Since its inception, the Geographical Research Bulletin has been devoted to serving as a pivotal platform for disseminating the latest research findings in the field of geography. In the upcoming 2024 volume, we continue to adhere to our proactive editorial policy, striving to elevate the academic standards of the journal and present readers with more captivating content from the realm of geographical studies. Geography, as an ancient yet continually evolving discipline, has borne witness to the progression of human understanding of nature, utilization of natural resources, and transformation of the environment. Over the past few years, the Geographical Research Bulletin has not only chronicled the developmental trajectory of geography but has also spotlighted the innovative facets of geographical research in terms of content, methods, breadth, and depth. The expansion of geography encompasses a wide spectrum, spanning from the macro to micro, from the Earth’s surface to its depths, and extending further into Earth’s spatial dimensions, revealing diverse and globalized characteristics. Amidst the changes of our times, geography faces heightened societal demands necessitating in-depth exploration through modern scientific technologies. The Geographical Research Bulletin actively responds to this demand by adopting a rapid publication policy to expedite the dissemination of research articles, ensuring that scholarly achievements promptly reach the academic community. We are committed to continuing to serve as a platform where natural sciences and social sciences intersect, reflecting the interplay between various disciplines within geography and conducting in-depth research with diverse perspectives and methodologies. Furthermore, in the upcoming volume, the Geographical Research Bulletin will persist in publishing articles that possess both academic depth and popular science appeal. We aim to convey the latest scientific information to readers, providing them with a comprehensive understanding of geographical science and related fields. By combining scholarly and popular science articles, we seek to facilitate information exchange, knowledge complementarity, and the advancement of scientific and technological innovation. In the new year, the Geographical Research Bulletin welcomes submissions from contributors worldwide, anticipating that through the collective efforts of the academic community, we can further propel the continuous development of geographical research. We extend our best wishes to all authors and readers, hoping for a more fruitful year in 2024 and collectively witnessing the progress and development of geography.

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Ecological agriculture is a comprehensive farming system dedicated to environmental conservation, reducing reliance on chemical pesticides and fertilizers, and promoting sustainability in agriculture. Its core features include avoiding chemical pesticides, widespread use of organic fertilizers, maintenance of biodiversity, crop rotation, and fallow periods. These practices collectively enhance agricultural products' yield and quality while minimizing adverse environmental impacts. Adhering to the no-chemical pesticide principle reduces pollution in soils, water sources, and the air. Applying organic fertilizers and protecting biodiversity contribute to improved soil structure and decreased reliance on chemical fertilizers. Crop rotation and fallow practices reduce soil erosion, providing a sustainable approach to soil management. Water resource management focuses on efficient utilization, maintaining water quality, and fostering the sustainable development of agricultural systems.

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This article explores the pivotal role of wheat in ecosystems, addressing its contributions to ecological balance, soil health, and biodiversity. It delves into the profound impacts of climate change on wheat-related ecosystems, detailing temperature changes, water stress, carbon dioxide concentrations, and more. Additionally, the article provides comprehensive strategies for biodiversity conservation in wheat cultivation, emphasizing the importance of diversity in farmland ecosystems, natural habitat preservation, and sustainable agricultural practices. The insights presented aim to foster a deeper understanding of wheat’s ecological significance and contribute to the development of sustainable agricultural approaches in the face of climate change.

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Paleogeography is a branch of geography that primarily focuses on the changes and evolution of geographical features, environments, human activities, and cultural landscapes on the Earth’s surface in the past. It examines the variations and impacts related to geographical patterns, climate changes, topography, ecosystems, and more during historical and geological periods. The objective is to reveal the historical processes, environmental changes, and the historical trajectory of interaction between humans and nature by studying past geographical information. This article provides an overview of the main themes in paleogeography research in recent years, aiming to offer readers a comprehensive understanding of studies in this field.

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The paper delves into the realm of historical geography, seeking to comprehend the past conditions of the Earth, encompassing geographical processes, environmental shifts, and human interaction with the environment. It investigates natural elements such as landforms and climate, alongside human aspects like historical distribution and cultural evolution. The field is progressing through numerical simulation, interdisciplinary integration, and GIS technology, augmenting precision and offering a holistic perspective. These advancements are anticipated to enrich our comprehension of Earth’s history and human societies, providing valuable insights for sustainable development.

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In space development, humanity gains new insights into the origin, evolution, and astrophysics of the universe, deepening our understanding of space and our existence. Observations from space contribute to understanding Earth’s environment, and climate change, and aid in crafting environmental protection policies and resource management. Furthermore, space development fosters international cooperation, enhancing peace and security. The allure of advanced technology drives innovation, fostering growth in new industries and employment opportunities.

