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Scientific evaluation of the development efficiency of the regional tourism industry has important practical significance in promoting the high-quality development of the industry. This study calculated the county tourism efficiency and total factor productivity (TFP) for 86 counties and cities in Xinjiang, China, from 2011 to 2019 based on the SBM-data envelopment analysis model and the Malmquist productivity index model, which determines the respective temporal changes and spatial differences. The factors affecting the evolution of the spatial–temporal pattern of the tourism industry efficiency were also analyzed using the geographic detector model. The results show that: (1) The average tourism efficiency of Xinjiang county from 2011 to 2019 was at a low level of 0.382. During the study period, the evolution trend of the tourism efficiency fluctuated. There was a positive spatial autocorrelation in the tourism efficiency. The difference between cold and hot spots was evident by “hot-in-the-north and cold-in-the-South” characteristics. (2) The TFP maintained an upward trend during the research period, with an average annual growth rate of 28.7%. The number of counties and cities with an increased TFP was much higher than those with a decreased TFP, and its growth was mainly attributed to the progress of technical efficiency. (3) The county tourism efficiency was mainly affected by the level of economic development, tourism resource endowment, market scale, and government policies. There were large differences in the intensity and space among various influencing factors. During the research period, the influence of the economic development level and market scale gradually weakened, and the influence of tourism resource endowment and government policies continuously strengthened.

[Objective]The aims of this study are to examine the spatial pattern evolution and its influencing factors of rural settlements in hilly and mountainous areas of eastern Fujian, and to provide scientific basis for the optimization and reconstruction of spatial layout of rural settlements.[Methods]Pingnan County in eastern Fujian was taken as an example. Kernel density analysis, landscape pattern index and GIS spatial analysis method were used to analyze the spatial and temporal evolution characteristics of rural settlements in Pingnan County from 2009 to 2019, and geographical detectors were used to reveal the influencing factors of evolution.[Results](1)In the past 10 years, the number and scale of rural settlements in Pingnan County only increased slightly.Among different levels of settlements, the area of large settlements accounted for the largest proportion, but the number increase and scale expansion were mainly small settlements.(2)The overall morphological evolution of rural settlements tended to be complex and fragmented from rules, but there was a trend of settlement contiguous in the surrounding areas of the county. The single form of rural settlements was dominated by dots, accounting for 67.84％.(3)The spatial distribution of rural settlements weakly concentrated, the whole concentrated in the middle, and the distribution pattern was sparse around, but the distribution of settlements in the central and southern parts of the county was becoming more and more concentrated in the past 10 years. Controlled by terrain, rural settlements mostly distributed in intermountain basins and have low slope directivity.(4)Topographic relief was the main natural factor controlling the evolution of the spatial pattern and scale of rural settlements in Pingnan County, but the economic development of the county and the improvement of transport accessibility in the past 10 years had become important factors driving the expansion of the scale of rural settlements in Pingnan County in the new period.[Conclusion]The natural factors in Pingnan have shaped the basic spatial pattern of rural settlements, and the location and socio-economic factors are the driving force for the continuous expansion of the scale of rural settlements, and the interaction of natural, location and economic factors promotes the further evolution of rural settlements. [ABSTRACT FROM AUTHOR]

In order to promote the high-quality and sustainable development of marine economy, the paper selected the panel data of ocean economy in terms of inputs and outputs, used the super-efficiency model to analyze the temporal and spatial pattern evolution and dynamic mechanism of China′s marine economic efficiency, and put forward development suggestions. The results showed that during the period from 2001 to 2019, China′s marine economic efficiency curve presented the phenomenon of overall forward development, stage twists and turns, peaks and valleys alternate. The 10th 5-Year Plan period was the extensive development stage, the 11th 5-Year Plan period was the transformation and upgrading stage, and the 12th 5-Year Plan and the 13th 5-Year Plan periods were the sustainable development stage. The regional development of marine economic efficiency was unbalanced, and its evolution types included stable, fluctuating and rising. Among them, Shanghai had maintained an upward momentum, while Guangxi and other regions had been low for a long time. The dynamic mechanisms of the evolution of the marine economic efficiency pattern were as follows: the 10th 5-Year Plan period was driven by resources, the 11th 5-Year Plan period was driven by technology, the 12th 5-Year Plan and 13th 5-Year Plan periods were driven by 2 wheels of policy and technology. In the future, some measures should be taken in the coordinated development of marine economy and ecological civilization, optimization of marine industrial structure, coordinated development of regional marine economy, and innovation-driven development of marine science and technology.

