Procrastinating reform: The impact of the market stability reserve on the EU ETS

We study the impact of the market stability reserve (MSR) on price and emission paths of the EU ETS. From 2019 onwards, the MSR will adjust the number of allowances auctioned as a function of the size of the surplus, i.e. in times of a large surplus it shifts the issue date of allowances into the future. In a perfectly competitive allowance market the MSR only affects price and emission paths if the baseline equilibrium becomes unfeasible. If the MSR is binding, prices increase in the short run but drop in the medium run relative to the baseline. The MSR increases price variability if uncertainty over future allowance demand is resolved while there is a surplus. The long run cap is unaffected by both the MSR and overlapping climate policies. This contrasts the EU׳s objectives of improving the resilience of the EU ETS and increasing synergies with overlapping climate policies.     

Land-use choices: the case of conservation reserve program (CRP) re-enrollment in Kansas,USA

Among the important alternatives for land conservation is the US Conservation Reserve Program (CRP) that celebrated its 30th anniversary in 2015. This paper explores how landowners decide on alternative land-use choices made available by the expiration of CRP contracts in Kansas. The study uses survey data and multinomial Logit models to predict land-use choices. Two models were tested. The first model does not incorporate variables concerning farmer perceptions and attitudes about land-use choices, while the second model does. The results show that CRP re-enrollment depends on factors, such as years of experience in cropping and percent of cropland irrigated. However, when perception variables are added, the models become more robust in explaining other land choice alternatives. The results suggest that as the perception of unfairness of more inflexible environmental policy rises, these farmers may be more likely to re-enroll their marginal land in the CRP program.     

食品应急储备配置比例及方法研究

为提升食品应急储备的科学性、合理性,在总结分析食品应急储备的种类、形式与影响因素的基础上,以我国官方发布的食物与营养发展目标为依据,确定了八大类应急储备食品的基础配置比例,并提出了食品大类配置比例的修正方法,随后综合考虑生产周期、保质期、易储性和储备成本,给出实物储备和产能储备的配置方法,最后提出了单类食品实物储备模式下单品的配置原则和方法,并以单价修正为例对单品选择性修正方法进行了说明,对不断提高突发事件应急保障工作的水平,提升应对突发事件的保障能力,实现受灾群众更科学合理的饮食结构有重要意义。     

土地利用/覆被变化对张掖黑河湿地国家级自然保护区景观破碎化的影响

在遥感和GIS技术支持下,基于1975-2010年长时间序列遥感影像,结合转移矩阵模型等方法,阐述了张掖黑河湿地国家级自然保护区及其周边区域的土地利用/覆被变化状况。选取斑块密度指数、聚合度、斑块平均面积指数、斑块形状破碎化指数等指标,系统分析了保护区内湿地景观破碎化过程,据此探讨了保护区及其周边区域土地利用/覆被变化对保护区内湿地景观破碎化过程的影响。结果表明:①保护区内及其周边地区的耕地比重分别增加了7.67%和5.5%,湿地比重分别减少了6.91%和0.4%;②保护区内湿地逐渐由研究初期大面积斑块体占主导、空间上连续分布的格局趋于景观破碎化;③区域土地利用/覆被变化直接导致了保护区内湿地平均斑块面积的缩减,间接降低了湿地斑块间的聚合度等;④保护区内湿地景观破碎化对土地利用/覆被变化的响应主要表现为各景观破碎化指数对大规模的耕地开垦等开发活动的响应上。     

鄱阳湖南矶山自然保护区渔业特点及资源现状

通过鄱阳湖对南矶山自然保护区鱼类的采样和调查,记录鱼类58种,分别隶属于6目14科43属。其中鲤科鱼类37种,占总数的63.79%,其余各科共21种,占总数的36.21%。与以往记录相比,保护区鱼类群落结构以及鱼类个体均小型化。此外,统计了主要鱼类的平均体重、生物量和K值,并探讨了鱼类资源衰竭和个体小型化的原因和保护对策。 较准确地反映了现阶段鄱阳湖西南水域渔业资源的特点和现状。     

我国自然保护区生态旅游存在问题分析

通过对2006年自然保护区建设管理基本情况调查和2008年自然保护区生态旅游专项问卷调查得到的数据进行分析,立足我国自然保护区生态旅游发展现状,从自然保护区生态旅游涉及的宏观决策管理,保护区管理机构,保护区与社区、旅游经营者、游客、生态环境的关系6个方面,系统地分析目前我国自然保护区生态旅游存在问题,并提出相应对策.     

