Climatic and genetic controls of yields of switchgrass, a model bioenergy species

The U.S. Renewable Fuel Standard calls for 136 billion liters of renewable fuels production by 2022. Switchgrass (Panicum virgatum L.) has emerged as a leading candidate to be developed as a bioenergy feedstock. To reach biofuel production goals in a sustainable manner, more information is needed to characterize potential production rates of switchgrass. We used switchgrass yield data and general additive models (GAMs) to model lowland and upland switchgrass yield as nonlinear functions of climate and environmental variables. We used the GAMs and a 39-year climate dataset to assess the spatio-temporal variability in switchgrass yield due to climate variables alone. Variables associated with fertilizer application, genetics, precipitation, and management practices were the most important for explaining variability in switchgrass yield. The relationship of switchgrass yield with climate variables was different for upland than lowland cultivars. The spatio-temporal analysis showed that considerable variability in switchgrass yields can occur due to climate variables alone. The highest switchgrass yields with the lowest variability occurred primarily in the Corn Belt region, suggesting that prime cropland regions are the best suited for a constant and high switchgrass biomass yield. Given that much lignocellulosic feedstock production will likely occur in regions with less suitable climates for agriculture, interannual variability in yields should be expected and incorporated into operational planning.     

SYNTHESIS OF FLOW-DURATION CURVES FOR UNREGULATED STREAMS IN NEW HAMPSHIRE1

ABSTRACT: Flow-duration curves are concise pictures of flow variability at a point on a stream, and provide essential information for all water-resource planning. In New Hampshire, useful estimates of flow-duration curves for ungaged points on unregulated streams can be made using only information readily available from contour maps: 1) area of the basin above the point of interest; and 2) either the measured mean basin elevation or the elevations of the highest and lowest points in the basin. Measured or estimated mean basin elevation is then used in regression equations to estimate mean flow QC and the flow exceeded 95% of the time, Q₉₅. QC is assumed to occur at the 27% exceedance frequency. Q₀₂, Q₀₅, and Q₃₀ are estimated as multiples of QC. Equations are provided for calculating 95% confidence intervals for future estimates using the method. The dependence of mean flow on elevation is due to positive vertical precipitation gradients and negative vertical evapotranspiration gradients. The dependence of Q₉₅ on elevation appears to be due largely to the fact that it rains more often, that snowmelt takes longer, and that evapotranspiration is reduced at higher elevations.     

水环境模拟中多孔介质场空间变异性研究方法述评

阐述了研究多孔介质空间变异性的经典统计法、地质统计学方法以及新兴的分形方法.经典统计方法由于不考虑研究对象的空间相关性,已经不能对这种变异性做出客观的分析;地质统计学方法很好地克服了经典统计学的缺点,是目前应用最多的一种方法;分形的研究对象为无规则和具有自相似性的体系,这一特性决定了它研究这种变异性有着独特的优点.最后对多孔介质空间变异性研究的趋势进行了展望.     

Deriving heart rate variability indices from cardiac monitoring—An indicator of driver sleepiness

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time.

Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5?min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform; (2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student’s t test.

Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations.

Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection.     

广东省雾霾天气能见度的时空特征分析Ⅰ:季节变化

雾霾已经成为一种新的气象及环境灾害性现象,分析雾霾天气下低能见度的时空分布特征,对掌握雾霾的发生规律和减灾预报具有重要意义。文章利用1980—2003年广东省沿海地区26个地面气象观测站23年的气象观测资料,分析了广东省雾霾天气下能见度的时空分布特征。分析结果发现,1980—2003年广东地区雾霾天气下能见度的季节变化规律与雾天气时能见度的季节变化规律大体一致,即广东地区低能见度天气主要受雾天气的影响;另一方面,雾、霾天气时能见度的季节变化规律有很大不同,雾天气时能见度观测值在冬、春两季相对较高,最低值出现在3月份,最高值出现在9月份,其年变化表现为峰—谷型、稳定型和不规则波动型三种变化;霾天气时能见度的值在秋、冬两季相对较高,最低值出现在6月份,而且在5、6、7三个月中能见度值都很低;受广东沿海地形特征影响,雾天能见度的空间分布从西到东呈低—高—低—高的波列状分布,而霾天气时能见度的空间分布则没有明显的区域差异。     

地统计学在土壤重金属研究中的应用及展望

从采矿学与地质学研究中发展起来的地统计学是应用数理统计学的一个分支。与传统的统计学相比，地统计学可应用于土壤重金属研究中，能探索土壤重金属的空间分布特征及其变异规律。地统计学的基础理论与方法主要包括：区域化变量、半方差函数、克立格空间插值技术。半方差函数可以用来描述研究土壤重金属分布的空间相关性；而克立格插值可以对未采样区土壤重金属的含量进行无偏最优估计。在对地统计学理论进行简要阐述的基础上，回顾了近些年在土壤重金属研究的采样设计、空间结构分析、空间插值等方面的应用，并就其应用前景作了展望。     

