Challenges of deep-sea biodiversity assessments in the Southern Ocean

Despite recent progress in deep-sea biodiversity assessments in the Southern Ocean （SO）, there remain gaps in our knowledge that hamper efficient deep-sea monitoring in times of rapid climate change. These include geographical sampling bias, depth and size-dependent faunal gaps in biology, ecology, distribution, and phylogeography, and the evolution of SO species. The phenomena of species patchiness and rarity are still not well understood, possibly because of our limited understanding of physiological adaptations and thresholds. Even though some shallow water species have been investigated physiologically, community-scale studies on the effects of multiple stressors related to ongoing environmental change, including temperature rise, ocean acidification, and shifts in deposition of phytoplankton, are completely unknown for deep-sea organisms. Thus, the establishment of long-term and coordinated monitoring programs, such as those rapidly growing under the umbrella of the Southern Ocean Observing System （SOOS） or the Deep Ocean Observing Strategy （DOOS）, may represent unique tools for measuring the status and trends of deep-sea and SO ecosystems.     

On the variation of frequency-based rainfall amounts: a case study for evaluating recent extreme rainfalls in Korea

Extreme rainfall events recently occurring in Korea have been shown to change frequency-based rainfall amounts quite significantly. Regardless of the reason for these extremes, the general concern of most hydrologists is how to handle these events for practical applications in Hydrology. Our study aim is to evaluate these extremes with their effect on frequency-based rainfall amounts, especially if they can be assumed to be within normal levels. As there is no commonly accepted methodology to be applied to this kind of study, we follow simplified steps such as: (1) estimation of the climatological variance of frequency-based rainfall amounts, (2) estimation of confidence intervals of frequency-based rainfall amounts (lower and upper bounds for the 5 and 1% significance levels estimated using the climatological variance), and (3) evaluation of the effect of extra rainfall events on the frequency-based rainfall amounts. Twelve stations on the Korean peninsula are selected as they have relatively longer data length. The annual maximum rainfall data collected from 1954 to 1998 are used. From this study we concluded that (1) at least 30 years of data length should be used for the frequency analysis in order to assure the stability of the variance of frequency-based rainfall amounts, (2) the climatological variances estimated all range from 5 to 8% of the frequency-based rainfall amounts, and (3) even though the frequency-based rainfall amount seems to become extreme with seemingly abnormal events, it still remains under its upper bound for the 5 or 1% significance levels estimated using the climatological variance, as well as it decays exponentially to the normal level as extra events are added. Thus, we conclude that we do not need to panic over seemingly abnormal events occurring so far, but just need to consider the variability inherent in frequency-based rainfall amounts.     

Estimation of background levels of contaminants

Samples from hazardous waste site investigations frequently come from two or more statistical populations. Assessment of background levels of contaminants can be a significant problem. This problem is being investigated at the U.S. Environmental Protection Agency's Environmental Monitoring Systems Laboratory in Las Vegas. This paper describes a statistical approach for assessing background levels from a dataset. The elevated values that may be associated with a plume or contaminated area of the site are separated from lower values that are assumed to represent background levels. It would be desirable to separate the two populations either spatially by Kriging the data or chronologically by a time series analysis, provided an adequate number of samples were properly collected in space and/or time. Unfortunately, quite often the data are too few in number or too improperly designed to support either spatial or time series analysis. Regulations typically call for nothing more than the mean and standard deviation of the background distribution. This paper provides a robust probabilistic approach for gaining this information from poorly collected data that are not suitable for above-mentioned alternative approaches. We assume that the site has some areas unaffected by the industrial activity, and that a subset of the given sample is from this clean part of the site. We can think of this multivariate data set as coming from two or more populations: the background population, and the contaminated populations (with varying degrees of contamination). Using robust M-estimators, we develop a procedure to classify the sample into component populations. We derive robust simultaneous confidence ellipsoids to establish background contamination levels. Some simulated as well as real examples from Superfund site investigations are included to illustrate these procedures. The method presented here is quite general and is suitable for many geological and biological applications.     

Implications of Habitat Fragmentation on Climate Change-Induced Forest Migration

A rapid warming caused by the release of greenhouse gases could result in the displacement of climatic controls that limit the current ranges of many species. Projected northward displacement for loblolly pine is over 400 km, with only a narrow region of overlap between the current and projected future range limits. A model of dispersal developed for loblolly pine is presented. The model utilizes a GIS to assess the critical influence of land use patterns on climate change-induced migration through modern landscapes. Results from two relatively large (150 × 150 km) study areas in the eastern United States suggest that potential migration rates may fall short by at least an order of magnitude of that necessary to track projected range shifts. Management options of species transplanting and the establishment of greenways are explored with the model. Species that are unable to keep pace with changing range limits may experience a reduction in population size and exist in climatic disequilibrium.     

