Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

MIGCLIM: Predicting plant distribution and dispersal in a changing climate

Many studies have forecasted the possible impact of climate change on plant distribution using models based on ecological niche theory. In their basic implementation, niche-based models do not constrain predictions by dispersal limitations. Hence, most niche-based modelling studies published so far have assumed dispersal to be either unlimited or null. However, depending on the rate of climatic change, the landscape fragmentation and the dispersal capabilities of individual species, these assumptions are likely to prove inaccurate, leading to under- or overestimation of future species distributions and yielding large uncertainty between these two extremes. As a result, the concepts of "potentially suitable" and "potentially colonisable" habitat are expected to differ significantly. To quantify to what extent these two concepts can differ, we developed MIGCLIM, a model simulating plant dispersal under climate change and landscape fragmentation scenarios. MIGCLIM implements various parameters, such as dispersal distance, increase in reproductive potential over time, barriers to dispersal or long distance dispersal. Several simulations were run for two virtual species in a study area of the western Swiss Alps, by varying dispersal distance and other parameters. Each simulation covered the hundred-year period 2001-2100 and three different IPCC-based temperature warming scenarios were considered. Our results indicate that: (i) using realistic parameter values, the future potential distributions generated using MIGCLIM can differ significantly (up to more than 95% decrease in colonized surface) from those that ignore dispersal; (ii) this divergence increases both with increasing climate warming and over longer time periods; (iii) the uncertainty associated with the warming scenario can be nearly as large as the one related to dispersal parameters; (iv) accounting for dispersal, even roughly, can importantly reduce uncertainty in projections.

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: a test with plants in an arid environment

Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.

Dynamic Modelling of Material Flows and Sustainable Resource Use: Case Studies in Regional Metabolism and Space Life Support Systems

Sustainable resource use is one of the most important environmental issues of our times. It is closely related to discussions on the 'peaking' of various natural resources serving as energy sources, agricultural nutrients, or metals indispensable in high-technology applications. Although the peaking theory remains controversial, it is commonly recognized that a more sustainable use of resources would alleviate negative environmental impacts related to resource use. In this thesis, sustainable resource use is analysed from a practical standpoint, through several different case studies. Four of these case studies relate to resource metabolism in the Canton of Geneva in Switzerland: the aim was to model the evolution of chosen resource stocks and flows in the coming decades. The studied resources were copper (a bulk metal), phosphorus (a vital agricultural nutrient), and wood (a renewable resource). In addition, the case of lithium (a critical metal) was analysed briefly in a qualitative manner and in an electric mobility perspective. In addition to the Geneva case studies, this thesis includes a case study on the sustainability of space life support systems. Space life support systems are systems whose aim is to provide the crew of a spacecraft with the necessary metabolic consumables over the course of a mission. Sustainability was again analysed from a resource use perspective. In this case study, the functioning of two different types of life support systems, ARES and BIORAT, were evaluated and compared; these systems represent, respectively, physico-chemical and biological life support systems. Space life support systems could in fact be used as a kind of 'laboratory of sustainability' given that they represent closed and relatively simple systems compared to complex and open terrestrial systems such as the Canton of Geneva. The chosen analysis method used in the Geneva case studies was dynamic material flow analysis: dynamic material flow models were constructed for the resources copper, phosphorus, and wood. Besides a baseline scenario, various alternative scenarios (notably involving increased recycling) were also examined. In the case of space life support systems, the methodology of material flow analysis was also employed, but as the data available on the dynamic behaviour of the systems was insufficient, only static simulations could be performed. The results of the case studies in the Canton of Geneva show the following: were resource use to follow population growth, resource consumption would be multiplied by nearly 1.2 by 2030 and by 1.5 by 2080. A complete transition to electric mobility would be expected to only slightly (+5%) increase the copper consumption per capita while the lithium demand in cars would increase 350 fold. For example, phosphorus imports could be decreased by recycling sewage sludge or human urine; however, the health and environmental impacts of these options have yet to be studied. Increasing the wood production in the Canton would not significantly decrease the dependence on wood imports as the Canton's production represents only 5% of total consumption. In the comparison of space life support systems ARES and BIORAT, BIORAT outperforms ARES in resource use but not in energy use. However, as the systems are dimensioned very differently, it remains questionable whether they can be compared outright. In conclusion, the use of dynamic material flow analysis can provide useful information for policy makers and strategic decision-making; however, uncertainty in reference data greatly influences the precision of the results. Space life support systems constitute an extreme case of resource-using systems; nevertheless, it is not clear how their example could be of immediate use to terrestrial systems.

