Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

浅淡监测数据的共享与社会效应

结合工作实际对如何有效利用监测数据进行了探讨 ,并引申出监测数据的 4种效应 ,即信息效应、价值效应、广告效应和政治效应。     

Wet weather impact on trihalomethane formation potential in tributaries to drinking water reservoirs

During rain storm events, land surface runoff and resuspension of bottom sediments cause an increase in Trihalomethane (THM) precursors in rivers. These precursors, when chlorinated at water treatment facilities will lead to the formation of THMs and hence impact drinking water resources. In order to evaluate the wet weather impact on the potential formation of THMs, river samples were collected before, during and after three rain storms ranging from 15.2 to 24.9 mm precipitation. The samples were tested for THM formation potential and other indicators including UV254 absorbance, turbidity and volatile suspended solid (VSS). Average levels of THMs increased from 61 μg/l during dry weather to 131 μg/l during wet weather, and then went back to 81 μg/l after rain ended. Wet weather values of THM are well above the maximum contaminant level (MCL) 80 μg/l, set by EPA for drinking water. THM indicators also exhibited similar trends. Average levels increased from 0.6 to 1.8 abs; 2.6 to 6 ntu; and 7.5 to 15 mg/l respectively for UV254, turbidity and VSS. A positive correlation was observed between THM formation and THM indicators. The t-test of significance (p-value) was less than 0.05 for all indicators, and R values ranged from 0.85 to 0.92 between THMs and the indicators, and 0.72 to 0.9 among indicators themselves.     

浅论环境指标的相关性分析在监测数据审核中的应用

数据审核是环境监测质量保证的重要环节之一,数据审核的方法有许多种,文章从监测数据中各环境指标之间的相关性分析出发,对水、气、声环境要素中的各环境指标间的相关性进行总结,并将其应用于数据合理性的审核,具有借鉴意义.     

四川省空气自动监测数据采集系统建设

介绍了四川省空气质量监测工作的现状和存在的问题,提出了建设四川省空气自动监测数据采集系统的技术路线,建设完成了全省空气监测数据的统一采集。     

对地观测技术在重大自然灾害监测与评估中的应用实例分析

对地观测技术可提供大范围、多时相、高分辨率的海量数据,用于自然灾害的监测与评估有其极大的优越性。本文叙述了对地观测技术在洪涝灾害、沙尘天气、森林火灾的监测与评估和地震形变场研究中的应用,并指出对地观测技术是建立数字减灾系统不可或缺的强大信息源。     

污水土地处理CAD系统设计

针对污水土地处理设计实际,以提高设计速度和质量为目标,结合计算机辅助设计技术和软件技术的发展,采用成熟而先进的参数化设计技术及ADS开发工具,对土地处理设计中的几个关系问题进行了探讨。     

鸭绿江（丹东段）江水中未知有机污染物分析鉴定与有毒有机物名录筛选

采用美国惠普公司MC/GS联用仪,对鸭绿江（丹东段）江水中有机污染物种类、组成进行了分析鉴定,进而采用高压液相色谱法对多环芳烃类进行定量测定与评价,进行了该江段有毒有机物名录筛选,提出由27种有毒有机污染物组成的名单。     

不同天气型下武汉城市圈PM2.5污染及大气层结特征分析

利用2015—2019年PM_2.5和气象要素观测资料、NCEP和ERA5再分析资料,分析不同天气型下武汉城市圈PM_2.5区域污染时空分布、天气尺度环流和大气层结特征.结果表明,城市圈污染以武汉为中心,多为轻度-中度污染,西部重于东部.造成武汉城市圈区域污染增长的天气形势包括4类,分别为冷高压底前部型、高压后部型、均压场型和低压倒槽型.4类污染天气型均有较低的混合层高度和地表通风系数,且边界层存在弱下沉运动和逆温,抑制污染垂直扩散.但气象要素影响PM_2.5污染的机理各异：冷高压底前部型主要为大气压梯度引导偏北大风带来污染物远程输送,边界层冷平流导致低温、锋面逆温和浅薄高湿层(65%～80%),强输入性污染配合吸湿性累积增长造成严重污染,逆温厚度对PM_2.5增幅作用明显;低压倒槽型东南风输入污染弱,但高温、低压引起气流辐合导致本地污染汇积,边界层暖平流带来平流逆温和深厚湿层(1000～750 hPa),逆温层底高偏低、厚度偏厚,促进污染物在近地面吸湿增长;高压后部和均压场型均为浅薄湿层(1000～975...     

基于PSO-SVM算法的环境监测数据异常检测和缺失补全

针对环境监测数据异常和数据缺失问题,提出了基于支持向量机的粒子群优化数据异常检测和缺失补全算法。利用粒子群优化算法选取较优的支持向量机训练参数组合,以此建立非线性的支持向量机模型,并利用结果模型对测得的真实数据拟合预测。以宁夏回族自治区某污水处理厂的污染物测量数据作为实验数据,结果表明,利用该算法预测数据的准确率可达97.977%,检测异常数据准确度高,缺失数据补全正确。