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This article explores the importance of nitrogen fertilizer in wheat production and its impact on agricultural production and sustainable development. It first introduces the benefits of nitrogen fertilizer in promoting plant growth and increasing yields, while also pointing out the environmental challenges that excessive use of nitrogen fertilizer may bring. The article then analyzes the demand for nitrogen fertilizer in wheat and the usage patterns in different regions. It discusses the potential consequences of excessive nitrogen fertilizer use, emphasizing the importance of finding a balance in its application. Recommendations for reducing nitrogen fertilizer use are proposed, including precision fertilization and promoting agricultural sustainability. In the future outlook, the importance of improving nitrogen fertilizer management is emphasized, and the role of research, technological innovation, and international cooperation in addressing nitrogen fertilizer issues is highlighted. The article underscores that through scientifically sound nitrogen fertilizer management, a win-win situation can be achieved for wheat production and agricultural sustainability.

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This article explores the importance of nitrogen fertilizer and management techniques for wheat growth. Firstly, it analyzes the promoting effects of nitrogen fertilizer on wheat growth, including promoting plant growth, influencing yield and quality, regulating nutrient balance, and controlling pests and diseases. Secondly, it discusses the influence of nitrogen fertilizer on wheat mineral content and balance, emphasizing the importance of proper nitrogen fertilizer management in maintaining mineral balance. Finally, it presents the technical points of nitrogen fertilizer management, including soil testing, fertilization planning, fertilization methods, nitrogen fertilizer type selection, supporting measures, and monitoring adjustments. Through scientific fertilization, nitrogen fertilizer efficiency can be improved, wheat growth and yield can be promoted, and negative environmental impacts can be reduced.

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The development of artificial intelligence (AI) technology has sparked a revolution in the entrepreneurial field. Entrepreneurs actively employ AI-powered products and services, such as smart robots, automated customer service systems, and personalized recommendation systems, to enhance work efficiency and user experience. Data-driven decision-making has become mainstream, with entrepreneurs utilizing deep learning and data mining technologies for market forecasting and customer analysis. The widespread application of automation and machine learning technologies in business processes reduces costs and improves efficiency. Emerging markets such as speech recognition and computer vision have generated more business opportunities, enabling entrepreneurs to innovate their business models through AI technology. Meanwhile, the application of AI technology in risk management and security provides reliable support for entrepreneurs, ensuring the steady development of their businesses. These trends indicate that AI technology has profoundly impacted all aspects of the entrepreneurial field, bringing abundant opportunities and challenges to entrepreneurs.

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The impact of artificial intelligence (AI) technology on the entrepreneurial field is profound and multifaceted. Firstly, entrepreneurs utilize AI-powered products and services, such as smart robots and personalized recommendation systems, to enhance work efficiency and user experience, driving the market towards greater intelligence. Secondly, AI technology enables personalized big data analysis, transforming marketing and service approaches, and increasing customer satisfaction and loyalty. Furthermore, automation technology applied across industries enhances production and operational efficiency, reduces costs, and enhances a company’s competitive advantage. In addition, predictive analytics provided by AI technology enables entrepreneurs to better understand market trends and risks, allowing them to formulate targeted strategies. Lastly, emerging fields such as autonomous vehicles and medical diagnostics bring abundant business opportunities to entrepreneurs, driving technological advancements and industry innovation. These trends indicate that the widespread application of AI technology in the entrepreneurial field has become an undeniable trend, bringing significant opportunities and challenges to entrepreneurs.

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The text focuses on the importance of the Paleolithic Era and prospects for future research. The Paleolithic Era is crucial in the evolution and cultural development of humanity, and understanding its lifestyle, technology, and social structures is essential. Future research will prioritize advanced technologies and interdisciplinary approaches. Moreover, it’s necessary to further elucidate the interactions with the Earth’s environment and the impacts of cultural exchanges. This will provide new insights into the evolution of humanity and cultural history, offering implications for contemporary societal challenges.

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This article aims to comprehensively introduce the basic concepts, research objects, and scope of soil geography, as well as its historical background in the field of geography. Firstly, a brief overview of the basic processes of soil formation and the characteristics of major soil types is provided, along with an outline of soil classification systems. Secondly, the interaction between soil and landform morphology, the role of soil in landform evolution, and the application of soil geography in landform research are discussed in depth. Next, the impact of soil on the environment, its role in ecosystems, and the application of soil geography in environmental protection are examined. Finally, an overview of research methods and technologies in soil geography, as well as future trends and challenges, is provided, along with suggestions and prospects for the development of soil geography. This article aims to offer readers a thorough understanding of soil geography through a comprehensive introduction and analysis, thereby fostering research and development in this field.

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This paper discusses the development trends and key directions in the study of residual oil distribution in high-water-cut reservoirs in the future. With the continuous advancement of digital technology, technologies such as artificial intelligence, big data analysis, and machine learning will play an increasingly important role in predicting residual oil in reservoirs and geological modeling. The application of intelligent oil recovery systems will make oil field production more intelligent and automated, improving oil recovery efficiency and reducing water content. Additionally, environmental protection and sustainable development have become important focal points of research. The development of environmentally friendly oil recovery technologies will reduce environmental impact and achieve the sustainability of oil field development. This paper aims to explore the development trends and key directions in the study of residual oil distribution in high-water-cut reservoirs in the future.

