Metsikön rakenteen ja hakkuiden vaikutus pintakasvillisuuteen Etelä-Suomen yleisimmillä kasvupaikkatyypeillä

Taman tutkielman tarkoituksena oli selvittaa metsikon rakenteen seka hakkuiden vaikutuksia pintakasvillisuuden lajikoostumukseen ja biomassaan Etela-Suomen lehtomaisilla, tuoreilla ja kuivahkoilla kankailla. Aineistona tassa tyossa on 8. valtakunnan metsien inventoinnin yhteydessa vuosina 1985–86 metsaluonnon ja ympariston tilan seurantaa varten perustetuista noin 3 000 pysyvasta koealasta poimittu otos. Pintakasvillisuuden lajisto muuttuu metsikon kehitysvaiheen mukaan. Hakkuu on huomattava hairio, joka aiheuttaa nopeita ja suuria muutoksia pintakasvillisuudessa. Pintakasvillisuutta on tarkasteltu lahinna lajiryhmittain (heinat, ruohot, varvut, sammalet seka jakalat). Kunkin lajiryhman peittavyyden eroavaisuuksia testattiin varianssianalyysilla kun selittavana muuttujana ovat luokittain metsikon ika ja edellisesta hakkuusta kulunut aika. Lajikohtaisia tarkasteluja on sen sijaan tehty kasvillisuuden ordinaatioanalyyseilla. Tassa kaytetty ordinaatiomenetelma on epametrinen moniulotteinen skaalaus (Non-metric multidimensional scaling, NMDS), jonka avulla voidaan tehda paatelmia kasvillisuuden rakenteen ekologisesta vaihtelusta ymparistomuuttujien suhteen. Harvennus- ja avohakkuiden vaikutuksia pintakasvillisuuteen myos mallinnettiin lajiryhmittain kayttaen yleistettyja lineaarisia malleja (Generalized linear models). Lajiryhmien peittavyyksien kehitysta mallinnettiin puuston pohjapinta-alan funktiona. Metsikon ian kasvaessa heinien ja ruohojen osuus pienenee, kun taas varpujen ja sammalten osuus lisaantyy. Harvennushakkuiden vaikutukset ovat lievempia kuin avohakkuiden eivatka ne useimmiten aiheuttaneet tilastollisesti merkittavia muutoksia pintakasvillisuuden peittavyyksissa. Avohakkuu sen sijaan on voimakkaampi ja aiheuttaa merkittavia muutoksia. Heinia ja ruohoja esiintyy hakkuun jalkeen enemman ja vastaavasti sammalet ja varvut taantuvat. Kasvillisuuden kokonaispeittavyys ja biomassa ovat suurimmillaan hakkaamattomissa metsikoissa. Harvennushakkuun jalkeen peittavyys ja biomassa voi kuitenkin hetkellisesti olla suurimmillaan kun harvennuksesta on kulunut muutama vuosi. Yleistetyt lineaariset mallit kuvasivat pintakasvillisuuden kehitysta metsikon pohjapinta-alan funktiona luotettavasti. Malleja voidaan kayttaa myos ennustamaan miten pintakasvillisuus kehittyy avohakkuun jalkeen. Malleja voidaan soveltaa esimerkiksi laskettaessa pintakasvillisuuden sitoman hiilen maaraa eriikaisissa metsissa. Niiden avulla voidaan myos arvioida esimerkiksi avohakkuuta voimaperaisemman energiapuun korjuun vaikutuksia pintakasvillisuuden runsauteen.

