The diffusion and accumulation of antibiotic resistance genes (ARGs) have become a major global challenge to environmental safety and public health. As a critical environmental reservoir of ARGs, soil plays a significant role in their generation, migration, and dissemination. This review systematically summarizes the primary sources of ARGs in soil, including anthropogenic activities, livestock manure, and wastewater treatment inputs, and outlines their distribution characteristics across different soil types. It emphasizes the influence of environmental factors, such as soil pH, organic matter content, and antibiotic residues, on the behavior of ARGs, revealing their migration, transformation, and horizontal gene transfer mechanisms. The potential risks of ARGs to ecosystem functions, food safety, and human health are elucidated, highlighting their critical role in the dissemination network of antibiotic resistance. Furthermore, this paper reviews ARG mitigation strategies, including source reduction, process interruption, and terminal treatment, while identifying research limitations and technological bottlenecks. Future studies are proposed to focus on developing precise and highly sensitive monitoring techniques, investigating multi-scale mechanisms of ARG migration and diffusion, and constructing ecosystem-based integrated control systems. These findings provide a theoretical foundation and technical support for understanding the environmental behavior of ARGs in soil and mitigating their spread.

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The smart grid, as the core of future energy systems, significantly enhances the efficiency, reliability, and flexibility of power systems by integrating advanced information and communication technologies. This paper provides a comprehensive discussion on the development directions of smart grids, focusing on several key areas. First, optimizing the integration and management of renewable energy, particularly the management of distributed energy and the development of efficient energy storage systems to address the intermittency of supply. Second, applying advanced data analytics and artificial intelligence technologies, utilizing big data and machine learning to optimize power demand forecasting and fault detection. Third, enhancing cybersecurity by researching measures to prevent cyberattacks and data breaches, as well as exploring the application of blockchain technology in power trading and data protection. Additionally, the interconnection of electric vehicles with the grid is discussed, including vehicle-to-grid interaction technologies and the optimization of smart charging systems. Lastly, the paper introduces methods to enhance grid resilience and self-healing capabilities, enabling the grid to self-repair and rapidly recover from faults and natural disasters. This paper aims to provide a comprehensive perspective on smart grid development, assisting related industries and policymakers in understanding future trends and challenges.

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This paper explores recent advancements and future development trends in the application of artificial intelligence (AI) to oil reservoir characterization. It focuses in particular on breakthroughs in deep learning, machine learning, and multi-source data fusion that enhance the accuracy of reservoir description, automate data processing, enable real-time monitoring, and support dynamic prediction. The paper highlights innovative directions such as customized model development, human–machine collaborative decision-making, uncertainty quantification, and risk assessment, outlining key pathways through which AI is transforming reservoir characterization from traditional experience-based methods into intelligent, data-driven approaches. In addressing current challenges—including data complexity, limited model generalization, and adaptability to diverse application scenarios—it proposes targeted research directions and development strategies. This paper aims to provide a systematic and comprehensive technical reference for researchers and engineers in oil and gas exploration and development, promoting the deep integration of AI with reservoir characterization and contributing to the efficient and sustainable utilization of hydrocarbon resources.

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With the accelerating process of population aging, urban governance, and social institutions are undergoing profound structural adjustments and functional transformations. Adopting a multidisciplinary perspective, this study integrates theories and methods from demography, social geography, and institutional economics to systematically examine the technological integration and ethical regulation of intelligent elderly care systems, the social acceptance and macroeconomic impacts of delayed retirement policies, the cultural transformation paths of family-based caregiving mechanisms, and the planning strategies for age-friendly urban spaces and barrier-free environments. On this basis, the paper proposes a coordinated pathway for institutional innovation and spatial restructuring, emphasizing the synergistic evolution of technology, institutions, culture, and space in facilitating urban transitions toward greater adaptability in an aging society. It argues that building an inclusive and sustainable aging society requires overcoming policy fragmentation through collaborative governance and systematic design, thereby promoting age-friendly public services and urban spaces. This study aims to provide theoretical support and policy insights for enhancing the governance system for aging populations and promoting social equity and justice.

