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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.

2023

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Abstract

Key words: VKM, pest risk analysis, Norwegian Scientific Committee for Food and Environment, Norwegian Food Safety Authority, Sudden oak death, Phytophthora ramorum Introduction The Norwegian Food Safety Authority has asked the Norwegian Scientific Committee for Food and Environment for an updated pest risk assessment of Phytophthora ramorum in Norway. The previous risk assessment of P. ramorum for Norway is from 2009. Since then, the pathogen has been detected repeatedly in Norway, primarily in parks, garden centres, and nurseries in southwestern Norway. The knowledge base concerning P. ramorum has changed since the last pest risk assessment, with increased genetic knowledge about different populations, lineages, and mating types. The risks associated with P. ramorum have also changed, since the disease has become epidemic in new host plants, such as larch trees in England. This updated pest risk assessment will provide important input to the Norwegian Food Safety Authority’s efforts to develop the Norwegian plant health regulation. Methods VKM established a project group with expertise in plant health, forest pathology, horticultural plant pathology, plant disease modelling, and pest risk assessment. The group conducted systematic literature searches and scrutinized the relevant literature. In the absence of Norwegian studies, VKM relied on literature from other countries. The group did a quantitative risk assessment describing the level of confidence in the conclusions and identifying uncertainties and data gaps. The report underwent pre-submission commenting and external expert reviewing before final approval and publication. Results and conclusions Phytophthora ramorum is present in the PRA area but has a restricted distribution, mainly being detected in the southern and southwestern parts of Norway. The only P. ramorum lineage considered to be present in Norway is EU1 with mating type A1. The other lineage in Europe, EU2, has so far mainly been documented from the UK. The most widely distributed multilocus genotype of P. ramorum in Norway is EU1MLG1, which became dominant in Europe (including Norway) after 2008. In North America, the NA1, NA2, and EU1 lineages are known from both nurseries and forests. NA1 and NA2 are of the opposite mating type (A2) than European lineages. Recently, various other lineages of P. ramorum have been described from Asia. The main risks for future problems with P. ramorum in Norway are related to entry and establishment of non-European isolates (of all lineages), as well as emergence of new genotypes in European P. ramorum populations. There are several options for diagnosing P. ramorum to species and lineage (mainly EU1, EU2, NA1, and NA2). From a management perspective it is more important to distinguish these entities than mating type and isolate groups (genotypes). The latter are mainly relevant for research purposes or in cases of unexpected disease developments, such as new hosts, increased spread or more severe symptoms on known hosts. However, for more detailed regulation, monitoring, and management of P. ramorum it could also be useful to test for genotypes, i.e. to distinguish EU1MLG1 from other genotypes. Rhododendron remains the most important host plant for P. ramorum in Norway, both in terms of imported plants and detections (mainly in nurseries, garden centres, and public parks). Species in other ornamental plant genera, such as Viburnum, Pieris, and Kalmia, are also listed as major hosts in Europe, and P. ramorum has been detected at least once on species in all these genera in Norway. In the US, Rhododendron, Viburnum, Pieris, Syringa, and Camellia are considered to be the main ornamental hosts. .....................

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Abstract

In this paper we examine how sensitive Value-at-Risk (VaR) forecasts based on simple linear quantile regressions are to the sampling frequency used to calculate realized volatility. We use sampling frequencies from one to 108 min for ICE Brent Crude Oil futures and test the out-of-sample performance of a set of quantile regression models using formal coverage tests. The results show that a one-factor model performs exceptionally well for most sampling frequencies used to calculate realized volatility. In comparison with the well-known Heterogeneous Auto-regressive Model of Realized Volatility (HAR-RV) and a quantile regression version of the HAR model (HAR-QREG), we also find that the one-factor model is much less sensitive to the sampling frequency used to calculate realized volatility.