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.
2023
Authors
Michael Altgen Michael Fröba Julius Gurr Andreas Krause Martin Ohlmeyer Uta Sazama Wim Willems Martin NopensAbstract
No abstract has been registered
Abstract
The European spruce bark beetle Ips typographus and the North American spruce beetle Dendroctonus rufipennis cause high mortality of spruces on their native continents. Both species have been inadvertently transported beyond their native ranges. With similar climates and the presence of congeneric spruce hosts in Europe and North America, there is a risk that one or both bark beetle species become established into the non-native continent. There are many challenges that an introduced population of bark beetles would face, but an important prerequisite for establishment is the presence of suitable host trees. We tested the suitability of non-native versus native hosts by exposing cut bolts of Norway spruce (Picea abies), black spruce (Picea mariana) and white spruce (Picea glauca) to beetle attacks in the field in Norway and Canada. We quantified attack density, brood density and reproductive success of I. typographus and D. rufipennis in the three host species. We found that I. typographus attacked white and black spruce at comparable densities to its native host, Norway spruce, and with similar reproductive success in all three host species. In contrast, D. rufipennis strongly preferred to attack white spruce (a native host) but performed better in the novel Norway spruce host than it did in black spruce, a suboptimal native host. Our results suggest that I. typographus will find abundant and highly suitable hosts in North America, while D. rufipennis in Europe may experience reduced reproductive success in Norway spruce.
Abstract
No abstract has been registered
Authors
Julia Le Noë Stefano Manzoni Rose Abramoff Tobias Bölscher Elisa Bruni Rémi Cardinael Philippe Ciais Claire Chenu Hugues Clivot Delphine Derrien Fabien Ferchaud Patricia Garnier Daniel Goll Gwenaëlle Lashermes Manuel Martin Daniel Rasse Frédéric Rees Julien Sainte-Marie Elodie Salmon Marcus Schiedung Josh Schimel William Wieder Samuel Abiven Pierre Barré Lauric Cécillon Bertrand GuenetAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Yi Zhang Yun Zhao Yijing Feng Yating Yu Yeqing Li Jian Li Zhonghao Ren Shuo Chen Lu Feng Junting Pan Hongjun Zhou Yongming HanAbstract
Industrial-scale garage dry fermentation systems are extremely nonlinear, and traditional machine learning algorithms have low prediction accuracy. Therefore, this study presents a novel intelligent system that employs two automated machine learning (AutoML) algorithms (AutoGluon and H2O) for biogas performance prediction and Shapley additive explanation (SHAP) for interpretable analysis, along with multiobjective particle swarm optimization (MOPSO) for early warning guidance of industrial-scale garage dry fermentation. The stacked ensemble models generated by AutoGluon have the highest prediction accuracy for digester and percolate tank biogas performances. Based on the interpretable analysis, the optimal parameter combinations for the digester and percolate tank were determined in order to maximize biogas production and CH4 content. The optimal conditions for the digester involve maintaining a temperature range of 35–38 °C, implementing a daily spray time of approximately 10 min and a pressure of 1000 Pa, and utilizing a feedstock with high total solids content. Additionally, the percolate tank should be maintained at a temperature range of 35–38 °C, with a liquid level of 1500 mm, a pH range of 8.0–8.1, and a total inorganic carbon concentration greater than 13.8 g/L. The software developed based on the intelligent system was successfully validated in production for prediction and early warning, and MOPSO-recommended guidance was provided. In conclusion, the novel intelligent system described in this study could accurately predict biogas performance in industrial-scale garage dry fermentation and guide operating condition optimization, paving the way for the next generation of intelligent industrial systems.
Abstract
The aim of the project is to evaluate and assess measures in lawn care management and at the same time to combine new techniques and alternative products to control diseases such as snow mold (Microdochium nivale) and dollar spots (Sclerotinia homoeocarpa) without or with a greatly reduced use of pesticides. Therefore, the lawn research group of the NIBIO (Norwegian Institute for Bioeconomy Research) started a project on Integrated Pest Management (IPM) with a focus on the most important fungal diseases and insect pests on golf turf. The project is supported by STERF (Scandinavian Turf and Environmental Research Foundation) and the R&A (The Royal and Ancient Golf Club of St. Andrews) as main sponsors, as well as by the German Golf Association, the Netherlands Golf Federation sponsor, the Botaniska Analysgruppen Sweden and the Danish Environmental Protection Agency. The current project aims is to develop new findings with regard to the increasing challenges in dealing with the above-mentioned pests. The two questions to check are: (1) the effectiveness of the “rolling” of greens (dollar spot treatment) and the effectivity of UV-C exposure (snow mold prevention). For this reason, two different attempts were made on a putting green at the golf course Osnabrueck (Bissendorf-Jeggen).
