Holocene permafrost history and cryostratigraphy in the High‐Arctic Adventdalen Valley,central Svalbard

This paper presents the history and cryostratigraphy of the upper permafrost in the High‐Arctic Adventdalen Valley, central Svalbard. Nineteen frozen sediment cores, up to 10.7 m long, obtained at five periglacial landforms, were analysed for cryostructures, ice, carbon and solute contents, and grain‐size distribution, and were ¹⁴C‐ and OSL‐dated. Spatial variability in ice and carbon contents is closely related to the sedimentary history and mode of permafrost aggradation. In the valley bottom, saline epigenetic permafrost with pore ice down to depths of 10.7 m depth formed in deltaic sediments since the mid‐Holocene; cryopegs were encountered below 6 m. In the top 1 to 5 m, syngenetic and quasi‐syngenetic permafrost with microlenticular, lenticular, suspended and organic‐matrix cryostructures developed due to loess and alluvial sedimentation since the colder late Holocene, which resulted in the burial of organic material. At the transition between deltaic sediments and loess, massive ice bodies occurred. A pingo developed where the deltaic sediments reached the surface. On hillslopes, suspended cryostructure on solifluction sheets indicates quasi‐syngenetic permafrost aggradation; lobes, in contrast, were ice‐poor. Suspended cryostructure in eluvial deposits reflects epigenetic or quasi‐syngenetic permafrost formation on a weathered bedrock plateau. Landform‐scale spatial variations in ground ice and carbon relate to variations in slope, sedimentation rate, moisture conditions and stratigraphy. Although the study reveals close links between Holocene landscape evolution and permafrost history, our results emphasize a large uncertainty in using terrain surface indicators to infer ground‐ice contents and upscale from core to landform scale in mountainous permafrost landscapes.     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

FEASIBLE STUDY ON THE INTEGRATION SYSTEM FOR THE SPACE MONITORING OF MAJOR EARTHQUAKES AND VOLCANOES IN TERRESTRIAL LAND

With the rapid development of space technology, earth observation technology and sky observatory technolo-gy, they have played a more and more important part in monitoring and predicting of earthquakes and volcanoes in the terres-trial land. In recent years, the related agencies have done the experiments and researches on monitoring and predicting ofearthquakes and volcanoes in the forewarning period by means of many approaches, such as satellite thermal infrared re-mote sensing (TIRS), Global Positioning System (GPS), differential interferometric synthesis aperture radar (D-INSAR),astronomical time-latitude residual anomaly, and Geographic Information Systems (GIS), etc. A quite large number of re-search foundation has been built in the fundamental theories and application methods. The experiments and researcheshave shown that these technology is efficient methods for high frequency crust movement. If the existed separate scientificforces and results are possibly assembled together to form a more complete integration monitoring system with the combina-tion of space, sky observation, ground, deep geology and macro anomaly, it will come into a new stage of monitoring andpredicting of earthquakes and volcanic eruptions.     

ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN

The ecological series of soil animals under the broad-leaved and pine mixed forest in Darlidai Mountainwas studied. Seven sample plots were selected according to different altitude gradients, which belong to different vegeta-tion types. By investigating and analyzing soil animals in every sample plot it is found that there are 45 groups and 1956individuals, which axe involved in 3 phylums, 7 classes, 16 orders, respectively. The altitude is a key factor which af-fects ecological series of soil animals. Both the groups and individuals of soil animals increase with altitude increasingunder certain conditions, which contrastes with ordinary cases, resulting from special micro-climate in studied area. Thegroups and individuls of soil animals are the most under the broad-leaved and pine forest on the top of the mountain, andthe least under Picea-Abies forest in the foot of the mountain.     

星风吸积引起的钡星重元素超丰

首先指出目前星风吸积模型中理论上的不自洽，考虑到δｒ≠０，重新推导轨道参量变化方程，消去了理论上的不自洽．提出一个新模型：首次将星风吸积同内禀ＡＧＢ星核合成模型结合起来计算钡（Ｂａ）星的重元素超丰，并将计算结果与观测值进行了比较．各参量按标准情况取值时，计算结果不太理想．取Ｂｏｎｄｉｈｏｙｌｅ吸积率的０．５倍或取较大的星风速率时，对于较长轨道周期（Ｐ＞１０００天）的Ｂａ星，计算结果与观测值基本符合；而较短轨道周期（Ｐ＜６００天）的Ｂａ星，其重元素超丰机制可能是盘吸积     

