This study develops an improved hybrid life cycle assessment (IHLCA) method to evaluate the carbon footprint of a straw-based photovoltaic hydrothermal liquefaction (PV-HTL) poly-generation system across 31 Chinese provinces. Results indicate that the greenhouse gas (GHG) emission intensity of the PV-HTL process is 2.5 g CO2-eq/MJ, achieving a 71.4% reduction compared to conventional thermal power. Integrating biochar soil amendment enables the system to achieve negative carbon emissions. Specifically, returning 8.22% of the co-produced biochar to the soil achieves net-zero emissions, while a 100% application rate yields a strong negative net GHG emission intensity of-27.6 g CO2-eq/MJ. Scaling this full biochar application scenario across the 31 provinces could sequester 20.23 million tons of CO2-eq in soil, offsetting 62.9% of total regional emissions. Finally, the provinces are categorized into negative, low, and high carbon-emission regions, providing a crucial scientific basis for tailoring agricultural decarbonization strategies.

Remote sensing inversion products for soil organic matter (SOM) are fundamental to monitor and assess soil quality in the black soil region of Northeast China. However, current research has largely prioritized the vertical optimization of inversion algorithms for single products, while ignoring systematic horizontal comparisons among different products, which limits their practical application. Based on a systematic literature review, we synthesized the spatial distribution characteristics, mainstream methodologies, and current status of data products for remote sensing-based inversion of soil organic matter (SOM) in the region. We found that 1) 77.5% of existing studies are concentrated in the Songnen and Sanjiang Plains, while regions such as eastern Inner Mongolia remain underrepresented; 2) a dominant paradigm has emerged, integrating multispectral data, environmental covariates and machine learning techniques; 3) there are inconsistencies among publicly available SOM products, with estimate discrepancies exceeding 30%. There are three major challenges: limited data sources, multiple interfering factors, and insufficient model interpretability and applicability of models. In the future, low altitude remote sensing data should be actively introduced, a ground aerospace multi-level remote sensing fusion system should be constructed, innovative modeling and promotion methods should be developed, grid-based datasets should be built, and data sharing should be promoted to fully explore the application value of soil data.

This study focuses on the landscape pattern changes in the Yellow River Basin of the Kubuqi Desert. Considering its ecological vulnerability and the challenges of ecological degradation and restoration, a remote sensing ecological index cube framework integrating multi-source remote sensing ecological indices was constructed to analyze the landscape pattern dynamics from 2013 to 2023. The study area includes the northern wetland and Yellow River corridor as well as the southern and central desert core areas. Landsat 8 and Sentinel-2 data were used, and after processes like atmospheric correction and cloud removal, multiple indices such as Ratio Vegetation Index and Normalized Difference Vegetation Index were selected. A spatio-temporal cube was built and analyzed through operations like slicing and aggregation. The results show that from 2013 to 2018, vegetation degraded, and after that, the vegetation restoration in the northern wetland and along the Yellow River accelerated, while the restoration of vegetation and water bodies in the southern core area was slow. Landscape patterns differed significantly among regions, affected by factors like geography and water resources. Future efforts should optimize soil improvement, water resource management, and ecological governance strategies. This study also provides a reference for subsequent desert ecological monitoring and management, though it still needs to incorporate meteorological data for further analysis.