Abstract The interfacial interactions between 2D materials and polymer substrates receive increasing interest due to the surge of flexible electronics, multifunctional coatings, and nanocomposites. Although the strain effect on electrical, optical, and mechanical properties of 2D materials is extensively investigated, understanding the interfacial mechanics of 2D material‐polymer systems by dynamic loading is still a challenge. Here, the interfacial degradation and pattern evolution of mechanically exfoliated single‐ and few‐layer graphene on polydimethylsiloxane (PDMS) substrates by cyclic mechanical loading, are reported. It is found that the tensile strain leads to interfacial slippage between graphene and PDMS, whereas the compressive strain can be transferred to graphene with a transfer efficiency above 80%. Through cyclic loading, the graphene surface is seriously deformed by formation of multiple instability patterns including wrinkles and cracks. The morphological characteristic and evolution mechanism of the wrinkles and cracks are analyzed and discussed in detail. The interfacial adhesion energy is evaluated by wrinkle profiles and it decreases from ≈23 to ≈2 mJ m−2 as the cycle number increases. This work can promote better understanding of the interfacial effect of 2D materials on polymer substrates and controllable fabrication of various wrinkled or crumpled surfaces of 2D functional materials by cyclic mechanical loading.

In order to investigate the evolution characteristics of gas-liquid two-phase flow passing through a 90° pipe bend, the volume of fluid (VOF) multiphase flow model and the Realizable k-ε turbulence model are used to conduct numerical simulations. The evolution of velocity, pressure distribution, gas void fraction, and flow pattern passing through a 90° pipe bend is studied in detail. The results show that different gas-liquid two-phase flow patterns will produce different degrees of secondary flow phenomenon after passing through the 90° pipe bend, and the tangential velocity presents a bimodal distribution, which eventually dissipates into a unimodal distribution in the horizontal pipe. The pressure on the outer wall of the pipe bend increases as the inlet velocity increases. The change of gas void fraction is related to the transformation of the flow pattern, the bubbly flow evolves into a slender slug flow in the horizontal pipe after passing through the 90° pipe bend, and the gas void fraction will decrease. The slug flow, the churn flow, and the annular flow evolve into the stratified-wave flow in the horizontal pipe after passing through the pipe bend, and the variation of the gas void fraction is relatively low. The research results can provide certain theoretical support for the design and development of gas-liquid two-phase flow conveying elbows and the prediction of induced stress.

[Objective] The temporal and spatial variation characteristics and their the influencing factors of cultivated land conversion in Yan'an City from 2000 to 2020 were analyzed in order to provide a theoretical basis for policy-making regarding cultivated land protection and prevention of farmland conversion. [Methods] Land-use and land-cover change data for 2000, 2005, 2010, and 2020 were analyzed to reveal the degree and causes of non-agriculturalization in the Loess Plateau. The research was carried out by using the methods of kernel density estimation and geodetector. [Results] ① From 2000 to 2020, the non-agricultural area of cultivated land in Yan'an City changed following a pattern of increase-decrease-increase. The total non-agricultural area was 7 865.28 hectares, and the non-agricultural conversion rate of cultivated land was 8.45%. ② From 2000 to 2020, cultivated land conversion in Yan'an City was mainly located along the river valleys of the Luohe River and the Yanhe River. The non-agricultural conversion of cultivated land was concentrated in the central and southern regions, with a maximum kernel density of 155.03 located near Yan'an New City, Baota District. The sub-concentration areas of non-agricultural cultivated land were Huangling County and Luochuan County, with maximum kernel densities of 75.95 and 51.77, respectively. ③ The phenomenon of non-agriculturalization of cultivated land in Yan'an City mainly occurred in areas with low slope, medium altitude, and low topographic index. ④ The most important factors affecting the conversion of cultivated land in Yan'an City were urban population, registered population, and gross domestic product, with explanation rates of 68.65%, 68.45%, and 66.54%, respectively. [Conclusion] The phenomenon of cultivated land conversion in Yan'an City from 2000 to 2020 was significant. The temporal changes were volatile, and the spatial heterogeneity was strong due to the comprehensive effects of nature, population, and social economy.

Abstract Wetland structure evolution is a basis of healthy ecosystem and one of the important indicators for restoration and protection of wetlands. In this paper, based on the Landsat remote sensing images from 1980 to 2020, the wetland structure was extracted by using the supervised classification method in the Dongping Lake. A CA–Markov Model was put forward to set up wetland transfer matrix and to improve the space and quantity of simulation results. The temporal-spatial evolution of the wetland and landscape indicators were studied, and the evolution trend as well as driving forces were analyzed. The studied results show that, in recent years, the wetland landscape pattern transfer were occurred continuously, in which the area of bare land significantly decreased, the infrastructure land use significantly increased, the natural water surface increased gradually. The studied landscape pattern indices show that the wetland landscape evenness index increased, the landscape diversity index tends to be decreased, the degree of wetland landscape fragmentation is basically balanced, but the overall trend is increasing, and the landscape diversity tends to be simple. At present, the area of wild reeds takes the dominant trend in the main wetland area, which accounts for 55% of the total wetland area. The proportion of forest and grass land area accounts for 9%.