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As an important artistic form integrating music and literature, children’s songs serve multiple functions, including aesthetic enlightenment, value guidance, and emotional expression. This paper systematically examines the artistic features of children’s song creation from the perspectives of language characteristics, structural form, and emotional expression, emphasizing that the language should be simple, rhythmic, and accessible, the structure should be compact and clear, and the content should reflect children’s daily lives and a sense of innocence. By analyzing existing issues in current practices—such as excessive commercialization, lack of professional expertise among creators, and a disconnect from child-centered perspectives—the paper proposes practical improvement strategies, including policy support, copyright protection, talent cultivation, and the integration of digital technologies. It further argues that children’s song creation should be rooted in children’s aesthetic psychology and cognitive characteristics, integrating insights from multiple disciplines to enhance artistic expression and educational value. This paper aims to provide theoretical reference and methodological support for optimizing the creative ecosystem of children’s songs and improving the quality of works, thereby promoting the sustainable development of children’s musical culture.

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This study aims to systematically analyze the success factors of rural tourism in Japan and examine the associated challenges and future research directions. Focusing on the management of natural resources, community participation, and the use of digital technologies, the research highlights the need to build sustainable tourism models, diversify local economies, and achieve harmony between tourism and environmental conservation. Through this analysis, the paper seeks to offer policy recommendations and practical insights applicable to other regions, based on successful cases of rural tourism in Japan. In particular, it explores strategies to effectively utilize regional resources, integrate environmental preservation, and present concrete research issues for the sustainable development of the tourism sector. The findings are expected to provide valuable implications for regions pursuing sustainable rural tourism and contribute to the long-term coexistence of tourism and local communities.

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As a product of the deep integration between information technology and modern agriculture, digital agriculture is reshaping traditional agricultural production systems and emerging as a key driver for high-quality development and green transformation in agriculture. This paper systematically reviews the current progress of core technologies and future trends in digital agriculture, with a focus on five representative frontier research areas: (1) multi-source data fusion and intelligent agricultural information sensing technologies; (2) crop yield prediction models and decision optimization methods based on machine learning; (3) the construction and application framework of digital twin agricultural systems; (4) intelligent agricultural machinery and autonomous operation path planning technologies; and (5) agricultural carbon emission monitoring and the development of green production evaluation systems. Supported by interdisciplinary integration of remote sensing, the Internet of Things, big data, and artificial intelligence, these technologies enable refined management and dynamic optimization throughout the agricultural production process, significantly improving resource use efficiency, crop productivity, and product quality. Moreover, digital agriculture demonstrates considerable potential in addressing climate change challenges, ensuring food security, and promoting low-carbon and sustainable agricultural development. Based on an analysis of current technological achievements, this paper further discusses key scientific issues and technical bottlenecks, and proposes future research priorities and development pathways.

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Amid growing global food security challenges and climate change, big data-driven crop prediction and breeding decisions are key to sustainable agriculture. By integrating multisource data, such as remote sensing, weather, soil, phenotypes, and genomics, with machine learning, this approach improves yield prediction accuracy and deepens understanding of genotype-by-environment (G×E) interactions. This paper summarizes recent advances in crop performance modeling and intelligent breeding, highlighting strategies for data integration, model generalization, environmental response modeling, and nonlinear phenotypic regulation. Emerging algorithms like deep learning, transfer learning, and federated learning enhance model adaptability, while cross-scale simulations enable dynamic agricultural regulation. The coupling of genomic selection with environmental data underpins intelligent breeding decisions, supporting precision agriculture and sustainable development.

