Phytoplankton ecology of subarctic lakes in Finnish Lapland

Climate is warming and it is especially seen in arctic areas, where the warming trend is expected to be greatest. Arctic freshwater ecosystems, which are a very characteristic feature of the arctic landscape, are especially sensitive to climate change. They could be used as early warning systems, but more information about the ecosystem functioning and responses are needed for proper interpretation of the observations. Phytoplankton species and assemblages could be especially suitable for climate-related studies, since they have short generation times and react rapidly to changes in the environment. In addition, phytoplankton provides a good tool for lake classifications, since different species have different requirements and tolerance ranges for various environmental factors. The use of biological indicators is especially useful in arctic areas, were many of the chemical factors commonly fall under the detection limit and therefore do not provide much information about the environment. This work brings new information about species distribution and dynamics of arctic freshwater phytoplankton in relation to environmental factors. The phytoplankton of lakes in Finnish Lapland and other European high-altitude or high-latitude areas were compared. Most lakes were oligotrophic and dominated by flagellated species belonging to chrysophytes, cryptophytes and dinoflagellates. In Finnish Lapland cryptophytes were of less importance, whereas desmids had high species richness in many of the lakes. In Pan-European scale, geographical and catchment-related factors were explaining most of the differences in species distributions between different districts, whereas lake water chemistry (especially conductivity, SiO2 and pH) was most important regionally. Seasonal and interannual variation of phytoplankton was studied in subarctic Lake Saanajärvi. Characteristic phytoplankton species in this oligotrophic, dimictic lake belonged mainly to chrysophytes and diatoms. The maximum phytoplankton biomass in Lake Saanajärvi occurs during autumn, while spring biomass is very low. During years with heavy snow cover the lake suffers from pH drop caused by melt waters, but the effects of this acid pulse are restricted to surface layers and last for a relatively short period. In addition to some chemical parameters (mainly Ca and nutrients), length of the mixing cycle and physical factors such as lake water temperature and thermal stability of water column had major impact on phytoplankton dynamics. During a year with long and strong thermal stability, the phytoplankton community developed towards an equilibrium state, with heavy dominance of only a few taxa for a longer period of time. During a year with higher windiness and less thermal stability, the species composition was more diverse and species with different functional strategies were able to occur simultaneously. The results of this work indicate that although arctic lakes in general share many common features concerning their catchment and water chemistry, large differences in biological features can be found even in a relatively small area. Most likely the lakes with very different algal flora do not respond in a similar way to differences in the environmental factors, and more information about specific arctic lake types is needed. The results also show considerable year to year differences in phytoplankton species distribution and dynamics, and these changes are most likely linked to climatic factors.

Oral Actinomyces Species in Health and Disease: Identification, Occurence and Importance of Early Colonization

The genus Actinomyces consists of a heterogeneous group of gram-positive, mainly facultatively anaerobic or microaerobic rods showing various degrees of branching. In the oral cavity, streptococci and Actinomyces form a fundamental component of the indigenous microbiota, being among initial colonizers in polymicrobial biofilms. The significance of the genus Actinomyces is based on the capability of species to adhere to surfaces such as on teeth and to co-aggregate with other bacteria. Identification of Actinomyces species has mainly been based on only a few biochemical characteristics, such as pigmentation and catalase production, or on the use of a single commercial kit. The limited identification of oral Actinomyces isolates to species level has hampered knowledge of their role both in health and disease. In recent years, Actinomyces and related organisms have attracted the attention of clinical microbiologists because of a growing awareness of their presence in clinical specimens and their association with disease. This series of studies aimed to amplify the identification methods for Actinomyces species. With the newly developed identification scheme, the age-related occurrence of Actinomyces in healthy mouths of infants and their distribution in failed dental implants was investigated. Adhesion of Actinomyces species to titanium surfaces processed in various ways was studied in vitro. The results of phenotypic identification methods indicated a relatively low applicability of commercially available test kits for reliable identification within the genus Actinomyces. However, in the study of conventional phenotypic methods, it was possible to develop an identification scheme that resulted in accurate differentiation of Actinomyces and closely related species, using various different test methods. Genotypic methods based on 16S rRNA sequence analysis of Actinomyces proved to be a useful method for genus level identification and further clarified the species level identification with phenotypic methods. The results of the study of infants showed that the isolation frequency of salivary Actinomyces species increased according to age: thirty-one percent of the infants at 2 months but 97% at 2 years of age were positive for Actinomyces. A. odontolyticus was the most prominent Actinomyces colonizer during the study period followed in frequency by A. naeslundii and A. viscosus. In the study of explanted dental implants, Actinomyces was the most prevalent bacterial genus, colonizing 94% of the fixtures. Also in the implants A. odontolyticus was revealed as the most common Actinomyces species. It was present in 84% of Actinomyces -positive fixtures followed in frequency by A. naeslundii, A. viscosus and A. israelii. In an in vitro study of titanium surfaces, different Actinomyces species showed variation regarding their adhesion to titanium. Surface roughness as well as albumin coating of titanium had significant effects on adhesion. The use of improved phenotypic and molecular diagnostic methods increased the accuracy of the identification of the Actinomyces to species level. This facilitated an investigation of their occurrence and distribution in oral specimens in both health and disease.

