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.
2020
Sammendrag
As a carbon dioxide removal measure, the Norwegian government is currently considering a policy of large-scale planting of spruce (Picea abies (L) H. Karst) on lands in various states of natural transition to a forest dominated by deciduous broadleaved tree species. Given the aspiration to bring emissions on balance with removals in the latter half of the 21st century in effort to limit the global mean temperature rise to “well below” 2°C, the effectiveness of such a policy is unclear given relatively low spruce growth rates in the region. Further convoluting the picture is the magnitude and relevance of surface albedo changes linked to such projects, which typically counteract the benefits of an enhanced forest CO2 sink in high-latitude regions. Here, we carry out a rigorous empirically based assessment of the terrestrial carbon dioxide removal (tCDR) potential of large-scale spruce planting in Norway, taking into account transient developments in both terrestrial carbon sinks and surface albedo over the 21st century and beyond. We find that surface albedo changes would likely play a negligible role in counteracting tCDR, yet given low forest growth rates in the region, notable tCDR benefits from such projects would not be realized until the second half of the 21st century, with maximum benefits occurring even later around 2150. We estimate Norway's total accumulated tCDR potential at 2100 and 2150 (including surface albedo changes) to be 447 (±240) and 852 (±295) Mt CO2-eq. at mean net present values of US$ 12 (±3) and US$ 13 (±2) per ton CDR, respectively. For perspective, the accumulated tCDR potential at 2100 represents around 8 years of Norway's total current annual production-based (i.e., territorial) CO2-eq. emissions.
Sammendrag
The aim of this work was to calculate farm specific LCAs for milk-production on 200 dairy farms in Central Norway, where 185 farmed conventional and 15 according to organic standards. We assume that there are variations in environmental emission drivers between farms and therefore also variation in indicators. We think that information can be utilized to find management improvements on individual farms. Farm specific data on inputs and production for the calendar years 2014 to 2016 were used. The LCAs were calculated for purchased products and on farm-emissions, including atmospheric deposition, biological nitrogen fixation, use of fertilizer and manure. The enteric methane emission from digestion was calculated for different animal groups. The functional unit was one kg energy- corrected milk (ECM) delivered at farm-gate. For the 200 dairy farms there were huge variations of farm characteristics, environmental per- formance and economic outcome. On average, the organic farms produced milk with a lower carbon footprint (1.2 kg CO2 eq./kg ECM) than the conventional ones (1.4 kg CO2 eq./kg ECM). The organic farms had also a lower energy intensity (3.1 MJ/kg ECM) and nitrogen intensity (5.0 kg N/kg N) than their conventional colleagues (4.1 MJ/kg ECM and 6.9 kg N/kg N respectively). The contribution margin was better on the organic farms with 6.6 NOK/kg ECM compared to the conventional with 5.9 NOK/kg ECM. The average levels of the environmental indicators were comparable but slightly higher than findings in other international studies. The current study proved that the FARMnor model allows to calculate LCAs for large number of individual farms. The results show that the environmental performance and economic outcome vary between farms. We recommend that farm specific LCA-results are used to unveil what needs to be changed for improving a farm’s environmental performance.
Forfattere
Bo Liu Keith Davies Avice HallSammendrag
Silicon is found in all plants and the accumulation of silicon can improve plant tolerance to biotic stress. Strawberry powdery mildew (Podosphaera aphanis) and two-spotted spider mite (Tetranychus urticae) are both detrimental to strawberry production worldwide. Two field trials were done on a UK commercial strawberry farm in 2014 and 2015, to assess the effects of silicon nutrient applied via the fertigation system on P. aphanis and T. urticae. The silicon treatments decreased the severity of both P. aphanis and T. urticae in two consecutive years on different cultivars. The percentage leaf area infected with P. aphanis mycelium from silicon treated plants were 2.19 (in 2014) and 0.41 (in 2015) compared with 3.08 (in 2014) and 0.57 (in 2015) from the untreated plants. The etiology of the pathogen as measured by the Area Under the Disease Progress Curve from silicon (with and without fungicides) treatments was 152.7 compared with 217.5 from non-silicon (with and without fungicides) treatments for the overall period of 2014–2015. The average numbers of T. urticae recorded on strawberry leaves were 1.43 (in 2014) and 1.83 (in 2015) in plants treated with silicon compared with 8.82 (in 2014) and 6.69 (in 2015) in untreated plants. The silicon contents of the leaves from the silicon alone treatment were 26.8 μg mg-1 (in 2014) and 22.2 μg mg-1 (in 2015) compared with 19.7 μg mg-1 (in 2014) and 21.4 μg mg-1 (in 2015) from the untreated. The silicon nutrient root application contributed to improved plant resilience against P. aphanis and T. urticae. Silicon could play an important role in broad spectrum control of pests and diseases in commercial strawberry production.