With the advancement of urban-rural integration in China, understanding rural household food commodification is crucial for uncovering the interconnections between rural socio-ecological systems and urban systems. This study aims to systematically identify the characteristics of rural household food commodification and provide new perspectives on the transformation mechanisms of rural socio-ecological systems. We first conceptualize rural food commodification and develop a theoretical framework that integrates the characteristics of production and consumption activities. Subsequently, we propose a dual measurement method to evaluate both production and consumption sides of food commodification, introducing the Food Production Commodification Index (FPCI), the Food Consumption Commodification Index (FCCI), and sales and purchase indices for various food types. Based on field survey data, Liaoning Province was selected as a case study. The results show that food commodification is widespread, with 33 % of households relying entirely on purchased food. However, the types of food production commodification are limited, with 75 % selling grains but fewer than 17 % engage in the production of beans, oil crops, vegetables, livestock, poultry, or fruits. Additionally, 51 % of households earn more than half of their income from non-agricultural activities, indicating a shift in rural livelihoods from traditional agricultural production to a more diversified economic structure. Rural households' food consumption behavior increasingly resemble those that of urban residents. The process of food commodification highlights the emergence of urban production and lifestyle characteristics within rural economies, while also demonstrating the role of commodified food transactions in linking urban and rural socio-economic systems. These findings provide a foundation for developing precise and effective strategies for rural sustainable development.

Greenhouse gas emissions are a leading cause of global warming, posing significant threats to both the natural environment and the sustainable development of global economies and societies. Environmental regulations have been crucial in reducing these emissions and improving ecological conditions. This study presents the first theoretical analysis of the mechanisms through which formal and informal environmental regulations influence carbon intensity. A panel data model was constructed to empirically test and analyze the impact of these regulations on carbon intensity across 118 countries. The findings reveal that both formal and informal environmental regulations exerted a reduced influence on global carbon emission intensity, affirming their significance in promoting energy conservation and emission reduction. Moreover, a synergistic effect was observed between the two types of regulations, indicating that their coordinated enforcement could further mitigate carbon emission intensity. Regional analysis revealed that formal environmental regulation exhibited a dampening effect on carbon emission intensity in both high- and low-carbon countries. However, the moderating impact of informal environmental regulation was found to be markedly stronger in low-carbon countries compared to their high-carbon counterparts. The synergy between these two forms of regulation had a more pronounced influence on the carbon emission intensity of high-carbon countries, underscoring their potent emission reduction effect when implemented in tandem. The insights gained from this study can aid policymakers in developing effective environmental policies aimed at realizing energy conservation and emission reduction goals, thereby contributing to the mitigation of global warming and the promotion of sustainable development.

The acceleration of the formation and development of new quality productive forces in the new era is an inevitable requirement for China's high-quality development and an important historical mission for achieving socialist modernization and ecological civilization. We interpreted the contemporary connotation of new quality productive forces from the perspective of applied ecology, which refers to an innovative production capacity driven by the optimization and sustainable utilization of ecosystem services, promoting harmonious coexistence between humans and nature. Furthermore, we summarized the developmental trajectory of applied ecology, evolving from biological to social and finally to digital applied ecology, and explored its crucial role in fostering disciplinary and technological innovation as well as the allocation of production resources. Looking ahead, applied ecology should take ecosystems as its core and strengthen the integration of biological cognition and human activities. It should focus on the development of ecological theories for new quality productive forces, the construction of methodological systems that integrate green development and innovation, and the practical application of ecological scenarios for new quality productive forces, which all contribute to achieving the green and healthy development of ecosystems. To promote the development of new quality productive forces through the interdisciplinary integration of applied ecology would provide ecological support for harmonious coexistence between humans and nature.

Addressing the ecological vulnerability and challenges of degradation-restoration dynamics in transitional human-earth systems represented by the Kubuqi Desert region, this study leverages the advantages of multisource remote sensing imagery in multifactor, annual cyclical, long-term, and spatially heterogeneous complex surface feature analysis. By integrating discrete pixel characteristics with continuous change processes in landscape pattern dynamics, we developed a remote sensing ecological index cube framework. This framework innovatively incorporates an improved dynamic composite weighted spatiotemporal cube approach, enabling adaptive capture of multiperiod nonlinear superposition effects and their spatiotemporal manifestations within the "policy-intensive intervention versus natural gradual recovery" temporal mismatch context. The results demonstrate 1) vegetation degradation dominated during 2013-2018, followed by accelerated recovery in northern wetlands and Yellow River riparian zones post-2018, while southern core areas exhibited sluggish vegetation and water body restoration; 2) significant interregional landscape pattern disparities driven by geographical constraints and water resource heterogeneity; and 3) distinct phase-specific responses to ecological policies, with northern areas showing higher restoration efficiency than southern regions under equivalent intervention intensity. Mechanistically, the spatiotemporal cube analysis revealed two superimposed cycles (5-year policy cycles and 11-year natural recovery cycles) explaining 68% of vegetation variance. This decoupling effect between anthropogenic and natural drivers provides quantitative evidence for optimizing spatial targeting of ecological engineering and synchronizing restoration chrono sequences.