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 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.

Effects of turbidity on feeding and distribution of fish

In aquatic systems, the ability of both the predator and prey to detect each other may be impaired by turbidity. This could lead to significant changes in the trophic interactions in the food web of lakes. Most fish use their vision for predation and the location of prey can be highly influenced by light level and clarity of the water environment. Turbidity is an optical property of water that causes light to be scattered and absorbed by particles and molecules. Turbidity is highly variable in lakes, due to seasonal changes in suspended sediments, algal blooms and wind-driven suspension of sediments especially in shallow waters. There is evidence that human activity has increased erosion leading to increased turbidity in aquatic systems. Turbidity could also play a significant role in distribution of fish. Turbidity could act as a cover for small fish and reduce predation risk. Diel horizontal migration by fish is common in shallow lakes and is considered as consequences of either optimal foraging behaviour for food or as a trade-off between foraging and predator avoidance. In turbid lakes, diel horizontal migration patterns could differ since turbidity can act as a refuge itself and affect the predator-prey interactions. Laboratory experiments were conducted with perch (Perca fluviatilis L.) and white bream (Abramis björkna (L.)) to clarify the effects of turbidity on their feeding. Additionally to clarify the effects of turbidity on predator preying on different types of prey, pikeperch larvae (Sander lucioperca (L.)), Daphnia pulex (Leydig), Sida crystallina (O.F. Müller), and Chaoborus flavicans (Meigen) were used as prey in different experiments. To clarify the role of turbidity in distribution and diel horizontal migration of perch, roach (Rutilus rutilus (L.)) and white bream, field studies were conducted in shallow turbid lakes. A clear and a turbid shallow lake were compared to investigate distribution of perch and roach in these two lakes in a 15-year study period. Feeding efficiency of perch and white bream was not significantly affected with increasing clay turbidity up to 50 NTU. The perch experiments with pikeperch larvae suggested that clay turbidity could act as a refuge especially at turbidity levels higher than 50 NTU. Perch experiments with different prey types suggested that pikeperch larvae probably use turbidity as a refuge better compared to Daphnia. Increase in turbidity probably has stronger affect on perch predating on plant-attached prey. The main findings of the thesis show that turbidity can play a significant role in distribution of fish. Perch and roach could use turbidity as refuge when macrophytes disappear while small perch may also use high turbidity as refuge when macrophytes are present. Floating-leaved macrophytes are probably good refuges for small fish in clay-turbid lakes and provide a certain level of turbidity and not too complex structure for refuge. The results give light to the predator-prey interactions in turbid environments. Turbidity of water should be taken in to account when studying the diel horizontal migrations and distribution of fish in shallow lakes.

Phospholipids of lipid-containing bacteriophages and their transbilayer distribution

In this study we used electro-spray ionization mass-spectrometry to determine phospholipid class and molecular species compositions in bacteriophages PM2, PRD1, Bam35 and phi6 as well as their hosts. To obtain compositional data of the individual leaflets, phospholipid transbilayer distribution in the viral membranes was studied. We found that 1) the membranes of all studied bacteriophage are enriched in PG as compared to the host membranes, 2) molecular species compositions in the phage and host membranes are similar, and 3) phospholipids in the viral membranes are distributed asymmetrically with phosphatidylglycerol enriched in the outer leaflet and phosphatidylethanolamine in the inner one (except Bam35). Alternative models for selective incorporation of phospholipids to phages and for the origins of the asymmetric phospholipid transbilayer distribution are discussed. Notably, the present data are also useful when constructing high resolution structural models of bacteriophages, since diffraction methods cannot provide a detailed structure of the membrane due to high motility of the lipids and lack of symmetric organization of membrane proteins.

