Generalised regression estimation for domain class frequencies

This study examines the properties of Generalised Regression (GREG) estimators for domain class frequencies and proportions. The family of GREG estimators forms the class of design-based model-assisted estimators. All GREG estimators utilise auxiliary information via modelling. The classic GREG estimator with a linear fixed effects assisting model (GREG-lin) is one example. But when estimating class frequencies, the study variable is binary or polytomous. Therefore logistic-type assisting models (e.g. logistic or probit model) should be preferred over the linear one. However, other GREG estimators than GREG-lin are rarely used, and knowledge about their properties is limited. This study examines the properties of L-GREG estimators, which are GREG estimators with fixed-effects logistic-type models. Three research questions are addressed. First, I study whether and when L-GREG estimators are more accurate than GREG-lin. Theoretical results and Monte Carlo experiments which cover both equal and unequal probability sampling designs and a wide variety of model formulations show that in standard situations, the difference between L-GREG and GREG-lin is small. But in the case of a strong assisting model, two interesting situations arise: if the domain sample size is reasonably large, L-GREG is more accurate than GREG-lin, and if the domain sample size is very small, estimation of assisting model parameters may be inaccurate, resulting in bias for L-GREG. Second, I study variance estimation for the L-GREG estimators. The standard variance estimator (S) for all GREG estimators resembles the Sen-Yates-Grundy variance estimator, but it is a double sum of prediction errors, not of the observed values of the study variable. Monte Carlo experiments show that S underestimates the variance of L-GREG especially if the domain sample size is minor, or if the assisting model is strong. Third, since the standard variance estimator S often fails for the L-GREG estimators, I propose a new augmented variance estimator (A). The difference between S and the new estimator A is that the latter takes into account the difference between the sample fit model and the census fit model. In Monte Carlo experiments, the new estimator A outperformed the standard estimator S in terms of bias, root mean square error and coverage rate. Thus the new estimator provides a good alternative to the standard estimator.

Signifying Angels : Analyses and Interpretations of Rautavaara s Instrumental Compositions

The subject of doctoral thesis is the analysis and interpretation of instrumental pieces composed by Einojuhani Rautavaara (b. 1928) that have been given angelic titles: Archangel Michael Fighting the Antichrist from the suite Icons (1955)/Before the Icons (2006), Angels and Visitations (1978), the Double Bass Concerto Angel of Dusk (1980), Playgrounds for Angels (1981)and the Seventh Symphony Angel of Light (1994). The aim of the work is to find those musical elements common to these pieces that distinguish them from Rautavaara s other works and to determine if they could be thought of as a series. I prove that behind the common elements and titles stands the same extramusical idea the figure of an angel that the composer has described in his commentaries. The thesis is divided into three parts. Since all of the compositions possess titles that refer to the spiritual symbol of an angel, the first part offers a theoretical background to demonstrate the significant role played by angels in various religions and beliefs, and the means by which music has attempted to represent this symbol throughout history. This background traces also Rautavaara s aesthetic attitude as a spiritual composer whose output can be studied with reference to his extramusical interests including literature, psychology, painting, philosophy and myths. The second part focuses on the analysis of the instrumental compositions with angelic titles, without giving consideration to their commentaries and titles. The analyses concentrate in particular on those musical features that distinguish these pieces from Rautavaara s other compositions. In the third part these musical features are interpreted as symbols of the angel through comparison with vocal and instrumental pieces which contain references to the character of an angel, structures of mythical narration, special musical expressions, use of instruments and aspects of brightness. Finally I explore the composer s interpretative codes, drawing on Rilke s cycle of poems Ten Duino Elegies and Jung s theory of archetypes, and analyze the instrumental pieces with angelic titles in the light of the theory of musical ekphrasis.

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.