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Selecting the right conference is crucial for submitting a high-quality conference paper, and careful attention to different paper formats is necessary during the writing process. Conference papers reflect the forefront of disciplinary developments, showcase innovative results, and promote scholarly communication. This paper provides advice on choosing appropriate conferences based on their level, impact, and focus areas, and it highlights four common paper formats: standard papers, extended abstracts, system descriptions, and short papers, analyzing their structures and suitable scenarios. By offering comprehensive strategies for conference selection and essential writing tips, this paper aims to help scholars complete high-level conference papers, effectively showcase their research achievements, and contribute to advancing their fields.

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Climate change has profoundly impacted agriculture, primarily by increasing the frequency of extreme weather events and altering the growing seasons and geographical distribution of crops. To effectively address this challenge, the agricultural sector must implement comprehensive measures. This article discusses strategies for addressing climate change: improving crop varieties, adjusting production methods, managing water resources, and protecting soil. By optimizing varieties, improving production methods, utilizing water resources efficiently, and enhancing soil management, the adaptability and resilience of agricultural production can be enhanced, thus ensuring the sustainable development of agriculture and the health of the ecological environment.

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The analysis and optimization of shale oil production is a complex and multi-faceted process, involving the integrated application of various technologies. Initial production rate and decline curve analyses are used to evaluate the production potential and economic feasibility of oil wells. Utilizing big data and machine learning technologies, dynamic monitoring and analysis of production data identify anomalies and potential issues, thereby optimizing production parameters and enhancing efficiency. Techniques such as hydraulic fracturing, horizontal drilling, re-fracturing, and acidizing are crucial for increasing recovery rates and production volumes. Additionally, compound-enhanced oil recovery technologies like chemical-gas and thermal-chemical methods further improve well recovery rates and production capacities. This paper explores in depth the application and optimization of these technologies and methods, aiming to enhance the efficiency and economic benefits of shale oil extraction.

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This paper discusses the evolution of China’s manufacturing industry and its underlying factors. China’s manufacturing sector has transitioned from low-cost competition to focusing on technological innovation and quality improvement. This shift is supported by rapid domestic market expansion, urbanization, middle-class growth, and increased consumer income levels. Additionally, efforts to address past environmental pollution issues and government ecological protection policies have strengthened environmental initiatives. Recently, China has been promoting investment in green industries and has been focusing on sectors such as electric vehicles and renewable energy.

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In the artificial intelligence (AI) era, AI technology is penetrating various academic disciplines at an unprecedented speed and depth, and geographic research is no exception. This paper aims to explore the applications, methods, challenges, and prospects of AI technology in geographic research. Firstly, the paper provides an overview of the specific applications of AI technology in remote sensing, spatial data analysis, and geographic information systems, highlighting its significant role in land cover change detection, urban planning, traffic flow prediction, and environmental monitoring. Secondly, in geographic research, the paper delves into the application methods of key technologies such as machine learning, deep learning, big data analysis, cloud computing, and edge computing. Subsequently, the paper discusses AI's technical challenges and ethical and social issues in geographic research. Finally, the paper envisions the future development trends of AI technology in geography, emphasizing the importance of integrating and innovatively applying new technologies. This paper hopes to provide valuable references for scholars and practitioners in the field of geography, promoting the extensive application and in-depth development of AI technology in geographic research.

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The application of big data in smart agriculture has significantly enhanced the efficiency and sustainability of agricultural production. Producers can obtain real-time information on soil quality, crop health, and weather conditions by collecting and analyzing large volumes of farming data, enabling more informed decision-making. This data-driven approach optimizes resource use, such as precision fertilization and irrigation, and effectively prevents and addresses agricultural pests and diseases, improving crop yield and quality. However, with the continuous advancement of big data technology, the agricultural sector faces a series of challenges, including data security and privacy protection, data quality and credibility, technical processing issues, and talent cultivation and technology dissemination. This paper will explore the current state of big data applications in smart agriculture, analyze these challenges in-depth, and propose corresponding solutions and future development directions.

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Cultural heritage is an important embodiment of a country or region’s unique history and culture and a significant resource for attracting tourists. However, with the rapid development of the tourism industry, the balance between the protection and utilization of cultural heritage has become increasingly important. This paper aims to explore the complex relationship between cultural heritage and tourism development by analyzing the promotion of tourism by cultural heritage and the impact of tourism on cultural heritage protection. Furthermore, the paper proposes strategies for sustainable tourism development, emphasizing the importance of cultural heritage protection and rational utilization, community participation, and benefit-sharing. The paper analyzes typical cases and summarizes successful experiences and challenges. Finally, it looks into future development trends in cultural heritage tourism and offers policy recommendations. This paper aims to provide valuable references and insights for strategies that achieve a win-win scenario for cultural heritage protection and tourism industry development.

