Effects of white‐nose syndrome on regional population patterns of 3 hibernating bat species

Hibernating bats have undergone severe recent declines across the eastern United States, but the cause of these regional‐scale declines has not been systematically evaluated. We assessed the influence of white‐nose syndrome (an emerging bat disease caused by the fungus Pseudogymnoascus destructans, formerly Geomyces destructans) on large‐scale, long‐term population patterns in the little brown myotis (Myotis lucifugus), the northern myotis (Myotis septentrionalis), and the tricolored bat (Perimyotis subflavus). We modeled population trajectories for each species on the basis of an extensive data set of winter hibernacula counts of more than 1 million individual bats from a 4‐state region over 13 years and with data on locations of hibernacula and first detections of white‐nose syndrome at each hibernaculum. We used generalized additive mixed models to determine population change relative to expectations, that is, how population trajectories differed with a colony's infection status, how trajectories differed with distance from the point of introduction of white‐nose syndrome, and whether declines were concordant with first local observation of the disease. Population trajectories in all species met at least one of the 3 expectations, but none met all 3. Our results suggest, therefore, that white‐nose syndrome has affected regional populations differently than was previously understood and has not been the sole cause of declines. Specifically, our results suggest that in some areas and species, threats other than white‐nose syndrome are also contributing to population declines, declines linked to white‐nose syndrome have spread across large geographic areas with unexpected speed, and the disease or other threats led to declines in bat populations for years prior to disease detection. Effective conservation will require further research to mitigate impacts of white‐nose syndrome, renewed attention to other threats to bats, and improved surveillance efforts to ensure early detection of white‐nose syndrome.     

Thermal Physiology,Disease, and Amphibian Declines on the Eastern Slopes of the Andes

Rising temperatures, a widespread consequence of climate change, have been implicated in enigmatic amphibian declines from habitats with little apparent human impact. The pathogenic fungus Batrachochytrium dendrobatidis (Bd), now widespread in Neotropical mountains, may act in synergy with climate change causing collapse in thermally stressed hosts. We measured the thermal tolerance of frogs along a wide elevational gradient in the Tropical Andes, where frog populations have collapsed. We used the difference between critical thermal maximum and the temperature a frog experiences in nature as a measure of tolerance to high temperatures. Temperature tolerance increased as elevation increased, suggesting that frogs at higher elevations may be less sensitive to rising temperatures. We tested the alternative pathogen optimal growth hypothesis that prevalence of the pathogen should decrease as temperatures fall outside the optimal range of pathogen growth. Our infection‐prevalence data supported the pathogen optimal growth hypothesis because we found that prevalence of Bd increased when host temperatures matched its optimal growth range. These findings suggest that rising temperatures may not be the driver of amphibian declines in the eastern slopes of the Andes. Zoonotic outbreaks of Bd are the most parsimonious hypothesis to explain the collapse of montane amphibian faunas; but our results also reveal that lowland tropical amphibians, despite being shielded from Bd by higher temperatures, are vulnerable to climate‐warming stress. Fisiología Termal, Enfermedades y Disminuciones de Anfibios en las Laderas Orientales de los Andes     

Impact of stratospheric volcanic aerosols on climate: Evidence for aerosol shortwave and longwave forcing in the Southeastern U.S.

Major volcanic eruptions inject massive amounts of dust and gases into the lower stratosphere and upper troposphere. Stratospheric volcanic aerosols can scatter incoming solar radiation to space, increasing planetary albedo, reducing the total amount of solar energy reaching the troposphere and the earth's surface, and decreasing the daytime maximum temperature (aerosol shortwave forcing). They can also absorb and scatter outgoing terrestrial longwave radiation, increasing the nighttime minimum surface temperature (longwave forcing). However, persuasive evidence of climate response to this forcing has thus far been lacking. Here we examine patterns of annual and seasonal variations in mean maximum and minimum temperature trend during the periods 1992–1994 and 1985–1987 relative to that during the period 1988–1990 at 47 stations in the southeastern U.S. for evidence of such climate responses. The stratospheric volcanic aerosol optical depths over the southeastern U.S. during the period 1985–1994 were inferred from the Stratospheric Aerosol and Gases Experiment (SAGE) 11 satellite extinction measurement. After the long-term trend signals are removed, it is shown that the dominant decreasing trend of mean maximum temperature and the dominant increasing trend of mean minimum temperature over periods 1992–1994 and 1985–1987 relative to that over the period 1988–1990 are consistent with the distribution of stratospheric volcanic aerosols and predictions from aerosol radiative forcing in the southeastern U.S.     

