中美县级土地整治政策对比研究

通过对比分析美国洛杉矶县住房供应规划中空闲地和低效利用地整治与我国县级城乡建设用地增减挂钩规划中农村空闲地和低效利用地整治在目的、空闲地和低效利用地确定、公共参与、与总体规划关系方面的差异,分析了我国目前县级城乡建设用地增减挂钩规划存在的不足,并进行了讨论。     

城市河道公共休闲的适宜性指标体系构建与评价简

城市河道是集城市生态保育、娱乐游憩、居住生活、景观等多重功能于一体的开放空间。对城市河道公共休闲空间的利用目前存在价值利用与控制难以协调的矛盾,构建城市河道公共休闲价值评价指标对城市河道休闲空间的规划与开发具有重要的现实意义。基于目前公众对城市河道休闲的识别要素,综合国内外学者对休闲空间评价、城市河道生态健康评价等研究,将城市河道公共休闲空间适宜性指标归纳为资源特性、形态特性、功能特性、文化特质、公共特性等5个维度共42项指标;综合考虑指标的代表性和易操作性等特征,在指标权重确定上,使用最常用的关联矩阵法,反映各指标的重要性差异;利用确定的指标体系和权重测度了北京城区已治理的14条河道的公共休闲适宜度。结果表明,北京市城市河道普遍存在生态景观特征较好,但实用性有待加强的现实问题。     

盐胁迫对红砂(Reaumuria soongorica)种子吸胀过程中生理特性的影响

以0%、0.5%、1.0%、1.5%、2.0%、2.5%、3.0%的NaCl和CaCl2溶液处理红砂(Reaumuria soongorica)种子,探讨了两种盐胁迫对种子吸胀过程中生理特性的影响及对种子的伤害程度。结果表明:红砂种子发芽率随两种盐胁迫的加剧极显著下降。种子丙二醛(MDA)含量在NaCl溶液胁迫后先下降后上升,在盐溶液浓度为1.0%时达到最小值,在2.5%处达到最大值;经不同浓度的CaCl2溶液胁迫后,MDA含量呈上升趋势,且均高于对照,最大值出现在3.0%处;种子内可溶性糖含量随NaCl和CaCl2溶液浓度的增大先下降后上升,分别在盐溶液浓度为1.0%和2.0%时达到最小值;种子过氧化氢酶(CAT)活性的变化较小;过氧化物酶(POD)活性随两种盐浓度的增加显著降低;超氧化物歧化酶(SOD)的活性随两种盐溶液浓度的增加先下降再上升又下降,但总体低于对照。经综合分析得出,CaCl2对红砂种子的伤害程度大于NaCl。     

梭梭(Haloxylon ammodendron)主根周围土壤特征

通过建立米级的空间尺度进行分层取样,研究了准噶尔盆地南缘建群种——梭梭(Haloxylon ammodendron)主根周围土壤的含水率、容重、pH值、电导率和养分含量的变化状况。结果表明:(1)土壤含水量在表层5cm处最小,土壤容重在0~40cm土层变动幅度不大,但随着与茎基垂线距离的增加,二者出现显著变化(p0.05)。(2)土壤pH值和电导率在主根区周围呈现聚集现象,最大聚集率均在0~1m圈层,但随着距离的增加,土层深度逐渐成为主导因素。(3)土壤养分在表层5cm处聚集,但水平聚集范围中除有机质和全氮可扩增到3~4m外,全磷和速效养分均在0~2m。本研究结论对于荒漠区耐盐性植被的合理密植有一定的理论意义。     

土壤氮、盐浓度对盐角草(Salicornia europaea)生长发育及氮素吸收的影响

以盐生植物盐角草(Salicornia europaea)为材料,以NaCl模拟不同盐度环境,盆栽试验了氮(0.3g·kg-1,N1;0.6g·kg-1,N2;1.2g·kg-1,N3;2.4g·kg-1,N4)、盐(2.5g·kg-1,S1;5.0g·kg-1,S2;7.5g·kg-1,S3)处理对其生长发育及氮素吸收利用的影响。结果表明:(1)不同盐度下施氮均可以显著促进盐角草的生长,地上部干质量均在N2处理下达到最大,而株高均在N1时达到最高,且施氮对盐角草生长的影响与盐度有关;(2)不同盐度环境下施氮所能达到的最高干物质产量及最高施氮限量不同,表现为S3S1S2,随着施氮量的增加,氮素生产力与氮素农学利用效率均表现出下降的趋势;(3)施氮显著增加了盐角草各器官含氮量及氮吸收量,同一施氮水平下盐角草各器官含氮量及氮吸收量均表现为同化枝茎根;(4)同一施氮水平下,随着盐度的增加,盐角草同化枝渗透势显著下降,同一盐度环境下,随着施氮量的增加,同化枝渗透势呈现出下降趋势,渗透调节能力增大;(5)3个盐度环境下,施氮均增加盐角草同化枝光合色素含量,从而提高光合效率,增强其对盐渍环境的适应能力。     