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With the development of urban built-up areas, accurately extracting the urban built-up area and spatiotemporal pattern evolution trends could be valuable for understanding urban sprawl and human activities. Considering the coarse spatial resolution of nighttime light (NTL) data and the inaccurate regional boundary reflection on point of interest (POI) data, land surface temperature (LST) data were introduced. A composite index method (LJ–POI–LST) was proposed based on the positive relationship for extracting the boundary and reflecting the spatial-temporal evolution of urban built-up areas involving the NTL, POIs, and LST data from 1993 to 2018 in this paper. This paper yielded the following results: (1) There was a spatial-temporal pattern evolution from north-east to south-west with a primary quadrant orientation of IV, V, and VI in the Hefei urban area from 1993–2018. The medium-speed expansion rate, with an average value of 14.3 km2/a, was much faster than the population growth rate. The elasticity expansion coefficient of urbanization of 1.93 indicated the incongruous growth rate between the urban area and population, leading to an incoordinate and unreasonable development trend in Hefei City. (2) The detailed extraction accuracy for urban and rural junctions, urban forest parks, and other error-prone areas was improved, and the landscape connectivity and fragmentation were optimized according to the LJ–POI–LST composite index based on a high-resolution remote sensing validation image in the internal spatial structure. (3) Compared to the conventional NTL data and the LJ–POI index, the LJ–POI–LST composite index method displayed an extraction accuracy greater than 85%, with a similar statistical and landscape pattern index result. This paper provides a suitable method for the positive relationship among these LST, NTL, and POI data for accurately extracting the boundary and reflecting the spatial-temporal evolution of urban built-up areas by the fusion data.

Abstract Starting from the overall pattern of wetland evolution in the Yellow River Delta, the combination of CA–Markov model and MLP model is studied. Based on the low-medium resolution Landsat data and the field survey data, the evolution trend of wetland landscape pattern in the Yellow River Delta is simulated and predicted by using the proposed models. Taking high resolution (2 m) data in 2016 as the precision verification, the model simulation results are validated. The results show that the area of natural wetlands in the Delta was decreased from 2593.63 km2 in 1976 to 1639.60 km2 in 2016, a total area of 954.03 km2wasreduced. According to the model simulation, the natural wetland area in 2026 is predicted to be 1252.7 km2, the constructed wetland area will be 1265.0 km2, and the non-wetland area will be 924.5 km2. The constructed wetland in the Yellow River Delta is increasing and spreading into the sea, but the area of natural wetland has been decreasing. If this trend be developed, the national natural wetland conservation target would not be realized. The results are of great significance to the wetland development planning, management and protection in the Yellow River Delta.

In this paper, the transesterification reaction of waste cooking oil (WCO) with methanol using KOH as catalyst to produce biodiesel was performed in a micro-reactor (1 mm ID) using a cross-flow inlet configuration. The effects of different variables such as, methanol-to-oil molar ratio, temperature, catalyst concentration, and residence time on biodiesel yield, as well as the associated flow patterns during the transesterification reaction were investigated and the relationship between flow characteristics and mass transfer performance of the system was examined. The work reveals important aspects and the links between the hydrodynamic behaviour and the mass transfer performance of the intensified reactors. It was found that high yield (>90%) of biodiesel can be achieved in one-stage reaction using cross-flow micro-reactors for a wide range of conditions, i.e., methanol-to-oil molar ratio: 8–14, catalyst concentration: 1.4%–1.8% w/w, temperature: 55°C–60°C, and residence times: 55–75 s.

Ensuring food and nutrient supply is a crucial aspect of achieving food safety. With rapid population growth, urbanization, and social and economic development, the challenges related to China’s food and nutrient production have become increasingly prominent. This paper analyzed the characteristics of the spatiotemporal pattern evolution of food and nutrient production in China from 1995 to 2020, utilizing the conversion of various food nutrients and the establishment of a gravity center model. The results showed that: (1) Food production exhibited increasing trends in China, six regions, and 90% of the provinces. Notably, the structure of food production underwent significant changes in China, East China, Central-South China, Southwest China, Northwest China, and 60% of the provinces. (2) The output of all categories of food nutrients demonstrated increasing trends in China, six regions, and most provinces. At three different geographical scales, the changes of six food nutrients production structure showed significant differences. (3) Natural, political, social, economic, and technological factors played pivotal roles in influencing the gravity centers of food and nutrient production in China. The gravity centers of cereal production shifted northeast, while those of root and tuber, oil crops, and stimulants production moved westward. Additionally, the gravity centers of sugar crop, pulse, vegetable, fruit, and aquatic product production moved southwest and those of livestock and poultry production shifted northward. (4) Affected by the food production, the gravity centers of food energy, food protein, and food carbohydrate production shifted northward, while those of food fat, food vitamins, and food minerals production shifted northwest, southwest, and westward, respectively. The results of this study are of great significance for policy adjustments pertaining to the distribution pattern of food production, food security stability, and sustainable development in China.