The sustainability and suitability of water resources are of great importance for maintaining urban populations. The landscapes and environment around urban waters have always been the main focus of maintaining water quality for sustainable water supplies. Early-stage field investigations recognized the influence of land use/land cover (LULC) on water quality. To extend the research scope in spatial and temporal dimensions, remote sensing techniques have been utilized to discover the relationships between LULC and water quality. However, these remote sensing datasets generally had a medium spatial resolution, making them unable to support the fine-detailed land classifications that are critical to explore the water quality in an urban area. Moreover, although more details regarding the land surface are available from the currently-generated high-resolution and very-high-resolution remote sensing images, this land surface information is too complex for the state-of-the-art deep learning approaches and benchmark datasets. This manuscript reports our efforts on developing a framework to explore the fine-resolution relationship between surface water pollution and LULC. To address the cost of computing time and limitations of well-labelled datasets, we employ a foundation model-enhanced approach for water extraction and water-surrounded LULC classification. We propose an estimator of surface water pollution susceptibility to main pollutants based on the surrounding LULCs. Selecting the Future City of Beijing as the study area, based on very-high-resolution remote sensing images, the experiment proved that our proposed approach could effectively map the susceptibility of surface water pollution caused by its surrounding land use and land cover. To our knowledge, the relationship of LULCs and water quality have not been investigated using 0.5 m spatial resolution data. We hope our work can provide a prospective fine-detailed water quality analysis in the community of water environment of remote sensing.

The quantitative analysis of spatio-temporal variations of vegetation cover and its correlation with climate are of great significance for understanding of ecological environment,ecological civilization construction,and sus-tainable development in semi-arid areas.We investigated the spatio-temporal variations of normalized difference vegetation index(NDVI)and its response to climate change during 2000-2020 in Xilin Gol,Inner Mongolia,by using trend analysis,regression analysis and partial correlation analysis based on the data of MODIS-NDVI,tempe-rature,precipitation,digital elevation model.The results showed that vegetation cover in Xilin Gol had been increased from 2000 to 2020,which generally included three phases,i.e.,stable fluctuation,rapid growth,and steady growth.The mean NDVI showed a zonal increasing distribution from southwest to northeast,and had a strong correlation with elevation and population density in Xilin Gol region.The high values of NDVI were mainly in the east,with a significant increasing trend,and the low values were in the southwest,with a local degradation.The sensitivity of vegetation cover to climate change showed spatial and temporal variations.The spatial variation of vegetation was more sensitive to temperature and the interannual variation was sensitive to annual precipitation.In summary,vegetation cover improved overall in Xilin Gol,but there was degradation in some areas.We should formulate differentiated and precise vegetation restoration and ecological environmental protection policies.

