Aerobic carbon-cycle related microbial communities in boreal peatlands: responses to water-level drawdown

Boreal peatlands represent a considerable portion of the global carbon (C) pool. Water-level drawdown (WLD) causes peatland drying and induces a vegetation change, which affects the decomposition of soil organic matter and the release of greenhouse gases (CO2 and CH4). The objective of this thesis was to study the microbial communities related to the C cycle and their response to WLD in two boreal peatlands. Both sampling depth and site type had a strong impact on all microbial communities. In general, bacteria dominated the deeper layers of the nutrient-rich fen and the wettest surfaces of the nutrient-poor bog sites, whereas fungi seemed more abundant in the drier surfaces of the bog. WLD clearly affected the microbial communities but the effect was dependent on site type. The fungal and methane-oxidizing bacteria (MOB) community composition changed at all sites but the actinobacterial community response was apparent only in the fen after WLD. Microbial communities became more similar among sites after long-term WLD. Litter quality had a large impact on community composition, whereas the effects of site type and WLD were relatively minor. The decomposition rate of fresh organic matter was influenced slightly by actinobacteria, but not at all by fungi. Field respiration measurements in the northern fen indicated that WLD accelerates the decomposition of soil organic matter. In addition, a correlation between activity and certain fungal sequences indicated that community composition affects the decomposition of older organic matter in deeper peat layers. WLD had a negative impact on CH4 oxidation, especially in the oligotrophic fen. Fungal sequences were matched to taxa capable of utilizing a broad range of substrates. Most of the actinobacterial sequences could not be matched to characterized taxa in reference databases. This thesis represents the first investigation of microbial communities and their response to WLD among a variety of boreal peatland habitats. The results indicate that microbial community responses to WLD are complex but dependent on peatland type, litter quality, depth, and variable among microbes.

Lignocellulose degradation and humus modification by the fungus Paecilomyces inflatus

Composting is the biological conversion of solid organic waste into usable end products such as fertilizers, substrates for mushroom production and biogas. Although composts are highly variable in their bulk composition, composting material is generally based on lignocellulose compounds derived from agricultural, forestry, fruit and vegetable processing, household and municipal wastes. Lignocellulose is very recalcitrant; however it is rich and abundant source of carbon and energy. Therefore lignocellulose degradation is essential for maintaining the global carbon cycle. In compost, the active component involved in the biodegradation and conversion processes is the resident microbial population, among which microfungi play a very important role. In composting pile the warm, humid, and aerobic environment provides the optimal conditions for their development. Microfungi use many carbon sources, including lignocellulosic polymers and can survive in extreme conditions. Typically microfungi are responsible for compost maturation. In order to improve the composting process, more information is needed about the microbial degradation process. Better knowledge on the lignocellulose degradation by microfungi could be used to optimize the composting process. Thus, this thesis focused on lignocellulose and humic compounds degradation by a microfungus Paecilomyces inflatus, which belongs to a flora of common microbial compost, soil and decaying plant remains. It is a very common species in Europe, North America and Asia. The lignocellulose and humic compounds degradation was studied using several methods including measurements of carbon release from 14C-labelled compounds, such as synthetic lignin (dehydrogenative polymer, DHP) and humic acids, as well as by determination of fibre composition using chemical detergents and sulphuric acid. Spectrophotometric enzyme assays were conducted to detect extracellular lignocellulose-degrading hydrolytic and oxidative enzymes. Paecilomyces inflatus secreted clearly extracellular laccase to the culture media. Laccase was involved in the degradation process of lignin and humic acids. In compost P. inflatus mineralised 6-10% of 14C-labelled DHP into carbon dioxide. About 15% of labelled DHP was converted into water-soluble compounds. Also humic acids were partly mineralised and converted into water-soluble material, such as low-molecular mass fulvic acid-like compounds. Although laccase activity in aromatics-rich compost media clearly is connected with the degradation process of lignin and lignin-like compounds, it may preferentially effect the polymerisation and/or detoxification of such aromatic compounds. P. inflatus can degrade lignin and carbohydrates also while growing in straw and in wood. The cellulolytic enzyme system includes endoglucanase and β-glucosidase. In P. inflatus the secretion of these enzymes was stimulated by low-molecular-weight aromatics, such as soil humic acid and veratric acid. When strains of P. inflatus from different ecophysiological origins were compared, indications were found that specific adaptation strategies needed for lignocellulosics degradation may operate in P. inflatus. The degradative features of these microfungi are on relevance for lignocellulose decomposition in nature, especially in soil and compost environments, where basidiomycetes are not established. The results of this study may help to understand, control and better design the process of plant polymer conversion in compost environment, with a special emphasis on the role of ubiquitous microfungi.

Water quality estimation by optical remote sensing in boreal lakes

In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.

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.

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.