Abstract Fluid‐structure coupling is the main cause for the vibration of fluid‐conveying pipelines, and fluid‐solid coupling vibration of fluid‐conveying pipelines is a “typical dynamic problem.” The present paper analyzes the dynamic characteristics and dynamic response of the elbow with simultaneous dual‐thread analysis, aiming to clarify the dynamic change law of pipe vibration induced by gas‐liquid two‐phase flow in the elbow. It can be concluded that the characteristics of the slug flow developed from the interphase instability mechanism have been captured in the volume of fluid (VOF) method. The dynamic evolution information of different two‐phase flow patterns is often accompanied by complex self‐similarity, but has different complex structures, chaotic characteristics, and dynamic behaviors. The unique modal frequencies of each order are applied to the elbow to obtain different exclusive mode shapes. The evolution of the flow pattern is related to the increase in the wave height, and the wave amplitude often depends on the gas‐liquid superficial velocity. The superficial liquid velocity is more sensitive to the influence of flow pattern formation and vibration than that of gas.

As an emerging strategic industry with high added value, wide application, and low energy consumption, the software and information technology service industry plays an important role in promoting the development and transformation of the national economy. The reasonable layout of the software and information technology service industry is of great significance to issues such as industrial development and optimizing the urban spatial structure. Based on the registration data of industrial and commercial enterprises, this study uses spatial analysis methods, such as Kernel Density(KDE) and Multi-Distance Spatial Cluster Analysis(Ripley's K), to study the spatial pattern evolution characteristics of software and information technology service enterprises in the main urban area of Chongqing from 2002 to 2017. In addition, this paper uses the Tobit model to explore the impact of location , transportation, industrial agglomeration and policies on the location of enterprises. The research shows that: (1) From the current distribution, the urban middle circle, which is 4-12 km away from the city center, has become the main space for the distribution of software and information technology service enterprises in the main urban area; it forms a "double peak" circle distribution. The spatial distribution pattern is expressed as "one main twice," and the agglomeration feature is remarkable. (2) From 2002 to 2017, while the distribution of enterprises was suburbanized, a large number of enterprises were concentrated 6-8 km away from the city center. The circle distribution changed from a "double peak" structure to a "single peak" structure, and the spatial pattern gradually evolved from a single center to "one main twice"; further, the intensity and scale of agglomeration also increased continuously. (3) Industrial agglomeration has the most significant impact on the location selection of software and information technology service enterprises in the main urban area. The location conditions and intra-city traffic factors have significant impact. The factors of spatial planning policy and external transportation facilities on the selection of enterprises' location are not significant. These research results show that the spatial distribution of the software and information technology service industry in the main urban area of Chongqing presents the characteristics of being concentrated in the middle layer of the city, having multiple centers, and of suburbanization. Compared to software companies in Shanghai, Nanjing, and other cities, the special landscape pattern and relatively backward development stage make the software and information technology service companies in the main urban area of Chongqing have a stronger preference for the urban middle circle. Additionally, the results of the influencing factors of location choice indicate that with the deepening of industry development, the role of various factors in the choice of enterprises' location is also changing. For Chongqing, which is undergoing industrial upgrading, these research findings can provide reference and guidance for the upgrading and transformation of Chongqing's industrial structure, and also provide a basis for understanding the optimization of the urban spatial structure of the main urban area. Nevertheless, due to problems such as data acquisition and the difficulty of quantifying some corporate location factors, this research is possibly inadequate and more in-depth research is needed.

The study determines the coupling degree of green investment and green ecology in China using kernel density estimation, spatial autocorrelation analysis, and standard deviation ellipse model to empirically evaluate the data of 30 Chinese provinces from 2005 to 2019. Moreover, the study investigates the temporal evolution trend, spatial clustering characteristics, and spatial evolution trend of coupling degree. Although the coupling coordination value of green investment and green ecology gradually increased, it is generally at a low coordination stage. At the same time, regional disparities narrowed with the most significant variability in the eastern region. Moreover, results found that the aggregation effect of the coupling and coordination of green investment and green ecology is more significant, and the high-value aggregation area extended from the lower reaches of the Yangtze River to the midstream region, while the western region is dominated by low-value aggregation. Similarly, the degree of synergy between green investment and green ecology is increased; however, the fragmentation trend is inevitable. At the same time, the center of gravity of coupling coordination shifted to the western regions, and the spatial pattern gradually weakened in the “northeast-southwest” direction. The findings of the study stress that local governments of China should improve the green investment system for green ecological development in the surrounding areas of the Yangtze River Economic Belt. Moreover, it is required to focus on the Northeast revitalization and Western development strategies to promote the synergistic development of green investment and green ecology.