Net ecosystem productivity (NEP) plays a vital role in quantifying the carbon exchange between the atmosphere and terrestrial ecosystems. Understanding the effects of dominant driving forces and their respective contribution rates on NEP can aid in the effective management of terrestrial carbon sinks, especially in rapidly urbanizing coastal areas where climate change (CC) and human activities (HA) occur frequently. Combining MODIS NPP products and meteorological data from 2000 to 2020, this paper established a Modis NPP-Soil heterotrophic respiration (Rh) model to estimate the magnitude of NEP in China’s coastal zone (CCZ). Hotspot analysis, variation trend, partial correlation, and residual analysis were applied to explore the spatiotemporal patterns of NEP and the contributions of CC and HA to the dynamics of NEP. We also explored the changes in NEP in different land use types. It was found that there is a clear north–south difference in the spatial pattern of NEP in CCZ, with Zhejiang Province serving as the main watershed for this difference. In addition, NEP in most regions showed an improvement trend, especially in the Beijing–Tianjin–Hebei region and Shandong Province, but the pixel values of NEP here were generally not as high as that in most southern provinces. According to the types of driving forces, the improvement of NEP in these regions primarily results from the synergistic effects of CC and HA. NEP changes in provinces south of Zhejiang are mainly dominated by single-factor-driven degradation. The area where HA contributes to the increase in NEP is much larger than that of CC. From the perspective of land use types, forests and farmland are the dominant contributors to the magnitude of NEP in CCZ.

The development of the eco-economy has become an important way to promote sustainable development and address climate change worldwide. Implementing eco-economic developmental policy globally or locally requires establishing precise indicators. Currently, there are many studies on eco-economy indicators at the academic level, but the eco-economy indicators researched at the academic level are difficult to be implemented and applied by local governments in China, and there is a knowledge gap between the political sector and the academic sector in the process of cooperation. This mainly stems from the lack of whole-process research and analysis that combines government practice and academic research. We attempt to analyze the differences in the understanding of eco-economic indicators between academics and government decision-makers through the study of the establishment process of China's local eco-economic indicator system. We try to find out the reasons for the knowledge gap between academics and government decision-makers, and to build a knowledge bridge between government practice and academic research. At the same time, China, as the largest developing country and an emerging country in the construction of ecological civilization, is worth studying and learning from its experience in the construction of eco-economic indicators. Therefore, we systematically study the connotation of China's eco-economy and the development process of the indicators. And we combine with the practical experience, describe the method and specific process of constructing eco-economy indicators at the provincial scale of the Chinese government. Meanwhile, we put forward the limitations of the construction of the eco-economy indicator system in Liaoning Province. In addition, we analyze in detail the characteristics and attributes of the ecological economy indicators in Liaoning Province, as well as the relationship of these indicators to the implementation of national strategies and to the SDGs. The discipline contributions and scientific and technological concerns of the indicator system's creation are reviewed, and additional improvement ideas are presented. It is expected that the practice of eco-economic indicators in China will further promote eco-economy development and provide methodological reference for countries to measure the level of eco-economic development.

Excessive emission of reactive nitrogen (Nr) in the environment has a negative impact on human health and biodiversity and aggravates the greenhouse effect. Food production and consumption is the primary source of anthropogenic Nr emissions. Currently, the research on China's nitrogen footprint lacks the exploration of regional differentiation, and the local virtual Nitrogen factor (VNF) is also insufficient. In this study, we developed localized VNF at the provincial level in China and then applied them to measure the per capita food production Nitrogen footprint of 31 provinces in mainland China from 1998 to 2018 by employing a modified N-Calculator model. We found that the national per capita food production N footprint varied from 15.30 to 21.09 kg/year over the past 20 years. Per capita food production N footprint of 29 provinces increased, ranging from 13% to 113%. The dominance of the food production N footprint of meat gradually increased, and the differences between regions showed a decreasing trend. Finally, we compared the results with different countries based on VNF and 2018 food consumption data. Although the limitations of the underlying data and parameters pose challenges to the accuracy of the estimation, our study provides an original data contribution to nitrogen footprint research to scientific communities and policymakers.

