安徽省市级区域发展的空间结构演变分析

以市级区域为空间结构研究对象,分析安徽省20世纪80年代以来区域经济空间结构的演化过程。结果表明：①安徽省各市级区域在近20年的发展中,区域差异空间格局整体上变化不大,20世纪80年代初期经济发达的地区现在仍为发达区,原先落后的地区仍落后;②1980年以来,工业化进程的空间差异与区域社会经济发展的空间差异具有很大的相似性,表明工业化是推动区域经济发展的重要力量;③通过分析区域发展差异的空间机制得出：轴线的地位差异显著,以贯穿南北的中轴线和沿江轴线为主,形成经济实力中心,而其它地区相对落后,形成了明显的中心-边缘模式。     

Generation of Monthly Precipitation Under Climate Change for the Upper Blue Nile River Basin,Ethiopia1

Abstract: This work develops a methodology to project the future precipitation in large river basins under limited data and climate change while preserving the historical temporal and spatial characteristics. The computationally simple and reliable conditional generation method (CGM) is presented and applied to generate reliable monthly precipitation data in the upper Blue Nile River Basin of Ethiopia where rain‐fed agriculture is prevalent. The results showed that the temporal analysis with the CGM performs better to reproduce the historical long‐term characteristics than other methods, and the spatial analysis with the CGM reproduced the historical spatial structure accurately. A 100‐year time series analysis using the outcomes of the six general circulation models showed that precipitation changes by the 2050s (2040 through 2069) can be ?7 to 28% with a mean increase of about 11%. The seasonal results showed increasing wet conditions in all seasons with changes of mean precipitation of 5, 47, and 6% for wet, dry, and mild seasons, respectively.     

Risk assessment and prioritisation of contaminated sites on the catchment scale

Contaminated sites pose a significant threat to groundwater resources worldwide. Due to limited available resources a risk-based prioritisation of the remediation efforts is essential. Existing risk assessment tools are unsuitable for this purpose, because they consider each contaminated site separately and on a local scale, which makes it difficult to compare the impact from different sites. Hence a modelling tool for risk assessment of contaminated sites on the catchment scale has been developed. The CatchRisk screening tool evaluates the risk associated with each site in terms of its ability to contaminate abstracted groundwater in the catchment. The tool considers both the local scale and the catchment scale. At the local scale, a flexible, site specific leaching model that can be adjusted to the actual data availability is used to estimate the mass flux over time from identified sites. At the catchment scale, a transport model that utilises the source flux and a groundwater model covering the catchment is used to estimate the transient impact on the supply well. The CatchRisk model was tested on a groundwater catchment for a waterworks north of Copenhagen, Denmark. Even though data scarcity limited the application of the model, the sites that most likely caused the observed contamination at the waterworks were identified. The method was found to be valuable as a basis for prioritising point sources according to their impact on groundwater quality. The tool can also be used as a framework for testing hypotheses on the origin of contamination in the catchment and for identification of unknown contaminant sources.     

水安全及城市水安全研究进展与趋势

归纳和总结国内外水安全及城市水安全相关研究实践及其所用的评价指标体系,并对几种常用模型与方法的应用情况及其各自的特点进行分析,针对目前水安全及城市水安全研究中存在的主要问题,指出水安全及城市水安全进一步研究的方向:从自然、生态环境、社会经济、人文4个基本方向,以系统性、持续性、动态性和层次性4个特征为基础,分析水安全及城市水安全的概念与内涵;根据研究区域特征及其主要水安全问题建立评价指标体系;以研究者对各个模型的理解程度及驾驭能力为准则选用或改造现有模型与方法;针对加强城市应急水源地建设、突发性水安全事件应急预案、湿润地区水安全等问题开展研究。     

Nutrient transfer functions: the site of integration between feeding behaviour and nutritional physiology

