湖泊水质参数空间分析中异常值的识别与处理

异常值的存在对湖泊水质参数局部估计精度产生重要影响 ,制约了地统计学在湖泊水质研究中的应用。文章以太湖为例 ,介绍了在湖泊水质参数研究中的三种异常值识别和处理的方法。应用这些方法可以有效地降低异常值的影响水平     

USE OF STAGE DATA TO CHARACTERIZE HYDROLOGIC CONDITIONS IN AN URBANIZING ENVIRONMENT1

ABSTRACT: This paper presents the results of a study on the use of continuous stage data to describe the relation between urban development and three aspects of hydrologic condition that are thought to influence stream ecosystems—overall stage variability, stream flashiness, and the duration of extreme‐stage conditions. This relation is examined using data from more than 70 watersheds in three contrasting environmental settings—the humid Northeast (the metropolitan Boston, Massachusetts, area); the very humid Southeast (the metropolitan Birmingham, Alabama, area); and the semiarid West (the metropolitan Salt Lake City, Utah, area). Results from the Birmingham and Boston studies provide evidence linking increased urbanization with stream flashiness. Fragmentation of developed land cover patches appears to ameliorate the effects of urbanization on overall variability and flashiness. There was less success in relating urbanization and streamflow conditions in the Salt Lake City study. A related investigation of six North Carolina sites with long term discharge and stage data indicated that hydrologic condition metrics developed using continuous stage data are comparable to flow based metrics, particularly for stream flashiness measures.     

我国物流产业基本经济活动空间格局分析

基于经济基础理论,对1991～2001年间我国各省区物流产业基本经济活动部分进行了实证分析,从省际差异、东中西部差异两个方面分析了我国区域物流产业基本经济活动的省区差异:在时间维度上区域差异呈逐步扩大趋势,在空间结构上表现出较明显的沿海指向性和交通指向性,并以此分析归纳出我国物流产业基本活动的"四区(物流集聚区)一带(物流集聚带)"空间格局特征,进而得出其基本经济活动强度与区域经济发展水平、物流需求程度、科技水平、区位条件、交通等基础设施、政策及历史发展作用紧密相关的结论.     

NUTRIENT CONCENTRATION CRITERIA AND CHARACTERIZATION OF PATTERNS IN TROPHIC STATE FOR RIVERS IN HETEROGENEOUS LANDSCAPES1

ABSTRACT: A method is demonstrated for the development of nutrient concentration criteria and large scale assessment of trophic state in environmentally heterogeneous landscapes. The method uses the River Environment Classification (REC) as a spatial framework to partition rivers according to differences in processes that control the accrual and loss of algae biomass. The method is then applied to gravel bed rivers with natural flow regimes that drain hilly watersheds in New Zealand's South Island. An existing model is used to characterize trophic state (in terms of chlorophyll a as a measure of maximum biomass) using nutrient concentration, which controls the rate of biomass accrual, and flood frequency, which controls biomass loss. Variation in flood frequency was partitioned into three classes, and flow data measured at 68 sites was used to show that the classes differ with respect to flood frequency. Variation in nutrient concentration was partitioned at smaller spatial scales by subdivision of higher level classes into seven classes. The median of flood frequency in each of the three higher level classes was used as a control variable in the model to provide spatially explicit nutrient concentration criteria by setting maximum chlorophyll a to reflect a desired trophic state. The median of mean monthly soluble reactive phosphorus and soluble inorganic nitrogen measured at 68 water quality monitoring sites were then used to characterize the trophic state of each of the seven lower level classes. The method models biomass and therefore allows variation in this response variable to provide options for trophic state and the associated nutrient concentrations to achieve these. Thus it is less deterministic than using reference site water quality. The choice from among these options is a sociopolitical decision, which reflects the management objectives rather than purely technical considerations.     

混凝土简支梁设计基准期内的可靠度

根据统计资料对不同类型建筑在不同防火措施下发生火灾的概率研究,得出了各类建筑达到轰燃的概率.基于蒙特卡罗随机有限元方法,引入材料高温本构关系、截面尺寸和计算模型系数等的变异性,按照ISO标准升温曲线升温,给出了单构件轰燃下的失效概率计算方法.最后,将设计基准期内建筑物达到轰燃的概率与单构件轰燃下的失效概率组合,给出了设计基准期内建筑构件在火灾下的失效概率公式.     

Effect of 450 MHz Microwave Modulated with 217 Hz on Human EEG in Rest

Summary This study focuses on discrimination of changes, produced by low-level microwave exposure in intensity and time variability of the human EEG at rest. The power spectral density (PSD) method and nonlinear scaling analysis of the length distribution of low variability periods (LDLVP) were selected for analysis of the EEG signal. During the study, 19 healthy volunteers were exposed to a microwave (450 MHz) of 217 Hz frequency on-off modulation. The field power density at the scalp was 0.16 mW/cm². The experimental protocol consisted of ten cycles of repetitive microwave exposure. Signals from frontal, temporal, parietal and occipital EEG channels on EEG theta, alpha and beta rhythms were analysed. Exposure to microwave causes average increase of EEG activity. LDLVP analysis discriminated significant effect in time variability for 2 subjects (11%). PSD method detected significant changes in intensity for 4 subjects (21%). The effect of low-level microwave exposure is stronger on EEG beta rhythm in temporal and parietal regions of the human brain.     

SUMMER LOW FLOWS IN NEW ENGLAND DURING THE 20TH CENTURY1

ABSTRACT: High springtime river flows came earlier by one to two weeks in large parts of northern New England during the 20th Century. In this study it was hypothesized that late spring/early summer recessional flows and late summer/early fall low flows could also be occurring earlier. This could result in a longer period of low flow recession and a decrease in the magnitude of low flows. To test this hypothesis, variations over time in the magnitude and timing of low flows were analyzed. To help understand the relation between low flows and climatic variables in New England, low flows were correlated with air temperatures and precipitation. Analysis of data from 23 rural, unregulated rivers across New England indicated little evidence of consistent changes in the timing or magnitude of late summer/early fall low flows during the 20th Century. The interannual variability in the timing and magnitude of the low flows in northern New England was explained much more by the interannual variability in precipitation than by the interannual variability of air temperatures. The highest correlation between the magnitude of the low flows and air temperatures was with May through November temperatures (r =?0.37, p= 0.0017), while the highest correlation with precipitation was with July through August precipitation (r = 0.67, p > 0.0001).     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low‐elevation wetlands or mid‐elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy—herbaceous alpine ecotones—were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. Patrones Espaciales del Éxito Reproductivo de Osos Pardos, Derivados de Modelos Jerárquicos Multi‐Estado