The scientific evaluation and identification of the relationship between urban comprehensive carrying capacity and urbanization in Northeast China, a famous old industrial base, is an important basis for realizing the overall revitalization of the region. Using a panel data set of 34 prefecture-level cities in Northeast China from 2003 to 2019, this study constructs an ordinary panel data model to identify the relationship between urban comprehensive carrying capacity and urbanization. The results show that urbanization has significantly positive effects on urban comprehensive carrying capacity, and there is a significant inverted U-shaped curve relationship between urban comprehensive carrying capacity and comprehensive urbanization in Northeast China, especially in the shrinking cites. In addition, the economic urbanization variables of the fixed-asset investment, the total retail sales of social consumer goods, and the social urbanization variable of internet users play significantly important roles in forming of the inverted U-shaped curve relationship with the urban comprehensive carrying capacity of the shrinking cities in Northeast China. Hence, innovation-driven economic regrowth, promoting equalization of basic public services, alleviating talent outflow, and strengthening the leading roles of the core cities are effective measures for improving urban comprehensive carrying capacity and urbanization quality in Northeast China.

村落尺度的低碳建设不仅可以提高村落的能源供给水平,充分挖掘农村资源的潜力,同时在促进绿色乡村的建设方面具有重要作用.本研究以河南省邑西里村为例,通过构建碳能源体系框架,研究不同情景下的碳排放水平,进而判断村落在低碳能源体系建设中的功能角色.结果表明:全村2020年的能源消费热值为5925 GJ,全村的碳排放量为877 t;在基准情景、慢速发展情景和快速发展情景下2030年消费量分别为6228、6594、6955 GJ,其碳排放量分别为928、987 t和1046 t;若能实现对太阳能等资源的综合利用,2030年总能源消耗自给率分别为50.76%、52.30%和53.72%.对比不同情景下能源使用的碳排放量,尽管能源种类逐渐向清洁能源的方向转型,但是全村的碳排放量还是呈现出逐渐上升的趋势.因此,如何保证在居民的能源消费结构升级及转型的前提下优化能源结构并提高村落的低碳水平,仍是在未来一段时间内亟需解决的问题.

实现"双碳"战略目标的科学基础主要在于深入且系统地理解地球环境系统和人类经济系统之间的相互作用关系.作为以人地系统为主要研究对象的地理学,在"双碳"研究及成果服务中发挥了重要作用.基于"学科分支—数据方法—研究对象—成果贡献"的思路,对2000年以来中国主流地理学期刊及学者发表的"双碳"文献进行回顾和总结后发现:①不同地理分支学科下"双碳"研究主题呈现多样性的特点,自然地理学侧重研究人为及自然碳源碳汇变化,人文地理学侧重分析碳排放时空分异格局及形成机理,信息地理学侧重构建高时空分辨率碳数据集及开发空间分析工具;②碳核算方法包括排放系数法、实际测量法和遥感估算法等,其数据源主要包括社会经济统计数据、遥感卫星监测数据以及新型地理感知数据等,地学分析模型主要用于描述碳源碳汇空间分布模式,预测空间过程及结果;③地理学视角下"双碳"研究对象分为空间对象和活动对象,前者关注微观、中观和宏观等不同尺度碳源碳汇的空间特征及规律,后者关注能源、工业、农业、土地利用变化及林业等活动产生的碳源碳汇的地理分布;④地理学对"双碳"的成果贡献出口主要包括地理空间分异规律的空间差异化低碳治理、"经济—社会—生态"复合系统的低碳国土空间格局优化、人地系统协调的区域低碳行为主体治理网络等.最后,从数据研发、方法模型、决策运用和全球语境等方面提出了地理学视角下未来"双碳"研究的方向,以期为更好地服务于"双碳"目标提供一定的借鉴和参考.