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Against the backdrop of escalating global climate change and increasing water scarcity, enhancing crop drought resistance and resource use efficiency has become a critical pathway toward ensuring food security and promoting sustainable agriculture. This review systematically summarizes recent advances in drought-tolerant crop screening and optimized cultivation strategies, with a focus on five key areas: (1) multi-omics integration for elucidating drought resistance mechanisms; (2) machine learning-based intelligent screening of drought-tolerant varieties; (3) optimization of root system architecture and mechanisms for efficient water utilization; (4) crop-environment dynamic management platforms driven by digital twin technology; and (5) agroecological coupling models for drought-resilient cultivation. This work aims to provide theoretical foundations and technical pathways for crop genetic improvement and the construction of intelligent agricultural systems in drought-prone regions, offering strategic insights for the future development of efficient, resilient, and environmentally friendly drought-adaptive agriculture.

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Iron is an essential micronutrient for plant growth, development, and metabolism, playing a critical role in rice productivity, stress resistance, and grain nutritional quality. This study systematically investigated the molecular mechanisms of iron uptake and transport in rice, with a focus on the pivotal roles of iron transport proteins in root absorption, translocation to aboveground tissues, and phloem-mediated distribution to grains. The synergistic and antagonistic interactions between iron and other metal elements, such as zinc and cadmium, during absorption were also elucidated. Furthermore, by analyzing iron isotopic fractionation behavior in the soil-plant system, the study revealed the characteristics and ecological significance of isotopic fractionation during iron cycling, phase transformation, and chelation processes. Using high-resolution spectroscopic techniques, including X-ray fluorescence spectroscopy and synchrotron radiation X-ray absorption spectroscopy, the subcellular localization of iron was examined, uncovering its distribution across different subcellular components and its impact on rice iron metabolism. This integrative research provides a comprehensive understanding of the molecular mechanisms, isotopic fractionation patterns, and subcellular distribution of iron in rice, offering theoretical insights into the dynamic behavior of iron within the plant. The findings not only propose new strategies for improving rice iron use efficiency and grain nutritional value but also provide scientific evidence and technical references for addressing heavy metal contamination and enhancing soil environmental quality.

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The dynamics of soil nutrients and their coupling mechanisms with crop growth constitute a core scientific question for understanding agroecosystem functions, enhancing nutrient use efficiency, and achieving sustainable agricultural development. In the context of increasingly complex agricultural production systems and tightening resource and environmental constraints, traditional static and experience-based fertilization practices can no longer meet the modern demands for precision, greenness, and system integration. This paper reviews key recent advances in the regulation of soil nutrient dynamics and crop nutritional responses, with a focus on five representative frontier areas: (1) the integrated application of precision fertilization and intelligent decision-support systems; (2) the regulatory roles of rhizosphere microecological processes and functional microorganisms in nutrient transformation; (3) the characterization of spatiotemporal heterogeneity of soil nutrients and dynamic modeling approaches; (4) the mechanisms stabilizing nutrient supply and demand under extreme climate conditions; and (5) the coupling potential of nanotechnology in nutrient slow-release and efficient crop uptake. By integrating perspectives from soil science, crop nutrition, and agricultural engineering, this paper aims to provide theoretical foundations and technological pathways for building efficient, intelligent, and eco-friendly soil nutrient management systems, offering valuable scientific insights and practical implications for the advancement of precision and green agriculture.

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Climate change poses multifaceted and increasingly severe threats to global wheat production, directly impacting crop growth, yield, and quality. This paper synthesizes recent findings on how major climatic factors—including rising temperatures, altered precipitation patterns, elevated atmospheric CO₂ concentrations, and sea level rise—affect wheat physiology and agronomic performance. It highlights direct and indirect stressors, such as heatwaves, drought, salinity intrusion, and extreme weather events, compromising wheat productivity and food security. Furthermore, the article discusses comprehensive and multilayered adaptation strategies, including breeding climate-resilient wheat varieties, applying gene editing technologies, intelligent water resource management, and sustainable soil and ecosystem practices. This paper provides a forward-looking perspective to guide sustainable wheat production under changing climate conditions by integrating insights from genetics, agronomy, and environmental sciences.

