Matching the Multiple Scales of Conservation with the Multiple Scales of Climate Change

Abstract:  To anticipate the rapidly changing world resulting from global climate change, the projections of climate models must be incorporated into conservation. This requires that the scales of conservation be aligned with the scales of climate-change projections. We considered how conservation has incorporated spatial scale into protecting biodiversity, how the projections of climate-change models vary with scale, and how the two do or do not align. Conservation planners use information about past and current ecological conditions at multiple scales to identify conservation targets and threats and guide conservation actions. Projections of climate change are also made at multiple scales, from global and regional circulation models to projections downscaled to local scales. These downscaled projections carry with them the uncertainties associated with the broad-scale models from which they are derived; thus, their high resolution may be more apparent than real. Conservation at regional or global scales is about establishing priorities and influencing policy. At these scales, the coarseness and uncertainties of global and regional climate models may be less important than what they reveal about possible futures. At the ecoregional scale, the uncertainties associated with downscaling climate models become more critical because the distributions of conservation targets on which plans are founded may shift under future climates. At a local scale, variations in topography and land cover influence local climate, often overriding the projections of broad-scale climate models and increasing uncertainty. Despite the uncertainties, ecologists and conservationists must work with climate-change modelers to focus on the most likely projections. The future will be different from the past and full of surprises; judicious use of model projections at appropriate scales may help us prepare.     

中国工业SO2排放量动态变化分析

中国工业SO2减排工作的重点。经济增长、经济空间结构变化、技术进步是影响污染物排放量变化的三个重要因素。在分析我国工业SO2排放量、排放结构、排放强度等变化趋势的基础上,通过构建对数平均权重分解模型定量分解经济增长、结构变化、技术进步这3个因素对工业SO2排放量变化的贡献。结果表明：（1）中国工业SO2排放量年均增长48.7×10^4 t,年均增长率为3.2%,且2002—2006年增速加快;（2）分地区看,1991年以来,东部地区SO2排放量所占比重明显下降,中部地区略有上升,而西部地区所占比重增加显著;（3）单位产值工业SO2排放强度在研究期内迅速降低,年均下降幅度为8.4%,对减缓SO2排放量的过快增长起到了积极作用;（4）经济增长平均每年促进SO2排放量增长183.7×10^4 t,技术进步则平均每年使SO2排放量减少134.2×10^4 t,空间结构因素平均每年减少SO2排放量0.8×10^4 t。可以看出,长期以来,虽然我国的技术水平有了一定程度提高,但经济规模的扩张使中国工业SO2排放量持续增长,对中国环境压力形成了巨大压力,同时,经济总量在不同地区的分配对SO2排放量的影响也在不断变化中。     

Lead astray: scale,environmental justice and the El Paso smelter

Residents in Paso del Norte (El Paso, Texas; Sunland Park, New Mexico; and Juárez, Mexico) have been concerned about heavy metal contamination in their communities since the 1970s, when high blood lead levels were found in children living in Smeltertown – a company town for the local metals smelter. After the smelter's closure in 1999, and throughout onsite and offsite cleanup efforts, residents have continued to express concerns about these contamination issues. Using a politics of scale framework and analysing ethnographic data and government, media and scientific documents, this paper identifies a set of major disjunctures between the scales of heavy metal contamination and the scales at which that contamination is regulated. These disjunctures exacerbate regional environmental injustice by complicating public participation, neglecting vulnerability and displacing hazards to new communities. Consequently, applying a politics of scale framework to this case study highlights regulatory and policy failures to address environmental justice.     

PM_(10)浓度时间序列多时间尺度分析的小波方法

文章利用Morlet小波函数进行小波变换,以乌鲁木齐市的大气污染物时间序列为例,分析了当地PM10的多时间尺度的演变特性。研究结果显示,其年际变化和季节性变化的时间尺度在尺度空间中分布不均匀,受气象和污染源因素影响,具有较明显的局部化特征。     

中国第四纪黄土古环境研究若干进展

随着技术进步和多方位研究进展,第四纪古环境研究向着多元古环境替代指标、高分辨率古气候研究、气候变化的多种驱动因素等方面发展。文章总结了中国黄土古环境研究中的主要替代性指标,包括黄土磁化率、黄土粒度、植物硅酸体、孢粉组合、蜗牛化石、碳氧同位素和^10Be、黄土与古土壤。概述了当前对黄土—古土壤的时间标尺、末次冰期的短尺度气候事件以及东亚古季风变化机制的认识。     

