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Forest fires pose a significant threat to forest ecosystems, with severe impacts on both the environment and human society. Understanding the post-fire recovery processes of forests is crucial for developing strategies for species diversity conservation and ecological restoration and preventing further damage. The present study proposes applying the EAswin-Mask2former model based on semantic segmentation in deep learning using visible light band data to better monitor the evolution of burn areas in forests after fires. This model is an improvement of the classical semantic segmentation model Mask2former and can better adapt to the complex environment of burned forest areas. This model employs Swin-Transformer as the backbone for feature extraction, which is particularly advantageous for processing high-resolution images. It also includes the Contextual Transformer (CoT) Block to better capture contextual information capture and incorporates the Efficient Multi-Scale Attention (EMA) Block into the Efficiently Adaptive (EA) Block to enhance the model's ability to learn key features and long-range dependencies. The experimental results demonstrate that the EAswin-Mask2former model can achieve a mean Intersection-over-Union (mIoU) of 76.35% in segmenting complex forest burn areas across different seasons, representing improvements of 3.26 and 0.58 percentage points, respectively, over the Mask2former models using ResNet and Swin-Transformer backbones, respectively. Moreover, this method surpasses the performance of the DeepLabV3+ and Segformer models by 4.04 and 1.75 percentage points, respectively. Ultimately, the proposed model offers excellent segmentation performance for both forest and burn areas and can effectively track the evolution of burned forests when combined with unmanned aerial vehicle (UAV) remote sensing images. [ABSTRACT FROM AUTHOR]

Industrial park (IP) development has passed through many stages, and the development evolution pathways of IPs have different characteristics according to different perspectives. Understanding the evolutionary characteristics of IPs will assist us in understanding their essential developmental trajectories. Achieving carbon neutrality in IPs is important for combating climate change. In order to reveal the evolutionary characteristics of IPs from a carbon neutrality perspective, this study examines the Kalundborg eco-industrial park by dividing its development into three stages. We also quantitatively analyze this evolution based on enterprise connectance and enterprise repetitive connectance. We then analyze the evolutionary characteristics at the national level by using China and South Korea as examples. The results showed that the development trajectories of IPs had spontaneous and conscious characteristics. Compared with the spontaneous stage, enterprise connectance and enterprise repetitive connectance were obviously higher during the conscious stage. This article contributes to our understanding of the nature of IP development from a carbon neutrality perspective. [ABSTRACT FROM AUTHOR]

Sustainable agricultural development is a fundamental requirement and a crucial goal of modern agriculture. It is also a significant means of enabling farmers to increase their incomes. This paper analyses the evolutionary characteristics, regional differences and spatial convergence of the level of sustainable agricultural development using kernel density estimation, Dagum's Gini coefficient and the spatial convergence model based on panel data from 30 provinces in China from 2012 to 2021.The results show that: (1) At the level of development, the level of sustainable agricultural development at the national level and in the three major regions has shown an upward trend with fluctuations, with the average level of development in the eastern and central parts of the country higher than the national average, and in the western part of the country lower than the national average; however, the growth rate in the western part of the country is the highest among the three major regions. (2) In terms of evolutionary characteristics, the level of sustainable agricultural development in the country and the three major regions is characterised by spatial agglomeration, with varying degrees of polarisation. (3) In terms of regional differences, the Gini coefficients for the country as a whole, within the three major regions and between regions, generally show a downward trend, with interregional differences remaining the main source of overall differences. (4) In terms of spatial convergence, there is σ-convergence and β-convergence in the level of sustainable agricultural development across the country and the three major regions, and there is a positive spatial spillover effect. The conditional β convergence results show that the eastern region has the fastest rate of convergence. The above findings provide a scientific basis for the formulation of policies related to sustainable agricultural development in China. [ABSTRACT FROM AUTHOR]

