Studies on the international effects of real shocks

This doctoral thesis addresses the macroeconomic effects of real shocks in open economies in flexible exchange rate regimes. The first study of this thesis analyses the welfare effects of fiscal policy in a small open economy, where private and government consumption are substitutes in terms of private utility. The main findings are as follows: fiscal policy raises output, bringing it closer to its efficient level, but is not welfare-improving even though government spending directly affects private utility. The main reason for this is that the introduction of useful government spending implies a larger crowding-out effect on private consumption, when compared with the `pure waste' case. Utility decreases since one unit of government consumption yields less utility than one unit of private consumption. The second study of this thesis analyses the question of how the macroeconomic effects of fiscal policy in a small open economy depend on optimal intertemporal behaviour. The key result is that the effects of fiscal policy depend on the size of the elasticity of substitution between traded and nontraded goods. In particular, the sign of the current account response to fiscal policy depends on the interplay between the intertemporal elasticity of aggregate consumption and the elasticity of substitution between traded and nontraded goods. The third study analyses the consequences of productive government spending on the international transmission of fiscal policy. A standard result in the New Open Economy Macroeconomics literature is that a fiscal shock depreciates the exchange rate. I demonstrate that the response of the exchange rate depends on the productivity of government spending. If productivity is sufficiently high, a fiscal shock appreciates the exchange rate. It is also shown that the introduction of productive government spending increases both domestic and foreign welfare, when compared with the case where government spending is wasted. The fourth study analyses the question of how the international transmission of technology shocks depends on the specification of nominal rigidities. A growing body of empirical evidence suggests that a positive technology shock leads to a temporary decline in employment. In this study, I demonstrate that the open economy dimension can enhance the ability of sticky price models to account for the evidence. The reasoning is as follows. An improvement in technology appreciates the nominal exchange rate. Under producer-currency pricing, the exchange rate appreciation shifts global demand toward foreign goods away from domestic goods. This causes a temporary decline in domestic employment.

The Macroeconomic Effects of Fiscal Policy in a Small Open Economy under a Flexible Exchange Rate Regime

This licentiate's thesis analyzes the macroeconomic effects of fiscal policy in a small open economy under a flexible exchange rate regime, assuming that the government spends exclusively on domestically produced goods. The motivation for this research comes from the observation that the literature on the new open economy macroeconomics (NOEM) has focused almost exclusively on two-country global models and the analyses of the effects of fiscal policy on small economies are almost completely ignored. This thesis aims at filling in the gap in the NOEM literature and illustrates how the macroeconomic effects of fiscal policy in a small open economy depend on the specification of preferences. The research method is to present two theoretical model that are extensions to the model contained in the Appendix to Obstfeld and Rogoff (1995). The first model analyzes the macroeconomic effects of fiscal policy, making use of a model that exploits the idea of modelling private and government consumption as substitutes in private utility. The model offers intuitive predictions on how the effects of fiscal policy depend on the marginal rate of substitution between private and government consumption. The findings illustrate that the higher the substitutability between private and government consumption, (i) the bigger is the crowding out effect on private consumption (ii) and the smaller is the positive effect on output. The welfare analysis shows that the less fiscal policy decreases welfare the higher is the marginal rate of substitution between private and government consumption. The second model of this thesis studies how the macroeconomic effects of fiscal policy depend on the elasticity of substitution between traded and nontraded goods. This model reveals that this elasticity a key variable to explain the exchange rate, current account and output response to a permanent rise in government spending. Finally, the model demonstrates that temporary changes in government spending are an effective stabilization tool when used wisely and timely in response to undesired fluctuations in output. Undesired fluctuations in output can be perfectly offset by an opposite change in government spending without causing any side-effects.