To overcome the problems of low accuracy of prediction results and high energy consumption in the prediction process existing in traditional forecasting methods, a prediction method of urban landscape pattern evolution based on Markov process was designed in this study. On the basis of designing the prediction principle of urban landscape pattern evolution, patch average area, patch type area, maximum patch index, patch number, and landscape percentage were selected to describe the patch types in landscape space, and then the landscape index was calculated. Based on this, the specific evolution of urban landscape pattern is predicted based on Markov process. The experimental results show that the prediction accuracy of the method is high, and the energy consumption of the prediction process is low, which proves that the method achieves the design expectation. [ABSTRACT FROM AUTHOR]

In our study, using the analysis of DNA barcodes and morphology (wing color, male genitalia, and female sphragis shape), we show that the group of species close to P. mnemosyne comprises the western and eastern phylogenetic lineages. The eastern lineage includes P. stubbendorfii, P. glacialis, and P. hoenei. The western lineage includes three morphologically similar species: P. mnemosyne (Western Eurasia), P. turatii (southwestern Europe), and P. nubilosus stat. nov. (Turkmenistan and NE Iran), as well as the morphologically differentiated P. ariadne (Altai). The latter species differs from the rest of the group in the presence of red spots on the wings. Parnassius mnemosyne s.s. is represented by four differentiated mitochondrial clusters that show clear association with specific geographic regions. We propose to interpret them as subspecies: P. mnemosyne mnemosyne (Central and Eastern Europe, N Caucasus, N Turkey), P. mnemosyne adolphi (the Middle East), P. mnemosyne falsa (Tian Shan), and P. mnemosyne gigantea (Gissar-Alai in Central Asia). We demonstrate that in P. ariadne, the red spots on the wing evolved as a reversion to the ancestral wing pattern. This reversion is observed in Altai, where the distribution areas of the western lineage, represented by P. ariadne, and the eastern lineage, represented by P. stubbendorfii, overlap. These two species hybridize in Altai, and we hypothesize that the color change in P. ariadne is the result of reinforcement of prezygotic isolation in the contact zone. The lectotype of Parnassius mnemosyne var. nubilosus Christoph, 1873, is designated.

Dynamic light scattering (DLS) and laser speckle contrast imaging (LSCI) are closely related techniques that exploit the statistics of speckle patterns, which can be utilized to measure cerebral blood flow (CBF). Conventionally, the temporal speckle intensity auto-correlation function g 2 t ( τ ) is calculated in DLS, while the spatial speckle contrast K s is calculated in LSCI measurements. Due to the rapid development of CMOS detection technology with increased camera frame rates while still maintaining a large number of pixels, the ensemble or spatial average of g 2 s ( τ ) as well as the temporal contrast K t can be easily calculated and utilized to quantify CBF. Although many models have been established, a proper summary is still lacking to fully characterize DLS and LSCI measurements for spatial and temporal statistics, laser coherence properties, various motion types, etc. As a result, there are many instances where theoretical models are misused. For instance, mathematical formulas derived in the diffusive regime or for ergodic systems are sometimes applied to small animal brain measurements, e.g., mice brains, where the assumptions are not valid. Therefore, we aim to provide a review of the speckle theory for both DLS and LSCI measurements with detailed derivations from first principles, taking into account non-ergodicity, spatial and temporal statistics of speckles, scatterer motion types, and laser coherence properties. From these calculations, we elaborate on the differences between spatial and temporal averaging for DLS and LSCI measurements that are typically ignored but can result in inaccurate measurements of blood flow, particularly the spatially varying nature of the static component in g 2 t ( τ ) and K t . We also obtained g 2 s ( τ ) maps in in vivo mouse brain measurements using high frame rate CMOS cameras which have not been demonstrated before, and compared with g 2 t ( τ ) and K s , t . This work provides a useful guide for choosing the correct model to analyze spatial and temporal speckle statistics in in-vivo DLS and LSCI measurements., Competing Interests: The authors declare no conflicts of interest., (© 2024 Optica Publishing Group.)

In order to describe the evolution process of global rare earth trade clearly, based on the United Nations commodity trade data from 1991 to 2021, social network analysis method was used to sort out the spatial and temporal evolution characteristics of global rare earth trade pattern since 1991. The results show that: ① In terms of the structure of rare earth trade products, downstream products always dominate the import and export of rare earth. China has become a major importer and exporter of rare earth with its strong market demand and resource endowment. ② In terms of network structure, the complexity of global rare earth trade network is gradually increasing, showing the characteristics of network structure dominated by exporting countries, and the trading countries with high node degree are in the core position in the whole network. "Peer-to-peer" trade patterns are obvious and economies are highly dependent on each other. ③ The interdependence degree of rare earth trade between China and other countries (regions) is deepening, the scale of individual network is expanding, the role of "bridge" in the rare earth trade network is significantly improved, the ability to use structural holes is increasing year by year, and the flexibility and freedom of the network are constantly enhanced. [ABSTRACT FROM AUTHOR]

