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
Caroline Brophy John A. Finn Andreas Lüscher M. Suter Laura Kirwan Maria-Teresa Sebastià Aslaug Helgadottir Ole Hans Baadshaug G. Bélanger Alistair Black Rosemary P. Collins Jure Čop Sigridur Dalmannsdottir Ignacio Delgado Anjo Elgersma Mick Fothergill Bodil E. Frankow-Lindberg An Ghesquiere Barbara Golinska Piotr Golinski Philippe Grieu Anne-Maj Gustavsson Mats Höglind Olivier Huguenin-Elie Marit Jørgensen Zydre Kadziuliene Päivi Kurki Rosa Llurba Tor Lunnan Claudio Porqueddu Ulrich Thumm John ConnollyAbstract
Increasing species diversity often promotes ecosystem functions in grasslands, but sward diversity may be reduced over time through competitive interactions among species. We investigated the development of species’ relative abundances in intensively managed agricultural grassland mixtures over three years to identify the drivers of diversity change. A continental-scale field experiment was conducted at 31 sites using 11 different four-species mixtures each sown at two seed abundances. The four species consisted of two grasses and two legumes, of which one was fast establishing and the other temporally persistent. We modelled the dynamics of the four-species mixtures over the three-year period. The relative abundances shifted substantially over time; in particular, the relative abundance of legumes declined over time but stayed above 15% in year three at many sites. We found that species’ dynamics were primarily driven by differences in the relative growth rates of competing species and secondarily by density dependence and climate. Alongside this, positive diversity effects in yield were found in all years at many sites.
Authors
Gregory Taff Yang Shao Jie Ren Ruoyu ZhangAbstract
The accuracy in land-cover classification using remotely sensed imagery can be increased using Bayesian methods that incorporate prior probabilities of classes. However, estimating these prior probabilities can be expensive and data intensive. We propose methods to improve the classification accuracy using Bayesian methods to classify ambiguous (or low-confidence) pixels, using only the remotely sensed imagery or existing land-cover maps to estimate prior probabilities. We propose a spatial method that predicts prior probabilities from the original image, and a temporal method that incorporates land-cover maps from previous years. We illustrate our methods with a neural network (NN) classifier on the U.S. state of Iowa to classify crops into corn/soybean/other using moderate resolution imaging spectroradiometer (MODIS) data. USDA cropland data layers were aggregated to the 250-m resolution of MODIS and used as ground truth, based on a cropland mask from the National Land Cover Database. Results show that the spatial-prior-adjustment method, which predicts prior probabilities for low-confidence pixels based on class percentages of initial NN classification, increased overall accuracy of low-confidence pixels between 2% and 3.3% over the standard NN classification. The temporal-prior-adjustment method, which uses crop classes from the previous six years to estimate prior probabilities for the current year, shows significantly greater accuracy improvement for low-confidence pixels (almost 7%) over the standard NN classification. Increased benefit of the temporal-prior-adjustment method relative to the spatial-prior-adjustment method is likely due to increased information from more ground truth data (from previous years) than the spatial method.
Authors
Van Minh Dang Stephen Joseph Huu Tap Van Thi Lan Anh Mai Thi Minh Hoa Duong Simon Weldon Paul Munroe David Mitchell Sarasadat TaherymoosaviAbstract
Heavy metal contamination of crop lands surrounding mines in North Vietnam is a major environmental issue for both farmers and the population as a whole. Technology for the production of biochar at a village and household level has been successfully introduced into Vietnamese villages. This study was undertaken to determine if rice straw biochar produced in simple drum ovens could remediate contaminated land. Tests were also carried out to determine if biochar and apatite mixed together could be more effective than biochar alone. Incubation trials were carried out over 90 days in pots to determine the total changes in exchangeable Cd, Pb and Zn. Detailed tests were carried out to determine the mechanisms that bound the heavy metals to the biochar. It was found that biochar at 5% (BC5) and the mixture of biochar and apatite at 3% (BCA3) resulted in the greatest reduction of exchangeable forms of Cd, Pb and Zn. The increase in soil pH caused by adding biochar and apatite created more negative charge on the soil surface that promoted Pb, Zn and Cd adsorption. Heavy metals were mainly bound in the organic, Fe/Mn and carbonate fractions of the biochar and the mixture of biochar and apatite by either ion exchange, adsorption, dissolution/precipitation and through substitution of cations in large organic molecules.
Lecture – Impact of large carnivores on Norwegian grazing industry.
