Impact of Climate Change on Fish Population Dynamics in the Baltic Sea: A Dynamical Downscaling Investigation

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties.     

Consistent assessments of pathways toward sustainable development and climate stabilization

Many of the numerous difficult issues facing the world today involve relationships entailing trade‐offs and synergies. This study quantitatively assesses some alternative scenarios using integrated assessment models, and provides several indicators relating to sustainable development and climate change, such as indicators of income (per capita GDP), poverty, water stress, food access, sustainable energy use, energy security, and ocean acidification, with high consistencies among the indicators within a scenario. According to the analyses, economic growth helps improve many of the indicators for sustainable development. On the other hand, climate change will induce some severe impacts such as ocean acidification under a non‐climate intervention scenario (baseline scenario). Deep emission reductions, such as to 2°C above the pre‐industrial level, could cause some sustainable development indicators to worsen. There are complex trade‐offs between climate change mitigation levels and several sustainable development indicators. A delicately balanced approach to economic growth will be necessary for sustainable development and responses to climate change.     

Measuring bed shear stress along vegetated river beds using FST-hemispheres

The measurement of the bed shear stress along vegetated river beds is essential for accurately predicting the water level, velocity and solute and sediment transport fluxes in computational hydroenvironmental models. Details are given herein of an experimental and theoretical study to determine the bed boundary shear stress along vegetated river beds introducing a novel field measuring method, namely the FliessWasserStammtisch (FST)-hemispheres. Although investigations have been conducted previously for sedimentary channels using the FST-hemispheres, this preliminary study is thought to be the first time that such hemispheres have been used to investigate the bed shear stresses in vegetated channels. FST-hemispheres were first developed by Statzner and Müller [1989. Standard hemispheres as indicators of flow characteristics in lotic benthos research. Freshwater Biology 21, 445-459] to act as an integrated indicator of the gross hydrodynamic stresses present near the bed. Test and validation data were found to be at least of the same order of magnitude for the stresses predicted from literature for sedimentary channels, with this study establishing the commencement of a database of calibrated FST-hemisphere laboratory data for vegetated channel beds. In a series of experiments, depths ranging from 0.1 to 0.28m were considered, equating directly to comparable conditions in small rivers or streams. The results of this study provide a basis for enabling the FST-hemispheres to be used to evaluate the boundary shear stress for a wider range of applications in the future, including vegetated river beds.     

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.