Giant hogweed at its northern distribution limit in North America: Experiments for a better understanding of its dispersal dynamics along rivers

We studied the reproduction and dispersal of giant hogweed (Heracleum mantegazzianum) at its northern distribution limit in North America (Québec, 2014–2016) to better understand the invasion dynamics of the species along rivers. Seeds were collected from a riparian population to conduct germination, floatation, and dispersal experiments. Data were analysed in comparison with a real invasion case that was initiated about 10 years ago along a river system. In Québec, giant hogweed individuals produce on average 14,000 to 16,000 seeds with a germination rate of 75–85%. Seeds with endosperm that fall in water likely sink within 5 hr. Along a small brook, most disperse over short distances (<40 m) in summer, although some can travel 100–300 m. These data suggest that late‐summer or early‐fall water dispersal of seeds would not explain the magnitude and rapidity of the invasion patterns observed along streams. We suggest that late‐fall and, especially, spring floods are the most efficient dispersal vectors for giant hogweed seeds and are likely responsible for the establishment of populations kilometres downstream from introduction points along river systems. The spread of giant hogweed would consequently be less influenced in the near future by a rise in temperature than by a change in the magnitude or timing of flood events.     

Effect of substrate on the risk of being washed away by floods for the Groundhoppers Tetrix subulata and Tetrix tenuicornis (Orthoptera: Tetrigidae)

Inundation zones of rivers are risky environments for terrestrial animals because of the regular or irregular occurrence of floods. Although animals in these zones have evolved several strategies to survive floods, behavioural anti‐flooding strategies have seldom been studied but could play an important role in their life history strategies. We previously reported that the groundhopper Tetrix tenuicornis moves to dense vegetation in response to low atmospheric pressure (which may signal rain and flooding) but prefers mossy microhabitats and bare ground under high atmospheric pressure. In the current study, we found that the ability of the semi‐aquatic groundhoppers T. tenuicornis and Tetrix subulata to withstand direct water flow was greater in patches of dense vegetation than in patches of moss or on bare ground. Even a relatively low water velocity led to water transport (presumably passive) of both species, perhaps because they lack arolia or other adhesive devices on their tarsi. This morphological limitation precludes vertical migration on vegetation, which is a common anti‐flooding strategy in insects. Our results suggest that, by moving to dense vegetation in response to drops in atmospheric pressure, groundhoppers may reduce their risk of being washed away by floods.     

Robust spatial flood vulnerability assessment for Han River using fuzzy TOPSIS with α-cut level set

This study aims to improve the general flood vulnerability approach using fuzzy TOPSIS based on α-cut level sets which can reduce the uncertainty inherent in even fuzzy multi-criteria decision making process. Since fuzzy TOPSIS leads to a crisp closeness for each alternative, it is frequently argued that fuzzy weights and fuzzy ratings should be in fuzzy relative closeness. Therefore, this study used a modified α-cut level set based fuzzy TOPSIS to develop a spatial flood vulnerability approach for Han River in Korea, considering various uncertainties in weights derivation and crisp data aggregation. Two results from fuzzy TOPSIS and modified fuzzy TOPSIS were compared. Some regions which showed no or small ranking changes have their centro-symmetric distributions, while other regions whose rankings varied dynamically, have biased (anti-symmetric) distributions. It can be concluded that α-cut level set based fuzzy TOPSIS produce more robust prioritization since more uncertainties can be considered. This method can be applied to robust spatial vulnerability or decision making in water resources management.     

基于混沌特征的运动模式分割和动态纹理分类

采用混沌理论对动态纹理中的像素值序列建模,提取动态纹理中的像素值序列的相关特征量,将视频用特征向量矩阵表示. 通过均值漂移（Mean shift）算法对矩阵中的特征向量聚类,实现对视频中的运动模式分割. 然后,采用地球移动距离（Earth mover’s distance,EMD）度量不同视频的差异,对动态纹理视频分类. 本文对多个数据库测试表明:1）分割算法可以分割出视频中不同的运动模式;2）提出的特征向量可以很好地描述动态纹理系统;3）分类算法可以对动态纹理视频分类,且对视频中噪声干扰具有一定的鲁棒性.     

