Using interview surveys and multispecies occupancy models to inform vertebrate conservation

Species distribution data are an essential biodiversity variable requiring robust monitoring to inform wildlife conservation. Yet, such data remain inherently sparse because of the logistical challenges of monitoring biodiversity across broad geographic extents. Surveys of people knowledgeable about the occurrence of wildlife provide an opportunity to evaluate species distributions and the ecology of wildlife communities across large spatial scales. We analyzed detection histories of 30 vertebrate species across the Western Ghats biodiversity hotspot in India, obtained from a large-scale interview survey of 2318 people who live and work in the forests of this region. We developed a multispecies occupancy model that simultaneously corrected for false-negative (non-detection) and false-positive (misidentification) errors that interview surveys can be prone to. Using this model, we integrated data across species in composite analyses of the responses of functional species groups (based on disturbance tolerance, diet, and body mass traits) to spatial variation in environmental variables, protection, and anthropogenic pressures. We observed a positive association between forest cover and the occurrence of species with low tolerance of human disturbance. Protected areas were associated with higher occurrence for species across different functional groups compared with unprotected lands. We also observed the occurrence of species with low disturbance tolerance, herbivores, and large-bodied species was negatively associated with developmental pressures, such as human settlements, energy production and mining, and demographic pressures, such as biological resource extraction. For the conservation of threatened vertebrates, our work underscores the importance of maintaining forest cover and reducing deforestation within and outside protected areas, respectively. In addition, mitigating a suite of pervasive human pressures is also crucial for wildlife conservation in one of the world's most densely populated biodiversity hotspots.     

环境中新型阻燃剂检测技术研究进展

新型阻燃剂(NFRs)是传统阻燃剂受到严格管控后的推广替代品,主要包括新型溴代阻燃剂(NBFRs)、新型氯代阻燃剂(NCFRs)和有机磷酸酯阻燃剂(OPFRs)等。NFRs是一类新污染物,大多属于持久性有机污染物。目前,已有多种NFRs在世界各地被检出,引起各国的普遍关注,环境中NFRs的来源及迁移转化规律也由此成为新的研究热点。通过综述环境样品中NFRs检测技术在提取、净化和仪器检测等方面的国内外研究现状,讨论了各种分析技术的特点,分析了NFRs分析过程的质量控制与质量保证问题,展望了该领域未来的发展趋势。     

基于特征提取的输油管道泄漏系数预测*

为准确预测管道泄漏系数,估计管道泄漏量,以基于瞬变流方法的模拟数据为例,建立多个管道泄漏系数预测模型(多层感知机、长短期记忆网络、随机森林、支持向量机以及K近邻回归),综合考虑管道流量和压力数据特点,提出序列提取法和均值提取法2种管道时序数据预处理方法,模型评价指标为相关系数（R2）和平均绝对百分比误差（MAPE）。研究结果表明:随机森林和多层感知机的抗噪性较强,在5%的噪声影响下,模型准确度下降幅度较小;均值提取法去噪功能较好,可在一定程度上降低噪声影响;基于均值提取法的多层感知机模型效果相对较好,R2为0.997 5,MAPE为1.599%,研究结果可为准确预测管道泄漏系数、估计泄漏量提供指导。     

基于电磁波传播的采空区AMT探测与异常快速圈定*——以云南东川烂泥坪铜矿区为例

为了研究电磁波的传播在采空区界面上发生反射和透射后对音频大地电磁测深（简称AMT）勘探的影响,模拟采空区推导出基于4层介质模型的阻抗计算公式。经过计算分析,采空区会引起AMT的电阻率和阻抗参数在高频段出现震荡,可利用高值异常波动来定性判断采空区。根据东川烂泥坪铜矿已知采空区的AMT探测资料,采空区引起视电阻率和阻抗在15~30 kHz频段出现高值异常,相对于视电阻率资料,阻抗对异常的反映更明显。提出采用阻抗平均法和最大阻抗法计算相对偏差,通过高值异常对采空区进行快速圈定。研究结果表明:2种方法得到的结果较为相似,基本符合实际采空区的分布情况,而最大阻抗法更适合采空区AMT探测使用。     

填埋场衬层渗漏的电学法检测研究进展

综述了几种常用的填埋场渗漏检测方法,指出电学法已成为填埋场不同运行阶段（施工期和运营期）渗漏检测的主流方法。分析了各阶段电学检测方法的适用条件和优缺点,在防渗膜铺设阶段,常利用双电极法或电极-偶极子法进行施工完整性检测;在填埋场运营期间,根据场地实际情况可以选择电极格栅法、基于物联网的监测预警云平台、阵列式偶极子法或高密度电法进行膜渗漏检测及长期监测。     

