Carbon,Fossil Fuel,and Biodiversity Mitigation With Wood and Forests

Life-cycle analyses, energy analyses, and a range of utilization efficiencies were developed to determine the carbon dioxide (CO₂) and fossil fuel (FF) saved by various solid wood products, wood energy, and unharvested forests. Some products proved very efficient in CO₂ and FF savings, while others did not. Not considering forest regrowth after harvest or burning if not harvested, efficient products save much more CO₂ than the standing forest; but wood used only for energy generally saves slightly less. Avoided emissions (using wood in place of steel and concrete) contributes the most to CO₂ and FF savings compared to the product and wood energy contributions. Burning parts of the harvested logs that are not used for products creates an additional CO₂ and FF savings. Using wood substitutes could save 14 to 31% of global CO₂ emissions and 12 to 19% of global FF consumption by using 34 to 100% of the world’s sustainable wood growth. Maximizing forest CO₂ sequestration may not be compatible with biodiversity. More CO₂ can be sequestered synergistically in the products or wood energy and landscape together than in the unharvested landscape. Harvesting sustainably at an optimum stand age will sequester more carbon in the combined products, wood energy, and forest than harvesting sustainably at other ages.     

考虑CTL免疫作用的HIV感染模型的全局动力学性态

研究了一个更一般的考虑CTL免疫作用的HIV感染的数学模型.模型的动力学性态完全由基本再生数R0决定.当R0≤1时,无病毒感染的平衡点是全局渐近稳定的;当R0>1时,平凡平衡点失去稳定性,感染平衡点是全局渐近稳定的.     

一种用于连续寻优的蚁群爬山算法

针对蚁群算法在连续寻优过程初期信息素匮乏、搜索时间长、收敛慢的弱点,对蚁群算法进行改进,并结合爬山算法提出了一种新的蚁群爬山算法.将新的蚁群爬山算法用于求解连续全局优化问题,数值实验证明该算法是可行的、有效的,并且精度和效率优于蚁群算法.     

求解无约束优化问题的一种新的共轭梯度法

一般情况下,求解大规模约束问题的有效算法是共轭梯度法,βk的选取不同构成不同的共轭梯度法。提出了求解无约束优化问题的一种新的共轭梯度法,修正了βk,并在Wolfe线搜索下证明了它的全局收敛性。     

SUSTAINABLE NITROGEN MANAGEMENT INDEX: DEFINITION,GLOBAL ASSESSMENT AND POTENTIAL IMPROVEMENTS

● A composite N management index is proposed to measure agriculture sustainability. ● Nitrogen management has been moving towards sustainability targets globally. ● The improvement was achieved mainly by yield increase, while Nitrogen Use Efficiency (NUE) stagnated. ● No country achieved both yield and NUE targets and spatial variation is large. ● Region-specific yield targets can be used to supplement the standard Sustainable Nitrogen Management Index (SNMI). To represent the sustainability of nitrogen management in the Sustainable Development Goals indicator framework, this paper proposes a sustainable nitrogen management index (SNMI). This index combines the performance in N crop yield and N use efficiency (NUE), thereby accounting for the need for both food production and environmental protection. Applying SNMI to countries around the world, the results showed improvement in the overall sustainability of crop N management over the past four decades, but this improvement has been mainly achieved by crop yield increase, while global NUE has improved only slightly. SNMI values vary largely among countries, and this variation has increased since the 1970s, implying different levels of success, even failure, in improving N management for countries around the world. In the standard SNMI assessment, the reference NUE was defined as 1.0 (considered an ideal NUE) and the reference yield was defined as 90 kg·ha⁻¹·yr⁻¹ N (considering a globally averaged yield target for meeting food demand in 2050). A sensitivity test that replaced the reference NUE of 1.0 with more realistic NUE targets of 0.8 or 0.9 showed overall reduction in SNMI values (i.e., improved performance), but little change in the ranking among countries. In another test that replaced the universal reference yield with region-specific attainable yield, SNMI values declined (i.e., improved performance) for most countries in Africa and West Asia, whereas they increased for many countries in Europe and South America. The index can be improved by further investigation of approaches for setting region-specific yield targets and high-quality data on crop yield potentials. Overall, SNMI offers promise for a simple and transparent approach to assess progress of countries toward sustainable N management with a single indicator.     