Distribution of non-biting midges (Diptera, Chironomidae) in subarctic lakes of Finnish Lapland applications in lake classification and palaeolimnology

Climate change contributes directly or indirectly to changes in species distributions, and there is very high confidence that recent climate warming is already affecting ecosystems. The Arctic has already experienced the greatest regional warming in recent decades, and the trend is continuing. However, studies on the northern ecosystems are scarce compared to more southerly regions. Better understanding of the past and present environmental change is needed to be able to forecast the future. Multivariate methods were used to explore the distributional patterns of chironomids in 50 shallow (≤ 10m) lakes in relation to 24 variables determined in northern Fennoscandia at the ecotonal area from the boreal forest in the south to the orohemiarctic zone in the north. Highest taxon richness was noted at middle elevations around 400 m a.s.l. Significantly lower values were observed from cold lakes situated in the tundra zone. Lake water alkalinity had the strongest positive correlation with the taxon richness. Many taxa had preference for lakes either on tundra area or forested area. The variation in the chironomid abundance data was best correlated with sediment organic content (LOI), lake water total organic carbon content, pH and air temperature, with LOI being the strongest variable. Three major lake groups were separated on the basis of their chironomid assemblages: (i) small and shallow organic-rich lakes, (ii) large and base-rich lakes, and (iii) cold and clear oligotrophic tundra lakes. Environmental variables best discriminating the lake groups were LOI, taxon richness, and Mg. When repeated, this kind of an approach could be useful and efficient in monitoring the effects of global change on species ranges. Many species of fast spreading insects, including chironomids, show a remarkable ability to track environmental changes. Based on this ability, past environmental conditions have been reconstructed using their chitinous remains in the lake sediment profiles. In order to study the Holocene environmental history of subarctic aquatic systems, and quantitatively reconstruct the past temperatures at or near the treeline, long sediment cores covering the last 10000 years (the Holocene) were collected from three lakes. Lower temperature values than expected based on the presence of pine in the catchment during the mid-Holocene were reconstructed from a lake with great water volume and depth. The lake provided thermal refuge for profundal, cold adapted taxa during the warm period. In a shallow lake, the decrease in the reconstructed temperatures during the late Holocene may reflect the indirect response of the midges to climate change through, e.g., pH change. The results from three lakes indicated that the response of chironomids to climate have been more or less indirect. However, concurrent shifts in assemblages of chironomids and vegetation in two lakes during the Holocene time period indicated that the midges together with the terrestrial vegetation had responded to the same ultimate cause, which most likely was the Holocene climate change. This was also supported by the similarity in the long-term trends in faunal succession for the chironomid assemblages in several lakes in the area. In northern Finnish Lapland the distribution of chironomids were significantly correlated with physical and limnological factors that are most likely to change as a result of future climate change. The indirect and individualistic response of aquatic systems, as reconstructed using the chironomid assemblages, to the climate change in the past suggests that in the future, the lake ecosystems in the north do not respond in one predictable way to the global climate change. Lakes in the north may respond to global climate change in various ways that are dependent on the initial characters of the catchment area and the lake.

Regeneration ecology and woody species diversity in the remnant natural forest at Wondo Genet, Ethiopia – Potential for landscape restoration

