Focusing biodiversity research on the needs of decision makers

The project on Biodiversity Uncertainties and Research Needs (BURN) ensures the advancement of usable knowledge on biodiversity by obtaining input from decision makers on their priority information needs about biodiversity and then using this input to engage leading scientists in designing policy-relevant research. Decision makers articulated concerns related to four issues: significance of biodiversity; status and trends of biodiversity; management for biodiversity; and the linkage of social, cultural, economic, legal, and biological objectives. Leading natural and social scientists then identified the research required to address the decision makers' needs and determined the probability of success. The diverse group of experts reached consensus on several fundamental issues, helping to clarify the role of biodiversity in land and resource management. The BURN participants identified several features that should be incorporated into policy-relevant research plans and management strategies for biodiversity. Research and assessment efforts should be: multidisciplinary and integrative, participatory with stakeholder involvement, hierarchical (multiple scales), and problem- and region-specific. The activities should be focused regionally within a global perspective. Meta-analysis of existing data is needed on all fronts to assess the state of the science. More specifically, the scientists recommended six priority research areas that should be pursued to address the information needs articulated by decision makers: (1) characterization of biodiversity, (2) environmental valuation, (3) management for sustainability—for humans and the environment (adaptive management), (4) information management strategies, (5) governance and stewardship issues, and (6) communication and outreach. Broad recommendations were developed for each research area to provide direction for research planning and resource management strategies. The results will directly benefit those groups that require biodiversity research to address their needs—whether to develop policy, manage natural resources, or make other decisions affecting biodiversity.     

Why ecosystem management can't work without Social science: An example from the California northern spotted owl controversy

It is increasingly obvious that social science, while not a sufficient condition for making ecosystem management effective, is a necessary condition. A social science typology of ecosystems is developed, applied, and shown to have substantial and unexpected implications for the practice of ecosystem management. Ecologists and environmental scientists, in particular, will find some conclusions uncomfortable. The application involves a case material from the California northern spotted owl controversy.     

Ecosystem management to achieve ecological sustainability: The case of South Florida

The ecosystems of South Florida are unique in the world. The defining features of the natural Everglades (large spatial scale, temporal patterns of water storage and sheetflow, and low nutrient levels) historically allowed a mosaic of habitats with characteristic animals. Massive hydrological alterations have halved the Everglades, and ecological sustainability requires fundamental changes in management.The US Man and the Biosphere Human-Dominated Systems Directorate is conducting a case study of South Florida using ecosystem management as a framework for exploring options for mutually dependent sustainability of society and the environment. A new methodology was developed to specify sustainability goals, characterize human factors affecting the ecosystem, and conduct scenario/consequence analyses to examine ecological and societal implications. South Florida has sufficient water for urban, agricultural, and ecological needs, but most water drains to the sea through the system of canals; thus, the issue is not competition for resources but storage and management of water. The goal is to reestablish the natural system for water quantity, timing, and distribution over a sufficient area to restore the essence of the Everglades.The societal sustainability in the Everglades Agricultural Area (EAA) is at risk because of soil degradation, vulnerability of sugar price supports, policies affecting Cuban sugar imports, and political/economic forces aligned against sugar production. One scenario suggested using the EAA for water storage while under private sugar production, thereby linking sustainability of the ecological system with societal sustainability. Further analyses are needed, but the US MAB project suggests achieving ecological sustainability consistent with societal sustainability may be feasible.     

森林大火潜在危险和可燃物干旱度研究

介绍了森林大火潜在危险的可燃物干旱度指标研究，以及干旱度指数ＳＤＩ的计算方法，同时对干旱度指数进行了划分确定，以便在森林大火预报中作参考使用。     

施工企业安全文化的核心——保护员工的安全与健康

分析了企业安全文化的发展和施工安全的特点，围绕企业目标、市场占有率、生产成本、企业形象、经济效益等内容，论述了保护员工安全与健康是施工企业安全文化的核心     

中国可持续发展与国家安全文化战略的新对策

“可持续发展”战略的实质是社会、经济发展与资源、环境相协调的一种发展模式。值得注意，这一人类社会发展模式中跨世纪重大转变的策略，尚未引起安全与减灾科技界的普遍关注，不仅在安全减灾战略研究中很少涉及，严重的是它阻碍了安全减灾诸领域跨世纪及决策课题研究的深度，造成与国际接轨进程缓慢。为此，立足可持续发展思路，并以全新视角、系统地讨论适宜安全减灾文化战略的总体对策，可望能为中国二十一世纪安全保障及科技发展提供科学指南     

农业气象干旱指标研究综述

干旱作为最严重的气象灾害之一，已经对我国社会经济和人民生活造成严重影响。结合农业干旱和气象干旱基本理论，对农业气象干旱的定义及指标作了较为详细的综述与评价，指出了不同指标的优点和缺点，对今后的研究方向进行了展望，为干旱的监测和评估及农业防灾减灾研究提供了方法和依据。     

气候条件变化对棉纤维品质的影响

对棉纤维品质试验的结果分析表明，其长度受气候条件的影响不明显，而比强度和麦克隆值则明显受气候条件的影响。从变异值分析，受气候影响大小顺序是：比强度〉发克隆值〉长度。影响比强度的气候因子主要是日均温、累积降水量和相对湿度，影响麦克隆值的气候因子主要是日均温和累积降水量或夜均温、累积降水量。并确定影响比强度的日均温最低临界值为24．5℃，最适值为26．1℃，铃期累积降水量的最高临界值为109．9mm，最适值为44．6mm，栩对湿度的最高临界值为77．7％，最适值为67．9％。麦克隆值适宜范围的日均温为20．5～24．8℃，累积降水量为108．2～308．2mm。长度适宜范围的最低温度为14．7～20．8℃，相对湿度为84．7％～89．5％。这些因子和指标的确定为建立棉纤维品质的定量模型奠定了基础。     

在役化工装置安全评价模式的研究

根据在役装置安全评价的两类目的,分析现有在役化工装置安全评价模式中存在的不足;提出在役化工装置安全评价的一个新思路和新模式;给出了基于新模式的安全评价程序,并对该评价程序各个步骤及采用的评价方法组合进行了较为详细的讨论,其关键是建立评价指标体系。该评价模式既能查找出装置中存在的具体安全隐患,也能给出装置总的安全评价结论。同时指出,安全评价指标体系的建立和完善应成为安全管理的一项标准化、基础性工作。该评价模式的思路不仅适用于在役化工装置的安全评价,也适用于其他系统安全现状评价,是对进一步完善当前安全现状评价工作的一个有益尝试。     

BP神经网络技术在交通工具火灾预警中的应用

通过对交通工具火灾成因机理以及现有典型交通工具火灾实例的分析研究,建立了预警评价指标体系。根据非线性理论和模式识别原理以及交通工具火灾的特点,采用基于BP神经网络的智能灾害诊断方法,对交通工具火灾发生的可能性和危险性进行评估和预测。研究表明:BP神经网络方法是解决非线性系统问题的一种有效方法,与传统的预警方法相比,该方法具有速度快、效率高、可信度好、自学能力强等特点。采用BP网络进行交通工具火灾预警时,只需输入影响交通工具火灾发生的相关指标因素,网络便可在较短的时间内得出可靠的预警结果。