Inger Hansen, Geir-Harald Strand
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Stef Bokhorst Matty P. Berg Guro Kristine Edvinsen Jacintha Ellers Amber Heitman Laura Jaakola Hanne Mæhre Gareth K. Phoenix Hans Tømmervik Jarle W. BjerkeAbstract
Climate change is one of many ongoing human-induced environmental changes, but few studies consider interactive effects between multiple anthropogenic disturbances. In coastal sub-arctic heathland, we quantified the impact of a factorial design simulating extreme winter warming (WW) events (7 days at 6–7∘C) combined with episodic summer nitrogen (+N) depositions (5 kg N ha-1) on plant winter physiology, plant community composition and ecosystem CO2 fluxes of an Empetrum nigrum dominated heathland during 3 consecutive years in northern Norway. We expected that the +N would exacerbate any stress effects caused by the WW treatment. During WW events, ecosystem respiration doubled, leaf respiration declined (-58%), efficiency of Photosystem II (Fv/Fm) increased (between 26 and 88%), while cell membrane fatty acids showed strong compositional changes as a result of the warming and freezing. In particular, longer fatty acid chains increased as a result of WW events, and eicosadienoic acid (C20:2) was lower when plants were exposed to the combination of WW and +N. A larval outbreak of geometrid moths (Epirrita autumnata and Operophtera brumata) following the first WW led to a near-complete leaf defoliation of the dominant dwarf shrubs E. nigrum (-87%) and Vaccinium myrtillus (-81%) across all experimental plots. Leaf emergence timing, plant biomass or composition, NDVI and growing season ecosystem CO2 fluxes were unresponsive to the WW and +N treatments. The limited plant community response reflected the relative mild winter freezing temperatures (-6.6∘C to -11.8∘C) recorded after the WW events, and that the grazing pressure probably overshadowed any potential treatment effects. The grazing pressure and WW both induce damage to the evergreen shrubs and their combination should therefore be even stronger. In addition, +N could have exacerbated the impact of both extreme events, but the ecosystem responses did not support this. Therefore, our results indicate that these sub-arctic Empetrum-dominated ecosystems are highly resilient and that their responses may be limited to the event with the strongest impact.
Authors
Victor Rueda-Ayala Hella Ellen Ahrends Stefan Siebert Thomas Gaiser Hubert Hüging Frank EwertAbstract
Impacts of nutrient supply and different cultivars (genotypes) on actual yield levels have been studied before, but the long-term response of yield trends is hardly known. We present the effects of 24 different fertilizer treatments on long-term yield trends (1953–2009) of winter wheat, winter rye, sugar beet and potato, with improved cultivars changing gradually over time. Data was obtained from the crop rotation within the long-term fertilization experiment at Dikopshof, Germany. Yield trends were derived as the slope regression estimates between adjusted yield means and polynomials of the first year of cultivation of each tested cultivar, when tested for more than two years. A linear trend fitted best all data and crops. Yields in highly fertilized treatments increased linearly, exceeding 0.08 t ha−1 a−1 for both, winter wheat and winter rye, and ≥0.30 and ≥0.20 t ha−1 a−1 for sugar beet and potato fresh matter yields. Yield trends of winter cereals and sugar beet increased over time at N rates ≥40 kg ha−1 a−1, being 0.04–0.10 t ha−1 a−1 for cereals and 0.26–0.34 t ha−1 a−1 for sugar beet, although N rates >80 kg ha−1 a−1 produced a stronger effect. Nitrogen was the most influential nutrient for realisation of the genetic yield potential. Additional supply of P and K had an effect on yield trends for rye and sugar beet, when N fertilization was also sufficient; high K rates benefited potato yield trends. We highlight the importance of adequate nutrient supply for maintaining yield progress to actually achieve the crop genetic yield potentials. The explicit consideration of the interaction between crop fertilization and genetic progress on a long-term basis is critical for understanding past and projecting future yield trends. Long-term fertilization experiments provide a suitable data source for such studies.
