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.
2020
Authors
Fatima Heinicke Xiangfu Zhong Karola Manuela Zucknick Johannes Breidenbach Arvind Yegambaram Meenakshi Sundaram Siri Tennebø Flåm Magnus Leithaug Marianne Dalland Simon Rayner Benedicte Alexandra Lie Gregor GilfillanAbstract
High-throughput sequencing has emerged as the favoured method to study microRNA (miRNA) expression, but biases introduced during library preparation have been reported. We recently compared the performance (sensitivity, reliability, titration response and differential expression) of six commercially-available kits on synthetic miRNAs and human RNA, where library preparation was performed by the vendors. We hereby supplement this study with data from two further commonly used kits (NEBNext, NEXTflex) whose manufacturers initially declined to participate. NEXTflex demonstrated the highest sensitivity, which may reflect its use of partially-randomized adapter sequences, but overall performance was lower than the QIAseq and TailorMix kits. NEBNext showed intermediate performance. We reaffirm that biases are kit specific, complicating the comparison of miRNA datasets generated using different kits.
Authors
Steen Magnussen Ronald E. McRoberts Johannes Breidenbach Thomas Nord-Larsen Göran Ståhl Lutz Fehrmann Sebastian SchnellAbstract
Background: Large area forest inventories often use regular grids (with a single random start) of sample locations to ensure a uniform sampling intensity across the space of the surveyed populations. A design-unbiased estimator of variance does not exist for this design. Oftentimes, a quasi-default estimator applicable to simple random sampling (SRS) is used, even if it carries with it the likely risk of overestimating the variance by a practically important margin. To better exploit the precision of systematic sampling we assess the performance of five estimators of variance, including the quasi default. In this study, simulated systematic sampling was applied to artificial populations with contrasting covariance structures and with or without linear trends. We compared the results obtained with the SRS, Matérn’s, successive difference replication, Ripley’s, and D’Orazio’s variance estimators. Results: The variances obtained with the four alternatives to the SRS estimator of variance were strongly correlated, and in all study settings consistently closer to the target design variance than the estimator for SRS. The latter always produced the greatest overestimation. In populations with a near zero spatial autocorrelation, all estimators, performed equally, and delivered estimates close to the actual design variance. Conclusion: Without a linear trend, the SDR and DOR estimators were best with variance estimates more narrowly distributed around the benchmark; yet in terms of the least average absolute deviation, Matérn’s estimator held a narrow lead. With a strong or moderate linear trend, Matérn’s estimator is choice. In large populations, and a low sampling intensity, the performance of the investigated estimators becomes more similar. Keywords: Spatial autocorrelation, Linear trend, Model based, Design biased, Matérn variance, Successive difference replication variance, Geary contiguity coefficient, Random site effects
Authors
Johannes BreidenbachAbstract
No abstract has been registered
Authors
Johannes BreidenbachAbstract
No abstract has been registered
Abstract
Forest inventories provide predictions of stand means on a routine basis from models with auxiliary variables from remote sensing as predictors and response variables from field data. Many forest inventory sampling designs do not afford a direct estimation of the among-stand variance. As consequence, the confidence interval for a model-based prediction of a stand mean is typically too narrow. We propose a new method to compute (from empirical regression residuals) an among-stand variance under sample designs that stratify sample selections by an auxiliary variable, but otherwise do not allow a direct estimation of this variance. We test the method in simulated sampling from a complex artificial population with an age class structure. Two sampling designs are used (one-per-stratum, and quasi systematic), neither recognize stands. Among-stand estimates of variance obtained with the proposed method underestimated the actual variance by 30-50%, yet 95% confidence intervals for a stand mean achieved a coverage that was either slightly better or at par with the coverage achieved with empirical linear best unbiased estimates obtained under less efficient two-stage designs.
Authors
Arne SteffenremAbstract
No abstract has been registered
Authors
Arne SteffenremAbstract
No abstract has been registered
Abstract
Purpose Biogas residues, digestates, contain valuable nutrients and are therefore suitable as agricultural fertilizers. However, the application of fertilizers, including digestates, can enhance greenhouse gas (GHG) emissions. In this study different processes and post-treatments of digestates were analyzed with respect to triggered GHG emissions in soil. Methods In an incubation experiment, GHG emissions from two contrasting soils (chernozem and sandy soil) were compared after the application of digestate products sampled from the process chain of a food waste biogas plant: raw substrate, digestate (with and without bentonite addition), digestates after separation of liquid and solid phase and composted solid digestate. In addition, the solid digestate was sampled at another plant. Results The plant, where the solid digestate originated from, and the soil type influenced nitrous oxide (N2O) emissions significantly over the 38-day experiment. Composting lowered N2O emissions after soil application, whereas bentonite addition did not have a significant effect. High peaks of N2O emissions were observed during the first days after application of acidified, liquid fraction of digestate. N2O emissions were strongly correlated to initial ammonium (NH4+) content. Conclusion Fertilization with dewatered digestate (both fractions) increased N2O emission, especially when applied to soils high in nutrients and organic matter.
Abstract
The Norwegian coastal goat is a national and endangered breed. Coastal goat populations are mainly divided with a large mainland and two small island populations. The objective of this study is to describe genetic diversity in the feral Skorpa island population and its relationship to the mainland coastal goat population (Selje) using the Norwegian milk goat population as a reference. Analyses were based on 96 samples genotyped by the CaprineSNP50 Beadchip from three populations; 7 Skorpa (SK), 37 Selje (SE) and 52 Norwegian milk goats (MG). The SK population had significantly less genetic variation and higher levels of inbreeding than the two other populations. It was more distant from the two mainland populations than they were from each other. The marginal contribution of the SK population to genetic diversity was small. Means of introducing genetic diversity into the SK population should be considered if the population is prioritized for conservation.
Abstract
Genetic selection in commercial sheep production has mainly focussed on production traits and to a large extent ignoring behavioural traits, such as response towards predators. The Icelandic leadersheep is a sheep breed selected and known for its special behavioural traits, such as leading the flock and bringing it home from pasture in case of danger. Those traits are also said to be beneficial in areas with a high predator pressure. In this study, it was investigated if there are behavioural differences in sheep flocks with and without a leadersheep present. Behaviour of sheep flocks was observed before, during and after a predator test, in small groups of Icelandic sheep with or without a leadersheep in the group. Eleven groups of Icelandic sheep with six ewes in each group were observed in a test arena while a human, a dog and a drone passed through the pasture. Six of the groups included a leadersheep and the remaining five did not. Groups including a leadersheep spent more time grazing after both the human and dog test, indicating a faster recovering to normal behaviour. They were also located close to the exit during the dog test compared to groups without a leadersheep, fitting well with the assertion that leadersheep bring the flock home in case of danger. During the drone test, groups with a leadersheep however spent more time moving around compared to the other groups. Since the sheep had experienced both humans and dogs before, but not drones, this may indicate that groups with leadersheep recovered quickly from the figurants they had experienced before, but tended to react more in the test which was a new situation. In conclusion, it appears likely that the earlier selection for leader traits in the leadersheep have indeed changed both their own behaviour and also that this has an effect on the behaviour of group members.