户外端子箱操作人因可靠性及其风险评价*

为正确评价人为因素对户外端子箱失效的影响,利用CREAM(Cognitive Reliability and Error Analysis Method)模型的共同绩效条件分析端子箱操作过程中人的行为机理以及行为可靠性因素;应用SLIM(Success Likelihood Index Method)模型计算人为失误概率,并采用比例故障模型计算户外端子箱自身的故障率;以某断路器端子箱为例进行验证。结果表明:研究案例的人为失误概率为1.56%,设备故障率为0.84%,系统的风险值为10.7%,系统的风险等级为3;从概率的角度说明事故发生原因中人为因素的影响更大。因此,从行为可靠性影响因素层面对人为失误概率进行调控,可使户外端子箱操作人因可靠性得到提高,系统的风险等级随之降低。     

大气扩散浓度估算在锅炉房烟囱高度计算中的应用

锅炉房的烟囱已从单纯的排气装置发展成为控制污染、保护环境的设备。因此烟囱高度的正确估算对于环境影响评价工作、建设单位都至关重要。结合唐山某城区集中供热锅炉房环境影响评价案例,利用大气扩散浓度公式估算锅炉房烟囱高度。在计算过程中,考虑了烟气流速及当地常年风向、风速、稳定度等污染气象特征,由正态分布模式导出的简化公式导出最大着地浓度与烟囱有效高度的平方成反比,从而计算出烟囱高度。另外还总结烟囱设计中应注意的一些问题,为建有锅炉房的建设项目环境影响评价工作提供参考。     

Local likelihood disease clustering: development and evaluation

This paper illustrates a method based on local likelihood (LL) for detecting disease clusters. The approach is based on estimating a lasso distance for each region: within which regions are considered to be clustered. An important advantage in implementing this approach is that it does not require any special Monte Carlo Markov Chain (MCMC) algorithm, e.g., reversible jump MCMC, which is essential in hidden Markov model approach. Another advantage is that extending the model to incorporate covariates is straightforward. We illustrate three ways of doing this by using Eastern Germany lip cancer data. By using simulated data, we have made a comparison with the BYM model [Besag et al. (1991) Annals of the Institute of Statistical Mathematics, 43, 1–59] and the mixture model [Lawson and Clark (2002) Disease Mapping and Risk Assessment for Public Health, Chapman and Hall]. We also did a limited examination of the ability of the LL model to recover true relative risk under different priors for lasso parameter. In order to check the edge effects, which has been overlooked in many spatial clustering models for disease mapping but deserves special attention as it lacks observable neighbors, we have adapted here a simple approach to observe the changes in relative risks when the edge regions are omitted. An erratum to this article is available at .     

基于微震活动性参数的矿山灾害风险性评价

微震灾害分级是判别及处理高风险采场的关键。为了预测并防治采空区失稳导致的灾害,结合用沙坝矿引进的IMS微震监测系统,首先统计矿山尺度的微震活动性特征,将主要采场进行分区。然后分析各分区的最大潜在震级及其重现时间、微震扩散率、微震劲度比、能量频次等特征。最后结合采场微震灾害风险性分级标准对各分区风险性进行分级。结果表明,综合考虑微震事件的能量分布特征、空间分布特征、时间分布特征进行灾害风险性分级的结果更为合理。     

Identifying factors affecting the safety of mid-block bicycle lanes considering mixed 2-wheeled traffic flow

Objective: Electric bikes (e-bikes) have been one of the fastest growing trip modes in Southeast Asia over the past 2 decades. The increasing popularity of e-bikes raised some safety concerns regarding urban transport systems. The primary objective of this study was to identify whether and how the generalized linear regression model (GLM) could be used to relate cyclists' safety with various contributing factors when riding in a mid-block bike lane. The types of 2-wheeled vehicles in the study included bicycle-style electric bicycles (BSEBs), scooter-style electric bicycles (SSEBs), and regular bicycles (RBs).