Accelerating the transformation of the rural energy structure is an indispensable part of energy transformation in developing countries. In this novel study, the transformation effect of China's rural energy structure from 2001 to 2020 was evaluated. Further, this paper also identified the decoupling state between the rural energy structure transition and carbon emissions, and decomposed the spatial–temporal effects of rural carbon decoupling through efficiency measures. According to the survey, the dual substitution index of the rural energy structure in China increased from 0.466 to 1.828, and showed a decreasing trend in spatial distribution from the east to the central and western regions. Economic development and climate characteristics have become important influencing factors for the dual substitution of the rural energy structure. The decoupling relationship between the dual substitution of the rural energy structure and carbon emissions was mainly characterized in the strong decoupling, expansion negative decoupling, and strong negative decoupling states. Regional imbalances have deepened as the efficiency of rural energy carbon decoupling has gradually increased. The annual average efficiency of rural energy carbon decoupling in a dynamic perspective has increased by 10.579%, and the dual substitution of the energy structure has a significant driving effect on rural carbon reduction. [ABSTRACT FROM AUTHOR]

With the rapid advancement of global technology, high-tech industries have become key drivers for the economic growth of many nations and regions. This study delves into the spatiotemporal dynamics and determinants influencing China's high-tech sector from 2007 to 2021. The key findings include the following: (1) Nationally, the high-tech sector has been a cornerstone for China's GDP growth over the preceding 15 years. The expansion rate of the high-tech domain consistently outpaces the broader economy. In particular, since 2015, the percentage of high-tech industries' GDP has surged to approximately 42%. (2) At the provincial level, the spatial representation of the high-tech sector's GDP predominantly leans towards the east and the south, revealing pronounced spatial autocorrelation. Nevertheless, the demarcations between east and west and between north and south are progressively diminishing. (3) Regarding influential determinants, R&D internal expenditure, operating revenue, and industry agglomeration have been instrumental in spearheading innovation and bolstering growth within the high-tech realm. These insights are invaluable for comprehending the evolutional nuances of China's high-tech industry and devising pertinent policy measures. [ABSTRACT FROM AUTHOR]

Watershed water cycles undergo profound changes under changing environments. Analyses of runoff evolution characteristics are fundamental to our understanding of the evolution of water cycles under changing environments. In this study, linear regression, moving average, Mann–Kendall, Pettitt, accumulative anomaly, STARS, wavelet analysis, and CEEMDAN methods were used to analyze the trends, mutations, and periodic and intrinsic dynamic patterns of runoff evolution using long-term historical data. The intra-annual distribution of runoff in the Dawen River Basin was uneven, with an overall decreasing trend and mutations in 1975–1976. The main periods of runoff were 1.9 and 2.2 years, and the strongest oscillations in the study period occurred in 1978–1983. The runoff decomposition high-frequency term (intra-annual fluctuation term) had a stronger fluctuation frequency, with a period of 0.51–0.55 years, while the low-frequency term (interannual fluctuation term) had a period of 1.55–2.26 years. The trend term for the runoff decomposition tended to decrease throughout the monitoring period and gradually stabilized at the end of the monitoring period, while the period gradually decreased from upstream to downstream. In summary, we used multiple methods to analyze the evolutionary characteristics of runoff, which are of great relevance to the adaptive management of water resources under changing environments. [ABSTRACT FROM AUTHOR]

Agricultural carbon mitigation is one of the most important components of China's carbon mitigation goals. This paper calculates China's agricultural carbon emissions (ACEs) from 2000 to 2020, studies the spatio-temporal evolution characteristics of China's ACEs, and aims to provide references for the development of China's ACEs reduction policies. The results show that the total ACEs in China presented an inverted "W" trend, with a slight increase of 2.81% in total. China's ACEs mainly came from livestock and poultry breeding and agricultural material inputs. Although the carbon emissions from rice cultivation and soil accounted for a relatively low proportion, they showed an uptrend of fluctuation during the study period. From a geographical point of view, ACEs in the regions of central China and western China were relatively high compared to those in eastern China. Carbon emissions decreased for crop farming and livestock and poultry breeding in most eastern provinces. Crop farming carbon emissions grew, while the emissions from livestock and poultry breeding declined in most of the central provinces. Carbon emissions increased for crop farming and livestock and poultry breeding in most western provinces. Therefore, the existing low-carbon agricultural policies should be optimized, crop farming technologies should be improved, and specific policies should be applied in the corresponding regions to support China's ACEs reduction. [ABSTRACT FROM AUTHOR]

