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.
2024
Abstract
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.
Abstract
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Authors
Nina SvartedalAbstract
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Nina SvartedalAbstract
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Vibeke LindAbstract
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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 ZuoAbstract
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.
Authors
Rolf David Vogt Øyvind Aaberg Garmo Kari Austnes Øyvind Kaste Ståle Haaland James Edward Sample Jan-Erik Thrane Liv Bente Skancke Cathrine Brecke Gundersen Heleen de WitAbstract
Rising organic charge in northern freshwaters is attributed to increasing levels of dissolved natural organic matter (DNOM) and changes in water chemistry. Organic charge concentration may be determined through charge balance calculations (Org.−) or modelled (OAN−) using the Oliver and Hruška conceptual models, which are based on the density of weak acid functional sites (SD) present in DNOM. The charge density (CD) is governed by SD as well as protonation and complexation reactions on the functional groups. These models use SD as a key parameter to empirically fit the model to Org.−. Utilizing extensive water chemistry datasets, this study shows that spatial and temporal differences in SD and CD are influenced by variations in the humic-to-fulvic ratio of DNOM, organic aluminum (Al) complexation, and the mole fraction of CD to SD, which is governed by acidity. The median SD values obtained for 44 long-term monitored acid-sensitive lakes were 11.1 and 13.9 µEq/mg C for the Oliver and Hruška models, respectively. Over 34 years of monitoring, the CD increased by 70%, likely due to rising pH and declining Al complexation with DNOM. Present-day median SD values for the Oliver and Hruška models in 16 low-order streams are 13.8 and 15.8 µEq/mg C, respectively, and 10.8 and 12.5 µEq/mg C, respectively, in 10 high-order rivers.
Abstract
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Linn SolliAbstract
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Nicole AndersonAbstract
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