Seasonal dynamics of soil CO_2 effluxes with responses to environmental factors in lower subtropical forests of China

Seasonal metrics and environmental responses to forestry soil surface CO2 emission effluxes among three types of lower subtropical forests were consistently monitored over two years with static chamber-gas chromatograph techniques among three types of lower subtropical forests. Results showed that annual CO2 effluxes (S L) reached 3942.20, 3422.36 and 2163.02 CO2 g·m-2·a-1, respectively in the monsoon evergreen broadleaf forest, mixed broadleaf-coniferous forest and coniferous forest. All the three types of forests revealed the same characteristics of seasonal changes with the CO2 effluxes peaking throughout June to August. During this peaking period, the effluxes were 35.9%, 38.1% and 40.2% of the total annual effluxes, respectively. The CO2 emission process responding to the environmental factors displayed significantly different patterns in forestry soils of the three types of forests. The coniferous forest (CF) was more sensitive to temperature than the other two types. The Q10 values were higher, along with greater seasonal variations of the CO2 efflux, indicating that the structurally unique forestry ecosystem has disadvantage against interferences. All the three types of forestry CO2 effluxes showed significant correlation with the soil temperature (Ts), soil water content (Ms) and air pressure (Pa). However, stepwise regression analysis indicated no significant correlation between air pressure and the soil CO2 efflux. With an empirical model to measure soil temperature and water content in 5 cm beneath the soil surface, the CO2 effluxes accounting for 75.7%, 77.8% and 86.5% of the efflux variability respectively in soils of BF, MF and PF were calculated. This model can be better used to evaluate the CO2 emission of soils under water stress and arid or semi-arid conditions.     

Mineralogical and geochemical study of a newly discovered mafic granulite, northwest China: Implications for tectonic evolution of the Altay Orogenic Belt

Abstract A mafic granulite body was newly discovered in the Altay Orogenic Belt, northwest China. The rocks comprise a suite of coarse‐grained and fine‐grained granulites. Orthopyroxenes (hypersthenes) in the rocks have high X_Mg and low Al₂O₃ contents, whereas clinopyroxenes have low TiO₂ and Al₂O₃ contents. Amphiboles and biotites have a high Mg/(Mg + Fe²⁺) ratio and low contents of F and Cl. The peak metamorphic pressure–temperature (P–T) conditions are estimated as 750–780°C and 6–7 kbar, and retrograde P–T conditions are in the range of 590–620°C and 2.3–3.7 kbar, indicating significant decompression. Metamorphic reactions and P–T estimates define a clockwise P–T path. Geochemically, the rocks are high in Mg/(Mg + Fe) and Al₂O₃, depleted in U, Th, K and Rb, and characterized by light rare earth element enrichment and a weak positive Eu anomaly. The Altay mafic granulite shows depleted Nb, P and Ti contents in the mid‐oceanic ridge basalt normalized spider diagram. The geochemical characteristics suggest that the protolith of the Altay mafic granulite was calc‐alkaline basalt and andesite with an island‐arc affinity. The rock has a high ¹⁴³Nd/¹⁴⁴Nd ratio with ?Nd(0) > 0, indicating derivation from a mantle‐depleted source. In the present study, a two‐stage model for the evolution of the Altay mafic granulite is proposed: an early stage in which calc‐alkaline basalt and andesite with island‐arc affinity were subducted into a deeper level of the crust and subjected to granulite‐facies metamorphism generating the mafic granulite, followed by the later stage exhumation of the system into the upper crust by the late Paleozoic thrusting.     

基于? -SVR算法的隧道围岩位移演化规律预测

针对目前广泛应用的灰色理论、遗传算法(GA)和人工神经网络(ANN)等方法预测隧道稳定性的缺陷，提出应用稳健性能较好的? -SVR（support vector machine）算法对非对称连拱隧道围岩位移演化规律进行预测研究。应用加速混合遗传算法搜索? -SVR最优参数，以提高? -SVR的预测能力。将预测结果与灰色理论、BP神经网络预测结果进行比较，显示? -SVR算法学习和预测精度高。     

黄河源区早更新世含植物化石地层的发现及意义

通过对扎根加陇早更新世湖相地层(1919.6kaB.P.)、棒咯涌K5号钻孔早更新世河湖相地层(1135.9～945.4kaB.P.)、野牛河西岸早更新世河湖相地层(1548.2～765.4kaB.P.)以及产于扎根加陇早更新世湖相地层中的植物化石、各剖面孢粉资料的分析,获知黄河源区早更新世早期为亚热带山地针叶林植被景观,地层中木本植物花粉占绝对优势,以针叶植物云杉属、松属、冷杉属、铁杉属为主,是源区动植物发育的鼎盛时期;进入早更新世晚期初,乔木植物花粉迅速减少乃至全部消失,草本植物花粉大幅度增加。晚期末,孢粉出现贫化,以草本植物花粉为主,呈现荒漠草原植被景观。提出了现今黄河源区生态地质环境的形成是地质演化的必然结果。     