Regeneration ecology, diversity of native woody species and its potential for landscape restoration was studied in the remnant natural forest at the College of Forestry and Natural Resources at Wondo Genet, Ethiopia. The type of forest is Afromontane rainforest , with many valuable tree species like Aningeria adolfi-friederici, and it is an important provider of ecological, social and economical services for the population that lives in this area. The study contains two parts, natural regeneration studies (at the natural forest) and interviews with farmers in the nearby village of the remnant patch. The objective of the first part was to investigate the floristic composition, densitiy and regeneration profiles of native woody species in the forest, paying special attention to woody species that are considered the most relevant (socio-economic). The second part provided information on woody species preferred by the farmers and on multiple uses of the adjacent natural forest, it also provided information and analysed perceptions on forest degradation. Systematic plot sampling was used in the forest inventory. Twenty square plots of 20 x 20 m were assessed, with 38 identified woody species (the total number of species was 45), representing 26 families. Of these species 61% were trees, 13% shrubs, 11% lianas and 16% species that could have both life forms. An analysis of natural regeneration of five important tree species in the natural forest showed that Aningeria adolfi-friederici had the best regeneration results. An analysis of population structure (as determined by height classes) of two commercially important woody species in the forest, Aningeria adolfi-friederici and Podocarpus falcatus, showed a marked difference: Aningeria had a typical “reversed J” frequency distribution, while Podocarpus showed very low values in all height classes. Multi dimensional scaling (MDS) was used to map the sample plots according to their similarity in species composition, using the Sørensen quantitative index, coupled with indicator species analysis .Three groups were identified with respective indicator species: Group 1 – Adhatoda schimperiana, Group 2 – Olea hochstetteri , Group 3 – Acacia senegal and Aningeria adolfi-friederici. Thirty questionnaire interviews were conducted with farmers in the village of Gotu Onoma that use the nearby remant forest patch. Their tree preferences were exotic species such as Eucalyptus globulus for construction and fuelwood and Grevillea robusta for shade and fertility. Considering forest land degradation farmers were aware of the problem and suggested that the governmental institutions address the problem by planting more Eucalyptus globulus. The natural forest seemed to have moderate levels of disturbance and it was still floristically diverse. However, the low rate of natural regeneration of Podocarpus falcatus suggested that this species is threatened and must be a priority in conservation actions. Plantations and agroforestry seem to be possible solutions for rehabilitation of the surrounding degraded lands, thereby decreasing the existent pressure in the remnant natural forest.

Essays on the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Modeling Nonlinearities and Asymmetries in Asset Pricing

Financial time series tend to behave in a manner that is not directly drawn from a normal distribution. Asymmetries and nonlinearities are usually seen and these characteristics need to be taken into account. To make forecasts and predictions of future return and risk is rather complicated. The existing models for predicting risk are of help to a certain degree, but the complexity in financial time series data makes it difficult. The introduction of nonlinearities and asymmetries for the purpose of better models and forecasts regarding both mean and variance is supported by the essays in this dissertation. Linear and nonlinear models are consequently introduced in this dissertation. The advantages of nonlinear models are that they can take into account asymmetries. Asymmetric patterns usually mean that large negative returns appear more often than positive returns of the same magnitude. This goes hand in hand with the fact that negative returns are associated with higher risk than in the case where positive returns of the same magnitude are observed. The reason why these models are of high importance lies in the ability to make the best possible estimations and predictions of future returns and for predicting risk.

Plant communities of field margins : the effects of management and environmental factors on species composition and diversity

Agri-environmental schemes have so far resulted in only minor positive implications for the biodiversity of agricultural environments, in contrast to what has been expected. Land-use intensification has decreased landscape heterogeneity and the amount of semi-natural habitats. Field margins are uncultivated areas of permanent vegetation located adjacent to fields. Since the number of these habitats is high, investing in their quality may result in more diverse agricultural landscapes. Field margins can be considered as multifunctional habitats providing agronomic, environmental and wildlife services. This thesis aimed at examining the plant communities of different types of field margin habitats and the factors affecting their species diversity and composition. The importance of edaphic, spatial and management factors was studied on regional, landscape and habitat scales. Vegetation surveys were conducted on regional and landscape scales and a field experiment on cutting management was conducted on a habitat scale. In field margin plant communities, species appeared to be indicators of high or intermediate soil fertility and moist soil conditions. The plant species diversity found was rather low, compared with most species-rich agricultural habitats in Finland, such as dry meadows. Among regions, land-use history, main production line, natural species and human induced distribution, climate and edaphic factors were elements inducing differences in species composition. The lowest regional species diversity of field margins was related to intensive and long-term cereal production. Management by cutting and removal or grazing had a positive effect on plant species diversity. The positive effect of cutting and removal on species richness was also dependent on the adjacent source of colonizing species. Therefore, in species-poor habitats and landscapes, establishment of margins with diverse seed mixtures can be recommended for enhancing the development of species richness. However, seed mixtures should include only native species preferably local origin. Management by cutting once a year for 5 years did not result in a decline in dominance of a harmful weed species, Elymus repens, showing that E. repens probably needs cutting more frequently than once per year. Agri-environmental schemes should include long-term contracts with farmers for the establishment, and management by cutting and removal or grazing, of field margins that are several metres wide. In such schemes, the timing and frequency of management should be planned so as not to harm other taxa, such as the insects and birds that are dependent on these habitats. All accidental herbicide drifts to field margins should be avoided when spraying the cultivated area to minimize the negative effects of sprayings on vegetation. The harmful effects of herbicides can be avoided by organic farming methods.

