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.
2024
Forfattere
Marta Vergarechea Clara Antón Fernández Jane Uhd Jepsen Ole Petter Laksforsmo Vindstad Rasmus AstrupSammendrag
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Forfattere
Andrea Seldeslachts Marius Filomeno Maurstad Jan Philip Øyen Eivind Andreas Baste Undheim Steve Peigneur Jan TytgatSammendrag
Lepidopterism, a skin inflammation condition caused by direct or airborne exposure to irritating hairs (setae) from processionary caterpillars, is becoming a significant public health concern. Recent outbreaks of the oak processionary caterpillar (Thaumetopoea processionea) have caused noteworthy health and economic consequences, with a rising frequency expected in the future, exacerbated by global warming promoting the survival of the caterpillar. Current medical treatments focus on symptom relief due to the lack of an effective therapy. While the source is known, understanding the precise causes of symptoms remain incomplete understood. In this study, we employed an advanced method to extract venom from the setae and identify the venom components through high-quality de novo transcriptomics, venom proteomics, and bioinformatic analysis. A total of 171 venom components were identified, including allergens, odorant binding proteins, small peptides, enzymes, enzyme inhibitors, and chitin biosynthesis products, potentially responsible for inflammatory and allergic reactions. This work presents the first comprehensive proteotranscriptomic database of T. processionea, contributing to understanding the complexity of lepidopterism. Furthermore, these findings hold promise for advancing therapeutic approaches to mitigate the global health impact of T. processionea and related caterpillars.
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Forfattere
Mohammad Tirgariseraji A. Pouyan Nejadhashemi Yaghoob Jafari Tomas Persson Mahmood Sabouhi Sabouni Alisher Mirzabaev Alireza Nikouei Naser Shahnoushi FroshaniSammendrag
The nitrogen regulatory policy (NRP) solution is introduced as a mitigation measure against environmental nitrogen losses and keeps food production in the Safe Operating Space of the Nitrogen Planetary Boundary. Meanwhile, scientific research shows that steps taken to reduce environmental harm can increase the unpredictability of calorie production from crops. This study sought to investigate the impact of NRP solutions on the level of risk of accessibility to calorie sources from domestic production, the variations in calorie sources by livestock and non-livestock diet components, and the responses of different dietary preferences, namely, poor, medium, and rich livestock protein diets, against NRP solutions in the Zayandeh-Rud River basin, Iran. We developed the aggregate household food security index (AHFSI) and combined it with outputs of crop simulation model to examine how changes in dietary energy supplies under three NRP scenarios—low, moderate, and high nitrogen fertilizer application—affect the stability of three regional dietary preferences. The comparison of NRP scenarios movements realized that increases (or decreases) in nitrogen fertilizer rates contradicted the stability in AHFSI. Additionally, a one-unit change in the average calories from non-livestock sources, such as wheat and potatoes, results in greater fluctuations in the standard deviations of produced calories compared to changes in meat and dairy production. We proposed that in order to prevent adverse effects of NRP solutions on food security, mitigation strategies addressing the NRP solution should be structured based on (i) regional heterogeneities, (ii) type of crops, that is, food and feed crops, (iii) the range of nitrogen rates movement; (iv) and the socioeconomic background related to dietary preferences or economic deciles of food expenditure.
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Extended Multiplicative Signal Correction (EMSC) is a multivariate linear modelling technique for multi-channel measurements that can identify and correct for different types of systematic variation patterns, known or unknown. It is typically used for pre-processing to separate light absorbance spectra, obtained by diffuse reflectance of intact samples, into three main sources of variation: additive variations due to chemical composition (≈Beer's law), mixed multiplicative and additive variations due to physical light scattering (≈Lambert's law) and more or less random measurement noise. The present work evaluates the use of EMSC to pre-process near infrared spectra obtained by hyperspectral imaging of Scots pine sapwood, inoculated with two different basidiomycete fungi and at various degradation stages. The spectral changes due to fungal decay and resulting mass loss are assessed by interpretation of the EMSC parameters and the partial least squares regression (PLSR) results. Including a cellulose (analyte) or bound water (interferent) spectral profile in the EMSC pre-processing model generally improves the predictive performance of the PLS modelling, but it can also make it worse. The inclusion of the additional polynomial baselines does not necessarily lead to a better separation of the physical and chemical effects present in the spectra. The estimated EMSC parameters provide insight into the differences in decay mechanisms. A detailed analysis of the EMSC results highlights advantages and disadvantages of using a complex pre-processing model.
