Bayesian statistical analysis of bacterial diversity

Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

Use of ecological information in urban planning

Urbanization leads to irreversible land-use change, which has ecological consequences such as the loss and fragmentation of green areas, and structural and functional changes in terrestrial and aquatic ecosystems. These consequences diminish ecosystem services important for human populations living in urban areas. All this results in a conflict situation: how to simultaneously meet the needs of city growth and the principles of sustainable development, and especially conserve important green areas within and around built-up areas? Urban planners and decisionmakers have an important role in this, since they must use the ecological information mainly from species and biotope inventories and biodiversity impact assessments in determining the conservation values of green areas. The main aim of this thesis was to study the use of ecological information in the urban land-use planning and decisionmaking process in the Helsinki Metropolitan Area, Finland. At first, the literature on ecological-social systems linkages related to urban planning was reviewed. Based on the review, a theoretical and conceptual framework for the research on Finnish urban setting was adapted. Secondly, factors determining the importance and effectiveness of incorporation of ecological information into the urban planning process, and the challenges related to the use of ecological information were studied. Thirdly, the importance and use of Local Ecological Knowledge in urban planning were investigated. Then, factors determining the consideration of urban green areas and related ecological information in political land-use decisionmaking were studied. Finally, in a case study illustrating the above considerations, the importance of urban stream ecosystems in the land-use planning was investigated. This thesis demonstrated that although there are several challenges in using ecological information effectively, it is considered as an increasingly important part of the basic information used in urban planning and decisionmaking process. The basic determinants for this are the recent changes in environmental legislation, but also the increasing appreciation of green areas and their conservation values by all the stakeholders. In addition, Local Ecological Knowledge in its several forms can be a source of ecological information for planners if incorporated effectively into the process. This study also showed that rare or endangered species and biotopes, and related ecological information receive priority in the urban planning process and usually pass through the decisionmaking system. Furthermore, the stream Rekolanoja case indicates that planners and residents see the value of urban stream ecosystem as increasingly important for the local health and social values, such as recreation and stress relief.

Effects of environmental variation on ecological and evolutionary dynamics

Environmental variation is a fact of life for all the species on earth: for any population of any particular species, the local environmental conditions are liable to vary in both time and space. In today's world, anthropogenic activity is causing habitat loss and fragmentation for many species, which may profoundly alter the characteristics of environmental variation in remaining habitat. Previous research indicates that, as habitat is lost, the spatial configuration of remaining habitat will increasingly affect the dynamics by which populations are governed. Through the use of mathematical models, this thesis asks how environmental variation interacts with species properties to influence population dynamics, local adaptation, and dispersal evolution. More specifically, we couple continuous-time continuous-space stochastic population dynamic models to landscape models. We manipulate environmental variation via parameters such as mean patch size, patch density, and patch longevity. Among other findings, we show that a mixture of high and low quality habitat is commonly better for a population than uniformly mediocre habitat. This conclusion is justified by purely ecological arguments, yet the positive effects of landscape heterogeneity may be enhanced further by local adaptation, and by the evolution of short-ranged dispersal. The predicted evolutionary responses to environmental variation are complex, however, since they involve numerous conflicting factors. We discuss why the species that have high levels of local adaptation within their ranges may not be the same species that benefit from local adaptation during range expansion. We show how habitat loss can lead to either increased or decreased selection for dispersal depending on the type of habitat and the manner in which it is lost. To study the models, we develop a recent analytical method, Perturbation expansion, to enable the incorporation of environmental variation. Within this context, we use two methods to address evolutionary dynamics: Adaptive dynamics, which assumes mutations occur infrequently so that the ecological and evolutionary timescales can be separated, and via Genotype distributions, which assume mutations are more frequent. The two approaches generally lead to similar predictions yet, exceptionally, we show how the evolutionary response of dispersal behaviour to habitat turnover may qualitatively depend on the mutation rate.

