Phylogeography of the pelagic fish Seriola lalandi at different scales: confirmation of inter-ocean population structure and evaluation of southern African genetic diversity

The study investigated the global and regional phylogeography of the yellowtail kingfish Seriola lalandi by examining genetic diversity and population genetic structure of this species at inter-and intra-ocean level and on a regional scale. DNA fragments of two mitochondrial genes, cytochrome b (Cytb) and cytochrome c oxidase subunit I (COI) and one nuclear gene, recombination activating gene 1 (RAG1), were sequenced to investigate the global-scale phylogeography of this species. The population genetic structure within the South Pacific, as well as along the South African coastline, was examined further using six microsatellite markers. Three distinct clades were identified for S. lalandi, which correspond with previously described subspecies of the North-East Pacific, North-West Pacific and the Southern Hemisphere. Within the latter, additional divergence was observed between the South Pacific and the South-East Atlantic regions. Divergence estimates were indicative of a Pacific origin for S. lalandi populations, because of Pleistocene vicariant events. Microsatellite analyses revealed overall significant genetic differentiation between South African and South Pacific samples. This corroborates recent findings on the global phylogeography of the species. No population differentiation was observed within South Africa, indicating high levels of gene flow.     

Tectono–Thermal Evolution, Hydrocarbon Filling and Accumulation Phases of the Hari Sag, in the Yingen–Ejinaqi Basin, Inner Mongolia, Northern China

This work restored the erosion thickness of the top surface of each Cretaceous formations penetrated by the typical well in the Hari sag, and simulated the subsidence burial history of this well with software BasinMod. It is firstly pointed out that the tectonic subsidence evolution of the Hari sag since the Cretaceous can be divided into four phases: initial subsidence phase, rapid subsidence phase,uplift and erosion phase, and stable slow subsidence phase. A detailed reconstruction of the tectonothermal evolution and hydrocarbon generation histories of typical well was undertaken using the EASY R_0% model, which is constrained by vitrinite reflectance(R_0) and homogenization temperatures of fluid inclusions. In the rapid subsidence phase, the peak period of hydrocarbon generation was reached at c.a.105.59 Ma with the increasing thermal evolution degree. A concomitant rapid increase in paleotemperatures occurred and reached a maximum geothermal gradient of about 43-45℃/km. The main hydrocarbon generation period ensued around 105.59-80.00 Ma and the greatest buried depth of the Hari sag was reached at c.a. 80.00 Ma, when the maximum paleo-temperature was over 180℃.Subsequently, the sag entered an uplift and erosion phase followed by a stable slow subsidence phase during which the temperature gradient, thermal evolution, and hydrocarbon generation decreased gradually. The hydrocarbon accumulation period was discussed based on homogenization temperatures of inclusions and it is believed that two periods of rapid hydrocarbon accumulation events occurred during the Cretaceous rapid subsidence phase. The first accumulation period observed in the Bayingebi Formation(K_1 b) occurred primarily around 105.59-103.50 Ma with temperatures of 125-150℃. The second accumulation period observed in the Suhongtu Formation(K_1 s) occurred primarily around84.00-80.00 Ma with temperatures of 120-130℃. The second is the major accumulation period, and the accumulation mainly occurred in the Late Cretaceous. The hydrocarbon accumulation process was comprehensively controlled by tectono-thermal evolution and hydrocarbon generation history. During the rapid subsidence phase, the paleo temperature and geothermal gradient increased rapidly and resulted in increasing thermal evolution extending into the peak period of hydrocarbon generation,which is the key reason for hydrocarbon filling and accumulation.     

小冰期时中国南方地区降水模式的差异研究

小冰期是过去一千年中全球气候变化的重要事件之一。关于小冰期时中国季风区和西风影响区气候变化的对比研究众多,但是缺乏中国南方地区降水模式时空差异的研究,难以了解中国南方地区降水变化规律。为了系统地了解小冰期时中国南方地区降水的复杂性,本文将中国南方地区划分为东南—华南沿海地区、中部地区以及西南地区三个区域,总共选取了19条高分辨率的古气候记录进行对比研究,主要有以下几点认识:(1)相对于中世纪暖期而言,小冰期期间中国南方东南—华南沿海地区的气候偏湿,这可能与雨带在中国南方的滞留时间延长和沿海地区受台风的影响增强有关。(2)中国中部地区秦岭南麓和神农架高山林区在小冰期时期主要呈"冷湿"的模式,差异在于秦岭南麓区域主要在小冰期中后期偏湿,这与中部其他区域偏"冷干"的模式不同。这种区域差异可能是由于地形地势和大气环流的复杂性导致。(3)中国西南地区受印度夏季风和东亚夏季风的共同影响,且该区域地形复杂,其气候变化在小冰期时期存在更加明显的空间差异,没有呈现出比较一致的降水模式。与小冰期期间的降水变化不同的是,近30年东南—华南沿海地区除了台湾和雷州半岛,其他区域降水明显减少,可能受气温和人类活动等因素的影响。通过结合高分辨率的古气候记录,我们系统分析了中国南方小冰期的干湿模式在时空上的差异及其可能的影响因子,这对于认识小冰期时中国南方不同区域降水的复杂性及未来旱涝灾害的防控具有一定意义。     

