Modeling ecological and evolutionary processes in spatially structured populations

Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

Habitat use and population dynamics of brown bears (Ursus arctos) in Scandinavia

Large carnivore populations are currently recovering from past extirpation efforts and expanding back into their original habitats. At the same time human activities have resulted in very few wilderness areas left with suitable habitats and size large enough to maintain populations of large carnivores without human contact. Consequently the long-term future of large carnivores depends on their successful integration into landscapes where humans live. Thus, understanding their behaviour and interaction with surrounding habitats is of utmost importance in the development of management strategies for large carnivores. This applies also to brown bears (Ursus arctos) that were almost exterminated from Scandinavia and Finland at the turn of the century, but are now expanding their range with the current population estimates being approximately 2600 bears in Scandinavia and 840 in Finland. This thesis focuses on the large-scale habitat use and population dynamics of brown bears in Scandinavia with the objective to develop modelling approaches that support the management of bear populations. Habitat analysis shows that bear home ranges occur mainly in forested areas with a low level of human influence relative to surrounding areas. Habitat modelling based on these findings allows identification and quantification of the potentially suitable areas for bears in Scandinavia. Additionally, this thesis presents novel improvements to home range estimation that enable realistic estimates of the effective area required for the bears to establish a home range. This is achieved through fitting to the radio-tracking data to establish the amount of temporal autocorrelation and the proportion of time spent in different habitat types. Together these form a basis for the landscape-level management of the expanding population. Successful management of bears requires also assessment of the consequences of harvest on the population viability. An individual-based simulation model, accounting for the sexually selected infanticide, was used to investigate the possibility of increasing the harvest using different hunting strategies, such as trophy harvest of males. The results indicated that the population can sustain twice the current harvest rate. However, harvest should be changed gradually while carefully monitoring the population growth as some effects of increased harvest may manifest themselves only after a time-delay. The results and methodological improvements in this thesis can be applied to the Finnish bear population and to other large carnivores. They provide grounds for the further development of spatially-realistic management-oriented models of brow bear dynamics that can make projections of the future distribution of bears while accounting for the development of human activities.

SU-8-Based Microchips for Capillary Electrophoresis and Electrospray Ionization Mass Spectrometry

Miniaturization of analytical instrumentation is attracting growing interest in response to the explosive demand for rapid, yet sensitive analytical methods and low-cost, highly automated instruments for pharmaceutical and bioanalyses and environmental monitoring. Microfabrication technology in particular, has enabled fabrication of low-cost microdevices with a high degree of integrated functions, such as sample preparation, chemical reaction, separation, and detection, on a single microchip. These miniaturized total chemical analysis systems (microTAS or lab-on-a-chip) can also be arrayed for parallel analyses in order to accelerate the sample throughput. Other motivations include reduced sample consumption and waste production as well as increased speed of analysis. One of the most promising hyphenated techniques in analytical chemistry is the combination of a microfluidic separation chip and mass spectrometer (MS). In this work, the emerging polymer microfabrication techniques, ultraviolet lithography in particular, were exploited to develop a capillary electrophoresis (CE) separation chip which incorporates a monolithically integrated electrospray ionization (ESI) emitter for efficient coupling with MS. An epoxy photoresist SU-8 was adopted as structural material and characterized with respect to its physicochemical properties relevant to chip-based CE and ESI/MS, namely surface charge, surface interactions, heat transfer, and solvent compatibility. As a result, SU-8 was found to be a favorable material to substitute for the more commonly used glass and silicon in microfluidic applications. In addition, an infrared (IR) thermography was introduced as direct, non-intrusive method to examine the heat transfer and thermal gradients during microchip-CE. The IR data was validated through numerical modeling. The analytical performance of SU-8-based microchips was established for qualitative and quantitative CE-ESI/MS analysis of small drug compounds, peptides, and proteins. The CE separation efficiency was found to be similar to that of commercial glass microchips and conventional CE systems. Typical analysis times were only 30-90 s per sample indicating feasibility for high-throughput analysis. Moreover, a mass detection limit at the low-attomole level, as low as 10E+5 molecules, was achieved utilizing MS detection. The SU-8 microchips developed in this work could also be mass produced at low cost and with nearly identical performance from chip to chip. Until this work, the attempts to combine CE separation with ESI in a chip-based system, amenable to batch fabrication and capable of high, reproducible analytical performance, have not been successful. Thus, the CE-ESI chip developed in this work is a substantial step toward lab-on-a-chip technology.