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This study conducts an in-depth analysis of the multiple challenges posed by high-penetration renewable energy integration to the stability of modern power systems, with a focus on declining system inertia, heightened risks to frequency and voltage stability, suppression of power angle oscillations, and the severe tests faced by grid protection and fault ride-through capabilities. Notably, on April 28, 2025, the Iberian Peninsula (Spain and Portugal) experienced one of the most severe large-scale blackouts in Europe in recent years. Although the exact cause remains under investigation, the vulnerability of power systems under high renewable penetration cannot be overlooked. In response to these challenges, this paper systematically reviews and analyzes a series of key coping strategies and cutting-edge technologies, including Virtual Synchronous Generators, Energy Storage Systems, Flexible AC Transmission Systems, and the application of advanced smart grid technologies. By examining typical cases from China and abroad and summarizing international practices, this study aims to provide solid theoretical guidance and feasible technical references for ensuring the safe and stable operation of future high-penetration renewable energy power systems, ultimately contributing to the construction of a more resilient and sustainable future grid.

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With the deepening of the global energy transition, the integration of high shares of renewable energy into power grids has become an irreversible trend. In April 2025, a regional power system disturbance in Spain and Portugal highlighted the systemic challenges faced by power systems in terms of stability maintenance, resilience assurance, and emergency response under high penetration of intermittent renewable energy. This paper systematically reviews the frontier research progress on enhancing power system stability and resilience, with a focused analysis on five key technical areas: disturbance identification and feature extraction, system inertia support, resilience quantification and assessment, multi-level coordinated control, and power-communication system coupling security. From a comprehensive perspective of cross-temporal-spatial scales, multi-hazard impacts, and system coupling, this paper aims to construct a novel analytical framework for power system stability and resilience, providing theoretical foundations and technological pathways for building a low-carbon, highly reliable, and resilient modern power system.

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Power systems are encountering unprecedented stability, resilience, and intelligent operation challenges against the backdrop of high-penetration renewable energy integration and deep energy system transformation. As a core pillar for building next-generation power systems, smart perception and collaborative control systems rapidly evolve from traditional centralized and static dispatching modes toward architectures characterized by real-time sensing, distributed decision-making, and cognitive control. This paper reviews the developmental trajectory and overarching technological framework of such systems, focusing on key technological pathways including multi-source heterogeneous state perception, edge-intelligent processing, AI-driven autonomous decision-making mechanisms, and multi-agent collaborative control. In light of persistent challenges such as insufficient data reliability, limited generalization of control strategies, and lagging resilience assurance mechanisms, this paper proposes that future efforts should prioritize the development of a cognitively enabled smart grid core system with reasoning, self-healing, and cross-scale coordination capabilities. The paper aims to promote the deep integration of digitalization, intelligence, and resilience in power grid evolution.

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With the increasing integration of high-proportion renewable energy, the growing penetration of power electronic devices, and the deep coupling of multi-energy systems, power system stability is exhibiting new characteristics such as enhanced nonlinearity, multi-scale interactions, and cross-domain coupling, posing unprecedented challenges to traditional analytical approaches. This paper systematically reviews five key frontier directions in the research on power system stability in the context of emerging power systems: (1) dynamic stability mechanisms and evolutionary patterns under high-proportion renewable energy scenarios; (2) multi-source disturbance identification and rapid response coordination control based on artificial intelligence; (3) cross-domain coupling and synergistic stability analysis methods in multi-energy complementary systems; (4) resilience-oriented distributed self-healing reconfiguration and coordinated control strategies for microgrid clusters; and (5) accurate multi-spatiotemporal scale stability modeling and cyber-physical fusion simulation based on digital twins. The findings are expected to support the transformation of power systems from traditional passive response modes to a new paradigm of proactive cognition, autonomous regulation, and intelligent coordination, enhancing system security, resilience, and intelligence, and providing theoretical and technological foundations for the low-carbon transition of energy and power systems.