Unveiling buried aeolian landscapes: reconstructing a late Holocene dune environment using 3D ground-penetrating radar

Across the UK, sandy beaches and dunes protect coastal infrastructure from waves and extreme water levels during large-scale storms, while providing important habitats and recreational opportunities. Understanding their long-term evolution is vital in managing their condition in a changing climate. Recently, ground-penetrating radar (GPR) methods have grown in popularity in geomorphological applications, yielding centimetre-scale resolution images of near-surface stratigraphy and structure, thus allowing landscape evolution to be reconstructed. Additionally, abrupt changes in palaeo-environments can be visualized in three dimensions. Although often complemented by core data, GPR allows interpretations to be extended into areas with minimal ground-truth control. Nonetheless, GPR data interpretation can be non-intuitive and ambiguous, and radargrams may not initially resemble the expected subsurface geometry. Interpretation can be made yet more onerous when handling the large 3D data volumes that are facilitated with modern GPR technology. Here we describe the development of novel semi-automated GPR feature-extraction tools, based on ‘edge detection’ and ‘thresholding’ methods, which detect regions of increased GPR reflectivity which can be applied to aid in the reconstruction of a range Quaternary landscapes. Since reflectivity can be related to lithological and/or pore fluid changes, the 3D architecture of the palaeo-landscape can be reconstructed from the features extracted from a geophysical dataset. We present 500 MHz GPR data collected over a buried Holocene coastal dune system in North Wales, UK, now reclaimed for use as an airfield. Core data from the site, reaching a maximum depth 2 m, suggest rapid vertical changes from sand to silty-organic units, and GPR profiles suggest similar lateral complexity. By applying thresholding methods to GPR depth slices, these lateral complexities are effectively and automatically mapped. Furthermore, automatic extraction of the local reflection power yields a strong correlation with the depth variation of organic content, suggesting it is a cause of reflectivity contrast. GPR-interpolated analyses away from core control thus offer a powerful proxy for parameters derived from invasive core logging. The GPR data collected at Llanbedr airfield highlight a complex dune system to a depth of 2.8 m, probably deposited in several phases over ~700 years, similar to elsewhere in North Wales.     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.     

汕头市PM2.5的气象要素影响分析及预报研究

利用2014—2017年汕头市PM_2.5的日浓度资料、以及汕头市国家基准气象观测站的同期地面气象资料,重点分析了汕头市PM_2.5浓度的变化特征以及风、混合层厚度、降水等气象条件对PM_2.5浓度的影响,同时探讨了污染物浓度变化的成因。在此基础上,根据汕头市的气候特点,采用BP （Back-Propagation）人工神经网络方法针对汛期和非汛期分别建立了PM_2.5质量浓度预报模型。结果表明：与多数内陆城市不同,汕头市PM_2.5浓度日变化为单峰型,这与汕头地处沿海受海陆风影响有关;PM_2.5浓度日峰值出现在08时左右,除早高峰污染物排放增加的因素外,与早晨时段的低风速环境有关;PM_2.5日均浓度随着风速的增大呈现减小趋势,PM_2.5日均浓度与08时混合层厚度显著相关（相关系数为-0.143）;汕头市非汛期PM_2.5浓度比汛期高,这与汕头市的亚热带季风气候特征有关,汛期各量级降水（暴雨以上除外）对PM_2.5的清除效果无明显差别,而非汛期降水对PM_2.5浓度有明显清除作用;BP人工神经网络模型的预报效果表明,汛期和非汛期的PM_2.5级别命中率TS分别为100%和90.3%,准确指数分别为87.7%和89.9%,总体预报效果良好。不同时期预报模型出现正误差的数量和程度均大于负误差,汛期预报模型在有强降水发生时误差较大,而非汛期预报模型在有冷空气入侵时误差较大。     