台风“达维”移动路径成因分析

利用NCEP/NCAR 1°×1°的6 h再分析资料和常规气象观测资料,综合分析了环流背景、"双台风效应"、冷空气活动和海陆下垫面对台风"达维"移动路径变化的影响,结果表明:(1)台风路径在登陆时第1次发生西折的主要原因是500 hPa副高东撤并由带状调整为块状分布,台风"苏拉"对"达维"吸附作用加强,且台风避开冷SST区趋向暖SST区行进;(2)鲁中山区的地形对台风第2次转向起到重要的阻挡作用,副高588线西伸明显,而副高边缘的西南气流增加了台风的东移分量,西风环流上短波槽的发展南下使台风向西移动的分量减弱消失,双台风强度的减弱和距离的增加使台风的吸附作用迅速减弱,这些因素共同导致了台风第2次转向。     

Effects of corridor networks on plant species composition and diversity in an intensive agriculture landscape

The development of modern agriculture has resulted in much homogenization of the landscape consisting of large patches of farmland,so small remnant non-crop habitats especially linear corridors play an important role in the conservation of species and the maintenance of ecosystem functions.However,little attention has been paid to the effects of corridors structural characteristics on the plant species restricted to such habitats.In this study,we selected three types of corridors including ditch,hedgerow and road,and ana-lyzed their structural characteristics.The plant species presented in these corridors were investigated,and the species diversity,abun-dance and frequency were estimated.Moreover,spatial arrangements of corridors were classified into different types to discuss whether there were significant effects of corridor network on plant distribution.The results show that three types of corridors have different ef-fects on plant species composition and diversity.The one-one combined corridor networks and total network associated by three corri-dors have more complex structural features than each single type of corridor.However,there is no strong correlation between the corri-dor networks with their plant species.We suggest that carrying out a pointed vegetation survey at corridor intersections to further test the relationships between structural features of corridor and plants is necessary.     

采用非线性决策树的学生课堂教学满意度研究

学生反馈是评估高等院校课堂教学质量的重要指标。目前,对学生反馈的问卷仅进行主观理解和简单统计,无法提供准确定量的分析和支持依据。使用非线性决策树,对近3年本科必修双语课程《数字图像处理》的学生评教问卷进行数据挖掘,首先将其分成3类和10个不同输入,然后通过数据预处理、模型选择和建模,最后构建树状模型对其进行分析。分析结果符合对于该课程学生反应和争议较大的问题预期,为课程设计提供定量有效的教学分析工具。     

Warmer-Get-Wetter or Wet-Get-Wetter? A Criterion to Classify Oceanic Precipitation

In this study, the temporal and spatial variations of observed global oceanic precipitation during 1979–2010 are investigated. It is found that the global trend in precipitation during this period varies at a rate of 1.5%/K of surface warming while the rate is 6.6%/K during 2006–2010. The precipitation is highly correlated with Sea Surface Temperature(SST) in both the temporal and the spatial patterns since the strong 1997–98 El Nino event. Considering the distributions of precipitation and SST, seven oceanic regions are classified and presented using the observed Global Precipitation Climatology Project(GPCP) data and Extended Reconstructed Sea Surface Temperatures, version 3(ERSST.v3) data. Further examining the mechanisms of the classified oceanic precipitation regions is conducted using the Tropical Rainfall Measuring Mission(TRMM) satellite, GFDL-ESM-2G model precipitation and SST data and Hadley Center sea ice and SST version 1(Had ISST1) data. More than 85% of global oceanic precipitations are controlled by either one or both of the warmer-get-wetter mechanism and wet-get-wetter mechanism. It is estimated that a 0.5 SST signal-to-noise ratio, representing the trend of SST time series to the standard deviation, is a criterion to distinguish the mechanism of a region. When the SST ratio is larger than 0.5, the precipitation of this region is controlled by the warmer-get-wetter mechanism. SST, rather than the humidity, is the pivotal factor. On the other hand, when the SST ratio is less than 0.5, the precipitation is controlled by the wet-get-wetter mechanism. The SST variability is a significant factor contributing to the precipitation variation.     

Verifying Fossil-Fuel Carbon Dioxide Emissions Forecasted by an Artificial Neural Network with the GEOS-Chem Model

In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions （ff） in 2009. The authors built and trained 29 Elman neural net- works based on the monthly average grid emission data （1979-2008） from different geographical regions. A three-dimensional global chemical transport model, God- dard Earth Observing System （GEOS）-Chem, was applied to verify the effectiveness of the networks. The results showed that the networks captured the annual increasing trend and interannual variation of ff well. The difference between the simulations with the original and predicted ff ranged from -1 ppmv to 1 ppmv globally. Meanwhile, the authors evaluated the observed and simulated north-south gradient of the atmospheric CO2 concentrations near the surface. The two simulated gradients appeared to have a similar changing pattern to the observations, with a slightly higher background CO2 concentration, - 1 ppmv. The results indicate that the Elman neural network is a useful tool for better understanding the spatial and tem- poral distribution of the atmospheric C02 concentration and ft.