Forfattere
Mehdi Daemi-Saeidabad Abdolali Shojaeiyan Adam Vivian-Smith Hans K. Stenøien Mohsen Falahati-AnbaranSammendrag
Many studies on Heracleum have shown poor correspondence between observed molecular clusters and established taxonomic classification amongst closely related species. This might reflect both unresolved taxonomy but perhaps also a lack of good genetic markers. This lack of appropriate and cost effective species-specific genetic markers hinders a resolved relationship for the species complex, and this in turn causes profound management challenges for a genus that contains both endemic species, with important ecological roles, and species with an invasive potential. Microsatellites are traditionally considered markers of choice for comprehensive, yet inexpensive, analyses of genetic variation, including examination of population structure, species identity, linkage map construction and cryptic speciation. In this study, we have used double digest restriction site associated DNA sequencing (ddRADseq) to develop microsatellite markers in Heracleum rechingeri. Genomic DNA from three individuals were digested with Sbf1 and Nde1 and size selected for library construction. The size-selected fragments were sequenced on an Ion Torrent sequencer and a total of 54 microsatellite sequences were bioinformatically confirmed. Twenty five loci were then tested for amplification, resulting in 19 of these being successfully amplified across eight species, comprising both the so-called thick-stemmed species (H. persicum, H. rechingeri, H. gorganicum and H. lasiopetalum), and thin-stemmed species (H. anisactis, H. pastinasifolium and H. transcaucasicum). Both Bayesian and distance-based clustering, and principal coordinate analyses clearly separated these into two groups. Surprisingly, three H. pastinacifolium populations were not separated from populations of the morphologically similar endemic species, H. anisactis, suggesting lack of genetic differentiation. Likewise, high genetic similarity was found between H. persicum and H. rechingeri populations, questioning taxonomic separation at the species level between these taxa. Further analyses are needed to re-evaluate the taxonomic significance of observed morphological variability currently applied to distinguish these sister taxa. Nevertheless, our results represent progress in the effort to develop cost-efficient molecular tools for species discrimination in this genus.
Forfattere
Marja Jalli Janne Kaseva Björn Andersson Andrea Ficke Lise Nistrup-Jørgensen Antanas Ronis Timo Kaukoranta Jens-Erik Ørum Annika DjurleSammendrag
Fungal plant diseases driven by weather factors are common in European wheat and barley crops. Among these, septoria tritici blotch (Zymoseptoria tritici), tan spot (Pyrenophora tritici-repentis), and stagonospora nodorum blotch (Parastagonospora nodorum) are common in the Nordic-Baltic region at variable incidence and severity both in spring and winter wheat fields. In spring barley, net blotch (Pyrenophora teres), scald (Rhynchosporium graminicola, syn. Rhynchosporium commune) and ramularia leaf spot (Ramularia collo-cygni) are common yield limiting foliar diseases. We analysed data from 449 field trials from 2007 to 2017 in wheat and barley crops in the Nordic-Baltic region and explored the differences in severity of leaf blotch diseases between countries and years, and the impact of the diseases on yield. In the experiments, septoria tritici blotch dominated in winter wheat in Denmark and southern Sweden; while in Lithuania, both septoria tritici blotch and tan spot were common. In spring wheat, stagonospora nodorum blotch dominated in Norway and tan spot in Finland. Net blotch and ramularia leaf blotch were the most severe barley diseases over large areas, while scald occurred more locally and had less yield impact in all countries. Leaf blotch diseases, with severity >50% at DC 73–77, caused an average yield loss of 1072 kg/ha in winter wheat and 1114 kg/ha in spring barley across all countries over 5 years. These data verify a large regional and yearly variation in disease severity, distribution and impact on yield, emphasizing the need to adapt fungicide applications to the actual need based on locally adapted risk assessment systems.