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Forfattere
Vibeke LindSammendrag
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Forfattere
Melinda D. Smith Kate D. Wilkins Martin C. Holdrege Peter Wilfahrt Scott L. Collins Alan K. Knapp Osvaldo E. Sala Jeffrey S. Dukes Richard P. Phillips Laura Yahdjian Laureano A. Gherardi Timothy Ohlert Claus Beier Lauchlan H. Fraser Anke Jentsch Michael E. Loik Fernando T. Maestre Sally A. Power Qiang Yu Andrew J. Felton Seth M. Munson Yiqi Luo Hamed Abdoli Mehdi Abedi Concepción L. Alados Juan Alberti Moshe Alon Hui An Brian Anacker Maggie Anderson Harald Auge Seton Bachle Khadijeh Bahalkeh Michael Bahn Amgaa Batbaatar Taryn Bauerle Karen H. Beard Kai Behn Ilka Beil Lucio Biancari Irmgard Blindow Viviana Florencia Bondaruk Elizabeth T. Borer Edward W. Bork Carlos Martin Bruschetti Kerry M. Byrne James F. Cahill Dianela A. Calvo Michele Carbognani Augusto Cardoni Cameron N. Carlyle Miguel Castillo-Garcia Scott X. Chang Jeff Chieppa Marcus V. Cianciaruso Ofer Cohen Amanda L. Cordeiro Daniela F. Cusack Sven Dahlke Pedro Daleo Carla M. D'Antonio Lee H. Dietterich Tim S. Doherty Maren Dubbert Anne Ebeling Nico Eisenhauer Felícia M. Fischer Tai G.W. Forte Tobias Gebauer Beatriz Gozalo Aaron C. Greenville Karlo G. Guidoni-Martins Heather J. Hannusch Siri Vatsø Haugum Yann Hautier Mariet Hefting Hugh A.L. Henry Daniela Hoss Oscar Iribarne Forest Isbell Yari Johnson Samuel Jordan Eugene F. Kelly Kaitlin Kimmel Juergen Kreyling György Kröel-Dulay Johannes Ingrisch Alicia Kröpfl Angelika Kübert Andrew Kulmatiski Eric G. Lamb Klaus Steenberg Larsen Julie Larson Cintia V. Leder Anja Linstädter Jielin Liu Shirong Liu Alexandra G. Lodge Grisel Longo Alejandro Loydi Junwei Luan Jason Lawson Frederick Curtis Lubbe Craig Macfarlane Kathleen Mackie-Haas Andrey V. Malyshev Adrián Maturano-Ruiz Thomas Merchant Daniel B. Metcalfe Akira S. Mori Edwin Mudongo Gregory S. Newman Uffe N. Nielsen Dale Nimmo Yujie Niu Paola Nobre Rory C. O'Connor Romà Ogaya Gastón R. Oñatibia Ildikó Orbán Brooke Osborne Rafael Otfinowski Meelis Pärtel Josep Penuelas Pablo L. Peri Guadalupe Peter Alessandro Petraglia Catherine Picon-Cochard Valério D. Pillar Juan Manuel Piñeiro-Guerra Laura W. Ploughe Robert M. Plowes Cristy Portales-Reyes Suzanne M. Prober Yolanda Pueyo Sasha C. Reed Euan G. Ritchie Dana Aylén Rodríguez William E. Rogers Christiane Roscher Ana M. Sánchez Bráulio A. Santos María Cecilia Scarfó Eric W. Seabloom Baoku Shi Lara Souza Andreas Stampfli Rachel J. Standish Marcelo Sternberg Wei Sun Marie Sünnemann Michelle Tedder Pål Thorvaldsen Dashuan Tian Katja Tielbörger Alejandro Valdecantos Liesbeth van den Brink Vigdis Vandvik Mathew R. Vankoughnett Liv Guri Velle Changhui Wang Yi Wang Glenda M. Wardle Christiane Werner Cunzheng Wei Georg Wiehl Jennifer L. Williams Amelia A. Wolf Michaela Zeiter Fawei Zhang Juntao Zhu Ning Zong Xiaoan ZuoSammendrag
Climate change is increasing the frequency and severity of short-term (~1 y) drought events—the most common duration of drought—globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function—aboveground net primary production (ANPP)—was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.
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