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1.
Macrophyte community diversity and composition respond to ecosystem conservation and local environmental factors. In this study, we developed a multidimensional diversity framework for macrophyte communities, including the taxonomic and functional alpha and beta diversity. We used the framework to explore the relationships among water level regimes and these diversity parameters in a case study of China's Baiyangdian Lake. Analysis of indicators of hydrologic alteration divided the water level from 1959 to 2019 into four regimes (dry, <6.42 m; low, 6.42–7.23 m; medium, 7.23–8.19 m; high, >8.19 m). Alpha and beta diversity were significantly higher in the medium regime than in the low and high regimes. Redundancy analysis indicated that the maximum water depth significantly affected taxonomic alpha diversity, and total nitrogen (TN) and chemical oxygen demand (COD) concentration significantly affected functional alpha diversity, respectively. Mantel tests showed that TN, Secchi depth (SD), and water depth in the high water level regime significantly increased the total beta diversity and turnover components. TN was the main factor that increased total taxonomic beta diversity. Water level regime mainly influenced interspecific relationships by changing the TN and COD concentration. The water level should be maintained between the medium and high water level regimes to promote restoration of the macrophyte community and improve ecosystem stability. The biodiversity evaluation framework would provide a deeper insight into the hydrological process management for restoration of aquatic macrophyte communities in shallow lakes.  相似文献   
2.
The source and hydrochemical makeup of a stream reflects the connectivity between rainfall, groundwater, the stream, and is reflected to water quantity and quality of the catchment. However, in a semi-arid, thick, loess covered catchment, temporal variation of stream source and event associated behaviours are lesser known. Thus, the isotopic and chemical hydrographs in a widely distributed, deep loess, semi-arid catchment of the northern Chinese Loess Plateau were characterized to determine the source and hydrochemical behaviours of the stream during intra-rainfall events. Rainfall and streamflow were sampled during six hydrologic events coupled with measurements of stream baseflow and groundwater. The deuterium isotope (2H), major ions (Cl, SO42−, NO3, Ca2+, K+, Mg2+, and Na+) were evaluated in water samples obtained during rainfall events. Temporal variation of 2H and Cl measured in the groundwater and stream baseflow prior to rainfall was similar; however, the isotope compositions of the streamflow fluctuated significantly and responded quickly to rainfall events, likely due to an infiltration excess, overland dominated surface runoff during torrential rainfall events. Time source separation using 2H demonstrated greater than 72% on average, the stream composition was event water during torrential rainfall events, with the proportion increasing with rainfall intensity. Solutes concentrations in the stream had loglinear relationships with stream discharge, with an outling anomaly with an example of an intra-rainfall event on Oct. 24, 2015. Stream Cl behaved nonconservative during rainfall events, temporal variation of Cl indicated a flush and washout at the onset of small rainfall events, a dilution but still high concentration pattern in high discharge and old water dominated in regression flow period. This study indicates rainfall intensity affects runoff responses in a semi-arid catchment, and the stored water in the thick, loess covered areas was less connected with stream runoff. Solute transport may threaten water quality in the area, requiring further analysis of the performance of the eco-restoration project.  相似文献   
3.
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.  相似文献   
4.
ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN   总被引:1,自引:0,他引:1  
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.  相似文献   
5.
在BPL信道上增加数据广播内容的探讨   总被引:1,自引:1,他引:0  
分析了现有罗兰C(包括BPL)在授时方面存在的不足,提出了在BPL信道上实现数据广播的主要目的。详细讨论了各种可能的数据信息的结构,并给出了有关参数和数据的计算方式和公式。认为发播内容的选择是由期望的系统功能决定的,广播内容的编排则与具体实现技术相关。最后给出了在不同调制方法下的传输速率,这是合理编排广播内容的基础。  相似文献   
6.
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  相似文献   
7.
With a new theory on the 1PN celestial mechanics recently developed by Damour, Soffel and Xu (1991,1992,1993,1994), definitions and expressions of the 1PN spin angular momentum are investigated and analysed. The total spin angular momentum of a system of extended bodies such as the solar system is calculated and expressed as the function of local parameters and observables under reasonable assumptions, which would find its application in the evolution and dynamics of systems of celestial bodies. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   
8.
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.  相似文献   
9.
10.
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.  相似文献   
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