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1.
ZHANG Guangliang BAI Junhong JIA Jia WANG Xin WANG Wei ZHAO Qingqing ZHANG Shuai 《中国地理科学(英文版)》2018,(3)
Plant invasion alters the fundamental structure and function of native ecosystems by affecting the biogeochemical pools and fluxes of materials and energy. Native(Suaeda salsa) and invasive(Spartina alterniflora) salt marshes were selected to study the effects of Spartina alterniflora invasion on soil organic carbon(SOC) contents and stocks in the Yellow River Delta. Results showed that the SOC contents(g/kg) and stocks(kg/m~2) were significantly increased(P 0.05) after Spartina alterniflora invasion of seven years, especially for the surface soil layer(0–20 cm). The SOC contents exhibited an even distribution along the soil profiles in native salt marshes, while the SOC contents were gradually decreased with depth after Spartina alterniflora invasion of seven years. The natural ln response ratios(Ln RR) were applied to identify the effects of short-term Spartina alterniflora invasion on the SOC stocks. We also found that Spartina alterniflora invasion might cause soil organic carbon losses in a short-term phase(2–4 years in this study) due to the negative Ln RR values, especially for 20–60 cm depth. And the SOCD in surface layer(0–20 cm) do not increase linearly with the invasive age. Spearman correlation analysis revealed that silt + clay content was exponentially related with SOC in surface layer(Adjusted R~2 = 0.43, P 0.001), suggesting that soil texture could play a key role in SOC sequestration of coastal salt marshes. 相似文献
2.
Zhong-bao Liu Fang-xiao Zhou Zhen-tao Qin Xue-gang Luo Jing Zhang 《Astrophysics and Space Science》2018,363(7):140
Support Vector Machine (SVM) is a popular data mining technique, and it has been widely applied in astronomical tasks, especially in stellar spectra classification. Since SVM doesn’t take the data distribution into consideration, and therefore, its classification efficiencies can’t be greatly improved. Meanwhile, SVM ignores the internal information of the training dataset, such as the within-class structure and between-class structure. In view of this, we propose a new classification algorithm-SVM based on Within-Class Scatter and Between-Class Scatter (WBS-SVM) in this paper. WBS-SVM tries to find an optimal hyperplane to separate two classes. The difference is that it incorporates minimum within-class scatter and maximum between-class scatter in Linear Discriminant Analysis (LDA) into SVM. These two scatters represent the distributions of the training dataset, and the optimization of WBS-SVM ensures the samples in the same class are as close as possible and the samples in different classes are as far as possible. Experiments on the K-, F-, G-type stellar spectra from Sloan Digital Sky Survey (SDSS), Data Release 8 show that our proposed WBS-SVM can greatly improve the classification accuracies. 相似文献
3.
Understanding the temporal variations of extreme floods that occur in response to climate change is essential to anticipate the trends in flood magnitude and frequency in the context of global warming. However, long-term records of paleofloods in arid regions are scarce, thus preventing a thorough understanding of such events. In this study, a reconstruction of paleofloods over the past 300 years was conducted through an analysis of grain sizes from the sediments of Kanas Lake in the Altay Mountains of northwestern China. Results showed that grain parameters and frequency distributions can be used to infer possible abrupt environmental events within the lake sedimentary sequence, and two extreme flood events corresponding to ca. 1736–1765 AD and ca. 1890 AD were further identified based on canonical discriminant analysis(CDA) and coarse percentile versus median grain size(C-M) pattern analysis, both of which occurred during warmer and wetter climate conditions by referring to tree-ring records. These two flood events are also evidenced by lake sedimentary records in the Altay and Tianshan mountains. Furthermore, through a comparison with other records, the flood event from ca. 1736–1765 AD in the study region seems to have occurred in both the arid central Asia and the Alps in Europe, and thus may have been associated with changes in the North Atlantic Oscillation(NAO) index. 相似文献
4.
Reservoirs of lowland floodplain rivers with eutrophic backgrounds cause variations in the hydrological and hydraulic conditions of estuaries and low-dam reservoir areas, which can promote planktonic algae to proliferate and algal bloom outbreaks. Understanding the ecological effects of variations in hydrological and hydraulic processes in lowland rivers is important for algal bloom control. In this study, the middle and lower reaches of the Han River, China, a typical regulated lowland river with a eutrophic background, are selected. Based on the effect of hydrological and hydraulic variability on algal blooms, a hydrological management strategy for river algal bloom control is proposed. The results showed that (a) differences in river morphology and background nutrient levels cause significant differences in the critical threshold flow velocities for algal bloom outbreaks between natural river and low-dam reservoir sections; there is no uniform threshold flow velocity for algal bloom control. (b) There are significant differences in the river hydrological/hydraulic conditions between years with and without algal blooms. The average river flow, water level and velocity in years with algal blooms are significantly lower than those in years without algal blooms. (c) For different river sections where algal blooms occur and to meet the threshold flow velocities, the joint operation of cascade reservoirs and diversion projects is an effective method to prevent and control algal blooms in regulated lowland rivers. This study is expected to deepen our understanding of the ecological significance of special hydrological processes and guide algal bloom management in regulated lowland rivers. 相似文献
5.