污水生物处理建模水质数据误差来源分析与影响评价

为进一步提高国内基础建模数据质量,降低建模实践中的数据清洗难度,本研究以北京龙庆再生水厂生物建模过程中的实际数据问题为例,基于数理统计理论及国内污水水质特征分别构建误差来源分析方法与误差影响评价方法.通过设计补充采样与实验排查方案,成功识别数据误差来源并实现不同类型误差对数据准确性的影响量化评价.研究结果表明,污水处理厂日常的取样与化验过程中产生的随机误差不可忽视,特别是当大量随机误差存在时,对数据总体造成的波动影响无法通过数据量的积累而消除;而不同的采样位置与不当的样品保存方式则会引起水质发生变化,由此产生的系统误差将导致测量结果长期偏高/偏低.因此,在依赖人工测量数据进行建模的国内实践中,应首先对历史数据进行误差检验,再进行必要的建模补充采样,以避免补充数据质量受相同误差影响,减少非必要的人力、物力浪费.     

基于VPL的输油管道实时泄漏检测系统

针对现有管道泄漏检测技术在管道微小泄漏检测和油品泄漏损失计算方面存在的不足,基于流体动力学和容量守恒原理,开发基于VPL（Visual Pipeline）的输油管道实时泄漏检测系统。建立管道模拟平台,通过组态编辑器、图像界面、管道工作室和SCADA 接口,开展输油管道实时泄漏检测、定位与分析,实现管道实时泄漏检测、报警,以及泄漏量的定量计算。现场测试结果显示,所开发的输油管道泄漏检测系统最小泄漏检出率为0.7%,泄漏点定位精度为96.96%,泄漏量计算准确率为94.42%。研究结果表明:基于VPL的输油管道实时泄漏检测系统漏报、误报率低,检测定位精度较高,尤其对于微小泄漏优势明显;同时,该系统能够实时定量计算油品泄漏损失,可以用于输油管道泄漏检测与应急辅助决策。     

环境中有机紫外吸收剂前处理及仪器分析方法研究进展

有机紫外吸收剂(OUVs)是广泛应用于个人护理品及工业产品的一种光稳定剂,也是一种新型"准"持久性有机污染物。由于环境样品基质复杂,且OUVs种类多、含量低,快速高效的样品前处理及准确灵敏的检测方法是提高OUVs监测精准度的基础。综述了自2005年以来环境样品中OUVs的常规前处理方法及分析方法。首先,在介绍水体、沉积物、生物样品前处理方法应用的基础上,分析了富集填料、洗脱剂、净化方法等实验条件对回收率的影响,目前在水体、沉积物、生物样品中,OUVs的回收率分别为14%~133.7%、30%~183%、46%~128%。其次,总结了质谱技术在OUVs分析中的应用,表明OUVs检测方法已经由传统的气相色谱-单四极杆联用逐渐过渡到液相色谱-串联质谱联用,并且着重阐述了离子源对OUVs信号强度影响的重要性。最后,结合OUVs监测现状,展望了环境样品中OUVs监测分析方法的发展趋势。     

Quantifying the probability of detection of wild ungulates with the Judas technique

The Judas technique is often used in control or eradication of particular vertebrate pests. The technique exploits the tendency of individuals to form social groups. A radio collar is affixed to an individual and its subsequent monitoring facilitates the detection of other conspecifics. Efficacy of this technique would be improved if managers could estimate the probability that a Judas individual would detect conspecifics. To calculate this probability, we estimated association rates of Judas individuals with other Judas individuals, given the length of time the Judas has been deployed. We developed a simple model of space-use for individual Judas animals and constrained detection probabilities to those specific areas. We then combined estimates for individual Judas animals to infer the probability that a wild individual could be detected in an area of interest via Judas surveillance. We illustrated the method by using data from a feral goat eradication program on Isla Santiago, Galápagos, and a feral pig eradication program on Santa Cruz Island, California. Association probabilities declined as the proximity between individual areas of use of a Judas pair decreased. Unconditional probabilities of detection within individual areas of use averaged 0.09 per month for feral pigs and 0.11 per month for feral goats. Probabilities that eradication had been achieved, given no detections of wild conspecifics, and an uninformative prior probability of eradication were 0.79 (90% CI 0.22–0.99) for feral goats and 0.87 (90% CI 0.44–1.0) for feral pigs. We envisage several additions to the analyses used that could improve estimates of Judas detection probability. Analyses such as these can help managers increase the efficacy of eradication efforts, leading to more effective effects to restore native biodiversity.