An application of the GLUE methodology for estimating the parameters of the INCA-N model

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist. (c) 2006 Elsevier B.V. All rights reserved.

Examining the interaction of growing crops with local climate using a coupled crop-climate model

This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.

Single versus multiple occupancy - Effects on toxicity parameters measured on Eisenia fetida in lead nitrate-treated soil

The mortality (7 and 14 d), weight change (7 and 14 d), and metal uptake of Eisenia fetida (Savigny, 1826) kept in Pb(NO3)(2)-treated Kettering loam soil in single- and multiple-occupancy (10 earthworms) test containers were determined. The number of earthworms to dry mass (g) ratio of soil was 1:50 in both sets of test containers. Lead concentrations were in the nominal range of 0 to 10,000 mg Pb/kg soil (mg/kg hereafter). Levels of mortality at a given concentration were statistically identical between the single- and multiple-occupancy tests, except at 1,800 mg/kg, at which significantly (p less than or equal to 0.05) more mortality occurred in the multiple-occupancy tests. Death of individual earthworms in the multiple-occupancy tests did not trigger death of the other earthworms in that soil. The LC50 values (concentration statistically likely to kill 50% of the population) were identical between the multiple- and single-occupancy soils: 2,662 mg/kg (2,598-2,984, 7 d) and 2,589 mg/kg (2,251-3,013, 14 d) for the multiple-occupancy soils and 2,827 mg/kg (2,443-3,168, both 7 and 14 d) for the single-occupancy soils (values in brackets represent the 95% confidence intervals). Data were insufficient to calculate the concentration statistically likely to reduce individual earthworm mass by 50% (EC50), but after 14 d, the decrease in earthworm weight in the 1,800 and 3,000 mg/kg tests was significantly greater in the multiple- than in the single-occupancy soils. At 1,000, 1,800, and 3,000 mg/kg tests, earthworm Pb tissue concentration was significantly (p less than or equal to 0.05) greater in earthworms from the multiple-occupancy soils. The presence of earthworms increased the NH3 content of the soil; earthworm mortality increased NH3 concentrations further but not to toxic levels.

Flow controls on lowland river macrophytes: A review

We review the current status of knowledge regarding the role that flow parameters play in controlling the macrophyte communities of temperate lowland rivers. We consider both direct and indirect effects and the interaction with other factors known to control macrophyte communities. Knowledge gaps are identified and implications for the management of river systems considered. The main factors and processes controlling the status of macrophytes in lowland rivers are velocity (hence also discharge), light, substrate, competition, nutrient status and river management practices. We suggest that whilst the characteristics of any particular macrophyte community reflect the integral effects of a combination of the factors, fundamental importance can be attributed to the role of discharge and velocity in controlling instream macrophyte colonisation, establishment and persistence. Velocity and discharge also appear to control the relative influence of some of the other controlling factors. Despite the apparent importance of velocity in determining the status of macrophyte communities in lowland rivers, relatively little is understood about the nature of the processes controlling this relationship. Quantitative knowledge is particularly lacking. Consequently, the ability to predict macrophyte abundance and distribution in rivers is still limited. This is further complicated by the likely existence of feedback effects between the growth of macrophytes and velocity. Demand for water resources increases the pressure on lowland aquatic ecosystems. Despite growing recognition of the need to allocate water for the needs of instream biota, the inability to assess the flow requirements of macrophyte communities limits the scope to achieve this. This increases the likelihood of overexploitation of the water resource as other users, whose demands are quantifiable, are prioritised. (C) 2008 Elsevier B.V. All rights reserved.

Identifying the critical parameters of a cyanobacterial growth and movement model by using generalised sensitivity analysis

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. A new deterministic-mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including, light, nutrients and temperature. A technique called generalised sensitivity analysis was applied to the model to identify the critical parameter uncertainties in the model and investigates the interaction between the chosen parameters of the model. The result of the analysis suggested that 8 out of 12 parameters were significant in obtaining the observed cyanobacterial behaviour in a simulation. It was found that there was a high degree of correlation between the half-saturation rate constants used in the model.

Experimental crop growing in Jordan to develop methodology for the identification of ancient crop irrigation

Crop irrigation has long been recognized as having been important for the evolution of social complexity in several parts of the world. Structural evidence for water management, as in the form of wells, ditches and dams, is often difficult to interpret and may be a poor indicator of past irrigation that may have had no need for such constructions. It would be of considerable value, therefore, to be able to infer past irrigation directly from archaeo-botanical remains, and especially the type of archaeo-botanical remains that are relatively abundant in the archaeological record, such as phytoliths. Building on the pioneering work of Rosen and Wiener (1994), this paper describes a crop-growing experiment designed to explore the impact of irrigation on the formation of phytoliths within cereals. If it can be shown that a systemic and consistent relationship exists between phytolith size, structure and the intensity of irrigation, and if various taphonomic and palaeoenvironmental processes can be controlled for, then the presence of past irrigation can feasibly be inferred from the phytoliths recovered from the archaeological record.

