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.
2022
Forfattere
Marit JørgensenSammendrag
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Forfattere
Jørgen A.B. MølmannSammendrag
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Forfattere
Marit JørgensenSammendrag
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Forfattere
Marit JørgensenSammendrag
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Forfattere
Till SeehusenSammendrag
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Forfattere
Krzysztof KusnierekSammendrag
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Sammendrag
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Sammendrag
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Forfattere
Sophie Mentzel Merete Grung Roger Holten Knut-Erik Tollefsen Marianne Stenrød S. Jannicke MoeSammendrag
The use of Bayesian networks (BN) for environmental risk assessment has increased in recent years as they offer a more transparent way to characterize risk and evaluate uncertainty than the traditional risk assessment paradigms. In this study, a novel probabilistic approach applying a BN for risk calculation was further developed and explored by linking the calculation a risk quotient to alternative future scenarios. This extended version of the BN model uses predictions from a process-based pesticide exposure model (World Integrated System for Pesticide Exposure - WISPE) in the exposure characterization and toxicity test data in the effect characterization. The probability distributions for exposure and effect are combined into a risk characterization (i.e. the probability distribution of a risk quotient), a common measure of the exceedance of an environmentally safe exposure threshold. The BN model was used to account for variabilities of the predicted pesticide exposure in agricultural streams, and inter-species variability in sensitivity to the pesticide among freshwater species. In Northern Europe, future climate scenarios typically predict increased temperature and precipitation, which can be expected to cause an increase in weed infestations, plant disease and insect pests. Such climate-related changes in pest pressure in turn can give rise to altered agricultural practices, such as increased pesticide application rates, as an adaptation to climate change. The WISPE model was used to link a set of scenarios consisting of two climate models, three pesticide application scenarios and three periods (year ranges), for a case study in South-East Norway. The model was set up for the case study by specifying environmental factors such as soil properties and field slope together with chemical properties of pesticides to predict the pesticide exposure in streams adjacent to the agricultural fields. The model was parameterized and evaluated for five selected pesticides: the three herbicides clopyralid, fluroxypyr-meptyl, and 2-(4-chloro-2-methylphenoxy) acetic acid (MCPA), and the two fungicides prothiocanzole and trifloxystrobin. This approach enabled the calculation and visualization of probability distribution of the risk quotients for the future time horizons 2050 and 2085. The risk posed by the pesticides were in general low for this case study, with highest probability of the risk quotient exceeding 1 for the two herbicides fluroxypyr-meptyl and MCPA. The future climate projections used here resulted in only minor changes in predicted exposure concentrations and thereby future risk. However, a stronger increase in risk was predicted for the scenarios with increased pesticide application, which can represent an adaptation to a future climate with higher pest pressures. In the current study, the specific BN model predictions were constrained by an existing set of climate projections which represented only one IPCC scenario (A1B) and two climate models. Further advancement of the BN modelling demonstrated herein, including more recent climate scenarios and a larger set of climate models, is anticipated to result in more relevant risk characterization also for future climate conditions. This probabilistic approach will have the potential to aid targeted management of ecological risks in support of future research, industry and regulatory needs.
Sammendrag
Environmental conditions during plant raising determine the yield potential of everbearing strawberries. We studied the effect of three rooting dates in the cultivars ‘Favori’ and ‘Murano’ in a greenhouse with 18 ℃ and 20-h long day and under outdoor conditions in Norway. The highest yield of 1.350 g/plant was obtained in ‘Favori’ plants rooted on 1 August and raised outdoors, being at level with ‘Favori’ plants produced in The Netherlands. High yields were mainly related to fruit size and less to fruit number, and determined by a complex three-factor interaction of rooting date, raising environment, and cultivar. The seasonal pattern of fruit flushes and off periods varied significantly between cultivars and treatments. The large first flush of high yielding ‘Favori’ plants was associated with a long off period, while the small first flush in ‘Murano’ resulted in a more even crop distribution. Earliness of ripening and berry harvest was superior in ‘Favori’, which had a larger share of its crop during the first half-season. We conclude that it is possible by choosing the right rooting date and raising environment to produce plants with the same high quality and yield potential under the cool Nordic conditions as those currently produced in Central Europe.