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.
2021
Sammendrag
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Sammendrag
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Forfattere
Mekjell MelandSammendrag
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Sammendrag
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Forfattere
Alexander Jüterbock Antoine J. P. Minne J. Mark Cock Melinda Ann Coleman Thomas Wernberg Lydia Scheschonk Ralf Rautenberger Jie Zhang Zi-Min HuSammendrag
Marine macrophytes, including seagrasses and macroalgae, form the basis of diverse and productive coastal ecosystems that deliver important ecosystem services. Moreover, western countries increasingly recognize macroalgae, traditionally cultivated in Asia, as targets for a new bio-economy that can be both economically profitable and environmentally sustainable. However, seagrass meadows and macroalgal forests are threatened by a variety of anthropogenic stressors. Most notably, rising temperatures and marine heatwaves are already devastating these ecosystems around the globe, and are likely to compromise profitability and production security of macroalgal farming in the near future. Recent studies show that seagrass and macroalgae can become less susceptible to heat events once they have been primed with heat stress. Priming is a common technique in crop agriculture in which plants acquire a stress memory that enhances performance under a second stress exposure. Molecular mechanisms underlying thermal priming are likely to include epigenetic mechanisms that switch state and permanently trigger stress-preventive genes after the first stress exposure. Priming may have considerable potential for both ecosystem restoration and macroalgae farming to immediately improve performance and stress resistance and, thus, to enhance restoration success and production security under environmental challenges. However, priming methodology cannot be simply transferred from terrestrial crops to marine macrophytes. We present first insights into the formation of stress memories in both seagrasses and macroalgae, and research gaps that need to be filled before priming can be established as new bio-engineering technique in these ecologically and economically important marine primary producers.
Forfattere
Till SeehusenSammendrag
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Forfattere
Sophie Mentzel Merete Grung Knut-Erik Tollefsen Marianne Stenrød Roger Holten S. Jannicke MoeSammendrag
In Northern Europe, future changes in land-use and weather patterns are expected to result in increased precipitation and temperature this may cause an increase in plant disease and insect pests. In addition, predicted population increase will change the production demands and in turn alter agricultural practices such as crop types and with that the use pattern of pesticides. Considering these variabilities and magnitudes of pesticide exposure to the aquatic environment still needs to be accounted for better in current probabilistic risk assessment. In order to improve ecological risk assessment, this study explores an alternative approach to probabilistic risk assessment using a Bayesian Network, as these can serve as meta-models that link selected input and output variables from other models and information sources. The developed model integrates variability in both exposure and effects in the calculation of risk estimate. We focus on environmental risk of pesticides in two Norwegian case study region representatives of northern Europe. Using pesticide fate and transport models (e.g. WISPE), environmental factors such as soil and site parameters together with chemical properties and climate scenarios (current and predicted) are linked to the exposure of a pesticide in the selected study area. In the long term, the use of tools based on Bayesian Network models will allow for a more refined assessment and targeted management of ecological risks by industry and policy makers.
Forfattere
Sophie Mentzel Merete Grung Knut-Erik Tollefsen Marianne Stenrød Petersen Karina S. Jannicke MoeSammendrag
The aquatic environment is constantly exposed to various chemicals caused by anthropogenic activities such as agricultural practices using plant protection products. Traditional Environmental Risk Assessment is based on calculated risk estimations usually representing a ratio of exposure to effects, in combination with assessment factors to account for uncertainty. In this study, we explore a more informative approach through probabilistic risk assessment, where probability distributions for exposure and effects are expressed and enable accounting for variability and uncertainty better. We focus on the risk assessment of various pesticides in a representative study area in the south east of Norway. Exposure data in this research was provided by the Norwegian Agricultural Environmental Monitoring Programme (JOVA)/ or predicted exposure concentration from a pesticide exposure model and effect data was derived from the NIVA Risk Assessment database (RAdb, www.niva.no/radb). A Bayesian network model is used as an alternative probabilistic approach to assess the risks of chemical. Bayesian Networks can serve as meta-models that link selected input and output variables from several separate project outputs and offer a transparent way of evaluating the required characterization of uncertainty for ERA. They can predict the probability of several risk levels, while facilitating the communication of estimates and uncertainties.
Forfattere
Trygve S. AamlidSammendrag
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Forfattere
Ola FlatenSammendrag
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