Authors
Kristi Parro Kajar Köster Kalev Jogiste Katrin Seglinš Allan Sims John A. Stanturf Marek MetslaidAbstract
Boreal forests are an important carbon (C) sink and fire is the main natural disturbance, directly affecting the Ccycle via emissions from combustion of biomass and organic matter and indirectly through long-term changes in C-dynamics including soil respiration. Carbon dioxide (CO2) emission from soil (soil respiration) is one of the largest fluxes in the global C-cycle. Recovery of vegetation, organic matter and soil respiration may be influenced by the intensity of post-fire management such as salvage logging. To study the impact of forest fire, fire and salvage, and recovery time on soil respiration and soil C and N content, we sampled two permanent research areas in north-western Estonia that were damaged by fire: Vihterpalu (59°13′ N 23°49′ E) in 1992 and Nõva (59°10′ N 23°45′ E) in 2008. Three types of sample plots were established: 1) unburned control with no harvesting (CO); 2) burned and uncleared (BU); and 3) burned and cleared (BC). Measurements were made in 2013, 21 years after wildfire in Vihterpalu and 5 years after wildfire in Nõva. Soil respiration ranged from 0.00 to 1.38 g CO2 m−2 h−1. Soil respiration in the burned and cleared areas (BC) was not reduced compared to burned and uncleared (BU) areas but the average soil respiration in unburned control areas was more than twice the value in burned areas (average soil respiration in CO areas was 0.34 CO2 m−2 h−1, versus 0.16 CO2 m−2 h−1, the average soil respiration of BC and BU combined). Recovery over 20 years was mixed; respiration was insignificantly lower on younger than older burned sites (when BC and BU values were combined, the average values were 0.15 vs. 0.17 g CO2 m−2 h−1, respectively); soil-C was greater in the older burned plots than the younger (when BC and BU values were combined, the average values were 9.71 vs. 5.99 kgm−2, respectively); but root biomass in older and recently burned areas was essentially the same (average 2.23 and 2.11 kgm−2, respectively); soil-N was highest on burned areas 20 years after fire. Twenty years post-fire may be insufficient time for carbon dynamics to fully recover on these low productivity sandy sites.
Abstract
In cold-temperate climate with high soil water content in spring, the farmer often faces the choice between topsoil compaction during seedbed preparation and delayed sowing, both of which may reduce attainable cereal yield. The objective of this study was to explore whether future climate change with increasing precipitation would aggravate this dilemma. We generated weather based on historical and projected future climate in Southeastern and Central Norway. Using this weather data as input, we simulated spring workability, attainable yield, timeliness costs, and mechanization management with a workability model and a mechanization model. The projected climate changes resulted in improved workability for spring fieldwork and higher attainable yield in South-eastern Norway, and either positive or negative changes in Central Norway compared to historical conditions. We observed a general increase in variability of workability and attainable yield, and a larger risk of extremely unfavourable years in the most unfavourable scenarios in Central Norway. Changes in profitability and mechanization management were small, but followed the same pattern. The negative effects in the most unfavourable climate scenarios in Central Norway were in contrast to positive effects in earlier studies. We explained discrepancies by differences in research methods and purpose. However, simulated sowing dates of annual crops should consider workability of the soil, in terms of water content. Under worst-case conditions, in need of a certain time window to complete their spring fieldwork, farmers might adapt to impaired spring workability by working the soil at higher water content than simulated in our study. The consequence would be a larger loss of attainable yield and less profitability in the future. We anticipate that negative effects may also be expected in other northern cold-temperate regions with high soil water content in spring.
Authors
Seyda Özkan-Gülzari Bouda Vosough Ahmadi Alistair W. StottAbstract
Impaired animal health causes both productivity and profitability losses on dairy farms, resulting in inefficient use of inputs and increase in greenhouse gas (GHG) emissions produced per unit of product (i.e. emissions intensity). Here, we used subclinical mastitis as an exemplar to benchmark alternative scenarios against an economic optimum and adjusted herd structure to estimate the GHG emissions intensity associated with varying levels of disease. Five levels of somatic cell count (SCC) classes were considered namely 50,000 (i.e. SCC50), 200,000, 400,000, 600,000 and 800,000 cells/mL (milliliter) of milk. The effects of varying levels of SCC on milk yield reduction and consequential milk price penalties were used in a dynamic programming (DP) model that maximizes the profit per cow, represented as expected net present value, by choosing optimal animal replacement rates. The GHG emissions intensities associated with different levels of SCC were then computed using a farm-scale model (HolosNor). The total culling rates of both primiparous (PP) and multiparous (MP) cows for the five levels of SCC scenarios estimated by the model varied from a minimum of 30.9% to a maximum of 43.7%. The expected profit was the highest for cows with SCC200 due to declining margin over feed, which influenced the DP model to cull and replace more animals and generate higher profit under this scenario compared to SCC50. The GHG emission intensities for the PP and MP cows with SCC50 were 1.01 kg (kilogram) and 0.95 kg carbon dioxide equivalents (CO 2 e) per kg fat and protein corrected milk (FPCM), respectively, with the lowest emissions being achieved in SCC50. Our results show that there is a potential to reduce the farm GHG emissions intensity by 3.7% if the milk production was improved through reducing the level of SCC to 50,000 cells/mL in relation to SCC level 800,000 cells/mL. It was concluded that preventing and/or controlling subclinical mastitis consequently reduces the GHG emissions per unit of product on farm that results in improved profits for the farmers through reductions in milk losses, optimum culling rate and reduced feed and other variable costs. We suggest that further studies exploring the impact of a combination of diseases on emissions intensity are warranted.