Task Support in Scenario Process: Case LUT 2016

This thesis attempts to find whether scenario planning supports the organizational strategy as a method for addressing uncertainty. The main issues are why, what and how scenario planning fits in organizational strategy and how the process could be supported to make it more effective. The study follows the constructive approach. It starts with examination of competitive advantage and the way that an organization develops strategy and how it addresses the uncertainty in its operational environment. Based on the conducted literature review, scenario methods would seem to provide versatile platform for addressing future uncertainties. The construction is formed by examining the scenario methods and presenting suitable support methods, which results in forming of the theoretical proposition for supporter scenario process. The theoretical framework is tested in laboratory conditions, and the results from the test sessions are used a basis for scenario stories. The process of forming the scenarios and the results are illustrated and presented for scrutiny

The Role of Information in Contemporary Migration. More Sources but Less Informed

La migració internacional contemporània és integrada en un procés d'interconnexió global definit per les revolucions del transport i de les tecnologies de la informació i la comunicació. Una de les conseqüències d'aquesta interconnexió global és que les persones migrants tenen més capacitat per a processar informació tant abans com després de marxar. Aquests canvis podrien tenir implicacions inesperades per a la migració contemporània pel que fa a la capacitat de les persones migrants per a prendre decisions més informades, la reducció de la incertesa en contextos migratoris, el desdibuixament del concepte de distància o la decisió d'emigrar cap a llocs més llunyans. Aquesta recerca és important, ja que la manca de coneixement sobre aquesta qüestió podria contribuir a fer augmentar la distància entre els objectius de les polítiques de migració i els seus resultats. El paper que tenen els agents de la informació en els contextos migratoris també podria canviar. En aquest escenari, perquè les polítiques de migració siguin més efectives, s'haurà de tenir en compte la major capacitat de la població migrant de processar la informació i les fonts d'informació en què es confia. Aquest article demostra que l'equació més informació equival a més ben informat no es compleix sempre. Fins i tot en l'era de la informació, les fonts no fiables, les expectatives falses, la sobreinformació i els rumors encara són presents en els contextos migratoris. Tanmateix, defensem l'argument que aquests efectes no volguts es podrien reduir complint quatre requisits de la informació fiable: que sigui exhaustiva, que sigui rellevant, que s'hi confiï i que sigui actualitzada.

Deposits of the sandy braided South Saskatchewan River: Implications for the use of modern analogs in reconstructing channel dimensions in reservoir characterization

Estimation of the dimensions of fluvial geobodies from core data is a notoriously difficult problem in reservoir modeling. To try and improve such estimates and, hence, reduce uncertainty in geomodels, data on dunes, unit bars, cross-bar channels, and compound bars and their associated deposits are presented herein from the sand-bed braided South Saskatchewan River, Canada. These data are used to test models that relate the scale of the formative bed forms to the dimensions of the preserved deposits and, therefore, provide an insight as to how such deposits may be preserved over geologic time. The preservation of bed-form geometry is quantified by comparing the Alluvial architecture above and below the maximum erosion depth of the modem channel deposits. This comparison shows that there is no significant difference in the mean set thickness of dune cross-strata above and below the basal erosion surface of the contemporary channel, thus suggesting that dimensional relationships between dune deposits and the formative bed-form dimensions are likely to be valid from both recent and older deposits. The data show that estimates of mean bankfull flow depth derived from dune, unit bar, and cross-bar channel deposits are all very similar. Thus, the use of all these metrics together can provide a useful check that all components and scales of the alluvial architecture have been identified correctly when building reservoir models. The data also highlight several practical issues with identifying and applying data relating to cross-strata. For example, the deposits of unit bars were found to be severely truncated in length and width, with only approximately 10% of the mean bar-form length remaining, and thus making identification in section difficult. For similar reasons, the deposits of compound bars were found to be especially difficult to recognize, and hence, estimates of channel depth based on this method may be problematic. Where only core data are available (i.e., no outcrop data exist), formative flow depths are suggested to be best reconstructed using cross-strata formed by dunes. However, theoretical relationships between the distribution of set thicknesses and formative dune height are found to result in slight overestimates of the latter and, hence, mean bankfull flow depths derived from these measurements. This article illustrates that the preservation of fluvial cross-strata and, thus, the paleohydraulic inferences that can be drawn from them, are a function of the ratio of the size and migration rate of bed forms and the time scale of aggradation and channel migration. These factors must thus be considered when deciding on appropriate length:thickness ratios for the purposes of object-based modeling in reservoir characterization.

Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data

Maximum entropy modeling (Maxent) is a widely used algorithm for predicting species distributions across space and time. Properly assessing the uncertainty in such predictions is non-trivial and requires validation with independent datasets. Notably, model complexity (number of model parameters) remains a major concern in relation to overfitting and, hence, transferability of Maxent models. An emerging approach is to validate the cross-temporal transferability of model predictions using paleoecological data. In this study, we assess the effect of model complexity on the performance of Maxent projections across time using two European plant species (Alnus giutinosa (L.) Gaertn. and Corylus avellana L) with an extensive late Quaternary fossil record in Spain as a study case. We fit 110 models with different levels of complexity under present time and tested model performance using AUC (area under the receiver operating characteristic curve) and AlCc (corrected Akaike Information Criterion) through the standard procedure of randomly partitioning current occurrence data. We then compared these results to an independent validation by projecting the models to mid-Holocene (6000 years before present) climatic conditions in Spain to assess their ability to predict fossil pollen presence-absence and abundance. We find that calibrating Maxent models with default settings result in the generation of overly complex models. While model performance increased with model complexity when predicting current distributions, it was higher with intermediate complexity when predicting mid-Holocene distributions. Hence, models of intermediate complexity resulted in the best trade-off to predict species distributions across time. Reliable temporal model transferability is especially relevant for forecasting species distributions under future climate change. Consequently, species-specific model tuning should be used to find the best modeling settings to control for complexity, notably with paleoecological data to independently validate model projections. For cross-temporal projections of species distributions for which paleoecological data is not available, models of intermediate complexity should be selected.

Doses monitoring in radiology: calibration of air kerma-area product (PKA) meters

Objective The authors have sought to study the calibration of a clinical PKA meter (Diamentor E2) and a calibrator for clinical meters (PDC) in the Laboratory of Ionizing Radiation Metrology at Instituto de Energia e Ambiente - Universidade de São Paulo. Materials and Methods Different qualities of both incident and transmitted beams were utilized in conditions similar to a clinical setting, analyzing the influence from the reference dosimeter, from the distance between meters, from the filtration and from the average beam energy. Calibrations were performed directly against a standard 30 cm3 cylindrical chamber or a parallel-plate monitor chamber, and indirectly against the PDC meter. Results The lowest energy dependence was observed for transmitted beams. The cross calibration between the Diamentor E2 and the PDC meters, and the PDC presented the greatest propagation of uncertainties. Conclusion The calibration coefficient of the PDC meter showed to be more stable with voltage, while the Diamentor E2 calibration coefficient was more variable. On the other hand, the PDC meter presented greater uncertainty in readings (5.0%) than with the use of the monitor chamber (3.5%) as a reference.

Analyzing Carbon Trade Permits in Optimization Framework

The threats caused by global warming motivate different stake holders to deal with and control them. This Master's thesis focuses on analyzing carbon trade permits in optimization framework. The studied model determines optimal emission and uncertainty levels which minimize the total cost. Research questions are formulated and answered by using different optimization tools. The model is developed and calibrated by using available consistent data in the area of carbon emission technology and control. Data and some basic modeling assumptions were extracted from reports and existing literatures. The data collected from the countries in the Kyoto treaty are used to estimate the cost functions. Theory and methods of constrained optimization are briefly presented. A two-level optimization problem (individual and between the parties) is analyzed by using several optimization methods. The combined cost optimization between the parties leads into multivariate model and calls for advanced techniques. Lagrangian, Sequential Quadratic Programming and Differential Evolution (DE) algorithm are referred to. The role of inherent measurement uncertainty in the monitoring of emissions is discussed. We briefly investigate an approach where emission uncertainty would be described in stochastic framework. MATLAB software has been used to provide visualizations including the relationship between decision variables and objective function values. Interpretations in the context of carbon trading were briefly presented. Suggestions for future work are given in stochastic modeling, emission trading and coupled analysis of energy prices and carbon permits.