Self-rating scales in the assessment of current and childhood symptoms of attention deficit hyperactivity disorder in adults

Objective: Attention deficit hyperactivity disorder (ADHD) is a life-long condition, but because of its historical status as a self-remitting disorder of childhood, empirically validated and reliable methods for the assessment of adults are scarce. In this study, the validity and reliability of the Wender Utah Rating Scale (WURS) and the Adult Problem Questionnaire (APQ), which survey childhood and current symptoms of ADHD, respectively, were studied in a Finnish sample. Methods: The self-rating scales were administered to adults with an ADHD diagnosis (n = 38), healthy control participants (n = 41), and adults diagnosed with dyslexia (n = 37). Items of the self-rating scales were subjected to factor analyses, after which the reliability and discriminatory power of the subscales, derived from the factors, were examined. The effects of group and gender on the subscales of both rating scales were studied. Additionally, the effect of age on the subscales of the WURS was investigated. Finally, the diagnostic accuracy of the total scores was studied. Results: On the basis of the factor analyses, a four-factor structure for the WURS and five-factor structure for the APQ had the best fit to the data. All of the subscales of the APQ and three of the WURS achieved sufficient reliability. The ADHD group had the highest scores on all of the subscales of the APQ, whereas two of the subscales of the WURS did not statistically differ between the ADHD and the Dyslexia group. None of the subscales of the WURS or the APQ was associated with the participant's gender. However, one subscale of the WURS describing dysthymia was positively correlated with the participant's age. With the WURS, the probability of a correct positive classification was .59 in the current sample and .21 when the relatively low prevalence of adult ADHD was taken into account. The probabilities of correct positive classifications with the APQ were .71 and .23, respectively. Conclusions: The WURS and the APQ can provide accurate and reliable information of childhood and adult ADHD symptoms, given some important constraints. Classifications made on the basis of the total scores are reliable predictors of ADHD diagnosis only in populations with a high proportion of ADHD and a low proportion of other similar disorders. The subscale scores can provide detailed information of an individual's symptoms if the characteristics and limitations of each domain are taken into account. Improvements are suggested for two subscales of the WURS.

Cognitive Functioning in Young Adults with Depression, Anxiety Disorders, or Burnout Symptoms : Findings from a Population-based Sample

Background. Evidence of cognitive dysfunction in depressive and anxiety disorders is growing. However, the neuropsychological profile of young adults has received only little systematic investigation, although depressive and anxiety disorders are major public health problems for this age group. Available studies have typically failed to account for psychiatric comorbidity, and samples derived from population-based settings have also seldom been investigated. Burnout-related cognitive functioning has previously been investigated in only few studies, again all using clinical samples and wide age groups. Aims. Based on the information gained by conducting a comprehensive review, studies on cognitive impairment in depressive and anxiety disorders among young adults are rare. The present study examined cognitive functioning in young adults with a history of unipolar depressive or anxiety disorders in comparison to healthy peers, and associations of current burnout symptoms with cognitive functioning, in a population-based setting. The aim was also to determine whether cognitive deficits vary as a function of different disorder characteristics, such as severity, psychiatric comorbidity, age at onset, or the treatments received. Methods. Verbal and visual short-term memory, verbal long-term memory and learning, attention, psychomotor processing speed, verbal intelligence, and executive functioning were measured in a population-based sample of 21-35 year olds. Performance was compared firstly between participants with pure non-psychotic depression (n=68) and healthy peers (n=70), secondly between pure (n=69) and comorbid depression (n=57), and thirdly between participants with anxiety disorders (n=76) and healthy peers (n=71). The diagnostic procedure was based on the SCID interview. Fourthly, the associations of current burnout symptoms, measured with the Maslach Burnout Inventory General Survey, and neuropsychological test performance were investigated among working young adults (n=225). Results. Young adults with depressive or anxiety disorders, with or without psychiatric comorbidity, were not found to have major cognitive impairments when compared to healthy peers. Only mildly compromised verbal learning was found among depressed participants. Pure and comorbid depression groups did not differ in cognitive functioning, either. Among depressed participants, those who had received treatment showed more impaired verbal memory and executive functioning, and earlier onset corresponded with more impaired executive functioning. In anxiety disorders, psychotropic medication and low psychosocial functioning were associated with deficits in executive functioning, psychomotor processing speed, and visual short-term memory. Current burnout symptoms were associated with better performance in verbal working memory and verbal intelligence. However, lower examiner-rated social and occupational functioning was associated with problems in verbal attention, memory, and learning. Conclusions. Depression, anxiety disorders, or burnout symptoms may not be associated with major cognitive deficits among young adults derived from the general population. Even psychiatric comorbidity may not aggravate cognitive functioning in depressive or anxiety disorders among these young adults. However, treatment-seeking in depression was found to be associated with cognitive deficits, suggesting that these deficits relate to increased distress. Additionally, early-onset depression, found to be associated with executive dysfunction, may represent a more severe form of the disorder. In anxiety disorders, those with low symptom-related psychosocial functioning may have cognitive impairment. An association with self-reported burnout symptoms and cognitive deficits was not detected, but individuals with low social and occupational functioning may have impaired cognition.

