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.
2019
Abstract
No abstract has been registered
Abstract
The measurement network Integrated Carbon Observation System (ICOS) is dedicated to the quantification of fluxes of CO2, H2O, N2O and CH4 at the boundary between vegetation surfaces and the lower atmosphere. The implementation of observations sites follows strict protocols and a challenging labelling process to ensure standardized intercomparable observations. We report on our experiences in attempting to establish the only Norwegian ICOS Ecosystem site thus far, NO-Hur, located in an old-growth spruce forest at Hurdal in Southeast Norway. NOHur is planned as a class 2 site, with the option to an upgrade to class 1 later. The instrumentation and sensors needed, the requirements for spatial homogeneity and a detailed analysis of a digital terrain model are presented. The current status of the tower construction, the preliminary measurements obtained with the existing ICOScertified equipment at a test site, and the plans for integrating the measurements operationally into the network are shown
Abstract
The measurement network Integrated Carbon Observation System (ICOS) is dedicated to the quantification of fluxes of CO2, H2O, N2O and CH4 at the boundary between vegetation surfaces and the lower atmosphere. The implementation of observations sites follows strict protocols and a challenging labelling process to ensure standardized intercomparable observations. We report on our experiences in attempting to establish the only Norwegian ICOS Ecosystem site thus far, NO-Hur, located in an old-growth spruce forest at Hurdal in Southeast Norway. NOHur is planned as a class 2 site, with the option to an upgrade to class 1 later. The instrumentation and sensors needed, the requirements for spatial homogeneity and a detailed analysis of a digital terrain model are presented. The current status of the tower construction, the preliminary measurements obtained with the existing ICOScertified equipment at a test site, and the plans for integrating the measurements operationally into the network are shown
Abstract
Many nonlinear methods of time series analysis require a minimal number of observations in the hundreds to thousands, which is not always easy to achieve for observations of environmental systems. Eddy Covariance (EC) measurements of the carbon exchange between the atmosphere and vegetation provide a noticeable exception. They are taken at high temporal resolution, typically at 20 Hz. This generates very long time series (many millions of data points) even for short measurement periods, rendering finite size effects unimportant. In this presentation, we investigate high-resolution raw data of 3D wind speed, CO2 concentrations, water vapor and temperature measured at a young forest plantation in Southeast Norway since July 2018. Guiding for the analysis is the gain or added value of the high resolution compared to more aggregated data, i.e. the scaling behavior of nonlinear properties of the time series. We present results of complexity analysis, Tarnopolski diagrams, q-Entropy, Hurst analysis, Empirical Mode Decomposition and Singular System Analysis. This provides detailed insights into the nature of dynamics of carbon fluxes across this system boundary at different temporal scales.
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Roger Holten Frederik Bøe Marit Almvik Sheela Katuwal Marianne Stenrød Mats Larsbo Nicholas Jarvis Ole Martin EkloAbstract
No abstract has been registered
Authors
Xiao Huang Höglind Mats Knut Bjørkelo Torben Christensen Kjetil Fadnes Teresa Gómez de la Bárcena Åsa Kasimir Leif Klemedtsson Bjørn Kløve Anders Lyngstad Mikhail Mastepanov Hannu Marttila Marcel van Oijen Peter Petros Ina Pohle Jagadeesh Yeluripati Hanna Marika SilvennoinenAbstract
Cultivated organic soils account for ∼7% of Norway’s agricultural land area, and they are estimated to be a significant source of greenhouse gas (GHG) emissions. The project ‘Climate smart management practices on Norwegian organic soils’ (MYR), commissioned by the Research Council of Norway (decision no. 281109), aims to evaluate GHG (e.g. carbon dioxide, methane and nitrous oxide) emissions and impacts on biomass productivity from three land use types (cultivated, abandoned and restored) on organic soils. At the cultivated sites, impacts of drainage depth and management intensity will be measured. We established experimental sites in Norway covering a broad range of climate and management regimes, which will produce observational data in high spatiotemporal resolution during 2019-2021. Using state-of-the-art modelling techniques, MYR aims to predict the potential GHG mitigation under different scenarios. Four models (BASGRA, DNDC, Coup and ECOSSE) will be further developed according to the soil properties, and then used independently in simulating biogeochemical processes and biomass dynamics in the different land uses. Robust parameterization schemes for each model will be based in the observational data from the project for both soil and crop combinations. Eventually, a multi-model ensemble prediction will be carried out to provide scenario analyses by 2030 and 2050. By integrating experimental results and modelling, the project aims at generating useful information for recommendations on environment-friendly use of Norwegian peatlands.
Authors
Xiao Huang Mats Höglind Knut Bjørkelo Torben Christensen Kjetil Fadnes Teresa Gómez de la Bárcena Åsa Kasimir Leif Klemedtsson Bjørn Kløve Anders Lyngstad Mikhail Mastepanov Hannu Marttila Marcel Van Oijen Peter Petros Ina Pohle Jagadeesh Yeluripati Hanna Marika SilvennoinenAbstract
Cultivated organic soils (7-8% of Norway’s agricultural land area) are economically important sources for forage production in some regions in Norway, but they are also ‘hot spots’ for greenhouse gas (GHG) emissions. The project ‘Climate smart management practices on Norwegian organic soils’ (MYR; funded by the Research Council of Norway, decision no. 281109) will evaluate how water table management and the intensity of other management practices (i.e. tillage and fertilization intensity) affects both GHG emissions and forage’s quality & production. The overall aim of MYR is to generate useful information for recommendations on climate-friendly management of Norwegian peatlands for both policy makers and farmers. For this project, we established two experimental sites on Norwegian peatlands for grass cultivation, of which one in Northern (subarctic, continental climate) and another in Southern (temperate, coastal climate) Norway. Both sites have a water table level (WTL) gradient ranging from low to high. In order to explore the effects of management practices, controlled trials with different fertilization strategies and tillage intensity will be conducted at these sites with WTL gradients considered. Meanwhile, GHG emissions (including carbon dioxide, methane and nitrous oxide), crop-related observations (e.g. phenology, production), and hydrological conditions (e.g. soil moisture, WTL dynamics) will be monitored with high spatiotemporal resolution along the WTL gradients during 2019-2021. Besides, MYR aims at predicting potential GHG mitigation under different scenarios by using state-of-the-art modelling techniques. Four models (BASGRA, Coup, DNDC and ECOSSE), with strengths in predicting grass growth, hydrological processes, soil nitrification-denitrification and carbon decomposition, respectively, will be further developed according to the soil properties. Then these models will be used independently to simulate biogeochemical and agroecological processes in our experimental fields. Robust parameterization schemes will be based on the observational data for both soil and crop combinations. Eventually, a multi-model ensemble prediction will be carried out to provide scenario analyses by 2030 and 2050. We will couple these process-based models with optimization algorithm to explore the potential reduction in GHG emissions with consideration of production sustenance, and upscale our assessment to regional level.