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.Metsien maaperän hiilivarastolla on merkittävä rooli metsien hiilitaseessa. Hakkuutähteiden keruu hakkuiden jälkeen vähentää puustosta maaperään siirtyvää hiilen määrää ja tämä hiilivarastomuutos on merkittävä verrattuna muihin hakkuutähteiden energiakäytön aiheuttamiin kasvihuonekaasupäästöihin. Metsien maaperä on merkittävä hiilen varasto. Ilmastonmuutos ja erilaiset metsänkäsittelyt vaikuttavat paitsi puuston biomassan myös maaperän hiilivarastoon. Näitä vaikutuksia ei kuitenkaan vielä täysin tunneta. Kansainvälinen ilmastosopimus kuitenkin velvoittaa sopijamaat raportoimaan myös maaperän hiilivarastossa tapahtuvat muutokset. Maaperän hiilivaraston muutosten arviointi mittaamalla on hyvin vaikeaa ja työlästä, koska varaston spatiaalinen vaihtelu on suurta verrattuna ajallisiin muutoksiin. Tämän vuoksi hiilivaraston ja sen muutosten arvioinnissa käytetään usein malleja. Tässä väitöskirjassa kehitettiin ja testattiin kivennäismaiden metsien orgaanisen aineen hajoamista ja maaperän hiilivaraston dynamiikkaa kuvaava YASSO-malli. Mallilla pyrittiin kuvaamaan tärkeimmät hiilivaraston dynamiikkaan vaikuttavat tekijät, mutta silti pitämään malli niin yksinkertaisena, että sen toimintaperiaatteiden ymmärtäminen ja käyttö sovelluksissa olisi helppoa. Mallin toimintaa arvioitiin tarkastelemalla mallitulosten herkkyyttä mallin parametriarvojen muutoksille, tutkimalla mallitulosten tarkkuutta epävarmuusanalyysin avulla ja vertaamalla mallituloksia mitattuihin havaintoihin ja toisen maamallin antamiin tuloksiin. Epävarmuus- ja herkkyysanalyysien mukaan YASSO-mallin hiilivarastoarviot ovat epävarmoja. Hiilivarastomuutosten arviot sen sijaan ovat verrattain tarkkoja. Testit mitattuja aineistoja vastaan vastaan osoittivat, että malli onnistuu kohtalaisesti kuvaamaan erilaisten karikkeiden hajoamisen erilaisissa ilmasto-olosuhteissa ja maaperän kokonaishiilivaraston erilaisissa suomalaisissa metsiköissä. Mallilla tutkittiin hakkuutähteiden talteenoton ja energiakäytön vaikutusta maaperän hiilivarastoon ja maaperän roolia Suomen metsien hiilitaseessa. Mallin dynaaminen lähestymistapa osoittautui tehokkaaksi sovelluksissa, joissa se yhdistettiin metsikkömalliin tai inventointitietoihin ja biomassa- ja karikemalleihin

Säävaihtelun ja ääri-ilmiöiden aiheuttamien riskien hallinta haavoittuvuuden vähentämiseksi ja puskurointi- ja palautumiskyvyn parantamiseksi

Loppuraportti, Ilmapuskuri201

Data format for model in- and output

A common format for model input variables and model output variables has been defined to be distributed to modellers participating in the model inter-comparison and improvement. The aim of common formats is to support the communication between the modellers, those providing empirical data of the experiments and those analysing the simulation results. The input format facilitates the model application in a way that each cropping-system to be modelled will be defined in the same way. Data will be delivered in EXCEL sheets with sub-tables for each block of inputs. Tables are mostly organized in a way that allows export and sequential read-in by the models. The common output format enables effective processing of results estimating model performance indicators.

Greenhouse Impact Due to the Use of Combustible Fuels: Life Cycle Viewpoint and Relative Radiative Forcing Commitment

Extensive information on the greenhouse impacts of various human actions is important in developing effective climate change mitigation strategies. The greenhouse impacts of combustible fuels consist not only of combustion emissions but also of emissions from the fuel production chain and possible effects on the ecosystem carbon storages. It is important to be able to assess the combined, total effect of these different emissions and to express the results in a comprehensive way. In this study, a new concept called relative radiative forcing commitment (RRFC) is presented and applied to depict the greenhouse impact of some combustible fuels currently used in Finland. RRFC is a ratio that accounts for the energy absorbed in the Earth system due to changes in greenhouse gas concentrations (production and combustion of fuel) compared to the energy released in the combustion of fuel. RRFC can also be expressed as a function of time in order to give a dynamic cumulative picture on the caused effect. Varying time horizons can be studied separately, as is the case when studying the effects of different climate policies on varying time scales. The RRFC for coal for 100 years is about 170, which means that in 100 years 170 times more energy is absorbed in the atmosphere due to the emissions of coal combustion activity than is released in combustion itself. RRFC values of the other studied fuel production chains varied from about 30 (forest residues fuel) to 190 (peat fuel) for the 100-year study period. The length of the studied time horizon had an impact on the RRFC values and, to some extent, on the relative positions of various fuels

Effects of climate and historical adaptation measures on barley yield trends in Finland

201

Using impact response surfaces to analyse the likelihood of impacts on crop yield under probabilistic climate change

Conventional methods of modelling impacts of future climate change on crop yields often rely on a limited selection of projections for representing uncertainties in future climate. However, large ensembles of climate projections offer an opportunity to estimate yield responses probabilistically. This study demonstrates an approach to probabilistic yield estimation using impact response surfaces (IRSs). These are constructed from a set of sensitivity simulations that explore yield responses to a wide range of changes in temperature and precipitation. Options for adaptation and different levels of future atmospheric carbon dioxide concentration [CO2] defined by representative concentration pathways (RCP4.5 and RCP8.5) were also considered. Model-based IRSs were combined with probabilistic climate projections to estimate impact likelihoods for yields of spring barley (Hordeum vulgare L.) in Finland during the 21st century. Probabilistic projections of climate for the same RCPs were overlaid on IRSs for corresponding [CO2] levels throughout the century and likelihoods of yield shortfall calculated with respect to a threshold mean yield for the baseline (1981–2010). Results suggest that cultivars combining short pre- and long post-anthesis phases together with earlier sowing dates produce the highest yields and smallest likelihoods of yield shortfall under future scenarios. Higher [CO2] levels generally compensate for yield losses due to warming under the RCPs. Yet, this does not happen fully under the more moderate warming of RCP4.5 with a weaker rise in [CO2], where there is a chance of yield shortfall throughout the century. Under the stronger warming but more rapid [CO2] increase of RCP8.5, the likelihood of yield shortfall drops to zero from mid-century onwards. Whilst the incremental IRS-based approach simplifies the temporal and cross-variable complexities of projected climate, it was found to offer a close approximation of evolving future likelihoods of yield impacts in comparison to a more conventional scenario-based approach. The IRS approach is scenario-neutral and existing plots can be used in combination with any new scenario that falls within the sensitivity range without the need to perform new runs with the impact model. A single crop model is used for demonstration, but an ensemble IRS approach could additionally capture impact model uncertainties.peerReviewe

A tool for sustainability impact assessment (ToSIA)of forest-wood chains linked with a database of sustainability indicators collected within the EFORWOOD project

Within the EFORWOOD project new approaches to assess the sustainability impacts of forest-wood chains (FWC) using indicators of environmental, social and economic sustainability were developed