Carbon dynamics in peatlands under changing hydrology : Effects of water level drawdown on litter quality, microbial enzyme activities and litter decomposition rates

Pristine peatlands are carbon (C) accumulating wetland ecosystems sustained by a high water level (WL) and consequent anoxia that slows down decomposition. Persistent WL drawdown as a response to climate and/or land-use change directly affects decomposition: increased oxygenation stimulates decomposition of the old C (peat) sequestered under prior anoxic conditions. Responses of the new C (plant litter) in terms of quality, production and decomposability, and the consequences for the whole C cycle of peatlands are not fully understood. WL drawdown induces changes in plant community resulting in shift in dominance from Sphagnum and graminoids to shrubs and trees. There is increasing evidence that the indirect effects of WL drawdown via the changes in plant communities will have more impact on the ecosystem C cycling than any direct effects. The aim of this study is to disentangle the direct and indirect effects of WL drawdown on the new C by measuring the relative importance of 1) environmental parameters (WL depth, temperature, soil chemistry) and 2) plant community composition on litter production, microbial activity, litter decomposition rates and, consequently, on the C accumulation. This information is crucial for modelling C cycle under changing climate and/or land-use. The effects of WL drawdown were tested in a large-scale experiment with manipulated WL at two time scales and three nutrient regimes. Furthermore, the effect of climate on litter decomposability was tested along a north-south gradient. Additionally, a novel method for estimating litter chemical quality and decomposability was explored by combining Near infrared spectroscopy with multivariate modelling. WL drawdown had direct effects on litter quality, microbial community composition and activity and litter decomposition rates. However, the direct effects of WL drawdown were overruled by the indirect effects via changes in litter type composition and production. Short-term (years) responses to WL drawdown were small. In long-term (decades), dramatically increased litter inputs resulted in large accumulation of organic matter in spite of increased decomposition rates. Further, the quality of the accumulated matter greatly changed from that accumulated in pristine conditions. The response of a peatland ecosystem to persistent WL drawdown was more pronounced at sites with more nutrients. The study demonstrates that the shift in vegetation composition as a response to climate and/or land-use change is the main factor affecting peatland ecosystem C cycle and thus dynamic vegetation is a necessity in any models applied for estimating responses of C fluxes to changes in the environment. The time scale for vegetation changes caused by hydrological changes needs to extend to decades. This study provides grouping of litter types (plant species and part) into functional types based on their chemical quality and/or decomposability that the models could utilize. Further, the results clearly show a drop in soil temperature as a response to WL drawdown when an initially open peatland converts into a forest ecosystem, which has not yet been considered in the existing models.

Exploring Problem Decomposition in Conceptual Design

Design embraces several disciplines dedicated to the production of artifacts and services. These disciplines are quite independent and only recently has psychological interest focused on them. Nowadays, the psychological theories of design, also called design cognition literature, describe the design process from the information processing viewpoint. These models co-exist with the normative standards of how designs should be crafted. In many places there are concrete discrepancies between these two in a way that resembles the differences between the actual and ideal decision-making. This study aimed to explore the possible difference related to problem decomposition. Decomposition is a standard component of human problem-solving models and is also included in the normative models of design. The idea of decomposition is to focus on a single aspect of the problem at a time. Despite its significance, the nature of decomposition in conceptual design is poorly understood and has only been preliminary investigated. This study addressed the status of decomposition in conceptual design of products using protocol analysis. Previous empirical investigations have argued that there are implicit and explicit decomposition, but have not provided a theoretical basis for these two. Therefore, the current research began by reviewing the problem solving and design literature and then composing a cognitive model of the solution search of conceptual design. The result is a synthetic view which describes recognition and decomposition as the basic schemata for conceptual design. A psychological experiment was conducted to explore decomposition. In the test, sixteen (N=16) senior students of mechanical engineering created concepts for two alternative tasks. The concurrent think-aloud method and protocol analysis were used to study decomposition. The results showed that despite the emphasis on decomposition in the formal education, only few designers (N=3) used decomposition explicitly and spontaneously in the presented tasks, although the designers in general applied a top-down control strategy. Instead, inferring from the use of structured strategies, the designers always relied on implicit decomposition. These results confirm the initial observations found in the literature, but they also suggest that decomposition should be investigated further. In the future, the benefits and possibilities of explicit decomposition should be considered along with the cognitive mechanisms behind decomposition. After that, the current results could be reinterpreted.