Body motion in liquid under ice plate with snow cover

The motion of a submarine in liquid under an ice plate covered with flooded snow is considered. The ice is modelled as an elastic plate and the snow cover is modelled as a viscous layer on the top of the plate. The submarine is modelled as a slender solid of revolution with scale 1:300. The experimental and theoretical study of the influence of the viscous snow layer on deflections of the floating ice plate is conducted. The viscous layer reduces the amplitudes of flexural-gravity waves. The greatest influence of the viscous layer on the plate deflections is achieved for velocities of the submarine, where the waves of maximum amplitude are generated. Theoretical results are in good qualitative and quantitative agreement with the model experiments.     

Modelling of the passive turning of a turret moored vessel in conditions of compact ice

The concept of the offshore oil and gas field development using floating ship-shaped platforms, frequently named floating production units (FPU further), with turret mooring is widely used in the world, including regions with harsh environment. The direct transfer of this concept to the Arctic seas is not possible, mostly due to the difficulties of maintaining a weathervaning, or passive turning regime in heavy ice conditions. The main danger relates to the fact that the expected FPU rotation under the action of high ice loads can be accompanied by a translational displacement of the FPU away from the mooring point. As a result, the mooring system may reach an overloaded state until the FPU turns to a favourable position relative to the ice drift direction. In the paper, we are focused on the investigation of a mathematical model of the passive FPU turning on a spot under the assumption that the ice cover is described by a rigid-plastic continuum. The study is performed both analytically and by numerical simulations. A number of specific FPU motion patterns are analytically derived from the model in quasi-static approximation in the form of successive limit states of the system FPU – ice continuum. Some results of the corresponding numerical simulation are presented that confirm the existence of similar solutions in the full dynamic setting of the problem. A partial parametric analysis of the problem is also performed.     

A stochastic method for the prediction of icebreaker bow extreme stresses

It is well established that the ship-ice interaction process is quite complex and associated ice loads on the icebreaker hull is a stochastic process. Obviously, novel accurate statistical methods and models should be developed and applied to estimate extreme bow stresses.This paper studies icebreaker bow stresses based on measured distribution of ice thickness in the Arctic Ocean on the way to and from the North Pole. Since the vessel route was carefully selected searching for easier ice conditions, the Arctic Ocean crossing was not a straight linear but a meandering path. Thus, the specific ship route data was biased with respect to general ice statistics in the region, but true with respect to the route specific ice data encountered by a ship navigating in that region. Therefore the route specific ice thickness data is directly needed for ship design and navigation analysis. It is assumed that captains are competent and knowledgeable, and therefore will select a route that provides the most favourable ice conditions.This paper contributes to study of the newest Chinese self-designed polar icebreaker, serving the purpose of enhancing icebreaker operational reliability. Finite Element Method software package ANSYS/LS-DYNA has been employed to simulate bow stress pattern for a particular icebreaker operating in the Arctic Ocean. Extreme bow stresses were estimated using Naess-Gaidai method. The latter is a first application of Naess-Gaidai method to a distribution with lower bound. Thus this paper aims at introducing an efficient method of estimating route-specific icebreaker extreme bow stresses.     

海河流域近60 a降水极值的频率分析及时空分布特征

以海河流域为研究区域,利用MK和F检验对站点的年最大日降雨序列进行趋势、突变和跳跃分析。基于水文气象分区线性矩法进行一致区的划分、最优分布的选择和降水极值的频率估计值计算,并分析其空间分布特征。结果表明:MK趋势和突变检验显示只有8个站点(22.9%)呈现显著下降趋势,通过了信度为0.1的显著性水平检验,特别是京津唐区域具有显著的下降趋势,突变时段主要发生在1980-1990年。均值和方差的跳跃性显示大部分站点都呈现出显著的向下跳跃,主要分布在流域的滦河子流域和北三河水系;趋势和跳跃的综合分析能够对降水极值有可能引起的旱涝灾害进行更全面合理的判断。不同重现期下的频率估计值的空间分布总体趋势一致,从东南到西北、从沿海到内陆逐渐减少,并与地形表现出很好的一致性;降水极值空间分布的中心主要集中在滦河子流域的遵化和青龙附近;大部分站点50 a一遇的估计值和AMP序列的最大观测值能够保持较好的一致性,间接反映了估计值的合理准确性。