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.
2022
Forfattere
Lu Feng Lise Bonne Guldberg Michael Jørgen Hansen Chun Ma Rikke Vinther Ohrt Henrik Bjarne MøllerSammendrag
Anaerobic digestion of animal slurry to produce biogas is the dominated treatment approach and a storage period is normally applied prior to digestion. Pre-storage, however, contributes to CH4 emissions and results in loss of biogas potential. Manure management was found to be an efficient approach to reduce not only the on-site CH4 emission but may also have extended influence on CH4 emission/losses for storage and subsequent biogas process, while the connection remains unclear. The objective of this study was therefore to evaluate the impact of slurry management (e.g. removal frequency) on CH4 emission (both on-site and storage process prior to biogas) and biogas yield. An experimental pig house for growing-finishing pigs (30–110 kg) and the relevant CH4 emission was monitored for one year. In addition, the specific CH4 activity (SMA) test was conducted and used as an alternative indicator to reflect the impact. Results showed that the manure management affected both on-site and subsequent methane emission; with increased manure removal frequencies, the methane emission became less dependent on variation of temperatures and the specific methanogenesis activity was significantly lower. The highest SMA (100 mL CH4 gVS-1), for instance, was observed from the slurries with limited emptied times, which was 10 times of that from the slurries being emptied three times a week. These findings could enlighten the development of environmentally friendly strategies for animal slurry management and biogas production.
Forfattere
Kyrre Linné Kausrud Vigdis Vandvik Daniel Flø Sonya Rita Geange Stein Joar Hegland Jo Skeie Hermansen Lars Robert Hole Rolf Anker Ims Håvard Kauserud Lawrence Richard Kirkendall Jenni Nordén Line Nybakken Mikael Ohlson Olav Skarpaas Per Hans Micael Wendell Hugo de Boer Katrine Eldegard Kjetil Hindar Paal Krokene Johanna Järnegren Inger Elisabeth Måren Anders Nielsen Erlend Birkeland Nilsen Eli Knispel Rueness Eva Bonsak Thorstad Gaute VelleSammendrag
Det er ikke registrert sammendrag
Forfattere
Erling Meisingset Joar Gusevik Atle Skjørestad Øystein Brekkum Atle Mysterud Frank Narve RosellSammendrag
Many wild animals perceive humans as predators, and human disturbance,especially in the form of hunting, triggers antipredatory behavior among prey.Yet, knowledge of how game species react to different types of human distur-bance and adapt to repeated disturbances is limited. We investigated howdisturbance in the form of a solitary human approacher (stalker) impactedbehavior (flight response and short-term habitat use) of 28 GPS-collared reddeer (Cervus elaphus) in two populations with contrasting population densitiesin Norway. We studied how the behavioral response differed: (1) with season(pre-hunting vs. hunting); (2) by consecutive approaches within a day;(3) among replicated experiments within the same season; and (4) betweentwo regions with contrasting densities of red deer. The average flight initiationdistance (FID) increased by 15% during the hunting season, and consecutiveapproaches within the same day caused the red deer to move 49% longerdistances. Flight initiation distance was longer in the high-density population,while escape distance was longer in the low-density population. Red deermoved out of their weekly home range after 52% approaches, and after theonset of hunting season, time spent outside the home range increased by 89%.Red deer preferred denser resting sites after the disturbance and animal siteshad shorter sighting distance and higher canopy cover than control plots.Tree density and canopy cover at animal sites increased at the onset of huntingseason, from first to second approach within day, and after replicated experi-ments within season. Our results suggest that red deer preferred dense restingsites, especially in the hunting season. However, these animal sites had thesame amount of the favorable forage plant bilberry (Vaccinium myrtillus), indi-cating no clear food–cover trade-off in selection of habitat. Our study showedthat onset of hunting initiates stronger fear responses in red deer, which mayin turn affect red deer distribution and harvesting efficiency
Forfattere
Stine Samsonstuen Helge Bonesmo Bente Aspeholen Åby Eli Gjerlaug-Enger Erland Kjesbu Magne Bergfjord Rune Okstad Svein Skøien Tony BarmanSammendrag
Through the joint project Climate Smart Agriculture, the agricultural sector in Norway have successfully implemented the whole-farm models HolosNor models as farm advisory tools for milk, beef, pig, sheep, poultry, and crop production. The HolosNor modes are empirical models based on the methodology of the Intergovernmental Panel on Climate Change with modifications to Norwegian conditions. The models estimate direct emissions of methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) from on-farm livestock production and includes indirect emissions of N2O and CO2 associated with inputs used on the farm in addition to including soil carbon balance through the ICBM model. The digital GHG Calculator automatically collects data from sources the farmer already uses for farm management, such as herd recording systems, manure planning systems, farm accounts, concentrate invoice, dairy, slaughterhouse, in addition to site-specific soil and weather data. Based on the collected data, both total emissions from the production and emission intensities for the different products are estimated. The emission intensities are shown by source relative to a reference group consisting of farms with the same type of production and production volume. Using the GHG Calculator, the farmers have the unique opportunity to have tailor-made mitigation plans to reduce emissions from the farm trough certified climate advisors. Participation and results from the GHG Calculator will be presented in addition to experiences from implementation of a GHG model as a farm advisory tool for commercial farms.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Valerie Isabelle Lengard Almli Milford Anna Birgitte Dypdal Lina FjørkenstadSammendrag
Det er ikke registrert sammendrag
Forfattere
Truls Nesbakken Håvard Steinshamn Iben Margrete Thomsen Dean Basic Thea B. Blystad Klem Tron Øystein Gifstad Kyrre Linné Kausrud Kjetil Klaveness Melby Lawrence Richard Kirkendall Christer Magnusson Inger Elisabeth Måren Mogens Nicolaisen Åshild Taksdal Randby Maria Stokstad Siamak Pour Yazdankhah Per Hans Micael Wendell Angelika Agdestein Hugo de Boer Jacques Xavier Leon Godfroid Solveig Jore Paal Krokene Live Lingaas Nesse Knut Madslien Trond Møretrø Gaute VelleSammendrag