Periglasiaalisten ilmiöiden alueellinen mallintaminen subarktisessa ympäristössä

Periglacial processes act on cold, non-glacial regions where the landscape deveploment is mainly controlled by frost activity. Circa 25 percent of Earth's surface can be considered as periglacial. Geographical Information System combined with advanced statistical modeling methods, provides an efficient tool and new theoretical perspective for study of cold environments. The aim of this study was to: 1) model and predict the abundance of periglacial phenomena in subarctic environment with statistical modeling, 2) investigate the most import factors affecting the occurence of these phenomena with hierarchical partitioning, 3) compare two widely used statistical modeling methods: Generalized Linear Models and Generalized Additive Models, 4) study modeling resolution's effect on prediction and 5) study how spatially continous prediction can be obtained from point data. The observational data of this study consist of 369 points that were collected during the summers of 2009 and 2010 at the study area in Kilpisjärvi northern Lapland. The periglacial phenomena of interest were cryoturbations, slope processes, weathering, deflation, nivation and fluvial processes. The features were modeled using Generalized Linear Models (GLM) and Generalized Additive Models (GAM) based on Poisson-errors. The abundance of periglacial features were predicted based on these models to a spatial grid with a resolution of one hectare. The most important environmental factors were examined with hierarchical partitioning. The effect of modeling resolution was investigated with in a small independent study area with a spatial resolution of 0,01 hectare. The models explained 45-70 % of the occurence of periglacial phenomena. When spatial variables were added to the models the amount of explained deviance was considerably higher, which signalled a geographical trend structure. The ability of the models to predict periglacial phenomena were assessed with independent evaluation data. Spearman's correlation varied 0,258 - 0,754 between the observed and predicted values. Based on explained deviance, and the results of hierarchical partitioning, the most important environmental variables were mean altitude, vegetation and mean slope angle. The effect of modeling resolution was clear, too coarse resolution caused a loss of information, while finer resolution brought out more localized variation. The models ability to explain and predict periglacial phenomena in the study area were mostly good and moderate respectively. Differences between modeling methods were small, although the explained deviance was higher with GLM-models than GAMs. In turn, GAMs produced more realistic spatial predictions. The single most important environmental variable controlling the occurence of periglacial phenomena was mean altitude, which had strong correlations with many other explanatory variables. The ongoing global warming will have great impact especially in cold environments on high latitudes, and for this reason, an important research topic in the near future will be the response of periglacial environments to a warming climate.

Environmental factors affecting the occurrence of periglacial landforms in Finnish Lapland: a numerical approach

Determination of the environmental factors controlling earth surface processes and landform patterns is one of the central themes in physical geography. However, the identification of the main drivers of the geomorphological phenomena is often challenging. Novel spatial analysis and modelling methods could provide new insights into the process-environment relationships. The objective of this research was to map and quantitatively analyse the occurrence of cryogenic phenomena in subarctic Finland. More precisely, utilising a grid-based approach the distribution and abundance of periglacial landforms were modelled to identify important landscape scale environmental factors. The study was performed using a comprehensive empirical data set of periglacial landforms from an area of 600 km2 at a 25-ha resolution. The utilised statistical methods were generalized linear modelling (GLM) and hierarchical partitioning (HP). GLMs were used to produce distribution and abundance models and HP to reveal independently the most likely causal variables. The GLM models were assessed utilising statistical evaluation measures, prediction maps, field observations and the results of HP analyses. A total of 40 different landform types and subtypes were identified. Topographical, soil property and vegetation variables were the primary correlates for the occurrence and cover of active periglacial landforms on the landscape scale. In the model evaluation, most of the GLMs were shown to be robust although the explanation power, prediction ability as well as the selected explanatory variables varied between the models. The great potential of the combination of a spatial grid system, terrain data and novel statistical techniques to map the occurrence of periglacial landforms was demonstrated in this study. GLM proved to be a useful modelling framework for testing the shapes of the response functions and significances of the environmental variables and the HP method helped to make better deductions of the important factors of earth surface processes. Hence, the numerical approach presented in this study can be a useful addition to the current range of techniques available to researchers to map and monitor different geographical phenomena.

