Interventions for Reducing Extinction Risk in Chytridiomycosis‐Threatened Amphibians

Wildlife diseases pose an increasing threat to biodiversity and are a major management challenge. A striking example of this threat is the emergence of chytridiomycosis. Despite diagnosis of chytridiomycosis as an important driver of global amphibian declines 15 years ago, researchers have yet to devise effective large‐scale management responses other than biosecurity measures to mitigate disease spread and the establishment of disease‐free captive assurance colonies prior to or during disease outbreaks. We examined the development of management actions that can be implemented after an epidemic in surviving populations. We developed a conceptual framework with clear interventions to guide experimental management and applied research so that further extinctions of amphibian species threatened by chytridiomycosis might be prevented. Within our framework, there are 2 management approaches: reducing Batrachochytrium dendrobatidis (the fungus that causes chytridiomycosis) in the environment or on amphibians and increasing the capacity of populations to persist despite increased mortality from disease. The latter approach emphasizes that mitigation does not necessarily need to focus on reducing disease‐associated mortality. We propose promising management actions that can be implemented and tested based on current knowledge and that include habitat manipulation, antifungal treatments, animal translocation, bioaugmentation, head starting, and selection for resistance. Case studies where these strategies are being implemented will demonstrate their potential to save critically endangered species. Intervenciones para Reducir el Riesgo de Extinción en Anfibios Amenazados por la Quitridiomicosis     

Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

Geography and Recovery under the U.S. Endangered Species Act

Abstract: The U.S. Endangered Species Act (ESA) defines an endangered species as one “at risk of extinction throughout all or a significant portion of its range.” The prevailing interpretation of this phrase, which focuses exclusively on the overall viability of listed species without regard to their geographic distribution, has led to development of listing and recovery criteria with fundamental conceptual, legal, and practical shortcomings. The ESA's concept of endangerment is broader than the biological concept of extinction risk in that the “esthetic, ecological, educational, historical, recreational, and scientific” values provided by species are not necessarily furthered by a species mere existence, but rather by a species presence across much of its former range. The concept of “significant portion of range” thus implies an additional geographic component to recovery that may enhance viability, but also offers independent benefits that Congress intended the act to achieve. Although the ESA differs from other major endangered‐species protection laws because it acknowledges the distinct contribution of geography to recovery, it resembles the “representation, resiliency, and redundancy” conservation‐planning framework commonly referenced in recovery plans. To address representation, listing and recovery standards should consider not only what proportion of its former range a species inhabits, but the types of habitats a species occupies and the ecological role it plays there. Recovery planning for formerly widely distributed species (e.g., the gray wolf [Canis lupus]) exemplifies how the geographic component implicit in the ESA's definition of endangerment should be considered in determining recovery goals through identification of ecologically significant types or niche variation within the extent of listed species, subspecies, or “distinct population segments.” By linking listing and recovery standards to niche and ecosystem concepts, the concept of ecologically significant type offers a scientific framework that promotes more coherent dialogue concerning the societal decisions surrounding recovery of endangered species.     

基于大气被动式采样的人体头发中类二(口恶)英多氯联苯暴露的途径

本研究通过分析采集自云南省开远市的13个树皮混合样品和13个相应的头发混合样品中DL-PCBs的水平、同族体分布及相关性,研究了当地人群对DL-PCBs的主要暴露途径.结果表明,云南开远树皮和头发样品中DL-PCBs的含量分别为4.0~88.9 pg·g^-1和4.1~19.3 pg·g^-1,其在当地环境和人体中的污染程度均较轻.树皮和头发样品中主要的DL-PCB同族体均是PCB-118,分别占总含量的48%和61%.树皮样品中DL-PCBs的各同族体具有相同的源,其主要的来源可能是大气的长距离输移.云南开远市居民头发中的PCBs可能来源于内部暴露和外部暴露的综合作用,其中外部暴露对低氯代PCBs的贡献要高于高氯代PCBs.     

后处理设施给水系统可靠性的GO法研究

后处理设施给水系统是后处理设施重要的公用系统,对后处理设施的稳定、安全运行至关重要.给水系统的可靠性需要深入分析,应用GO法进行了研究.获得了给水系统的平均故障概率、最小割集、重要度等可靠性指标.结果表明,给水系统的可靠性比较高,符合单一故障准则,二阶最小割集对系统故障的贡献最大,应该采取措施予以消除.进一步深入对比分析GO法与故障树法,结果显示,对于给水系统的可靠性分析,GO法有建模容易且图形简洁的优点.     

土壤pH、Eh对土壤-苦丁茶树系统中铅分布的影响

以苫丁茶冬青(Ilex kudingcha C.J.Tseng)扦插苗(15个月生)进行盆栽实验,通过土施H2SO4、Ca(OH)2和复合肥,改变土壤pH和氧化还原电位(Eh),研究土壤pH、Eh条件对土壤-苦丁茶树系统中铅分布的影响.结果表明:在所研究的土壤pH范围内,从酸性到碱性变化,铅在土壤中含量分布趋于减少,在...     

基于增强回归树的城市PM2.5日均值变化分析:以常州为例

利用2014年12月至2015年11月常州市区6个国控监测站空气污染物浓度逐时数据,分析了PM_(2.5)浓度季节变化特征,采用增强回归树模拟分析了PM10、4种气态污染物和7个气象因子对ρ(PM_(2.5))日变化的贡献.结果表明,常州市区PM_(2.5)污染季节差异明显,冬季污染严重且持续时间长,夏季污染较轻.四季ρ(PM_(2.5))空间分布特征存在一定差异,但各季内不同监测站差异较小.增强回归树对ρ(PM_(2.5))日均值进行模拟和验证得到,训练数据的相关性为0.981,交叉验证的相关性为0.957.此外,模拟值与实测值的标准化平均偏差为1.80%,标准化平均误差为10.41%,可见模型拟合效果较好.PM10、气态污染物、气象因子和区域输送及扩散这4种影响类型对全年ρ(PM_(2.5))日均值差异的贡献率分别为23.4%、28%、36.2%和12.6%,表明在对ρ(PM_(2.5))日均值差异的影响上,气象因子二次形成一次源区域输送及扩散.在对ρ(PM_(2.5))日均值差异贡献率大于5%的因子中,ρ(PM_(2.5))日均值与PM10、相对湿度、CO和O3正相关,与温度、SO2和混合层高度负相关,与大气压和NO2关系较复杂.区域输送及扩散方面,东南风向、偏西风向和偏北风向等上风向周边城市的污染物输送对常州市区PM_(2.5)污染存在较大的负面影响.     

简易垃圾填埋场的安全分析

以福建省晋江市铜锣山垃圾填埋场为例,采用系统的安全分析方法--事故树分析法对该简易垃圾填埋场进行安全分析,发现铜锣山垃圾填埋场存在发生火灾、爆炸、垃圾堆体崩塌及因发生火灾或爆炸事故对邻近建筑物造成破坏的可能性,确定了影响该垃圾填埋场安全的主要因素,提出了有效的安全防范措施.     

FTA在城市控制爆破工程事故中的运用

城市控制爆破工程采用电雷管网路起爆,极易发生爆破事故.运用FTA方法,编制了爆破事故树,并进行了定性分析.结合工程实际,提出了爆破事故的具体预防措施,更依法采取了爆破安全管理措施.