Mitä autismin kirjon opiskelijat oppivat valmentavassa koulutuksessa

The purpose of this research was to evaluate the special vocational training programme, which aimed at enhancing the pupils with autism spectrum to prepare themselves for work and independent life. The vocational training programme is based on TEACCH (Treatment and Education of Autistic and Related Communication handicapped CHildren), which takes into account the autism spectrum disorders and autistic behaviour. TEACCH is based on the principles of structured teaching, functional teaching and preparation training for work and independent life. The TEACCH has been adapted to Finnish society and the educational system. Treatment programmes were individually designed for each student´s educational needs. There is also an important role for the AAPEP rating scale (Adolescent and Adult Psychoeducational Profile). The AAPEP has been the major tool for planning and following the courses. The AAPEP is an assessment instrument designed by the TEACCH programme, and it is used to provide an evaluation of current and potential skills. The AAPEP contains three scales: a direct observation scale, a home scale and a school / work scale. The AAPEP includes six test variables: vocational skills, independent functions, functional communication, interpersonal behaviour, vocational behaviour and leisure skills; these are evaluated at three levels: pass, emerge and fail. The subjects were 49 students (65% male and 35 % female) with autism spectrum, who have been followed and tested several times, also one year after the vocational training. The design is therefore a longitudinal one. The research data were collected 1997-2004 using the AAPEP rating scales. The teachers have used the AAPEP scales and the codings have been checked by the researcher. The results of the principal component analysis (PCA) suggested that the structure of AAPEP rating scales works quite well as a hypothesis. The factor structure of the scales of the AAPEP was almost the same in these data as in the original publications. The learning-and-changes results showed that learning is a slow process, but that there were also intended changes in several AAPEP areas. The Cohen´s kappa was used as an effect-size measure and the most important result of this research showed that the student´s skills were developing on a school / work scale; vocational skills variable (0,34), vocational behaviour variable (0,28), leisure skills variable (0,26) and on a direct observation scale; interpersonal behaviour variable (0,21). On a home scale skills of some students were developing negatively and also that effect-size was small. The results showed that the students´ vocational skills and vocational behaviour will continue to develop after school in many areas. There were differences between scales. The result of this research shows that the student´s skills were developing significantly in 3 of 48 variables on a direct observation scale and also on a home scale. On a school / work scale student´s skills were developing significantly in 17 of 48 variables. This result implies that students can do the work without extra assistance if there exist continuing supports for the skills after the vocational training. The fully independent life of students will be difficult, because their independent functions, functional communications and leisure skills regressed after the schooling. This seems to indicate that they will not manage their daily life without support. The students and their parents said that the treatment programmes were individually designed for each student s educational needs, and that they were satisfied with the programmes and services. Generally, it can be concluded that vocational special education can be developed for pupils with autistic syndrome and the detailed teaching can be done using TEACCH principles and applying the tool of AAPEP.

Mammographic mass-screening and future breast cancer burden in Finland

A population-based early detection program for breast cancer has been in progress in Finland since 1987. According to regulations during the study period 1987-2001, free of charge mammography screening was offered every second year to women aged 50-59 years. Recently, the screening service was decided to be extended to age group 50-69. However, the scope of the program is still frequently discussed in public and information about potential impacts of mass-screening practice changes on future breast cancer burden is required. The aim of this doctoral thesis is to present methodologies for taking into account the mass-screening invitation information in breast cancer burden predictions, and to present alternative breast cancer incidence and mortality predictions up to 2012 based on scenarios of the future screening policy. The focus of this work is not on assessing the absolute efficacy but the effectiveness of mass-screening, and, by utilizing the data on invitations, on showing the estimated impacts of changes in an existing screening program on the short-term predictions. The breast cancer mortality predictions are calculated using a model that combines incidence, cause-specific and other cause survival on individual level. The screening invitation data are incorporated into modeling of breast cancer incidence and survival by dividing the program into separate components (first and subsequent rounds and years within them, breaks, and post screening period) and defining a variable that gives the component of the screening program. The incidence is modeled using a Poisson regression approach and the breast cancer survival by applying a parametric mixture cure model, where the patient population is allowed to be a combination of cured and uncured patients. The patients risk to die from other causes than breast cancer is allowed to differ from that of a corresponding general population group and to depend on age and follow-up time. As a result, the effects of separate components of the screening program on incidence, proportion of cured and the survival of the uncured are quantified. According to the predictions, the impacts of policy changes, like extending the program from age group 50-59 to 50-69, are clearly visible on incidence while the effects on mortality in age group 40-74 are minor. Extending the screening service would increase the incidence of localized breast cancers but decrease the rates of non-localized breast cancer. There were no major differences between mortality predictions yielded by alternative future scenarios of the screening policy: Any policy change would have at the most a 3.0% reduction on overall breast cancer mortality compared to continuing the current practice in the near future.