To reveal the level and variation characteristics of China ′s grain production eco-efficiency, this paper estimates the grain ecoefficiency of 30 provinces from 2000 to 2021 based on the super-efficiency SBM model, reveals its evolution characteristics through nonparametric kernel density analysis, and analyzes its influencing factors through fixed effect model. The results show that: from the perspective of grain eco-efficiency level, China ′s grain eco-efficiency increased from 0.662 to 0.787 from 2000 to 2021, with an average annual increase of 0.827%. The change trend of grain eco-efficiency in the main production area and the production and marketing balance area is similar to the national level, while the main sales area is far lower than the national average; from the perspective of the evolution of spatial and temporal patterns, China ′ s grain eco-efficiency has long been polarized between high-high agglomeration and low-low agglomeration, and has gradually gathered to a higher level over time, showing the characteristics that the north is higher than the south, and the major producing areas are higher than the non-main producing areas. Among the influencing factors, the influence of per capita GDP and grain operation scale is significantly positive, and the influence of chemical fertilizer application intensity, agricultural machinery intensity and natural disasters is significantly negative. The research shows that the overall level of China ′s grain eco-efficiency is still low and the regional gap is large. Most provinces have not reached the efficiency frontier, and there is a large room for improvement. [ABSTRACT FROM AUTHOR]

[Objective] The evolution characteristics and correlation degree of landscape pattern and carbon source/carbon sink in Karamay city were studied in order to provide reference for regional low-carbon development and adjustment of land use and optimization of land man- agement. (Method) Based on the remote sensing image data of Karamay city from 1995 to 2021, the paper uses Frastate4. 2 software to calculate the landscape pattern index, uses the carbon emission coefficient method to estimate the carbon source/carbon sink of land use, and uses the grey correlation model to measure the correlation between the two. [Result] (i) From 1995 to 2021, the landscape fragmentation of Kara- may city showed an upward trend, the largest patch type decreased continuously, the patch distance was dispersed, the landscape distribution was complicated, the segmentation degree was gradually serious, the landscape diversity changed from single to complex, and the landscape types tended to be diversified. (ii) From 1995 to 2021, the carbon source/carbon sink of Karamay city showed an upward trend. Because the amount of carbon source was significantly greater than the amount of carbon sink, Karamay city was finally the carbon source area and the net carbon emissions increased year by year. (iii) The increase of carbon emissions in Karamay city was closely related to the gradual seriousness of landscape segmentation in the study area, the complexity of landscape distribution, the dispersion of patch distance in the landscape and the continuous decrease of the largest patch area. [Conclusion] The landscape pattern of landscape level and patch type level in Karamay city is closely related to carbon emissions, and each landscape pattern index is the main factor affecting the change of carbon emissions. [ABSTRACT FROM AUTHOR]

Kunming is the capital city of Yunnan Province and a bridgehead city facing South Asia and Southeast Asia. With the rapid development of Kunming's economy and society, the urbanization rate continues to increase, and the quality of the ecological environment in this area is also changing rapidly. How to quickly and accurately obtain the temporal and spatial pattern evolution of Kunming's ecological environment quality and explore the driving factors is of great significance to the realization of ecological environmental protection and sustainable development of Kunming. In this paper, the Google Earth Engine (GEE) platform is used to use the long-term Landsat remote sensing image data to mask the water body, extract greenness, dryness, humidity and heat, and construct the remote sensing ecological index RSEI through PCA. Using spatial analysis methods such as cold and hot spot analysis and center of gravity migration to explore the evolution of the spatio-temporal pattern of ecological environment quality in Kunming from 2000 to 2019, and use single-factor analysis and interactive detection in geographic detectors to analyze its internal driving forces. The results show, (1) From 1995 to 2019, the quality of the ecological environment in Kunming showed a trend of first increasing-then decreasing-then increasing. The overall ecological environment quality was in a general state in the past 25 years, but the ecological environment continued to improve. (2) In the past 25 years, the ecological environment quality grade area of Kunming City is, medium ecological environment area > good ecological environment area > poor ecological environment area > poor ecological environment area > excellent ecological environment area. From the perspective of spatial distribution, the ecological environment quality presents The spatial distribution pattern of high in the southwest and poor in the northeast. (3) From 1995 to 2019, the centers of the standard deviation ellipse of Kunming's ecological environment were relatively close to each other, and the major axes all showed a south-north direction. (4) In Kunming, the ecological environment quality is poor in areas with concentrated rocky desertification, concentrated water and soil erosion, concentrated population and rapid urban expansion, while areas with better ecological environment mostly have higher vegetation coverage. Population and slope are the human activity factors and natural factors that dominate the spatial distribution of ecological environment in Kunming, respectively. Slope, population and GDP, together with other factors, have a significant impact on the quality of ecological environment in Kunming. (5) In the future, Kunming City should rigorously prioritize the protection of key ecological areas, enhance ecological conservation and restoration efforts, optimize land use and development, continuously enhance the quality of the ecological environment, and achieve synchronous and sustainable development of the ecological environment and the economy. [ABSTRACT FROM AUTHOR]