Sammendrag
Key message A locus on wheat chromosome 2A was found to control feld resistance to both leaf and glume blotch caused by the necrotrophic fungal pathogen Parastagonospora nodorum. Abstract The necrotrophic fungal pathogen Parastagonospora nodorum is the causal agent of Septoria nodorum leaf blotch and glume blotch, which are common wheat (Triticum aestivum L.) diseases in humid and temperate areas. Susceptibility to Septoria nodorum leaf blotch can partly be explained by sensitivity to corresponding P. nodorum necrotrophic efectors (NEs). Susceptibility to glume blotch is also quantitative; however, the underlying genetics have not been studied in detail. Here, we genetically map resistance/susceptibility loci to leaf and glume blotch using an eight-founder wheat multiparent advanced generation intercross population. The population was assessed in six feld trials across two sites and 4 years. Seedling infltration and inoculation assays using three P. nodorum isolates were also carried out, in order to compare quantitative trait loci (QTL) identifed under controlled conditions with those identifed in the feld. Three signifcant feld resistance QTL were identifed on chromosomes 2A and 6A, while four signifcant seedling resistance QTL were detected on chromosomes 2D, 5B and 7D. Among these, QSnb.niab-2A.3 for feld resistance to both leaf blotch and glume blotch was detected in Norway and the UK. Colocation with a QTL for seedling reactions against culture fltrate from a Norwegian P. nodorum isolate indicated the QTL could be caused by a novel NE sensitivity. The consistency of this QTL for leaf blotch at the seedling and adult plant stages and culture fltrate infltration was confrmed by haplotype analysis. However, opposite efects for the leaf blotch and glume blotch reactions suggest that diferent genetic mechanisms may be involved.
Forfattere
Johannes Breidenbach Lars T. Waser Misganu Debella-Gilo Johannes Schumacher Johannes Rahlf Marius Hauglin Stefano Puliti Rasmus AstrupSammendrag
Nation-wide Sentinel-2 mosaics were used with National Forest Inventory (NFI) plot data for modelling and subsequent mapping of spruce-, pine-, and deciduous-dominated forest in Norway at a 16 m × 16 m resolution. The accuracies of the best model ranged between 74% for spruce and 87% for deciduous forest. An overall accuracy of 90% was found on stand level using independent data from more than 42 000 stands. Errors mostly resulting from a forest mask reduced the model accuracies by ∼10%. The produced map was subsequently used to generate model-assisted (MA) and poststratified (PS) estimates of species-specific forest area. At the national level, efficiencies of the estimates increased by 20% to 50% for MA and up to 90% for PS. Greater minimum numbers of observations constrained the use of PS. For MA estimates of municipalities, efficiencies improved by up to a factor of 8 but were sometimes also less than 1. PS estimates were always equally as or more precise than direct and MA estimates but were applicable in fewer municipalities. The tree species prediction map is part of the Norwegian forest resource map and is used, among others, to improve maps of other variables of interest such as timber volume and biomass.
Sammendrag
Cereal grain contaminated by Fusarium mycotoxins is undesirable in food and feed because of the harmful health effects of the mycotoxins in humans and animals. Reduction of mycotoxin content in grain by cleaning and size sorting has mainly been studied in wheat. We investigated whether the removal of small kernels by size sorting could be a method to reduce the content of mycotoxins in oat grain. Samples from 24 Norwegian mycotoxin-contaminated grain lots (14 from 2015 and 10 from 2018) were sorted by a laboratory sieve (sieve size 2.2 mm) into large and small kernel fractions and, in addition to unsorted grain samples, analyzed with LC-MS-MS for quantification of 10 mycotoxins. By removing the small kernel fraction (on average 15% and 21% of the weight of the samples from the two years, respectively), the mean concentrations of HT-2+T-2 toxins were reduced by 56% (from 745 to 328 µg/kg) in the 2015 samples and by 32% (from 178 to 121 µg/kg) in the 2018 samples. Deoxynivalenol (DON) was reduced by 24% (from 191 to 145 µg/kg) in the 2018 samples, and enniatin B (EnnB) by 44% (from 1059 to 594 µg/kg) in the 2015 samples. Despite low levels, our analyses showed a trend towards reduced content of DON, ADON, NIV, EnnA, EnnA1, EnnB1 and BEA after removing the small kernel fraction in samples from 2015. For several of the mycotoxins, the concentrations were considerably higher in the small kernel fraction compared to unsorted grain. Our results demonstrate that the level of mycotoxins in unprocessed oat grain can be reduced by removing small kernels. We assume that our study is the first report on the effect of size sorting on the content of enniatins (Enns), NIV and BEA in oat grains.