Multiple socioeconomic circumstances and health : associations and explanations among Finnish and British public sector employees

Socioeconomic health inequalities have been widely documented, with a lower social position being associated with poorer physical and general health and higher mortality. For mental health the results have been more varied. However, the mechanisms by which the various dimensions of socioeconomic circumstances are associated with different domains of health are not yet fully understood. This is related to a lack of studies tackling the interrelations and pathways between multiple dimensions of socioeconomic circumstances and domains of health. In particular, evidence from comparative studies of populations from different national contexts that consider the complexity of the causes of socioeconomic health inequalities is needed. The aim of this study was to examine the associations of multiple socioeconomic circumstances with physical and mental health, more specifically physical functioning and common mental disorders. This was done in a comparative setting of two cohorts of white-collar public sector employees, one from Finland and one from Britain. The study also sought to find explanations for the observed associations between economic difficulties and health by analysing the contribution of health behaviours, living arrangements and work-family conflicts. The survey data were derived from the Finnish Helsinki Health Study baseline surveys in 2000-2002 among the City of Helsinki employees aged 40-60 years, and from the fifth phase of the London-based Whitehall II study (1997-9) which is a prospective study of civil servants aged 35-55 years at the time of recruitment. The data collection in the two countries was harmonised to safeguard maximal comparability. Physical functioning was measured with the Short Form (SF-36) physical component summary and common mental disorders with the General Health Questionnaire (GHQ-12). Socioeconomic circumstances were parental education, childhood economic difficulties, own education, occupational class, household income, housing tenure, and current economic difficulties. Further explanatory factors were health behaviours, living arrangements and work-family conflicts. The main statistical method used was logistic regression analysis. Analyses were conducted separately for the two sexes and two cohorts. Childhood and current economic difficulties were associated with poorer physical functioning and common mental disorders generally in both cohorts and sexes. Conventional dimensions of socioeconomic circumstances i.e. education, occupational class and income were associated with physical functioning and mediated each other’s effects, but in different ways in the two cohorts: education was more important in Helsinki and occupational class in London. The associations of economic difficulties with health were partly explained by work-family conflicts and other socioeconomic circumstances in both cohorts and sexes. In conclusion, this study on two country-specific cohorts confirms that different dimensions of socioeconomic circumstances are related but not interchangeable. They are also somewhat differently associated with physical and mental domains of health. In addition to conventionally measured dimensions of past and present socioeconomic circumstances, economic difficulties should be taken into account in studies and attempts to reduce health inequalities. Further explanatory factors, particularly conflicts between work and family, should also be considered when aiming to reduce inequalities and maintain the health of employees.

