A biodiversity evaluation framework for restoration of aquatic macrophyte communities in shallow lakes driven by hydrological process management     

Shuhan Li  Tao Sun  Wei Yang  Baoshan Cui  Xinan Yin 《水文研究》2021,35(1):e13983

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   

Exploring the stemflow dynamics and driving factors at both inter- and intra-event scales in a typical subtropical deciduous forest     

Haixia Zhang  Congsheng Fu  Aimin Liao  Can Zhang  Jiufu Liu  Niu Wang  Bin He 《水文研究》2021,35(3):e14091

Numerous efforts have been made to understand stemflow dynamics under different types of vegetation at the inter-event scale, but few studies have explored the stemflow characteristics and corresponding influencing factors at the intra-event scale. An in-depth investigation of the inter- and intra-event dynamics of stemflow is important for understanding the ecohydrological processes in forest ecosystems. In this study, stemflow volume (F_V), stemflow funnelling ratio (F_R), and stemflow ratio (F_%) from Quercus acutissima and Broussonetia papyrifera trees were measured at both inter- and intra-event scales in a subtropical deciduous forest, and the driving factors, including tree species and meteorological factors were further explored. Specifically, the F_V, F_R and F_% of Q. acutissima (52.3 L, 47.2, 9.6%) were lower than those of B. papyrifera (85.1 L, 91.2, 12.4%). The effect of tree species on F_V and F_% was more obvious under low intensity rainfall types. At the inter-event scale, F_V had a strong positive linear correlation with rainfall amount (G_P) and event duration (D_E) for both tree species, whereas F_R and F_% had a positive logarithmic correlation with G_P and D_E only under high-intensity, short-duration rainfall type. F_R and F_% were mainly affected by wind speed and the maximum 30-min rainfall intensity under low-intensity, long-duration rainfall type. At the intra-event scale, for both tree species, the mean lag time between the start of rainfall and stemflow was the shortest under high-intensity, short-duration rainfall type, while the mean duration and amount of stemflow after rain cessation were the greatest under high-amount, long-duration rainfall type. The relationship between stemflow intensity and rainfall intensity at the 5-min interval scale also depended greatly on rainfall type. These findings can help clarify stemflow dynamics and driving factors at both inter- and intra-event scales, and also provide abundant data and parameters for ecohydrological simulations in subtropical forests.  相似文献   

基于NPSVM模型的超新星识别方法          下载免费PDF全文

王精东  陈星星  梁吴颖  黄泽锋  全少武  沈锦泫  石雄辉 《天文学报》2021,62(2):15-53

巡天观测与高能物理、黑洞天文等领域均有密切的联系.基于星系-超新星二分类问题,研究光谱数据预处理,结合余弦相似度改善PCA(Principal Component Analysis)光谱分解特征提取方法,用SDSS(the Sloan Digital Sky Survey)、WISeREP(the Weizmann Interactive Supernova data REPository)组成的5620条光谱数据集训练支持向量机,可以得到0.498%泛化误差的识别模型和新样本分类概率.使用Neyman-Pearson决策方法建立NPSVM(Neyman-Pearson Support Vector Machine)模型可进一步降低超新星的漏判率.  相似文献   