Digitoitujen väri-infrailmakuvien numeerinen monikuvatulkinta metsäninventoinnissa

The use of remote sensing imagery as auxiliary data in forest inventory is based on the correlation between features extracted from the images and the ground truth. The bidirectional reflectance and radial displacement cause variation in image features located in different segments of the image but forest characteristics remaining the same. The variation has so far been diminished by different radiometric corrections. In this study the use of sun azimuth based converted image co-ordinates was examined to supplement auxiliary data extracted from digitised aerial photographs. The method was considered as an alternative for radiometric corrections. Additionally, the usefulness of multi-image interpretation of digitised aerial photographs in regression estimation of forest characteristics was studied. The state owned study area located in Leivonmäki, Central Finland and the study material consisted of five digitised and ortho-rectified colour-infrared (CIR) aerial photographs and field measurements of 388 plots, out of which 194 were relascope (Bitterlich) plots and 194 were concentric circular plots. Both the image data and the field measurements were from the year 1999. When examining the effect of the location of the image point on pixel values and texture features of Finnish forest plots in digitised CIR photographs the clearest differences were found between front-and back-lighted image halves. Inside the image half the differences between different blocks were clearly bigger on the front-lighted half than on the back-lighted half. The strength of the phenomenon varied by forest category. The differences between pixel values extracted from different image blocks were greatest in developed and mature stands and smallest in young stands. The differences between texture features were greatest in developing stands and smallest in young and mature stands. The logarithm of timber volume per hectare and the angular transformation of the proportion of broadleaved trees of the total volume were used as dependent variables in regression models. Five different converted image co-ordinates based trend surfaces were used in models in order to diminish the effect of the bidirectional reflectance. The reference model of total volume, in which the location of the image point had been ignored, resulted in RMSE of 1,268 calculated from test material. The best of the trend surfaces was the complete third order surface, which resulted in RMSE of 1,107. The reference model of the proportion of broadleaved trees resulted in RMSE of 0,4292 and the second order trend surface was the best, resulting in RMSE of 0,4270. The trend surface method is applicable, but it has to be applied by forest category and by variable. The usefulness of multi-image interpretation of digitised aerial photographs was studied by building comparable regression models using either the front-lighted image features, back-lighted image features or both. The two-image model turned out to be slightly better than the one-image models in total volume estimation. The best one-image model resulted in RMSE of 1,098 and the two-image model resulted in RMSE of 1,090. The homologous features did not improve the models of the proportion of broadleaved trees. The overall result gives motivation for further research of multi-image interpretation. The focus may be improving regression estimation and feature selection or examination of stratification used in two-phase sampling inventory techniques. Keywords: forest inventory, digitised aerial photograph, bidirectional reflectance, converted image co­ordinates, regression estimation, multi-image interpretation, pixel value, texture, trend surface

Tukien tuotannosta irrottamisen vaikutukset viljan, naudanlihan ja sianlihan tarjontaan Suomessa

This research discusses decoupling CAP (Common Agricultural Policy) support and impacts which may occur on grain cultivation area and supply of beef and pork in Finland. The study presents the definitions and studies on decoupled agricultural subsidies, the development of supply of grain, beef and pork in Finland and changes in leading factors affecting supply between 1970 and 2005. Decoupling agricultural subsidies means that the linkage between subsidies and production levels is disconnected; subsidies do not affect the amount produced. The hypothesis is that decoupling will decrease the amounts produced in agriculture substantially. In the supply research, the econometric models which represent supply of agricultural products are estimated based on the data of prices and amounts produced. With estimated supply models, the impacts of changes in prices and public policies, can be forecasted according to supply of agricultural products. In this study, three regression models describing combined cultivation areas of rye, wheat, oats and barley, and the supply of beef and pork are estimated. Grain cultivation area and supply of beef are estimated based on data from 1970 to 2005 and supply of pork on data from 1995 to 2005. The dependencies in the model are postulated to be linear. The explanatory variables in the grain model were average return per hectare, agricultural subsidies, grain cultivation area in the previous year and the cost of fertilization. The explanatory variables in the beef model were the total return from markets and subsidies and the amount of beef production in the previous year. In the pork model the explanatory variables were the total return, the price of piglet, investment subsidies, trend of increasing productivity and the dummy variable of the last quarter of the year. The R-squared of model of grain cultivation area was 0,81, the model of beef supply 0,77 and the model of pork supply 0,82. Development of grain cultivation area and supply of beef and pork was estimated for 2006 - 2013 with this regression model. In the basic scenario, development of explanatory variables in 2006 - 2013 was postulated to be the same as they used to be in average in 1995 - 2005. After the basic scenario the impacts of decoupling CAP subsidies and domestic subsidies on cultivation area and supply were simulated. According to the results of the decoupling CAP subsidies scenario, grain cultivation area decreases from 1,12 million hectares in 2005 to 1,0 million hectares in 2013 and supply of beef from 88,8 million kilos in 2005 to 67,7 million kilos in 2013. Decoupling domestic and investment subsidies will decrease the supply of pork from 194 million kilos in 2005 to 187 million kilos in 2006. By 2013 the supply of pork grows into 203 million kilos.