Communities of wood-inhabiting fungi : Ecological requirements and responses to forest management and fragmentation

Despite much research on forest biodiversity in Fennoscandia, the exact mechanisms of species declines in dead-wood dependent fungi are still poorly understood. In particular, there is only limited information on why certain fungal species have responded negatively to habitat loss and fragmentation, while others have not. Understanding the mechanisms behind species declines would be essential for the design and development of ecologically effective and scientifically informed conservation measures, and management practices that would promote biodiversity in production forests. In this thesis I study the ecology of polypores and their responses to forest management, with a particular focus on why some species have declined more than others. The data considered in the thesis comprise altogether 98,318 dead-wood objects, with 43,085 observations of 174 fungal species. Out of these, 1,964 observations represent 58 red-listed species. The data were collected from 496 sites, including woodland key habitats, clear-cuts with retention trees, mature managed forests, and natural or natural-like forests in southern Finland and Russian Karelia. I show that the most relevant way of measuring resource availability can differ to a great extent between species seemingly sharing the same resources. It is thus critical to measure the availability of resources in a way that takes into account the ecological requirements of the species. The results show that connectivity at the local, landscape and regional scales is important especially for the highly specialized species, many of which are also red-listed. Habitat loss and fragmentation affect not only species diversity but also the relative abundances of the species and, consequently, species interactions and fungal successional pathways. Changes in species distributions and abundances are likely to affect the food chains in which wood-inhabiting fungi are involved, and thus the functioning of the whole forest ecosystem. The findings of my thesis highlight the importance of protecting well-connected, large and high-quality forest areas to maintain forest biodiversity. Small habitat patches distributed across the landscape are likely to contribute only marginally to protection of red-listed species, especially if habitat quality is not substantially higher than in ordinary managed forest, as is the case with woodland key habitats. Key habitats might supplement the forest protection network if they were delineated larger and if harvesting of individual trees was prohibited in them. Taking the landscape perspective into account in the design and development of conservation measures is critical while striving to halt the decline of forest biodiversity in an ecologically effective manner.

Ecological impacts of Phlebiopsis gigantea biocontrol treatment against Heterobasidion spp. as revealed by fungal community profiling and population analyses

Wood decay fungi belonging to the species complex Heterobasidion annosum sensu lato are among the most common and economically important species causing root rot and stem decay in conifers of the northern temperate regions. New infections by these pathogens can be suppressed by tree stump treatments using chemical or biological control agents. In Finland, the corticiaceous fungus Phlebiopsis gigantea has been formulated into a commercial biocontrol agent called Rotstop (Verdera Ltd.). This thesis addresses the ecological impacts of Rotstop biocontrol treatment on the mycoflora of conifer stumps. Locally, fungal communities within Rotstop-treated and untreated stumps were analyzed using a novel method based on DGGE profiling of small subunit ribosomal DNA fragments amplified directly from wood samples. Population analyses for P. gigantea and H. annosum s.l. were conducted to evaluate possible risks associated with local and/or global distribution of the Rotstop strain. Based on molecular community profiling by DGGE, we detected a few individual wood-inhabiting fungal species (OTUs) that seemed to have suffered or benefited from the Rotstop biocontrol treatment. The DGGE analyses also revealed fungal diversity not retrieved by cultivation and some fungal sequence types untypical for decomposing conifer wood. However, statistical analysis of DGGE community profiles obtained from Rotstop-treated and untreated conifer stumps revealed that the Rotstop treatment had not caused a statistically significant reduction in the species diversity of wood-inhabiting fungi within our experimental forest plots. Locally, ISSR genotyping of cultured P. gigantea strains showed that the Rotstop biocontrol strain was capable of surviving up to six years within treated Norway spruce stumps, while in Scots pine stumps it was sooner replaced by successor fungal species. In addition, the spread of resident P. gigantea strains into Rotstop-treated forest stands seemed effective in preventing the formation of genetically monomorphic populations in the short run. On a global scale, we detected a considerable level of genetic differentiation between the interfertile European and North American populations of P. gigantea. These results strongly suggest that local biocontrol strains should be used in order to prevent global spread of P. gigantea and hybrid formation between geographically isolated populations. The population analysis for H. annosum s.l. revealed a collection of Chinese fungal strains that showed a high degree of laboratory fertility with three different allopatric H. annosum s.l. taxa. However, based on the molecular markers, the Chinese strains could be clearly affiliated with the H. parviporum taxonomical cluster, which thus appears to have a continuous distribution range from Europe through southern Siberia to northern China. Keywords: Rotstop, wood decay, DGGE, ISSR fingerprinting, ribosomal DNA

The role of productivity in the ecological and evolutionary dynamics of predator-prey interaction