Methods: Traffic conflict technology was applied as a surrogate measure to evaluate the safety of 2-wheeled vehicles. The safety performance model was developed by adopting a generalized linear regression model for relating the frequency of rear-end conflicts between e-bikes and regular bikes to the operating speeds of BSEBs, SSEBs, and RBs in mid-block bike lanes.

Results: The frequency of rear-end conflicts between e-bikes and bikes increased with an increase in the operating speeds of e-bikes and the volume of e-bikes and bikes and decreased with an increase in the width of bike lanes. The large speed difference between e-bikes and bikes increased the frequency of rear-end conflicts between e-bikes and bikes in mid-block bike lanes. A 1% increase in the average operating speed of e-bikes would increase the expected number of rear-end conflicts between e-bikes and bikes by 1.48%. A 1% increase in the speed difference between e-bikes and bikes would increase the expected number of rear-end conflicts between e-bikes/bikes by 0.16%.

Conclusions: The conflict frequency in mid-block bike lanes can be modeled using generalized linear regression models. The factors that significantly affected the frequency of rear-end conflicts included the operating speeds of e-bikes, the speed difference between e-bikes and regular bikes, the volume of e-bikes, the volume of bikes, and the width of bike lanes. The safety performance model can help better understand the causes of crash occurrences in mid-block bike lanes.     

2017年最大降水对再生水受水河道径流组成的影响

再生水受水河道水文条件作为河流水生环境及生化反应重要控制因子,会受到丰水季降水汇入的影响.以潮白河典型受水河道——顺义段为例,通过丰水期前（2017-06-11）、降水中（2017-07-06）、降水后（2017-07-08、2017-07-09）河水中氢氧同位素特征和氯离子浓度的变化,识别地表径流组成对2017年最大日降水量（重现期3.3a）的响应,揭示河流汇水过程径流组成的时空差异及原因.结果表明,在降水初期,降水中氢氧同位素主要受雨量效应影响,后期微小变幅主要受水汽来源差异影响,整个河段接受降水的同位素值相近.降水后3 d内坡地汇流尚未停止,在各断面占比各异;坡地汇流占比沿程增加（2%~85.6%）,再生水占比沿程减少（90%~67%）,再生水通过优先通道到达下游断面.降水后3 d内SY01~SY05断面水量由坡地汇流、再生水、原位水组成,有明显的河网汇水过程,SY06~SY07断面水量由坡地汇流及原位水组成.     

基于小波和 EMD 的电阻探针监测信号自适应去噪

目的从监测信号中恢复有效腐蚀信息(长期变化趋势、周期性窄带尖峰),提出一种基于经验模态分解(Empirical Mode Decomposition,EMD)和小波阈值去噪(Wavelet Threshold Denoised,WTD)相结合的自适应去噪算法(EMD-WTD)。方法先将信号进行EMD分解,利用最大信息系数(Max Information Coefficient,MIC)判断噪声主导和有效信号主导信号分量的分界点,然后将噪声主导的信号分量进行自适应小波阈值去噪。最后以人工模拟信号和电阻探针监测信号进行验证。结果 EMD-WTD算法能有效去除噪声,信噪比可提升10 d B以上。结论与多个去噪算法相比,EMD-WTD算法能够更好地保留信号中周期性窄带尖峰信息,为后续准确建立电阻探针监测信号与环境之间的数学模型奠定了基础。