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.
2017
Abstract
In the Nordic countries, changes in pore structure during winter can affect e.g. water transport capacity in soils after winter. A reduction in pore space can cause an increase in runoff volume due to snowmelt and rain, resulting in flooding and soil erosion. This study quantified the effect of freezing-thawing cycles (FTCs) on the macropore structure of a silt and a sandy soil. Six consecutive FTCs were applied to intact soil samples, which were scanned after 0, 1, 2, 4 and 6 FTCs with an industrial X-ray scanner. Using state-of-the-art image processing and analysis techniques, changes in soil macropore network characteristics were quantified. The results showed that freezing-thawing affected the looser sandy soil more than the silt with its more cohesive structure. However, in both soils freezing-thawing had a negative effect on properties of macropore networks (e.g. reduction in macroporosity, thickness and specific surface area of macropores). These findings can help improve understanding of how undisturbed soils react to different winter conditions, which can be beneficial in the development of models for predicting flooding and soil erosion.
Abstract
The moisture status of the upper 10cm of the soil profile is a key variable for the prediction of a catchment's hydrological response to precipitation, and of pivotal importance to the estimation of trafficability. Prediction, and even mapping, of topsoil water content is complicated, not in the least because of its large spatial heterogeneity. In IRIDA, an EU/JPI project, measurements, models and weather predictions will be applied to estimate the soil moisture status at the sub-field scale in near-real time. The project is in its early stages, during which the relevant parameters will be selected that will allow for soil moisture mapping on agricultural fields at a 10 m resolution.
Authors
Diego Faustolo Alves Bispo Marx Leandro Naves Silva Joao Jose Granate de Sa e Melo Marques Marianne Bechmann Pedro Velloso Gomes Batista Nilton CuriAbstract
Identifying and ranking nutrient loss risk areas are important steps towards integrated catchment management. This study aimed to apply the P index model at the Posses catchment, south of the state of Minas Gerais, Brazil. We applied the P index for the current land use at the Posses catchment and for two hypothetical scenarios: scenario 1, in which P fertilizer was applied to all land uses, except for native forests; and scenario 2, which considered the use of P fertilizer as in scenario 1, and that the Environmental Protection Areas referring to the riparian forests and springs were totally restored. Considering current land use, almost the whole catchment area (91.4%) displayed a low P loss risk. The highest P index was associated to croplands and eucalyptus plantations. Regarding scenario 1, areas under pasture fell into the low (15.1%), medium (45.5%), high (27.1%) and very high (12.3%) P index categories. Environmental Protection Areas on scenario 2 decreased the P loss risk from the scenario 1 in 37.6%. Hence, the model outputs indicate that the reforestation of buffer zones can decrease P loss risk in the case increasing use of P fertilizer. The P index model is a potential support tool to promote judicious use of fertilizers and conservation practices at the Posses catchment.
Authors
Annette Dathe Attila Nemes Esther Bloem Matthew Patterson Daniel Gimenez Anna Angyal Johannes Koestel Nicholas JarvisAbstract
No abstract has been registered
Authors
Annette Dathe Attila Nemes Esther Bloem Matthew Patterson Daniel Gimenez Julia Szocs Johannes Koestel Nicholas JarvisAbstract
No abstract has been registered
Authors
Annette Dathe Attila Nemes Esther Bloem Matthew Patterson Daniel Gimenez Julia Szocs Johannes Koestel Nicholas JarvisAbstract
No abstract has been registered
Lecture – What is IRIDA? And some results so far.
Johannes Deelstra, Robert Barneveld, Csilla Farkas
Abstract
No abstract has been registered
Authors
Roger Holten Frederik Bøe Marit Almvik Marianne Stenrød Mats Larsbo Nicholas Jarvis Ole Martin EkloAbstract
No abstract has been registered
Authors
Roger Holten Frederik Bøe Marit Almvik Marianne Stenrød Mats Larsbo Nicholas Jarvis Ole Martin EkloAbstract
No abstract has been registered
Abstract
Farmers are exposed to climate change and uncertainty about how that change will develop. As farm incomes, in Norway and elsewhere, greatly depend on government subsidies, the risk of a policy change constitutes an additional uncertainty source. Hence, climate and policy uncertainty could substantially impact agricultural production and farm income. However, these sources of uncertainty have, so far, rarely been combined in food production analyses. The aim of this study was to determine the effects of a combination of policy and climate uncertainty on agricultural production, land use, and social welfare in Norway. Output yield distributions of spring wheat and timothy, a major forage grass, from simulations with the weatherdriven crop models, CSM-CERES-Wheat and, LINGRA, were processed in the a stochastic version Jordmod, a price-endogenous spatial economic sector model of the Norwegian agriculture. To account for potential effects of climate uncertainty within a given future greenhouse gas emission scenario on farm profitability, effects on conditions that represented the projected climate for 2050 under the emission scenario A1B from the 4th assessment report of the Intergovernmental Panel on Climate Change and four Global Climate Models (GCM) was investigated. The uncertainty about the level of payment rates at the time farmers make their management decisions was handled by varying the distribution of payment rates applied in the Jordmod model. These changes were based on the change in the overall level of agricultural support in the past. Three uncertainty scenarios were developed and tested: one with climate change uncertainty, another with payment rate uncertainty, and a third where both types of uncertainty were combined. The three scenarios were compared with results from a deterministic scenario where crop yields and payment rates were constant. Climate change resulted in on average 9% lower cereal production, unchanged grass production and more volatile crop yield as well as 4% higher farm incomes on average compared to the deterministic scenario. The scenario with a combination of climate change and policy uncertainty increased the mean farm income more than a scenario with only one source of uncertainty. On the other hand, land use and farm labour were negatively affected under these conditions compared to the deterministic case. Highlighting the potential influence of climate change and policy uncertainty on the performance of the farm sector our results underline the potential error in neglecting either of these two uncertainties in studies of agricultural production, land use and welfare.