钢筋混凝土梁抗震性能指标分析

采用软件ABAQUS对钢筋混凝土梁进行有限元模拟,即可获取梁的荷载-位移骨架曲线。将试验结果和模拟结果进行对比,结果表明,有限元可以较准确地模拟试验情况。然后同样采用软件ABAQUS来模拟146根梁,并获取该批梁的弯矩-转角骨架曲线。将曲线按照不同因素进行分类,并由这些曲线得出梁的性能参数:塑性转角限值。塑性转角限值能为梁的性能评估提供定量的参考指标。     

山地森林群落物种多样性垂直格局研究进展

山地森林群落物种多样性垂直格局研究是揭示植被地带性分布式样的重要手段,其研究内容主要包括山地森林群落物种多样性的垂直变化模式、山地森林群落物种多样性垂直带谱和山地森林群落物种多样性及其环境解释等。目前对于山地森林群落物种多样性沿海拔梯度的格局变化模式尚无统一认识,但大致可概括为5类变化模式。垂直带谱研究从最初的单因子单目标已逐步过渡到单因子多目标,最后到多因子多目标。研究深度也从根据样地资料的简单描述和分析,发展为山地森林群落物种多样性机理假说的提出与证实,尚未见有关山地森林群落物种多样性垂直格局机理的报道。山地森林群落物种多样性垂直格局研究方法可分为取样方法和测度方法两大类。常用的取样方法有梯度格局法（或连续样带取样法）和典型群落随机取样法,其中最小取样面积的确定尤为关键。就山地森林群落物种多样性垂直格局测度和分析而言,物种多样性指数的测度和单元统计分析（回归、假设检验、方差分析、相关分析等）较为常见,随着分析手段的不断创新,植被数量分类和排序等多元统计学分析方法得到了日益广泛的应用。     

Temporal variability of dimethylsulfide and dimethylsulfoniopropionate in the Sargasso Sea

Vertical profiles of dimethylsulfide (DMS) and β-dimethylsulfoniopropionate, particulate (pDMSP) and dissolved (dDMSP), were measured biweekly in the upper 140 m of the Sargasso Sea (32°10′N, 64°30′W) during 1992 and 1993. DMS and pDMSP showed strong, but different, seasonal patterns; no distinct intra-annual pattern was observed for dDMSP. During winter, concentrations of DMS were generally less than 1 nmol l⁻¹ at all depths, dDMSP was less than 3 nmol l⁻¹ and pDMSP was less than 8 nmol l⁻¹. In spring, concentrations of both dDMSP and pDMSP rose, on a few occasions up to 20 nmol l⁻¹ in the dissolved pool and up to 27 nmol l⁻¹ in the particulate pool. These increases, due to blooms of DMSP-containing phytoplankton, resulted in only minor increases in DMS concentrations (up to 4 nmol l⁻¹). Throughout the summer, the concentrations of DMS continued to increase, reaching a maximum in August of 12 nmol l⁻¹ (at 30 m depth). There was no concomitant summer increase in dDMSP or pDMSP. The differences among the seasonal patterns of DMS, dDMSP, and pDMSP suggest that the physical and biological processes involved in the cycling of DMS change with the seasons. There is a correlation between the concentration of DMS and temperature in this data set, as required by some of the climate feedback models that have been suggested for DMS. A full understanding of the underlying processes controlling DMS is required to determine if the temperature-DMS pattern is of significance in the context of global climate change.     

Relation water content ratio-to-liquidity index versus the Atterberg limits ratio evaluated with the Kaniadakis exponential law

Water content ratio (WCR) is defined as the ratio water content to liquid limit (LL) and it is proved to be a good replacer of the well-known parameter liquidity index (LI) to predict shear strength of fine-grained soils. An interesting correlation between the slope of LI and WCR and LL/PL ratio was observed. However, this trend is poorly described by conventional regression functions. By employing the Kaniadakis exponential law based on the relativistic mechanics, 22 data set, considering the LL/PL vs the slope of LI and WCR, were very-well matched.     

中国山地垂直带信息系统的设计与开发

本文收集了大量翔实的山地垂直带资料,建立了我国山地垂直带数据库,创建了山地垂直带谱"数字引擎".使垂直带谱数字化成为可能。采用ArcObject组件开发技术及Visual Basic,自主开发中国山地垂直带信息系统(1.0)。该系统是一个面向对象(山地垂直带谱)的地理信息系统;以山地垂直带"数字引擎"为系统内核,在功能上实现了山地垂直带分布与地理空间区域的联接,同时实现了大范围内选择多个区域进行数据分析的功能。系统界面友好,易操作,显示直观、明了,为自然地理和生态学家者提供了一个比较丰富的山地垂直带谱数据集和有效的分析工具。标志着山地垂直带谱研究进入了数字时代。     

苏里格气田致密砂岩储层物性下限值的研究

苏里格气田东区盒8层段属致密砂岩层,具有低孔低渗的特点。采用经验统计法、孔隙度—渗透率交会法、岩芯饱和度分析法、最小孔喉半径法、有效孔隙百分含量法、相渗分析法和试气法等7种方法综合分析,确定了苏东地区盒8层段孔隙度和渗透率下限值分别为4.7%和0.08×10-3μm2,并运用试气结论和试气产量证明了储层物性下限值的合理性。