【Objective/Meaning】By exploring the spatial and temporal pattern and evolution process of carbon emissions in the metropolitan area of Fuzhou from 2001 to 2020, it would provide reference for the green development of metropolitan area in Fuzhou and the reasonable control of carbon emissions in the metropolitan area of China.【Methods/Procedures】The influencing factors and mechanism of the spatial and temporal pattern evolution of carbon emissions in the metropolitan area of Fuzhou were analyzed, and then the suggestions for the sustainable development and transformation of industrial structure in the metropolitan area of Fuzhou were discussed. 【 Results/Conclusions】 The results showed that: (1) From the perspective of time series, the interannual variation of total carbon emissions in the metropolitan areas could be roughly divided into two stages: a rapid growth period from 2001 to 2011, during which there was a rapid increase in the carbon emissions of the metropolitan area, and a fluctuation adjustment period from 2012 to 2020, during which the adjustment of energy structure in the metropolitan area slowed down the continued growth of carbon emissions. (2) In terms of the evolution of spatial and temporal pattern, the spatial pattern of carbon emissions in the metropolitan area of Fuzhou has gradually concentrated from the early scattered layout to the southeastern coastal areas showing a circular spatial layout with Fuqing City as the core. (3) In terms of the driving factors, the population growth, regional economic development, and industrial structure were the important influencing factors. Based on this, by combining the research findings with the existing experience, the countermeasures were put forward for the industrial transformation and energy structure optimization of metropolitan area in Fuzhou. [ABSTRACT FROM AUTHOR]

In recent years, air pollution related to PM2.5 has caused a significant impact on human health. The Grand Canal (GC) is not only a great Cultural heritage created in ancient China but also the longest and largest canal in the world. Based on remotely sensed PM2.5 gridded data in the GC region covering 2000 to 2018, we used the holistic methods of standard deviation ellipse, local moran index, slope trend analysis to reveal the spatiotemporal evolutions of PM2.5 concentrations in the GC regions and investigated the driving factors of PM2.5 concentrations by using the geographically weighted regression (GWR) model. Results show that (1) PM2.5 concentrations in the GC region exhibited an increasing trend and followed by a decreasing trend from 2000 to 2018 (the turning point emerged in 2010). (2) The standard deviation ellipse analyses show that the spatial distributions of PM2.5 concentrations featured more and more concentrated over time, whereas, after the year 2010, the distributions gradually featured scattered. (3) The concentrations of PM2.5 exhibited the strong effects of local spatial autocorrelation and areas with "high-high" agglomeration were mainly located in the central and west regions of the GC region and gradually expanded to the north over time. (4) The areas of regions with rapidly increasing in PM2.5 concentrations gradually decreased over time, however, those with rapidly decreasing in PM2.5 concentrations increased. (5) The influences of the natural factors and socio-economic factors on the distributions of PM2.5 concentrations varied spatially. In detail, the elevation was negatively correlated with PM2.5 concentrations, whereas an opposite relationship between industrial structure and PM2.5 concentrations was observed. The coefficients of rainfall, population density, GDP per capita and foreign investment show different results in positive and negative correlations depending on the position.

Nowadays, the challenges of energy depletion, environmental pollution and food security caused by extensive agriculture development are attracting global attention. In China, the construction of ecological farms is a key initiative to effectuate the goal of peaking carbon dioxide emissions and achieving carbon neutrality, contributing to high-quality agricultural development. Based on this, this study selects the national-level ecological farms directories issued by the Ministry of Agriculture and Rural Affairs (MARA) of China in 2021 and 2022, and collects the corresponding economic, social and physical geographic data for GIS spatial analysis and Geodetector. The results are as follows: (1) The distribution of ecological farms in various provinces of China is uneven and spatially clustered. It generally presents a ‘high in the east and low in the west with concentrated cores’ pattern. The construction scope significantly expanded over time, and the high-value areas of nuclear density are concentrated in East China, with the development core transitioned from East China to Central China. (2) Environmental conditions, industrial foundation, economic and social development level, science and technology level and financial support all significantly affect the spatial distribution of ecological farms in China, among which the science and technology level has the most significant enhancement effect on other factors. (3) Environmental conditions provide the construction basis for ecological farms, while economic and social development level and financial support determine the number of ecological farms. The industrial foundation affects the scale of ecological farms in China, while the level of science and technology eliminates the restrictions of other factors to a certain extent. This study provides a reference for optimizing the spatial distribution pattern of ecological farms in China and promoting ecological agriculture. In addition, it presents a viable approach to safeguarding food security.

Based on thin plate tensile tests of super-elastic NiTi alloy at different temperatures, a trilinear elasto-plastic constitutive model was adopted and the effect of latent heat of phase transformation on the temperature rise was considered through an equivalent method of thermo-physical constants.The transformation pattern evolutions were simulated by finite element software ABAQUS, and the rate-dependent mechanisms were also revealed. The simulated results show that the stress-induced martensitic transformation occurs under tensile loading, which macroscopically exhibits as the initiation, propagation and merging of local transformation bands; due to the release of latent heat, the initiation of transformation bands is accompanied by local temperature rise, and peak temperature rise is closely related to the loading strain rate; the local transformation bands are at a certain angle to the loading direction, which is about 50°-65°; with the increase of loading rate, the sample is changed from the isothermal state to the adiabatic one, the transformation stress and local temperature rise increase then. Therefore, the transformation tends to occur in the low temperature region, which results in an increasing number of transformation bands. The simulated transformation patterns and temperature field evolutions of super-elastic NiTi alloy at different strain rates are in good agreement with the corresponding experimental results, which provide a reference for clarifying the evolution of transformation localization of the alloy.