Soil carbon modelling as a tool for carbon balance studies in forestry

Soils represent a remarkable stock of carbon, and forest soils are estimated to hold half of the global stock of soil carbon. Topical concern about the effects of climate change and forest management on soil carbon as well as practical reporting requirements set by climate conventions have created a need to assess soil carbon stock changes reliably and transparently. The large spatial variability of soil carbon commensurate with relatively slow changes in stocks hinders the assessment of soil carbon stocks and their changes by direct measurements. Models therefore widely serve to estimate carbon stocks and stock changes in soils. This dissertation aimed to develop the soil carbon model YASSO for upland forest soils. The model was aimed to take into account the most important processes controlling the decomposition in soils, yet remain simple enough to ensure its practical applicability in different applications. The model structure and assumptions were presented and the model parameters were defined with empirical measurements. The model was evaluated by studying the sensitivities of the model results to parameter values, by estimating the precision of the results with an uncertainty analysis, and by assessing the accuracy of the model by comparing the predictions against measured data and to the results of an alternative model. The model was applied to study the effects of intensified biomass extraction on the forest carbon balance and to estimate the effects of soil carbon deficit on net greenhouse gas emissions of energy use of forest residues. The model was also applied in an inventory based method to assess the national scale forest carbon balance for Finland’s forests from 1922 to 2004. YASSO managed to describe sufficiently the effects of both the variable litter and climatic conditions on decomposition. When combined with the stand models or other systems providing litter information, the dynamic approach of the model proved to be powerful for estimating changes in soil carbon stocks on different scales. The climate dependency of the model, the effects of nitrogen on decomposition and forest growth as well as the effects of soil texture on soil carbon stock dynamics are areas for development when considering the applicability of the model to different research questions, different land use types and wider geographic regions. Intensified biomass extraction affects soil carbon stocks, and these changes in stocks should be taken into account when considering the net effects of forest residue utilisation as energy. On a national scale, soil carbon stocks play an important role in forest carbon balances.

Temperature sensitivity of soil organic matter decomposition in boreal soils

The temperature sensitivity of decomposition of different soil organic matter (SOM) fractions was studied with laboratory incubations using 13C and 14C isotopes to differentiate between SOM of different age. The quality of SOM and the functionality and composition of microbial communities in soils formed under different climatic conditions were also studied. Transferring of organic layers from a colder to a warmer climate was used to assess how changing climate, litter input and soil biology will affect soil respiration and its temperature sensitivity. Together, these studies gave a consistent picture on how warming climate will affect the decomposition of different SOM fractions in Finnish forest soils: the most labile C was least temperature sensitive, indicating that it is utilized irrespective of temperature. The decomposition of intermediate C, with mean residence times from some years to decades, was found to be highly temperature sensitive. Even older, centennially cycling C was again less temperature sensitive, indicating that different stabilizing mechanisms were limiting its decomposition even at higher temperatures. Because the highly temperature sensitive, decadally cycling C, forms a major part of SOM stock in the organic layers of the studied forest soils, these results mean that these soils could lose more carbon during the coming years and decades than estimated earlier. SOM decomposition in boreal forest soils is likely to increase more in response to climate warming, compared to temperate or tropical soils, also because the Q10 is temperature dependent. In the northern soils the warming will occur at a lower temperature range, where Q10 is higher, and a similar increase in temperature causes a higher relative increase in respiration rates. The Q10 at low temperatures was found to be inversely related to SOM quality. At higher temperatures respiration was increasingly limited by low substrate availability.

A dynamic programming model for optimising feeding and slaughter decisions regarding fattening pigs

Costs of purchasing new piglets and of feeding them until slaughter are the main variable expenditures in pig fattening. They both depend on slaughter intensity, the nature of feeding patterns and the technological constraints of pig fattening, such as genotype. Therefore, it is of interest to examine the effect of production technology and changes in input and output prices on feeding and slaughter decisions. This study examines the problem by using a dynamic programming model that links genetic characteristics of a pig to feeding decisions and the timing of slaughter and takes into account how these jointly affect the quality-adjusted value of a carcass. The model simulates the growth mechanism of a pig under optional feeding and slaughter patterns and then solves the optimal feeding and slaughter decisions recursively. The state of nature and the genotype of a pig are known in the analysis. The main contribution of this study is the dynamic approach that explicitly takes into account carcass quality while simultaneously optimising feeding and slaughter decisions. The method maximises the internal rate of return to the capacity unit. Hence, the results can have vital impact on competitiveness of pig production, which is known to be quite capital-intensive. The results suggest that producer can significantly benefit from improvements in the pig's genotype, because they improve efficiency of pig production. The annual benefits from obtaining pigs of improved genotype can be more than €20 per capacity unit. The annual net benefits of animal breeding to pig farms can also be considerable. Animals of improved genotype can reach optimal slaughter maturity quicker and produce leaner meat than animals of poor genotype. In order to fully utilise the benefits of animal breeding, the producer must adjust feeding and slaughter patterns on the basis of genotype. The results suggest that the producer can benefit from flexible feeding technology. The flexible feeding technology segregates pigs into groups according to their weight, carcass leanness, genotype and sex and thereafter optimises feeding and slaughter decisions separately for these groups. Typically, such a technology provides incentives to feed piglets with protein-rich feed such that the genetic potential to produce leaner meat is fully utilised. When the pig approaches slaughter maturity, the share of protein-rich feed in the diet gradually decreases and the amount of energy-rich feed increases. Generally, the optimal slaughter weight is within the weight range that pays the highest price per kilogram of pig meat. The optimal feeding pattern and the optimal timing of slaughter depend on price ratios. Particularly, an increase in the price of pig meat provides incentives to increase the growth rates up to the pig's biological maximum by increasing the amount of energy in the feed. Price changes and changes in slaughter premium can also have large income effects. Key words: barley, carcass composition, dynamic programming, feeding, genotypes, lean, pig fattening, precision agriculture, productivity, slaughter weight, soybeans

