Protected-Area Monitoring Dilemmas: a New Tool to Assess Success

Abstract:  Understanding factors that influence the success of protected areas in curbing unsustainable resource consumption is essential for determining best management strategies and allocating limited resources to those projects most likely to succeed. I used a law-enforcement and monitoring game-theory model from the political science literature to identify three key variables useful in predicting the success of a protected area: costs of monitoring for rule breakers, benefits of catching a rule breaker, and probability of catching a rule breaker if monitoring. Although assigning exact values for each of these variables was difficult, the variables had a strong predictive capacity even when coded as coarse ordinal values. A model in which such values were used correctly predicted the outcome of 88 of 116 protected areas sampled from the peer-reviewed literature. The model identified a critical zone of common mismatch between protected-area circumstances and management policies. In situations where the costs of monitoring were greater than the product of the probability of catching a rule breaker and the benefit of doing so, conservation was unlikely to succeed. Control of illegal use of protected resources was reported in only 8% of such cases, regardless of strategies to motivate potential users to cooperate with conservation. My model does not prescribe a best management policy for conserving natural resources; rather, it can be used as a tool to help predict whether a proposed management policy will likely succeed in a given situation.     

Bayesian Decision Analysis for Evaluating Management Options to Promote Recovery of a Depleted Salmon Population

Abstract:  The endangered population of sockeye salmon (Oncorhynchus nerka) in Cultus Lake, British Columbia, Canada, migrates through commercial fishing areas along with other, much more abundant sockeye salmon populations, but it is not feasible to selectively harvest only the latter, abundant populations. This situation creates controversial trade-offs between recovery actions and economic revenue. We conducted a Bayesian decision analysis to evaluate options for recovery of Cultus Lake sockeye salmon. We used a stochastic population model that included 2 sources of uncertainty that are often omitted from such analyses: structural uncertainty in the magnitude of a potential Allee effect and implementation uncertainty (the deviation between targets and actual outcomes of management actions). Numerous state-dependent, time-independent management actions meet recovery objectives. These actions prescribe limitations on commercial harvest rates as a function of abundance of Cultus Lake sockeye salmon. We also quantified how much reduction in economic value of commercial harvests of the more abundant sockeye salmon populations would be expected for a given increase in the probability of recovery of the Cultus population. Such results illustrate how Bayesian decision analysis can rank options for dealing with conservation risks and can help inform trade-off discussions among decision makers and among groups that have competing objectives.     

Hedging Rules for the Operation of Lake Okeechobee in Southern Florida

Lake Okeechobee is the major source of freshwater in Southern Florida. With the increasing possibility of water stress, determining how to manage water during drought periods is essential to the operation of the Lake. This study deals with operational problems related to the management of Lake Okeechobee and the challenges involved in the implementation of hedging policy. We examine the implications of applying a theoretical hedging rule approach, comprising inter‐ and intrayear models, for the management of Lake Okeechobee and explore several optional hedging policies. The results demonstrate that hedging rules could reduce profit loss particularly under serious water stress, and might be applied sooner to mitigate the risk of severe water shortages. We suggested that the management of Lake Okeechobee should consider both short‐ and long‐term hedging nested. It is also demonstrated that the practical applicability of rolling decision making with updated forecast. Based on the results of the model, the merits of explicit optional hedging rules are demonstrated.     

基于随机森林的高速公路运营隧道风险判别法则研究*

为快速、准确识别山区高速公路隧道不同区段风险因素组合,基于交通事故调研数据,分析其时空变化规律;从人-车-路-环境角度系统筛选风险影响因素,采用随机森林理论构建风险等级预测模型;以决策树与规则相互关系为基础,结合自变量重要评分法,提出基于随机森林的高速公路运营隧道风险判别法则。研究结果表明:判别法则集预测精度较好且运行时间短,能够明确高速公路不同隧道区段事故成因,为预防隧道严重交通事故发生提供参考。     

有效提高英语水平的一种途径--识记

本文针对大学生在英语学习过程中出现的识记能力差,贬低记忆作用的偏见,提出教学中应帮助学生了解和掌握记忆规律,提倡识记词汇、句法、段落或课文,有助于提高学生听、阅读和写作能力.     

论清洁生产法治的技术基础

本文深入探讨了产业结构调整、工业污染防治与清洁生产法治的关系，以及企业管理、清洁技术与清洁生产法治的关系。指出产业结构调整、企业管理和清洁技术的应用是实现清洁生产法治的重要技术途径和方式。并已经得到许多国家清洁生产及其法治实践的普遍采用和证实，而清洁生产法治的实现又有利于促进产业结构和企业管理更加生态化，促进清洁技术进一步发展。     

采用神经网络半主动模糊控制系统提高桥梁结构的安全性

研究了桥梁结构的半主动控制对提高桥梁结构安全性的作用 ,在算法上采用基于神经网络的模糊控制 ,不需要建立精确的分析模型 ,计算较为简便 ,避免了多参量建立的模糊关系方程的求解困难。数值结果表明 ,笔者提出的半主动控制系统对减小结构的地震响应是有效的     

电子废物资源化循环转化过程与代谢规律研究

选择废印刷电路板和废CRT玻壳玻璃的资源化过程作为承载实体,进行了研究分析.建立了电子废物资源化技术过程的物质能量转化模型;分析了废印刷电路板和废CRT玻壳玻璃的资源化过程中的物质流、能量流、废物流以及污染物的释放与迁移;核算了物质、能量转化清单.分析结果表明,废印刷电路板资源化过程中的分选环节能耗较高,达100kW×h/t,而拆解和非金属材料的热压成型是控制污染物排放的重点环节;废CRT玻壳玻璃资源化过程中屏玻璃和锥玻璃的再利用环节能耗较高,利用屏玻璃制造泡沫玻璃和锥玻璃冶炼铅的能耗分别为600, 250kW×h/t,破碎、研磨、锥玻璃冶炼铅是控制污染物排放的重点环节.     

移动危险源事故统计分析及发生规律探讨

每年有大量的危险化学品需要运输,这些可移动危险源发生的事故越来越频繁,已严重影响到社会公共安全。收集整理了从2006年1月-2010年10月间的408起移动危险源事故案例,从事故发生的日期、路段、车辆类型、地区、原因、危险物品种类等方面进行统计分析,总结移动危险源事故特点,分析事故的内在规律和发生原因,并根据分析的结果结合我国目前的实际情况,提出相关的安全管理措施及建议。     

Do EPA regulations affect labor demand? Evidence from the pulp and paper industry

Any opinions and conclusions expressed herein are those of the author(s) and do not necessarily represent the views of the U.S. Census Bureau or the U.S. Environmental Protection Agency. All results have been reviewed to ensure that no confidential information is disclosed. We thank Wang Jin and Shital Sharma for excellent research assistance; we also thank Jim Davis at the Boston Research Data Center for his continued help, and Reed Walker and participants at the 2011 AERE Summer Conference and the Environmental Economics seminar at Harvard University?s Kennedy School for helpful comments. Any remaining errors are ours.