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.
2018
Forfattere
Klaus MittenzweiSammendrag
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Forfattere
Xiao Huang Shaoqiang Ni Chaoqing Yu Jim Hall Conrad Zorn Xiaomeng HuangSammendrag
Precipitation is an important source of soil water, which is critical to crop growth, and is therefore an important input when modelling crop growth. Although advances are continually being made in predicting and recording precipitation, input uncertainty of precipitation data is likely to influence the robustness of parameter estimate and thus the predictive accuracy in soil water and crop modelling. In this study, we use the Bayesian total error analysis (BATEA) method for the water-oriented crop model AquaCrop to identify the input uncertainty from multiple precipitation products respectively, including gauge-corrected grid dataset CPC, remote sensing based TRMM and reanalysis based ERA-Interim. This methodology uses latent variables to correct the input data errors. Adopting a single-multiplier method for precipitation correction, we simulate maize growth in both field and regional levels in China for a range of different possible climatic scenarios. Meanwhile, we use the average of multiple products for model driving in comparison. The results show that the BATEA method can consistently reduce uncertainty for crop growth prediction among different precipitation products. In regional simulation, the improvements for the three products are 1%, 7.3% and 2.8% on average in drought scenarios. These results imply the BATEA approach can be of great assistance for crop modeling studies and agricultural assessments under future changing climates.
Sammendrag
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Sammendrag
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Forfattere
Vibeke Stærkebye Nørstebø Gerardo Alfredo Perez Valdes Svein Olav Krøgli Wenche Dramstad Misganu Debella-Gilo Kristin Tolstad UggenSammendrag
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Forfattere
Caroline Brophy John A. Finn Andreas Lüscher M. Suter Laura Kirwan Maria-Teresa Sebastià Aslaug Helgadottir Ole Hans Baadshaug G. Bélanger Alistair Black Rosemary P. Collins Jure Čop Sigridur Dalmannsdottir Ignacio Delgado Anjo Elgersma Mick Fothergill Bodil E. Frankow-Lindberg An Ghesquiere Barbara Golinska Piotr Golinski Philippe Grieu Anne-Maj Gustavsson Mats Höglind Olivier Huguenin-Elie Marit Jørgensen Zydre Kadziuliene Päivi Kurki Rosa Llurba Tor Lunnan Claudio Porqueddu Ulrich Thumm John ConnollySammendrag
Increasing species diversity often promotes ecosystem functions in grasslands, but sward diversity may be reduced over time through competitive interactions among species. We investigated the development of species’ relative abundances in intensively managed agricultural grassland mixtures over three years to identify the drivers of diversity change. A continental-scale field experiment was conducted at 31 sites using 11 different four-species mixtures each sown at two seed abundances. The four species consisted of two grasses and two legumes, of which one was fast establishing and the other temporally persistent. We modelled the dynamics of the four-species mixtures over the three-year period. The relative abundances shifted substantially over time; in particular, the relative abundance of legumes declined over time but stayed above 15% in year three at many sites. We found that species’ dynamics were primarily driven by differences in the relative growth rates of competing species and secondarily by density dependence and climate. Alongside this, positive diversity effects in yield were found in all years at many sites.
Sammendrag
Det nærmer seg jul. Snøen laver ned og dyra som beitet seg gjennom utmarka i sommer, har nå kommet inn i små og store fjøs rundt om i landet. Noen har endt sine dager på en juletallerken, mens andre gomler på vinterfôret som bonden har gjort klart. På kalde vinterdager er det godt å være sau og ku inne i fjøset.
Sammendrag
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Forfattere
Gregory Taff Yang Shao Jie Ren Ruoyu ZhangSammendrag
The accuracy in land-cover classification using remotely sensed imagery can be increased using Bayesian methods that incorporate prior probabilities of classes. However, estimating these prior probabilities can be expensive and data intensive. We propose methods to improve the classification accuracy using Bayesian methods to classify ambiguous (or low-confidence) pixels, using only the remotely sensed imagery or existing land-cover maps to estimate prior probabilities. We propose a spatial method that predicts prior probabilities from the original image, and a temporal method that incorporates land-cover maps from previous years. We illustrate our methods with a neural network (NN) classifier on the U.S. state of Iowa to classify crops into corn/soybean/other using moderate resolution imaging spectroradiometer (MODIS) data. USDA cropland data layers were aggregated to the 250-m resolution of MODIS and used as ground truth, based on a cropland mask from the National Land Cover Database. Results show that the spatial-prior-adjustment method, which predicts prior probabilities for low-confidence pixels based on class percentages of initial NN classification, increased overall accuracy of low-confidence pixels between 2% and 3.3% over the standard NN classification. The temporal-prior-adjustment method, which uses crop classes from the previous six years to estimate prior probabilities for the current year, shows significantly greater accuracy improvement for low-confidence pixels (almost 7%) over the standard NN classification. Increased benefit of the temporal-prior-adjustment method relative to the spatial-prior-adjustment method is likely due to increased information from more ground truth data (from previous years) than the spatial method.
Forfattere
Van Minh Dang Stephen Joseph Huu Tap Van Thi Lan Anh Mai Thi Minh Hoa Duong Simon Weldon Paul Munroe David Mitchell Sarasadat TaherymoosaviSammendrag
Heavy metal contamination of crop lands surrounding mines in North Vietnam is a major environmental issue for both farmers and the population as a whole. Technology for the production of biochar at a village and household level has been successfully introduced into Vietnamese villages. This study was undertaken to determine if rice straw biochar produced in simple drum ovens could remediate contaminated land. Tests were also carried out to determine if biochar and apatite mixed together could be more effective than biochar alone. Incubation trials were carried out over 90 days in pots to determine the total changes in exchangeable Cd, Pb and Zn. Detailed tests were carried out to determine the mechanisms that bound the heavy metals to the biochar. It was found that biochar at 5% (BC5) and the mixture of biochar and apatite at 3% (BCA3) resulted in the greatest reduction of exchangeable forms of Cd, Pb and Zn. The increase in soil pH caused by adding biochar and apatite created more negative charge on the soil surface that promoted Pb, Zn and Cd adsorption. Heavy metals were mainly bound in the organic, Fe/Mn and carbonate fractions of the biochar and the mixture of biochar and apatite by either ion exchange, adsorption, dissolution/precipitation and through substitution of cations in large organic molecules.