Capillary electrochromatography: a versatile instrumental technique for nanodomain interaction studies

This doctoral thesis describes the development of a miniaturized capillary electrochromatography (CEC) technique suitable for the study of interactions between various nanodomains of biological importance. The particular focus of the study was low-density lipoprotein (LDL) particles and their interaction with components of the extracellular matrix (ECM). LDL transports cholesterol to the tissues through the blood circulation, but when the LDL level becomes too high the particles begin to permeate and accumulate in the arteries. Through binding sites on apolipoprotein B-100 (apoB-100), LDL interacts with components of the ECM, such as proteoglycans (PGs) and collagen, in what is considered the key mechanism in the retention of lipoproteins and onset of atherosclerosis. Hydrolytic enzymes and oxidizing agents in the ECM may later successively degrade the LDL surface. Metabolic diseases such as diabetes may provoke damage of the ECM structure through the non-enzymatic reaction of glucose with collagen. In this work, fused silica capillaries of 50 micrometer i.d. were successfully coated with LDL and collagen, and steroids and apoB-100 peptide fragments were introduced as model compounds for interaction studies. The LDL coating was modified with copper sulphate or hydrolytic enzymes, and the interactions of steroids with the native and oxidized lipoproteins were studied. Lipids were also removed from the LDL particle coating leaving behind an apoB-100 surface for further studies. The development of collagen and collagen decorin coatings was helpful in the elucidation of the interactions of apoB-100 peptide fragments with the primary ECM component, collagen. Furthermore, the collagen I coating provided a good platform for glycation studies and for clarification of LDL interactions with native and modified collagen. All methods developed are inexpensive, requiring just small amounts of biomaterial. Moreover, the experimental conditions in CEC are easily modified, and the analyses can be carried out in a reasonable time frame. Other techniques were employed to support and complement the CEC studies. Scanning electron microscopy and atomic force microscopy provided crucial visual information about the native and modified coatings. Asymmetrical flow field-flow fractionation enabled size measurements of the modified lipoproteins. Finally, the CEC results were exploited to develop new sensor chips for a continuous flow quartz crystal microbalance technique, which provided complementary information about LDL ECM interactions. This thesis demonstrates the potential of CEC as a valuable and flexible technique for surface interaction studies. Further, CEC can serve as a novel microreactor for the in situ modification of LDL and collagen coatings. The coatings developed in this study provide useful platforms for a diversity of future investigations on biological nanodomains.

Comprehensive Two-Dimensional Gas Chromatography: Instrumental and Methodological Development