进化策略算法在地面沉降量计算参数反演中的应用

多数情况下,评估的研究区缺乏多年积累的地下水位及开采量资料。因此,通常采用土力学模型,根据太沙基固结理论,进行地面沉降量预测。在地面沉降量计算中,土层变形参数值的选取直接影响计算结果的精确性。深层含水层埋深通常大于100m。通过现场勘探,采取土样进行岩土物理力学性质试验获取参数值,成本过于昂贵。通过参考区域土层物理力学性质资料,结合工程经验获取参数值,预测结果的精度得不到保证。针对上述情况,作者提出用非线性优化算法-进化策略算法,根据实测地面沉降量反演土层变形参数值。通过这种方法确定参数值,既节约成本,又保证了计算结果的可靠性。进化策略算法通过模拟生物遗传及进化过程,利用转移概率来帮助指导搜索。搜索结果不依赖于初始点的选择,对于求解全局最优解有很强的鲁棒性。作者将进化策略算法用于某一工程实例土层变形参数的反演,结果表明了该算法的可行性及稳健性,值得在工程实践中推广应用。     

长白山区图们江流域新生代火山岩的岩石化学研究

图们江流域新生代火山岩以溢流式喷发为特征，其主要岩石类型以拉斑玄武岩为主，含少量玄武质粗安岩、碱性玄武岩、玄武质安山岩和粗面玄武岩。根据图们江流域火山岩的Mg#（Mg#=100Mg^2＋／（Mg^2＋＋Fe^2＋））值多数≤60，Ni含量〈100μg／g和主、微量元素地球化学特征综合表明，形成火山岩的岩浆不是原始岩浆，它们是原始岩浆在上地幔经历了橄榄石、辉石分离结晶作用后形成的以拉斑玄武岩为主，包括碱性玄武岩和粗面玄武岩等演化岩浆，结晶分异作用是岩浆演化过程的主要控制因素。拉斑玄武质岩浆在上升过程中发生了不同程度的壳源物质同化混染作用，发生在上地壳遭受较大程度混染的岩浆K2O含量明显偏高（〉2．6％），形成玄武质粗安岩。     

吉林伊通-大屯地区晚中生代-新生代玄武岩的地球化学特征及其意义

吉林伊通-大屯地区有长达80Ma的火山喷发历史,为探讨该区深部地质演化提供了条件。从晚白垩长春大屯火山(92．5±0．5Ma)到伊舒地堑内第三纪伊通火山群(31Ma、9～15Ma),玄武岩碱性逐渐增强,Dy/Yb比值逐渐升高,根据地幔动态熔融模型计算获得的玄武岩最终形成深度由约50km变深至110km。根据岩石圈盖效应推测该区晚白垩纪以来岩石圈厚度逐渐增厚。伊通第三纪碱性玄武岩显示了均一的地球化学组成;类似洋岛玄武岩(OIB)的微量元素分配模式和Nb/U比值,以及低(~(87)Sr/~(86)Sr)_i、正ε_(Nd)(t)同位素特征暗示它主要来源于软流圈。与第三纪碱性玄武岩相比,晚白垩大屯拉斑玄武岩具有相对偏高的Ni、Cr和Sc,高Ba/Th、Rb/Nb、Ba/Nb比值,高(~(87)Sr/~(86)Sr)_i和低(~(143)Nd/~(144)Nd)_i。这些特征可能与软流圈熔体与古老富集地幔之间的相互反应有关。伊通-大屯玄武岩的演化特征反映了岩石圈在板内岩浆作用中所担当的不同角色:第三纪时,岩石圈并没有在物质上直接参与岩浆作用,但岩石圈对上涌软流圈起到了机械阻挡作用;而在晚白垩岩浆作用中,岩石圈的间接和直接作用都得到了体现。     

两类ENSO事件赤道太平洋次表层海温异常的演变特征

基于美国马里兰大学提供的海洋同化(SODA)月平均资料,用个例和合成分析方法,剖析了两类ENSO事件赤道太平洋海温异常演变特征。结果指出,东部型ENSO事件的初始海温异常源来自赤道西太平洋次表层,海温异常中心沿气候温跃层向东向上传送,至赤道东太平洋表层形成ENSO事件。东部型ENSO冷暖事件互为初始场,在形成某一位相的ENSO事件的过程中也同时为相反位相的ENSO事件准备条件。中部型ENSO事件的初始海温异常源出现在赤道中太平洋次表层,海温异常中心沿气候温跃层向东向上传送至赤道中东太平洋表层形成ENSO事件。中部型ENSO事件多在前次事件减弱中断后出现。     

环境同位素和模糊聚类法研究堤坝渗漏

利用环境同位素方法对高水河堤防几个典型段进行了渗漏分析,查明了其地下水的渗漏来源,结果表明,江都船厂段T1#孔、小菜谭段T23#孔中的地下水为河水补给来源,T5#孔附近的黑鱼塘水为当地降雨补给,万寿宫段T7#孔中的地下水为河水和当地降雨的混合。由于环境同位素的分析方法只能定性的说明问题,笔者尝试应用模糊聚类方法,选取环境同位素和水化学值作为指标特征值,并赋与不同的权重,进行模糊聚类分析,分析结果与环境同位素、水化学分析结论一致。     

环境同位素在水循环研究中的应用

环境同位素广泛存在于自然界水体中,在降水、地表水、地下水、土壤水和植物体内相互转化的水循环过程中,同位素的分馏效应导致不同水体具有不同的同位素含量。利用不同水体同位素含量之间的差异,可研究它们之间的相互转化方式及转化量。介绍了环境同位素在大气降水和降水-地表水-地下水“三水”之间转化中的研究进展,并阐述了其在水循环应用中存在的问题及应用前景。