美军气象影响决策辅助系统实现方法 及应用

目的研究美军气象影响决策辅助系统发展现状。方法收集资料,对比分析。结果详细分析了两种美军的气象战术决策辅助系统,即综合天气影响辅助决策系统和目标探测器软件。结论天气条件对于军事行动的计划和实施都具有重要影响,而气象影响决策辅助系统可以帮助作战指挥官准确判断当前及未来的天气威胁,应选择合适的武器系统,优化武器系统效能的发挥。     

我国造纸工业对环境的污染及解决方法

本文论述造纸工业的主要污染源及解决造纸工业对环境污染问题的关键技术和方法, 提出我国造纸工业环境保护的基本对策,认为我国的造纸工业也能成为洁净工业。     

地铁人员可用疏散时间模拟

人员可用安全疏散时间是衡量公共场所安全性能的重要指标.为了能从定量风险分析的角度考察公共场所的安全疏散性能,引入蒙特卡罗模拟技术.选取天津小白楼地铁系统作为研究对象;建立极限状态方程以刻画地铁人员可用安全疏散时间;最后,通过Matlab提供的M语言编程,实现了蒙特卡罗模拟,得到了与极限状态方程相对应的概率密度函数,累加分布函数和余补累加分布函数.通过余补累加分布函数定量描述了人员在地铁火灾事故中安全逃生的概率.结果表明,蒙特卡罗模拟技术是描述同时具有参数不确定性和模型不确定性的复杂问题的有力工具.     

Strategic implications of counter-geoengineering: Clash or cooperation?

Solar geoengineering has received increasing attention as an option to temporarily stabilize global temperatures. A key concern is that heterogeneous preferences over the optimal amount of cooling combined with low deployment costs may allow the country with the strongest incentive for cooling, the so-called free-driver, to impose a substantial externality on the rest of the world. We analyze whether the threat of counter-geoengineering technologies capable of negating the climatic effects of solar geoengineering can overcome the free-driver problem and tilt the game in favour of international cooperation. Our game-theoretical model of countries with asymmetric preferences allows for a rigorous analysis of the strategic interaction surrounding solar geoengineering and counter-geoengineering. We find that counter-geoengineering prevents the free-driver outcome, but not always with benign effects. The presence of counter-geoengineering leads to either a climate clash where countries engage in a non-cooperative escalation of opposing climate interventions (negative welfare effect), a moratorium treaty where countries commit to abstain from either type of climate intervention (indeterminate welfare effect), or cooperative deployment of solar geoengineering (positive welfare effect). We show that the outcome depends crucially on the degree of asymmetry in temperature preferences between countries.     

Participatory development of incentives to coexist with jaguars and pumas

Reducing costs and increasing benefits for rural communities coexisting with large carnivores is necessary for conservation of jaguar (Panthera onca) and puma (Puma concolor). To design acceptable incentives, stakeholders must be involved in the process. We conducted an innovative, structured, group communication process based on a Delphi technique as a template for identifying potential incentives. Community workshops with 133 members of 7 communities and surveys with 25 multidisciplinary experts from government, nongovernmental organizations, and academia provided iterative data to design a plan of incentives through 4 rounds of discussion. The final product integrated 862 ideas into 6 types of incentives: organization of communities, mechanisms for improved dialogue, citizen technical assistance, green labeling for community products, payment for the ecosystem service of biodiversity, and an assessment of financial alternatives. We used quantitative and qualitative techniques to indicate support for decisions about the design of incentives, which reduced researcher subjectivity. The diverse incentives developed and the cooperation from multiple stakeholders resulted in an incentive plan that integrated issues of governance, equity, and social norms.     

Exploring oil and gas industry workers’ knowledge and information needs

Many incident reports and much research literature have concluded that incident rates in high-hazard industries can be reduced by enhancing the knowledge and information sources available to workers. However, a sparsity of published research reporting workers' perspectives on the value of information and knowledge sources in different operational situations potentially limits the effectiveness of interventions aimed at improving human responses to process safety performance. In response, this work seeks to understand how frontline oil and gas industry workers, responsible for managing process safety and other risks in their hazardous workplaces, rely on their own knowledge, the knowledge of others and information provided to manage different operating scenarios. A set of open and closed-ended survey questions were distributed to workers at several upstream and downstream oil and gas companies. Statistical analysis of 133 responses revealed interesting insights relating to participants’ experience levels, decision making practices and perceptions on the importance of various information and knowledge sources in different operating circumstances. The data revealed differences in the sources of knowledge relied upon by experienced and less experienced workers. Experienced workers rely on their own knowledge in both routine and potentially high-impact scenarios. Less experienced workers also rely on their own knowledge for routine decisions however they reported seeking out external knowledge and information in potentially high-impact scenarios. The data suggests that interventions to improve safety by enhancing the availability of knowledge and information sources are less likely to affect experienced workers and alternate strategies might be needed. However, such interventions might be effective if they are focused on supporting newer workers.     