Isolating the 'farmer' effect as a component of the advantage of growing genetically modified varieties in developing countries: a Bt cotton case study from Jalgaon, India

The present paper explores the 'farmer' effect in economic advantages often claimed for Bt cotton varieties (those with the endotoxin gene from Bacillus thuringiensis conferring resistance to some insect pests) compared to non-Bt varieties. Critics claim that much of the yield advantage of Bt cotton could be due to the fact that farmers adopting the technology are in a better position to provide inputs and management and so much of any claimed Bt advantage is an artefact rather than reflecting a real advantage of the variety per se. The present paper provides an in-depth analysis of 63 non-adopting and 94 adopting households of Bt cotton in Jalgaon, Maharashtra State, India, spanning the seasons 2002 and 2003. Results suggest that Bt adopters are indeed different from non-adopters in a number of ways. Adopters appear to specialize more on cotton (at least in terms of the land area they devote to the crop), spend more money on irrigation and grow well-performing non-Bt varieties of cotton (Bunny). Taking gross margin as the basis for comparison, Bt plots had 2.5 times the gross margin of non-Bt plots in both seasons. If only adopters are considered then the gross margin advantage of Bt plots reduces to 1.6 times that of non-Bt plots. This is still a significant advantage and could well explain the popularity of Bt in Maharashtra. However, it is clear that great care needs to be taken with such comparative studies.

Effects of metals on life cycle parameters of the earthworm Eisenia fetida exposed to field-contaminated, metal-polluted soils

Two control and eight field-contaminated, metal-polluted soils were inoculated with Eisenia fetida (Savigny, 1826). Three, 7, 14, 21, 28 and 42 days after inoculation, earthworm survival, body weight, cocoon production and hatching rate were measured. Seventeen metals were analysed in E.fetida tissue, bulk soil and soil solution. Soil organic carbon content, texture, pH and cation exchange capacity were also measured. Cocoon production and hatching rate were more sensitive to adverse conditions than survival or weight change. Soil properties other than metal concentration impacted toxicity. The most toxic soils were organic-poor (1-10 g C kg(-1)), sandy soils (c. 74% sand), with intermediate metal concentrations (e.g. 7150-13, 100 mg Ph kg(-1), 2970-53,400 mg Zn kg(-1)). Significant relationships between soil properties and the life cycle parameters were determined. The best coefficients of correlation were generally found for texture, pH, Ag, Cd, Mg, Pb, Tl, and Zn both singularly and in multivariate regressions. Studies that use metal-amended artificial soils are not useful to predict toxicity of field multi-contaminated soils. (c) 2007 Elsevier Ltd. All rights reserved.

"Ever-growing Amman", Jordan: Urban expansion, social polarisation and contemporary urban planning issues

Amman the primate capital city of the Hashemite Kingdom of Jordan currently has a population in excess of 2 million, but in 1924 it consisted of little more than a collection of dwellings and some 2000-3000 inhabitants. The present paper sets out to document and explain the phenomenal expansion of "ever-growing Amman". The physical geography of the urban region and the early growth of the city are considered at the outset and this leads directly to consideration of the highly polarised social structuring that characterises contemporary Amman. In doing this, original data derived from the recent Greater Amman Municipality's Geographical Information System are presented. In this respect, the essential modernity of the city is exemplified. The employment and industrial bases of the city and a range of pressing contemporary issues are then considered, including transport and congestion, the provision of urban water under conditions of water stress and privatisation, and urban and regional development planning for the city. The paper concludes by emphasizing the growing regional and international geopolitical salience of the city of Amman at the start of the 21st century. (C) 2008 Elsevier Ltd. All rights reserved.

Assessing the discourses and practices of urban regeneration in a growing region

Most research on the discourses and practices of urban regeneration in-the UK has examined case studies located in areas of relative socio-economic distress. Less research has been undertaken on regeneration projects and agendas in areas characterise by strong economic growth. Yet, it is in such places that some of the best examples of the discourses, practices and impacts of contemporary urban regeneration can be. found. In some areas of high demand regeneration projects have used inner urban brownfield sites as locations for new investment. With the New Labour government's urban policy agendas targeting similar forms of regeneration, an examination of completed or on-going schemes is timely and relevant to debates over the direction that policy should take. This paper, drawing on a study of urban regeneration in one of England's, fastest growing towns, Reading in Berkshire, examines the discourses, practices and impacts of redevelopment schemes during the 1990s and 2000s. Reading's experiences have received national attention and have been hailed as a model for other urban areas to follow. The research documents the discursive and concrete aspects of local regeneration and examines the ways in which specific priorities and defined problems have come to dominate agendas. Collectively, the study argues that market-driven objectives come to dominate regeneration agendas, even in areas of strong demand where development agencies wield a relatively high degree of influence. Such regeneration plays a symbolic and practical role in creating new forms of exclusion and interpretations of place. (C) 2003 Elsevier Science Ltd. All rights reserved.

Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters

Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC-AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water-balance-related parameters. Temperature-dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon 'dieback' results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long-term investments are required.

Fast training of self organizing maps for the visual exploration of molecular compounds

Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen’s Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.