Makrodomeeni-inhibiittorit antiviraalisina yhdisteinä

Alfavirukset ovat positiivissäkeisiä RNA-viruksia, jotka kuuluvat Togaviridea –heimoon. Alfaviruksia levittävät Aedes –suvun hyttyset ja niitä esiintyy Etelämanteretta lukuunottamatta kaikilla mantereilla. Alfaviruksia on tähän mennessä löydetty 29 lajia ja ne voidaan jakaa uuden ja vanhan maailman viruksiin niiden maantieteellisen esiintyvyyden ja taudinaiheuttamiskyvyn mukaan. Chikunkunyavirus (CHIKV) on yksi vanhan maailman alfaviruksista, jota esiintyy muun muassa Afrikassa ja Aasiassa. Ilmaston lämmettyä se on leviämässä myös eteläiseen Eurooppaan. Ihmisessä se aiheuttaa muun muassa kuumetta, päänsärkyä, ihottumaa ja niveltulehdusta, joka voi kestää useita vuosia ja ne voivat olla hyvinkin kivuliaita. Pienillä lapsilla chikungunya on todettu aiheuttavan myös neurologisia oireita kuten aivotulehdusta. Alfaviruksen genomi koodaa neljää rakenneproteiinia ja neljää replikaatioproteiinia. Replikaatioproteiineista nsP3 sisältää makrodomeeniosan. Makrodomeeniproteiinit ovat eliökunnassa konservoituneita, mutta makrodomeeniproteiinien tarkkaa merkitystä ei vielä tunneta. Makrodomeenien on osoitettu sitovan ADP-riboosia ja sen johdannaisia ja alfaviruksen nsP3-proteiinin on osoitettu olevan tärkeä osa viruksen replikaatiossa. Tutkimuksen tavoitteena oli tutkia makrodomeeniproteiiniin sitoutuvien yhdisteiden käyttöä antiviraalisena yhdisteinä. Tietokonemallinnuksella valittiin antiviraalitutkimuksiin 45 yhdistettä, joiden oletettiin sitoutuvan makrodomeeniproteiiniin. Kilpailevassa sitoutumiskokeessa viisi yhdistettä esti yli 50 % poly-ADP-riboosia (PAR) sitoutumasta MDO1-makrodomeeniproteiiniin, jolla tietokonemallinnus oli tehty. SFV-makrodomeeniproteiinilla tehdyssä kokeessa vain yksi yhdiste esti yli 50 % poly-ADP-riboosin sitoutumisen. SFV-antiviraalikokeessa seitsemällä yhdisteellä inhibitioprosentti oli yli 50 %. Näillä yhdisteillä ei kuitenkaan ollut merkittävää vaikutusta poly-ADP-riboosin sitoutumisen estossa. CHIKV-replikonikokeessa yli 50 % inhibitioprosentti oli viidellä yhdisteellä. Muiden mahdollisia vaikutusmekanismeja tutkittiin selvittämällä estävätkö yhdisteet virusta pääsemästä solun sisään. Tässä kokeessa tutkituista yhdisteistä lähes kaikilla oli vaikutusta viruksen soluun pääsyn estossa. Yleisesti ottaen kyky estää PAR:n sitoutuminen makrodomeeniproteiineihin ja antiviraaliset vaikutukset eivät korreloineet keskenään tutkittavilla yhdisteillä. Vaikka antiviraalista vaikutusta omaavat yhdisteet eivät osoittaneetkaan makrodomeeni-inhibiitiota, työssä löydettiin potentiaalisia antiviraalisia yhdisteitä joiden käyttö viruksen soluun pääsyn estäjinä antaa aihetta jatkotutkimuksille.