Productivity is predicted to drive the ecological and evolutionary dynamics of predator-prey interaction through changes in resource allocation between different traits. However, resources are seldom constantly available and thus temporal variation in productivity could have considerable effect on the species' potential to evolve. To study this, three long-term microbial laboratory experiments were established where Serratia marcescens prey bacteria was exposed to predation of protist Tetrahymena thermophila in different prey resource environments. The consequences of prey resource availability for the ecological properties of the predator-prey system, such as trophic dynamics, stability, and virulence, were determined. The evolutionary changes in species traits and prey genetic diversity were measured. The prey defence evolved stronger in high productivity environment. Increased allocation to defence incurred cost in terms of reduced prey resource use ability, which probably constrained prey evolution by increasing the effect of resource competition. However, the magnitude of this trade-off diminished when measured in high resource concentrations. Predation selected for white, non-pigmented, highly defensive prey clones that produced predation resistant biofilm. The biofilm defence was also potentially accompanied with cytotoxicity for predators and could have been traded off with high motility. Evidence for the evolution of predators was also found in one experiment suggesting that co-evolutionary dynamics could affect the evolution and ecology of predator-prey interaction. Temporal variation in resource availability increased variation in predator densities leading to temporally fluctuating selection for prey defences and resource use ability. Temporal variation in resource availability was also able to constrain prey evolution when the allocation to defence incurred high cost. However, when the magnitude of prey trade-off was small and the resource turnover was periodically high, temporal variation facilitated the formation of predator resistant biofilm. The evolution of prey defence constrained the transfer of energy from basal to higher trophic levels, decreasing the strength of top-down regulation on prey community. Predation and temporal variation in productivity decreased the stability of populations and prey traits in general. However, predation-induced destabilization was less pronounced in the high productivity environment where the evolution of prey defence was stronger. In addition, evolution of prey defence weakened the environmental variation induced destabilization of predator population dynamics. Moreover, protozoan predation decreased the S. marcescens virulence in the insect host moth (Parasemia plantaginis) suggesting that species interactions outside the context of host-pathogen relationship could be important indirect drivers for the evolution of pathogenesis. This thesis demonstrates that rapid evolution can affect various ecological properties of predator-prey interaction. The effect of evolution on the ecological dynamics depended on the productivity of the environment, being most evident in the constant environments with high productivity.

A systematic-ecological approach to Baltic Sea ice studies of algae and protists

The seasonal occurrence of sea ice that annually covers almost half the Baltic Sea area provides a unique habitat for halo- and cold temperature-tolerant extremophiles. Baltic Sea ice biology has more than 100 years of tradition that began with the floristic observation of species by the early pioneers using light microscopic techniques that were the only thing available at the time. Since the discovery of life within sea ice, more technologies have become available for taxonomy. Electron microscopy and genetic evidence have been used to identify sea ice biota revealing increased numbers of taxa. Meanwhile ecologists have used light microscopic cell enumeration in addition to the chemical and physical properties of sea ice in attempts to explain the food web structure of sea ice and its functions. Thus, during the Baltic winter, the sea ice hosts more abundant and diverse microbial communities than the water column beneath it. These communities are typically dominated by autotrophic diatoms together with a diverse assortment of dinoflagellates, auto- and heterotrophic flagellates, ciliates, metazoan rotifers and bacteria, which are mostly responsible for the recycling of nutrients. This thesis comprises ecological and systematic studies. In addition to the results of the previous studies carried out on landfast ice, the data presented here provide new insight into the spatial distribution of pelagial sea ice, which has remained largely unexplored. The studies reveal spatial heterogeneity in the pelagial sea ice of the Gulf of Bothnia. There were mismatches in chlorophyll-a concentrations and in photosynthetic efficiencies of the communities studied. The temporal succession was followed and experimental studies performed investigating the community responses towards increased or decreased light in landfast ice in the Gulf of Finland. The systematic studies carried out with established dinoflagellate cultures revealed a new resting cyst belonging to common sea ice dinoflagellate, Scrippsiella hangoei (Schiller) Larsen 1995. The cyst can be used to explain the overwintering of this species during prolonged periods of darkness. The dissimilarities and similarities in the material isolated from the sea ice called for description of a new subspecies Heterocapsa arctica ssp. frigida. The cells obtained in the cultured material were unlike those of the previously described species, necessitating description of ssp. frigida. As a result of its own unique habitus, the subspecies had been noted by Finnish taxonomists during the past three decades and thus its annual occurrence and geographical distribution in the Baltic Sea. This illustrates how combining ecology and systematics increases our understanding of organisms.

