基于景观格局变化的海岸带生态风险评价——以辽宁省瓦房店市为例

文章利用RS和GIS技术手段对辽宁省瓦房店市1990—2015年的变迁过程进行监测,得出各历史时期的土地利用变化信息。将各类土地利用信息与景观生态学相结合,利用景观格局破碎度、景观分离度、景观优势度作为指标构建景观损失指数,并利用景观组分的面积比重构建海岸带生态风险指数。基于ArcGIS和Fragstats软件平台,通过空间采样和插值方法得到区域生态风险的空间分布,据此重构了瓦房店市1990—2015年的生态风险值变化过程。监测表明,1990—2015年期间,耕地、林地和滩涂呈减少趋势,水域和建设用地逐年增加,其他类型变化幅度不大。虽然耕地所占总面积比例由45.37%减少至37.23%,但一直是瓦房店最主要的景观。25年间瓦房店生态安全总体呈下降态势,1990—2015年6时段的生态风险年平均值分别为0.211 9、0.200 3、0.203 2、0.194 9、0.209 7和0.209 1。在时间维度,1990—2005年和2010—2015年生态安全度下降明显;在空间维度,瓦房店市海岸带的李官镇-三台满族乡和谢屯镇-炮台镇的生态风险度高,西杨乡、东岗镇和驼山乡生态风险由极高降为高或中,生态安全度有所提高。研究表明,人口和社会经济发展是影响瓦房店市景观格局变化的主要因素,该区域未来海岸带要实现可持续开发必须要进行科学的规划。     

Guiding ecological principles for marine spatial planning

The declining health of marine ecosystems around the world is evidence that current piecemeal governance is inadequate to successfully support healthy coastal and ocean ecosystems and sustain human uses of the ocean. One proposed solution to this problem is ecosystem-based marine spatial planning (MSP), which is a process that informs the spatial distribution of activities in the ocean so that existing and emerging uses can be maintained, use conflicts reduced, and ecosystem health and services protected and sustained for future generations. Because a key goal of ecosystem-based MSP is to maintain the delivery of ecosystem services that humans want and need, it must be based on ecological principles that articulate the scientifically recognized attributes of healthy, functioning ecosystems. These principles should be incorporated into a decision-making framework with clearly defined targets for these ecological attributes. This paper identifies ecological principles for MSP based on a synthesis of previously suggested and/or operationalized principles, along with recommendations generated by a group of twenty ecologists and marine scientists with diverse backgrounds and perspectives on MSP. The proposed four main ecological principles to guide MSP—maintaining or restoring: native species diversity, habitat diversity and heterogeneity, key species, and connectivity—and two additional guidelines, the need to account for context and uncertainty, must be explicitly taken into account in the planning process. When applied in concert with social, economic, and governance principles, these ecological principles can inform the designation and siting of ocean uses and the management of activities in the ocean to maintain or restore healthy ecosystems, allow delivery of marine ecosystem services, and ensure sustainable economic and social benefits.     

基于人工神经网络的沿海风速多步预测研究

基于气象历史观测资料,将长短期记忆网络LSTM方法和Transformer模型结合提出了混合短期风速多步预测模型BLSTM TRA。以山东半岛南部沿海6个台站为研究区域,通过气象台站观测数据构建数据集。经与2018年ECMWF模式6 h预报结果对比分析,得出如下结论：构建的BLSTM TRA多步预测模型可大幅度降低风速误差,BLSTM TRA的1 h单步预测结果和ECMWF预报模式结果对比,其RMSE平均降低了58.9%,MAE平均降低了63.2%;风速误差和大风统计过程分析发现,BLSTM TRA模型具有一定的抗干扰能力,可以抓住短时大风等敏感信息,对于大风预报结果明显优于ECWMF模式和传统LSTM模型。     

长江源区生态及灾害地质调查与防治对策

简述了长江源区自然地理和生态地质环境特征,分析了环境恶化的主要原因及防治对策。     

Machine learning for pore-water pressure time-series prediction: Application of recurrent neural networks

Knowledge of pore-water pressure(PWP)variation is fundamental for slope stability.A precise prediction of PWP is difficult due to complex physical mechanisms and in situ natural variability.To explore the applicability and advantages of recurrent neural networks(RNNs)on PWP prediction,three variants of RNNs,i.e.,standard RNN,long short-term memory(LSTM)and gated recurrent unit(GRU)are adopted and compared with a traditional static artificial neural network(ANN),i.e.,multi-layer perceptron(MLP).Measurements of rainfall and PWP of representative piezometers from a fully instrumented natural slope in Hong Kong are used to establish the prediction models.The coefficient of determination(R^2)and root mean square error(RMSE)are used for model evaluations.The influence of input time series length on the model performance is investigated.The results reveal that MLP can provide acceptable performance but is not robust.The uncertainty bounds of RMSE of the MLP model range from 0.24 kPa to 1.12 k Pa for the selected two piezometers.The standard RNN can perform better but the robustness is slightly affected when there are significant time lags between PWP changes and rainfall.The GRU and LSTM models can provide more precise and robust predictions than the standard RNN.The effects of the hidden layer structure and the dropout technique are investigated.The single-layer GRU is accurate enough for PWP prediction,whereas a double-layer GRU brings extra time cost with little accuracy improvement.The dropout technique is essential to overfitting prevention and improvement of accuracy.     

AN~2 APPLICATION IN THE METRODS OF POPULATION GEOGRAPHY

1.PoPulation~aphyisthestudy0fthespatialdistributionmdarrangnatsofhumanpoPulation.ItisthesdenceofhowspatialvariarionsinthecomPosihon,growth,whgraion,anddistribLItionofpoPulatonsaiere1ataltospatialvariationsinthenatureofplaces.ThemethodsplayanimPohanroleinr…     

广东省强震台网建设概况

本文论述了广东省强震台网建设的目的和原则,介绍了台网中使用的强震仪,收取的强震记录和处理情况、台网管理及其展望。     

运用人工神经网络作汛期降水预报

本文提出汛期降水预报的人工神经网络方法，并选择一组标样进行了具体分析，预报成功率达100％，结果表明，该方法性能良好，可望成为汛期降水预报的有效手段。