Growth release of trees following canopy disturbances is of interest to ecological scientists and forest managers. Using dendroecological techniques, I examined growth release of canopy and subcanopy trees following the formation of natural, fine-scale canopy gaps in old-growth, western red cedar-western hemlock forests of coastal British Columbia. I aimed to quantify detailed information on release of the three shade-tolerant tree species that constitute these stands: western red cedar (Thuja plicata), western hemlock (Tsuga heterophylla), and Pacific silver fir (Abies amabilis). As a first step, I calibrated the radial-growth averaging method to account for regional-scale variability and capture a more complete range of growth releases that may occur following the formation of fine-scale gaps in the study stands. A 25% threshold, 5-year moving average, and 10-year window emerged as appropriate parameters for detecting releases using radial-growth averaging. Basal area increment was also the most appropriate growth index for detecting releases. Establishing these empirically-based criteria was important for quantifying the magnitude and duration of releases. Tree diameter and growth rate prior to release were the most important predictors of the magnitude and duration of releases, but identity of the tree species and distance from the gap center were also important predictors. Western hemlock and Pacific silver fir were often growing slowly both in the canopy and subcanopy, giving them tremendous potential to release. For these species, releases were generally intensive and persistent. In contrast, western red cedar were often growing quickly both in the canopy and subcanopy, giving them less potential to release. Compared to western hemlock and Pacific silver fir, western red cedar releases were less intensive and persistent. Patterns related to distance from the gap center emerged for trees growing along the north-south axis of gaps. Regardless of species, increasing distance from the gap center resulted in decreasing magnitude and duration of releases. However, patterns for duration were complex, as the distance effect was greater for trees north of the gap center. Information on growth release of trees is useful for reconstructing the history of past canopy disturbances, elucidating mechanisms of tree species coexistence, and assessing and predicting stand changes due to forest management in coastal British Columbia. / Arts, Faculty of / Geography, Department of / Graduate

Buffer tanks are widely used within the process industry to prevent flow variations from being directly propagated throughout a plant. The capacity of the tank is used to smoothly transfer inlet flow upsets to the outlet. Ideally, the tank thus works as a low pass filter where the available tank capacity limits the achievable flow smoothing. For infrequently occurring upsets, where the system has time to reach steady state between flow changes, the averaging level control problem has been extensively studied. After an inlet flow change, flow filtering has traditionally been obtained by letting the tank level deviate from its nominal value while slowly adapting the outlet to cancel out the flow imbalance and eventually bringing back the level to its set-point. The system is then again in steady state and ready to surge the next upset. By ensuring that the single largest upset can be handled without violating the level constraints, satisfactory flow smoothing is obtained. In this thesis, the smoothing of frequently changing inlet flows is addressed. In this case, standard level controllers struggle to obtain acceptable flow smoothing since the system rarely is in steady state and flow upsets can thus not be treated as separate events. To obtain a control law that achieves optimal filtering while directly accounting for future upsets, the averaging level control problem was approached using robust model predictive control (MPC). The robust MPC differs in the way it obtains flow smoothing by not returning the tank level to a fixed set-point. Instead, it lets the steady state tank level depend on the current value of the inlet flow. This insight was then used to propose a linear control structure, designed to filter frequent upsets optimally. Analyses and simulation results indicate that the proposed linear and robust MPC controller obtain flow smoothing comparable to the standard optimal averaging level controllers for infrequent upsets while handling frequent upsets considerably better.

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A significant progress in the evolution of the computer systems and their interconnection over the past 70 years has allowed replacing the frequently used centralized architectures with the highly distributed ones, formed by independent entities fulfilling specific functionalities as one user-intransparent unit. This has resulted in an intense scientic interest in distributed algorithms and their frequent implementation into real systems. Especially, distributed algorithms for multi-sensor data fusion, ensuring an enhanced QoS of executed applications, find a wide usage. This doctoral thesis addresses an optimization and an analysis of the distributed systems, namely the distributed consensus-based algorithms for an aggregate function estimation (primarily, my attention is focused on a mean estimation). The first section is concerned with a theoretical background of the distributed systems, their evolution, their architectures, and a comparison with the centralized systems (i.e. their advantages/disadvantages). The second chapter deals with multi-sensor data fusion, its application, the classification of the distributed estimation techniques, their mathematical modeling, and frequently quoted algorithms for distributed averaging (e.g. protocol Push-Sum, Metropolis-Hastings weights, Best Constant weights etc.). The practical part is focused on mechanisms for an optimization of the distributed systems, the proposal of novel algorithms and complements for the distributed systems, their analysis, and comparative studies in terms of such as the convergence rate, the estimation precision, the robustness, the applicability to real systems etc.

<p>Predmet ovog istraživanja je ponašanje donosilaca odluka u uslovima<br />neizvesnosti. Na osnovu sprovedene simulacije među subjektima i<br />dobijenih rezultata, cilj ove disertacije je da se utvrde dominantni<br />faktori prilikom poslovnog odlučivanja u uslovma kada donosiolac<br />poslovnih odluka ne raspolaže informacijama potrebnim za ispravno<br />donošenje odluka u trenucima kada njegova investicija ostvaruje<br />gubitak. Prilikom utvrđivanja sklonosti donosioca odluke u obzir je<br />uzet i pol donosioca odluke i poslovni status, kao i prethodno<br />iskazane sklonosti ka riziku.</p> / <p>The subject of this research is behavior of decision &ndash; makers in ambiguous<br />surroundings. Based on the simulation that was conducted among subjects<br />and results obtained from it, the aim of this dissertation is to establish<br />dominant factors that influence decision &ndash; making process in situations<br />where information neccesery for adequate decision &ndash; making are not<br />available to decision &ndash; makers in situations where decision &ndash; makers are<br />facing loss. Gender and employmet status were taken into consideration<br />during determination of decision &ndash; makers preferences, as well as their<br />previously exhibited risk preferences.</p>

The dissertation is a compilation of three empirical papers on the effects of financial development. In the first paper, we examine finance's effect on long-term economic growth using Bayesian model averaging to address model uncertainty. Our global sample findings indicate that the efficiency of financial intermediation is robustly related to long-term growth. The second and third papers investigate the determinants of wealth and income inequality, capturing various economic, financial, political, institutional, and geographical factors. We reveal that finance plays a considerable role in shaping both distributions.

The relationship between income inequality and happiness is central to a host of welfare policies. If higher income inequality puts people down, advocating for income redistribution from the rich to the poor could make society happier. We show, however, that this popular consensus on the relationship's direction is rather absent in the academic literature. Based on the 868 observations col- lected from 53 studies and controlling for 62 aspects of study design, we use state-of-the-art meta-analysis techniques to identify several important drivers of the efect. Unless each study gets the same weight, the literature is driven by publication bias pushing the estimates against the popular consensus. While geographical diferences dominate among the systematic infuences of the re- lationship's magnitude, the relationship is also strongly afected by various methods and data the authors use in the primary studies. Most prominently, it matters if authors control for diferent individual's characteristics, such as perceived trust in people or their health status.

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