基于双谱滤波的综合脉冲星时算法研究          下载免费PDF全文

周庆勇  魏子卿  张华  刘思伟  孙鹏飞  张奋  姜坤  刘晓刚  李奎 《天文学报》2021,62(2):19-95

毫秒脉冲星的自转频率非常稳定,提供了一种独立的基于遥远自然天体并能持续数百万乃至数十亿年的时间基准,具有稳定性强、运行时间长、服务范围广等特点.为了减弱毫秒脉冲星计时观测中各种高斯噪声对脉冲星时的影响,研究了一种基于双谱滤波的综合脉冲星时构建算法,处理分析了国际脉冲星计时阵(International Pul-sar Timing Array,IPTA)最新发布的4颗毫秒脉冲星(PSR J0437-4715、J0613-0200、J1713+0747和J1909-3744)的观测数据,分析了不同时间尺度综合脉冲星时的稳定性,并与构成国际原子时(International Atomic Time,TAI)的4家授时单位原子钟稳定性进行了比较.结果表明:双谱滤波算法能够较好地抑制观测噪声,提高综合脉冲星时的稳定性.相比于经典加权算法,综合脉冲星时1 yr、10 yr稳定度从7.77×10^-14、8.56×10^-16分别提高到1.50×10^-14、3.50×10^-16,单脉冲星时稳定性的提升也类似.同时发现,综合脉冲星时稳定性在5 yr及以上时间尺度上优于原子钟稳定性,可用于改善当前原子时的长期稳定性.  相似文献   

黄土洞室掘进深度与围岩位移变化规律研究     

时卫民  王鹏  赵尚毅 《岩土工程技术》2020,(2):70-75

应用PLAXIS 2D/3D有限元分析软件,对某黄土洞室进行了二维、三维分步掘进、三维一次掘进等工况的弹塑性有限元分析,研究分析了不同工况下洞室围岩位移的变化规律,并对掌子面的空间效应进行了分析。分析结果表明,二维与三维分步计算的最终位移基本一致,可以用二维的计算结果来估算洞室开挖的最终位移。三维分步掘进的分析表明,不同埋深的洞室其位移比的变化规律基本一致,当L/B<1时(L为掘进深度,B为洞室跨度),位移比呈线性增加;当L/B>1时,位移比呈非线性增加;当L/B>3时,其最大位移接近最终位移。掌子面的空间效应分析表明,在掌子面处的位移约为最终位移的1/3,距掌子面0.5倍跨度处的位移约为最终位移的2/3,距掌子面2.5倍跨度处的位移基本达到了最终位移。  相似文献   

微量硫化物、硫酸盐硫同位素EA-IRMS在线测试分析     

武晓珮  范昌福  胡斌  高建飞  李延河 《地球学报》2020,41(5):605-612

常规EA-IRMS硫同位素测试中, 硫化银(Ag2S)的需样量为0.2~1.0 mg, 硫酸钡(BaSO4)的需样量为0.35~1.5 mg, 较大的需样量已难以满足珍贵样品及微区样品的分析要求, 因此如何减少测试样品量已成为EA-IRMS测试分析工作中急需解决的问题。通过对EA-IRMS测试系统的研究发现, 在采用常规方法测试样品时, 由于初始He载气流速(100 mL/min)、进入分流接口时的流速(10 mL/min)与进入离子源时流速 (0.3 mL/min)的差异导致样品燃烧产生的目标气体中99.7%的气体被浪费, 样品的总体利用率仅有0.3%。因此如何减少样品在测试过程中的损耗, 提高样品的利用率, 从而减少需样量的关键在于缩小载气流速的差距。本实验在常规EA-IRMS测试技术基础上进行了关键改进,在元素分析仪和分流接口之间设计增加一个由六通阀和自动加热冷阱构成的装置, 自动加热冷阱可在Load模式时收集SO2气体, 六通阀在Load-Inject模式之间切换时可改变He载气流速, 通过与分流接口匹配的反吹He载气(10 mL/min)将冷阱中富集的SO2气体送入分流接口, 从而保证进入分流接口前样品燃烧产生的SO2气体全部收集。这一改进, 理论上可以将样品的利用率提高10倍, 该系统需硫量降至3~13 μg, 并且可以提高反应管的寿命, 降低清灰的频率, 提高工作效率。同时有效避免了拖尾的产生, 提高分析结果的精密度。本次微量样品实验获得的硫同位素数据与常规方法一致, 分析精度优于0.15‰(1SD), 测量值与真值的差异在0.4‰以内, 达到国际同类实验室先进水平。此外, 该方法可为微量有机碳、氮同位素EA-IRMS测试分析工作的开展提供参考经验。  相似文献   