Comprehensive two-dimensional gas chromatography (GC×GC) offers enhanced separation efficiency, reliability in qualitative and quantitative analysis, capability to detect low quantities, and information on the whole sample and its components. These features are essential in the analysis of complex samples, in which the number of compounds may be large or the analytes of interest are present at trace level. This study involved the development of instrumentation, data analysis programs and methodologies for GC×GC and their application in studies on qualitative and quantitative aspects of GC×GC analysis. Environmental samples were used as model samples. Instrumental development comprised the construction of three versions of a semi-rotating cryogenic modulator in which modulation was based on two-step cryogenic trapping with continuously flowing carbon dioxide as coolant. Two-step trapping was achieved by rotating the nozzle spraying the carbon dioxide with a motor. The fastest rotation and highest modulation frequency were achieved with a permanent magnetic motor, and modulation was most accurate when the motor was controlled with a microcontroller containing a quartz crystal. Heated wire resistors were unnecessary for the desorption step when liquid carbon dioxide was used as coolant. With use of the modulators developed in this study, the narrowest peaks were 75 ms at base. Three data analysis programs were developed allowing basic, comparison and identification operations. Basic operations enabled the visualisation of two-dimensional plots and the determination of retention times, peak heights and volumes. The overlaying feature in the comparison program allowed easy comparison of 2D plots. An automated identification procedure based on mass spectra and retention parameters allowed the qualitative analysis of data obtained by GC×GC and time-of-flight mass spectrometry. In the methodological development, sample preparation (extraction and clean-up) and GC×GC methods were developed for the analysis of atmospheric aerosol and sediment samples. Dynamic sonication assisted extraction was well suited for atmospheric aerosols collected on a filter. A clean-up procedure utilising normal phase liquid chromatography with ultra violet detection worked well in the removal of aliphatic hydrocarbons from a sediment extract. GC×GC with flame ionisation detection or quadrupole mass spectrometry provided good reliability in the qualitative analysis of target analytes. However, GC×GC with time-of-flight mass spectrometry was needed in the analysis of unknowns. The automated identification procedure that was developed was efficient in the analysis of large data files, but manual search and analyst knowledge are invaluable as well. Quantitative analysis was examined in terms of calibration procedures and the effect of matrix compounds on GC×GC separation. In addition to calibration in GC×GC with summed peak areas or peak volumes, simplified area calibration based on normal GC signal can be used to quantify compounds in samples analysed by GC×GC so long as certain qualitative and quantitative prerequisites are met. In a study of the effect of matrix compounds on GC×GC separation, it was shown that quality of the separation of PAHs is not significantly disturbed by the amount of matrix and quantitativeness suffers only slightly in the presence of matrix and when the amount of target compounds is low. The benefits of GC×GC in the analysis of complex samples easily overcome some minor drawbacks of the technique. The developed instrumentation and methodologies performed well for environmental samples, but they could also be applied for other complex samples.

Remote sensing of leaf area index: enhanced retrieval from close-range and remotely sensed optical observations

A wide range of models used in agriculture, ecology, carbon cycling, climate and other related studies require information on the amount of leaf material present in a given environment to correctly represent radiation, heat, momentum, water, and various gas exchanges with the overlying atmosphere or the underlying soil. Leaf area index (LAI) thus often features as a critical land surface variable in parameterisations of global and regional climate models, e.g., radiation uptake, precipitation interception, energy conversion, gas exchange and momentum, as all areas are substantially determined by the vegetation surface. Optical wavelengths of remote sensing are the common electromagnetic regions used for LAI estimations and generally for vegetation studies. The main purpose of this dissertation was to enhance the determination of LAI using close-range remote sensing (hemispherical photography), airborne remote sensing (high resolution colour and colour infrared imagery), and satellite remote sensing (high resolution SPOT 5 HRG imagery) optical observations. The commonly used light extinction models are applied at all levels of optical observations. For the sake of comparative analysis, LAI was further determined using statistical relationships between spectral vegetation index (SVI) and ground based LAI. The study areas of this dissertation focus on two regions, one located in Taita Hills, South-East Kenya characterised by tropical cloud forest and exotic plantations, and the other in Gatineau Park, Southern Quebec, Canada dominated by temperate hardwood forest. The sampling procedure of sky map of gap fraction and size from hemispherical photographs was proven to be one of the most crucial steps in the accurate determination of LAI. LAI and clumping index estimates were significantly affected by the variation of the size of sky segments for given zenith angle ranges. On sloping ground, gap fraction and size distributions present strong upslope/downslope asymmetry of foliage elements, and thus the correction and the sensitivity analysis for both LAI and clumping index computations were demonstrated. Several SVIs can be used for LAI mapping using empirical regression analysis provided that the sensitivities of SVIs at varying ranges of LAI are large enough. Large scale LAI inversion algorithms were demonstrated and were proven to be a considerably efficient alternative approach for LAI mapping. LAI can be estimated nonparametrically from the information contained solely in the remotely sensed dataset given that the upper-end (saturated SVI) value is accurately determined. However, further study is still required to devise a methodology as well as instrumentation to retrieve on-ground green leaf area index . Subsequently, the large scale LAI inversion algorithms presented in this work can be precisely validated. Finally, based on literature review and this dissertation, potential future research prospects and directions were recommended.

