Evaluating the role of climate and tectonics during non-steady incision of the Yellow River: evidence from a 1.24 Ma terrace record near Lanzhou,China

The competing roles of bedrock uplift and climatic change in the formation of fluvial terraces remain uncertain. Most of recent studies have attributed terrace formation to climatic changes and held that, even in tectonically active settings, climate variations control cycles of terrace planation and abandonment. Based on field investigations of loess-paleosol sequences, magnetostratigraphy and optically stimulated luminescence (OSL) dating, we develop a new chronology for a spectacular flight of terraces along the Yellow River near Lanzhou, China over past 1.24 Ma. All the terraces are strikingly similar in that they have several meters of paleosol developed directly above fluvial deposits on the terrace treads, suggesting that the abandonment of each terrace due to river incision occurs during the transition from glacial to interglacial climates. However, the ages of terraces cluster in two relatively short time periods (1.24–0.86 Ma and 0.13 Ma – present). During the intervening time between 0.86 Ma and 0.13 Ma, terraces either did not form or were not preserved. We suggest that this record indicates that rock uplift rates varied through time and influenced terrace formation/preservation. Thus, our results demonstrate the utility of deep chronologic records from fluvial terraces for deconvolving the effects of tectonics and climate on fluvial incision.     

Simulating CO2 flux of three different ecosystems in ChinaFLUX based on artificial neural networks

The nonlinearity of the relationship between CO₂ flux and other micrometeorological variables flux parameters limits the applicability of carbon flux models to accurately estimate the flux dynamics. However, the need for carbon dioxide (CO₂) estimations covering larger areas and the limitations of the point eddy covariance technique to address this requirement necessitates the modeling of CO₂ flux from other micrometeorological variables. Artificial neural networks (ANN) are used because of their power to fit highly nonlinear relations between input and output variables without explaining the nature of the phenomena. This paper applied a multilayer perception ANN technique with error back propagation algorithm to simulate CO₂ flux on three different ecosystems (forest, grassland and cropland) in ChinaFLUX. Energy flux (net radiation, latent heat, sensible heat and soil heat flux) and temperature (air and soil) and soil moisture were used to train the ANN and predict the CO₂ flux. Diurnal half-hourly fluxes data of observations from June to August in 2003 were divided into training, validating and testing. Results of the CO₂ flux simulation show that the technique can successfully predict the observed values with R ² value between 0.75 and 0.866. It is also found that the soil moisture could not improve the simulative accuracy without water stress. The analysis of the contribution of input variables in ANN shows that the ANN is not a black box model, it can tell us about the controlling parameters of NEE in different ecosystems and micrometeorological environment. The results indicate the ANN is not only a reliable, efficient technique to estimate regional or global CO₂ flux from point measurements and understand the spatiotemporal budget of the CO₂ fluxes, but also can identify the relations between the CO₂ flux and micrometeorological variables.

     

Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares

The feasibility of using fluorescence excitation-emission matrix (EEM) along with parallel factor analysis (PARAFAC) and nonnegative least squares (NNLS) method for the differentiation of phytoplankton taxonomic groups was investigated. Forty-one phytoplankton species belonging to 28 genera of five divisions were studied. First, the PARAFAC model was applied to EEMs, and 15 fluorescence components were generated. Second, 15 fluorescence components were found to have a strong discriminating capability based on Bayesian discriminant analysis (BDA). Third, all spectra of the fluorescence component compositions for the 41 phytoplankton species were spectrographically sorted into 61 reference spectra using hierarchical cluster analysis (HCA), and then, the reference spectra were used to establish a database. Finally, the phytoplankton taxonomic groups was differentiated by the reference spectra database using the NNLS method. The five phytoplankton groups were differentiated with the correct discrimination ratios (CDRs) of 100% for single-species samples at the division level. The CDRs for the mixtures were above 91% for the dominant phytoplankton species and above 73% for the subdominant phytoplankton species. Sixteen of the 85 field samples collected from the Changjiang River estuary were analyzed by both HPLC-CHEMTAX and the fluorometric technique developed. The results of both methods reveal that Bacillariophyta was the dominant algal group in these 16 samples and that the subdominant algal groups comprised Dinophyta, Chlorophyta and Cryptophyta. The differentiation results by the fluorometric technique were in good agreement with those from HPLC-CHEMTAX. The results indicate that the fluorometric technique could differentiate algal taxonomic groups accurately at the division level.     

