[i]In silico[/i] system analysis of physiological traits determining grain yield and protein concentration for wheat as influenced by climate and crop management

Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work

Towards a Fiscal Illusion Index

This paper presents an index of Fiscal Illusion for 68 democratic countries from 1960 to 2006. The studied Fiscal Illusion is the one related to a wrong perception of the budget aggregates according to the voters and taxpayers’ perspectives. In the construction of the index, methodological issues were carefully taken into account. The results obtained reveal that fiscal illusion varies greatly around the world. Countries such as Mali, Pakistan, Russia and Sri Lanka have the highest average values over the time period considered; while Austria, Luxembourg, Netherlands and New Zealand have the lowest. Regarding the time dimension, between 1980 and 1995 there was a significant decrease in the average value of the index across countries, suggesting a reduction in the adoption of fiscal illusion measures during this period. After 1995, the index remained stable in most of the countries.Fiscal Illusion; Indexes/Indicators; Democracy

Assessment of human immediate response capability related to tsunami threats in Indonesia at a sub-national scale

Human immediate response is contextualized into different time compartments reflecting the tsunami early warning chain. Based on the different time compartments the available response time and evacuation time is quantified. The latter incorporates accessibility of safe areas determined by a hazard assessment, as well as environmental and demographic impacts on evacuation speed properties assessed using a Cost Distance Weighting GIS approach. <br><br> Approximately 4.35 million Indonesians live in tsunami endangered areas on the southern coasts of Sumatra, Java and Bali and have between 20 and 150 min to reach a tsunami-safe area. Most endangered areas feature longer estimated-evacuation times and hence the population possesses a weak immediate response capability leaving them more vulnerable to being directly impacted by a tsunami. At a sub-national scale these hotspots were identified and include: the Mentawai islands off the Sumatra coast, various sub-districts on Sumatra and west and east Java. Based on the presented approach a temporal dynamic estimation of casualties and displacements as a function of available response time is obtained for the entire coastal area. As an example, a worst case tsunami scenario for Kuta (Bali) results in casualties of 25 000 with an optimal response time (direct evacuation when receiving a tsunami warning) and 120 000 for minimal response time (no evacuation). The estimated casualties correspond well to observed/reported values and overall model uncertainty is low with a standard error of 5%. <br><br> The results obtained allow for prioritization of intervention measures such as early warning chain, evacuation and contingency planning, awareness and preparedness strategies down to a sub-district level and can be used in tsunami early warning decision support

A Comparison of Sensitivity Analysis Techniques for Complex Models for Environmental Management

Computer based modelling methods are being used increasingly to replicate natural systems in order to review both large and small scale policy measures prior to their implementation. Integrated Assessment Modelling (IAM) incorporates knowledge from several different disciplines into one model in order to provide an overarching assessment of the impact of different management decisions. The importance of IAM is that the environmental, social and economic impacts of management choices can be assessed within a single model, further allowing assessment in relation to sustainability criteria. The considerable detail facilitated by these models often requires the inclusion of a large number of parameters and model inputs, many of whose values may not be known with certainty. For this reason and because models do not always behave intuitively (in particular when there are non-linearities involved), sensitivity analysis (SA) of the model to changes in its parameters and inputs is an important stage of model development. Current SA methods have not kept pace with rapid increases in computing power and availability and more importantly the resultant increases in model size and complexity. Also related to the complexity is increased difficulty in finding and fitting distributions to all parameters. Further, the complex nature of integrated models requires SA that is flexible and can be implemented regardless of model structure. This research aims to establish new criteria for SA used in the context of integrated models for environmental management and decision-making. These criteria are believed to reflect the current requirements specific to this type of modelling. Desirable criteria are identified as: high computational efficiency; ability to take into account higher order parameter interactions; ability to account for model non-linearities; not requiring knowledge of parameter probability distributions; and use in decision making. SA of an integrated model of the Namoi River catchment is performed using the Fourier Amplitude Sensitivity Testing (FAST) method, Morris method, method of Sobol', and regression and correlation coefficients. The results from these analyses are used as a basis for comparing the SA methods by the new criteria outlined above. The Namoi model is a combination of a flow model with a non-linear component, a policy model, an economic model and an extraction model. It can be used for assessing management options for the river. SA of two different potential management options for the catchment is undertaken to facilitate comparison of sensitivity between two slightly different models. Comparison of the different SA methods shows that none of the methods meet all of the criteria and, in particular, there are no methods that are effective for use when comparing management options. This lack of an adequate SA method for integrated models indicates that development of a new method of SA specifically for integrated models for environmental management is desirable. The FAST method is shown to meet the criteria most effectively, being able to account for model non-linearity and non-monotonicity, requiring only parameter ranges (not distributions), and being relatively computationally efficient (although this does come at a loss of some resolution). Results from the FAST SA of the Namoi model show the model to be sensitive to several parameters within the non-linear loss module. Further, one management option shows sensitivity to the decision variables within the model while the other does not. This means that the first management option clearly corresponds to the more controllable form of the model

Towards a Puviani’s Fiscal Illusion Index

This paper presents an index of Fiscal Illusion for 68 democratic countries from 1960 to 2006. The theory of Fiscal Illusion studied relates to a wrong perception of government budget aggregates from the voters’ and taxpayers’ perspectives. In the construction of the index, methodological issues were carefully taken into account. The results obtained reveal that Fiscal Illusion varies greatly around the world. Countries such as Mali, Pakistan, Russia, and Sri Lanka have the highest average values over the time period considered, while Austria, Luxembourg, Netherlands, and New Zealand have the lowest. Regarding the time dimension, between 1980 and 1995 there was a significant decrease in the average value of the index across countries, suggesting a reduction in the adoption of Fiscal Illusion practices during this period. After 1995, the index remained stable in most countries.Fiscal Illusion; Indexes/Indicators; Democracy.

A computational and empirical analysis of the thermal performance of insulating concrete formwork

The research presented in this EngD thesis focused on Insulated Concrete Formwork (ICF), a site-based, Modern Method of Construction (MMC). An ICF wall consists of modular prefabricated Expanded Polystyrene Insulation (EPS) hollow blocks and cast in situ concrete. The blocks are assembled on site and the concrete is poured into the void. Once the concrete has cured, the insulating formwork stays in place permanently, providing very low U-values and high levels of airtightness. ICF is often thought of as just an insulated panel acting thermally as a lightweight structure. There is a view that the internal layer of insulation isolates the thermal mass of the concrete from the internal space and interferes with thermal interaction. Despite evidence of ICF’s enhanced thermal storage capacity (compared to a lightweight timber-frame panel with equivalent insulation), there is still a gap in understanding when attempting to quantify the effect of the thermal mass within ICF.Using computational analysis (Building Performance Simulation - BPS) and empirical evaluation (monitoring data), the aim of the EngD research was to analyse the aspects that affect the thermal performance of ICF; to develop an understanding about its thermal behaviour and its response to dynamic heat transfer; and, to investigate how the latter is affected by the inherent thermal inertia of the concrete core. [Continues.]</div