我国物流产业基本经济活动空间格局分析

基于经济基础理论,对1991～2001年间我国各省区物流产业基本经济活动部分进行了实证分析,从省际差异、东中西部差异两个方面分析了我国区域物流产业基本经济活动的省区差异:在时间维度上区域差异呈逐步扩大趋势,在空间结构上表现出较明显的沿海指向性和交通指向性,并以此分析归纳出我国物流产业基本活动的"四区(物流集聚区)一带(物流集聚带)"空间格局特征,进而得出其基本经济活动强度与区域经济发展水平、物流需求程度、科技水平、区位条件、交通等基础设施、政策及历史发展作用紧密相关的结论.     

广东省的地质灾害与防治对策

广东省地质灾害类型多,分布广,频率高,危害大.地震、滑坡、崩塌、地裂缝、地面塌陷、地面沉降和软土地基变形等地质灾害是影响当地经济发展和城乡建设的消极因素.地质灾害的时间分布具有波动性,过去35年来存在两个明显的高发期,分别是1985-1992年和1997年至今;其空间分布具有区域耦合性,地质构造复杂、自然环境恶劣的粤西、粤北低山丘陵区和人类活动剧烈、经济发达的沿海平原地区都是重灾区.地质灾害与自然条件、人类活动关系密切.它们的防治应以防为主,防治结合,将生态与工程措施相结合,并调整人类的经济行为,保持生态环境的平衡.     

洪涝灾害评价的威布尔模型

首次将威布尔分布用于淮河流域水灾成灾面积研究,揭示了淮河流域洪涝灾害成灾面积形成的 内在规律,进而利用河南、安徽、江苏和山东4省的各自灾度对淮河流域的灾害风险建立了线性回归模型.实证分析表明,本方法切实可行,特别适用于大样本计算.     

饮用水源水库铁锰垂直分布规律及原因

经对水温分层型季节性缺氧水库铁、锰污染的研究表明,Fe、Mn分布随着季节变化、水库水温分层而变化,呈现明显的垂直分布规律:高浓度Fe、Mn主要出现在水温分层期水库中、下层,与库底缺氧、pH值下降、基岩溶蚀、沉积物高浓度Fe、Mn释放造成的二次污染等密切相关,从而为自来水厂实施优化分层取水和污染控制提供了依据.     

北京市地热资源开发的时空变化

简要介绍了北京地热资源特点,分析了北京地热资源开发的时空演变规律.在搜集资料和实地调查的基础上,绘制出了北京城区地热井分布示意图,并针对其开发利用中可能出现的问题提出了对策.     

Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low‐elevation wetlands or mid‐elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy—herbaceous alpine ecotones—were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. Patrones Espaciales del Éxito Reproductivo de Osos Pardos, Derivados de Modelos Jerárquicos Multi‐Estado     

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land‐use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land‐use change projections with the latest developments in network‐connectivity research and spatial, multipurpose conservation prioritization. We used land‐use change simulations to explore robustness of species’ habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land‐use change. The application of connectivity criteria alongside habitat‐quality criteria for protected‐area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade‐offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

Geography and Recovery under the U.S. Endangered Species Act

Abstract: The U.S. Endangered Species Act (ESA) defines an endangered species as one “at risk of extinction throughout all or a significant portion of its range.” The prevailing interpretation of this phrase, which focuses exclusively on the overall viability of listed species without regard to their geographic distribution, has led to development of listing and recovery criteria with fundamental conceptual, legal, and practical shortcomings. The ESA's concept of endangerment is broader than the biological concept of extinction risk in that the “esthetic, ecological, educational, historical, recreational, and scientific” values provided by species are not necessarily furthered by a species mere existence, but rather by a species presence across much of its former range. The concept of “significant portion of range” thus implies an additional geographic component to recovery that may enhance viability, but also offers independent benefits that Congress intended the act to achieve. Although the ESA differs from other major endangered‐species protection laws because it acknowledges the distinct contribution of geography to recovery, it resembles the “representation, resiliency, and redundancy” conservation‐planning framework commonly referenced in recovery plans. To address representation, listing and recovery standards should consider not only what proportion of its former range a species inhabits, but the types of habitats a species occupies and the ecological role it plays there. Recovery planning for formerly widely distributed species (e.g., the gray wolf [Canis lupus]) exemplifies how the geographic component implicit in the ESA's definition of endangerment should be considered in determining recovery goals through identification of ecologically significant types or niche variation within the extent of listed species, subspecies, or “distinct population segments.” By linking listing and recovery standards to niche and ecosystem concepts, the concept of ecologically significant type offers a scientific framework that promotes more coherent dialogue concerning the societal decisions surrounding recovery of endangered species.     

南京北郊秋冬季相对湿度及气溶胶理化特性对大气能见度的影响

为了解南京北郊秋冬季相对湿度与气溶胶理化特性对大气能见度的影响,利用2012年秋冬季气象要素资料、颗粒物浓度及其主要成分和气溶胶粒子谱分布等观测数据,分析了南京北郊大气能见度与气象要素、颗粒物污染之间的关系.结果表明,南京北郊秋冬季节平均大气能见度仅为4.76 km.颗粒物浓度与能见度存在一定的负相关关系,尤其细粒子对能见度的影响更为显著.随细粒子质量浓度和相对湿度(RH)的增大,低能见度出现的频率呈现上升趋势.能见度从5~10 km衰减到5km时,PM10和PM2.1质量浓度分别增加了7.56%和37.64%;其中SO2-4和NO-3质量浓度均有显著增加.气溶胶粒子数浓度对能见度的影响与相对湿度有关,粒径0.5~2μm的气溶胶数浓度随RH增加增长缓慢,而2~10μm范围内的粒子数浓度随RH增加而减小;结合气溶胶表面积浓度与能见度进行相关性分析,表明0.5~2μm的细粒子及相对湿度是导致南京北郊秋冬季大气能见度下降的主要因素.