Spatial and temporal variation of water mass mixing characteristic in the East China Sea

On the basis of the observation data of Kuroshio since 1984 and relative historical data in the East China Sea, spatial and temporal variation of water mass mixing characteristic in the observation area is analysed. The main results are as follows.     

Impact factors identification of spatial heterogeneity of herbaceous plant diversity on five southern islands of Miaodao Archipelago in North China

Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity. Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns. Five southern islands in the Miaodao Archipelago, North China were studied herein. The spatial distribution of herbaceous plant diversity on these islands was analyzed, and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA. The results reveal 114 herbaceous plant species, belonging to 94 genera from 34 families in the 50 plots sampled. The total species numbers on different islands were significantly positively correlated with island area, and the average α diversity was correlated with human activities, while the β diversity among islands was more affected by island area than mutual distances. Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude, slope, total nitrogen, total carbon, and canopy density, and lower moisture content, pH, total phosphorus, total potassium, and aspect. Among the environmental factors, pH, canopy density, total K, total P, moisture content, altitude, and slope had significant gross effects, but only canopy density exhibited a significant net effect. Terrain affected diversity by restricting plantation, plantation in turn influenced soil properties and the two together affected diversity. Therefore, plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.     

基于像元二分模型的地表植被覆盖度估算模块化设计与实现

地表植被覆盖度是的一种应用广泛的定量遥感产品,在水文、生态、区域变化等方面都具有重要的意义。像元二分模型是应用最多的一种遥感估算地表覆盖度的方法。目前,用遥感的方法进行地表植被覆盖度估算没有完整、系统的工具,用户只能逐步进行操作,效率低下,鉴于上述情况,本文运用IDL交互式数据语言,基于ENVI二次开发了一个植被覆盖度估算程序,取得了一定的成效,对遥感定量产品的生产、应用具有一定意义。     

台湾以北海域浮游桡足类生物海洋学特征的研究Ⅱ.群落特征

在对台湾以北海域浮游桡足类生物海洋学特征进行数量分布方面的研究后的续篇,重点对本海区浮游挠足类的群落结构和群落性质以及与栖区环境条件间的关系作了分析探讨．结果表明,本区桡足类群落结构种类组成复杂,出现种类共２３７种,但周年共有种比例仅占３２％．桡足类群落的多样度和均匀度年均值各为３．７１４和０．６９０,在平面分布上呈外部海区高于近岸海区的大体趋势．本区群落可划分为５个生态类群,其中暖水性外海高温偏低盐类群和热带大洋高温高盐类群可分别指示台湾海峡水和黑潮表层水的季节消长过程．从不同侧面的计算分析均表明,冬季在环境条件上均有异于其他３季．在春、夏、秋季,以普通波水蚤最具优势,盐度是影响群落特征值的主导因子,群落的性质是以暖水性外海种类为主、热带大洋种也占相当比例的亚热带－热带群落结构的特点;在冬季,主要优势种是海洋真刺水蚤,温度是群落特征值的主要制约因子,群落呈现以热带大洋种占支配地位的热带大洋群落结构属性．     

东海水系与生物关系的初步分析

本文利用中日黑潮联合调查研究期间1986年5—6月和1989年7—8月航次水文与生物的同步取样资料,分析了东海测区内水系组成与浮游甲藻类及浮游桡足类等分布之间的对应关系。指出了不同生态类型的生物需要不同的物理海洋环境条件。同时,某些指示生物的分布又为区分水系、了解流系情况提供了良好的示性指标,并且从某些生物数量的变化还可以判断出水系混合与变性的程度。     

小兴安岭湿地景观格局模拟及动态演变分析

针对小兴安岭湿地生态功能退化,急须对其景观格局动态演变特征进行分析,该文提出 了耦合人工神经网络、元胞自动机和马尔科夫链构建模型来预测小兴安岭湿地未来景观格局的方法;通过转移矩阵、景观格局指数分析小兴安岭湿地1995-2025年景观格局动态演变特征.结果表明:所构建模型耦合了马尔科夫链数量预测与元胞自动机空间预测的优势,能够较大限度地克服元胞自动机模型主观赋权的影响,有效地提高了预测模型的精度;1995-2025年,小兴安岭地区湿地面积呈波动式变化,1995-2005年湿地面积急剧减少,2005年后缓慢增加,至2025年趋于平稳;小兴安岭湿地景观格局总体趋于破碎化,景观异质性增加,2005年达到最大值,2015年后各景观类型比例基本稳定.研究结果为小兴安岭湿地生态功能修复提供有力的技术支撑.     

陕西省地理国(省)情监测中的基本地貌类型及划分指标

基本地貌类型划分是陕西省地理国(省)情监测试点需要解决的重点问题之一。以数字高程模型为基础数据,根据地貌划分基本原理,将陕西省划分为6个典型地貌区。探讨省域地貌区域划分的方法和指标,确定符合陕西省地方特点的地貌类型系统,并介绍根据省域地貌特点选取划分指标的方法。以此为依据完成陕西省基本地貌区域的定量划分,并从划分成果的位置关系、统计数据和形态成因等方面讨论划分方法和成果的合理性。     

基础地理数据中心平台设计

基础地理数据中心建设是实现地理信息的交换与共享关键所在。本文提出了基础地理信息数据中心平台的总体架构,设计平台的基本功能,探讨了需解决和应用的关键技术。     

Android平台下的地形图图幅信息检索

针对当前移动端缺少快速、实时检索地形图图幅信息的系统,本文依据国家基本比例尺地形图分幅与编号标准,提出了基于Andriod平台的地形图图幅信息检索方法并编程实现了该系统。该系统实现的功能有:点所在图幅编号检索、图幅范围检索、地形图新旧编号的转换及区域范围内图幅编号集检索。此系统可应用于Andriod智能手机和平板电脑等移动设备。实验表明,本文的方法和系统执行效率能够基本满足移动用户实时检索地形图图幅信息的需求。     

Distribution and controlling factors of phytoplankton assemblages in a semi-enclosed bay during spring and summer

The phytoplankton assemblages' patterns and their correlation to environmental factors were studied in Bohai Bay during spring and summer. Two zones, the northern (NWA) and southern (SWA) water area, were identified by cluster analysis based on their physical and chemical properties. Principal component analysis (PCA) showed that more phytoplankton species was found in the SWA with low nutrient concentration, while high phytoplankton abundance occurred in the NWA with high nutrient concentration. The seasonal variability in phytoplankton can be explained by water temperature, nutrient, and hydrodynamic conditions (includes mixing during spring and stratification during summer). Results of redundancy analysis (RDA) showed that silicate (SiO(4)) and soluble reactive phosphorus (SRP) were the most important environmental factors influencing the phytoplankton distribution during spring and summer, respectively. Hydrodynamics condition plays a key role in controlling variation of the environmental factors, which determined phytoplankton distribution in Bohai Bay.