基于组件技术的猪肉安全生产全程数字化监控系统

选用WindowsNTServer操作系统平台、SQLServer 2 0 0 0数据库管理系统和VB .NET系统作为开发工具 ,采用了n层体系结构和可重用组件技术。系统主要包括养殖生产过程、屠宰加工和市场销售等 3个应用模块 ,根据猪肉生产不同阶段的要求 ,在各应用模块中建立了档案管理、安全监控、标准法规和警级监控等子系统。系统中的畜体标识保留了原塑料耳标中的数字编码 ,同时增加了与数字编码一致的二维条形码 (datamatrix) ,提高了自动识别水平。系统的警级预报子系统 ,可自动判断生产操作是否违反法规和标准 ,并及时报警。系统为信息技术在畜牧业的运用提供了一种组件化的基础框架。     

基于土地利用变化的江汉平原景观生态风险时空分异特征分析

土地利用/覆被变化能够在一定程度上表征城市景观生态风险空间分异特征。研究基于湖北省江汉平原2000—2015年(2000年、2005年、2010年、2015年)4期土地利用遥感监测数据及县级行政单元区划数据,采用全局自相关模型和地统计空间分析等方法,定量揭示了江汉平原土地利用水平与景观生态风险之间的空间耦合关系。研究表明:(1)2000—2015年江汉平原土地利用类型主要以耕地、水域和建设用地为主,土地转移类型主要以耕地向建设用地转移为主。(2)2000—2015年江汉平原景观生态风险时空演变差异显著,冷点、次冷点数量增加,次热点和热点均呈现先增加后减少态势。生态风险聚集的高值区主要分布在江汉平原东南部洪湖市,低风险区主要分布在江汉平原西部当阳市及松滋市。(3)2000—2015年江汉平原低生态风险区面积呈现逐渐减小态势,从2000年的2 015.63 km²,较少到2015年的1 960.87 km²。中风险区面积呈现先增加后减少的态势,其中2005—2010年增加幅度最大,达到了2 061.26 km²。(4)2000—2005年江汉平原低生态风险重心整体转移不明显,主要集中分布在江汉平原西北部,较低生态风险重心转移空间跨度最大,向西转移了79.80 km。中风险区主要向东北方向转移,较高风险区和高风险区重心主要集中分布在江汉平原东南部洪湖市,且呈现向东北方向转移的趋势,其中较高风险区重心转移速度明显快于高风险区。本研究成果可为城市内部土地利用开发与景观生态风险评价提供科学依据和理论参考。     

Spatial modeling of the carbon stock of forest trees in Heilongjiang Province,China

Heilongjiang province is the largest forest zone in China and the forest coverage rate is 46%. Forests of Heilongjiang province play an important role in the forest ecosystem of China. In this study we investi- gated the spatial distribution of forest carbon storage in Heilongjiang province using 3083 plots sampled in 2010. We attempted to fit two global models, ordinary least squares model （OLS）, linear mixed model （LMM）, and a local model, geographically weighted regression model （GWR）, to the relationship between forest carbon content and stand, environment, and climate factors. Five predictors significantly affected forest carbon storage and spatial distribution, viz. average diameter of stand （DBH）, number of trees per hectare （TPH）, elevation （Elev）, slope （Slope） and the product of precipitation and temperature （Rain Temp）. The GWR model outperformed the two global models in both model fitting and prediction because it successfully reduced both spatial auto- correlation and heterogeneity in model residuals. More importantly, the GWR model provided localized model coefficients for each location in the study area, which allowed us to evaluate the influences of local stand conditions and topographic features on tree and stand growth, and forest carbon stock. It also helped us to better understand the impacts of silvi- cultural and management activities on the amount and changes of forest carbon storage across the province. The detailed information can be readily incorporated with the mapping ability of GIS software to provide excellent tools for assessing the distribution and dynamics of the for- est-carbon stock in the next few years.