Spatio-seasonal patterns of fish diversity,Haizhou Bay,China

Spatial-seasonal patterns in fish diversity in Haizhou Bay were studied based on stratified random surveys conducted in 2011.Principal component analysis was conducted to distinguish different diversity components,and the relationships among 11 diversity indices were explored.Generalized additive models were constructed to examine the environmental effects on diversity indices.Eleven diversity indices were grouped into four components:(1) species numbers and richness,(2) heterogeneous indices,(3) evenness,and(4) taxonomic relatedness.The results show that diversity indices among different components are complementary.Spatial patterns show that fish diversity was higher in coastal areas,which was affected by complex bottom topography and spatial variations of water mass and currents.Seasonal trends could be best explained by the seasonal migration of dominant fish species.Fish diversity generally declined with increasing depth except for taxonomic distinctness,which increased with latitude.In addition,bottom temperature had a significant effect on diversity index of richness.These results indicate that substrate complexity and environmental gradients had important influences on fish diversity patterns,and these factors should be considered in fishery resource management and conservation.Furthermore,diversity in two functional groups(demersal/pelagic fishes) was influenced by different environmental factors.Therefore,the distribution of individual species or new indicators in diversity should be applied to examine spatio-seasonal variations in fish diversity.     

南海北部琼东南盆地陵水段峡谷沉积建造及勘探意义

琼东南盆地中央峡谷为一大型轴向峡谷体系,具有明显的"分段性"特征,不同区段沉积充填和内部结构均存在明显的差异,其中陵水段位于峡谷西段,具有非常好的储层物性特征,是深水区峡谷勘探的重点区域。为了进一步精细刻画陵水段峡谷内部水道复合体的沉积充填及沉积微相展布特征,本文借助新增加的三维地震资料和新钻井资料,通过峡谷三级层序界面的识别,将峡谷充填划分为3个三级层序SQ1、SQ2和SQ3,并通过古生物有孔虫化石带、钙质超微化石带及井-震结合确定了峡谷底界为中中新世晚期S40界面,陵水段峡谷自西向东依次识别出6种主要的内部充填结构,且将SQ3层序细分为5个次级层序(SSQ1~SSQ5);结合属性特征,精细刻画了陵水段峡谷内沉积微相平面展布及空间演化特征,并指出点砂坝在SSQ1层序最发育,且规模较大,横向上连片分布,将是下步勘探的有利储集体。     

海表水温变动对东、黄海鲐鱼栖息地分布的影响

海表水温(SST)通常是表征鱼类栖息地分布的主要指标。本文根据1999—2007年我国大型灯光围网的鲐鱼生产统计数据,结合海洋遥感获得的SST,分析了渔汛期间鲐鱼栖息地的适宜SST范围,探讨了SST变动情况下鲐鱼栖息地的变化趋势。研究结果表明,东、黄海鲐鱼7—12月的适宜SST范围为15~30℃。根据政府气候变化专门委员会(IPCC)第四份评估报告,本文拟定4种SST上升的情况,即(1)每月平均SST+0.5℃;(2)每月平均SST+1℃;(3)每月平均SST+2℃;(4)每月平均SST+4℃。结果显示,东、黄海鲐鱼的潜在栖息有明显向北移动的趋势,并且栖息地面积逐渐减小。研究认为,全球气候变化引起的SST上升,可能会对近海鲐鱼栖息地造成严重的影响。     

聚类分析的伪距偏差特性研究

针对如何对由信号畸变导致的伪距偏差数据快速准确地进行判断分类这个问题,该文进行了分析研究,提出采用聚类分析中的K-medoids算法展开伪距偏差特性研究,实现信号畸变导致的伪距偏差自动判别.通过对实际观测数据的分析比较可以看出,引入聚类分析方法实现伪距偏差的自动判别比仅按照接收机厂商、接收机模型划分伪距偏差更加符合实际情况.由信号畸变导致的伪距偏差在全球卫星导航系统(GNSS)精密数据处理中至关重要,会对精密单点定位精度和收敛性能、电离层延迟提取等产生影响.随着卫星导航系统以及GNSS跟踪网的建设与完善,海量的基准站及丰富的接收机类型为GNSS精密处理带来了更多的挑战.引入聚类分析方法实现了伪距偏差的自动判别,对于卫星导航精密数据处理性能具有重要的意义.     

基于图分割的可变比例尺地图分幅回溯算法

总结了地图分幅需遵循的原则,并针对地图集中可变比例尺的分幅,将其定义为基于约束条件的图分割问题,用最小生成树(minimum spanning tree,MST)将制图区域关联起来,基于回溯算法对MST裁剪实现地图集的分幅。实验结果表明,所提出的方法能较好顾及地图集分幅的相关原则,满足地图集制作的要求。同时,利用该方法设计的地图集分幅工具已成功应用于《武汉市汉阳地区地名图集》等的制作,有效提高了地图设计人员的工作效率。