An Automatic Method for Detecting Transients and Variable Sources in AST3 Survey Based on Image Subtraction and Random Forest     

《Chinese Astronomy and Astrophysics》2020,44(1):41-60

AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.  相似文献   

Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process     

《地学前缘(英文版)》2020,11(6):2207-2219

This investigation assessed the efficacy of 10 widely used machine learning algorithms (MLA) comprising the least absolute shrinkage and selection operator (LASSO), generalized linear model (GLM), stepwise generalized linear model (SGLM), elastic net (ENET), partial least square (PLS), ridge regression, support vector machine (SVM), classification and regression trees (CART), bagged CART, and random forest (RF) for gully erosion susceptibility mapping (GESM) in Iran. The location of 462 previously existing gully erosion sites were mapped through widespread field investigations, of which 70% (323) and 30% (139) of observations were arbitrarily divided for algorithm calibration and validation. Twelve controlling factors for gully erosion, namely, soil texture, annual mean rainfall, digital elevation model (DEM), drainage density, slope, lithology, topographic wetness index (TWI), distance from rivers, aspect, distance from roads, plan curvature, and profile curvature were ranked in terms of their importance using each MLA. The MLA were compared using a training dataset for gully erosion and statistical measures such as RMSE (root mean square error), MAE (mean absolute error), and R-squared. Based on the comparisons among MLA, the RF algorithm exhibited the minimum RMSE and MAE and the maximum value of R-squared, and was therefore selected as the best model. The variable importance evaluation using the RF model revealed that distance from rivers had the highest significance in influencing the occurrence of gully erosion whereas plan curvature had the least importance. According to the GESM generated using RF, most of the study area is predicted to have a low (53.72%) or moderate (29.65%) susceptibility to gully erosion, whereas only a small area is identified to have a high (12.56%) or very high (4.07%) susceptibility. The outcome generated by RF model is validated using the ROC (Receiver Operating Characteristics) curve approach, which returned an area under the curve (AUC) of 0.985, proving the excellent forecasting ability of the model. The GESM prepared using the RF algorithm can aid decision-makers in targeting remedial actions for minimizing the damage caused by gully erosion.  相似文献   

Farmland Abandonment Research Progress: Influencing Factors and Simulation Model     

SONG Wei  ZHANG Ying 《资源与生态学报(英文版)》2019,10(4):345-352

Farmland abandonment is a global problem and considered one of the most important areas in land use change research. Farmland abandonment research currently focuses on understanding the factors that affect farmland abandonment and developing scientific models to simulate farmland abandonment. The study reviewed the natural and political factors driving farmland abandonment and summarized the main models for farmland abandonment simulation together with their advantages and disadvantages. We discuss the main ecological effects of farmland abandonment and propose farmland abandonment research directions. The study found that: (1) the influence of labor cost change and ageing labor force on farmland abandonment needs further investigation, (2) simulation models for farmland abandonment must include the decision-making mechanism of individual farmers and focus on macro large-scale abandonment prediction models, and (3) the influence of farmland abandonment on landscape culture must be investigated in detail.  相似文献   

隧道工程地震易损性分析研究综述与展望          下载免费PDF全文

吴桥  程永志  黄超 《世界地震工程》2020,(2):191-199

易损性分析是隧道工程领域防震减灾研究的重要方法。首先,详细综述了国内外隧道地震易损性研究历史与现状;其次,归纳了国内外隧道地震易损性分析主要方法,并总结了各种方法的实际适用性;接着,提出了隧道地震易损性评估步骤,并且讨论了以数值模拟为主要手段的理论易损性曲线建立中的3个关键内容:(1)输入参数确定;(2)破坏状态分级;(3)相关不确定性参数计算;最后,指出该领域一些亟待解决的问题和未来研究发展的方向。结果表明:隧道地震易损性分析能通过考虑相关不确定性因素,反映了隧道在地震荷载作用下的性能,有利于未来的风险评估和损失估算,对基于性能的隧道抗震设计的发展具有重要意义。  相似文献