长江经济带新型城镇化协调性的空间差异与时空演化

从城乡、产城、区域和城镇化与资源环境协调发展4个方面建立指标体系,衡量长江经济带105个地级及以上市新型城镇化的协调性,并运用泰尔系数和探索性空间分析考察协调性的空间差异和时空演化,结果发现:长江经济带新型城镇化协调性存在明显的反地势分布和"城市圈俱乐部"特征;东、中、西部城镇化协调性差异随时间越来越明显,东部城市主要体现在非省会城市之间的差异,中部主要体现在省会城市与非省会城市的组间差异,西部主要体现在省会城市之间以及省会城市和非省会城市之间的组间差异;长江经济带新型城镇化协调性表现出正的全局空间自相关,协调性高的区域开始集聚在一起,这种趋势随时间不断增强并且空间溢出效应明显。     

长湖流域水质时空分布特征及影响因子

利用2009—2014年长湖5个水质监测点数据,采用时间序列法分析了长湖水质的时间变化规律,采用相关性分析法,分析了流域水污染的影响因子。结果表明:在时间上,长湖水污染物质量浓度季节变化明显,COD、TN、NH3-N均为7、9月较低,1、3月较高,丰水期水质好于枯水期。入湖地区TP质量浓度7月达最高值,且7月份入湖地区的桥河口、关沮口的NH3-N、TN含量稍高于5月。空间上,西北部入湖地区水质劣于湖心及东南部出湖地区。工业、生活等点源污水,以耕地为主的农业非点源以及天然降水量和径流量是影响水质的主要因素,入湖排污量、降水量和径流量与长湖水质呈显著相关关系(P0.05)。     

长江中游城市群经济与生态成本空间演化模式分析

综合运用变异系数、泰尔指数及ESDA-GIS多种方法,在充分考虑传统经济影响因子的基础上,尝试引入经济发展生态成本指标,分析长江中游城市群经济综合发展水平与生态成本的空间匹配及演化模式。研究表明:经济综合发展水平高低聚集特征明显,空间极化现象是导致区域经济发展不平衡的主要原因;生态成本空间集聚现象以高高集聚和低低集聚为主,且呈现出高高集聚减少、低低集聚增多的现象,生态成本消耗有所改善;2001~2012年长江中游城市群市域经济综合发展水平与生态成本表现出越来越显著的差异化空间格局,呈现出由低经济综合发展水平-低生态成本过渡到高经济综合发展水平-高生态成本,进而发展到高经济综合发展水平-低生态成本的空间匹配模式的阶段性特征;高经济综合发展水平-高生态成本的经济发展模式仍在大部分城市中存在,经济与生态空间协调发展的潜力仍然很大。     

2000~2014年武汉市城市扩展时空特征分析

基于不同时相的高分辨率遥感影像，采用面向对象的解译方法提取了武汉市2000、2005、2010和2014年的土地覆被信息，从城市扩展强度指数，城市中心坐标迁移和分形维数等方面分析了武汉市2000～2014年城市扩展时空特征。结果表明：2000～2014年间，武汉市城市扩展强度指数为1.41，各主城区城市扩展强度不一，洪山区建设用地的增加对主城区城市扩展的贡献最大；在扩展过程中，武汉市城市分形维数增加，城市空间形态变复杂；其扩展呈现核心-放射扩展模式，并逐渐转向圈层式；自然条件、经济、人口、交通、政策和城市规划是武汉市城市扩展的主要驱动力，但随着交通的发展，自然条件和经济对武汉市城市扩展的驱动作用正逐渐减弱。     

中国碳排放强度的时空演进及跃迁机制

面对气候变化所带来的生存危机以及环境治理的复杂状况,对中国碳排放强度时空演进的动态监测与预警治理的研究是实现碳排放强度下降目标的关键。文章测算1997—2015年中国大陆30个省区碳排放强度的空间面板数据,采用探索性时空数据分析(ESTDA)方法对中国碳排放强度的空间相关性、集聚特征及其时空跃迁进行空间统计分析,借助分位数回归与时空跃迁嵌套模型,揭示在时间和空间推移的双重作用下中国各省区碳排放强度的时空跃迁机制。研究结果表明:(1)中国30个省区的碳排放强度在时空分布上并不是完全随机状态,各个省区碳排放强度之间具有显著的空间相关性特征,碳排放强度的变动趋势会受到其相临近省区碳排放强度的影响,省域间的碳排放强度在空间分布上呈现"集聚"与"分异"并存的时空演进特征。(2)中国碳排放强度空间集聚趋势增强,具有高度的凝固性和较低的流动性,10个高碳排放强度省区碳排放强度的稳定性将成为制约中国碳排放强度整体跃迁的重点省区,相关省区的跃迁性将成为驱动中国碳排放强度整体跃迁的关键省区。(3)各省区的碳排放强度空间集聚过程中存在时空跃迁的驱动模式和制约模式,分位数回归模型能够很好地解释各驱动因素对碳排放强度时空跃迁的驱动机制,不同响应阶段的驱动因素的分位数与碳排放强度时空跃迁类型之间具有很强的嵌套性。(4)根据各省区碳排放强度时空演进及其跃迁机制的分析结果,进一步提出加强对关键省区碳排放强度的有效监测与治理,加大碳排放的约束力度等差异化的碳减排调控措施。     