基于非参数方法的中国棉花产出规模效率时空特征

人类需要的无限性和用来满足需要的各种稀缺资源之间的矛盾,要求人们对生产资源进行有效配置。为研究中国棉花流通体制市场化改革以来,棉花生产资源的配置效率--产出规模效率及其时空特征,基于生产前沿面理论的非参数方法,利用生产资源配置效率测度软件对中国棉花主产区的棉花产出规模效率进行了具体测定与分析。结果表明：中国棉花产出规模效率时空差异显著,报告期长江流域优于黄河流域,同时两大流域棉花产出规模效率变化态势与我国棉花流通体制市场化改革的政策安排高度相关。认为中央政府应根据市场化进程中棉花生产所表现出来的新特点与市场调节出现的新问题,适时做出进一步激励棉花生产,最大程度发挥产出规模效率的政策安排。     

中国城市用地增长极限规模测算

快速城市化出现的城市建设用地扩张问题,受到人们广泛关注,借鉴发达国家经验,我国需要测算一个极限区间值进行自上而下的总量控制,以促进最严格耕地保护制度和节约用地制度的落实.但是如何测算这个极限规模一直没有得到很好解决.本文提出了一个常规方法组合和关键指标相结合的技术思路来尝试解决这个问题.研究首先对城市用地扩展规模的影响因子进行了分析,讨论了城市人口数量和GDP分别与建成区面积相关性,确定了城市人口数量对建成区面积影响更大;在此基础上,采用逻辑斯蒂模型,依据我国1950-2010年经济数据,对城市化水平进行预测;用自回归分布滞后模型,依据1951-2010年全国人口数据对未来人口规模进行预测,并分为三个方案对结果进行了讨论;最后按照城市用地分类与规划建设用地标准,以节约集约用地为原则,将人均城市用地规模取值控制在65.0-115.0 m2,计算城市用地扩展极限规模.结果表明,到2045年,中国的城市化预测水平为79.99％,在中国人口增长控制较好的情况下,人口规模将达到14.97亿人,城市用地扩展规模为77 857.38-137 747.70 km1;若中国人口达到有关研究的预测峰值16亿人,中国城市化水平稳定在80％,城市用地扩展极限规模将会是83 200.00-147 200.00 km2.综合以上分析,未来我国的城市建设用地总量应在7.8万km2到14.7万km2之间.     

大空间建筑烟气填充研究方法的对比

为了对大空间建筑烟气填充研究方法进行对比分析。以一个废弃的大空间仓库为研究对象,采用了全尺寸火灾实验、计算机数值模拟和理论分析相互应用验证的研究方法,研究理论及数值模拟两种火灾烟气层高度的描述方法的准确性。结果表明当采用t2火模型时,在与现实的吻合程度方面,数值模拟〉Zukoski理论模型〉Yamana-Tanaka理论模型;随着火灾的不断发展,相对误差逐渐增大。通过对比分析发现,全尺寸实验、理论模型和数值模拟三种方法相互验证可以更好地保证研究的准确性;总结得到了两种与现实较吻合的描述烟气层高度的理论方法,并且提出减小误差应注意的几点事项,包括尽可能提高火源热释放速率、烟气层温度描述的准确性;不考虑火源热量通过建筑边界结构散失等。     

基于亲景度和竞争态的京沪陕入境旅游市场研究

依据1999-2008年相关统计数据,选取我国入境旅游市场份额前13位的客源国,以北京、上海、陕西等三大入境旅游热点地区为研究对象,利用亲景度指标,分析总结了其入境旅游市场的时空动态变化规律及深层原因,并引入竞争态模型,重点选取日本、韩国、美国三大客源市场进行京沪陕三地的比较研究.     

Forecasting population trend from the scaling pattern of occupancy

Forecasting the temporal trend of a focal species, its range expansion or retraction, provides crucial information regarding population viability. To this end, we require the accumulation of temporal records which is evidently time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution across large scales. Therefore, it would be appealing to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields of range dynamics, occupancy scaling and spatial autocorrelation, here I present a model for forecasting the population trend solely from its spatial distribution. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in species range sizes and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a single snapshot of its current distribution. Further applications in biodiversity conservation could provide a swift risk assessment, especially, for endangered and invasive species.