Uncertainty in forest simulators and forest planning systems

The forest simulator is a computerized model for predicting forest growth and future development as well as effects of forest harvests and treatments. The forest planning system is a decision support tool, usually including a forest simulator and an optimisation model, for finding the optimal forest management actions. The information produced by forest simulators and forest planning systems is used for various analytical purposes and in support of decision making. However, the quality and reliability of this information can often be questioned. Natural variation in forest growth and estimation errors in forest inventory, among other things, cause uncertainty in predictions of forest growth and development. This uncertainty stemming from different sources has various undesirable effects. In many cases outcomes of decisions based on uncertain information are something else than desired. The objective of this thesis was to study various sources of uncertainty and their effects in forest simulators and forest planning systems. The study focused on three notable sources of uncertainty: errors in forest growth predictions, errors in forest inventory data, and stochastic fluctuation of timber assortment prices. Effects of uncertainty were studied using two types of forest growth models, individual tree-level models and stand-level models, and with various error simulation methods. New method for simulating more realistic forest inventory errors was introduced and tested. Also, three notable sources of uncertainty were combined and their joint effects on stand-level net present value estimates were simulated. According to the results, the various sources of uncertainty can have distinct effects in different forest growth simulators. The new forest inventory error simulation method proved to produce more realistic errors. The analysis on the joint effects of various sources of uncertainty provided interesting knowledge about uncertainty in forest simulators.

Valuation of reduced eutrophication in the Gulf of Finland : Choice experiment with attention to heterogeneous and discontinuous preferences and respondent uncertainty

Eutrophication of the Baltic Sea is a serious problem. This thesis estimates the benefit to Finns from reduced eutrophication in the Gulf of Finland, the most eutrophied part of the Baltic Sea, by applying the choice experiment method, which belongs to the family of stated preference methods. Because stated preference methods have been subject to criticism, e.g., due to their hypothetical survey context, this thesis contributes to the discussion by studying two anomalies that may lead to biased welfare estimates: respondent uncertainty and preference discontinuity. The former refers to the difficulty of stating one s preferences for an environmental good in a hypothetical context. The latter implies a departure from the continuity assumption of conventional consumer theory, which forms the basis for the method and the analysis. In the three essays of the thesis, discrete choice data are analyzed with the multinomial logit and mixed logit models. On average, Finns are willing to contribute to the water quality improvement. The probability for willingness increases with residential or recreational contact with the gulf, higher than average income, younger than average age, and the absence of dependent children in the household. On average, for Finns the relatively most important characteristic of water quality is water clarity followed by the desire for fewer occurrences of blue-green algae. For future nutrient reduction scenarios, the annual mean household willingness to pay estimates range from 271 to 448 and the aggregate welfare estimates for Finns range from 28 billion to 54 billion euros, depending on the model and the intensity of the reduction. Out of the respondents (N=726), 72.1% state in a follow-up question that they are either Certain or Quite certain about their answer when choosing the preferred alternative in the experiment. Based on the analysis of other follow-up questions and another sample (N=307), 10.4% of the respondents are identified as potentially having discontinuous preferences. In relation to both anomalies, the respondent- and questionnaire-specific variables are found among the underlying causes and a departure from standard analysis may improve the model fit and the efficiency of estimates, depending on the chosen modeling approach. The introduction of uncertainty about the future state of the Gulf increases the acceptance of the valuation scenario which may indicate an increased credibility of a proposed scenario. In conclusion, modeling preference heterogeneity is an essential part of the analysis of discrete choice data. The results regarding uncertainty in stating one s preferences and non-standard choice behavior are promising: accounting for these anomalies in the analysis may improve the precision of the estimates of benefit from reduced eutrophication in the Gulf of Finland.

Optimisation Problems in Wireless Sensor Networks : Local Algorithms and Local Graphs

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.

Environmental factors and uncertainty in fisheries management in the northern Baltic Sea

The Baltic Sea is a geologically young, large brackish water basin, and few of the species living there have fully adapted to its special conditions. Many of the species live on the edge of their distribution range in terms of one or more environmental variables such as salinity or temperature. Environmental fluctuations are know to cause fluctuations in populations abundance, and this effect is especially strong near the edges of the distribution range, where even small changes in an environmental variable can be critical to the success of a species. This thesis examines which environmental factors are the most important in relation to the success of various commercially exploited fish species in the northern Baltic Sea. It also examines the uncertainties related to fish stocks current and potential status as well as to their relationship with their environment. The aim is to quantify the uncertainties related to fisheries and environmental management, to find potential management strategies that can be used to reduce uncertainty in management results and to develop methodology related to uncertainty estimation in natural resources management. Bayesian statistical methods are utilized due to their ability to treat uncertainty explicitly in all parts of the statistical model. The results show that uncertainty about important parameters of even the most intensively studied fish species such as salmon (Salmo salar L.) and Baltic herring (Clupea harengus membras L.) is large. On the other hand, management approaches that reduce uncertainty can be found. These include utilising information about ecological similarity of fish stocks and species, and using management variables that are directly related to stock parameters that can be measured easily and without extrapolations or assumptions.