涉及自然保护区建设项目的环境管理

针对自然保护区的特点和生物多样性保护的要求,明确了涉及自然保护区建设项目的范畴、准入条件,对建设项目立项期、施工期和运营期3个阶段自然保护区管理机构应采取的环境管理措施进行了分析,并提出了相关对策建议,以期为促进自然保护区的建设管理提供规范性指导.     

基于净初级生产力的生态足迹模型及其与传统模型的对比分析

生态足迹模型因其可以定量度量生态可持续发展、计算简单、结论易懂、全球可比等特点,提出之后得到了大量的关注和应用,同时也面临着一些质疑和争论。文章介绍了一种基于净初级生产力的生态足迹理论和计算方法,并以该方法和传统生态足迹模型分别计算了中国1961—2007年的生态足迹,对计算结果进行了对比分析。结果表明,两种生态足迹模型的计算结果具有较高的相关性,表明基于净初级生产力的生态足迹模型结果可信。该种方法能够克服传统生态足迹模型的部分缺陷,在均衡因子选取、土地生态功能假设、CO2吸收等方面有了较大改进,能够较好地反映不同生态系统在生产力上的差异;在时间序列分析方面也更加合理。但该方法本身同时存在着计算方法不完善、对生态系统变化不敏感等问题,如何更紧密地结合生态足迹和净初级生产力是需要进一步研究的内容。     

Effects of connectivity and spatial resolution of analyses on conservation prioritization across large extents

The outcome of analyses that prioritize locations for conservation on the basis of distributions of species, land cover, or other elements is influenced by the spatial resolution of data used in the analyses. We explored the influence of data resolution on prioritization of Finnish forests with Zonation, a software program that ranks the priority of cells in a landscape for conservation. We used data on the distribution of different forest types that were aggregated to nine different resolutions ranging from 0.1 × 0.1 km to 25.6 × 25.6 km. We analyzed data at each resolution with two variants of Zonation that had different criteria for prioritization, with and without accounting for connectivity and with and without adjustment for the effect on the analysis of edges between areas at the project boundary and adjacent areas for which data do not exist. Spatial overlap of the 10% of cells ranked most highly when data were analyzed at different resolutions varied approximately from 15% to 60% and was greatest among analyses with similar resolutions. Inclusion of connectivity or edge adjustment changed the location of areas that were prioritized for conservation. Even though different locations received high priority for conservation in analyses with and without accounting for connectivity, accounting for connectivity did not reduce the representation of different forest types. Inclusion of connectivity influenced most the outcome of fine-resolution analyses because the connectivity extents that we based on dispersal distances of typical forest species were small. When we kept the area set aside for conservation constant, representation of the forest types increased as resolution increased. We do not think it is necessary to avoid use of high-resolution data in spatial conservation prioritization. Our results show that large extent, fine-resolution analyses are computationally feasible, and we suggest they can give more flexibility to implementation of well-connected reserve networks.     

Identifying Conservation Areas on the Basis of Alternative Distribution Data Sets

Abstract:  Distribution data on biodiversity features is a major component of conservation planning that are often inaccurate; thus, the true distribution of each feature is commonly over- or underrepresented. The selection of distribution data sets may therefore lead to variability in the spatial configuration and size of proposed reserve networks and uncertainty regarding the extent to which these networks actually contain the biodiversity features they were identified to protect. Our goals were to investigate the impact on reserve selection of choosing different distribution data sets and to propose novel methods to minimize uncertainty about target attainment within reserves. To do so, we used common prioritization methods (richness mapping, systematic reserve design, and a novel approach that integrates multiple types of distribution data) and three types of data on the distribution of mammals (predicted distribution models, occurrence records, and a novel combination of the two) to simulate the establishment of regional biodiversity reserves for the state of Arizona (U.S.A.). Using the results of these simulations, we explored variability in reserve placement and size as a function of the distribution data set. Spatial overlap of reserve networks identified with only predicted distribution data or only occurrence distribution data never exceeded 16%. In pairwise comparisons between reserves created with all three types of distribution data, overlap never achieved 50%. The reserve size required to meet conservation targets also varied with the type of distribution data used and the conservation goal; the largest reserve system was 10 times the smallest. Our results highlight the impact of employing different types of distribution data and identify novel tools for application to existing distribution data sets that can minimize uncertainty about target attainment.