Growing Political: Violence,Community Forestry,and Environmental Defender Subjectivity

Why do environmental defenders continue to participate in community-based efforts to protect the environment despite threats to their lives and minimal success in deterring or punishing offenders? Examining Community Forestry initiatives in Cambodia, we find that forest protection is not only a means to gain environmental, economic, or social benefits, but also a means for forest defenders to assert themselves as political actors in relation to the state and other citizens. Rather than simply repressing and disciplining forest dwelling populations, violence against defenders shapes their subjectivity and re-politicizes their lives. Distinguishing between various forms of violence associated with different illicit forest users, we highlight how forest protection becomes a means of political self-expression and rights-based resistance as forest defenders reinterpret direct violence through experiences and understandings of structural and symbolic violence. Participation in CF thus unlocks ways of being political and contesting oppressive structures while acting within sanctioned institutions.     

Geospatial data mining for digital raster mapping

We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural networks, and support vector machines. The advantages of each data mining approach as well as approaches to avoid overfitting are subsequently discussed. We also provide suggestions and examples for the mapping of problematic variables or classes, future or historical projections, and avoidance of model bias. Finally, we address the separate issues of parallel processing, error mapping, and incorporation of “no data” values into modeling processes. Given the improved availability of digital spatial products and remote sensing products, data mining approaches combined with parallel processing potentials should greatly improve the quality and extent of ecological datasets.     

人工育珠对三角帆蚌(Hyriopsis cumingii)遗传基因影响的初步研究

采用酚-氯仿和试剂盒两种提取法对三角帆蚌怀珠群与非怀珠群各6个个体进行基因组DNA的提取,然后在优化RAPD(随机扩增多态性DNA)检测条件基础上,从80个随机引物中筛选出12个扩增较好且多态性强的引物进行RAPD扩增,产物通过水平板琼脂糖凝胶电泳和垂直板聚丙烯酰胺凝胶电泳两种方法进行检验并对DNA的多态性进行分析。结果显示在怀珠群和非怀珠群检测到的位点数、多态位点比例、平均Shannon多态性信息指数、平均Nei's基因多样性指数、群体内个体间平均遗传相似率和平均遗传距离分别为100、33%、0.1927、0.1324、0.904、0.096,95、47.37%、0.2711、0.1879、0.861、0.139,群体间的平均遗传距离为0.821,非怀珠群的变异性大于怀珠群;本研究还获得了两群体各自的特异扩增谱带及两群体间表达差异较大谱带,这些位点很可能是由人工育珠所引起。根据MEGA4.0软件的UPGMA和NJ程序构建的分子系统树可直观地将两群体分开。     

Classifier ensembles for land cover mapping using multitemporal SAR imagery

SAR data are almost independent from weather conditions, and thus are well suited for mapping of seasonally changing variables such as land cover. In regard to recent and upcoming missions, multitemporal and multi-frequency approaches become even more attractive. In the present study, classifier ensembles (i.e., boosted decision tree and random forests) are applied to multi-temporal C-band SAR data, from different study sites and years. A detailed accuracy assessment shows that classifier ensembles, in particularly random forests, outperform standard approaches like a single decision tree and a conventional maximum likelihood classifier by more than 10% independently from the site and year. They reach up to almost 84% of overall accuracy in rural areas with large plots. Visual interpretation confirms the statistical accuracy assessment and reveals that also typical random noise is considerably reduced. In addition the results demonstrate that random forests are less sensitive to the number of training samples and perform well even with only a small number. Random forests are computationally highly efficient and are hence considered very well suited for land cover classifications of future multifrequency and multitemporal stacks of SAR imagery.     

Numerical simulation of nearshore circulation on field topography under random wave environment

In order to investigate surf zone hydrodynamics through two-dimensional numerical simulations of nearshore circulation under random wave environment, a nearshore circulation model, SHORECIRC, and a random wave model, SWAN, were combined and utilized. Using this combined model, a numerical simulation of the October 2, 1997 SandyDuck field experiment was performed. For this simulation, field topography and an input offshore spectrum were constructed using observed data sets synchronized with the experiment. The wave-breaking model in SWAN was modified by using breaker parameters varied according to bottom slope. The simulation results were compared with the experimental data, which revealed a well-developed longshore current, as well as with results using other combinations which were SHORECIRC and its original monochromatic wave-driver, and SHORECIRC and the default of SWAN. The results from the novel combined model agreed well with the experimental data. The results of the present simulation also indicate that alongshore field topography influences shear fluctuation of longshore currents.     

Numerical simulation of random wave slamming on structures in the splash zone

The numerical investigation of random wave slamming on superstructures of marine structures in the splash zone is presented in this paper. The impact pressures on the underside of the structure are computed based on the improved volume of fluid method (VOF). The governing equations are Reynolds time-averaged equations and the two equation k– model. The third order upwind difference scheme is applied to the convection term to reduce the effect of numerical viscosity. The numerical wave flume with random wave-maker suitable for VOF is established. Appropriate moving contact-line boundary conditions are introduced to the model wave in contact with and separated from the underside of structure. Parametric studies have been carried out for different incident waves, structure dimensions and structure clearance. The numerical results are verified by the experimental results.     

植被电磁散射的半空间模型研究

本文给出了地面植被电磁散射的半空间模型研究方法.在以往的相关文献中,均采用自由空间格林函数求解单个叶片散射体的散射场,本文利用半空间并矢格林函数求出了单个散射体的散射场,然后运用Monte Carlo方法模拟生成地面植被层,得到了在半空间下植被层的电磁散射特性,计算出了单、双站雷达散射截面,并与自由空间下的散射场做了相互对比.结果表明,在半空间格林函数下得到的散射场更为适用于描述地面植被的电磁散射特性.     

On-line estimation of nonlinear physical systems

Recursive algorithms for estimating states of nonlinear physical systems are presented. Orthogonality properties are rediscovered and the associated polynomials are used to linearize state and observation models of the underlying random processes. This requires some key hypotheses regarding the structure of these processes, which may then take account of a wide range of applications. The latter include streamflow forecasting, flood estimation, environmental protection, earthquake engineering, and mine planning. The proposed estimation algorithm may be compared favorably to Taylor series-type filters, nonlinear filters which approximate the probability density by Edgeworth or Gram-Charlier series, as well as to conventional statistical linearization-type estimators. Moreover, the method has several advantages over nonrecursive estimators like disjunctive kriging. To link theory with practice, some numerical results for a simulated system are presented, in which responses from the proposed and extended Kalman algorithms are compared.     

随机地震模型及反应谱分析

本文以实际地震加速度的频谱特性和相位谱特性为依据，仿概率统计理论中的高斯概率密度函数，建立了随机地震加速度频数学模型。