Univariate, bivariate, and multivariate methods in corpus-based lexicography : A study of synonymy

In this dissertation, I present an overall methodological framework for studying linguistic alternations, focusing specifically on lexical variation in denoting a single meaning, that is, synonymy. As the practical example, I employ the synonymous set of the four most common Finnish verbs denoting THINK, namely ajatella, miettiä, pohtia and harkita ‘think, reflect, ponder, consider’. As a continuation to previous work, I describe in considerable detail the extension of statistical methods from dichotomous linguistic settings (e.g., Gries 2003; Bresnan et al. 2007) to polytomous ones, that is, concerning more than two possible alternative outcomes. The applied statistical methods are arranged into a succession of stages with increasing complexity, proceeding from univariate via bivariate to multivariate techniques in the end. As the central multivariate method, I argue for the use of polytomous logistic regression and demonstrate its practical implementation to the studied phenomenon, thus extending the work by Bresnan et al. (2007), who applied simple (binary) logistic regression to a dichotomous structural alternation in English. The results of the various statistical analyses confirm that a wide range of contextual features across different categories are indeed associated with the use and selection of the selected think lexemes; however, a substantial part of these features are not exemplified in current Finnish lexicographical descriptions. The multivariate analysis results indicate that the semantic classifications of syntactic argument types are on the average the most distinctive feature category, followed by overall semantic characterizations of the verb chains, and then syntactic argument types alone, with morphological features pertaining to the verb chain and extra-linguistic features relegated to the last position. In terms of overall performance of the multivariate analysis and modeling, the prediction accuracy seems to reach a ceiling at a Recall rate of roughly two-thirds of the sentences in the research corpus. The analysis of these results suggests a limit to what can be explained and determined within the immediate sentential context and applying the conventional descriptive and analytical apparatus based on currently available linguistic theories and models. The results also support Bresnan’s (2007) and others’ (e.g., Bod et al. 2003) probabilistic view of the relationship between linguistic usage and the underlying linguistic system, in which only a minority of linguistic choices are categorical, given the known context – represented as a feature cluster – that can be analytically grasped and identified. Instead, most contexts exhibit degrees of variation as to their outcomes, resulting in proportionate choices over longer stretches of usage in texts or speech.

Do UNESCO Schools in Finland Prepare Their Students for the Future? : A Study of Their School-based Curriculums

The purpose of the research was to study how Finnish lower-stage schools participating in the international network of UNESCO schools, also called the Associated Schools Project (ASP), prepare their students for the future at the level of their school-based curriculums. In the research, the future trends were discussed, and the importance of their consideration in educational practice was explained from a global viewpoint: Based on the examination of today's problematic world state, and development trends characterized by globalization, the challenges and demands set for schooling and education in the future were discussed. Understanding the significance of an individual's action and responsibility was considered to be the central resource for building a more just and sustainable future. The study was grounded on a theoretical model developed by the researcher, which combined the models of Dalin & Rust (1996) and UNESCO (Delors et al. 1996) about future-oriented learning. The model consists of four basic elements of curriculum; "Nature", "Culture", "Myself", and "Others", and four dimension of learning; "Learning to know", "Learning to do", "Learning to live together" and "Learning to be". The model represents the holistic aspect of educational theory, and its aim is to maintain a balance between its different components. The research material composed of ten lower-stage UNESCO schools' school-based curriculums. They were analyzed using the theoretical model by the methology of content analysis. The research results were notably consistent between the different schools. They showed cultural learning and learning concerned with "myself" to be clearly more emphasized than learning referring to nature and other people. In addition, they reflected the central position of subjects, knowledge and skills, thus leaving the development of the pupils' personalities, and particularly learning concerned with living with other people, in a marginal role. The question about whether the schools prepare for the future interms of their curriculums, was discussed in the light of the results. The research offered a way and a model to approach the relationship between education and the future, and to evaluate schools' future-orientation. Based on the results, the schools are suggested to lay more stress on learning concerned with nature and other people, and focus more on developing the mental capasities of their pupils and competencies they need for living with other people. Above all, what the present societies require of schools is education which produces balanced and broadly aware human beings who have the mental strength to face the challenges of the future and abilities to direct it along the lines they desire. Keywords: future, curriculum, content analysis