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Rice, as a major global staple crop, holds significant importance for food security and the enhancement of agricultural productivity. In recent years, the rapid development of big data technology has introduced new pathways and methodologies for studying rice variety adaptability. This paper systematically reviews the current status of big data technology applications in rice variety adaptability research, elaborating on its fundamental concepts and key technologies in the agricultural domain. It analyzes the primary factors influencing rice adaptability, including climatic conditions, soil characteristics, and other environmental factors. Through discussions of typical research cases, this paper highlights the application outcomes and research achievements facilitated by big data technology in rice adaptability studies. Furthermore, it delves into the limitations currently faced in the field, such as data quality, data sharing, and analytical methods. Future development directions are proposed, including data integration, interdisciplinary collaboration, and the potential application of emerging technologies. This paper aims to provide valuable academic insights for related research endeavors.

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Soil health serves as a fundamental guarantee for sustainable agricultural development, directly impacting food security, ecosystem stability, and the regulation of global climate change. This article explores the multidimensional connotation of soil health and provides a comprehensive review of recent research progress in key areas such as soil microbial community structure and function, soil organic carbon management, optimization of tillage and fertilization practices, and soil degradation control. Studies have shown that soil microorganisms play a central role in maintaining nutrient cycling, enhancing crop stress resistance, and improving resource use efficiency. Scientific carbon management strategies and long-term appropriate tillage and fertilization regimes contribute to the construction of efficient and stable soil ecosystems. In recent years, plant-microbe-soil integrated remediation technologies have demonstrated great potential in restoring the functions of degraded soils. Further analysis indicates that enhancing soil health in the context of climate change is crucial for improving the adaptability and resilience of agricultural systems. Looking ahead, research on soil health should strengthen interdisciplinary integration and promote the synergistic evolution of precision management technologies and comprehensive remediation approaches, thereby providing a solid foundation for the green transformation and sustainable development of global agriculture.

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As a key geographical element of the Earth's surface, terrain plays a fundamental and multidimensional role in regulating the structure and evolution of the climate system. In recent years, with the rapid advancement of technologies such as ground-based observation, remote sensing, and high-resolution numerical simulation, research on the mechanisms of terrain’s influence on climate has become increasingly refined and multiscale. This paper systematically reviews six current frontier research directions in this field: (1) the thermodynamic and dynamic regulatory mechanisms of complex terrain on local climate systems; (2) the multiscale coupling and feedback between terrain and atmospheric circulation; (3) the triggering and regulating mechanisms of terrain in the formation, intensification, and spatial distribution of extreme climate events; (4) the co-evolution patterns of the terrain–land surface processes–climate feedback system; (5) the multiscale impacts of urban terrain on the urban boundary layer and microclimate and corresponding modeling approaches; and (6) the integrated application and methodological innovation of remote sensing data and high-resolution climate simulation technologies in terrain–climate research. Studies show that complex terrain exerts significant spatial heterogeneity and nonlinear processes in regulating precipitation patterns, temperature variation, atmospheric boundary layer stability, and climate anomalies. Future research urgently needs to strengthen the integration of multi-source observational data and uncertainty assessments, promote cross-scale coupled modeling and mechanism validation of the terrain–climate system, and deepen the understanding of regional climate evolution driven by terrain, thereby providing theoretical support and technical basis for improving climate prediction, disaster prevention, and ecosystem management.

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As one of the most pressing global scientific and policy challenges today, climate change is profoundly affecting the stability and sustainable development of the Earth system. As a vital branch of Earth system science, environmental geophysics provides robust technical and theoretical support for identifying the driving mechanisms, feedback processes, and ecological and societal impacts of climate change through multi-source geophysical detection and monitoring technologies. This paper systematically reviews six key application areas of environmental geophysics in climate change research: glacial seismology, marine seismology, monitoring of polar and marine environments, assessment of greenhouse gas concentrations and emissions, evaluation of carbon capture and storage technologies, and climate system modeling. The research indicates that advanced technologies such as high-resolution seismic arrays, satellite remote sensing, ocean-bottom seismometers, and drone-based sensors enable refined monitoring and quantitative simulation of ice sheet melting, sea-level rise, greenhouse gas emissions, and subsurface carbon sequestration processes. Moreover, the deep integration of artificial intelligence and machine learning methods into geophysical data processing and climate system modeling has significantly enhanced the resolution and accuracy of climate predictions. Environmental geophysics is expected to play an increasingly strategic role in deepening our understanding of climate processes, improving climate risk assessment, optimizing global response strategies, and supporting the construction of climate governance systems.

