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

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Abstract

Since Emaraviruses have been discovered in 2007 several new species were detected in a range of host plants. Five genome segments of a novel Emaravirus from mosaic‐diseased Eurasian aspen (Populus tremula) have been completely determined. The monocistronic, segmented ssRNA genome of the virus shows a genome organisation typical for Emaraviruses encoding the viral RNA‐dependent RNA polymerase (RdRP, 268.2 kDa) on RNA1 (7.1 kb), a glycoprotein precursor (GPP, 73.5 kDa) on RNA2 (2.3 kb), the viral nucleocapsid protein (N, 35.6 kDa) on RNA3 (1.6 kb), and a putative movement protein (MP, 41.0 kDa) on RNA4 (1.6 kb). The fifth identified genome segment (RNA5, 1.3 kb) encodes a protein of unknown function (P28, 28.1 kDa). We discovered that it is distantly related to proteins encoded by Emaraviruses, such as P4 of European mountain ash ringspot‐associated virus. All proteins from this group contain a central hydrophobic region with a conserved secondary structure and a hydrophobic amino acid stretch, bordered by two highly conserved positions, thus clearly representing a new group of homologues of Emaraviruses. The virus identified in Eurasian aspen is closely associated with observed leaf symptoms, such as mottle, yellow blotching, variegation and chloroses along veins. All five viral RNAs were regularly detectable by RT‐PCR in mosaic‐diseased P. tremula in Norway, Finland and Sweden (Fennoscandia). Observed symptoms and testing of mosaic‐diseased Eurasian aspen by virus‐specific RT‐PCR targeting RNA3 and RNA4 confirmed a wide geographic distribution of the virus in Fennoscandia. We could demonstrate that the mosaic‐disease is graft‐transmissible and confirmed that the virus is the causal agent by detection in symptomatic, graft‐inoculated seedlings used as rootstocks as well as in the virus‐infected scions used for graft‐inoculation. Owing to these characteristics, the virus represents a novel species within the genus Emaravirus and was tentatively denominated aspen mosaic‐associated virus.

Abstract

The term Circular Regulations (CR) is introduced to describe a broad regulatory framework, designed with a circular understanding of the economy. Central in this discussion is the transition towards bioeconomy, a term that is not always used consistently, and sometimes treated in the same way as circular economy (CE), although these terms are not necessarily equivalent. In this article we endorse a systemic interpretation of CE, where a continuum of approaches, extending from reusing/recycling/upcycling to refuse/rethink/reduce, gradually replace existing linear “end-of-life” concepts. CE is a key prerequisite for the bioeconomy shift, a transition that further builds on CE, where circular design and processes are further augmented with increased resource utilization and intensive applications of innovative science and technology. The prevailing regulatory arrangements in CE, however, remain either fragmented or largely based on pre-existing policies, drafted to address issues of the linear economy, thus presenting several limitations when dealing with the underlying paradigm shift: complex market relationships that go beyond the standard neoclassical model. CR adopts an encompassing approach to regulatory design; it is not meant to be a rigid set of rules, but rather a regulatory framework where institutions, market rules, and business practice explicitly account for environmental and socially responsible activities, while securing an enabling environment for innovation. CR directly reflects on CE, where bioeconomy growth is informed by science, enabled by technology, driven by business, and supported by relevant policies and institutional frameworks. The article presents a conceptual setting towards CR and a practical example for its development.

