Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2005
Authors
Inge Stupak Møller Karsten Raulund-Rasmussen Antti Asikainen Dominik Röser Anders Lunnan Erik Karltun M. Jonsell M. Schröder R. Ozolincius M. Mandre Talis Gaitnieks Ingeborg Callesen Nicholas Clarke Heljä-Sisko Helmisaari A. Indriksons Morten Ingerslev L. KairiukstisAbstract
The substitution of biomass for fossil fuels in energy consumption is a measure to mitigate global warming, and political action plans at European and national levels exist for an increased use. The use of forest biomass for energy can imply different economic and environmental advantages and disadvantages for the society, the energy sector and forestry. For the achievement of an increased and sustainable use of forest biomass for energy, the WOOD-EN-MAN project aimed at synthesis and creation of new knowledge within the field.
Authors
Rosario Mosello Monica Amoriello Tiziana Amoriello Silvia Arisci Andrea Carcano Nicholas Clarke John Derome Kirsti Derome Nils Konig Gabriele Tartari Erwin UlrichAbstract
No abstract has been registered
Authors
Toril Drabløs Eldhuset Holger Lange Nicholas Clarke Per Otto Flæte Erlend Ystrøm Haartveit Gro Wollebæk O. Janne KjønaasAbstract
Root and needle litter are the most important sources of organic carbon in forest soils. Their decomposition is thus important for the long-term storage of C in, and release of CO2 from, the soil. Different components in the organic matter will decompose with different speeds. NIRS (Near InfraRed Spectroscopy) is a relatively simple and promising way of analysing the composition of organic matter, but its use in forest soil and litter studies has been limited up to now. We will present preliminary results from litter decomposition studies in two forest ecosystems: Picea abies stands (30 and 120 years old) from Nordmoen, Norway, and uneven-aged P. abies stands with a mean age of 90 years and under different N treatments at Gårdsjön, Sweden. ags with litter collected from the stands have been buried in the soil for different time periods and have been analysed using a CHN-analyzer and NIRS. Two aspects will be discussed: a) model calibration and validation for C and N concentrations, and b) assessment of decomposability using NIRS.
Abstract
We investigate ecosystem dynamics by analyzing time series of measured variables. The information content and the complexity of these data are quantifed by methods from information theory.When applied to runoff (stream discharge) from catchments, the information/complexity relation reveals a simple non-trivial property for a large ensemble (more than 1800) of time series. This behaviour is so far not understood in hydrology.Using a multi-agent network receiving input resembling rainfall and producing output, we are able to reproduce the observed behaviour for the first time. The reconstruction is based on the identification and subsequent replacement of general patterns in the input. We thus consider runoff dynamics as the expression of an interactive learning problem of agents in an ecosystem.
Abstract
We investigate a data set of 160 river runoff time series at daily resolution from catchments in Southern Germany. Our aim is to seek spatial patterns for best parametrization of extreme value distributions to these data sets on one hand, and to analyze temporal instationarities of parameter estimates and extreme value attributes on the other. Conventional extreme value statistics and the calculation of return periods implicitly assume that the most extreme events are statistically independent. We demonstrate that this assumption is invalid, and that correlations, temporal as well as spatial, of arbitrary extent prevail instead. An important consequence is that the concept of return periods is obsolete. In order to find explanatory variables for the observed patterns, features of the waiting time distribution at a given relative threshold are correlated to catchment properties, such as size, mean runoff volume, elevation, and others. Finally, the effect of varying temporal resolution on the duration periods is exhibited. http://www.cosis.net/abstracts/EGU05/03192/EGU05-J-03192.pdf
Abstract
Instationarities in runoff time series are ubiquitous. However, simple trend analyses are often obscured by the presence of long-term correlations, and some instationarities are not simply changes in the mean or periodicities. Thus, wherever feasible, instationarities should be based on the full frequency distribution, or the cumulative distribution function (cdf), of the series. In this paper, we investigate the time-dependence of the empirical cdfs of 97 runoff datasets from the upper Danube basin applying a new pairwise test statistic, KSSUM, based on integrated differences of the cdfs. This is an improvement to the Kolmogorov-Smirnov (KS) test and was applied on different time scales, i.e. windows of varying size. If desired, the influence of drifts in the mean as well as heteroscedasticity can be excluded via z-transformations. The resulting time series of the KSSUM variable, either within a runoff series for different windows, or across series for the same period, is then subjected to the detection of spatiotemporal patterns with different methods. For most of the time series the underlying distributions move towards higher values in the long run. We also observed a periodic drift in the mean across all analysed gauges. It is furthermore possible to separate exceedingly variable runoff series from those with intermediate or small changes in value distribution on a regional basis, and thus to separate overall trends from local deviations at individual gauges. It is demonstrated that KSSUM is a sensitive method to investigate instationarities in sets of time series based on pairwise comparisons. An extension to a proper multivariate comparison is a possible further development. http://www.cosis.net/abstracts/EGU05/04198/EGU05-J-04198.pdf
Authors
D. Tønnesen Tor Myking Ingvald Røsberg Nicholas Clarke Brit Lisa Skjelkvåle Øyvind Kaste Thorbjørn LarssenAbstract
Impact assessment for a proposed LNG plant has been carried out for three potential locations in northwest Russia. The impact from the plant is small, and the critical loads for terrestrial ecosystems and aquatic ecosystems will not be exceeded at any of the 3 locations.
2004
Abstract
No abstract has been registered
Abstract
The quantitative expression and the regulation of chitinase-encoding genes ech30, ech42 and nag1 in Trichoderma atroviride P1 under varying growth conditions were investigated using real-time RTPCR, principle component and multivariate analyses. Twelve media combinations including 0.1% and 3% glucose as carbon source and no (0 mmol/L), low (10 mmol/L) and high (100 mmol/L)ammonium acetate as nitrogen source combined with or without colloidal chitin at 3 time intervals and 2 replications were applied to current study. The real-time RT-PCR analysis showed that the expression of ech30, ech42 and nag1 was regulated by the interaction of nitrogen, glucose and chitin under different growth conditions. The highest and earliest expressions of ech30 were induced by glucose and nitrogen starvation i.e. 0.1% glucose and 10 mmol/L ammonium acetate in the growth media. This was also the case for ech42 and nag1 but at a relatively low level. In contrast, high (3 %) glucose and high (100 mmol/L) ammonium acetate concentrations repressed the expression of all the genes studied. These results were confirmed by principle component and multivariate analyses.The effect of chitin on ech30, ech42 and nag1 expression varied depending on the concentrations of glucose and ammonium acetate.
Abstract
Conventional extreme value statistics and the calculation of return periods implicitly assume stationarity of distributions and statistical independence at least asymptotically (most extreme events).We demonstrate, using a collection of river runoff time series from Southern Germany, that these assumptions are invalid, and that temporal as well as spatial correlations prevail instead: temporal differences of distributions are nearly synchronized within a region, and there are systematic trends of percentiles especially at low flow conditions within the 20th century.As a consequence, the estimated return periods of a given threshold flow are fluctuating, in some cases even in a dramatic fashion. On the other hand, a general trend towards an increase in flood frequencies cannot be stated on basis of our investigations, in accordance with other recent findings (Mudelsee et al. 2003), but contrary to general expectations drawn from climate change studies.