Barriers of ESCO Service Business in Finland

The purpose of this study is to determine what are the key barriers hampering ESCO service business success in Finland. Research approach for this study is qualitative. Data was collected using Delphi method with two questionnaire rounds. Internet based tool was applied in carrying out questionnaires. Respondents of the questionnaires were ESCO service experts and researchers, and people working for ESCO service providers. Characteristics of ESCO service and ESCO project implementation are analyzed by using transaction costs theory of service business. In terms of ESCO service in Finland, uncertainty and asset specificity are relevant dimensions of TCE. General uncertainty in world’s economy hinders demand for ESCO service, and asset specificity of ESCO contracts induces slight problems for project financiers. Also bounded rationalism and opportunism are present in Finnish ESCO business. The most significant barriers of success of ESCO service in Finland are problems in legislative and political frameworks, and in customers’ investment processes. ESCO service providers should move more strongly towards service dominant business logic and improve understanding of customer needs. Political barriers are unsuitable procurement processes, unclear and unpredictable laws, and lack of compelling factors in subsidy system. Investment process hurdles are caused by customers’ lack of interest to change course of action. These are things in which ESCOs can have influence in.

In-House Validation of Capillary Electrophoresis Method

Capillary electrophoresis method designed originally for the analysis of monosaccharides was validated using reference solutions of polydatin. The validation was conducted by studying and determining the concentration levels of LOD and LOQ and the range of linearity and by determining levels of uncertainty in respect to repeatability and reproducibility. The reliability of the gained results is also discussed. A guide with recommendations considering the validation and overall design of analysis sequences with CE is also produced as a result of this study.

From genes to communities : stress tolerance in eelgrass (Zostera marina)

Shallow coastal areas are dynamic habitats that are affected by a variety of abiotic and biotic factors. In addition to the natural environmental stress, estuarine and coastal seagrass ecosystems are exposed to effects of climate change and other anthropogenic impacts. In this thesis the effect of different abiotic (shading stress, salinity and temperature) and biotic stressors (presence of co-occurring species) and different levels and combinations of stressors on the performance and survival of eelgrass (Zostera marina) was assessed. To investigate the importance of scale for stress responses, varying levels of biological organization (genotype, life stage, population and plant community) were studied in field and aquarium experiments. Light limitation, decreased salinity and increased temperature affected eelgrass performance negatively in papers I, II and III, respectively. While co-occurring plant species had no notable effect on eelgrass in paper IV, the presence of eelgrass increased the biomass of Potamogeton perfoliatus. The findings in papers II and III confirmed that more extreme levels of salinity and temperature had stronger impacts on plant performance compared to intermediate levels, but intermediate levels also had more severe effects on plants when they were exposed to several stressors, as illustrated in paper II. Thus, multiple stressors had negative synergetic effects. The results in papers I, II and III indicate that future changes in light climate, salinity and temperature can have serious impacts on eelgrass performance and survival. Stress responses were found to vary among genotypes, life stages and populations in papers I, II and III, respectively, emphasizing the importance of study scale. The results demonstrate that while stress in general affects seagrass productivity negatively, the severity of effects can vary substantially depending on the studied scale or level of biological organization. Eelgrass genotypes can differ in their stress and recovery processes, as observed in paper I. In paper II, eelgrass seedlings were less prone to abiotic stress compared to adult plants, but stress also decreased their survival considerably. This indicates that recruitment and re-colonization through seeds might be threatened in the future. Variation among population responses observed in paper III indicates that long-term local adaptation under differing selection pressures has caused divergence in salinity tolerance between Baltic eelgrass populations. This variability in stress tolerance observed in papers I and III suggests that some eelgrass genotypes and populations have a better capacity to adapt to changes and survive in a changing environment. Multiple stressors and biological level-specific responses demonstrate the uncertainty in predicting eelgrass responses in a changing environment. As eelgrass populations may differ in their stress tolerance both within and across regions, conservation strategies at both local and regional scales are urgently needed in order to ensure the survival of these important ecosystems.

Price movement in the Brazilian land market (1994-2010): an analysis in the light of post-Keynesian theory

ABSTRACT The present study aims to evaluate crop, pasture and forest land prices in Brazil, between 1994 and 2010, in the light of Post-Keynesian theory. The results provide evidence that land, more than just a simple factor of production, must be conceived of as an economic asset. In fact, the price of rural land is determined not only by the expected profitability deriving from agricultural activities but also by the agents' expectations about its future appreciation and liquidity in an economic environment permeated with uncertainty. In this context, as an object of speculation, land has been particularly important as a store of value.