Effect of thawing duration and temperature on field performance of frozen-stored Norway spruce container seedlings

Abstract

Dispersal and metacommunity dynamics in a soft-sediment benthic system : how well is the seafloor connected?

Connectivity depends on rates of dispersal between communities. For marine soft-sediment communities continued small-scale dispersal as post-larvae and as adults can be equally important in maintaining community composition, as initial recruitment of substrate by pelagic larvae. In this thesis post-larval dispersal strategies of benthic invertebrates, as well as mechanisms by which communities are connected were investigated. Such knowledge on dispersal is scarce, due to the difficulties in actually measuring dispersal directly in nature, and dispersal has not previously been quantified in the Baltic Sea. Different trap-types were used underwater to capture dispersing invertebrates at different sites, while in parallel measuring waves and currents. Local community composition was found to change predictably under varying rates of dispersal and physical connectivity (waves and currents). This response was, however, dependent on dispersal-related traits of taxa. Actively dispersing taxa will be relatively better at maintaining their position, as they are not as dependent on hydrodynamic conditions for dispersal and will be less prone to be passively transported by currents. Taxa also dispersed in relative proportions that were distinctly different from resident community composition and a significant proportion (40 %) of taxa were found to lack a planktonic larval life-stage. Community assembly was re-started in a large-scale manipulative field experiment over one year across several sites, which revealed how patterns of community composition (α-, β- and λ-diversity) change depending on rates of dispersal. Results also demonstrated that in response to small-scale disturbance, initial recruitment was by nearby-dominant species after which other species arrived from successively further away. At later assembly time, the number of coexisting species increased beyond what was expected purely by local niche requirements (species sorting), transferring regional differences in community composition (β-diversity) to the local scale (α-diversity, mass effect). Findings of this thesis complement more theoretical studies in metacommunity ecology by demonstrating that understanding how and when individuals disperse relative to underlying environmental heterogeneity is key to interpreting how patterns of diversity change across different spatial scales. Such information from nature is critical when predicting responses to, for example, different types of disturbances or management actions in conservation.

Factors predicting mortality in type 2 diabetes. With special reference to physical exercise, blood pressure, proteinuria, inflammation and P wave duration

Background: Type 2 diabetes patients have a 2-4 fold risk of cardiovascular disease (CVD) compared to the general population. In type 2 diabetes, several CVD risk factors have been identified, including obesity, hypertension, hyperglycemia, proteinuria, sedentary lifestyle and dyslipidemia. Although much of the excess CVD risk can be attributed to these risk factors, a significant proportion is still unknown. Aims: To assess in middle-aged type 2 diabetic subjects the joint relations of several conventional and non-conventional CVD risk factors with respect to cardiovascular and total mortality. Subjects and methods: This thesis is part of a large prospective, population based East-West type 2 diabetes study that was launched in 1982-1984. It includes 1,059 middle-aged (45-64 years old) participants. At baseline, a thorough clinical examination and laboratory measurements were performed and an ECG was recorded. The latest follow-up study was performed 18 years later in January 2001 (when the subjects were 63-81 years old). The study endpoints were total mortality and mortality due to CVD, coronary heart disease (CHD) and stroke. Results: Physically more active patients had significantly reduced total, CVD and CHD mortality independent of high-sensitivity C-reactive protein (hs-CRP) levels unless proteinuria was present. Among physically active patients with a hs-CRP level >3 mg/L, the prognosis of CVD mortality was similar to patients with hs-CRP levels ≤3 mg/L. The worst prognosis was among physically inactive patients with hs-CRP levels >3 mg/L. Physically active patients with proteinuria had significantly increased total and CVD mortality by multivariate analyses. After adjustment for confounding factors, patients with proteinuria and a systolic BP <130 mmHg had a significant increase in total and CVD mortality compared to those with a systolic BP between 130 and 160 mmHg. The prognosis was similar in patients with a systolic BP <130 mmHg and ≥160 mmHg. Among patients without proteinuria, a systolic BP <130 mmHg was associated with a non-significant reduction in mortality. A P wave duration ≥114 ms was associated with a 2.5-fold increase in stroke mortality among patients with prevalent CHD or claudication. This finding persisted in multivariable analyses. Among patients with no comorbidities, there was no relationship between P wave duration and stroke mortality. Conclusions: Physical activity reduces total and CVD mortality in patients with type 2 diabetes without proteinuria or with elevated levels of hs-CRP, suggesting that the anti-inflammatory effect of physical activity can counteract increased CVD morbidity and mortality associated with a high CRP level. In patients with proteinuria the protective effect was not, however, present. Among patients with proteinuria, systolic BP <130 mmHg may increase mortality due to CVD. These results demonstrate the importance of early intervention to prevent CVD and to control all-cause mortality among patients with type 2 diabetes. The presence of proteinuria should be taken into account when defining the target systolic BP level for prevention of CVD deaths. A prolongation of the duration of the P wave was associated with increased stroke mortality among high-risk patients with type 2 diabetes. P wave duration is easy to measure and merits further examination to evaluate its importance for estimation of the risk of stroke among patients with type 2 diabetes.

Statistical analysis of survey-based event history data with application to modeling of unemployment duration

Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.