富氏谱分析法模拟地壳垂直运动的地学依据及其策应力模型

应用地壳波浪与镶嵌构造学说对富氏谱分析法提取地壳垂直形变信息的科学性做了地质学意义上的阐释 ,并提出了根据多期形变资料提取特定波段上构造策应力的数学模型     

Propagation of Alfvén waves in multi-layer solar atmosphere model

In this paper, we idealize the actual solar atmosphere as a multi-isothermal-layer system so as to obtain the energy transmittance of the linear Alfvén wave that propagates through such a system in presence of a uniform oblique magnetic filed. The results indicate that the two-layer model is essentially different to the three-layer one. In the two-layer model, the temperature jump acts as a high pass filter. In the three-layer model, resonant transfer will take place and the transmittance undergoes oscillation as the trigonometric function terms dominate its behavior. For actual solar atmosphere, the result reveals that the lower parts of solar atmosphere are more suitable for those Alfvén waves with period of seconds to transfer their energy.     

Optical Flash of GRB 990123: Constraints on the Physical Parameters of the Reverse Shock

The optical flash accompanying GRB 990123 is believed to be powered by the reverse shock of a thin shell. With the best-fit physical parameters for GRB 990123 and the assumption that the parameters in the optical flash are the same as in the afterglow, we show that: 1) the shell is thick rather than thin, and we have provided the light curve for the thick shell case which coincides with the observation; 2) the theoretical peak flux of the optical flash accounts for only 3×10~-4 of the observed. In order to remove this discrepancy, the physical parameters, the electron energy and magnetic ratios, εe and εB, should be 0.61 and 0.39, which are very different from their values for the late afterglow.     

Silicon limitation on primary production and its destiny in Jiaozhou Bay, China——Ⅳ：Study on cross-bay transect from estuary to ocean

The authors analyzed the data collected in the Ecological Station Jiaozhou Bay from May 1991 to November 1994, including 12 seasonal investigations, to determine the characteristics, dynamic cycles and variation trends of the silicate in the bay. The results indicated that the rivers around Jiaozhou Bay provided abundant supply of silicate to the bay. The silicate concentration there depended on river flow variation. The horizontal variation of silicate concentration on the transect showed that the silicate concentration decreased with distance from shorelines. The vertical variation of it showed that silicate sank and deposited on the sea bottom by phytoplankton uptake and death, and zooplankton excretion. In this way, silicon would endlessly be transferred from terrestrial sources to the sea bottom. The silicon took up by phytoplankton and by other biogeochemical processes led to insufficient silicon supply for phytoplankton growth. In this paper, a 2D dynamic model of river flow versus silicate concentration was established by which silicate concentrations of 0.028–0.062 μmol/L in seawater was yielded by inputting certain seasonal unit river flows (m³/s), or in other words, the silicate supply rate; and when the unit river flow was set to zero, meaning no river input, the silicate concentrations were between 0.05–0.69 μmol/L in the bay. In terms of the silicate supply rate, Jiaozhou Bay was divided into three parts. The division shows a given river flow could generate several different silicon levels in corresponding regions, so as to the silicon-limitation levels to the phytoplankton in these regions. Another dynamic model of river flow versus primary production was set up by which the phytoplankton primary production of 5.21–15.55 (mgC/m²·d)/(m³/s) were obtained in our case at unit river flow values via silicate concentration or primary production conversion rate. Similarly, the values of primary production of 121.98–195.33 (mgC/m²·d) were achieved at zero unit river flow condition. A primary production conversion rate reflects the sensitivity to silicon depletion so as to different phytoplankton primary production and silicon requirements by different phytoplankton assemblages in different marine areas. In addition, the authors differentiated two equations (Eqs. 1 and 2) in the models to obtain the river flow variation that determines the silicate concentration variation, and in turn, the variation of primary production. These results proved further that nutrient silicon is a limiting factor for phytoplankton growth. This study was funded by NSFC (No. 40036010), and the Director's Fund of the Beihai Sea Monitoring Center, the State Oceanic Administration.     

基于GIS的印度洋大眼金枪鱼延绳钓钓获率与水温关系的研究

采用GIS定性分析和数值分析的方法,研究了印度洋大眼金枪鱼延绳钓钓获率与水温的 关系。结果表明,大眼金枪鱼延绳钓高钓获率的出现与印度洋加权水温大面分布存在明显的相互 关系,大眼金枪鱼的渔获适温在14～17℃间。建议测量200m水深处的水温作为海上生产时的参 考。