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This article explores the crucial role of biodiversity in crop growth and ecosystem services. Firstly, it introduces how biodiversity enhances ecosystem services, including pollination, soil health, and nutrient cycling. Next, it discusses the role of biodiversity in pest and disease management, highlighting how diverse plant and animal species can reduce crop damage through natural control mechanisms, decrease reliance on chemical pesticides, and lower pathogen transmission risks through diverse plant communities. Furthermore, the article examines how biodiversity improves crop resilience to environmental changes, including adverse conditions such as drought and salinity. Finally, it analyzes how biodiversity increases ecosystem stability and resilience, enabling ecosystems to effectively cope with climate change and extreme weather events while maintaining productivity and ecological functions.

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With the rapid development of artificial intelligence (AI) technology, education has encountered unprecedented opportunities and challenges. This paper explores the current state of AI applications in education, their opportunities, challenges, and future development trends. First, the paper analyzes the current status of AI technologies such as intelligent tutoring, adaptive learning, teaching assistance, teaching resource generation, educational management automation, and their practical applications in education. This includes typical cases like intelligent tutoring systems, adaptive learning platforms, intelligent teaching assistants, and educational data analysis and management systems. Next, the paper discusses in detail the potential opportunities of AI in improving learning outcomes, achieving personalized education, reducing teacher workload, enhancing educational equity, and optimizing educational management. At the same time, it addresses the challenges AI technology faces in educational applications, such as ethical issues, data privacy protection, and inequalities in educational resources. Finally, the paper looks ahead to the future development trends of AI in education, proposing important directions for technological advancement, the integration of emerging technologies, the transformation of educational models, and continuous research. It provides a comprehensive analysis and forward-looking recommendations for the application of AI in the field of education.

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The application of Artificial Intelligence (AI) in soil data analysis is rapidly advancing, driving agriculture towards a more intelligent, precise, and sustainable future. The progress of AI technology plays a crucial role in soil data analysis, enhancing the intelligence level of agricultural management and providing strong support for global food security and sustainable development. The future development trends include (1) Improvement in data collection and processing technologies, such as advanced sensors and remote sensing techniques; (2) Innovation in data analysis and modeling methods, including the application of machine learning and deep learning; (3) Intelligent soil health assessment and management, with applications in precision agriculture and automated equipment; (4) Development of intelligent decision support systems, offering real time data analysis and decision-making recommendations; (5) Data integration and sharing, promoting research and collaboration through open platforms; (6) Integration and innovation of technologies, including the application of edge computing and blockchain technology. These trends will continue to drive the advancement of soil data analysis, enhancing the efficiency and sustainability of agricultural production.

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Breeding drought-resistant agricultural varieties is essential in combating drought under global climate change. Key future research areas include: utilizing genomics for identifying and editing drought-resistant genes; exploring epigenomics and transcriptomics to uncover molecular mechanisms; analyzing drought-related changes in metabolites and proteins through metabolomics and proteomics; studying root structures to improve water absorption; promoting plant-microbe symbiosis; optimizing plant physiological and ecological responses; applying AI and big data to accelerate breeding; and integrating traditional and modern breeding techniques with multi-environment trials. These approaches will enhance drought-resistant crop innovation and agriculture’s resilience to drought.

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This paper systematically explores the theoretical foundations, research methods, application areas, and future development trends of commercial geography. First, it introduces the definition, research objects, and scope of commercial geography, with a focus on explaining the geographical distribution characteristics of commercial activities and the spatial layout patterns of commercial facilities. Second, it discusses the importance of consumer behavior and market analysis in commercial geography and introduces relevant theories and models. Next, the paper emphasizes the application of commercial geography in urban planning and management, including commercial district planning and design, as well as the coordination between commercial activities and urban development. Finally, it looks ahead to the future development trends of commercial geography, highlighting the impact of digital technologies and the challenges and opportunities for sustainable commercial development. This paper aims to provide a comprehensive overview of the current research status and future directions of commercial geography, to promote the further development and application of this discipline.

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The application of big data technology in rice rotation systems provides a scientific basis and decision support for improving agricultural production efficiency and achieving sustainable development. This paper explores the main research directions of rice rotation systems in the context of big data. First, big data analysis and modeling are used to optimize planting patterns and scheduling to increase yields, improve soil health, control pests, and enhance water resource utilization efficiency. Second, by integrating meteorological, soil, and crop growth data, pest and disease prediction models are established to enable real-time warnings and management, reducing chemical pesticides and enhancing system sustainability. Additionally, by analyzing historical soil data and fertilizer usage, the impact of different rotation patterns on soil fertility is assessed, and scientific soil management strategies are proposed to ensure long-term sustainability. Simultaneously, meteorological, hydrological, and crop data optimize irrigation management, reducing water waste and increasing water use efficiency. Finally, big data technology is applied to assess the carbon emissions and environmental impacts of different rotation systems, and low-carbon, efficient rotation models are developed to address the challenges of climate change.