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Abstract

Wheat dwarf virus (WDV), a mastrevirus transmitted by the leafhopper Psammotettix alienus, causes a severe disease in cereal crops. Typical symptoms of wheat plants infected by WDV are yellowing and severe dwarfing. In this present study, RNA-Seq was used to perform gene expression analysis in wheat plants in response to WDV infection. Comparative transcriptome analysis indicated that a total of 1042 differentially expressed genes (DEGs) were identified in the comparison between mock and WDV-inoculated wheat plants. Genomes ontology (GO) annotation revealed a number of DEGs associated with different biological processes, such as phytohormone metabolism, photosynthesis, DNA metabolic process, response to biotic stimulus and defense response. Among these, DEGs involved in phytohormone and photosynthesis metabolism and response pathways were further enriched and analyzed, which indicated that hormone biosynthesis, signaling and chloroplast photosynthesis-related genes might play an important role in symptom development after WDV infection. These results illustrate the dynamic nature of the wheat-WDV interaction at the transcriptome level and confirm that symptom development is a complex process, providing a solid foundation to elucidate the pathogenesis of WDV.

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Abstract

To support decision-makers considering adopting integrated pest management (IPM) cropping in Norway, we used stochastic efficiency analysis to compare the risk efficiency of IPM cropping and conventional cropping, using data from a long-term field experiment in southeastern Norway, along with data on recent prices, costs, and subsidies. Initial results were not definitive, so we applied stochastic efficiency with respect to a function, limiting the assumed risk aversion of farmers to a plausible range. We found that, for farmers who are risk-indifferent to moderately (hardly) risk averse, the conventional system was, compared to IPM, less (equally) preferred.

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Abstract

Although it is well known that insects are sensitive to temperature, how they will be affected by ongoing global warming remains uncertain because these responses are multifaceted and ecologically complex. We reviewed the effects of climate warming on 31 globally important phytophagous (plant‐eating) insect pests to determine whether general trends in their responses to warming were detectable. We included four response categories (range expansion, life history, population dynamics, and trophic interactions) in this assessment. For the majority of these species, we identified at least one response to warming that affects the severity of the threat they pose as pests. Among these insect species, 41% showed responses expected to lead to increased pest damage, whereas only 4% exhibited responses consistent with reduced effects; notably, most of these species (55%) demonstrated mixed responses. This means that the severity of a given insect pest may both increase and decrease with ongoing climate warming. Overall, our analysis indicated that anticipating the effects of climate warming on phytophagous insect pests is far from straightforward. Rather, efforts to mitigate the undesirable effects of warming on insect pests must include a better understanding of how individual species will respond, and the complex ecological mechanisms underlying their responses.

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Abstract

Aim: Distribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for, for example, red-list assessments. While distribution modelling methods have been applied mostly to single species, modelling of communities and ecosystems (EDM; ecosystem-level distribution modelling) produces results that are more directly relevant for management and decision-making. Although the choice of predictors is a pivotal part of the modelling process, few studies have compared the suitability of different sets of predictors for EDM. In this study, we compare the performance of 50 single environmental variables with that of 11 composite landscape gradients (CLGs) for prediction of ecosystem types. The CLGs represent gradients in landscape element composition derived from multivariate analyses, for example “inner-outer coast” and “land use intensity.” Location: Norway. Methods: We used data from field-based ecosystem-type mapping of nine ecosystem types, and environmental variables with a resolution of 100 × 100 m. We built nine models for each ecosystem type with variables from different predictor sets. Logistic regression with forward selection of variables was used for EDM. Models were evaluated with independently collected data. Results: Most ecosystem types could be predicted reliably, although model performance differed among ecosystem types. We identified significant differences in predictive power and model parsimony across models built from different predictor sets. Climatic variables alone performed poorly, indicating that the current climate alone is not sufficient to predict the current distribution of ecosystems. Used alone, the CLGs resulted in parsimonious models with relatively high predictive power. Used together with other variables, they consistently improved the models. Main conclusions: Our study highlights the importance of variable selection in EDM. We argue that the use of composite variables as proxies for complex environmental gradients has the potential to improve predictions from EDMs and thus to inform conservation planning as well as improve the precision and credibility of red lists and global change assessments.conservation planning, distribution modelling, ecosystem classification, ecosystem types, IUCN Red List of Ecosystems, landscape gradients, spatial prediction, species response curves