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
Yi Zhang Xingru Yang Yijing Feng Zhiyue Dai Zhangmu Jing Yeqing Li Lu Feng Yanji Hao Shasha Yu Weijin Zhang Yanjuan Lu Chunming Xu Junting PanSammendrag
Exploring the complex mechanism of anaerobic digestion with hydrothermal pretreatment (HTAD) for biomass efficiently and optimising the reaction conditions are critical to improving the performance of methane production. This study used H2O automated machine learning (AutoML) for comprehensive prediction, analysis, and targeted optimization of the HTAD system. An IterativeImputer system for data filling was constructed. The comparison of three basic regressors showed that random forest performed optimally for filling (R2 > 0.95). The gradient boosting machine (GBM) model was searched by H2O AutoML to show optimal performance in prediction (R2 > 0.96). The software was developed based on the GBM model, and two prediction schemes were devised. The generalization error of the software was less than 10%. The Shapley Additive exPlanations value showed that solid to liquid ratio, hydrothermal pretreatment (HT) temperature, and particle size have greater potential for improving cumulative methane production (CMP). A Bayesian-HTAD optimization strategy was devised, using the Bayesian optimization to directionally optimize the reaction conditions, and performing experiments to validate the results. The experimental results showed that the CMP was significantly improved by 51.63%. Compared to the response surface methodology, the Bayesian optimization relatively achieved a 2.21–2.50 times greater effect. Mechanism analyses targeting the experiments showed that HT was conducive to improving the relative abundance of Sphaerochaeta, Methanosaeta, and Methanosarcina. This research achieved accurate prediction and targeted optimization for the HTAD system and proposed multiple filling, prediction, and optimization strategies, which are expected to provide an AutoML optimization paradigm for anaerobic digestion in the future.
Forfattere
Klemens Schadauer Rasmus Astrup Johannes Breidenbach Jonas Fridman Stephan Gräber Michael Köhl Kari T. Korhonen Vivian Kvist Johannsen Francois Morneau Risto Päivinen Thomas RiedelSammendrag
Det er ikke registrert sammendrag
Forfattere
Ivy Britzny Osae Peep Mardiste Dina Stober Sebastian Eiter Matthias Buchecker Monika SuškevičsSammendrag
The ‘Aarhus Convention’ – regulating access to environmental information, public participation and justice in environmental decision−making – is a key international agreement with a long history and a considerable number of signatory countries. While implementation has been studied nationally, there is little comparative research at the transnational level. Based on ten criteria, we analysed national implementation reports of the 2014, 2017 and 2021 reporting cycles in terms of how 33 countries in Europe have implemented the access to information and public participation pillars, and identified obstacles they encountered. We also studied similarities and differences supra-nationally. Overall, countries are quite successfully fulfilling the obligations of the two pillars. Most obstacles reported concern four criteria: access to information, information provision, interaction, and trust. Implementation practices have changed little from 2014 to 2021. However, East- and South-European countries report more, and more persistent or repetitive obstacles, compared to Northern and Western European countries. The national democratic context seems to affect the quality of implementation. The Convention’s compliance bodies and national agencies responsible for coordinating the implementation are encouraged to interact more closely, to account for the differences and leverage implementation.
Forfattere
Daniel Ruiz Potma Gonçalves Thiago Inagaki Luis Gustavo Barioni Newton La Scala Junior Maurício Roberto Cherubin João Carlos de Moraes Sá Carlos Eduardo Pellegrino Cerri Adriano AnselmiSammendrag
Soils are the third largest carbon pool on Earth and play a crucial role in mitigating climate change. Therefore, understanding and predicting soil carbon sequestration is of major interest to mitigate climate change globally, especially in countries with strong agricultural backgrounds. In this study, we used a new database composed of 5029 samples collected up to 1-meter depth in three biomes that are most representative of agriculture, Pampas (Prairie), Cerrados (Savanna), and Atlantic Forest (Forest), to explore soil organic carbon (SOC) stocks and its environmental drivers. The Cerrado (Savanna) biome was the only one where croplands presented higher SOC stocks than native vegetation (Native vegetation 121.23 Mg/ha and croplands 127.85 Mg/ha or 5 % higher). From the tested models, the Random Forest outperformed the others, achieving an R2 of 0.64 for croplands and 0.56 for native vegetation. The accuracy of the models varied with soil depth, showing better predictions in shallow layers for croplands and deeper layers for native vegetation. Our results highlight the importance of clay content, precipitation, net primary production (NPP), and temperature as key predictors for soil carbon stocks in the studied biomes. The findings emphasize the importance of protecting the surface layers, especially in the Cerrado biome, to enhance SOC stocks and promote sustainable land management practices. Moreover, the results provide valuable insights for the development of nature-based carbon markets and suggest potential strategies for climate change mitigation. Enhancing our understanding of SOC dynamics and adopting precise environmental predictors will contribute to the formulation of targeted soil management strategies and accelerate progress toward achieving climate goals.