The Emerging Phenotype: Ecological Genetics of Color, Form and Sex in the Common Frog

One of the main aims of evolutionary biology is to explain why organisms vary phenotypically as they do. Proximately, this variation arises from genetic differences and from environmental influences, the latter of which is referred to as phenotypic plasticity. Phenotypic plasticity is thus a central concept in evolutionary biology, and understanding its relative importance in causing the phenotypic variation and differentiation is important, for instance in anticipating the consequences of human induced environmental changes. The aim of this thesis was to study geographic variation and local adaptation, as well as sex ratios and environmental sex reversal, in the common frog (Rana temporaria). These themes cover three different aspects of phenotypic plasticity, which emerges as the central concept for the thesis. The first two chapters address geographic variation and local adaptation in two potentially thermally adaptive traits, namely the degree of melanism and the relative leg length. The results show that although there is an increasing latitudinal trend in the degree of melanism in wild populations across Scandinavian Peninsula, this cline has no direct genetic basis and is thus environmentally induced. The second chapter demonstrates that although there is no linear, latitudinally ordered phenotypic trend in relative leg length that would be expected under Allen s rule an ecogeographical rule linking extremity length to climatic conditions there seems to be such a trend at the genetic level, hidden under environmental effects. The first two chapters thus view phenotypic plasticity through its ecological role and evolution, and demonstrate that it can both give rise to phenotypic variation and hide evolutionary patterns in studies that focus solely on phenotypes. The last three chapters relate to phenotypic plasticity through its ecological and evolutionary role in sex determination, and consequent effects on population sex ratio, genetic recombination and the evolution of sex chromosomes. The results show that while sex ratios are strongly female biased and there is evidence of environmental sex reversals, these reversals are unlikely to have caused the sex ratio skew, at least directly. The results demonstrate that environmental sex reversal can have an effect on the evolution of sex chromosomes, as the recombination patterns between them seem to be controlled by phenotypic, rather than genetic, sex. This potentially allows Y chromosomes to recombine, lending support for the recent hypothesis suggesting that sex-reversal may play an important role on the rejuvenation of Y chromosomes.

Ecological consequences of genetic modifications - an invasion analysis approach

Biological invasions are considered as one of the greatest threats to biodiversity, as they may lead to disruption and homogenization of natural communities, and in the worst case, to native species extinctions. The introduction of gene modified organisms (GMOs) to agricultural, fisheries and forestry practices brings them into contact with natural populations. GMOs may appear as new invasive species if they are able to (1) invade into natural habitats or (2) hybridize with their wild relatives. The benefits of GMOs, such as increased yield or decreased use of insecticides or herbicides in cultivation, may thus be reduced due the potential risks they may cause. A careful ecological risk analysis therefore has to precede any responsible GMO introduction. In this thesis I study ecological invasion in relation to GMOs, and what kind of consequences invasion may have in natural populations. A set of theoretical models that combine life-history evolution, population dynamics, and population genetics were developed for the hazard identification part of ecological risks assessment of GMOs. In addition, the potential benefits of GMOs in management of an invasive pest were analyzed. In the first study I showed that a population that is fluctuating due to scramble-type density dependence (due to, e.g., nutrient competition in plants) may be invaded by a population that is relatively more limited by a resource (e.g., light in plants) that is a cause of contest-type density dependence. This result emphasises the higher risk of invasion in unstable environments. The next two studies focused on escape of a growth hormone (GH) transgenic fish into a natural population. The results showed that previous models may have given too pessimistic a view of the so called Trojan gene -effect, where the invading genotype is harmful for the population as a whole. The previously suggested population extinctions did not occur in my studies, since the changes in mating preferences caused by the GH-fish were be ameliorated by decreased level of competition. The GH-invaders may also have to exceed a threshold density before invasion can be successful. I also showed that the prevalence of mature parr (aka. sneaker) strategy among GH-fish may have clear effect on invasion outcome. The fourth study assessed the risks and developed methods against the invasion of the Colorado Potato Beetle (CPB, Leptinotarsa decemlineata). I showed that the eradication of CPB is most important for the prevention of their establishment, but the cultivation of transgenic Bt-potato could also be effective. In general, my results emphasise that invasion of transgenic species or genotypes to be possible under certain realistic conditions and resulting in competitive exclusion, population decline through outbreeding depression and genotypic displacement of native species. Ecological risk assessment should regard the decline and displacement of the wild genotype by an introduced one as a consequence that is as serious as the population extinction. It will also be crucial to take into account different kinds of behavioural differences among species when assessing the possible hazards that GMOs may cause if escaped. The benefits found of GMO crops effectiveness in pest management may also be too optimistic since CPB may evolve resistance to Bt-toxin. The models in this thesis could be further applied in case specific risk assessment of GMOs by supplementing them with detailed data of the species biology, the effect of the transgene introduced to the species, and also the characteristics of the populations or the environments in the risk of being invaded.