Community gardening: cultivating subjectivities,space, and justice

Community gardens have been lauded for being inherently resistant to neoliberalism and criticised for underwriting it. To move beyond this either/or debate, we need to employ more focused lenses and specify both the processes of neoliberalisation at play and the outcomes they can produce. This paper explores the ways in which neoliberal processes of privatisation, state entrepreneurialism, and devolution intersect with community gardens, and the subjectivities that may be cultivated, the spaces that may be created and the types of justice that may be advanced as a result. It argues that certain characteristics and orientations of gardens are more conducive to resisting neoliberalism. These include the cultivation of producer, citizen, and activist subjectivities (over those of consumer, entrepreneur, and volunteer); the elevation of the use value of shared lived space (over a site’s potential exchange value) and the advancement of spatial justice through community access to non-privatised space; and food justice, through non-commodified means of obtaining food. Holding these ends in mind can help ensure that proponents of community gardening sow the seeds of the fruits they most wish to reap.     

太原市土壤六六六和滴滴涕的暴露格局及健康风险

为研究六六六(HCHs)和滴滴涕(DDTs)在太原市不同功能区土壤中的暴露格局、来源以及对周围人群的健康风险,在太原市化工区、灌区、矿区、生态区周边荒地土壤中进行采样,分析测定了土壤中HCHs和DDTs含量,根据太原市人群实际情况的暴露参数和USEPA的部分参数,对土壤HCHs和DDTs的健康风险进行评价。结果表明:1)太原市表层土壤中HCHs的平均含量大小依次为化工区>灌区>矿区>生态区;DDTs平均含量的大小依次为化工区>灌区>矿区>生态区,仅6%的HCHs和3%的DDTs和的平均残留水平均高于我国土壤质量标准一级标准,但均不超过二级标准值;2)土壤中HCHs残留主要源于历史上林丹的使用,DDTs残留则来源于历史和新污染源的共同影响;3)太原市表层土壤HCHs和DDTs致癌风险大小为化工园区>矿区>灌区>生态区。非致癌风险大小为化工区>矿区>灌区>生态区。3种暴露途径的在不同功能区的健康风险贡献率大小均为经口摄入>呼吸吸入>皮肤接触;综合来看太原市表层土壤中的HCHs和DDTs并未对人类造成非致癌风险,但有一定的致癌风险。本文的研究结果可为太原市土壤质量评价和环境污染防治提供科学指导,并对太原市人群的健康风险防治提供依据。     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

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     

Industrial pollution,spatial stigma and economic decline: the case of Asopos river basin through the lens of local small business owners

This paper explores the notion of environmentally induced spatial stigma through an analysis of data from interviews across public attitudes to pollution within the Asopos river basin in central Greece. The area has a 40 year plus history of legal and illicit industrial waste disposal and public debate on the associated environmental degradation. The study focuses on the perceptions and beliefs of a sector of the community likely to be directly and negatively affected by stigma, that is small business owners in the tourism and hospitality sector. The qualitative analysis explores awareness and viewpoints on environmental degradation and water quality within the local context, implications for the local economy and the individual's own enterprise, views on industrial environmental management as well as corporate responsibility and future prospects for the environmental problems of Asopos. Findings reveal a noticeable variation in views on industrial pollution and ecosystem deterioration among the respondents, but overall a strong environmentally induced stigmatization of the area. They also uncover an information asymmetry and lack of credible commitment by government bodies and industry members in disclosing accurate information, a situation likely to increase speculation and uncertainty within the community. The paper concludes by addressing implications of the findings to policy-making and managerial considerations, along with future research perspectives which aim to increase considerations of sustainability aspects for local development.