Matrix Decomposition Methods for Data Mining : Computational Complexity and Algorithms

Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.

Country-scale carbon accounting of the vegetation and mineral soils of Finland

The increase in global temperature has been attributed to increased atmospheric concentrations of greenhouse gases (GHG), mainly that of CO2. The threat of severe and complex socio-economic and ecological implications of climate change have initiated an international process that aims to reduce emissions, to increase C sinks, and to protect existing C reservoirs. The famous Kyoto protocol is an offspring of this process. The Kyoto protocol and its accords state that signatory countries need to monitor their forest C pools, and to follow the guidelines set by the IPCC in the preparation, reporting and quality assessment of the C pool change estimates. The aims of this thesis were i) to estimate the changes in carbon stocks vegetation and soil in the forests in Finnish forests from 1922 to 2004, ii) to evaluate the applied methodology by using empirical data, iii) to assess the reliability of the estimates by means of uncertainty analysis, iv) to assess the effect of forest C sinks on the reliability of the entire national GHG inventory, and finally, v) to present an application of model-based stratification to a large-scale sampling design of soil C stock changes. The applied methodology builds on the forest inventory measured data (or modelled stand data), and uses statistical modelling to predict biomasses and litter productions, as well as a dynamic soil C model to predict the decomposition of litter. The mean vegetation C sink of Finnish forests from 1922 to 2004 was 3.3 Tg C a-1, and in soil was 0.7 Tg C a-1. Soil is slowly accumulating C as a consequence of increased growing stock and unsaturated soil C stocks in relation to current detritus input to soil that is higher than in the beginning of the period. Annual estimates of vegetation and soil C stock changes fluctuated considerably during the period, were frequently opposite (e.g. vegetation was a sink but soil was a source). The inclusion of vegetation sinks into the national GHG inventory of 2003 increased its uncertainty from between -4% and 9% to ± 19% (95% CI), and further inclusion of upland mineral soils increased it to ± 24%. The uncertainties of annual sinks can be reduced most efficiently by concentrating on the quality of the model input data. Despite the decreased precision of the national GHG inventory, the inclusion of uncertain sinks improves its accuracy due to the larger sectoral coverage of the inventory. If the national soil sink estimates were prepared by repeated soil sampling of model-stratified sample plots, the uncertainties would be accounted for in the stratum formation and sample allocation. Otherwise, the increases of sampling efficiency by stratification remain smaller. The highly variable and frequently opposite annual changes in ecosystem C pools imply the importance of full ecosystem C accounting. If forest C sink estimates will be used in practice average sink estimates seem a more reasonable basis than the annual estimates. This is due to the fact that annual forest sinks vary considerably and annual estimates are uncertain, and they have severe consequences for the reliability of the total national GHG balance. The estimation of average sinks should still be based on annual or even more frequent data due to the non-linear decomposition process that is influenced by the annual climate. The methodology used in this study to predict forest C sinks can be transferred to other countries with some modifications. The ultimate verification of sink estimates should be based on comparison to empirical data, in which case the model-based stratification presented in this study can serve to improve the efficiency of the sampling design.

