Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2018
Sammendrag
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Sammendrag
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Redaktører
Heidi KnutsenSammendrag
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Sammendrag
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Forfattere
Arne Verstraeten Elena Gottardini Nicolas Bruffaerts Bruno de Vos Elena Vanguelova Fabiana Cristofolini Sue Benham Pasi Rautio Liisa Ukonmaanaho Päivi Merilä Peter Waldner Marijke Hendrickx Gerrit Genouw Peter Roskams Nathalie Cools J Neirynck Anita Nussbaumer Mathias Neumann Nicholas Clarke Volkmar Timmermann Karin Hansen Hans-Peter Diettrich Manuel Nicolas Maria Schmitt Anne Thimonier Katrin Meusburger Silvio Schueler Anna KowalskaSammendrag
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Forfattere
Cecilie Marie Mejdell Grete H. Meisfjord Jørgensen Knut Egil BøeSammendrag
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Forfattere
Monika Suškevičs Sebastian Eiter Stanislav Martinat Dina Stober Elis Vollmer Cheryl L. de Boer Matthias BucheckerSammendrag
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Sammendrag
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Sammendrag
The present work focuses on an assessment of the applicability of groundwater table (GWT) measures in the modelling of soil water retention characteristics (SWRC) using artificial neural network (ANN) methods. Model development, testing, validation and verification were performed using data collected across two decades from soil profiles at full-scale research objects located in Southwest Poland. A positive effect was observed between the initial GWT position data and the accuracy of soil water reserve estimation. On the other hand, no significant effects were observed following the implementation of GWT fluctuation data over the entire growing season. The ANN tests that used data of either soil water content or GWT position gave analogous results. This revealed that the easily obtained data (temperature, precipitation and GWT position) are the most accurate modelling parameters. These outcomes can be used to simplify modelling input data/parameters/variables in the practical implementation of the proposed SWRC modelling variants.
Forfattere
Marcin Strozecki Hanna Marika Silvennoinen Pawel Strzelinski Bogdan Heronim ChojnickiSammendrag
It is important to quantify carbon decomposition to assess the reforestation impact on the forest floor C stocks. Estimating the loss of C stock in a short-term perspective requires measuring changes in soil respiration. This is not trivial due to the contribution of both soil microbes and vegetation to the measured CO2 flux. However, C stable isotopes can be used to partition the respiration and potentially to assess how much of the recalcitrant C stock in the forest floor is lost. Here, we measured the soil respiration at two forest sites where different regeneration methods were applied, along with an intact forest soil for reference. In so doing, we used a closed dynamic chamber for measuring respiration and the 13C composition of the emitted CO2. The chamber measurements were then supplemented with the soil organic carbon analysis and its δ13C content. The mean δ13C-CO2 estimates for the source of the CO2 were -26.4, -27.9 and -29.5‰, for the forest, unploughed and ploughed, respectively. The 13C of the soil organic carbon did, not differ significantly between sites. The higher soil respiration rate at the forest, as compared to the unploughed site, could be attributed to the autotrophic respiration by the forest floor vegetation.