通过调查分析黑龙江省规模化繁育母牛场母牛泌乳初期矿物质代谢、能量代谢、蛋白质代谢和肝功能酶类代谢特征,以期明确地区肉牛繁育母牛主要营养代谢紊乱的特征.于黑龙江省双鸭山、哈尔滨、大庆、齐齐哈尔等4个地区选取4个规模化舍饲肉牛养殖场,采集牧场产后7d和3d母牛血液,分别记为SYS组(双鸭山产后7d母牛)、HEB组(哈尔滨产后7d母牛)、DQ组(大庆产后7d母牛)、QQHR7组(齐齐哈尔产后7d母牛)、QQHR3组(齐齐哈尔产后3d母牛),并对血液中主要矿物质代谢、能量代谢、蛋白质、肝功相关指标进行检测分析.结果 显示,矿物质代谢方面,QQHR7组母牛血钙浓度显著高于SYS组、HEB组,以血钙＜2.1 mmol/L为低钙血症诊断标准,则低钙血症发病率SYS组为12.5％,DQ组为33.0％,QQHR3组为50.0％,其他2组未见低钙血症母牛;SYS组母牛血Mg2+显著高于HEB、DQ和QQHR7组,DQ组母牛血Mg2+浓度极显著高于QQHR7组.能量代谢方面,SYS和HEB组母牛产后β-羟丁酸(BHBA)浓度显著高于QQHR7组,HEB组母牛BHBA浓度极显著高于QQHR7组;SYS、DQ和HEB组母牛产后甘油三酯(TG)浓度极显著高于QQHR7组;QQHR7组母牛产后游离脂肪酸(NEFA)浓度极显著高于HEB组,DQ组母牛NEFA浓度显著高于HEB组.蛋白质代谢方面,SYS和HEB组母牛产后总蛋白(TP)浓度均极显著高于DQ和QQHR7组;SYS和QQHR7组母牛产后尿素氮(BUN)浓度极显著高于HEB组,QQHR7组母牛显著高于SYS组,DQ组母牛显著高于HEB组;SYS组母牛产后白蛋白(ALB)浓度极显著高于HEB、DQ和QQHR7组;HEB组母牛极显著高于DQ和QQHR7组;HEB和QQHR7组母牛产后球蛋白(GLO)极显著高于SYS组,HEB组母牛显著高于DQ组,HEB组母牛极显著高于QQHE7组.肝脏代谢方面,SYS、HEB和QQHR7组母牛产后谷氨酰转移酶(GGT)浓度极显著高于DQ组;SYS组母牛产后血清谷丙转氨酶(ALT)浓度极显著高于HEB、DQ和QQHR7组;SYS组血清天冬氨酸转氨酶(AST)浓度显著高于QQHR7组;QQHR7和DQ组母牛总胆红素(TBIL)浓度极显著高于SYS组.此外,QQHR3组母牛血清Ca2+、P、GLU、BHBA、TG浓度显著低于QQHR7组,而AST浓度显著高于QQHR7组.结果 表明,由于饲料营养及饲养管理差异围产期肉牛繁育母牛泌乳初期低钙血症发病率较高,个别牧场泌乳初期母牛仍有能量代谢失衡性疾病的发生风险.

The development of ecological economy is one of the core elements of the ecological civilization system and an essential means to optimize the social-ecological systems. The key to developing ecological economy lies in preparing the development plan to realize concrete implementation. Given the objective and realistic demand for the development of ecological economy, it is critically needed to propose the approach of eco-economic planning and conduct empirical research. We sorted out the connotation of ecological economy, proposed the general idea of "object identification-resource evaluation-principal construction-target setting-task content-mechanism guarantee", and proposed three work modules, including "preliminary preparation, content design, review & approval", and finally built a technical system for the preparation of provincial-scale ecological economy planning. We outlined the 14th Five-Year Plan for Eco-Economic Development of Liaoning Province, and discussed critical issues such as the connotation definition and index system establishment for eco-economic development plan. This work provides ideas for the scientific and standardized preparation of ecological economy development plan at the provincial level in China.