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This article explores the innovative application and prospects of AI and gene editing technology in cultivating high-yield crops. It introduces five key areas: identification and optimization of gene editing targets, multi-gene regulation of complex traits, enhancement of environmental adaptability and stress resistance, shortening of breeding cycles, and data integration with intelligent analysis. The extensive use of AI in gene screening, CRISPR/Cas system optimization, multi-gene network analysis, phenotypic prediction, stress resistance gene selection, environmental simulation, breeding decisions, and precision agriculture feedback has greatly improved breeding efficiency and crop yields. By combining these technologies, the article envisions the future direction of agriculture, where crops more adaptable to their environment, with stronger stress resistance and higher yields, can be developed in shorter breeding cycles. This provides strong support for global food security and sustainable agriculture.

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This article delves into the key research directions for shale oil reservoirs, covering core areas such as enhancing recovery rates, optimizing fracturing efficiency, assessing environmental impact and sustainability, precise reservoir characterization and simulation, advancing smart oil fields and digital technologies, promoting carbon capture and enhanced oil and gas recovery techniques, as well as evaluating economic viability and innovative business models. Through a systematic analysis of these research directions, the article aims to uncover the technical challenges and creative opportunities in future oil development, emphasizing the importance of maintaining competitiveness and driving sustainable development in the global energy market. Breakthroughs in cutting-edge research will inject new momentum into shale oil development, propelling the oil industry toward greater efficiency and environmental sustainability.

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This paper explores the critical role of nitrogen fertilizers in crop rotation systems and identifies future research directions. Nitrogen fertilizers are essential not only for promoting crop growth and increasing yields but also for improving soil health. However, an imbalanced nitrogen supply can lead to environmental issues. To address these challenges, future research will focus on the application of precision fertilization technologies, the development of microbial growth promoters, crop variety improvement, optimization of ecological rotation systems, comprehensive assessment of the environmental impact of nitrogen fertilizers, the promotion of smart agriculture and data-driven management, and the exploration of nitrogen fertilizer alternatives. These research directions aim to enhance nitrogen use efficiency, reduce environmental burdens, and promote sustainable agricultural development.

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Climate change is one of the most pressing global challenges, profoundly affecting all Earth system components. This paper systematically analyzes the major impacts of climate change on the atmosphere, ocean, and terrestrial systems, covering aspects such as rising temperatures, increased frequency of extreme weather events, sea-level rise, glacier melting, and ecosystem changes. Additionally, the paper delves into the models and methods used for simulating and predicting climate change, including the latest developments and applications of global and regional climate models. Addressing the uncertainties and challenges in simulation predictions, the paper examines factors such as the quality of data inputs, model complexity, and the potential of emerging technologies like artificial intelligence and machine learning. The paper also assesses the sensitivity of different regions to climate change, predicts future climate scenarios, and discusses adaptation and mitigation strategies. By emphasizing the importance of interdisciplinary research, the paper proposes future research directions and policy recommendations, aiming to provide readers with a comprehensive framework for understanding the impact of climate change on the Earth system and its simulation predictions and offering insights for future research and policy-making.

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This paper delves into the key research directions of crop molecular breeding and intelligent technologies in future agriculture. With advancements in multi-omics data integration and analysis, researchers can more precisely identify genes associated with target traits. The deep application of artificial intelligence and machine learning has greatly enhanced breeding efficiency and decision-making accuracy. The optimized application of gene editing technology combined with big data has accelerated improvements in disease resistance, stress tolerance, and nutritional value. The establishment of global breeding big data platforms has promoted data sharing, speeding up the global crop improvement process. Automated phenotypic data collection and analysis technologies, using tools such as drones and sensors, have increased data accuracy and efficiency. Molecular breeding techniques are gradually integrating with sustainable agriculture principles, leading to the development of new varieties that are adapted to climate change and reduce environmental impact. The application of digital twin technology accelerates the development of new varieties under different environmental conditions through virtual modeling. Personalized breeding technologies meet the increasingly diverse demands of consumers through targeted breeding, driving agricultural products toward precision and high-added value.

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Artificial intelligence is critical in crop growth prediction, and future research directions span several key areas. These include multimodal data integration, which aims to enhance prediction accuracy by combining satellite imagery, meteorological data, and soil sensor information; climate change modeling to predict its impact on crop growth; the development of reinforcement learning and adaptive systems for real-time optimization of planting strategies; the advancement of precision agriculture to improve resource efficiency through more detailed predictions; the application of intelligent agricultural robots to reduce reliance on manual labor; and the enhancement of deep learning model training efficiency. These innovations will drive the advancement of agricultural technology, increase yields, protect the environment, and achieve sustainable agricultural growth.