Forfattere
Bertrand Guenet Benoit Gabrielle Claire Chenu Dominique Arrouays Jerome Balesdent Martial Bernoux Elisa Bruni Jean-Pierre Caliman Remi Cardinael Songchao Chen Philippe Ciais Dominique Desbois Julien Fouche Stefan Frank Cathrine Henault Emanuele Lugato Victoria Naipal Thomas Nesme Michael Obersteiner Sylvain Pellerin David S. Powlson Daniel Rasse Frédéric Rees Jean-Francois Soussana Yang Su Hanqin Tian Hugo Valin Feng ZhouSammendrag
To respect the Paris agreement targeting a limitation of global warming below 2°C by 2100, and possibly below 1.5 °C, drastic reductions of greenhouse gas emissions are mandatory but not sufficient. Large‐scale deployment of other climate mitigation strategies are also necessary. Among these, increasing soil organic carbon (SOC) stocks is an important lever because carbon in soils can be stored for long periods and land management options to achieve this already exist and have been widely tested. However, agricultural soils are also an important source of nitrous oxide (N2O), a powerful greenhouse gas, and increasing SOC may influence N2O emissions, likely causing an increase in many cases, thus tending to offset the climate change benefit from increased SOC storage. Here, we review the main agricultural management options for increasing SOC stocks. We evaluate the amount of SOC that can be stored as well as resulting changes in N2O emissions to better estimate the climate benefits of these management options. Based on quantitative data obtained from published meta‐analyses and from our current level of understanding, we conclude that the climate mitigation induced by increased SOC storage is generally overestimated if associated N2O emissions are not considered but, with the exception of reduced tillage, is never fully offset. Some options (e.g, biochar or non‐pyrogenic C amendment application) may even decrease N2O emissions.
Sammendrag
In the EU 2020 biodiversity strategy, maintaining and enhancing forest biodiversity is essential. Forest managers and technicians should include biodiversity monitoring as support for sustainible forest management and conservation issues, through the adoption of forest biodiversity indices. The present study investigates the potential of a new type of Structure from Motion (SfM) photogrammetry derived variables for modelling forest structure indicies, which do not require the availability of a digital terrain model (DTM) such as those obtainable from Airborne Laser Scanning (ALS) surveys. The DTM-independent variables were calculated using raw 3D UAV photogrammetric data for modeling eight forest structure indices which are commonly used for forest biodiversity monitoring, namely: basal area (G); quadratic mean diameter (DBHmean); the standard deviation of Diameter at Breast Height (DBHσ); DBH Gini coefficient (Gini); the standard deviation of tree heights (Hσ); dominant tree height (Hdom); Lorey’s height (Hl); and growing stock volume (V). The study included two mixed temperate forestsareas withadifferenttype ofmanagement, with onearea, left unmanagedfor thepast 50years while the other being actively managed. A total of 30 fieldsample plots were measured in the unmanaged forest, and 50 field plots were measured in the actively managed forest. The accuracy of UAV DTM-independent predictions was compared with a benchmark approach based on traditional explanatory variables calculated from ALS data. Finally, DTM-independent variables were used to produce wall-to-wall maps of the forest structure indices in the two test areas and to estimate the mean value and its uncertainty according to a model-assisted regression estimators. DTM-independent variables led to similar predictive accuracy in terms of root mean square error compared to ALS in both study areas for the eight structure indices (DTM-independent average RMSE% = 20.5 and ALS average RMSE% = 19.8). Moreover, we found that the model-assisted estimation, with both DTM-independet and ALS, obtained lower standar errors (SE) compared to the one obtained by modelbased estimation using only field plots. Relative efficiency coefficient (RE) revealed that ALS-based estimates were, on average, more efficient (average RE ALS = 3.7) than DTM-independent, (average RE DTM-independent = 3.3). However, the RE for the DTM-independent models was consistently larger than the one from theALSmodelsfortheDBH-relatedvariables(i.e.G,DBHmean,andDBHσ)andforV.Thishighlightsthepotential of DTM-independent variables, which not only can be used virtually on any forests (i.e., no need of a DTM), but also can produce as precise estimates as those from ALS data for key forest structural variables and substantially improve the efficiency of forest inventories.