Dynamic nature of proteins - interpretation of residual dipolar couplings

Protein conformations and dynamics can be studied by nuclear magnetic resonance spectroscopy using dilute liquid crystalline samples. This work clarifies the interpretation of residual dipolar coupling data yielded by the experiments. It was discovered that unfolded proteins without any additional structure beyond that of a mere polypeptide chain exhibit residual dipolar couplings. Also, it was found that molecular dynamics induce fluctuations in the molecular alignment and doing so affect residual dipolar couplings. The finding clarified the origins of low order parameter values observed earlier. The work required the development of new analytical and computational methods for the prediction of intrinsic residual dipolar coupling profiles for unfolded proteins. The presented characteristic chain model is able to reproduce the general trend of experimental residual dipolar couplings for denatured proteins. The details of experimental residual dipolar coupling profiles are beyond the analytical model, but improvements are proposed to achieve greater accuracy. A computational method for rapid prediction of unfolded protein residual dipolar couplings was also developed. Protein dynamics were shown to modulate the effective molecular alignment in a dilute liquid crystalline medium. The effects were investigated from experimental and molecular dynamics generated conformational ensembles of folded proteins. It was noted that dynamics induced alignment is significant especially for the interpretation of molecular dynamics in small, globular proteins. A method of correction was presented. Residual dipolar couplings offer an attractive possibility for the direct observation of protein conformational preferences and dynamics. The presented models and methods of analysis provide significant advances in the interpretation of residual dipolar coupling data from proteins.

Performance of Finnish Mutual Funds: A Decomposition Approach

Mutual funds have increased in popularity among Finnish investors in recent years. In this study returns on domestic funds have been decomposed into several elements that measure different aspects of fund performance. The results indicate that fund managers in the long run tend to allocate fund capital between different stock categories in a profitable way. When it comes to the short term timing of their allocation decisions they are however unable to further improve overall performance. The evidence also suggests that managers possess the ability to pick above average performing stocks within the individual stock categories. During the investigated period most funds returned more than a broad benchmark index even after fees and indirect costs were taken into account.

Towards a Dynamic Communication Model: A Useful Tool in Relationship Communication

In order to bring insight into the emerging concept of relationship communication, concepts from two research traditions will be combined in this paper. Based on those concepts a new model, the dynamic relationship communication model, will be presented. Instead of a company perspective focusing on the integration of outgoing messages such as advertising, public relations and sales activities, it is suggested that the focus should be on factors integrated by the receiver. Such factors can be historical, future, external and internal factors. Thus, the model put a strong focus on the receiver in the communication process. The dynamic communication model is illustrated empirically using it as a tool on 78 short stories about communication. The empirical findings show that relationship communication occurs in some cases; in some cases it does not occur. The model is a useful tool in displaying relationship communication and how it differs from other communication. The importance of the time dimension, historical and future factors, in relationship communications is discussed. The possibility of reducing communications costs by the notion of relationship communication is discussed in managerial implications.

European aspen and hybrid aspen under changing environment : Leaf traits, growth and litter decomposition

Understanding the responses of species and ecosystems to human-induced global environmental change has become a high research priority. The main aim of this thesis was to investigate how certain environmental factors that relate to global change affect European aspen (Populus tremula), a keystone species in boreal forests, and hybrid aspen (P. tremula × P. tremuloides), cultivated in commercial plantations. The main points under consideration were the acclimatization potential of aspen through changes in leaf morphology, as well as effects on growth, leaf litter chemistry and decomposition. The thesis is based on two experiments, in which young aspen (< 1 year) were exposed either to an atmospheric pollutant [elevated ozone (O3)] or variable resource availability [water, nitrogen (N)]; and two field studies, in which mature trees (> 8 years) were growing in environments exposed to multiple environmental stress factors (roadside and urban environments). The field studies included litter decomposition experiments. The results show that young aspen, especially the native European aspen, was sensitive to O3 in terms of visible leaf injuries. Elevated O3 resulted in reduced biomass allocation to roots and accelerated leaf senescence, suggesting negative effects on growth in the long term. Water and N availability modified the frost hardening of young aspen: High N supply, especially when combined with drought, postponed the development of frost hardiness, which in turn may predispose trees to early autumn frosts. This effect was more pronounced in European aspen. The field studies showed that mature aspen acclimatized to roadside and urban environments by producing more xeromorphic leaves. Leaf morphology was also observed to vary in response to interannual climatic variation, which further indicates the ability of aspen for phenotypic plasticity. Intraspecific variation was found in several of the traits measured, although intraspecific differences in response to the abiotic factors examined were generally small throughout the studies. However, some differences between clones were found in sensitivity to O3 and the roadside environment. Aspen leaf litter decomposition was retarded in the roadside environment, but only initially. By contrast, decomposition was found to be faster in the urban than the rural environment throughout the study. The higher quality of urban litter (higher in N, lower in lignin and phenolics), as well as higher temperature, N deposition and humus pH at the urban site were factors likely to promote decay. The phenotypic plasticity combined with intraspecific variation found in the studies imply that aspen has potential for withstanding environmental changes, although some global change factors, such as rising O3 levels, may adversely affect its performance. The results also suggest that the multiple environmental changes taking place in urban areas which correspond closely with the main drivers of global change can modify ecosystem functioning by promoting litter decomposition, mediated partly by alterations in leaf litter quality.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).