甾醇对南山老龙洞地下河粪便污染的指示

分别于2014年10月,2015年1、3、5月采集重庆南山老龙洞地下河出口的水样,过滤取水悬浮物质,采用气相色谱-质谱联用仪(GC-MS)定量分析悬浮物中甾类物质的成分与质量浓度;利用多指标综合分析对南山老龙洞地下河粪便污染进行判断并追溯粪便污染物的主要来源.结果表明,样品中共测出10种甾类物质,其中包括9种醇类和1种酮类.总甾类物质的质量浓度为1 573~5 007 ng·L-1,且3、5月均大于10、1月.虽然各月间地下河的组成存在差异,但以胆固醇、β-谷甾醇和粪醇为主要成分,三者的质量浓度之和占总甾类的50.8%~80.4%.另外,(差向异构粪醇+粪醇)/(粪醇+差向异构粪醇+二氢胆固醇)的值均大于0.7,指示各月均受到粪便污染;10月差向异构粪醇/粪醇的值小于0.2,指示污水主要来自上游污水处理厂;1、3、5月的粪醇/ΣSteroids、粪醇/24-乙基粪醇的值分别为0.109~0.254、6.3~10.3,指示地下河主要受到人类粪便的影响;3月的24-乙基粪醇/24-乙基胆甾烷醇为0.86,小于1月的5.4和5月的2.3,说明该月地下河受家禽类动物粪便的影响较1月和5月严重.     

典型岩溶区地下河中溶解态脂类生物标志物来源解析及其变化特征

利用气相色谱-质谱联用仪(GC-MS)测定了青木关地下河中溶解态类脂物的含量.研究了其在地下河中的来源、组成及迁移特征.结果表明,7~11月,各溶解态类脂物的平均含量随着青木关地下河运移距离的增加呈降低趋势,其中以溶解态饱和直链脂肪酸的下降最为显著,即由最初的5 704 ng·L~(-1)下降到1 043 ng·L~(-1),减少了约81.71%.正构烷烃能够较为详尽地指征地下河中溶解性有机质来源,而饱和直链脂肪酸、脂肪醇则对藻类和细菌等微生物有较好的指示意义.随着地下河运移距离增加,有机质输入类型呈现多样化,可能与岩溶地表不均一性有关.正构烷烃三端元图解中,水生植物的输入为地下河中溶解性有机质的主要来源,其次分别为陆地高等植物和藻类、细菌等微生物,但随着地下河运移距离的增加水生植物的相对贡献量逐渐减少.青木关地下河中正构烷烃TAR值对降雨有一定的指示意义,而饱和直链脂肪酸CPI、L/H值则指示细菌降解活动.     

太湖流域上游平原河网污染物综合衰减系数的测定

改善太湖水质需要削减上游河流进入太湖的污染物总量.为了探求太湖流域上游平原河网的自净能力,开展原位实验测定了枯水期高锰酸盐指数、氨氮(NH_4~+-N)、总氮(TN)和总磷(TP)的综合衰减系数,根据河道的水力特征对综合衰减系数进行了修正,并利用一维稳态水质模型对修正前后综合衰减系数的可靠性进行了验证.结果表明,高锰酸盐指数、NH_4~+-N、TN和TP的综合衰减系数分别为:0.0296~0.4106、0.0224~0.3564、0.0137~0.3046和0.0555~0.5725 d~(-1).可靠性验证表明高锰酸盐指数、NH_4~+-N、TN和TP综合衰减系数修正前的平均相对误差分别为8.39%、14.40%、11.43%和19.22%,修正后的平均相对误差分别为10.65%、14.34%、11.37%和19.24%.修正前后高锰酸盐指数、NH_4~+-N、TN和TP的平均相对误差均小于20%且变化不显著,表明综合衰减系数的测定结果能够为太湖流域上游平原河网的污染物总量控制管理提供科学参数;也表明枯水期的水力条件对综合衰减系数的影响较小.     

波流式生态滤床氨氮去除效果及其微生物群落结构分析

利用波流式生态滤床处理受污染的河水,考察了其对氨氮的去除效果和沿程污染物转化情况,并采用扫描电镜、高通量测序手段解析了波流式生态滤床不同时间和位置基质上生物膜的细菌群落组成,分析了波流式生态滤床小试反应器中硝化细菌和反硝化细菌的分布特点,以探讨其去除氨氮的机理.结果表明,反应器稳定运行以后,对氨氮平均去除率为74.83%,基质表面可以观察到大量微生物,不同时期优势细菌有较大不同.反应器前部主要发挥硝化作用,中部发挥反硝化作用,硝化菌的分布呈现上多下少、前多后少的特点,使得氨氮在前端被快速去除;中部以黄杆菌属(Flavobacterium)为代表的反硝化菌丰度较高,促进了反硝化作用的发挥,降低了出水中总氮浓度;不同部位样品中细菌多样性差别不大,微生物种群多样性随着水流方向呈现先增加,到后段减少的趋势.     

Backwater Confluences of the Ohio River: Organic and Inorganic Fingerprints Explain Sediment Dynamics in Wetlands and Marinas

In the Ohio River (OR), backwater confluence sedimentation dynamics are understudied, however, these river features are expected to be influential on the system’s ecological and economic function when integrated along the river’s length. In the following paper, we test the efficacy of organic and inorganic tracers for sediment fingerprinting in backwater confluences; we use fingerprinting results to evidence sediment dynamics controlling deposition patterns in confluences used for wetland and marina functions; and we quantify the spatial extent of tributary drainages with wetland and marina features in OR confluences. Both organic and inorganic tracers statistically differentiate sediment from stream and river end‐members. Carbon and nitrogen stable isotopes produce greater uncertainty in fingerprinting results than inorganic elemental tracers. Uncertainty analysis of the nonconservative tracer term in the organic matter fingerprinting application estimates an apparent enrichment of the carbon stable isotopes during instream residence, and the nonconservativeness is quantified with a statistical approach unique to the fingerprinting literature. Wetland and marina features in OR confluences impact 42% and 11% of tributary drainage areas, respectively. Sediment dynamics show wetland and marina confluences experience deposition from river backwaters with longitudinally linear and nonlinear patterns, respectively, from sediment sources.     

关于城市河流水污染防治技术应用和研究

随着我国经济的不断发展,各种工厂也大量的成立,而这也使得很多废弃物及废水被过度排放到湖泊与河流之中,进而导致其出现了严重的污染问题。污染不仅对人们的生活质量产生了影响,同时也对生态的平衡发展产生了很大的阻碍,业已经成为社会各界高度关注和重视的问题。基于此,本文围绕城市河流水污染的现状进行了分析,对于污染产生的原因也进行了阐述,针对城市河流水污染防治技术的应用也进行了探讨和研究,以期可以有效解决我国出现的河流水污染问题,进而为人们及社会营造一个全新、绿色的河流环境。     

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.