基于VSD模型的铁山港湾红树林生态系统脆弱性初步评价 总被引:2,自引:0,他引:2
基于脆弱性域图 (vulnerability scoping diagram, VSD)评价模型, 从暴露程度、敏感性、适应能力3个方面构建了红树林生态系统脆弱性评价指标体系。采用改进的综合指数法和模糊综合评价法, 重新定义脆弱性分级标准, 定量评价了铁山港湾红树林生态系统在1989年、2003年和2014年3个年份的脆弱性水平。结果显示, 铁山港湾红树林生态系统在3个年份的脆弱性水平值分别为0.145、0.255、0.334, 呈现增加趋势。首先, 铁山港湾红树林生态系统面临的暴露程度不断增大, 主要胁迫因子为滩涂围垦面积、废水排放量; 其次, 生态系统的敏感性增强, 主要敏感因子是海洋生物质量综合指数、底栖生物和潮间带生物多样性指数; 第三, 生态系统的适应能力略有增加, 总体上较弱。 相似文献
6.
南极高原拥有独特的天文观测优势,为了对南极中山站夜天文观测条件进行实测研究,中国科学院云南天文台专门研制了一套具有耐低温、自动除雪除霜等适应南极气候特征的全自动全天信息采集系统,该系统可以提供实时的全天云量、天光背景和全天图像,并将信息推送到网页实时显示。介绍了系统的研制及为适应南极气候进行的耐低温实验,统计分析了中山站2016~2017年的全天信息数据,结果显示,中山站2016和2017年的可观测时间为772.21 h和437.38 h,可观测夜数为93 d和51 d,天光背景最大真实值为22.05 Mag/arcsec 2,年平均气温为-10.6℃,最高气温19.1℃,最低气温为-44℃,2016年平均相对湿度为55.2%。 相似文献
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9.
浙南近海虾类群落结构及其多样性分析 总被引:1,自引:0,他引:1
作者根据2015年11月(秋季)、2016年2月(冬季)、2016年5月(春季)和2016年8月(夏季)对浙南近海进行的渔业资源调查数据,用生物量作为虾类资源分布的数量指标,对该海域虾类的组成、数量分布以及季节变化进行分析。结果显示:该区域共鉴定出虾类30种,隶属于10科21属,以对虾科(Penaeidae)虾类最多,其次为管鞭虾科(Solenoceridae),长臂虾科(Palaemonida)位居第3位。按季节来看,秋季共鉴定虾类27种,各站位平均生物量为6.97 kg/km2,优势种为凹陷管鞭虾(Solenocera koelbeli)、中国毛虾(Acetes chinensis)和中华管鞭虾(Solenocera crassicornis)等3种;冬季鉴定出虾类25种,平均生物量为1.65 kg/km2,优势种为凹陷管鞭虾、扁足异对虾(Atypopenaeus stenodactylus)、日本鼓虾(Alpheus japonicus)、鲜明鼓虾(Alpheus digitalis)、中国毛虾、中华管鞭虾和周氏新对虾(Metapenaeus joyneri)等7种;春季20种,平均生物量为2.22 kg/km2,优势种为戴氏赤虾(Metapenaeopsis dalei)、东海红虾(Metapenaeopsis dalei)和中华管鞭虾等3种;夏季16种,平均生物量为10.36 kg/km2,优势种有鹰爪虾(Trachysalambria curvirostris)和中华管鞭虾等2种。Margalef丰富度指数(D)、Shannon-Wiener多样性指数(H′)和Pielou均匀度指数(J′)秋季均低于冬季。秋冬季受到浙闽沿岸流影响,温度、盐度相对较低,夏季受到台湾暖流外侧影响,温度、盐度相对较高,且各季节间由于瓯江、椒江、飞云江、鳌江等陆源性冲淡水的影响,盐度、温度变化相对较大,使得该区域的物种不得不适应一个跨度较大的温盐范围,广温广盐性种类为主。 相似文献
10.
Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant (SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set’s reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis (PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting (SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image. 相似文献