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Future research directions in ecological agriculture encompass several key areas. Firstly, it involves developing sustainable agricultural technologies such as precision agriculture and water-saving irrigation to enhance resource use efficiency and reduce environmental impact. Secondly, it focuses on strengthening soil health and biodiversity research to improve crop resilience and ecosystem stability. Additionally, the exploration of carbon farming, aimed at reducing greenhouse gas emissions through soil organic carbon accumulation, and promoting circular agriculture by utilizing agricultural waste to enhance resource efficiency and minimize waste, are also critical. Further research includes enhancing the agricultural system's ability to adapt to climate change, such as adjusting cropping patterns and selecting resilient crop varieties. Meanwhile, quantifying and assessing ecosystem services like soil and water conservation and climate regulation is essential for a deeper understanding of ecological agriculture's economic and environmental benefits. Lastly, policy support and economic incentives, such as subsidies and carbon trading markets, are crucial for promoting the widespread adoption of ecological agriculture. These research efforts will advance ecological agriculture, providing effective solutions for global food security and environmental protection.

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This article explores the future development directions and prospects of big data analysis in crop molecular breeding and intelligent breeding technologies. Key areas include the deep integration of big data and artificial intelligence, precise breeding through gene editing and molecular marker technologies, intelligent breeding platforms and automated breeding systems, personalized breeding, regional custom variety development, dual improvements in crop stress resistance and nutritional quality, shortening of the breeding cycle and efficient utilization of germplasm resources, sustainable agriculture and green breeding technologies, as well as global collaboration and data sharing. The integration of these technologies and strategies will significantly enhance breeding efficiency, promote sustainable agricultural development, and address challenges related to climate change and global food security.

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Amid increasing environmental and resource pressures on global agriculture, maintaining soil health has become a critical factor in promoting sustainable agricultural development. Advances in big data technology offer new tools for monitoring, managing, and optimizing soil health. This paper focuses on analyzing the interactions between soil structure, nutrients, and microbial communities, and explores the application of big data in soil resource management to support sustainable agriculture. First, the paper provides an overview of the basic concepts of soil health and its importance in sustainable agriculture. Then, it delves into the application of big data in soil health research, including data collection, monitoring, and intelligent management technologies. Furthermore, the complex dynamic relationships between soil structure, nutrients, and microbial communities and their impact on soil function and agricultural productivity are examined. Finally, the paper summarizes the advantages and challenges of big data technology in soil health management and forecasts its future application in sustainable agricultural practices. This study aims to provide theoretical support and methodological references for research and practice in the field of big data technology applied to soil health and sustainable agriculture.

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As an important agricultural management practice, crop rotation has significant long-term effects on soil fertility and nutrient cycling. This article explores the impact of crop rotation on soil nutrient dynamics, soil organic matter accumulation, and nutrient release and utilization efficiency, analyzing its role in enhancing agricultural sustainability and soil health. This article covers the cycling of major nutrients (nitrogen, phosphorus, potassium) and trace elements, as well as the long-term effects on soil organic matter and nutrient release mechanisms. Through long-term field experiments, soil nutrient level measurements, crop yield, and fertilizer requirement records, soil chemical analyses, and nutrient modeling applications, this article evaluates the actual effects of different crop rotation systems on soil fertility and nutrient cycling. These findings not only reveal the contribution of crop rotation to soil health and crop productivity but also provide a scientific basis for formulating fertilization strategies and optimizing agricultural management practices. The primary aim of this article is to provide empirical support for promoting sustainable agricultural development by gaining a deeper understanding of the long-term effects of crop rotation, ensuring efficient resource utilization, and sustainable environmental health.

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With the rapid development of big data technology, agricultural research is increasingly adopting advanced data analysis methods to optimize farming practices and improve soil health. This article explores how big data technology can deepen our understanding of the impact of crop rotation on soil microbial communities by introducing the systematic collection and integration process of soil samples, environmental data, and crop data. High-throughput sequencing technology and functional genomics are utilized to analyze microbial communities' structure and functional potential, while soil enzyme activity tests assess their performance. In the data analysis and modeling section, the focus is on using statistical analysis and machine learning techniques to mine patterns and trends within the data, establish predictive models, and perform spatiotemporal analysis to evaluate the specific effects of crop rotation on soil microbial communities. Finally, the importance of interdisciplinary collaboration is emphasized, highlighting that cooperation with bioinformaticians and agricultural scientists can effectively translate research findings into practical applications, promoting sustainable agricultural development. Through these studies, this article aims to provide a scientific reference for agrarian management, enhance soil health and crop productivity, and achieve long-term sustainability in agriculture.

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Research on the impact of crop rotation on soil structure and erosion control plays a crucial role in sustainable agricultural practices. This paper will comprehensively evaluate the effects of crop rotation on the physical properties of soil, particularly focusing on soil structure and erosion prevention. Specifically, it will analyze the influence of crop rotation on soil aggregate structure, aeration, and water retention capacity, exploring how different crops contribute to soil physical stability and erosion resistance. Furthermore, this paper will discuss how crop rotation acts to protect the soil surface and prevent erosion, as well as the influence of weather conditions on the effectiveness of crop rotation. These studies are expected to lead to the development of practical management strategies that simultaneously promote soil conservation and enhance agricultural productivity.