作为使用频率最高、服务人群最广的公共服务基础设施,公厕是城乡生态文明建设的重要体现.传统的公共基础设施服务能力评价大多存在空间可视化程度低、位置信息不准确等问题.以兴趣点(point of interest,POI)大数据为代表的新型数据源为更精确更实时认知与评价公共基础设施提供了新的路径.本研究以POI数据为重要数据源,融合传统数据,以公厕资源均衡性和可达性作为衡量公共设施服务能力的指标,对辽宁省其所辖市域、县域及10 km格网下的公厕空间分布格局和服务能力进行评价.研究发现:1)公厕集中分布在副省级城市沈阳和大连,呈现双核多点式分布;公厕在所有城市内部均呈现单核多点、多核多点及小规模多点式聚集分布;85％的公厕分布于城市建成区内,乡镇地区公厕建设亟须强化.2)仅沈阳、本溪和26％的县级单元的公厕数量满足基本需求,而旅游资源丰富的城市其公厕服务能力却较差,说明辽宁省旅游品质的建设和保障亟待提升.3)公厕分布与道路具有较强的相关性,距离邻近道路10～100 m内的公厕占70％以上,公厕分布在可达性方面具有一定合理性.本文将为区域重要公共服务基础设施的合理规划提供科学的决策依据.

为探究二丁酰环磷腺苷钙(dibutyryl cyclic adenosine monophosphate-calcium,DbcAMP-Ca)对育肥期肉牛生长性能、血清生化指标、体液免疫和氨基酸代谢的影响,随机选取12月龄体质量相近的健康西门塔尔肉牛14头分为对照组和试验组,试验组每4d肌肉注射0.2 mg/kg的DbcAMP-Ca,对照组在同一时间内注射0.2 mg/kg的0.9％生理盐水.每次注射DbcAMP-Ca之前采集血液样本,试验期32 d.结果 显示:(1)试验组平均日增重极显著高于对照组(P＜0.01),料重比显著降低(P＜0.05).(2)试验组血清IgG含量第8,20,24天显著高于对照组(P＜0.05),第28,32天极显著升高(P＜0.01);血清IgM含量第20天显著高于对照组(P＜0.05),第32天极显著升高(P＜0.01);血清IgA平均浓度有趋势性升高,但差异不显著.(3)试验组肉牛血清BUN浓度第16,20天显著降低(P＜0.05),在第28,32天极显著降低(P＜0.01);血清TP浓度第12,16,20天显著高于对照组(P＜0.05),第24,28,32天极显著升高(P＜0.01).(4)试验组血清Gly、Ser浓度第24天显著低于对照组(P＜0.05),第32天的血清Gly、Ser以及第24,32天血清Asp浓度极显著降低(P＜0.01);试验组血清Ile、Trp浓度第16天显著高于对照组(P＜0.05),血清Ile、Trp和Thr浓度第24,32天极显著升高(P＜0.01);血清Val浓度第8天显著高于对照组(P＜0.05),血清Val在第16,24,32天以及血清Phe第8,16,24,32天极显著升高(P＜0.01).综上表明,补充适量的DbcAMP-Ca在一定程度上能促进育肥期肉牛的生长性能,增强肉牛的体液免疫以及改善蛋白质和氨基酸代谢.

The rational allocation of functional areas is the foundation for addressing the sustainable development of cities. Efficient and accurate identification methods of urban functional areas are of great significance to the adjustment and testing of urban planning and industrial layout optimization. Firstly, by employing multisource geographic data, an identification method of urban functional areas was developed. A quantitative measurement approach of the urban functional area was then established considering the comprehensive effects of human-land, space-time, and thematic information to present the covering area of ground objects, public awareness, and empirical research. Finally, the Zhengzhou city, which locates in Henan province of central China, was used to test the method. The results show that the developed method is efficient, accurate, and universal and can identify urban functional areas quickly and accurately. We found that the overall distribution of Zhengzhou’s functional areas presents a spatial pattern of single and multimixed coordinated development. The city’s commercial functional areas and commercial-based mixed functional areas are located in the city’s central area. The green square’s function area occupies relatively low and is mainly distributed in the city’s fringe.