2 resultados para Pets

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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基于中国东北样带(NECT)30个植被样方调查和表土孢粉资料,从个体、群落水平研究了孢粉-植被关系,结果表明,孢粉类型与植被关系密切,在 = 0.05的显著性水平上,相关系数大于0.5;表土孢粉组合与植物群落间有较大的相似性,相似系数大于50%。采用定量描述花粉与植物关系的参数:联合指数(association)A、超代表性指数(over-representation)O、低代表性指数(under-representation)U、相关系数(correlation coefficient)C和代表性系数(representation coefficient)R等值,应用TWINSPAN分类、PCA排序和回归分析,把表土花粉类型划分为4类:具代表性类群组Group1,它们能正确反映植被;超代表性类群组Group2,它们常具有高花粉值与植被不成比例;低代表性类群组Group3,它们的花粉很难分离提取;以及低代表性类群的Group4,其花粉在土壤地层中较常见;指出一些常见花粉类型:松(Pinus)、桦(Betula)、栎(Quercus)、椴(Tilia)、槭(Acer)、榆(Ulmus)、蒿(Artemisia)、藜(Chenopodiaceae)、禾本科(Gramineae)和莎草科(Cyperaceae)的回归参数在东部森林区和西部草原区是有变化的,因此回归参数在应用于古植被恢复中要注意适用范围。 以Biomization模型为基础,根据植物的生理生态特性,定义了NECT孢粉类型的植物功能型(PETs)各种生物群区(Biome)的PFTs组合,构建了经表土孢粉检验的适用于NECT的以孢粉数据为驱动的模型框架,该模型模拟的生物群区与其化指标(气候、植物生理、土壤等)模拟划分的BIOME(Holdrige, BIOME3)是可比的,与植被类型有较好的对应性。 根据29剖面(986个样品)的孢粉数据,重建了NECT 6 kaB.P以来的生物群区。从时空二方面阐述了NECT6kaB.P以来生物群区的分布特点: (1)6ka B. P是一暖湿期,气温比现在高1~4℃,降水比现在多50%。落叶阔叶林分最广,面积最大。森林草原、落叶阔叶林、针阔混交林向西延伸最远。 (2)5ka B. P 是一降温期,气温比现在低2℃,降水多30%。有苔原、寒温带针叶林分布。 (3)4ka B. P是一暖湿期,气温比现在高1~2℃,降水比现在多50%。针阔光林和森林草原有最大分布面积。 (4)3Ka-2kaBP的气温与现代相似,降水比现在多20%左右。与4Ka B. P相比,森林和森林草原过渡带都向东移动。 (5)1Ka B. P的气温与现代相似,降水比现在多10%左右。草原向东大幅度扩张,森林分布面积减小。 (6)东部森林,中部森林草原,西部草原的分布格局的3Ka B. P基本确定,此后随着气候的不断变干冷,草原向东扩张。 (7)森林向扩张最大距离的时期发生在6Ka B. P,此时也是森林草原向西扩张最远时期。落叶阔叶林、针阔混交林、森林草原向西移动最大距离的时间是6Ka B. P,草原向西移动最远距离的时期发生在3Ka B. P。

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A three-dimensional MHD solver is described in the paper. The solver simulates reacting flows with nonequilibrium between translational-rotational, vibrational and electron translational modes. The conservation equations are discretized with implicit time marching and the second-order modified Steger-Warming scheme, and the resulted linear system is solved iteratively with Newton-Krylov-Schwarz method that is implemented by PETS,: package. The results of convergence tests arc plotted, which show good scalability and convergence around twice faster when compared with the DPLR method. Then five test runs are conducted simulating the experiments done at the NASA Ames MHD channel, and the calculated pressures, temperatures, electrical conductivity, back EMF, load factors and flow accelerations are shown to agree with the experimental data. Our computation shows that the electrical conductivity distribution is not uniform in the powered section of the MHD channel, and that it is important to include Joule heating in order to calculate the correct conductivity and the MHD acceleration.