Det er ikke registrert sammendrag
Sammendrag
Interactions among fungi and insects involve hundreds of thousands of species. While insect communities on plants have formed some of the classic model systems in ecology, fungus-based communities and the forces structuring them remain poorly studied by comparison. We characterize the arthropod communities associated with fruiting bodies of eight mycorrhizal basidiomycete fungus species from three different orders along a 1200-km latitudinal gradient in northern Europe. We hypothesized that, matching the pattern seen for most insect taxa on plants, we would observe a general decrease in fungal-associated species with latitude. Against this backdrop, we expected local communities to be structured by host identity and phylogeny, with more closely related fungal species sharing more similar communities of associated organisms. As a more unique dimension added by the ephemeral nature of fungal fruiting bodies, we expected further imprints generated by successional change, with younger fruiting bodies harboring communities different from older ones. Using DNA metabarcoding to identify arthropod communities from fungal fruiting bodies, we found that latitude left a clear imprint on fungus-associated arthropod community composition, with host phylogeny and decay stage of fruiting bodies leaving lesser but still-detectable effects. The main latitudinal imprint was on a high arthropod species turnover, with no detectable pattern in overall species richness. Overall, these findings paint a new picture of the drivers of fungus-associated arthropod communities, suggesting that latitude will not affect how many arthropod species inhabit a fruiting body but, rather, what species will occur in it and at what relative abundances (as measured by sequence read counts). These patterns upset simplistic predictions regarding latitudinal gradients in species richness and in the strength of biotic interactions.
Sammendrag
Accurate and non-destructive diagnosis of crop nitrogen (N) surplus and deficit status based on N nutrition index (NNI) is crucially important for the success of precision N management to improve N use efficiency (NUE) and reduce negative environmental impacts. However, due to the variability of the reflectance data obtained from different active crop sensors and complexity of the environmental and management conditions for regional applications, accurate determination of crop N status and topdressing N rate only using active canopy sensor data is very challenging. The objectives of this study were to (1) develop an in-season N status diagnosis and recommendation model based on NNI prediction using multi-source data fusion with machine learning, and (2) evaluate the accuracy of N diagnosis and recommendation in terms of rice yield and NUE under diverse on-farm conditions. Thirty plot experiments and thirteen on-farm experiments were conducted in Qixing Farm, Jiansanjiang, Northeast China from 2008 to 2018, and the dataset was used for the model calibration, validation, and evaluation. Two indirect and one direct NNI prediction methods using simple regression, stepwise multiple linear regression (SMLR) and random forest regression (RFR) were compared for N diagnosis and then integrated into N recommendation model. The results indicated that combining environmental and agronomic variables with crop sensor data improved the SMLR and RFR model performance by 1–16% and 9–40% over the corresponding models only using crop sensor data, respectively. The direct NNI prediction approach achieved slightly better N status diagnostic accuracy (areal agreement = 84% and Kappa statistics = 0.71) than indirect NNI prediction strategies based on plant N uptake and ΔN estimation (areal agreement = 81% and Kappa statistics = 0.67) or aboveground biomass and plant N uptake estimation (areal agreement = 77% and Kappa statistics = 0.58) across plot experiments and diverse on-farm conditions, based on multi-source data fusion with random forest regression models. About 82% of recommended N rates by the developed integrated in-season rice N diagnosis and recommendation model were within ±10 kg ha−1 of the measured economic optimum N rate across different varieties, environmental conditions and transplanting densities. Precision rice management based on in-season N diagnosis and recommendation decreased N rates and increased N partial factor productivity (PFPN) by 23% over regional optimum rice management, and significantly increased yield (7–11%) and PFPN (33–77%) over farmer's management. More studies are needed to develop in-season N diagnosis and recommendation strategies for applications across different regions and combine them with integrated precision rice management strategies for food security and sustainable development.
Forfattere
Milena Ðorđević Tatjana Vujović Radosav Cerović Ivana Glišić Nebojša Milošević Slađana Marić Sanja Radičević Milica Fotirić Akšić Mekjell MelandSammendrag
A study was conducted to investigate the effect of different storage periods and temperatures on pollen viability in vitro and in vivo in plum genotypes ‘Valerija’, ‘Čačanska Lepotica’ and ‘Valjevka’. In vitro pollen viability was tested at day 0 (fresh dry pollen) and after 3, 6, 9 and 12 months of storage at four different temperatures (4, −20, −80 and −196 °C), and in vivo after 12 months of storage at distinct temperatures. In vitro germination and fluorescein diacetate (FDA) staining methods were used to test pollen viability, while aniline blue staining was used for observing in vivo pollen tube growth. Fresh pollen germination and viability ranged from 42.35 to 63.79% (‘Valjevka’ and ‘Čačanska Lepotica’, respectively) and 54.58 to 62.15%, (‘Valjevka’ and ‘Valerija’, respectively). With storage at 4 °C, pollen viability and germination decreased over the period, with the lowest value after 12 months of storage. Pollen germination and viability for the other storage temperatures (−20, −80 and −196 °C) were higher than 30% by the end of the 12 months. Pollination using pollen stored at 4 °C showed that pollen tube growth mostly ended in the lower part of the style. With the other storage temperatures, pollen tube growth was similar, ranging between 50 and 100% of the pistils with pollen tubes penetrated into the nucellus of the ovule in the genotype ‘Čačanska Lepotica’. The results of these findings will have implications for plum pollen breeding and conservation.