Rapid urbanization has had an important impact on the pattern and function of rural land use. To better understand the key drivers of the landscape pattern evolution in southern Henan in China from 1980 to 2020, we used techniques of GIS(Geographic Information System) technology and the geodetector model in the research area of landscape pattern evolution characteristics. The research results show that the land use transformation in the rural areas of southern Henan has been characterized by the conversion of production land to living land and ecological land, with the highest conversion rate and continuous growth of construction land, a decreasing trend of cropland, and continuous and stable growth of land for forest and water body in the past 40 years. Land use conversion in the rural areas of southern Henan is mainly concentrated in the northern, central, and southern areas, and the spatial conversion has shifted from mountainous areas to the plains. The center of gravity of forest, cropland, and water body has most obviously shifted, and human interference and ecological environment destruction are the main influencing factors. The overall landscape pattern in the rural areas of southern Henan has increased in fragmentation and landscape heterogeneity, evenness has decreased, irregular patches have increased, and landscape connectivity has decreased. The combined effect of the six dimensions of elevation, slope, night lighting, average annual precipitation, average annual temperature, and population density in the rural areas of southern Henan has led to the transformation of land use and changes in landscape pattern. Physical geographic factors are the main drivers of rural landscape pattern changes in southern Henan, while population density changes and urbanization are secondary drivers. The results of the study have important guiding significance for the further optimization of rural landscape patterns and the sustainable development of rural areas. [ABSTRACT FROM AUTHOR]

GATA transcription factor genes participate in plant growth, development, morphogenesis, and stress response. In this study, we carried out a comprehensive genome-wide analysis of wheat GATA transcription factor genes to reveal their molecular evolutionary characteristics and involvement in salt and drought tolerance. In total, 79 TaGATA genes containing a conserved GATA domain were identified in the wheat genome, which were classified into four subfamilies. Collinear analysis indicated that fragment duplication plays an important role in the amplification of the wheat GATA gene family. Functional disproportionation analysis between subfamilies found that both type I and type II functional divergence simultaneously occurs in wheat GATA genes, which might result in functional differentiation of the TaGATA gene family. Transcriptional expression analysis showed that TaGATA genes generally have a high expression level in leaves and in response to drought and salt stresses. Overexpression of TaGATA62 and TaGATA73 genes significantly enhanced the drought and salt tolerance of yeast and Arabidopsis. Protein–protein docking indicated that TaGATAs can enhance drought and salt tolerance by interacting between the DNA-binding motif of GATA transcription factors and photomorphogenesis-related protein TaCOP9-5A. Our results provided a base for further understanding the molecular evolution and functional characterization of the plant GATA gene family in response to abiotic stresses. [ABSTRACT FROM AUTHOR]

With the ecological protection and high-quality development of the Yellow River Basin rising to China's national strategy, the Yellow River Delta is facing a historic development opportunity, and the surface water problems in this region are becoming more and more severe. Owing to the dual effects of the swing of the Yellow River's channel and human activities, the surface water in the Yellow River Delta is in an evolving state. Consequently, it is important to pay attention to the ecosystem response caused by surface water evolution for the ecological protection and high-quality development of the Yellow River Delta. Drawing on ecological, economic, and network analysis, in this study, the ecological service and landscape effects of the surface water evolution in the Yellow River Delta from 1986 to 2019 are explored using remote sensing and socioeconomic data. The results are as follows: (1) The surface water in the Yellow River Delta has evolved significantly in the last 35 years. Artificial water accounted for the dominant proportion of the total water, and the composition of water tended to be remarkably heterogeneous. (2) The ecological services of the surface water in the delta increased significantly during the study period. The ecological services of the surface water improved to varying degrees except for sedimentary land reclamation. Tourism, materials production, and water supply became the leading service functions of the surface water in the Yellow River Delta. The proportion of cultural functions rose rapidly, and the share of regulatory functions shrank significantly. (3) The evolution of the surface water had an evident impact on the landscape pattern of the Yellow River Delta, which was manifested as physical cutting and spatial attraction. This demonstrates the comprehensive effect of protective constraints, spatial attraction, and spatial exclusion on the landscape pattern of regional land types. The results of this study have a certain guiding significance for the development and management of the water resources in the Yellow River Delta and also provide information for ecological protection in this region. [ABSTRACT FROM AUTHOR]

