_o- Southern Oscillation （ENSO）. Results show that the precipitation in Central Asia is mainly concentrated in spring and summer seasons, especially in spring. For the whole study period, increasing trends were found in spring and winter, while decreasing trends were detected in summer and fall. Inter-annual signals with 3-7 years multi-periods were derived to explain the dominant components for seasonal precipitation variability. In terms of the dominant spatial pattern, Empirical orthogonal function （EOF） results show that the spatial distribution of EOF-1 mode in summer is different from those of the other seasons during 1901-2013. Moreover, significant ENSO-associated changes in precipitation are evident during the fall, winter, spring, and absent during summer. The lagged associations between ENSO and seasonal precipitation are also obtained in Central Asia. The ENSO-based composite analy- ses show that these water vapor fluxes of spring, fall and winter precipitation are mainly generated in Indian and North Atlantic Oceans during El Nino. The enhanced westerlies strengthen the western water vapor path for Central Asia, thereby causing a rainy winter.