The many ways to delimit species: hairs, genes and surface chemistry

Species identification forms the basis for understanding the diversity of the living world, but it is also a prerequisite for understanding many evolutionary patterns and processes. The most promising approach for correctly delimiting and identifying species is to integrate many types of information in the same study. Our aim was to test how cuticular hydro- carbons, traditional morphometrics, genetic polymorphisms in nuclear markers (allozymes and DNA microsatellites) and DNA barcoding (partial mitochondrial COI gene) perform in delimiting species. As an example, we used two closely related Formica ants, F. fusca and F. lemani, sampled from a sympatric population in the northern part of their distribu- tion. Morphological characters vary and overlap in different parts of their distribution areas, but cuticular hydrocarbons include a strong taxonomic signal and our aim is to test the degree to which morphological and genetic data correspond to the chemical data. In the morphological analysis, species were best separated by the combined number of hairs on pro- notum and mesonotum, but individual workers overlapped in hair numbers, as previously noted by several authors. Nests of the two species were separated but not clustered according to species in a Principal Component Analysis made on nuclear genetic data. However, model-based Bayesian clustering resulted in perfect separation of the species and gave no indication of hybridization. Furthermore, F. lemani and F. fusca did not share any mitochondrial haplotypes, and the species were perfectly separated in a phylogenetic tree. We conclude that F. fusca and F. lemani are valid species that can be separated in our study area relatively well with all methods employed. However, the unusually small genetic differen- tiation in nuclear markers (FST = 0.12) shows that they are closely related, and occasional hybridization between F. fusca and F. lemani cannot be ruled out.

Literature Review: Investigating Drug Transport at the Blood-Brain Barrier and the Effects of P-glycoprotein on the Brain Distribution of Drugs.

The blood-brain barrier (BBB) is a unique barrier that strictly regulates the entry of endogenous substrates and xenobiotics into the brain. This is due to its tight junctions and the array of transporters and metabolic enzymes that are expressed. The determination of brain concentrations in vivo is difficult, laborious and expensive which means that there is interest in developing predictive tools of brain distribution. Predicting brain concentrations is important even in early drug development to ensure efficacy of central nervous system (CNS) targeted drugs and safety of non-CNS drugs. The literature review covers the most common current in vitro, in vivo and in silico methods of studying transport into the brain, concentrating on transporter effects. The consequences of efflux mediated by p-glycoprotein, the most widely characterized transporter expressed at the BBB, is also discussed. The aim of the experimental study was to build a pharmacokinetic (PK) model to describe p-glycoprotein substrate drug concentrations in the brain using commonly measured in vivo parameters of brain distribution. The possibility of replacing in vivo parameter values with their in vitro counterparts was also studied. All data for the study was taken from the literature. A simple 2-compartment PK model was built using the Stella™ software. Brain concentrations of morphine, loperamide and quinidine were simulated and compared with published studies. Correlation of in vitro measured efflux ratio (ER) from different studies was evaluated in addition to studying correlation between in vitro and in vivo measured ER. A Stella™ model was also constructed to simulate an in vitro transcellular monolayer experiment, to study the sensitivity of measured ER to changes in passive permeability and Michaelis-Menten kinetic parameter values. Interspecies differences in rats and mice were investigated with regards to brain permeability and drug binding in brain tissue. Although the PK brain model was able to capture the concentration-time profiles for all 3 compounds in both brain and plasma and performed fairly well for morphine, for quinidine it underestimated and for loperamide it overestimated brain concentrations. Because the ratio of concentrations in brain and blood is dependent on the ER, it is suggested that the variable values cited for this parameter and its inaccuracy could be one explanation for the failure of predictions. Validation of the model with more compounds is needed to draw further conclusions. In vitro ER showed variable correlation between studies, indicating variability due to experimental factors such as test concentration, but overall differences were small. Good correlation between in vitro and in vivo ER at low concentrations supports the possibility of using of in vitro ER in the PK model. The in vitro simulation illustrated that in the simulation setting, efflux is significant only with low passive permeability, which highlights the fact that the cell model used to measure ER must have low enough paracellular permeability to correctly mimic the in vivo situation.