基于区域生长的多源遥感图像配准

多源遥感图像由于成像设备、所用光谱、拍摄时间等因素的不同,给配准带来极大的困难.尽管已经提出了多种匹配方法,但已有方法一般只能适用于特定的应用环境,开发出更加稳定和适用的配准算法仍然是一个极具挑战性的研究课题.提出一种基于区域生长的配准方法,首先,提取改进后的尺度不变特征,通过全局匹配确定种子点和种子区域并完成变换模型的初始化;然后,运用迭代区域生长和双向匹配策略,得到整个图像的可靠匹配点,从而实现多源遥感图像之间的配准.实验表明,该方法提取的匹配点的数量和正确率均远高于已有方法,能够对存在严重灰度差异的多源遥感图像实现高精度的配准,充分证明了该方法的鲁棒性和适用性.     

融合异构特征的子空间迁移学习算法

特征迁移重在领域共有特征间学习,然而其忽略领域特有特征的判别信息,使算法的适应性受到一定的局限. 针对此问题,提出了一种融合异构特征的子空间迁移学习（The subspace transfer learning algorithm integrating with heterogeneous features,STL-IHF）算法.该算法将数据的特征空间看成共享和特有两个特征子空间的组合,同时基于经验风险最 小框架将共享特征和特有特征共同嵌入到支持向量机（Support vector machine,SVM）的训练过程中.其在共享特征子空间上实现知识迁移的 同时兼顾了领域特有的异构信息,增强了算法的适应性.模拟和真实数据集上的实验结果表明了所提方法的有效性.     

R-SMA共聚树脂及其改性研究

本文介绍了无规苯乙烯—马来酸酐共聚树脂（Ｒ—ＳＭＡ）的合成工艺、特性和用途，并叙述了Ｒ—ＳＭＡ改性研究状况．     

基于MIKE FLOOD的洪泽湖周边滞洪区洪水演进模拟研究

基于实测断面资料建立了研究区的一维水动力模型,基于高精度DEM以及1∶10000地形图建立了研究区的二维水动力模型,并用MIKE FLOOD将一维模型和二维模型进行耦合,构建了洪泽湖周边滞洪区一、二维耦合的洪水演进数学模型。利用2003年历史洪水资料对模型参数进行了率定,并以2007年历史洪水资料进行了验证。以洪泽湖百年一遇设计洪水为模型上边界,二河闸、三河闸以及高良涧闸的现行调度方案的水位-流量关系为模型下边界,对洪泽湖百年一遇设计洪水方案进行模拟计算,当蒋坝水位达到14.33m时,洪泽湖周边滞洪区开始滞洪,得到开始滞洪后不同时段研究区内各类洪水风险要素的动态分布情况以及最大淹没水深、淹没历时,验证了模型的合理性,可用于蓄滞洪区洪水演算分析。     

Flood Inundation Modelling for Mid‐Lower Brisbane Estuary

This study utilizes a two‐dimensional hydrodynamic model to calibrate and validate an inundation model for the Brisbane River estuary in Queensland, Australia. The bathymetry data used in the hydraulic model are derived from one arc second (1 s) shuttle radar topography mission digital elevation model, and the two‐dimensional hydraulic model is parameterized using the generated bathymetry with four open boundaries with water level observations and roughness coefficients. The calibration performance is evaluated by comparing the simulated results with the digitized records during the January 2013 flood event (a low magnitude event) at three gauging stations. The calibrated model is validated with water level data and available discharge data during the January 2011 flood (a large magnitude event) at four gauging stations located along the Brisbane River. Different performance indices are applied to demonstrate that the developed model performs well during calibration and validation. A sensitivity analysis is presented to assess the influence of riverbed elevation changes on the model because the main uncertainty of the model is the bathymetry data. The proposed model with the shuttle radar topography mission digital elevation model‐derived riverbed elevation for the Brisbane estuary is able to predict the flood inundation extent at an accuracy of 66.9% which is higher than or comparable with the accuracies of the existing studies. However, it is expected that the accuracy will increase if some improved bathymetry data become available in the future. Copyright © 2016 John Wiley & Sons, Ltd.