Leisure activities and obesity in adolescence : a follow-up study among twins

The aims of this dissertation were 1) to investigate associations of weight status of adolescents with leisure activities, and computer and cell phone use, and 2) to investigate environmental and genetic influences on body mass index (BMI) during adolescence. Finnish twins born in 1983–1987 responded to postal questionnaires at the ages of 11-12 (5184 participants), 14 (4643 participants), and 17 years (4168 participants). Information was obtained on weight and height, leisure activities including television viewing, video viewing, computer games, listening to music, board games, musical instrument playing, reading, arts, crafts, socializing, clubs, sports, and outdoor activities, as well as computer and cell phone use. Activity patterns were studied using latent class analysis. The relationship between leisure activities and weight status was investigated using logistic and linear regression. Genetic and environmental effects on BMI were studied using twin modeling. Of individual leisure activities, sports were associated with decreased overweight risk among boys in both cross-sectional and longitudinal analyses, but among girls only cross-sectionally. Many sedentary leisure activities, such as video viewing (boys/girls), arts (boys), listening to music (boys), crafts (girls), and board games (girls), had positive associations with being overweight. Computer use was associated with a higher prevalence of overweight in cross-sectional analyses. However, musical instrument playing, commonly considered as a sedentary activity, was associated with a decreased overweight risk among boys. Four patterns of leisure activities were found: ‘Active and sociable’, ‘Active but less sociable’, ‘Passive but sociable’, and ‘Passive and solitary’. The prevalence of overweight was generally highest among the ‘Passive and solitary’ adolescents. Overall, leisure activity patterns did not predict overweight risk later in adolescence. An exception were 14-year-old ‘Passive and solitary’ girls who had the greatest risk of becoming overweight by 17 years of age. Heritability of BMI was high (0.58-0.83). Common environmental factors shared by family-members affected the BMI at 11-12 and 14 years but their effect had disappeared by 17 years of age. Additive genetic factors explained 90-96% of the BMI stability across adolescence. Genetic correlations across adolescence were high, which suggests similar genetic effects on BMI throughout adolescence, while unique environmental effects on BMI appeared to vary. These findings suggest that family-based interventions hold promise for obesity prevention into early and middle adolescence, but that later in adolescence obesity prevention should focus on individuals. A useful target could be adolescents' leisure time, and our findings highlight the importance of versatility in leisure activities.

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.

Genetic and environmental influences on human responses to odors

Olfaction, the sense of smell, has many important functions in humans. Human responses to odors show substantial individual variation. Olfactory receptor genes have been identified and other genes may also influence olfaction. However, the proportion of phenotypic variation in odor response due to genetic variation remains largely unknown. Little is also known about which genes modify specific responses to odors. This study aimed to elucidate genetic and environmental influences on human responses to odors. Individuals from Finnish families (n=146) and Australian (n=413), British (n=163), Danish (n=336), and Finnish (n=399) twins rated intensity and pleasantness of a set of 12 (families) or 6 (twins) odors and tried to identify the odors. In addition, the participants rated their own sense of smell and annoyance experienced with different environmental odors. The odor stimuli of a commercial smell test (The Brief Smell Identification Test; banana, chocolate, cinnamon, gasoline, lemon, onion, paint thinner, pineapple, rose, smoke, soap, and turpentine) were presented in the family study. Based on the results of the family study and a literature survey, a new set of odor stimuli (androstenone, chocolate, cinnamon, isovaleric acid, lemon, and turpentine) was designed for the twin studies. In the family sample, heritabilities of the traits were estimated and underlying genomic regions were searched using a genome-wide linkage scan. In the pooled twin sample, variation in the measured traits was decomposed into genetic and environmental components using quantitative genetic modeling. In addition, associations between nongenetic factors (e.g., sex, age, and smoking) and olfactory-related traits were explored. Suggestive evidence for a genetic linkage for pleasantness of cinnamon at a locus on chromosome 4q32.3 emerged from the family sample. High heritability for the pleasantness of cinnamon was found in the family but not the twin study. Heritability of perceived intensity of androstenone odor was determined to be ~30% in the twin sample. A strong genetic correlation between perceived intensity and pleasantness of androstenone, in the absence of any environmental correlation, indicated that only the genetic correlation explained the phenotypic correlation between the traits (r=-0.27) and that the traits were influenced by an overlapping set of genes. Self-rated olfactory function appeared to reflect the odor annoyance experienced rather than actual olfactory acuity or genetic involvement. Results from nongenetic analyses supported the speculated superiority of females' olfactory abilities, the age-related diminishing of olfactory acuity, and the influences of experience-dependent factors on odor responses. This was the first study to estimate heritabilities and perform linkage screens for individual odors. A genetic effect was detected for only a few responses to specific odors, suggesting the predominance of environmental effects in odor perceptions.

The white-rot fungi Phlebia radiata and Dichomitus squalens in wood-based cultures: expression of laccases, lignin peroxidases, and oxalate decarboxylase