Vertebrate pigmentation patterns are amongst the best characterised model systems for studying the genetic basis of adaptive evolution. The wealth of available data on the genetic basis for pigmentation evolution allows for analysis of trends and quantitative testing of evolutionary hypotheses. We employed Gephebase, a database of genetic variants associated with natural and domesticated trait variation, to examine trends in how cis-regulatory and coding mutations contribute to vertebrate pigmentation phenotypes, as well as factors that favour one mutation type over the other. We found that studies with lower ascertainment bias identified higher proportions of cis-regulatory mutations, and that cis-regulatory mutations were more common amongst animals harbouring a higher number of pigment cell classes. We classified pigmentation traits firstly according to their physiological basis and secondly according to whether they affect colour or pattern, and identified that carotenoid-based pigmentation and variation in pattern boundaries are preferentially associated with cis-regulatory change. We also classified genes according to their developmental, cellular, and molecular functions. We found a greater proportion of cis-regulatory mutations in genes implicated in upstream developmental processes compared to those involved in downstream cellular functions, and that ligands were associated with a higher proportion of cis-regulatory mutations than their respective receptors. Based on these trends, we discuss future directions for research in vertebrate pigmentation evolution., (© 2023 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.)

Carbon emissions based on land use change have attracted extensive attention from scholars, but the current land use carbon emission accounting model is still relatively rough. Despite the continuous promotion of China’s ecological civilization strategy, whether green economic development promotes carbon emission reduction remains to be studied. This study uses the Exploratory Spatial-temporal Data Analysis (ESTDA) framework system to revise the land-use carbon emission accounting model; it integrates the NDVI adjustment index and systematically analyzes the spatial and temporal patterns and evolutionary path characteristics of carbon emissions from 2000 to 2020 for 130 prefecture-level cities in the eastern coastal region of China, a high carbon emission region. The spatial econometric model is further used to explore the impact of green economy development on carbon emissions. The results show that the spatial distribution of carbon sources and sinks in the eastern coastal cities demonstrates a year-on-year increase during the study period. The spatial distribution of carbon sources is higher in the north than in the south, and the economically developed regions are more elevated than less developed economic areas. Net carbon emissions show prominent spatial clustering characteristics. The south has a more stable internal spatial structure than the north, and the inland has a more stable internal spatial structure than the coast. Green economic development can significantly reduce carbon emission intensity and has a significant spatial spillover effect. The findings imply that policy-makers need to consider the spatial and temporal distribution and spatial correlation of carbon emissions among cities; they can achieve carbon emission reduction by formulating a more reasonable green economy development approach and implementing regional linkages.

[Objective] This study aims to explore the evolution process and driving factors of land use landscape in Kuye River Basin from 1980 to 2020, and to provide reference for the management and high-quality development of ecosystem in the whole Yellow River Basin. [Methods] Landsat series remote sensing data were selected as the data source, and the characteristics of land use landscape pattern change in the Kuoye River Basin were analyzed by landscape ecology and GIS spatial analysis. Combined with climate data and socioeconomic data, the driving factors of land use landscape pattern evolution in Kuye River Basin were discussed. [Results] The cultivated land area in the Kuye River Basin decreased from 1 677.92 km 2 in 1980 to 1 365.58 km 2 in 2020. The grassland area decreased from 5 144.35 km 2 in 1980 to 5 038.97 km 2 in 2020. The forestland area and construction land area increased by 86.07 km 2 and 798.96 km 2, respectively, while the water area and unused land area decreased by 60.25 km ² and 408.72 km ², respectively. From 1980 to 2020, the transfer of land use types was mainly from unused land to arable land and grassland, accounting for 8.63% and 61.47% of the reduction of unused land area. Arable land, grassland and unused land transferred to construction land accounted for 23.07%, 50.98% and 10.95% of the increase of construction land area, and the intensity of land use type transfer from 2000 to 2020 was higher than that from 1980 to 2000. The landscape patches in the watershed showed the characteristics of increasing the number of patches, decreasing the degree of connectedness, increasing the degree of fragmentation, increasing the degree of segmentation, decreasing the degree of cohesion and increasing the complexity. [Conclusion] Climate change and human activities are both the influencing factors of landscape pattern evolution in Kuye River Basin, among which the increasing human activities are the main factor promoting landscape pattern evolution, while climate change is the secondary factor. [ABSTRACT FROM AUTHOR]