民勤绿洲-荒漠过渡带典型固沙植物生殖物候对气候变化的响应

通过对民勤绿洲-荒漠过渡带典型固沙植物多枝柽柳(Tamarix ramosissima)、梭梭(Haloxylon ammodendron)、白刺(Nitraria tangutorum)1974-2009年开花及结实物候的观测,结合同步观测的气象资料,分析了3种植物生殖物候特征对气候变化的响应规律。结果表明:(1)研究区年平均气温、年平均空气相对湿度呈增加趋势; 年降雨量波动,变幅不大; 20世纪90年代以来蒸发量呈显著下降趋势。(2)3种植物始花期提前,花期延长; 3种植物结实始期先延迟后缩短,结实期延长; (3)3种植物生殖物候与年降雨量、气温、空气相对湿度及前期累计降雨量、累计平均气温、累计空气相对湿度之间的相关性不一致; (4)3种植物始花期与前期累计降雨量、累计平均气温、累计空气相对湿度的相关性总体上表现为大于年降雨量、年均气温、年均空气相对湿度的相关性; 除空气平均相对湿度对结实始期影响大于前期累计降雨量、累计平均气温和累计空气相对湿度外,其他与开花物候相似,表明植物开花物候和结实物候与前期气象因子有着密切的关系,尤其是物候发生前期累计气象指标。     

Compression behavior of MICP-treated sand with various gradations

Acta Geotechnica - One-dimensional compression tests on quartz sands treated by microbially induced carbonate precipitation (MICP) were carried out to evaluate the effects of gradation and calcium...     

基于CODE GIM的震前电离层TEC异常分析

利用CODE GIM数据分析了2008年5月12日汶川地震和2010年4月14日青海玉树地震震前电离层TEC变化。以震前10天TEC中位数为基准,1.5倍标准差为误差限值,并考虑相应时期的太阳和地磁活动水平（Dst指数和Kp指数）,对震前电离层异常的分布进行了分析。结果表明,两次地震震前几天内都有TEC异常出现。     

Long-Term Changes in the Extreme Significant Wave Heights on the Western North Pacific: Impacts of Tropical Cyclone Activity and ENSO

Seasonal extreme wave statistics were reproduced by using the 25-km-grid global wave model of WAVEWATCH-III. The results showed that the simulated wave dataset for the present climate (1979-2009) was similar to Climate Forecast System Reanalysis (CFSR) wave data. Statistics such as the root mean squared error (RMSE) and correlation coefficient (CC) over the western North Pacific (WNP) basin were 0.5 m and 0.69 over the analysis domain. The largest trends and standard deviation were around the southern coast of Japan and western edge of the WNP. Linear regression analysis was employed to identify the relationship between the leading principal components (PCs) of significant wave heights (SWHs) in the peak season of July to September and sea surface temperature (SST) anomalies in the equatorial Pacific. The results indicated that the inter-annual variability of SWH can be associated with the El Niño-Southern Oscillation in the peak season. The CC between the first PC of the SWH and anomalies in the Nino 3.4 SST index was also significant at a 99% confidence level. Significant variations in the SWH are affected by tropical cyclones (TCs) caused by increased SST anomalies. The genesis and development of simulated TCs can be important to the variation in SWHs for the WNP in the peak season. Therefore, we can project the variability of SWHs through TC activity based on changes in SST conditions for the equatorial Pacific in the future.     

Assessing Cryptic Invasion State: Fine-Scale Genetic Analysis of Ciona savignyi Population in Putative Native Habitat of the Korean Coast

The solitary ascidian, Ciona savignyi (Ascidiacea, Enterogona) is a notorious marine invader still expanding its habitat range worldwide. This species is considered native to the North West Pacific, but its indigeneity in Korean coastal waters has been questioned because of outdated taxonomic records and its inhabitation of oceanographically marginal areas. To clarify their cryptic invasion state, 247 individual C. savignyi samples were collected from 12 harbors and marinas on the Korean coast, and a 744 bp region of mitochondrial DNA (mtDNA) cytochrome c oxidase subunit I gene was sequenced and analyzed. Our analyses of population genetic structure and demographic history provided considerable pieces of evidence supporting their long-term establishment on the Korean coasts: differentiated population genetic structure, sequentially arrayed star-shape haplotype network, neutrality test results of past population expansions, and post-glacial colonization pattern of demography. Consequently, we concluded that C. savignyi populations on the Korean Coast are indigenous rather than exotic. These results could be used as reference data for further phylogeo graphic and demographic studies of problematic Ciona species, and to clarify and resolve similar cryptic invasion states of the other Korean coastal marine organisms. This study is the first to resolve the cryptic in vasion state of Korean marine organisms using genetic analysis.