Joint Regression and Association Models for Repeated Categorical Responses

The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

Short-term effects of variable retention on epigaeic spiders and carabid beetles in Finland

Forestry has influenced forest dwelling organisms for centuries in Fennoscandia. For example, in Finland ca. 30% of the threatened species are threatened because of forestry. Nowadays forest management recommendations include practices aimed at maintaining biodiversity in harvesting, such as green-tree retention. However, the effects of these practices have been little studied. In variable retention, different numbers of trees are retained, varying from green-tree retention (at least a few live standing trees in clear-cuts) to thinning (only individual trees removed). I examined the responses of ground-dwelling spiders and carabid beetles to green-tree retention (with small and large tree groups), gap felling and thinning aimed at an uneven age structure of trees. The impacts of these harvesting methods were compared to those of clear-cutting and uncut controls. I aimed to test the hypothesis that retaining more trees positively affects populations of those species of spiders and carabids that were present before harvesting. The data come from two studies. First, spiders were collected with pitfall traps in south-central Finland in 1995 (pre-treatment) and 1998 (after-treatment) in order to examine the effects of clear-cutting, green-tree retention (with 0.01-0.02-ha sized tree groups), gap felling (with three 0.16-ha sized openings in a 1-ha stand), thinning aiming at an uneven age structure of trees and uncut control. Second, spiders and carabids were caught with pitfall traps in eastern Finland in 1998-2001 (pre-treatment and three post-treatment years) in eleven 0.09-0.55-ha sized retention-tree groups and clear-cuts adjacent to them. Original spider and carabid assemblages were better maintained after harvests that retained more trees. Thinning maintained forest spiders well. However, gap felling and large retention-tree groups maintained some forest spider and carabid species in the short-term, but negatively affected some species over time. However, use of small retention-tree groups was associated with negative effects on forest spider populations. Studies are needed on the long-term effects of variable retention on terrestrial invertebrates; especially those directed at defining appropriate retention patch size and on the importance of structural diversity provided by variable retention for invertebrate populations. However, the aims of variable retention should be specified first. For example, are retention-tree groups planned to constitute life-boats , stepping-stones or to create structural diversity? Does it suffice that some species are maintained, or do we want to preserve the most sensitive ones, and how are these best defined? Moreover, the ecological benefits and economic costs of modified logging methods should be compared to other approaches aimed at maintaining biodiversity.

Population dynamics of blue mussels in a variable environment at the edge of their range

Spatial and temporal variation in the abundance of species can often be ascribed to spatial and temporal variation in the surrounding environment. Knowledge of how biotic and abiotic factors operate over different spatial and temporal scales in determining distribution, abundance, and structure of populations lies at the heart of ecology. The major part of the current ecological theory stems from studies carried out in central parts of the distributional range of species, whereas knowledge of how marginal populations function is inadequate. Understanding how marginal populations, living at the edge of their range, function is however in a key position to advance ecology and evolutionary biology as scientific disciplines. My thesis focuses on the factors affecting dynamics of marginal populations of blue mussels (Mytilus edulis) living close to their tolerance limits with regard to salinity. The thesis aims to highlight the dynamics at the edge of the range and contrast these with dynamics in more central parts of the range in order to understand the potential interplay between the central and the marginal part in the focal system. The objectives of the thesis are approached by studies on: (1) factors affecting regional patterns of the species, (2) long-term temporal dynamics of the focal species spaced along a regional salinity gradient, (3) selective predation by increasing populations of roach (Rutilus rutilus) when feeding on their main food item, the blue mussel, (4) the primary and secondary effects of local wave exposure gradients and (5) the role of small-scale habitat heterogeneity as determinants of large-scale pattern. The thesis shows that populations of blue mussels are largely determined by large scale changes in sea water salinity, affecting mainly recruitment success and longevity of local populations. In opposite to the traditional view, the thesis strongly indicate that vertebrate predators strongly affect abundance and size structure of blue mussel populations, and that the role of these predators increases towards the margin where populations are increasingly top-down controlled. The thesis also indicates that the positive role of biogenic habitat modifiers increases towards the marginal areas, where populations of blue mussels are largely recruitment limited. Finally, the thesis shows that local blue mussel populations are strongly dependent on high water turbulence, and therefore, dense populations are constrained to offshore habitats. Finally, the thesis suggests that ongoing sedimentation of rocky shores is detrimental for the species, affecting recruitment success and post-recruit survival, pushing stable mussel beds towards offshore areas. Ongoing large scale changes in the Baltic Sea, especially dilution processes with attendant effects, are predicted to substantially contract the distributional range of the mussel, but also affect more central populations. The thesis shows that in order to understand the functioning of marginal populations, research should (1) strive for multi-scale approaches in order to link ecosystem patterns with ecosystem processes, and (2) challenge the prevailing tenets that origin from research carried out in central areas that may not be valid at the edge.