A genetic component to size in queens of the ant,<Emphasis Type="Italic"> Formica truncorum</Emphasis>

The genetic basis of morphological traits in social insects remains largely unexplored. This is even true for individual body size, a key life-history trait. In the social insects, the size of reproductive individuals affects dispersal decisions, so that small size in queens is often associated with reduced dispersal, and large size with long-range dispersal and independent colony founding. Worker size is connected to division of labour when workers specialize in certain tasks according to their size. In many species, variation in worker size has been shown to increase colony performance. In this study, we present the first evidence of an additive genetic component to queen size in ants, using maternal half sib analysis. We also compared intra-colony size variation in colonies with high (queen doubly mated) versus low (queen singly mated) genetic variability. We found a high and significant heritability (h²=0.51) for queen size in one of the two study years, but not in the other. Size variation among queens was greater in colonies headed by a doubly mated queen in one of the study years, but not in the other. This indicates that genetic factors can influence queen size, but that environmental factors may override these under some circumstances. The heritability for worker size was low (h²=0.09) and non-significant. Increased genetic diversity did not increase worker size variation in the colonies. Worker size appeared largely environmentally determined, potentially allowing colonies to adjust worker size ratios to current conditions.Communicated by J. Heinze     

Intra- and inter- laboratory variability in paper industry PCDD/PCDF analysis

Studies were conducted to quantify variability for pulp industry wastewater effluent, pulp and sludge analyses. Intralaboratory variability studies indicated that there is a potential for greater between batch variability in results than for within a batch. Intralaboratory relative standard deviations for replicate analyses ranged from 6% to 60%. Interlaboratory studies, using standard reference materials showed relative standard deviations from 4% to 135%. There appeared to be little dependance of variability on concentration, suggesting matrix effects were very important. In general, effluent variability was greater than observed for pulps or sludges. Analysis of reference standards indicated that 13% to 17% variability can be attributed to differences in calibration standards. A limited study of full congener PCDD/PCDF analysis variability showed it to be greater than observed for TCDD/TCDF.     

长三角地区2015年大气重污染特征及其影响因素

基于2015年长三角地区129个环境空气质量监测站的空气质量指数（AQI）及主要大气污染物浓度数据,结合气象资料和HYSPLIT后向轨迹模式,探究长三角地区大气重污染的时间变化和空间集聚特征,并深入分析气象条件和区域传输对重污染过程发生和维持的影响.结果表明,2015年长三角地区各城市平均出现AQI超过200的重污染天气共8 d,重污染频率为2.01%,PM_2.5作为首要污染物出现频次最多.从时间变化看,重污染主要分布在1月和12月;从空间分布看,北部地区重污染相比南部地区更为严重,徐州和常州市出现频率最高.选取典型重污染过程1月9—11日（纬向扩散型）、1月24—26日（经向扩散型）和12月20—26日（两种模式相结合的重污染天气）进行成因分析,发现长三角地区重污染天气主要受到西北风向、低风速、高湿度和逆温层的影响,导致大气污染物积累且不易扩散.基于HYSPLIT的大气传输轨迹及频率分布表明,来自西北方向的气流对江苏北部地区的污染输送特征有着显著影响.     

南方丘陵山区典型地物景观特征尺度研究

景观的特征尺度反映了人与自然交互作用的空间过程,合理识别景观空间结构及其特征尺度有助于遥感影像景观空间异质性分析。论文以地处南方丘陵山区的福建省福州市为研究区,针对城市、农田、森林与水域4种地物景观,基于SPOT 10 m影像,分别利用半方差分析、小波分析与平均局部方差方法,开展景观特征尺度研究。结果表明:①不同景观类型的空间异质性差异较大,其中森林景观空间异质性最大,其次为城市、农田景观,水域的空间异质性最小;②小波方差分析和半方差分析分别检测到两个不同的特征尺度,而局部方差仅仅检测到较小的空间结构;③森林景观特征尺度比通常偏小,与南方丘陵山区破碎地形有关,城市景观更多体现为人类活动的影响,南方丘陵山区城市景观至少具有两种不同的空间结构,其特征尺度均较小,农田景观特征尺度最大。基于小波分析与半方差各自的特点,总结提炼出综合两种方法合理识别景观特征尺度的基本流程,即:首先开展小波分析,然后在此基础上利用半方差分析多种理论模型组合从而获得更详细的特征尺度信息,模型组合个数与参数初始值依据小波分析的结果而定。