Genotyping for genetic association studies: Methods and applications

In this thesis, two separate single nucleotide polymorphism (SNP) genotyping techniques were set up at the Finnish Genome Center, pooled genotyping was evaluated as a screening method for large-scale association studies, and finally, the former approaches were used to identify genetic factors predisposing to two distinct complex diseases by utilizing large epidemiological cohorts and also taking environmental factors into account. The first genotyping platform was based on traditional but improved restriction-fragment-length-polymorphism (RFLP) utilizing 384-microtiter well plates, multiplexing, small reaction volumes (5 µl), and automated genotype calling. We participated in the development of the second genotyping method, based on single nucleotide primer extension (SNuPeTM by Amersham Biosciences), by carrying out the alpha- and beta tests for the chemistry and the allele-calling software. Both techniques proved to be accurate, reliable, and suitable for projects with thousands of samples and tens of markers. Pooled genotyping (genotyping of pooled instead of individual DNA samples) was evaluated with Sequenom s MassArray MALDI-TOF, in addition to SNuPeTM and PCR-RFLP techniques. We used MassArray mainly as a point of comparison, because it is known to be well suited for pooled genotyping. All three methods were shown to be accurate, the standard deviations between measurements being 0.017 for the MassArray, 0.022 for the PCR-RFLP, and 0.026 for the SNuPeTM. The largest source of error in the process of pooled genotyping was shown to be the volumetric error, i.e., the preparation of pools. We also demonstrated that it would have been possible to narrow down the genetic locus underlying congenital chloride diarrhea (CLD), an autosomal recessive disorder, by using the pooling technique instead of genotyping individual samples. Although the approach seems to be well suited for traditional case-control studies, it is difficult to apply if any kind of stratification based on environmental factors is needed. Therefore we chose to continue with individual genotyping in the following association studies. Samples in the two separate large epidemiological cohorts were genotyped with the PCR-RFLP and SNuPeTM techniques. The first of these association studies concerned various pregnancy complications among 100,000 consecutive pregnancies in Finland, of which we genotyped 2292 patients and controls, in addition to a population sample of 644 blood donors, with 7 polymorphisms in the potentially thrombotic genes. In this thesis, the analysis of a sub-study of pregnancy-related venous thromboses was included. We showed that the impact of factor V Leiden polymorphism on pregnancy-related venous thrombosis, but not the other tested polymorphisms, was fairly large (odds ratio 11.6; 95% CI 3.6-33.6), and increased multiplicatively when combined with other risk factors such as obesity or advanced age. Owing to our study design, we were also able to estimate the risks at the population level. The second epidemiological cohort was the Helsinki Birth Cohort of men and women who were born during 1924-1933 in Helsinki. The aim was to identify genetic factors that might modify the well known link between small birth size and adult metabolic diseases, such as type 2 diabetes and impaired glucose tolerance. Among ~500 individuals with detailed birth measurements and current metabolic profile, we found that an insertion/deletion polymorphism of the angiotensin converting enzyme (ACE) gene was associated with the duration of gestation, and weight and length at birth. Interestingly, the ACE insertion allele was also associated with higher indices of insulin secretion (p=0.0004) in adult life, but only among individuals who were born small (those among the lowest third of birth weight). Likewise, low birth weight was associated with higher indices of insulin secretion (p=0.003), but only among carriers of the ACE insertion allele. The association with birth measurements was also found with a common haplotype of the glucocorticoid receptor (GR) gene. Furthermore, the association between short length at birth and adult impaired glucose tolerance was confined to carriers of this haplotype (p=0.007). These associations exemplify the interaction between environmental factors and genotype, which, possibly due to altered gene expression, predisposes to complex metabolic diseases. Indeed, we showed that the common GR gene haplotype associated with reduced mRNA expression in thymus of three individuals (p=0.0002).