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This article presents several key recommendations for future research in the fields of cultural geography and heritage conservation, aiming to address the increasingly complex challenges in cultural heritage preservation today. This article focuses on analyzing the potential of digital technologies in heritage conservation, the threats posed by climate change to cultural heritage, the importance of community participation and local knowledge, the urgency of protecting cultural diversity in the context of globalization, sustainable development pathways for heritage tourism, and the need to strengthen legal and policy frameworks to promote global heritage conservation cooperation. Through an in-depth exploration of these research directions, this article aspires to lay an innovative research foundation for the long-term protection and sustainable use of cultural heritage, providing practical references.

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Soil health plays a crucial role in the development of sustainable agriculture. This article explores several key research directions, including the development and assessment of soil health indicators, detection and remediation of soil degradation, the impact of sustainable agricultural practices on soil health, the relationship between soil biodiversity and ecosystem functions, the role of soil carbon sequestration in climate change mitigation, and the interactions between soil and water resource management. By analyzing research advancements in these areas, this article aims to propose research direction suggestions for enhancing soil health, optimizing agricultural productivity, and addressing climate change. These research directions not only lay a scientific foundation for the sustainable development of agriculture but also provide important references for global ecosystem protection and climate adaptation strategies.

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Marine Geography, a crucial branch of geography, studies the natural features, dynamic processes, and interactions between the ocean, land, and atmosphere. This paper reviews the major research areas in marine geography, covering topics such as ocean topography, seafloor structures, ocean dynamics, hydrological processes, marine ecosystems, biodiversity, and the impact of human activities on the marine environment. It emphasizes the critical roles of ocean currents, tides, and global ocean circulation in the climate system, and explores the current state of marine biodiversity and conservation strategies. Additionally, it examines environmental issues caused by human activities. This paper introduces commonly used research methods and techniques, including remote sensing, Geographic Information Systems, and data modeling, while also highlighting future research directions and challenges in addressing global change and ensuring the sustainable use of marine resources. Through a comprehensive analysis of frontier research in marine geography, this paper aims to thoroughly understand the field and offer theoretical support and a reference framework for future research and practice.

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This paper explores the theoretical foundation, practical approaches, and challenges faced in globalization concerning cultural geography and heritage conservation. First, it provides an overview of the evolution of cultural geography and its crucial role in interpreting regional cultures. Then, it analyzes the core concepts of heritage conservation, covering tangible and intangible cultural heritage protection strategies and policy frameworks. This paper further examines the interrelationship between cultural geography and heritage conservation, showcasing its application through specific case studies. Lastly, it analyzes the impact of globalization on local cultures, offers coping strategies, and envisions the future role of cultural geography and heritage conservation in sustainable development. This paper aims to provide theoretical support and practical guidance for understanding and addressing the complex issues in contemporary heritage conservation.

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Crop rotation, as an important practice in sustainable agriculture, has a significant long-term impact on improving soil health. With the widespread application of big data technology in agriculture, the effects of crop rotation on soil health can now be monitored and evaluated with greater precision and efficiency. This study, based on a big data platform, comprehensively collects and analyzes the physical, chemical, and biological properties of the soil, exploring the mechanisms by which crop rotation improves soil structure, promotes nutrient cycling, regulates microbial communities, and suppresses pathogens. Through big data modeling and long-term monitoring, this study evaluates the lasting effects of rotation patterns on soil organic matter accumulation, microbial diversity, and soil resilience. Based on the analysis, optimized rotation systems and soil management strategies are proposed, aimed at continuously enhancing soil health and promoting sustainable agricultural development. This study provides important data support and reference for agricultural decision-making and soil management.

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With the increasing global focus on food security and sustainable agriculture, the demand for genetic improvement of potatoes, as a key food crop, is becoming more urgent. Gene editing technologies such as CRISPR/Cas9 offer promising applications for enhancing potato disease resistance, drought tolerance, and nutritional quality. However, traditional gene target identification methods often face challenges such as time consumption and high costs, which limit editing efficiency. This paper presents a new perspective on gene target identification based on artificial intelligence (AI). By deeply mining genomic sequences and predicting gene functions, AI technologies accelerate the discovery and validation of gene targets, significantly improving the efficiency and precision of gene editing. This paper aims to promote the academic community's awareness of AI-driven gene target identification technologies and facilitate innovation and progress in crop improvement research.

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As global agricultural production faces increasingly severe challenges from diseases, research on disease-resistance genes in corn, an important food crop, becomes particularly significant. This paper explores several research directions for optimizing disease resistance gene editing targets in corn, including the application of artificial intelligence technology in target identification and validation, prediction and assessment of off-target effects, enhancement of editing efficiency, and the integration of diversity and adaptability studies. The paper also emphasizes the importance of interdisciplinary collaboration and data-driven dynamic adjustments in improving the precision and efficiency of gene editing. These research directions promote gene editing technologies' development and provide a scientific basis and practical guidance for disease-resistant breeding in corn. By integrating the latest research findings, this paper aims to explore the optimization pathways for disease-resistance gene editing targets in corn, thereby providing references for improving agricultural productivity and ensuring food security.

