2018年永清M_S 4.3地震前易县地震台形变异常分析

2018年2月12日18:31:36河北省廊坊市永清县MS 4.3地震发生前,易县地震台SS-Y型铟瓦棒伸缩仪和DSQ型水管倾斜仪记录出现不同程度的异常,从异常形态起始及持续时间、异常幅度和发震时刻进行分析,发现二者相对应,认为此次异常应为永清地震震前异常。     

基于ArcGIS Online的地震应急共享服务

ArcGIS Online是一种协作式GIS管理云平台,集地图、程序、群组、资源和服务于一体,可为地震应急工作有效提供协同办公平台。本文以地震应急服务共享为目标,阐述ArcGIS Online公有云平台的功能特点,分析其优缺点,尝试在该平台上创建地图、应用程序,并在私有群组内进行地图共享,组内成员、内业外业工作者协同评估,为应急指挥决策提供服务与支持。     

Progress in plant phenology modeling under global climate change

Plant phenology is the study of the timing of recurrent biological events and the causes of their timing with regard to biotic and abiotic forces. Plant phenology affects the structure and function of terrestrial ecosystems and determines vegetation feedback to the climate system by altering the carbon, water and energy fluxes between the vegetation and near-surface atmosphere. Therefore, an accurate simulation of plant phenology is essential to improve our understanding of the response of ecosystems to climate change and the carbon, water and energy balance of terrestrial ecosystems. Phenological studies have developed rapidly under global change conditions, while the research of phenology modeling is largely lagged. Inaccurate phenology modeling has become the primary limiting factor for the accurate simulation of terrestrial carbon and water cycles.Understanding the mechanism of phenological response to climate change and building process-based plant phenology models are thus important frontier issues. In this review, we first summarized the drivers of plant phenology and overviewed the development of plant phenology models. Finally, we addressed the challenges in the development of plant phenology models and highlighted that coupling machine learning and Bayesian calibration into process-based models could be a potential approach to improve the accuracy of phenology simulation and prediction under future global change conditions.     

基于开源软件的地震影响场快速生成及动态修正方法研究与实现

地震发生后,盲场快速评估阶段生成的地震影响场对极震区的判定和应急救援的实施起着重要的作用。震后依据地震震级、震中所在地区的地震烈度衰减关系和活动断裂分布情况可快速绘制第1时段地震影响场,然后综合考虑此次地震震源的特性,充分利用余震序列、震源机制解等结果可动态修正影响场。本文基于开源软件实现地震影响场的自动生成,并依据余震序列、震源机制解等结果,实现动态修正地震影响场,为震后灾情评估和多时段应急图件产出打下基础。     

Relationship between toxic and harmful microalgae and environmental factors in typical mariculture areas of East China Sea

Toxic and harmful algal blooms are usually more frequent in mariculture areas due to the abundant trophic conditions. To investigate the relationship between toxic and harmful microalgae and environmental factors, we set up 12 stations near three mariculture regions (Gouqi Island, Sandu Bay, and Dongshan Bay) in the East China Sea. We collected samples from all four seasons starting from May 2020 to March 2021. We identified 199 species belonging to 70 genera, of which 38 species were toxic and harmful, including 24 species of Dinophyceae, 13 species of Bacillariophyceae, and 1 species of Raphidophyceae. The species composition of toxic and harmful microalgae showed a predominance of diatoms in the summer (August), and dinoflagellates in the spring (May), autumn (November), and winter (March). The cell densities of toxic and harmful microalgae were higher in summer (with an average value of 15.34×10³ cells/L) than in other seasons, 3.53×10³ cells/L in spring, 1.82×10³ cells/L in winter, and 1.0×10³ cells/L in autumn. Pseudonitzschia pungens, Prorocentrum minimum, Paralia sulcata, and Prorocentrum micans were the dominant species and were available at all 12 stations in the three mariculture areas. We selected 10 toxic and harmful microalgal species with frequency >6 at the survey stations for the redundancy analysis (RDA), and the results show that NO ^?₃ , water temperature (WT), pH, DO, and NO ^?₂ were the main factors on distribution of toxic and harmful microalgae. We concluded that the rich nutrient conditions in the East China Sea mariculture areas increased the potential for the risk of toxic and harmful microalgal bloom outbreaks.