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To meet the needs of sustainable agricultural development, in-depth research on the effects of different rotation systems and fertilization practices on soil health is of great significance. This study focused on paddy fields in the middle reaches of the Yangtze River and systematically compared the effects of two rotation systems—rapeseed-rice and wheat-rice—under different fertilization treatments (no fertilization, chemical fertilization alone, and combined application of chemical fertilizers and straw return) on soil nutrients, physical properties, and aggregate characteristics. The results showed that the rapeseed-rice rotation significantly increased soil organic matter and available phosphorus content and optimized total porosity and capillary porosity, outperforming the wheat-rice rotation in improving soil structure. The combined application of straw return and chemical fertilizers exhibited a notable synergistic effect, significantly enhancing soil nutrient levels and aggregate stability. This effect was particularly pronounced under the “chemical fertilizers and straw return” treatment, where the relevant indicators reached optimal levels. Furthermore, the rapeseed-rice rotation notably increased the proportion of macro aggregates, improved aggregate stability, and further enhanced the soil’s water retention and nutrient supply capacity. The study indicates that rational selection of rotation systems and fertilization practices can effectively improve soil quality, providing scientific evidence for agricultural production and sustainable development in the middle reaches of the Yangtze River. The findings of this study offer valuable insights for optimizing agricultural management strategies, improving soil health, and promoting the sustainable development of regional agriculture.

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As one of the world’s major grain and oil crops, soybean plays a crucial role in ensuring food security, promoting economic development, and maintaining ecological balance. With the intensification of global climate change and increasing resource and environmental constraints, the soybean industry urgently needs transformation and upgrading to achieve efficient, environmentally friendly, and sustainable development. This study explores frontier technologies and sustainable development pathways in the soybean industry, covering key areas such as molecular breeding and gene editing, soil-microbe interactions, precision agriculture and intelligent management, stress-resistant variety cultivation, and the construction of ecological planting models. By comprehensively analyzing the latest research findings from both domestic and international sources, this paper aims to reveal the supporting role of technological innovation in driving the green transformation of the soybean industry and proposes strategic recommendations for optimizing resource allocation and reducing environmental burdens, providing scientific and practical insights for global food security and ecological conservation.

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Quaternary science, as a core field in studying Earth’s environmental evolution over the past million years, integrates interdisciplinary collaboration and multiple technological approaches, such as high-precision isotope analysis, remote sensing monitoring, and numerical simulations, to systematically reconstruct the historical processes of climate change, glacial dynamics, biodiversity succession, and landform evolution. These studies not only reveal the internal feedback mechanisms of the climate system and the occurrence patterns of natural disasters but also provide a solid scientific foundation for improving climate models and enhancing the accuracy of future environmental change predictions. Furthermore, an in-depth analysis of the interactions between human activities and the natural environment in Quaternary science contributes to understanding the environmental response mechanisms across different historical periods. Looking ahead, with breakthroughs in observation technology and continuous optimization of modeling approaches, this field is expected to achieve greater progress in deciphering the complex interactions among Earth system components, thereby providing more precise scientific support for addressing global climate change, ecological conservation, and sustainable development strategies.

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In recent years, driven by multi-omics technologies and systems biology, significant progress has been made in the study of the rice rhizosphere microbiome, providing new theoretical foundations and technical support for enhancing rice productivity, optimizing soil ecological functions, and ensuring food security. Research has shown that rice genotypes play a crucial role in shaping the structure of rhizosphere bacterial communities, while root exudates profoundly influence microbial composition and function by regulating nutrient uptake, activating plant immunity, and enhancing stress resistance. Future studies should focus on the mechanisms underlying the formation of rhizosphere microbial communities, metabolic networks, and their ecological functions, as well as explore how microbial interactions affect rice growth and environmental adaptation. By integrating artificial intelligence, bioinformatics, and synthetic biology, precise strategies for regulating the rhizosphere microbiome can be developed, facilitating the advancement of microbiome-based sustainable agricultural technologies. A deeper understanding of the diversity and functional regulation mechanisms of rice rhizosphere bacterial communities will not only expand the theoretical framework of agricultural microbiology but also promote the practical applications of green agriculture and ecological restoration.