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Wheat root system architecture plays a crucial role in drought resistance, with characteristics such as deep rooting, high root density, root branching, and root hair development significantly affecting water acquisition and utilization efficiency. As climate change exacerbates drought risks, it is essential to understand how root system architecture adapts to different environmental conditions to enhance wheat’s drought tolerance. Future research should focus on several areas: first, identifying the genetic basis associated with root system architecture through genome-wide association studies (GWAS) and quantitative trait locus (QTL) mapping; second, exploring the adaptive mechanisms of roots under different soil types and moisture conditions; third, investigating the interactions between roots and rhizosphere microorganisms to improve water absorption efficiency; fourth, analyzing the physiological mechanisms of roots under drought stress; fifth, applying gene editing techniques to optimize root traits for drought environments; sixth, assessing the impact of climate change on root growth and drought resistance; and seventh, studying the effects of integrated agricultural management practices on wheat root system architecture. These studies will provide scientific evidence for drought-resistant breeding in wheat and promote the achievement of food security and ecological balance in sustainable agriculture.

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As climate change and extreme weather events increase, natural disasters’ frequency and intensity continue to rise worldwide. Traditional disaster prediction and prevention methods face numerous challenges regarding accuracy and response speed. This paper explores the cutting-edge applications of big data and artificial intelligence (AI) technologies in natural disaster prediction and prevention, with a focus on analyzing the ability of big data to extract disaster patterns from multisource data and the innovative approaches AI employs—through machine learning and deep learning—to enhance prediction accuracy. Using case studies of earthquakes, floods, and landslides, the paper demonstrates the practical effectiveness of these technologies in real-time monitoring, early warning systems, and emergency response. Additionally, the paper discusses future technological trends and ethical challenges in disaster management, emphasizing the importance of interdisciplinary collaboration and technological integration. This paper aims to provide a comprehensive technical review of the disaster management field, revealing the potential of big data and AI in enhancing global disaster response capabilities and offering a reference for future research and applications.

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This study uses big data and artificial intelligence technologies to analyze the impact mechanisms of multi-level soil characteristics and topsoil thickness on nitrogen denitrification. By collecting environmental data such as different soil structures, textures, and moisture content, a predictive model for nitrogen denitrification was constructed. The results show that soil structure and moisture content significantly affect the denitrification rate, while topsoil thickness plays a key role in nitrogen transformation by regulating soil aeration and microbial activity. The study also evaluates the risk of nitrogen loss under different topsoil thicknesses and proposes strategies for optimizing topsoil management and reducing nitrogen loss. This research provides new practical references for improving nitrogen use efficiency and promoting the development of precision agriculture.

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Water-saving cultivation and dryland farming are key strategies to address global water scarcity and climate change. This paper systematically analyzes the development and application of water-saving cultivation technologies, including efficient irrigation methods such as drip and micro-irrigation, as well as soil moisture retention measures. It also explores adaptive regulation mechanisms in dryland farming, with a particular focus on drought-resistant crop selection, root system optimization, and biotechnology applications. By examining the synergistic effects of these approaches, the complementary advantages of water-saving cultivation and dryland farming in improving water use efficiency and enhancing crop drought resistance are revealed. Additionally, the paper assesses their positive impact on ecosystems, soil health, and water resource management, and discusses their contributions to sustainable agricultural development through an analysis of economic benefits. Finally, the paper looks ahead to future development directions supported by smart agriculture and big data technologies, as well as the challenges posed by climate change and corresponding response strategies. This paper aims to provide valuable practical insights for global sustainable agriculture.

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Climate change seriously challenges agricultural production, profoundly impacting crop disease resistance. This paper aims to explore research directions on the impact of climate change on maize disease resistance gene expression, with a focus on the multidimensional effects on maize disease resistance. First, the paper reviews the importance of genomics and transcriptomics in identifying key disease-resistance genes and their regulatory mechanisms. Next, it discusses how metabolomic analysis reveals the effects of climate change on plant hormones and disease-resistant compounds, as well as the relationship between these metabolites and disease-resistance gene expression. Subsequently, the necessity of climate condition simulation experiments is introduced to observe how various environmental factors affect disease resistance gene expression and resistance capability. Additionally, the application of transgenic technology in enhancing disease resistance gene expression is mentioned, underscoring its potential in addressing the challenges posed by climate change. Finally, this paper highlights the importance of long-term monitoring and data analysis, ecological research, and comprehensive multi-factor studies to fully understand the mechanisms of climate change’s impact on maize disease resistance. These studies are expected to provide a scientific basis for maize breeding and management practices to enhance disease resistance in changing environments, thus safeguarding future food security and sustainable agricultural development.

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