基于二元水循环理论的水资源资产化管理框架构建

我国实行的是国家所有的水资源产权制度,在水资源的实际管理中存在多级代理和管理者短视行为等问题。水资源资产化管理作为解决管理者短视行为的重要措施引入到水资源管理中,然而由于相关理论的不足,相应措施沦为缺乏监督的政府间行为,并限制水资源资产市场机制的形成。本文考虑到水资源的多重功能,以及水资源资产与承担支撑社会经济功能的社会水循环通量的内涵一致性,将二元水循环理论引入水资源资产化管理的框架构建中去。本文根据资产的定义和水资源的功能界定了水资源资产的内涵,并发现其与社会水循环通量的重合,提出这部分水资源可以作为水资源资产进行管理,并总结了二元水循环耦合水资源资产化管理中的水资源资产界定、监管体系、用途管制以及产权界定方面的路径。在此基础上,本文辨析了水资源资产管理与水资源管理的关系,认为水资源资产管理与传统的水资源管理组成水资源管理,水资源资产管理弥补了传统水资源管理上的不足。在分层管理上,提出传统水资源管理作用于宏观、中观管理,水资源资产管理作用于微观管理的机制。此外,根据二元水循环理论中的社会水循环过程,将其权属进行分解,并结合各部门的社会水循环机制对水资源资产化管理进行了设计。     

环境影响的IPAT模型再认识

伴随工业文明的发展,探究日益恶化环境问题的社会根源成为学术界激烈争论的议题,从人口规模与技术水平的单因素争论拓展到文化背景、政府类型和消费观念等多因素论的讨论,在横向上从宏观社会到微观个体层次的解释,最终形成经典的环境影响的IPAT模型,试图解释环境问题产生的复杂社会动力机制。本文通过国内外学者对IPAT模型的实证研究以及理论探讨梳理发现:模型中的因变量环境影响I以及自变量人口数量P、富裕程度A和技术水平T的内涵、完备性以及分析单位的适用性等方面备受争议。为了克服变量的局限,首先通过分解IPAT模型中T变量,进一步拓展模型中可能被忽略的对环境影响的多重因素;同时为了避免模型中不同因素对环境影响的同比例线性变化的局限性,将IPAT模型转化为非线性的STIRPAT随机模型,使各变量值随观察值的变化而变化;其次为了克服研究中忽视个体对环境影响差异性的不足,以"双重转换"理论为基础分析少数特权群体对环境造成不成比例的影响;最后面对分析单位以及分析情景的差异性与复杂性,基于"世界体系论"视角突破特定区域时空以国家间互动关系为分析单位对全球环境退化展开讨论。研究表明,IPAT模型的发展演变表明环境保护与经济发展关系逐渐从悲观的"零和"冲突走向协调发展的路径,有利于探索更加有效的举措应对全球复杂而严峻的环境问题,同时对新常态下中国推进生态文明建设具有重要的理论和实践意义。     

基于双主体博弈的地方政府任期对区域环境合作稳定性影响研究

区域内地方政府合作是解决跨界环境污染的重要途径,我国现行环境管理体制决定了任期长短对地方政府是否环境合作具有重要影响。基于博弈论分析方法,针对地方政府任期对区域环境合作的稳定性影响进行了理论分析。首先,分析了完全信息静态博弈时两个地方政府非合作与合作情形下的均衡污染排放量,构建基于无限次重复博弈模型并讨论两个地方政府采取冷酷战略时彼此合作的临界贴现因子。然后,基于有限次重复博弈模型讨论了临界贴现因子与任期长短的关系。研究发现,贴现因子高于临界水平是地方政府选择环境合作的必要条件;而地方政府的任期越长则临界贴现因子越小,地方政府之间环境合作稳定性越强。基于此,提出了地方政府任期及环境保护终身追责等促进区域环境合作的建议。     