Multimethod,multistate Bayesian hierarchical modeling approach for use in regional monitoring of wolves

In many cases, the first step in large‐carnivore management is to obtain objective, reliable, and cost‐effective estimates of population parameters through procedures that are reproducible over time. However, monitoring predators over large areas is difficult, and the data have a high level of uncertainty. We devised a practical multimethod and multistate modeling approach based on Bayesian hierarchical‐site‐occupancy models that combined multiple survey methods to estimate different population states for use in monitoring large predators at a regional scale. We used wolves (Canis lupus) as our model species and generated reliable estimates of the number of sites with wolf reproduction (presence of pups). We used 2 wolf data sets from Spain (Western Galicia in 2013 and Asturias in 2004) to test the approach. Based on howling surveys, the naïve estimation (i.e., estimate based only on observations) of the number of sites with reproduction was 9 and 25 sites in Western Galicia and Asturias, respectively. Our model showed 33.4 (SD 9.6) and 34.4 (3.9) sites with wolf reproduction, respectively. The number of occupied sites with wolf reproduction was 0.67 (SD 0.19) and 0.76 (0.11), respectively. This approach can be used to design more cost‐effective monitoring programs (i.e., to define the sampling effort needed per site). Our approach should inspire well‐coordinated surveys across multiple administrative borders and populations and lead to improved decision making for management of large carnivores on a landscape level. The use of this Bayesian framework provides a simple way to visualize the degree of uncertainty around population‐parameter estimates and thus provides managers and stakeholders an intuitive approach to interpreting monitoring results. Our approach can be widely applied to large spatial scales in wildlife monitoring where detection probabilities differ between population states and where several methods are being used to estimate different population parameters.     

Quantifying the burden of managing wildlife diseases in multiple host species

Mitigation of infectious wildlife diseases is especially challenging where pathogens affect communities of multiple host species. Although most ecological studies recognize the challenge posed by multiple-species pathogens, the implications for management are typically assessed only qualitatively. Translating the intuitive understanding that multiple host species are important into practice requires a quantitative assessment of whether and how secondary host species should also be targeted by management and the effort this will require. Using a multiple-species compartmental model, we determined analytically whether and how intensively secondary host species should be managed to prevent outbreaks in focal hosts based on the reproduction number of individual host species and between-species transmission rates. We applied the model to the invasive pathogenic fungus Batrachochytrium salamandrivorans in a 2-host system in northern Europe. Avoiding a disease outbreak in the focal host (fire salamanders [Salamandra salamandra]) was impossible unless management also heavily targeted the secondary host (alpine newts [Ichthyosaura alpestris]). Preventing an outbreak in the community required targeted removal of at least 80% of each species. This proportion increased to 90% in the presence of an environmental reservoir of B. salamandrivorans and when the proportion of individuals removed could not be adjusted for different host species (e.g., when using traps that are not species specific). We recommend the focus of disease-mitigation plans should shift from focal species to the community level and calculate explicitly the management efforts required on secondary host species to move beyond the simple intuitive understanding that multiple host species may all influence the system. Failure to do so may lead to underestimating the magnitude of the effort required and ultimately to suboptimal or futile management attempts.     

The dilemma of pest suppression in the conservation of endangered species

In the conservation of endangered species, suppression of a population of one native species to benefit another poses challenges. Examples include predator control and nest parasite reduction. Less obvious is the control of blood-feeding arthropods. We conducted a case study of the effect of native black flies (Simulium spp.) on reintroduced Whooping Cranes (Grus americana). Our intent was to provide a science-driven approach for determining the effects of blood-feeding arthropods on endangered vertebrates and identifying optimal management actions for managers faced with competing objectives. A multiyear experiment demonstrated that black flies reduce nest success in cranes by driving incubating birds off their nests. We used a decision-analytic approach to develop creative management alternatives and evaluate trade-offs among competing objectives. We identified 4 management objectives: establish a self-sustaining crane population, improve crane well-being, maintain native black flies as functional components of the ecosystem, and minimize costs. We next identified potential management alternatives: do nothing, suppress black flies, force crane renesting to occur after the activity period of black flies, relocate releases of cranes, suppress black flies and relocate releases, or force crane renesting and relocate releases. We then developed predictions on constructed scales of 0 (worst-performing alternative) to 1 (best-performing alternative) to indicate how alternative actions performed in terms of management objectives. The optimal action depended on the relative importance of each objective to a decision maker. Only relocating releases was a dominated alternative, indicating that it was not optimal regardless of the relative importance of objectives. A rational decision maker could choose any other management alternative we considered. Recognizing that decisions involve trade-offs that must be weighed by decision makers is crucial to identifying alternatives that best balance multiple management objectives. Given uncertainty about the population dynamics of blood-feeding arthropods, an adaptive management approach could offer substantial benefits.     

Untapped potential of collective intelligence in conservation and environmental decision making

Environmental decisions are often deferred to groups of experts, committees, or panels to develop climate policy, plan protected areas, or negotiate trade-offs for biodiversity conservation. There is, however, surprisingly little empirical research on the performance of group decision making related to the environment. We examined examples from a range of different disciplines, demonstrating the emergence of collective intelligence (CI) in the elicitation of quantitative estimates, crowdsourcing applications, and small-group problem solving. We explored the extent to which similar tools are used in environmental decision making. This revealed important gaps (e.g., a lack of integration of fundamental research in decision-making practice, absence of systematic evaluation frameworks) that obstruct mainstreaming of CI. By making judicious use of interdisciplinary learning opportunities, CI can be harnessed effectively to improve decision making in conservation and environmental management. To elicit reliable quantitative estimates an understanding of cognitive psychology and to optimize crowdsourcing artificial intelligence tools may need to be incorporated. The business literature offers insights into the importance of soft skills and diversity in team effectiveness. Environmental problems set a challenging and rich testing ground for collective-intelligence tools and frameworks. We argue this creates an opportunity for significant advancement in decision-making research and practice.