New aspects of the diagnosis of Helicobacter pylori infection

Aims: Helicobacter pylori infection, although the prevalence is declining in Western world, is still responsible for several clinically important diseases. None of the diagnostic tests is perfect and in this study, the performance of three stool antigen tests was assessed. In areas of high H. pylori prevalence, the definition of patients with the greatest benefit from eradication therapy may be a problem; the role of duodenal gastric metaplasia in categorizing patients at risk for duodenal ulcer was evaluated in this respect. Whether persistent chronic inflammation and elevated H. pylori antibodies after successful eradication are associated with each other or with atrophic gastritis, a long term sequelae of H. pylori infection, were also studied. Patients and methods: The three stool antigen tests were assessed in pre- and post-eradication settings among 364 subjects in two studies as compared to the rapid urease test (RUT), histology, culture, the 13C-urea breath test (UBT) and enzyme immunoassay (EIA) based H. pylori serology. The association between duodenal gastric metaplasia with duodenal ulcer was evaluated in a retrospective study including 1054 patients gastroscopied due to clinical indications and 154 patients previously operated for duodenal ulcer. The extent of duodenal gastric metaplasia was assessed from histological specimens in different patient groups formed on the basis of gastroscopy findings and H. pylori infection. Chronic gastric inflammation (108 patients) and H. pylori antibodies and serum markers for atrophy (77 patients) were assessed in patients earlier treated for H. pylori. Results: Of the stool antigen tests studied, the monoclonal antibody-based EIA-test showed the highest sensitivity and specificity both in the pre-treatment setting (96.9% and 95.9%) and after therapy (96.9% and 97.8%). The polyclonal stool antigen test and the in-office test had at baseline a sensitivity of 91% and 94%, and a specificity of 96% and 89%, respectively and in a post-treatment setting, a sensitivity of 78% and 91%, and a specificity of 97%, respectively. Duodenal gastric metaplasia was strongly associated with H. pylori positive duodenal ulcer (odds ratio 42). Although common still five years after eradication, persistent chronic gastric inflammation (21%) and elevated H. pylori antibodies (33%) were neither associated with each other nor with atrophic gastritis. Conclusions: Current H. pylori infection can feasibly be diagnosed by a monoclonal antibody-based EIA test with the accuracy comparable to that of reference methods. The performance of the polyclonal test as compared to the monoclonal test was inferior especially in the post-treatment setting. The in-office test had a low specificity for primary diagnosis and hence positive test results should probably be confirmed with another test before eradication therapy is prescribed. The presence of widespread duodenal gastric metaplasia showed promising results in detecting patients who should be treated for H. pylori due to an increased risk of duodenal ulcer. If serology is used later on in patients with earlier successfully treated for H. pylori, it should be taken into account that H. pylori antibodies may persist elevated for years for unknown reason. However, this phenomenon was not found to be associated with persistent chronic inflammation or atrophic changes.

Silvicultural decisions based on simulation-optimization systems

Forest management is facing new challenges under climate change. By adjusting thinning regimes, conventional forest management can be adapted to various objectives of utilization of forest resources, such as wood quality, forest bioenergy, and carbon sequestration. This thesis aims to develop and apply a simulation-optimization system as a tool for an interdisciplinary understanding of the interactions between wood science, forest ecology, and forest economics. In this thesis, the OptiFor software was developed for forest resources management. The OptiFor simulation-optimization system integrated the process-based growth model PipeQual, wood quality models, biomass production and carbon emission models, as well as energy wood and commercial logging models into a single optimization model. Osyczka s direct and random search algorithm was employed to identify optimal values for a set of decision variables. The numerical studies in this thesis broadened our current knowledge and understanding of the relationships between wood science, forest ecology, and forest economics. The results for timber production show that optimal thinning regimes depend on site quality and initial stand characteristics. Taking wood properties into account, our results show that increasing the intensity of thinning resulted in lower wood density and shorter fibers. The addition of nutrients accelerated volume growth, but lowered wood quality for Norway spruce. Integrating energy wood harvesting into conventional forest management showed that conventional forest management without energy wood harvesting was still superior in sparse stands of Scots pine. Energy wood from pre-commercial thinning turned out to be optimal for dense stands. When carbon balance is taken into account, our results show that changing carbon assessment methods leads to very different optimal thinning regimes and average carbon stocks. Raising the carbon price resulted in longer rotations and a higher mean annual increment, as well as a significantly higher average carbon stock over the rotation.

Soil carbon modelling as a tool for carbon balance studies in forestry

Soils represent a remarkable stock of carbon, and forest soils are estimated to hold half of the global stock of soil carbon. Topical concern about the effects of climate change and forest management on soil carbon as well as practical reporting requirements set by climate conventions have created a need to assess soil carbon stock changes reliably and transparently. The large spatial variability of soil carbon commensurate with relatively slow changes in stocks hinders the assessment of soil carbon stocks and their changes by direct measurements. Models therefore widely serve to estimate carbon stocks and stock changes in soils. This dissertation aimed to develop the soil carbon model YASSO for upland forest soils. The model was aimed to take into account the most important processes controlling the decomposition in soils, yet remain simple enough to ensure its practical applicability in different applications. The model structure and assumptions were presented and the model parameters were defined with empirical measurements. The model was evaluated by studying the sensitivities of the model results to parameter values, by estimating the precision of the results with an uncertainty analysis, and by assessing the accuracy of the model by comparing the predictions against measured data and to the results of an alternative model. The model was applied to study the effects of intensified biomass extraction on the forest carbon balance and to estimate the effects of soil carbon deficit on net greenhouse gas emissions of energy use of forest residues. The model was also applied in an inventory based method to assess the national scale forest carbon balance for Finland’s forests from 1922 to 2004. YASSO managed to describe sufficiently the effects of both the variable litter and climatic conditions on decomposition. When combined with the stand models or other systems providing litter information, the dynamic approach of the model proved to be powerful for estimating changes in soil carbon stocks on different scales. The climate dependency of the model, the effects of nitrogen on decomposition and forest growth as well as the effects of soil texture on soil carbon stock dynamics are areas for development when considering the applicability of the model to different research questions, different land use types and wider geographic regions. Intensified biomass extraction affects soil carbon stocks, and these changes in stocks should be taken into account when considering the net effects of forest residue utilisation as energy. On a national scale, soil carbon stocks play an important role in forest carbon balances.