分布式认知理论框架下农户土地转出意愿影响因素研究——基于SEM模型的武汉城市圈典型地区实证分析

基于分布式认知理论,从"个人力"、"地域力"、"文化力"三个层次构建农户土地流转认知的影响因素理论框架,利用"武汉城市圈"典型地区土地流转调查数据构建结构方程模型(Structural Equation Model,SEM),定量分析各影响因素在农户土地流转认知中的作用。研究证实:不同农户认知群体之间存在不同流转认知偏好,"无文化的老农民"相对于"有文化的年轻职业者"在土地流转认知中更加保守;农户对土地的需求普遍偏向土地的资产属性和财产权利,农村土地流转具备内在动力;然而,出于对土地社会保障功能的需求,农户不会因为其家庭生产方式和经济来源明显脱离土地而产生强烈的土地转出愿意,农户的家庭生计条件及"土地情节"在一定程度上制约了土地流转;村镇干部"取信于民"是农户获得"安全感",克服风险规避心理促进土地流转认知的最重要因素;流转价格是对农户在土地流转中物质与精神"双重损失"的资金补偿,两者的匹配程度对农户的认知具有重要作用。在此基础上,得出要规范流转程序、健全流转监督机制、保护农民利益,加强农村社会保障制度建设以确保农民获得公平的社会保障,加快推进和支持农村教育以提高农村劳动力素质,建立和完善土地流转制度保障和农业经营扶持机制等政策启示。     

海洋环境风险的特性及形成机理:基于扎根理论分析

随着人口向沿海区域聚集,以及海洋开发的深入,海洋环境风险徒增。要实现海洋环境风险的有效防治,需要洞悉海洋环境风险不同于一般环境风险的特性,了解其独特的形成机理。目前,海洋环境风险的概念使用更多地是基于经验而非学理。鉴于海洋环境风险概念的认知匮乏,文章采用扎根理论对其进行分析,从而挖掘了海洋环境风险的一些特有属性。研究发现,在海洋环境风险的形成机理中,自然因素、心理因素和社会因素共同作用,并呈现依次递进、不断放大的关系;人们对海洋环境风险内涵及特性的认知,是两个方面的综合:"有关海洋环境的风险",以及"因由海洋环境引发的社会风险";对于防治者而言,要有效区分民众对沿海自然项目的风险感知与民众对沿海自然项目管理状况的风险感知;要有特别注意海洋环境风险的"镜像"效应。     

The influence of social experience on cooperative behaviour of rats (Rattus norvegicus): direct vs generalised reciprocity

Cooperation among non-kin has been attributed sometimes to reciprocal altruism: Two or more individuals exchange behaviour that benefits the respective partner. According to direct reciprocity, cooperation is based on past behaviour of a known partner. In contrast, in generalised reciprocity, cooperation is based on anonymous social experience where the identity of the partner is irrelevant. In a previous study, female Norway rats (Rattus norvegicus) were found to cooperate according to a generalised reciprocity mechanism. In this study, we tested whether Norway rats would also cooperate as predicted by a direct reciprocity mechanism and whether direct reciprocity would cause a higher propensity to cooperate than generalised reciprocity. Focal animals were experimentally manipulated to receive social experience from known or unknown, helpful or defecting partners in an instrumental cooperative task. Our first experiment shows that rats are more helpful towards a partner from which they had received help before than towards a partner that had not helped (i.e. direct reciprocity). Our second experiment revealed that after receiving help by others, rats were more helpful towards a partner from which they had received help before than towards a new partner (i.e. direct reciprocity generated a higher cooperation propensity than generalised reciprocity). We conclude that in female Norway rats, the tendency to cooperate is influenced by partner-specific information. To our knowledge, this is the first study to demonstrate direct reciprocity in rodents, and it is the first study testing direct vs generalised reciprocity in animals.     

A Graph-Theory Framework for Evaluating Landscape Connectivity and Conservation Planning

Abstract:  Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A).^. We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.     

Six Common Mistakes in Conservation Priority Setting

A vast number of prioritization schemes have been developed to help conservation navigate tough decisions about the allocation of finite resources. However, the application of quantitative approaches to setting priorities in conservation frequently includes mistakes that can undermine their authors’ intention to be more rigorous and scientific in the way priorities are established and resources allocated. Drawing on well‐established principles of decision science, we highlight 6 mistakes commonly associated with setting priorities for conservation: not acknowledging conservation plans are prioritizations; trying to solve an ill‐defined problem; not prioritizing actions; arbitrariness; hidden value judgments; and not acknowledging risk of failure. We explain these mistakes and offer a path to help conservation planners avoid making the same mistakes in future prioritizations. Seis Errores Comunes en la Definición de Prioridades de Conservación