Characterizing species co-occurrence patterns of imperfectly detected stream fishes to inform species reintroduction efforts

Species reintroduction efforts can improve the recovery of imperiled species, but successful implementation of this conservation strategy requires a thorough understanding of the abiotic and biotic factors influencing species viability. Species interactions are especially understudied, in particular by omitting the effect of imperfect detection on negative, neutral, or positive associations within a community. Using repeat surveys from 5 southern Ontario, Canada, Great Lakes tributaries, we quantified species co-occurrence patterns with the eastern sand darter (ESD) (Ammocrypta pellucida), listed as federally threatened, and characterized how imperfect detection during sampling can influence inference regarding these relationships. We used a probabilistic framework that included 3 approaches of increasing complexity: probabilistic co-occurrence analysis ignoring imperfect detection; single-species occupancy models with subsequent co-occurrence analysis; and 2-species occupancy models. We then used our occupancy models to predict suitable sites for potential future reintroduction efforts while considering the influence of negative species interactions. Based on the observed data, ESD showed several positive associations with co-occurring species; however, species associations differed when imperfect detection was considered. Specifically, a negative association between ESD and rosyface shiner (Notropis rubellus) was observed only after accounting for imperfect detection in the Grand River. Alternatively, positive associations in the Grand River between ESD and northern hogsucker (Hypentelium nigricans) and silver shiner (Notropis photogenis) were observed regardless of whether imperfect detection was accounted for. Our models predicted several potential reintroduction sites for ESD in formerly occupied watersheds with high levels of certainty. Overall, our results demonstrate the importance of investigating imperfect detection and species co-occurrence when planning reintroduction efforts.     

Method for identifying errors in chemical process development and design base on accidents knowledge

It has been claimed that the high accident rate in the chemical process industry is due to poor dissemination of accident knowledge that affects directly the level of learning from accidents. In response to this situation, this paper utilized past accident knowledge as a basis to develop a safety oriented design tool whereby the accident information were directly disseminated into plant design. The method was developed based on our previous accident analysis of design error in which the common design errors were ranked in accordance to their frequency and its origins during normal plant design project. Based on the design error ranking and its origin at a specific design phases, a method for design error detection is proposed. The method is expected to be able to identify the possible design error and its causes throughout chemical process development and design. The main objective is to trigger safe design thinking at the specific design phases so that appropriate action for risk reduction could be timely implemented. The Bhopal and BP Texas tragedies are used as case studies to test and verify the method. The proposed method can detect up to 74% of design errors.     

Mechanistic understanding of human–wildlife conflict through a novel application of dynamic occupancy models

Crop and livestock depredation by wildlife is a primary driver of human–wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models to elephant crop depredation data from India between 2005 and 2011 to estimate crop depredation occurrence and model its underlying dynamics as a function of spatiotemporal covariates while accounting for imperfect detection of conflicts. The probability of detecting conflicts was consistently <1.0 and was negatively influenced by distance to roads and elevation gradient, averaging 0.08–0.56 across primary periods (distinct agricultural seasons within each year). The probability of crop depredation occurrence ranged from 0.29 (SE 0.09) to 0.96 (SE 0.04). The probability that sites raided by elephants in primary period t would not be raided in primary period t + 1 varied with elevation gradient in different seasons and was influenced negatively by mean rainfall and village density and positively by distance to forests. Negative effects of rainfall variation and distance to forests best explained variation in the probability that sites not raided by elephants in primary period t would be raided in primary period t + 1. With our novel application of occupancy models, we teased apart the spatiotemporal drivers of conflicts from factors that influence how they are observed, thereby allowing more reliable inference on mechanisms underlying observed conflict patterns. We found that factors associated with increased crop accessibility and availability (e.g., distance to forests and rainfall patterns) were key drivers of elephant crop depredation dynamics. Such an understanding is essential for rigorous prediction of future conflicts, a critical requirement for effective conflict management in the context of increasing human–wildlife interactions.     

Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat

Predicting a species’ distribution can be helpful for evaluating management actions such as critical habitat designations under the U.S. Endangered Species Act or habitat acquisition and rehabilitation. Whooping Cranes (Grus americana) are one of the rarest birds in the world, and conservation and management of habitat is required to ensure their survival. We developed a species distribution model (SDM) that could be used to inform habitat management actions for Whooping Cranes within the state of Nebraska (U.S.A.). We collated 407 opportunistic Whooping Crane group records reported from 1988 to 2012. Most records of Whooping Cranes were contributed by the public; therefore, developing an SDM that accounted for sampling bias was essential because observations at some migration stopover locations may be under represented. An auxiliary data set, required to explore the influence of sampling bias, was derived with expert elicitation. Using our SDM, we compared an intensively managed area in the Central Platte River Valley with the Niobrara National Scenic River in northern Nebraska. Our results suggest, during the peak of migration, Whooping Crane abundance was 262.2 (90% CI 40.2?3144.2) times higher per unit area in the Central Platte River Valley relative to the Niobrara National Scenic River. Although we compared only 2 areas, our model could be used to evaluate any region within the state of Nebraska. Furthermore, our expert‐informed modeling approach could be applied to opportunistic presence‐only data when sampling bias is a concern and expert knowledge is available.     

Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy‐based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy‐based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per‐visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. Poder de Análisis Espacialmente Explícito para el Monitoreo Basado en Ocupación del Glotón (Gulo gulo) en las Montañas Rocallosas de Estados Unidos     

空气中BTEX检测方法研究进展

BTEX（苯系物）作为空气中的一种痕量组分,主要包括苯、甲苯、乙苯、间-二甲苯、对-二甲苯、邻二甲苯,这些物质可影响人体健康和环境空气质量.分析和探讨了环境空气中BTEX常用的采样、前处理和检测方法,并列举了各方法的国内外应用实例.BTEX采样方法主要包括以下2种:①吸附管采样法,其采样器体积小、便于携带,但易造成穿透现象,样品易损失.②空气采样法,其操作简单、重复使用率高,但清洗复杂、价格较高.BTEX前处理方法主要包括以下3种:①固相微萃取法,其可减少样品与空气接触的机会,自动化程度较高,但难以实现样品的多次分析.②溶剂解析法,因其对环境影响较大,所以应用较少.③热脱附法,其常采用二级热脱附实现样品富集和浓缩,操作过程简单,设备体积相对较大,其升温和降温系统是影响前处理速度和效果的关键.BTEX检测方法主要包括:①质子转移反应质谱法,其灵敏度高,但因其价格昂贵应用较少.②气相色谱-光离子化检测法,其设备体积小巧常用于外场监测中.③差分吸收光谱法、直接空气进样质谱法、低压化学电离质谱法、大气压化学电离质谱法、固相微萃取-气相色谱法、吸附/热脱附-气相色谱-火焰离子检测法/质谱检测法等.研究显示,空气中BTEX的分析方法应根据实际应用条件来确定,在保证分析仪器灵敏度和精确度的基础上,开发外场检测的便携式自动在线分析仪器,提高仪器便携性、自动化、智能化,更好地满足各项标准和部门管理的需求.      

基于通勤时间距离的LE污水处理过程故障检测方法

污水处理过程的性能监测与故障诊断,对于保障污水处理过程正常运行及保证出水质量达标具有重要意义.针对污水处理过程数据具有非线性、不确定性及且易受随机噪声影响等特征,提出了一种新的基于通勤时间距离的LE流形学习算法实现对复杂过程数据的特征提取.改进算法采用通勤时间距离方式进行样本间的相似度衡量并构造邻域图,理论分析和仿真测试表明改进算法可有效克服基本LE算法的邻域参数敏感问题并提高了算法的鲁棒性.将基于通勤时间距离的LE流形学习算法用于污水处理过程故障检测建模,在低维流形子空间构造综合统计量进行过程监测.应用结果表明,与基于PCA方法和LE方法的故障检测模型相比,基于改进算法的故障检测模型可及时探测故障的发生,具有较低的故障漏报率和故障误报率.为污水处理等复杂工业过程的故障监测提供了一种可行的解决方案.     

泄漏检测与修复(LDAR)检测数据准确性评估方法研究

泄漏检测与修复技术(LDAR)是控制石化企业设备与管线泄漏的最佳可行技术,检测数据准确度对于企业核算VOCs排放量及环境保护主管部门进行VOCs排污费征收和排污许可证管理至关重要.针对中国石化企业工艺装置特点和LDAR检测数据特征,设计了一套LDAR检测数据准确性评估方法,并运用该方法对24套石化装置的LDAR检测数据准确性进行抽测评估.结果表明该方法可以直观反映企业LDAR检测数据准确度,客观体现不同企业、不同装置在LDAR检测管理水平上的差异.     

电力通信机房监控系统对室内空气净化程度检测研究

为解决当前电力通信机房室内空气监控系统抗干扰能力弱,室内空气净化检测精度低等问题.设计了基于ARM的电力通信机房室内空气监控系统,以提高室内空气净化检测精度.选用DHT11温度传感器,引入专用数字单元采集技术和温度传感技术,实现空气温度监控.安设 HS1101传感器,监控空气湿度.采用OLED液晶显示作为系统的可视化窗口,完成电力通信机房监控系统设计.实验结果表明,该系统能耗低,抗干扰能力强,为准确检测室内空气净化程度起到重要作用.     

Measurement method for objective cyclist behavior parameters

Abstract

Objective: The objective of this research is to study the feasibility of measuring behavioral indicators that reflect effects of infrastructure and interaction with other road users.

Methods: An observation study was performed using 6 cameras above a separated cycle path next to a road which included a crossing with both cyclists and cars. A learning method based on Single Shot MultiBox Detector was applied to automatically detect the cyclists, and cyclist tracks were determined. Next, kinematic parameters were calculated from the cyclists’ tracks. Amongst others, the cyclists’ intensity, speed, position on the cycle path, and the distance to each other were analyzed for a busy period as well as for a quiet period of the day.

Results: With the measurement method developed in this study it is possible to analyze the cyclists’ intensity, the space they use at the cycle path, their average velocity, waiting times, the space and velocity amongst each other, and red light negation. However, collisions were not seen in the dataset analyzed, and the data is not sufficiently accurate to analyze sudden braking actions.

Conclusion: It can be concluded that the developed measurement method provides insight of the cyclists’ behavior in such a way that it can already be used for obtaining information to make changes to the infrastructure that will improve the comfort and safety of cyclists. The method could be further developed for doing qualitative comfort and safety analyses, and for doing analyses of the interaction between various types of road participants.