两类藻毒素聚酮合成酶遗传相似性及其二级结构预测分析

研究微囊藻毒素聚酮合成酶、节球藻毒素聚酮合成酶之间的遗传关联性,并对其二级结构进行预测分析.应用聚合酶链反应得到2株蓝绿藻的毒素聚酮合成酶(PKS)基因,并进行基因序列分析.从GenBank中提取产微囊藻毒素、产节球藻毒素藻株的相应基因序列,利用DNAStar和phylip软件分析目的基因一致性及2类藻毒素PKS的进化情况.采用Garnier-Robson法、Karplus-Schulz法预测项圈藻株202A1/35、节球藻株NSOR10PKS蛋白片段的二级结构,Kyte-doolittle法分析蛋白的亲水性,Emini法预测蛋白质的表面可能性.结果表明,2类藻毒素PKS目的基因的相似性非常高;项圈藻属、念珠藻属的微囊藻毒素PKS与节球藻毒素PKS的进化关系较近;2种藻毒素PKS分析片段二级结构具有较大的相似性,其亲水性与表面可能性区域等特征也极为相似.     

燃烧过程颗粒物的形成及我国燃烧源分析

燃料燃烧会排放一次颗粒物和二次颗粒物,一次颗粒物中亚微米粒子主要是由于无机矿物质经蒸发-成核-凝结-凝并的途径形成的;超微米颗粒的产生不同于亚微米颗粒的形成,是由于破碎机理.二次颗粒物是由气态前驱体在大气中转化而成的.我国燃烧源主要是煤燃烧、燃油机动车和农村生活燃料等.深入认识颗粒物的形成及燃烧源的特征对有效控制颗粒物的排放是很有帮助的.     

Forest resources and household welfare: Empirical evidence from North Central Vietnam

Using secondary data from a socio-economic quantitative household survey of the North Central region of Vietnam, the main aim of our study is to analyze the causal effect of forest resources on household income and poverty. Based on the observed characteristics of a forest-based livelihood and forest-related activities, we use a propensity score matching (PSM) method to control for potential bias arising from self-selection. The PSM results indicate that households with a forest-based livelihood had a higher level of income and lower poverty rates than did those without. Interestingly, our findings confirm that a forest-based livelihood offers much higher income than any other type of livelihood adopted by local households. Also, the poverty rate among households with a forest-based livelihood is lower than those earning non-labor income or engaged in wage/crop and crop livelihoods. Among households and provinces, we find varying opportunities deriving from forest resources, suggesting that there are potential barriers hindering local households from pursuing a forest livelihood or participating in some forest activities. Therefore, government policy and regulations on forest management should focus on improving the access of households to forest resources, while enhancing the sustainability of these resources.     

西南山地区域森林火险综合预报模型研究——以重庆市为例

森林火灾严重破坏森林生态系统的结构和功能,针对其风险预报开展研究具有重要的理论意义和应用价值。通过融合气象、地表覆盖和人类活动等要素的方式构建森林火险综合预报模型,是西南山地区域森林火险综合预报业务化应用的重要发展方向。基于《森林火险气象等级》国家标准(GB/T 36743-2018),本文研究首先构建了重庆市森林火险气象风险预报模型。然后通过融合可燃物因素和人为因素的方式,进一步构建重庆市森林火险综合预报模型。最后利用历史火点数据针对上述两类模型的精度进行对比和分析。研究结果表明:重庆市森林火灾发生次数较多,且呈现出季节性规律;重庆市森林火灾的发生不仅受到气象条件的影响,而且受到地表覆盖和人类活动等多种要素条件的共同影响;与森林火险气象风险预报结果相比,森林火险综合预报结果在空间分布上具有更高的精细程度;森林火险综合预报模型能有效提高森林火险等级预报精度。     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

A Simulation Study to Assess the Sensitivity of a Forest Health Monitoring Network to Outbreaks of Defoliating Insects

The sensitivity of the United States Forest Health Monitoring network to outbreaks of defoliating insects was examined by means of a simulation study. A model constructed specifically for the study was used to generate a wide variety of defoliation patterns in forested landscapes. Forest configuration was that of Minnesota, USA, as expressed by the GAP land cover classification. Combinations of model parameters were based on a Latin Hypercube sample. The relationship between the average number of plots defoliated and outbreak characteristics was then examined via multiple regression. Both theoretical and model results pointed to a strong, linear relationship between the average number of plots defoliated and outbreak size. Model results provided additional insight, suggesting a significant relationship between the average number of plots defoliated and other outbreak characteristics after outbreak size was taken into account.     