Stand structural dynamics on pristine and managed boreal peatlands

The objectives of this study were to investigate the stand structure and succession dynamics in Scots pine (Pinus sylvestris L.) stands on pristine peatlands and in Scots pine and Norway spruce (Picea abies (L.) Karst.) dominated stands on drained peatlands. Furthermore, my focus was on characterising how the inherent and environmental factors and the intermediate thinnings modify the stand structure and succession. For pristine peatlands, the study was based on inventorial stand data, while for drained peatlands, longitudinal data from repeatedly measured stands were utilised. The studied sites covered the most common peatland site types in Finland. They were classified into two categories according to the ecohydrological properties related to microsite variation and nutrient levels within sites. Tree DBH and age distributions in relation to climate and site type were used to study the stand dynamics on pristine sites. On drained sites, the Weibull function was used to parameterise the DBH distributions and mixed linear models were constructed to characterise the impacts of different ecological factors on stand dynamics. On pristine peatlands, both climate and the ecohydrology of the site proved to be crucial factors determining the stand structure and its dynamics. Irrespective of the vegetation succession, enhanced site productivity and increased stand stocking they significantly affected the stand dynamics also on drained sites. On the most stocked sites on pristine peatlands the inter-tree competition seemed to also be a significant factor modifying stand dynamics. Tree age and size diversity increased with stand age, but levelled out in the long term. After drainage, the stand structural unevenness increased due to the regeneration and/or ingrowth of the trees. This increase was more pronounced on sparsely forested composite sites than on more fully stocked genuine forested sites in Scots pine stands, which further undergo the formation of birch and spruce undergrowth beneath the overstory as succession proceeds. At 20-30 years after drainage the structural heterogeneity started to decrease, indicating increased inter-tree competition, which increased the mortality of suppressed trees within stand. Peatland stands are more dynamic than anticipated and are generally not characterized by a balanced, self-perpetuating structure. On pristine sites, various successional pathways are possible, whereas on drained sites the succession has more uniform trend. Typically, stand succession proceeds without any distinct developmental stages on pristine peatlands, whereas on drained peatlands, at least three distinct stages could be identified. Thinnings had only little impact on the stand succession. The new information on stand dynamics may be utilised, e.g. in forest management planning to facilitate the allocation of the growth resources to the desired crop component by appropriate silvicultural treatments, as well as assist in assessing the effects of the climate change on the forested boreal peatlands.

Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

Retirement Transition and Well-being : A 16-year Longitudinal Study

The ageing of the labour force and falling employment rates have forced policy makers in industrialized countries to find means of increasing the well-being of older workers and of lengthening their work careers. The main objective of this thesis was to study longitudinally how health, functional capacity, subjective well-being, and lifestyle change as people grow older, and what effect retirement has on these factors and on their relationships. The present study is a follow-up questionnaire study of Finnish municipal workers, conducted in 1981 to 1997 at the Finnish Institute of Occupational Health. In 1981, a postal questionnaire was sent to 7344 municipal workers in different parts of Finland. The respondents were born between 1923 and 1937. A total of 6257 persons responded to the first questionnaire. In the end, a total of 3817 persons had responded to all four (1981, 1985, 1992, 1997) questionnaires. (The response rate was 69% of the living participants). Cross-tabulations, comparison of means, logistic regression analyses and general linear models with repeated measures were used to derive the results. The transition from work life to retirement, and the following years as a pensioner were associated with many changes. Involvement in various activities increased during the transition stage but later decreased to the previous level. Physical exercise was an exception: it became increasingly popular over the years. Perceived health improved markedly from the working stage to the retirement transition stage, even though morbidity increased steadily during the follow-up. On the other hand, functional capacity decreased over the follow-up, especially among those who were occupationally active until the retirement stage. Subjective well-being remained stable during the follow-up period. There were, however, great differences based on the type of work, favouring those whose work had been mental in nature. The impact of activity level on maintaining well-being became greater during the follow-up, whereas the effect of physical functioning diminished. Good physical functioning and an active life-style contributed to staying on at work until normal retirement age. Also work-related factors, i.e. possibilities for development and influence at work, responsibility for others, meaningful work, and satisfaction with working time arrangements were positively related to continuing working. The transition from work to retirement had a positive impact on a person s health and functional capacity. The study results support the view that it should be possible to ease one s work pace during the last years of a work career. This might lower the threshold between work and retirement and convince people that there will still be time to enjoy retirement also a few years later.

On linear order and computation : The expressiveness of interactive computations on linear orders and computations indexed by ordinals

We solve the Dynamic Ehrenfeucht-Fra\"iss\'e Game on linear orders for both players, yielding a normal form for quantifier-rank equivalence classes of linear orders in first-order logic, infinitary logic, and generalized-infinitary logics with linearly ordered clocks. We show that Scott Sentences can be manipulated quickly, classified into local information, and consistency can be decided effectively in the length of the Scott Sentence. We describe a finite set of linked automata moving continuously on a linear order. Running them on ordinals, we compute the ordinal truth predicate and compute truth in the constructible universe of set-theory. Among the corollaries are a study of semi-models as efficient database of both model-theoretic and formulaic information, and a new proof of the atomicity of the Boolean algebra of sentences consistent with the theory of linear order -- i.e., that the finitely axiomatized theories of linear order are dense.

Diagnostic Tests Based on Quantile Residuals for Nonlinear Time Series Models

This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

An Empirical Comparison of Linear and Nonlinear Volatility Models for Nordic Stock Returns

This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.