Authors
Iris Hordijk Daniel S. Maynard Simon P. Hart Mo Lidong Hans ter Steege Jingjing Liang Sergio de-Miguel Gert-Jan Nabuurs Peter B. Reich Meinrad Abegg C. Yves Adou Yao Giorgio Alberti Angelica M. Almeyda Zambrano Braulio V. Alvarado Alvarez-Davila Esteban Patricia Alvarez-Loayza Luciana F. Alves Christian Ammer Clara Antón Fernandéz Alejandro Araujo-Murakami Luzmila Arroyo Valerio Avitabile Gerardo A. Aymard C Timothy Baker Radomir Bałazy Olaf Banki Jorcely Barroso Meredith L. Bastian Jean-Francois Bastin Luca Birigazzi Philippe Birnbaum Robert Bitariho Pascal Boeckx Frans Bongers Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Roel Brienen Eben N. Broadbent Helge Bruelheide Filippo Bussotti Roberto Cazzolla Gatti Ricardo G. César Goran Cesljar Robin Chazdon Han Y. H. Chen Chelsea Chisholm Emil Cienciala Connie J. Clark David B. Clark Gabriel Colletta David Coomes Fernando Cornejo Valverde Jose J. Corral-Rivas Philip Crim Jonathan Cumming Selvadurai Dayanandan André L. de Gasper Mathieu Decuyper Géraldine Derroire Ben DeVries Ilija Djordjevic Amaral Iêda Aurélie Dourdain Engone Obiang Nestor Laurier Brian Enquist Teresa Eyre Adandé Belarmain Fandohan Tom M. Fayle Leandro V. Ferreira Ted R. Feldpausch Leena Finér Markus Fischer Christine Fletcher Lorenzo Frizzera Javier G. P. Gamarra Damiano Gianelle Henry B. Glick David Harris Andrew Hector Andreas Hemp Geerten Hengeveld Bruno Hérault John Herbohn Annika Hillers Eurídice N. Honorio Coronado Cang Hui Hyunkook Cho Thomas Ibanez Il Bin Jung Nobuo Imai Andrzej M. Jagodzinski Bogdan Jaroszewicz Vivian Johanssen Carlos A. Joly Tommaso Jucker Viktor Karminov Kuswata Kartawinata Elizabeth Kearsley David Kenfack Deborah Kennard Sebastian Kepfer-Rojas Gunnar Keppel Mohammed Latif Khan Timothy Killeen Hyun Seok Kim Kanehiro Kitayama Michael Köhl Henn Korjus Florian Kraxner Diana Laarmann Mait Lang Simon Lewis Huicui Lu Natalia Lukina Brian Maitner Yadvinder Malhi Eric Marcon Beatriz Schwantes Marimon Ben Hur Marimon-Junior Andrew Robert Marshall Emanuel Martin Olga Martynenko Jorge A. Meave Omar Melo-Cruz Casimiro Mendoza Cory Merow Stanislaw Miscicki Abel Monteagudo Mendoza Vanessa Moreno Sharif A. Mukul Philip Mundhenk Maria G. Nava-Miranda David Neill Victor Neldner Radovan Nevenic Michael Ngugi Pascal A. Niklaus Jacek Oleksyn Petr Ontikov Edgar Ortiz-Malavasi Yude Pan Alain Paquette Alexander Parada-Gutierrez Elena Parfenova Minjee Park Marc Parren Narayanaswamy Parthasarathy Pablo L. Peri Sebastian Pfautsch Oliver L. Phillips Nicolas Picard Maria Teresa Piedade Daniel Piotto Nigel C. A. Pitman Irina Polo Lourens Poorter Axel Dalberg Poulsen John R. Poulsen Hans Pretzsch Freddy Ramirez Arevalo Zorayda Restrepo-Correa Mirco Rodeghiero Samir Rolim Anand Roopsind Francesco Rovero Ervan Rutishauser Purabi Saikia Christian Salas-Eljatib Peter Schall Dmitry Schepaschenko Michael Scherer-Lorenzen Bernhard Schmid Jochen Schöngart Eric B. Searle Vladimír Šebeň Josep M. Serra-Diaz Douglas Sheil Anatoly Shvidenko Javier Silva-Espejo Marcos Silveira James Singh Plinio Sist Ferry Slik Bonaventure Sonké Alexandre F. Souza Krzysztof Stereńczak Jens-Christian Svenning Miroslav Svoboda Ben Swanepoel Natalia Targhetta Nadja Tchebakova Raquel Thomas Elena Tikhonova Peter Umunay Vladimir Usoltsev Renato Valencia Fernando Valladares Fons van der Plas Do Van Tran Michael E. Van Nuland Rodolfo Vasquez Martinez Hans Verbeeck Helder Viana Alexander C. Vibrans Simone Vieira Klaus von Gadow Hua-Feng Wang James Watson Gijsbert D. A. Werner Susan K. Wiser Florian Wittmann Verginia Wortel Roderick Zagt Tomasz Zawila-Niedzwiecki Chunyu Zhang Xiuhai Zhao Mo Zhou Zhi-Xin Zhu Irie Casimir Zo-Bi Thomas W. CrowtherAbstract
1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions.
Authors
Till SeehusenAbstract
No abstract has been registered