Basidiomycetous white-rot fungi are the only organisms that can efficiently decompose all the components of wood. Moreover, white-rot fungi possess the ability to mineralize recalcitrant lignin polymer with their extracellular, oxidative lignin-modifying enzymes (LMEs), i.e. laccase, lignin peroxidase (LiP), manganese peroxidase (MnP), and versatile peroxidase (VP). Within one white-rot fungal species LMEs are typically present as several isozymes encoded by multiple genes. This study focused on two effi cient lignin-degrading white-rot fungal species, Phlebia radiata and Dichomitus squalens. Molecular level knowledge of the LMEs of the Finnish isolate P. radiata FBCC43 (79, ATCC 64658) was complemented with cloning and characterization of a new laccase (Pr-lac2), two new LiP-encoding genes (Pr-lip1, Pr-lip4), and Pr-lip3 gene that has been previously described only at cDNAlevel. Also, two laccase-encoding genes (Ds-lac3, Ds-lac4) of D. squalens were cloned and characterized for the first time. Phylogenetic analysis revealed close evolutionary relationships between the P. radiata LiP isozymes. Distinct protein phylogeny for both P. radiata and D. squalens laccases suggested different physiological functions for the corresponding enzymes. Supplementation of P. radiata liquid culture medium with excess Cu2+ notably increased laccase activity and good fungal growth was achieved in complex medium rich with organic nitrogen. Wood is the natural substrate of lignin-degrading white-rot fungi, supporting production of enzymes and metabolites needed for fungal growth and the breakdown of lignocellulose. In this work, emphasis was on solid-state wood or wood-containing cultures that mimic the natural growth conditions of white-rot fungi. Transcript analyses showed that wood promoted expression of all the presently known LME-encoding genes of P. radiata and laccase-encoding genes of D. squalens. Expression of the studied individual LME-encoding genes of P. radiata and D. squalens was unequal in transcript quantities and apparently time-dependent, thus suggesting the importance of several distinct LMEs within one fungal species. In addition to LMEs, white-rot fungi secrete other compounds that are important in decomposition of wood and lignin. One of these compounds is oxalic acid, which is a common metabolite of wood-rotting fungi. Fungi produce also oxalic-acid degrading enzymes of which the most widespread is oxalate decarboxylase (ODC). However, the role of ODC in fungi is still ambiguous with propositions from regulation of intra and extracellular oxalic acid levels to a function in primary growth and concomitant production of ATP. In this study, intracellular ODC activity was detected in four white-rot fungal species, and D. squalens showed the highest ODC activity upon exposure to oxalic acid. Oxalic acid was the most common organic acid secreted by the ODC-positive white-rot fungi and the only organic acid detected in wood cultures. The ODC-encoding gene Ds-odc was cloned from two strains of D. squalens showing the first characterization of an odc-gene from a white-rot polypore species. Biochemical properties of the D. squalens ODC resembled those described for other basidiomycete ODCs. However, the translated amino acid sequence of Ds-odc has a novel N-terminal primary structure with a repetitive Ala-Ser-rich region of ca 60 amino acid residues in length. Expression of the Ds-odc transcripts suggested a constitutive metabolic role for the corresponding ODC enzyme. According to the results, it is proposed that ODC may have an essential implication for the growth and basic metabolism of wood-decaying fungi.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Gene flow from transgenic plant populations: models and applications for risk assessment

The future use of genetically modified (GM) plants in food, feed and biomass production requires a careful consideration of possible risks related to the unintended spread of trangenes into new habitats. This may occur via introgression of the transgene to conventional genotypes, due to cross-pollination, and via the invasion of GM plants to new habitats. Assessment of possible environmental impacts of GM plants requires estimation of the level of gene flow from a GM population. Furthermore, management measures for reducing gene flow from GM populations are needed in order to prevent possible unwanted effects of transgenes on ecosystems. This work develops modeling tools for estimating gene flow from GM plant populations in boreal environments and for investigating the mechanisms of the gene flow process. To describe spatial dimensions of the gene flow, dispersal models are developed for the local and regional scale spread of pollen grains and seeds, with special emphasis on wind dispersal. This study provides tools for describing cross-pollination between GM and conventional populations and for estimating the levels of transgenic contamination of the conventional crops. For perennial populations, a modeling framework describing the dynamics of plants and genotypes is developed, in order to estimate the gene flow process over a sequence of years. The dispersal of airborne pollen and seeds cannot be easily controlled, and small amounts of these particles are likely to disperse over long distances. Wind dispersal processes are highly stochastic due to variation in atmospheric conditions, so that there may be considerable variation between individual dispersal patterns. This, in turn, is reflected to the large amount of variation in annual levels of cross-pollination between GM and conventional populations. Even though land-use practices have effects on the average levels of cross-pollination between GM and conventional fields, the level of transgenic contamination of a conventional crop remains highly stochastic. The demographic effects of a transgene have impacts on the establishment of trangenic plants amongst conventional genotypes of the same species. If the transgene gives a plant a considerable fitness advantage in comparison to conventional genotypes, the spread of transgenes to conventional population can be strongly increased. In such cases, dominance of the transgene considerably increases gene flow from GM to conventional populations, due to the enhanced fitness of heterozygous hybrids. The fitness of GM plants in conventional populations can be reduced by linking the selectively favoured primary transgene to a disfavoured mitigation transgene. Recombination between these transgenes is a major risk related to this technique, especially because it tends to take place amongst the conventional genotypes and thus promotes the establishment of invasive transgenic plants in conventional populations.