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Japan serves as a model for integrating cultural industries and the tourism economy, with its deep integration of culture and tourism injecting strong momentum into economic growth and cultural dissemination. This study systematically reviews the concepts and current development status of Japan’s cultural industries and tourism economy, summarizing their integration’s necessity and key trends. Through analysis of typical cases and empirical data, it explores the mainstream models, driving mechanisms, and critical influencing factors of their integration while identifying the main challenges faced in the current development. Based on this, the study proposes specific pathways to promote integration, focusing on industrial chain synergy, cultural intellectual property development, the empowerment of digital technologies, and the innovative combination of traditional culture with modern tourism. Finally, the paper highlights Japan’s successful experiences in urban cultural shaping, regional cultural heritage excavation, and the construction of international cultural tourism models. It also provides practical insights and strategic suggestions for fostering coordinated development between cultural industries and the tourism economy in China, considering its unique national conditions. This study aims to provide a theoretical foundation and practical guidance for the deep integration of culture and tourism while exploring feasible pathways for cultural tourism cooperation between China and Japan to promote regional economic growth and cultural innovation.

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The impact of global warming on soil carbon cycling has become a core issue in climate change research. As a critical flux of carbon exchange between terrestrial ecosystems and the atmosphere, soil CO2 emissions have profound implications for the global carbon budget and climate change. However, the response mechanisms of soil CO2 emissions to warming in different ecosystems remain unclear. Using a meta-analysis approach, this study systematically integrated 380 publications, covering 265 research sites and 620 datasets, to investigate the response characteristics of soil CO2 emissions to warming and their key driving factors. Results showed that soil CO2 emissions exhibited a significant positive response under global warming, with notable variations in response intensity among different ecosystems. Forest ecosystems showed the strongest response, followed by agricultural and grassland ecosystems. Annual mean temperature, precipitation, and soil moisture were identified as the primary environmental factors driving soil CO2 emissions, exerting significant positive effects, while factors such as altitude showed negative impacts. Moreover, the dynamic changes in soil CO2 emissions were influenced by direct temperature increases and soil properties and ecosystem types. This study provides an important theoretical basis for understanding the spatiotemporal variations of soil CO2 emissions under global warming while offering critical data support and scientific insights for evaluating and managing soil carbon sink functions and predicting future climate change.

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As important carriers of local economy and culture, characteristic towns not only embody rich history and culture but also bring new opportunities for regional development. This study conducts a comparative analysis of the development trajectories of two characteristic towns in Japan: Beppu in Oita Prefecture and Lake Tazawa. Beppu has achieved sustainable development through its abundant hot spring resources and diversified tourism industry, whereas Lake Tazawa faces developmental stagnation due to a lack of innovation and ineffective market promotion. The research identifies resource endowment, community participation, infrastructure development, marketing strategies, and innovation capacity as key factors influencing the development of characteristic towns. By summarizing the experiences and lessons of these two cases, the study provides valuable insights into the planning and construction of characteristic towns in other countries.

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This study aims to explore how resource characteristics drive Japan’s eco-economic development. By examining the current state of natural resources, human resources, and technological innovation, the study reveals the influence of these factors on eco-economic practices. It first highlights key cases in renewable energy, circular economy, and ecological agriculture, including the promotion of solar and wind energy, waste recycling and reuse practices, and the development models of organic farming. Subsequently, the research summarizes critical success factors and challenges and discusses future development directions. Finally, it offers a series of policy recommendations to support sustainable development. This study not only provides empirical insights into Japan’s eco-economic development but also offers valuable guidance for other countries transitioning toward an eco-economy driven by resource characteristics.

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