Incorporating Spatial Dependence in Predictive Vegetation Models: Residual Interpolation Methods*

Predictive vegetation modeling can be used statistically to relate the distribution of vegetation across a landscape as a function of important environmental variables. Often these models are developed without considering the spatial pattern that is inherent in biogeographical data, resulting from either biotic processes or missing or misspecified environmental variables. Including spatial dependence explicitly in a predictive model can be an efficient way to improve model accuracy with the available data. In this study, model residuals were interpolated and added to model predictions, and the resulting prediction accuracies were assessed. Adding kriged residuals improved model accuracy more often than adding simulated residuals, although some alliances showed no improvement or worse accuracy when residuals were added. In general, the prediction accuracies that were not increased by adding kriged residuals were either rare in the sample or had high nonspatial model accuracy. Regression interpolation methods can be an important addition to current tools used in predictive vegetation models as they allow observations that are predicted well by environmental variables to be left alone, while adjusting over‐ and underpredicted observations based on local factors.     

Interannual Variability in Pollen Dispersal and Deposition on the Tropical Quelccaya Ice Cap*

Pollen collected from snow samples on the Quelccaya Ice Cap in 2000 and 2001 reveals significant interannual variability in pollen assemblage, concentration, and provenance. Samples from 2000, a La Niña year, contain high pollen concentrations and resemble samples from the Andean forests (Yungas) to the east. Samples from 2001, an El Niño year, contain fewer pollen and resemble those from the Altiplano. We suggest that varying wind patterns under different El Niño/Southern Oscillation (ENSO) conditions may affect the processes of pollen transport over the Altiplano and on the ice cap, although confounding variables such as flowering phenology and sublimation should also be considered     

空间信息网格中动态复制策略的研究

空间信息网格项目数据量大，用户遍及各地，对数据文件的请求延时大、占大量带宽。复制可以节省带宽、减少时延、均衡负载、改善系统可靠性。采用动态复制技术可以使用户有效地获得所需的数据。详细地论述了动态复制策略以及空间信息网格中的复制管理机制、复制服务流程和具体实施。     

Ice-core pollen record of climatic changes in the central Andes during the last 400 yr

This paper presents a high-resolution ice-core pollen record from the Sajama Ice Cap, Bolivia, that spans the last 400 yr. The pollen record corroborates the oxygen isotopic and ice accumulation records from the Quelccaya Ice Cap and supports the scenario that the Little Ice Age (LIA) consisted of two distinct phases—a wet period from AD 1500 to 1700, and a dry period from AD 1700 to 1880. During the dry period xerophytic shrubs expanded to replace puna grasses on the Altiplano, as suggested by a dramatic drop in the Poaceae/Asteraceae (P/A) pollen ratio. The environment around Sajama was probably similar to the desert-like shrublands of the Southern Bolivian Highlands and western Andean slopes today. The striking similarity between the Sajama and Quelccaya proxy records suggests that climatic changes during the Little Ice Age occurred synchronously across the Altiplano.     

空间运动对象与时空数据类型研究

当前时空数据模型多以描述空间实体的离散变化为主。该文中对空间运动对象在抽象层次的无限连续空间、离散层次的有限离散空间上的数据类型进行分析和定义，将其分别划分为时间类型、空间类型和时态类型来研究，并提出支持空间运动对象的表示方法和操作方式。该方法既能表示空间实体的连续运动，也能表示其离散变化，为空间运动对象时空数据模型的建立奠定了基础。     

天津地区表土PAHs含量的多尺度空间相关性

本文应用因子克立格分析方法,分析了天津表土16种PAHs之间多尺度空间结构特征。分析结果显示,天津表土PAHs在空间上可以划分三种尺度:块金尺度(0～5km),小空间尺度(5～10km)和大空间尺度(10～50km)。在不同的空间尺度上,16种PAHs之间表现出不同的空间相关性,具有空间尺度相关性。这种空间尺度相关性,是由于不同的空间污染过程造成的,有助于下一步的多尺度空间污染源的判断和污染物迁移转化规律的识别。     

基于城市体系的长江三角洲旅游地域系统研究

首先分析了长江三角洲旅游资源的分布格局及长三角旅游发展的整体性现状，认为长三角旅游整体发展的协调性不足。然后从城市体系与区域旅游整体发展耦合的角度出发，引入了长江三角洲城市体系的规模结构、空间结构、交通网络结构和城市群内部经济联系的分析研究，并以此划分出了长三角两个层次的旅游地域系统，给出了长三角地域旅游城市网络体系的空间组织。最后提出了长三角区域旅游产业联动发展的对策和建议。