     

中国城市群热岛效应时空演变及其影响因素分析

基于长期不透水面和MODIS地表温度数据,分析2000—2015年中国城市群扩张及热岛效应时空演变,进而综合采用冗余分析(RDA)、线性回归分析和变异分配分析(VPA)等方法,揭示城市群城市热岛效应的驱动机制。结果表明：城市群内建成区面积快速扩张,不透水面比例从2000年2.08%增长到2015年5.33%,且主要集中于珠江三角洲等沿海城市群;2000—2015年,夏季热岛分布较广,且白天强度高于夜晚。东部以及大部分北部城市群如哈长城市群等,降温强度较大,但其夜晚热岛效应在不同程度增强。冬季夜晚比白天热岛分布广、强度高,北方、西北、东部等地区夜晚热岛效应也在增强;自然环境因素显著影响城市群热岛强度,降水对夏季夜晚热岛强度起显著负贡献(22%),纬度越高,冬季夜晚热岛强度也越高。人为因素显著影响夜晚热岛分布和城市群内热岛强度的平衡,城市植被覆盖显著减少夜晚城市群内热岛分布,灯光强度对夏季夜晚热岛强度起显著负贡献(24%),对热岛比例起显著正贡献(27%),人口密度对夏季夜晚热岛强度起显著负贡献(31%);自然环境因素对热岛强度的贡献占主导,而人为干扰因素对热岛比例的贡献占主导。     

海洋环境因子对澳洲鲐亲体补充量关系的影响——基于贝叶斯模型平均法的研究

澳洲鲐（Scomber australasicus）是西北太平洋重要的中上层经济鱼类,生命周期相对较短,资源量受补充量影响明显,了解澳洲鲐太平洋群系补充量状况对掌握其资源量及确保其可持续利用具有重要的意义。本文利用产卵场1（30°~32°N,130°~132°E）海表面温度（sea surface temperature,SST1）、产卵场2（34°~35°N,138°~141°E）海表面温度（SST2）、索饵场（35°~45°N,140°~160°E）海表面温度（SST3）、潮位差（tidal range,TR）、太平洋年代际涛动（Pacific decadal oscillation,PDO）和亲体量（spawning stock biomass,SSB）6个影响因子任意组合与补充量构建多个模型,运用贝叶斯模型平均法（Bayesian model averaging,BMA）分析各个环境因子对资源补充量的解释能力,并预测其补充量的变化。结果表明,SSB对补充量具有最长期且稳定的解释能力,其次是SST3,PDO、TR、SST2、SST1也对补充量模型具有一定的解释能力。SST3是环境因子中影响最大的因子,可能是由于补充群体在索饵场内生活时间较长,索饵场温度对仔鱼或鱼卵的生长存活有较大的影响。研究认为,基于BMA的组合预报综合考虑了各个模型的优势,优于单一模型,可用于澳洲鲐资源补充量的预测。     

Modelling combined open channel flow by artificial neural networks

Combined open channel flow is encountered in many hydraulic engineering structures and processes, such as irrigation ditches and wastewater treatment facilities. Extensive experimental studies have conducted to investigate combined flow characteristics. Nevertheless, there is no simple relationship that can fully describe the velocity profiles in a turbulent flow. The artificial neural network (ANN) has great computational capability for solving various complex problems, such as function approximation. The main objective of this study is to evaluate the applicability of the ANN for simulating velocity profiles, velocity contours and estimating the discharges accordingly. The velocity profiles measured by an acoustic doppler velocimeter in the open channel of the Chihtan purification plant, Taipei, with different discharges at fixed measuring section and different depths are presented. The total number of data sets is 640 and the data sets are split into two subsets, i.e. training and validation sets. The backpropagation algorithm is used to construct the neural network. The results demonstrate that the velocity profiles can be modelled by the ANN, and the ANN constructed can nicely fit the velocity profiles and can precisely predict the discharges for the conditions investigated. Copyright © 2005 John Wiley & Sons, Ltd.     

On the Power Distribution of Solar p MODES

We present a simple idealized model of stochastically forced solar oscillations, and compare the distribution function of energy, averaged over 12-hour intervals, with that of low-degree solar modes. We find that the simulated energy distribution is similar to the observations, except at extremely high energy.