Forfattere
Nina SvartedalSammendrag
Det er ikke registrert sammendrag
Sammendrag
Rapporten gir en oversikt over NIBIO sine aktiviteter i AdaptaN II prosjektet gjennomført i samarbeid med tsjekkiske partnere. NIBIO har bidratt med vurdering av erosjonsrisiko og modellering av erosjonstiltak for klimatilpasning på jordbruksarealer for et nedbørfelt i Větřkovice i Moravian – Silesian Region i Tsjekkia. Delrapport 1 gir en oversikt over aktuelle erosjonstiltak i bruk i Norge samt regelverk, støtteordninger og subsidier for miljøtiltak. Delrapport 2 gir en oversikt over viktige faktorer ved vurdering av erosjonsrisiko og resultat fra modellering av utvalgte erosjonstiltak, spesielt vegetasjonssoner og grasdekte vannveier for studieområdet i Tsjekkia.
Sammendrag
Denne rapporten gir en oversikt over NIBIO sine aktiviteter i AdaptaN II prosjektet gjennomført i samarbeid med tsjekkiske partnere. NIBIO har bidratt med vurdering av erosjonsrisiko og modellering av erosjonstiltak for klimatilpasning på jordbruksarealer for et nedbørfelt i Větřkovice i Moravian – Silesian Region i Tsjekkia. Delrapport 1 gir en oversikt over aktuelle erosjonstiltak i bruk i Norge samt regelverk, støtteordninger og subsidier for miljøtiltak. Delrapport 2 gir en oversikt over faktorer ved vurdering av erosjonsrisiko og resultat fra modellering av utvalgte erosjonstiltak, spesielt vegetasjonssoner og grasdekte vannveier for studieområdet i Tsjekkia.
Forfattere
Anne Muola Ivan M. De-la-Cruz Femke Batsleer Dries Bonte Carolina Diller Sonia Osorio David Posé Aurora de la Rosa José Luis Izquierdo Martijn Lodewijk Vandegehuchte Timo Hytönen Johan A. StenbergSammendrag
Det er ikke registrert sammendrag
Sammendrag
Ensiling of whole-crop biomass of barley before full maturity is common practice in regions with a short growing season. The developmental stage of barley at harvest can have a large impact on yield and nutritive composition. The relationships between crop growth, environmental conditions and crop management can be described in process-based simulation models. Some models, including the Basic Grassland (BASGRA) model, have been developed to simulate the yield and nutritive value of forage grasses, and usually evaluated against metrics of relevance for whole-crop silage. The objectives of this study were to: i) modify the BASGRA model to simulate whole-crop spring barley; ii) evaluate the performance of this model against empirical data on dry matter (DM) yield and nutritive value attributes from field experiments, divided into geographical regions; and iii) evaluate DM yield, nutritive value and cutting date under current and future climate conditions for three locations in Sweden and four cutting regimes. Main model modifications included addition of a spike pool, equations for carbon (C) and nitrogen (N) allocation to the spike pool and equations for C and N translocation from vegetative plant parts to spikes. Model calibration and validation against field trial data from Sweden, including samples harvested from late anthesis stage to hard dough stage that were either pooled or divided into regions, showed better prediction accuracy, evaluated as normalised root mean squared error (RMSE), of neutral detergent fibre (NDF) (7.58–18.4%) than of DM yield (16.8–27.8%), crude protein (15.5–23.2%) or digestible organic matter in the DM (DOMD) (12.0–22.2%). Model prediction using weather data representing 1990–2020 and 2021–2040 climate conditions for three locations in Sweden (Skara, Umeå, Uppsala) showed lower DM yield, earlier harvest and slightly higher NDF concentration on average (across locations and developmental stage at cutting) when using near-future climate data rather than historical data. The model can be used to evaluate whole-crop barley performance under production conditions in Sweden or in other countries with similar climate, soils and crop management regimes.
Forfattere
Brigitta Szabó Piroska Kassai Svajunas Plunge Attila Nemes Péter Braun Michael Strauch Felix Witing János Mészáros Natalja ČerkasovaSammendrag
Det er ikke registrert sammendrag