Good Lives, Hidden Miseries : An Ethnography of Uncertainty in a Finnish Village

This is an ethnographic study, in the field of medical anthropology, of village life among farmers in southwest Finland. It is based on 12 months of field work conducted 2002-2003 in a coastal village. The study discusses how social and cultural change affects the life of farmers, how they experience it and how they act in order to deal with the it. Using social suffering as a methodological approach the study seeks to investigate how change is related to lived experiences, idioms of distress, and narratives. Its aim has been to draw a locally specific picture of what matters are at stake in the local moral world that these farmers inhabit, and how they emerge as creative actors within it. A central assumption made about change is that it is two-fold; both a constructive force which gives birth to something new, and also a process that brings about uncertainty regarding the future. Uncertainty is understood as an existential condition of human life that demands a response, both causing suffering and transforming it. The possibility for positive outcomes in the future enables one to understand this small suffering of everyday life both as a consequence of social change, which fragments and destroys, and as an answer to it - as something that is positively meaningful. Suffering is seen to engage individuals to ensure continuity, in spite of the odds, and to sustain hope regarding the future. When the fieldwork was initiated Finland had been a member of the European Union for seven years and farmers felt it had substantially impacted on their working conditions. They complained about the restrictions placed on their autonomy and that their knowledge was neither recognised, nor respected by the bureaucrats of the EU system. New regulations require them to work in a manner that is morally unacceptable to them and financial insecurity has become more prominent. All these changes indicate the potential loss of the home and of the ability to ensure continuity of the family farm. Although the study initially focused on getting a general picture of working conditions and the nature of farming life, during the course of the fieldwork there was repeated mention of a perceived high prevalence of cancer in the area. This cancer talk is replete with metaphors that reveal cultural meanings tied to the farming life and the core values of autonomy, endurance and permanence. It also forms the basis of a shared identity and a means of delivering a moral message about the fragmentation of the good life; the loss of control; and the invasion of the foreign. This thesis formed part of the research project Expressions of Suffering. Ethnographies of Illness Experiences in Contemporary Finnish Contexts funded by the Academy of Finland. It opens up a vital perspective on the multiplicity and variety of the experience of suffering and that it is particularly through the use of the ethnographic method that these experiences can be brought to light. Keywords: suffering, uncertainty, phenomenology, habitus, agency, cancer, farming

Flexible Budgeting under Uncertainty: A Real Options Perspective

This paper examines the relationships between uncertainty and the perceived usefulness of traditional annual budgets versus flexible budgets in 95 Swedish companies. We form hypotheses that the perceived usefulness of the annual budgets as well as the attitudes to more flexible budget alternatives are influenced by the uncertainty that the companies face. Our study distinguishes between two separate kinds of uncertainty: exogenous stochastic uncertainty (deriving from the firm’s environment) and endogenous deterministic uncertainty (caused by the strategic choices made by the firm itself). Based on a structural equations modelling analysis of data from a mail survey we found that the more accentuated exogenous uncertainty a company faces, the more accentuated is the expected trend towards flexibility in the budget system, and vice versa; the more endogenous uncertainty they face, the more negative are their attitudes towards budget flexibility. We also found that these relationships were not present with regard to the attitudes towards the usefulness of the annual budget. Noteworthy is, however, that there was a significant negative relationship between the perceived usefulness of the annual budget and budget flexibility. Thus, our results seem to indicate that the degree of flexibility in the budget system is influenced by both general attitudes towards the usefulness of traditional budgets and by the actual degree of exogenous uncertainty a company faces and by the strategy that it executes.

Real Estate Investment and Uncertainty: Econometric Modelling using Finnish Data

The purpose of this paper is to test for the effect of uncertainty in a model of real estate investment in Finland during the hihhly cyclical period of 1975 to 1998. We use two alternative measures of uncertainty. The first measure is the volatility of stock market returns and the second measure is the heterogeneity in the answers of the quarterly business survey of the Confederation of Finnish Industry and Employers. The econometric analysis is based on the autoregressive distributed lag (ADL) model and the paper applies a 'general-to-specific' modelling approach. We find that the measure of heterogeneity is significant in the model, but the volatility of stock market returns is not. The empirical results give some evidence of an uncertainty-induced threshold slowing down real estate investment in Finland.

Does Uncertainty Affect Investment and Labor Demand?

This paper analyzes the effect of uncertainty on investment and labor demand for Finnish firms during the time period 1987 – 2000. Utilizing a stock return based measure of uncertainty decomposed into systematic and idiosyncratic components, the results reveal that idiosyncratic uncertainty significantly reduces both investment and labor demand. Idiosyncratic uncertainty seems to influence investment in the current period, whereas the depressing effect on labor demand appears with a one-year lag. The results provide support that the depressing effect of idiosyncratic uncertainty on investment is stronger for small firms in comparison to large firms. Some evidence is reported regarding differential effects of uncertainty on labor demand conditional on firm characteristics. Most importantly, the depressing effect of lagged idiosyncratic uncertainty on labor demand tends to be stronger for diversified firms compared with focused firms.

Optimisation problems in wireless sensor networks

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating–dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating–dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs – these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating–dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.