Evaluation of Carbon Uptake and Emissions by Forests in Korea During the Last Thirty Years (1973–2002)

The contribution of Korean forests to carbon sequestration for anthropogenic carbon emissions was evaluated. In addition, monitoring of carbon species released from forest fires was conducted. Despite a high carbon uptake by Korean forests, a tremendous increase in fossil fuel burning resulted in a small contribution by forests to carbon removal. The removal efficiency had a 5–31% range with an average of 12% during the period 1973–2002. In 2000, the amount of carbon released from burned trees corresponded to 1.6% of carbon uptake by forests. The distribution of surface CO concentration (ppb) derived from MOPITT (Measurement of Pollution in the Troposphere) showed high CO levels over the East/Japan Sea on April 10, 2000 when the largest forest fires occurred along the east coast of Korea. Trajectory analysis and ground CO measurements also indicated that CO levels over the East/Japan Sea were influenced by forest fires. This study suggests that continuous monitoring of carbon emissions from forest fires is needed for a more reliable estimate of carbon flux in the environment.     

基于随机森林的突发事件分级模型研究

突发事件的分级是快速响应和有效应对的基础,为了解决目前突发事件分级宽泛、主观性强和动态适应性弱等问题,将多分类器集成引入突发事件的分级过程中,借助随机森林组合分类器,针对突发事件特征,构建突发事件分级的随机森林模型,形成突发事件分级过程,进而对事前的应急预案制定、事中的应急资源配置和应急决策提供有力支撑;最后,以2014-2016年洪涝灾害突发事件为例检验构建的模型和过程。研究结果表明:与支持向量机方法相比,通过检验随机森林组合分类器分类结果准确率达到97.56%,在突发事件分级的应用上是可行的,进而可为突发事件的快速响应和应急决策提供信息支撑和参考依据。     

O3/BAF工艺系统中有机物生物降解数学模型

研究臭氧预氧化/曝气生物滤池（O₃/BAF）联合工艺深度处理实际城市污水二级出水过程中,后续BAF系统中有机物的生物降解数学模型。以有机底物浓度、填料层高度两个基本变量为控制条件,研究BAF的总体运行常数和填料特性常数,得出BAF有机物生物降解动力学方程为S_e/S₀=exp(－Kh/qSⁿ₀)。出水与进水COD浓度比值（S_e/S₀）的对数与反应器填料高度（h）之间可表达成一次函数关系。在不同的进水浓度（S₀）下,根据ln（S_e/S₀）~h和关系式m=K/qSⁿ₀,得到方程ln(q_m)=－nln(S₀)+lnK。BAF总体运行常数K和填料特性常数n分别为1.708和0.5063。该模型对BAF工艺有如下指导意义：可以根据设计流量、进水有机物浓度和出水浓度,初步确定BAF的尺寸（如横截面积、高度等）。     

Monitoring Regional Riparian Forest Cover Change Using Stratified Sampling and Multiresolution Imagery1

Claggett, Peter R., Judy A. Okay, and Stephen V. Stehman, 2010. Monitoring Regional Riparian Forest Cover Change Using Stratified Sampling and Multiresolution Imagery. Journal of the American Water Resources Association (JAWRA) 46(2):334-343. DOI: 10.1111/j.1752-1688.2010.00424.x Abstract: The Chesapeake Bay watershed encompasses 165,760 km² of land area with 464,098 km of rivers and streams. As part of the Chesapeake Bay restoration effort, state and federal partners have committed to restoring 26,000 miles (41,843 km) of riparian forest buffers. Monitoring trends in riparian forest buffers over large areas is necessary to evaluate the efficacy of these restoration efforts. A sampling approach for estimating change in riparian forest cover from 1993/1994 to 2005 was developed and implemented in Anne Arundel County, Maryland, to exemplify a method that could be applied throughout the Bay watershed. All stream reaches in the county were stratified using forest cover change derived from Landsat imagery. A stratified random sample of 219 reaches was selected and forest cover change within the riparian buffer of each sampled reach was interpreted from high-resolution aerial photography. The estimated footprint of gross change in riparian forest cover (i.e., the sum of gross gain and gross loss) for the county was 1.83% (SE = 0.22%). Stratified sampling taking advantage of a priori knowledge of locations of change proved to be a practical and efficient protocol for estimating riparian forest buffer change at the county scale and the protocol would readily extend to much broader scale monitoring.