Fluorescence properties of Baltic Sea phytoplankton

To obtain data on phytoplankton dynamics with improved spatial and temporal resolution, and at reduced cost, traditional phytoplankton monitoring methods have been supplemented with optical approaches. In this thesis, I have explored various fluorescence-based techniques for detection of phytoplankton abundance, taxonomy and physiology in the Baltic Sea. In algal cultures used in this thesis, the availability of nitrogen and light conditions caused changes in pigmentation, and consequently in light absorption and fluorescence properties of cells. In the Baltic Sea, physical environmental factors (e.g. mixing depth, irradiance and temperature) and related seasonal succession in the phytoplankton community explained a large part of the seasonal variability in the magnitude and shape of Chlorophyll a (Chla)-specific absorption. The variability in Chla-specific fluorescence was related to the abundance of cyanobacteria, the size structure of the phytoplankton community, and absorption characteristics of phytoplankton. Cyanobacteria show very low Chla-specific fluorescence. In the presence of eukaryotic species, Chla fluorescence describes poorly cyanobacteria. During cyanobacterial bloom in the Baltic Sea, phycocyanin fluorescence explained large part of the variability in Chla concentrations. Thus, both Chla and phycocyanin fluorescence were required to predict Chla concentration. Phycobilins are major light harvesting pigments for cyanobacteria. In the open Baltic Sea, small picoplanktonic cyanobacteria were the main source of phycoerythrin fluorescence and absorption signal. Large filamentous cyanobacteria, forming harmful blooms, were the main source of the phycocyanin fluorescence signal and typically their biomass and phycocyanin fluorescence were linearly related. Using phycocyanin fluorescence, dynamics of cyanobacterial blooms can be detected at high spatial and seasonal resolution not possible with other methods. Various taxonomic phytoplankton pigment groups can be separated by spectral fluorescence. I compared multivariate calibration methods for the retrieval of phytoplankton biomass in different taxonomic groups. Partial least squares regression method gave the closest predictions for all taxonomic groups, and the accuracy was adequate for phytoplankton bloom detection. Variable fluorescence has been proposed as a tool to study the physiological state of phytoplankton. My results from the Baltic Sea emphasize that variable fluorescence alone cannot be used to detect nutrient limitation of phytoplankton. However, when combined with experiments with active nutrient manipulation, and other nutrient limitation indices, variable fluorescence provided valuable information on the physiological responses of the phytoplankton community. This thesis found a severe limitation of a commercial fast repetition rate fluorometer, which couldn t detect the variable fluorescence of phycoerythrin-lacking cyanobacteria. For these species, the Photosystem II absorption of blue light is very low, and fluorometer excitation light did not saturate Photosystem II during a measurement. This thesis encourages the use of various in vivo fluorescence methods for the detection of bulk phytoplankton biomass, biomass of cyanobacteria, chemotaxonomy of phytoplankton community, and phytoplankton physiology. Fluorescence methods can support traditional phytoplankton monitoring by providing continuous measurements of phytoplankton, and thereby strengthen the understanding of the links between biological, chemical and physical processes in aquatic ecosystems.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.