Modeling population effects of the Deepwater Horizon oil spill on a long-lived species

The 2010 Deepwater Horizon (DWH) oil spill exposed common bottlenose dolphins (Tursiops truncatus) in Barataria Bay, Louisiana to heavy oiling that caused increased mortality and chronic disease and impaired reproduction in surviving dolphins. We conducted photographic surveys and veterinary assessments in the decade following the spill. We assigned a prognostic score (good, fair, guarded, poor, or grave) for each dolphin to provide a single integrated indicator of overall health, and we examined temporal trends in prognostic scores. We used expert elicitation to quantify the implications of trends for the proportion of the dolphins that would recover within their lifetime. We integrated expert elicitation, along with other new information, in a population dynamics model to predict the effects of observed health trends on demography. We compared the resulting population trajectory with that predicted under baseline (no spill) conditions. Disease conditions persisted and have recently worsened in dolphins that were presumably exposed to DWH oil: 78% of those assessed in 2018 had a guarded, poor, or grave prognosis. Dolphins born after the spill were in better health. We estimated that the population declined by 45% (95% CI 14–74) relative to baseline and will take 35 years (95% CI 18–67) to recover to 95% of baseline numbers. The sum of annual differences between baseline and injured population sizes (i.e., the lost cetacean years) was 30,993 (95% CI 6607–94,148). The population is currently at a minimum point in its recovery trajectory and is vulnerable to emerging threats, including planned ecosystem restoration efforts that are likely to be detrimental to the dolphins’ survival. Our modeling framework demonstrates an approach for integrating different sources and types of data, highlights the utility of expert elicitation for indeterminable input parameters, and emphasizes the importance of considering and monitoring long-term health of long-lived species subject to environmental disasters. Article impact statement: Oil spills can have long-term consequences for the health of long-lived species; thus, effective restoration and monitoring are needed.     

基于模糊集理论和专家知识的互因失效分析

针对传统方法对系统内部各部件互相影响研究较少的现状,提出了互因失效数学模型。以陀螺仪信号处理模块为对象,用互因失效模型进行分析,利用模糊集理论和专家知识确定互因相关系数,计算了各部件的互因失效率并进行排序,找出了系统薄弱环节。     

靶场训练环境构设效果评估方法研究

目的 针对靶场基地化训练战场环境构设效果难以定量评估的实际情况,研究定量评估方法,开展效果评估,辅助支撑改进环境构设方案筹划与课目实施。方法 分析环境构设的内容,确定效果评估的对象,构建环境构设效果评估指标体系,采用层次分析法计算权重取值,采用专家打分法确定指标取值,最终得出效果评估值,并给出环境构设效果等级。结果 以某次基地化训练实践活动为例,通过以上方法评估战场环境构设活动效果,验证了该评估方法的可行性。结论 该评估方法实际可行,提供了环境构设效果定量评估的思路,对改进战场环境构设活动有较强的指导意义。     

基于规则的露天矿土地复垦适宜性评价专家系统

根据土地复垦适宜性评价的主导因子法，利用CLIPS专家系统语言设计了基于规则的土地复垦适宜性评价专家系统，为露天煤矿土地复垦的土地利用方向提供了决策工具。     

遥感技术在察布查尔县土壤侵蚀调查中的应用

依据陆地卫星TM遥感影像资料,在ERDAS软件下,通过室内判读与野外调查相结合的方法,解译出土地利用类型图、植被覆盖度图、坡度图。在建立知识库的基础上,利用土壤侵蚀专家分类系统,快速获得察布查尔县土壤侵蚀分类分级状况,为今后该区域的水土保持工作提供参考和依据。     

活性污泥处理专家系统的构建

将活性污泥污水处理系统的预测知识、异常诊断知识及分析和控制知识进行整合，并利用基于Rough集的数据挖掘方法梳理、约简知识库，建立专家系统，实现对污水生物处理异常预测及专家诊断等功能。用VC．NET将CLIPS专家系统嵌入到基于网络的污水处理实时控制和数据采集实验平台系统中。通过多传感器的数据融合技术，经过对在线实时采集实验数据的分析，综合判断活性污泥的状态参数及其对系统的影响。     

基于大坝安全鉴定和专家经验的病险程度评价技术

针对目前我国大坝安全鉴定办法在病险水库严重程度评价中的不足,提出一种大坝病险严重程度的评价方法。以现行大坝安全鉴定技术和专家经验为基础,将水库大坝病险分为五级;提出病险严重性分级以及定性定量转换原则;建立防洪能力、渗流、稳定、变形裂缝、抗震能力、金属结构、工程质量、运行管理、现场检查9个评价大坝病险程度因素的指标体系以及分级和定性-定量转换方法;采用线性加权和法进行病险严重程度综合评价;研究并提出病险程度综合评价影响系数模型以及两种权重确定方法;建立了一套较为完整的病险程度综合评价体系。通过举例分析,提供了使用该方法的途径和过程,表明该方法的可操作性,可行性和实用性。     

上海环境空气质量预报考核评分方法研究和应用

根据环境空气质量新标准和技术规范的要求,结合上海空气质量预报工作的实际,制定了一套环境空气质量预报考核评分方法,为空气质量预报结果的考核和预报工作的改进提供了定量依据,并在上海得到实际应用。该方法基于空气质量指数评价方法,重点对未来24 h的分段预报（当日夜间20：00至次日6：00、次日上午6：00—12：00、次日下午12：00—20：00）结果进行考核,区分优级时段和非优级时段,侧重对污染日的评估并突出首要污染物的评分权重,并增加级别变化趋势的描述评分和污染加分项。     

国外湖泊营养物基准向标准转化方法对我国的启示

由于我国现行水质标准中关于富营养化指标的制定缺乏基于营养物基准的分析研究,急需通过借鉴国外经验,找出适宜方法。介绍了美国和其他发达国家的营养物标准体系,回顾了美国国家环境保护局(US EPA)及各州和部落采用的不同营养物标准的制定程序和技术方法,重点分析了国外营养物标准指标的选取和确定标准值的方法。从湖泊营养物基准入手,探讨了制定我国湖泊营养物标准的方法及技术。     

Projecting biodiversity benefits of conservation behavior-change programs

Biodiversity loss is driven by human behavior, but there is uncertainty about the effectiveness of behavior-change programs in delivering benefits to biodiversity. To demonstrate their value, the biodiversity benefits and cost-effectiveness of behavior changes that directly or indirectly affect biodiversity need to be quantified. We adapted a structured decision-making prioritization tool to determine the potential biodiversity benefits of behavior changes. As a case study, we examined two hypothetical behavior-change programs––wildlife gardening and cat containment––by asking experts to consider the behaviors associated with these programs that directly and indirectly affect biodiversity. We assessed benefits to southern brown bandicoot (Isoodon obesulus) and superb fairy-wren (Malurus cyaneus) by eliciting from experts estimates of the probability of each species persisting in the landscape given a range of behavior-change scenarios in which uptake of the behaviors varied. We then compared these estimates to a business-as-usual scenario to determine the relative biodiversity benefit and cost-effectiveness of each scenario. Experts projected that the behavior-change programs would benefit biodiversity and that benefits would rise with increasing uptake of the target behaviors. Biodiversity benefits were also predicted to accrue through indirect behaviors, although experts disagreed about the magnitude of additional benefit provided. Scenarios that combined the two behavior-change programs were estimated to provide the greatest benefits to species and be most cost-effective. Our method could be used in other contexts and potentially at different scales and advances the use of prioritization tools to guide conservation behavior-change programs.