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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.

2018

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Insufficient reference database coverage is a widely recognized limitation of molecular ecology ap-proaches which are reliant on database matches for assignment of function or identity. Here, we use datafrom 65 amplicon high-throughput sequencing (HTS) datasets targeting the internal transcribed spacer(ITS) region of fungal rDNA to identify substrates and geographic areas whose underrepresentation in theavailable reference databases could have meaningful impact on our ability to draw ecological conclu-sions. A total of 14 different substrates were investigated. Database representation was particularly poorfor the fungal communities found in aquatic (freshwater and marine) and soil ecosystems. Aquaticecosystems are identified as priority targets for the recovery of novel fungal lineages. A subset of the datarepresenting soil samples with global distribution were used to identify geographic locations andterrestrial biomes with poor database representation. Database coverage was especially poor in tropical,subtropical, and Antarctic latitudes, and the Amazon, Southeast Asia, Australasia, and the Indian sub-continent are identified as priority areas for improving database coverage in fungi.

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In spite of its important role as predator of small game species, estimating the density of red fox Vulpes vulpes has been hampered by the species’ highly variable ranging pattern and elusive behavior. DNA analysis from scats combined with spatially explicit capture–recapture (SECR) modeling might remedy this. In a 50-km2 coniferous forest in southeast Norway, we collected scats on logging roads in late winter. DNA was extracted, amplified, and genotyped using 11 microsatellite markers. Of 184 samples collected, 126 were genotyped successfully, of which 46 (36.5%) produced individual genetic profiles. Twenty-five of these were different individuals: 13 females and 12 males. Nine of them were identified in multiple scats; mean recapture rate among all was 1.8/animal. Applying a conventional capture–recapture model (CAPWIRE) to the genotyped samples, 36 (95% CI 26–52) different individuals were estimated to have been present in the area during the sampling period. For estimating population density, we constructed three differently sized occupancy areas based on distances between recaptures, viz. ½ and 1/1 mean maximum distance moved (MMDM) and the local convex hull home range method (LoCoH). Areas varied from 60 km2 (½MMDM) to 112 km2 (MMDM), producing density estimates of 0.60 and 0.32 foxes/km2, respectively; the 95% LoCoH range method produced an estimate of 0.44 animals/km2 . Based on SECR modeling, the density was estimated at 0.38 (95% CI 0.21–0.70) animals/km2 . Smaller confidence intervals are expected with more appropriate sampling design than used in this pilot study.

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The Earth magnetic field (or geomagnetic field, GMF) is a natural component of our planet and variations of the GMF are perceived by plants with a still uncharacterized magnetoreceptor. The purpose of this work was to assess the effect of near null magnetic field (NNMF, ∼40 nT) on Arabidopsis thaliana Col0 root ion modulation. A time-course (from 10 min to 96 h) exposure of Arabidopsis to NNMF was compared to GMF and the content of some cations (NH4 +, K+, Ca2+ and Mg2+) and anions (Cl−, SO4 =, NO3 − and PO4 =) was evaluated by capillary electrophoresis. The expression of several cation and anion channel- and transporter-related genes was assessed by gene microarray. A few minutes after exposure to NNMF, Arabidopsis roots responded with a significant change in the content and gene expression of all nutrient ions under study, indicating the presence of a plant magnetoreceptor that responds immediately to MF variations by modulating channels, transporters and genes involved in mineral nutrition. The response of Arabidopsis to reduced MF was a general reduction of plant ion uptake and transport. Our data suggest the importance to understand the nature and function of the plant magnetoreceptor for future space programs involving plant growth in environments with a reduced MF.

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Background: Over the last decades, many forest simulators have been developed for the forests of individual European countries. The underlying growth models are usually based on national datasets of varying size, obtained from National Forest Inventories or from long-term research plots. Many of these models include country- and location-specific predictors, such as site quality indices that may aggregate climate, soil properties and topography effects. Consequently, it is not sensible to compare such models among countries, and it is often impossible to apply models outside the region or country they were developed for. However, there is a clear need for more generically applicable but still locally accurate and climate sensitive simulators at the European scale, which requires the development of models that are applicable across the European continent. The purpose of this study is to develop tree diameter increment models that are applicable at the European scale, but still locally accurate. We compiled and used a dataset of diameter increment observations of over 2.3 million trees from 10 National Forest Inventories in Europe and a set of 99 potential explanatory variables covering forest structure, weather, climate, soil and nutrient deposition. Results: Diameter increment models are presented for 20 species/species groups. Selection of explanatory variables was done using a combination of forward and backward selection methods. The explained variance ranged from 10% to 53% depending on the species. Variables related to forest structure (basal area of the stand and relative size of the tree) contributed most to the explained variance, but environmental variables were important to account for spatial patterns. The type of environmental variables included differed greatly among species. Conclusions: The presented diameter increment models are the first of their kind that are applicable at the European scale. This is an important step towards the development of a new generation of forest development simulators that can be applied at the European scale, but that are sensitive to variations in growing conditions and applicable to a wider range of management systems than before. This allows European scale but detailed analyses concerning topics like CO2 sequestration, wood mobilisation, long term impact of management, etc.

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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.

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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.