Summary. We describe and extend a graphical approach to quantitative nutrition that focuses on the interplay between behavioural and physiological components of nutritional regulation. The site of integration is the nutrient transfer function, which is the function describing the time course of nutrient transfer between serially connected nutritional compartments (e.g., from the gut to the blood). The relationship between the shape of the nutrient transfer function and the temporal patterns of feeding determines the values of two key quantitative parameters of nutrition: the rate ('power') and the efficiency of nutrient acquisition. The approach can be extended to consider, in addition to the short-term behavioural and physiological decisions made by animals, some ecological determinants and longer-term, life history consequences of such decisions. Most importantly, this category of models can provide insights into the interplay among the various nutrients in an animal's diet. We illustrate this using hypothetical examples, and also present preliminary data for the power-efficiency relationships of protein and digestible carbohydrates in locusts. Finally, we consider existing evidence for the various means available to these and other insects for regulating such relationships. Received 24 September 1997; accepted 9 December 1997.     

Natural control mechanisms in models of aquatic ecosystems

Based on cybernetic categories of natural control mechanisms, four generations of ecosystem models are distinguished: feed-forward, feedback, self-adaptation and self-organization models. The analysis of the natural control mechanisms in aquatic ecosystems suggests that different processes are controlled in different ways, and, although the four mechanisms were identified in historical sequence, they all operate simultaneously. The concept of self-organization of an ecosystem is introduced and specified for a model of an aquatic pelagic ecosystem. The concept of the ecosystem as a multilayer, multigoal and multiechelon hierarchical system with hierarchy of the levels of biological organization is also introduced.     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

Calculating losses of crops in Denmark caused by high ozone levels

In order to help guide air pollution legislation at the European level, harmful air pollution effects on agriculture crops and the consequent economic implications for policy have been studied for more than a decade. Ozone has been labeled as the most serious of the damaging air pollutants to agriculture, where growth rates and consequently yields are dramatically reduced. Quantifying the effects has formed a key factor in policymaking. Based on the widely held view that AOT40 (Accumulated exposure Over Threshold of 40 ppb) is a good indicator of ozone-induced damage, the Danish Eulerian Model (DEM) was used to compute reduced agriculture yields on a 50 km×50 km grid over Europe. In one set of scenarios, a ten year meteorological time series was combined with realistic emission inventories. In another, various idealized emission reduction scenarios are applied to the same meteorological time series. The results show substantial inter-annual variability in economic losses, due in most part to meteorological conditions which varied much more substantially than the emissions during the same period. It is further shown that, taking all uncertainties into account, estimates of ozone-induced economic losses require that a long meteorological record is included in the analysis, for statistical significance to be improved to acceptable levels for use in policy analysis. In this study, calculations were made for Europe as a whole, though this paper presents results relevant for Denmark.     

A New Approach to Plant Diversity Assessment Combining HPLC Data, Simplex Mixture Design and Discriminant Analysis

The quantitative assessment of plant diversity and its monitoring with time represent a key environmental issue for management and conservation of natural resources. Assessment of plant diversity could be based on chemical analyses of secondary metabolites (e.g. flavonoids, terpenoids), because of the substantial quantitative and qualitative between-individual variability in such compounds. At a geographical scale, the plant populations become widely dispersed, and their monitoring from numerous routine individual analyses could become restricting. To overcome such constraint, this study develops a multivariate calibration model giving the relative frequency of a particular taxon from a simple high-performance liquid chromatography (HPLC) analysis of a plant mixture. The model was built from a complete set of mixtures combining different taxons, according to an experimental design (Scheffé’s matrix). For each mixture, a reference HPLC pattern was simulated by averaging the individual HPLC profiles of the constitutive taxons. The calibration models, based on Bayesian discriminant analysis (BDA), gave statistical relationships between the contributions of each taxon in mixtures and reference HPLC patterns of these mixtures. Finally, these models were validated on new mixtures by using outside plants. This new biodiversity survey approach is illustrated on four chemical taxons (four chemotypes) of Astragalus caprinus (Fabaceae). The more differentiated the taxon, the better predicted its contributions (in mixtures) were by BDA calibration model. This new approach could be very useful for a global routine survey of plant diversity.