Optimization of capture–recapture monitoring of elusive species illustrated with a threatened grasshopper

Information on population sizes and trends of threatened species is essential for their conservation, but obtaining reliable estimates can be challenging. We devised a method to improve the precision of estimates of population size obtained from capture–recapture studies for species with low capture and recapture probabilities and short seasonal activity, illustrated with population data of an elusive grasshopper (Prionotropis rhodanica). We used data from 5 capture–recapture studies to identify methodological and environmental factors affecting capture and recapture probabilities and estimates of population size. In a simulation, we used the population size and capture and recapture probability estimates obtained from the field studies to identify the minimum number of sampling occasions needed to obtain unbiased and robust estimates of population size. Based on these results we optimized the capture–recapture design, implemented it in 2 additional studies, and compared their precision with those of the nonoptimized studies. Additionally, we simulated scenarios based on thresholds of population size in criteria C and D of the International Union for Conservation of Nature (IUCN) Red List to investigate whether estimates of population size for elusive species can reliably inform red-list assessments. Identifying parameters that affect capture and recapture probabilities (for the grasshopper time since emergence of first adults) and optimizing field protocols based on this information reduced study effort (−6% to −27% sampling occasions) and provided more precise estimates of population size (reduced coefficient of variation) compared with nonoptimized studies. Estimates of population size from the scenarios based on the IUCN thresholds were mostly unbiased and robust (only the combination of very small populations and little study effort produced unreliable estimates), suggesting capture–recapture can be considered reliable for informing red-list assessments. Although capture–recapture remains difficult and costly for elusive species, our optimization procedure can help determine efficient protocols to increase data quality and minimize monitoring effort.     

环境空气质量自动监测站的管理与维护

随着工业化、城镇化的深入推进,二氧化硫、氮氧化物、烟粉尘和挥发性有机物等各类污染物排放到环境中,致使中国大气受到严重污染,给人体的健康、动植物的生长、发育和繁殖等带来负面的影响。为实时监测环境空气质量,建立环境空气质量自动监测站逐渐成为大气污染防治的主要手段。文中以环境空气质量自动监测站为研究对象,提出环境空气质量自动监测站管理与维护面临的问题,探讨相应的解决措施,以期为环境空气质量自动监测站的管理与维护提供参考依据。     

德国铁路噪声实时监测系统研究现状

分析了德国铁路噪声在线监测的应用背景,介绍了德国铁路噪声实时监测系统的研究现状,包括测量站点的选取原则、技术结构和具体信息,列车声压级曲线时域连续变化图、单次列车通过声压级曲线图、单次列车通过参数表和等效声压级曲线图/表等测量结果的表达方法,以及无效数据的处理方式等,为我国建立铁路噪声自动监测系统提供参考。     

饮用水源微生物快速检测技术的发展及应用

微生物是威胁饮用水安全的首要问题,水环境微生物快速检测技术的开发和应用是推动饮用水源微生物快速检测和水质安全预警技术发展的保障。随着对水质微生物污染快速检测和准确预警新要求的提出,水环境中微生物在线检测和预警技术得到了越来越多的开发和应用。笔者总结了水环境常见微生物检测方法和技术的发展,重点讨论了饮用水源微生物快速检测技术的发展和应用,根据各项技术的应用和推广使用程度,将其归纳为常用快速检测技术、潜在适用快速检测技术和新型快速检测技术等类别,并详细阐述了一些应用较广的技术,以期为构建水质微生物污染早期预警系统提供参考。     

便携式GC-MS仪快速测定水中硝基苯及其在应急监测中的应用

采用便携式GC-MS仪快速测定水中硝基苯,通过优化水中离子强度和顶空加热时间,使方法在0μg/L^300μg/L范围内线性良好,方法检出限为2.5μg/L。标准溶液6次测定结果的RSD为7.8%~10.9%,实际水样的加标回收率为80.7%~103%。同步测定试验表明,硝基苯与7种苯系物分离良好。与国标方法对比,该方法单个样品测定时间由2 h缩短为15 min。将该方法用于应急监测工作中,及时有效的数据可为污水处理及事故调查提供分析和研判依据。     

玛纳斯河流域荒漠草地沙化遥感监测研究

以1989—2016年玛纳斯河流域TM/OLI遥感影像为数据源,利用混合像元分解技术,计算玛纳斯河流域草地总覆盖度和裸沙面积。在此基础上通过监测年与基期年的比较,计算草地覆盖度相对基期年的减少率和裸沙面积相对基期年的增加率两个监测指标,依据《天然草地退化、沙化、盐渍化的分级指标》(GB 19377—2003),对计算出的两个指标分别进行沙化等级评定和赋值,将两种评定结果相综合来监测草地沙化。结果表明,玛纳斯河流域近30年来荒漠草地沙漠化总体呈现先增加后降低的趋势。分析表明,玛纳斯河流域草地沙化是人为和自然因素双重作用的结果。     

浅谈如何开展环境监测类设施公众开放日活动

随着城市工业化的快速发展,突发性环境污染事故逐渐增多,因此,环境公众开放日活动显得尤为重要。本文结合实际情况,探讨如何开展监测类公众开放日活动。     

基于视频分析的人群密集场所客流监控预警研究

为实现人群密集场所客流安全隐患早发现,辅助管理人员早决策,人群聚集风险区早疏散,提升对灾难的预见性和主动性。在国内外人群异常聚集监测预警现状分析基础上,对比分析得出监控视频分析技术是解决人群密集场所精准预警难题较为理想的解决方案;构建以视频智能分析的人群计数、密度估计、行人追踪、活动烈度识别为核心技术的人群密集场所风险预警技术框架;将该技术框架应用到某大型商圈的商业街区,获得监控区域内的人群总数、密度分布、行人轨迹和异常活动等特征。结果表明:提出的基于视频分析的人群密集场所风险预警技术框架可为城市大型商圈、交通枢纽、大型活动场所等城市公共场所的安全管理提供参考和借鉴。     

县级环境监测站垂直管理后工作思考

简要分析了县级环境监测站在监测监察执法垂直管理制度改革后面临的问题,并针对问题提出建议。     

Can we gain precision by sampling with probabilities proportional to size in surveying recent landscape changes in the Netherlands?

Seventy-two squares of 100 ha were selected by stratified random sampling with probabilities proportional to size (pps) to survey landscape changes in the period 1996–2003. The area of the plots times the urbanization pressure was used as a size measure. The central question of this study is whether the sampling with probabilities proportional to size leads to gain in precision compared to equal probability sampling. On average 1.03 isolated buildings per 100 ha have been built, while 0.90 buildings per 100 ha have been removed, leading to a net change of 0.13 building per 100 ha. The area with unspoiled natural relief has been reduced by 2.3 ha per 100 ha, and the length of linear relicts by 137 m per 100 ha. On average 74 m of linear green elements have been planted per 100 ha, while 106 m have been removed, leading to a net change of −31 m per 100 ha. For the state variables ‘unspoiled natural relief', ‘ linear relicts', ‘removed linear green elements', and ‘new – removed linear green elements' there is a gain in precision due to the pps-sampling. For the remaining state variables there is no gain or even a loss of precision (`new buildings', ‘removed buildings', ‘new – removed buildings', ‘new linear green elements'). Therefore, if many state variables must be monitored or when interest is not only in the change but also in the current totals, we recommend to keep things simple, and to select plots with equal probability.