Urban energy fluxes in Helsinki and their high frequency spectral corrections

Inadvertent climate modification has led to an increase in urban temperatures compared to the surrounding rural area. The main reason for the temperature rise is the altered energy portioning of input net radiation to heat storage and sensible and latent heat fluxes in addition to the anthropogenic heat flux. The heat storage flux and anthropogenic heat flux have not yet been determined for Helsinki and they are not directly measurable. To the contrary, turbulent fluxes of sensible and latent heat in addition to net radiation can be measured, and the anthropogenic heat flux together with the heat storage flux can be solved as a residual. As a result, all inaccuracies in the determination of the energy balance components propagate to the residual term and special attention must be paid to the accurate determination of the components. One cause of error in the turbulent fluxes is the fluctuation attenuation at high frequencies which can be accounted for by high frequency spectral corrections. The aim of this study is twofold: to assess the relevance of high frequency corrections to water vapor fluxes and to assess the temporal variation of the energy fluxes. Turbulent fluxes of sensible and latent heat have been measured at SMEAR III station, Helsinki, since December 2005 using the eddy covariance technique. In addition, net radiation measurements have been ongoing since July 2007. The used calculation methods in this study consist of widely accepted eddy covariance data post processing methods in addition to Fourier and wavelet analysis. The high frequency spectral correction using the traditional transfer function method is highly dependent on relative humidity and has an 11% effect on the latent heat flux. This method is based on an assumption of spectral similarity which is shown not to be valid. A new correction method using wavelet analysis is thus initialized and it seems to account for the high frequency variation deficit. Anyhow, the resulting wavelet correction remains minimal in contrast to the traditional transfer function correction. The energy fluxes exhibit a behavior characteristic for urban environments: the energy input is channeled to sensible heat as latent heat flux is restricted by water availability. The monthly mean residual of the energy balance ranges from 30 Wm-2 in summer to -35 Wm-2 in winter meaning a heat storage to the ground during summer. Furthermore, the anthropogenic heat flux is approximated to be 50 Wm-2 during winter when residential heating is important.

Discovering hidden structures in molecular data using a Bayesian partition model approach

Advancements in the analysis techniques have led to a rapid accumulation of biological data in databases. Such data often are in the form of sequences of observations, examples including DNA sequences and amino acid sequences of proteins. The scale and quality of the data give promises of answering various biologically relevant questions in more detail than what has been possible before. For example, one may wish to identify areas in an amino acid sequence, which are important for the function of the corresponding protein, or investigate how characteristics on the level of DNA sequence affect the adaptation of a bacterial species to its environment. Many of the interesting questions are intimately associated with the understanding of the evolutionary relationships among the items under consideration. The aim of this work is to develop novel statistical models and computational techniques to meet with the challenge of deriving meaning from the increasing amounts of data. Our main concern is on modeling the evolutionary relationships based on the observed molecular data. We operate within a Bayesian statistical framework, which allows a probabilistic quantification of the uncertainties related to a particular solution. As the basis of our modeling approach we utilize a partition model, which is used to describe the structure of data by appropriately dividing the data items into clusters of related items. Generalizations and modifications of the partition model are developed and applied to various problems. Large-scale data sets provide also a computational challenge. The models used to describe the data must be realistic enough to capture the essential features of the current modeling task but, at the same time, simple enough to make it possible to carry out the inference in practice. The partition model fulfills these two requirements. The problem-specific features can be taken into account by modifying the prior probability distributions of the model parameters. The computational efficiency stems from the ability to integrate out the parameters of the partition model analytically, which enables the use of efficient stochastic search algorithms.