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.
2018
Authors
Arne StensvandAbstract
No abstract has been registered
Authors
Inge Stupak Tat Smith Nicholas Clarke Teodorita Al-Seadi Lina Beniušienė Niclas Scott Bentsen Quentin Cheung Virginia Dale Jinke van Dam Rocio Diaz-Chavez Uwe Fritsche Martyn Futter Jianbang Gan Kaija Hakala Thomas Horschig Martin Junginger Yoko Kitigawa Brian Kittler Keith Kline Charles Lalonde Søren Larsen Dagnija Lazdina Thuy P. T. Mai-Moulin Maha Mansoor Edmund Mupondwa Shyam Nair Nathaniel Newlands Liviu Nichiforel Marjo Palviainen John Stanturf Kay Schaubach Johanny Arilexis Perez Sierra Vita Tilvikiene Brian Titus Daniela Thrän Sergio Ugarte Liisa Ukonmaanaho Iveta Varnagyrite-Kabasinkiene Maria WellischAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
We investigated whether diversification and/or structural change would improve Norwegian agriculture. Using a flexible technology approach to account for different technologies, we assessed economies of scope and scale of dairy and cropping farms, including regional differences. We fitted translog cost functions to farm-level panel data for the period 1991–2014. We found both economies of scope and scale on the farms. Dairy farms have an economic incentive to integrate dairying with cropping in all regions of Norway, and vice versa. Thus, policy makers should eschew interventions that inhibit diversification or structural change and that increase the costs of food production.
Authors
Volkmar Timmermann Mari Mette Tollefsrud Halvor Solheim Isabella Børja Nina Elisabeth Nagy Ari HietalaAbstract
No abstract has been registered
Abstract
In recent years, rising competition for water coupled with new environmental regulations has exerted pressure on water allocations for turfgrass irrigation. In this article, we reviewed published scientific and industry evidence on the agronomic and environmental impacts of turfgrass irrigation using a robust systematic review methodology. Our focus was on the links between (i) irrigation management (amount and frequency), (ii) agronomic responses to irrigation (turf quality, growth rates and rooting) and (iii) environmental impacts (nitrogen leaching). Based on an initial screening of 653 studies and data extracted from 83 papers, our results show that in most cases, under moderate levels of deficit irrigation (50%–60% of actual evapotranspiration), turf quality can be maintained at an acceptable level but with lower water consumption compared to irrigating back to field capacity. Irrigation beyond field capacity was found to increase the risk of nutrient leaching. However, evidence also showed that the concentration and total loss of urn:x-wiley:09312250:media:jac12265:jac12265-math-0001 in leachate were influenced more by nitrogen (N) rates, soil characteristics, turfgrass species and turfgrass growth rates than by irrigation practices. Our analyses suggest that turfgrass irrigation should be scheduled to apply water at moderate levels of deficit irrigation, sufficient to maintain turfgrass quality but limited to promote a deep and extensive rooting system. The findings provide new insights and valuable evidence for both scientists and practitioners involved in turfgrass research and management.
Authors
Gudrun Schwilch Tatenda Lemann Örjan Berglund Carlo Camarotto Artemi Cerdà Ioannis N. Daliakopoulos Silvia Kohnová Dominika Krzeminska Teodoro Maranon René Rietra Grzegorz Siebielec Johann Thorsson Mark Tibbett Sandra Valente Hedwig van Delden Jan van den Akker Simone Verzandvoort Nicoleta Olimpia Vrînceanu Christos Zoumides Rudi HesselAbstract
Only a few studies have quantified and measured ecosystem services (ES) specifically related to soil. To address this gap, we have developed and applied a methodology to assess changes in ecosystem services, based on measured or estimated soil property changes that were stimulated by soil management measures (e.g., mulching, terracing, no-till). We applied the ES assessment methodology in 16 case study sites across Europe representing a high diversity of soil threats and land use systems. Various prevention and remediation measures were trialled, and the changes in manageable soil and other natural capital properties were measured and quantified. An Excel tool facilitated data collection, calculation of changes in ecosystem services, and visualization of measured short-term changes and estimated long-term changes at plot level and for the wider area. With this methodology, we were able to successfully collect and compare data on the impact of land management on 15 different ecosystem services from 26 different measures. Overall, the results are positive in terms of the impacts of the trialled measures on ecosystem services, with 18 out of 26 measures having no decrease in any service at the plot level. Although methodological challenges remain, the ES assessment was shown to be a comprehensive evaluation of the impacts of the trialled measures, and also served as an input to a stakeholder valuation of ecosystem services at local and sub-national levels.
Abstract
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.
Authors
Leif Sundheim Christer Magnusson Arild Sletten Per Hans Micael Wendell Guro Brodal Åshild Ergon Halvor Solheim Anne Marte Tronsmo Trond RafossAbstract
No abstract has been registered
Authors
Rachel Cassidy Philip Jordan Marianne Bechmann Brian Kronvang Katarina Kyllmar Mairead ShoreAbstract
Achieving an operational compromise between spatial coverage and temporal resolution in national scale river water quality monitoring is a major challenge for regulatory authorities, particularly where chemical concentrations are hydrologically dependent. The efficacy of flow-weighted composite sampling (FWCS) approaches for total phosphorus (TP) sampling (n = 26–52 analysed samples per year), previously applied in monitoring programmes in Norway, Sweden and Denmark, and which account for low to high flow discharges, was assessed by repeated simulated sampling on high resolution TP data. These data were collected in three research catchments in Ireland over the period 2010–13 covering a base-flow index range of 0.38 to 0.69. Comparisons of load estimates were also made with discrete (set time interval) daily and sub-daily sampling approaches (n = 365 to >1200 analysed samples per year). For all years and all sites a proxy of the Norwegian sampling approach, which is based on re-forecasting discharge for each 2-week deployment, proved most stable (median TP load estimates of 87–98%). Danish and Swedish approaches, using long-term flow records to set a flow constant, were only slightly less effective (median load estimates of 64–102% and 80–96%, respectively). Though TP load estimates over repeated iterations were more accurate using the discrete approaches, particularly the 24/7 approach (one sample every 7 h in a 24 bottle sampler - median % load estimates of 93–100%), composite load estimates were more stable, due to the integration of multiple small samples (n = 100–588) over a deployment.