MicroRNA166 (miR166) is a highly conserved plant miRNA that plays a crucial role in plant growth and the resistance to various abiotic stresses. However, the miR166s in tea (Camellia sinensis (L.) O. Kuntze) have not been comprehensively identified and analyzed. This study identified 30 mature miR166s and twelve pre-miR166s in tea plants. An evolutionary analysis revealed that csn-miR166s originating from the 3′ arm of their precursors were more conserved than the csn-miR166s derived from the 5′ arm of their precursors. The twelve pre-miR166s in tea were divided into two groups, with csn-MIR166 Scaffold364-2 separated from the other precursors. The Mfold-based predictions indicated that the twelve csn-MIR166s formed typical and stable structures comprising a stem-loop hairpin, with minimum free energy ranging from −110.90 to −71.80 kcal/mol. An analysis of the CsMIR166 promoters detected diverse cis-acting elements, including those related to light responses, biosynthesis and metabolism, abiotic stress defenses, and hormone responses. There was no one-to-one relationship between the csn-miR166s and their targets, but most csn-miR166s targeted HD-Zip III genes. Physiological characterization of tea plants under drought stress showed that leaf water content proportionally decreased with the aggravation of drought stress. In contrast, tea leaves' malondialdehyde (MDA) content proportionally increased. Moreover, the cleavage site of the ATHB-15-like transcript was identified according to a modified 5′ RNA ligase-mediated rapid amplification of cDNA ends. The RT-qPCR data indicated that the transcription of nine csn-miR166s was negatively correlated with their target gene. [ABSTRACT FROM AUTHOR]

GATA transcription factor genes participate in plant growth, development, morphogenesis, and stress response. In this study, we carried out a comprehensive genome-wide analysis of wheat GATA transcription factor genes to reveal their molecular evolutionary characteristics and involvement in salt and drought tolerance. In total, 79 TaGATA genes containing a conserved GATA domain were identified in the wheat genome, which were classified into four subfamilies. Collinear analysis indicated that fragment duplication plays an important role in the amplification of the wheat GATA gene family. Functional disproportionation analysis between subfamilies found that both type I and type II functional divergence simultaneously occurs in wheat GATA genes, which might result in functional differentiation of the TaGATA gene family. Transcriptional expression analysis showed that TaGATA genes generally have a high expression level in leaves and in response to drought and salt stresses. Overexpression of TaGATA62 and TaGATA73 genes significantly enhanced the drought and salt tolerance of yeast and Arabidopsis. Protein-protein docking indicated that TaGATAs can enhance drought and salt tolerance by interacting between the DNA-binding motif of GATA transcription factors and photomorphogenesis-related protein TaCOP9-5A. Our results provided a base for further understanding the molecular evolution and functional characterization of the plant GATA gene family in response to abiotic stresses.

The evolution of toppling deformation of anti-dip slope is essentially a process of energy dissipation and transformation. Aiming to study the characteristics of energy evolution in different stages, the DEM (discrete element method) software PFC (Particle Flow Code) was utilized to establish a two-dimensional numerical model for a bank slope in Chongqing based on geological background data and field investigation. The DEM model was proven to be reliable not only because the deformation discrepancy between the numerical model and actual bank slope was not large but also because some obvious fractures in the actual bank slope can readily be found in the numerical model as well. In this article, content about displacement in the shallow layer was analyzed briefly. Special effort was made to analyze the energy field and divide the toppling deformation process into three stages. (1) Shear deformation stage: this is an energy accumulating stage in which the strain energy, friction energy, and kinetic energy are all small and the deformation is mainly shear deformation in the slope toe. (2) Stage of main toppling fracture surface hole-through: all three kinds of energy present the increasing trend. The shear deformation in the slope toe expands further, and the toppling deformation also appears in the middle and rear parts of the bank slope. (3) Stage of secondary toppling and fracture surface development: strain energy and friction energy increase steadily but kinetic energy remains constant. Deformation consists mainly of secondary shearing and a fracture surface in the shallow layer. Secondary toppling and fracture surface develop densely. [ABSTRACT FROM AUTHOR]